Children with autism spectrum disorder (ASD) often have co‐occurring symptoms of attention‐deficit/hyperactivity disorder (ADHD) and/or anxiety. It is unclear whether these disorders arise from shared or distinct developmental pathways. We explored this question by testing the specificity of early‐life (infant and toddler) predictors of mid‐childhood ADHD and anxiety symptoms compared to ASD symptoms.n = 104) at high and low familial risk for ASD took part in research assessments at 7, 14, 24 and 38 months, and 7 years of age. Symptoms of ASD, ADHD and anxiety were measured by parent report at age 7. Activity levels and inhibitory control, also measured by parent report, in infancy and toddlerhood were used as early‐life predictors of ADHD symptoms. Fearfulness and shyness measured in infancy and toddlerhood were used as early‐life predictors of anxiety symptoms. Correlations and path analysis models tested associations between early‐life predictors and mid‐childhood ADHD and anxiety symptoms compared to mid‐childhood ASD symptoms, and the influence of controlling for ASD symptoms on those associations.Infants (Increased activity levels and poor inhibitory control were correlated with ADHD symptoms and not ASD or anxiety; these associations were unchanged in path models controlling for risk‐group and ASD symptoms. Increased fearfulness and shyness were correlated with anxiety symptoms, but also ASD symptoms. When controlling for risk‐group in path analysis, the association between shyness and anxiety became nonsignificant, and when further controlling for ASD symptoms the association between fearfulness and anxiety became marginal.The specificity of early‐life predictors to ADHD symptoms suggests early developmental pathways to ADHD might be distinct from ASD. The overlap in early‐life predictors of anxiety and ASD suggests that these disorders are difficult to differentiate early in life, which could reflect the presence of common developmental pathways or convergence in early behavioural manifestations of these disorders. Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by social communication deficits, restricted and repetitive behaviours and sensory atypicalities  were associated with mid‐childhood symptoms of ADHD but not ASD or anxiety, and whether atypicalities in infancy and toddlerhood that have previously been associated with anxiety (high fearfulness and shyness) were associated with mid‐childhood symptoms of anxiety but not ASD or ADHD. Second, we tested the specificity of those associations to ADHD and anxiety while controlling for the influence of ASD symptoms. We investigated this in a sample of infants at familial high‐risk for ASD (due to having an older sibling with ASD) studied prospectively into mid‐childhood. Around 20% of high‐risk infants develop ASD , 104 infants took part in research assessments at 7, 14, 24 and 38 months and were invited to return for a follow‐up study at age 7 years. At enrolment, each high‐risk (HR) infant (n = 54) had an older sibling  with a community clinical ASD diagnosis, confirmed using the Development and Well‐Being Assessment  were full‐term infants (one exception) recruited from a volunteer database at the Birkbeck Centre for Brain and Cognitive Development. At enrolment, all LR infants had at least one older sibling; the SCQ was used to confirm absence of ASD in older siblings, with no child scoring above instrument cutoff . Not all children were retained at the 7‐year assessment  for the DSM‐IV‐TR  were used in analysis.A battery of assessments was used to measure ASD symptoms and assign research diagnoses of ASD  was computed for each child.The Early‐life behaviours predicted to be associated with later ADHD  and anxiety (fearfulness and shyness) were measured at the 7‐ and 14‐month visits using the Infant Behavior Questionnaire‐Revised  and the rate and intensity of gross motor activity (ECBQ). Inhibitory control was indexed by the ECBQ Inhibitory Control subscale at 24 months , which assesses the capacity to stop, moderate or refrain from behaviours under instruction. Sustained attention was indexed by the Duration of Orienting IBQ‐R subscale at 7 and 14 months, which measures attention to/interaction with an object for extended time periods, and the Attentional Focusing ECBQ subscale at 24 months, which measures sustained orienting to an object and resisting distraction. Example items for these scales are provided in the online Locomotor activity was indexed by the IBQ‐R and ECBQ Fear subscale at 7, 14 and 24 months. This subscale measures distress/startle to sudden environmental changes and inhibited approach to novelty (IBQ‐R), and startle to sudden events and negative affect related to anticipated pain, distress, and potentially threatening situations (ECBQ). Shyness was indexed by the ECBQ Shyness subscale at 24 months , which measures slow/inhibited approach or discomfort in novel/uncertain social situations. Example items are provided in the online Fearfulness was indexed by the IBQ‐R and ECBQ p‐values >.11). The α level was set to .05, with correlations considered statistically significant from zero if the p obtained was <.05. In addition, we highlight associations that remained significant with a Bonferroni‐corrected alpha level of .001 (α = .05/50 = .001), with correlations considered statistically significant if the obtained p was <.001. Early‐life variables that were not significantly associated with mid‐childhood symptoms in the Pearson correlations were not included in the next stage of analysis  to limit the number of variables entered into longitudinal models given our modest sample size.As a first step, we computed Pearson correlation coefficients between early‐life predictors and mid‐childhood symptoms of ADHD, anxiety, and ASD to examine how our hypothesised individual predictors and symptom domains were related to one another, before controlling for the influence of other variables and assessing the specificity of associations with ADHD and anxiety compared to ASD. ADHD, anxiety and ASD symptom scores were skewed and so an lnskew0 transformation was applied using Stata  and mid‐childhood ADHD, anxiety and ASD symptoms. Model 2a included inhibitory control, shyness and risk‐group as predictors of ADHD, anxiety and ASD symptoms to test whether inhibitory control would be associated with mid‐childhood ADHD symptoms (not ASD or anxiety) and shyness would be associated with mid‐childhood anxiety symptoms (and not ASD or ADHD). Model 2b included mid‐childhood ASD symptoms as a predictor rather than an outcome to assess whether controlling for ASD symptoms affected associations between inhibitory control and ADHD and shyness and anxiety.We repeated these models including 1) ASD outcome rather than dimensional ASD symptoms as a covariate to assess whether the 15 HR children with ASD in mid‐childhood were driving effects; 2) sex and IQ as covariates to test whether these variables influenced associations; and 3) an interaction term between risk‐group and each early‐life predictor to check our assumption that associations between predictors and mid‐childhood symptoms would be similar in HR and LR groups. Due to space limitations, these additional models are reported and discussed in the online Sample characteristics are presented in Table Correlations between early‐life predictors and mid‐childhood ADHD, anxiety, and ASD symptoms are summarised in Table 2(28) = 32.41, p = .26; comparative fit index, CFI = 0.99; root‐mean‐square error adjusted, RMSEA = 0.039). For the ‘Fear’ factor, all standardised factor loadings (SFL) were significant . Similarly, for the ‘Activity’ factor, factor loadings for all time‐points were significant . Fear and Activity were significantly positively correlated . Table p‐values for each path in the model. Activity was significantly associated with mid‐childhood hyperactivity/impulsivity and inattention, with higher activity levels across infancy and toddlerhood associated with higher ADHD symptoms. Activity was not significantly associated with ASD or anxiety. Fear was significantly associated with later anxiety, with higher infant and toddler fear associated with higher anxiety symptoms, but was not significantly associated with ASD or ADHD. Risk‐group was marginally associated with hyperactivity/impulsivity and significantly with inattention, anxiety and ASD, with higher symptoms in the high‐risk siblings.A path analysis model Figure  using a 2(28) = 32.53, p = .25, CFI = 0.98, RMSEA = 0.039. Factor loadings and the correlation between factors were unchanged from Model 1a. Activity remained a significant predictor of ADHD symptoms and not anxiety while controlling for ASD symptoms . Inhibitory control was significantly associated with inattentive and hyperactive/impulsive symptoms, with lower inhibitory control in toddlerhood associated with greater mid‐childhood ADHD symptoms, but was not significantly associated with ASD or anxiety  not with ASD or anxiety. In path analysis, activity levels and inhibitory control were specifically associated with ADHD and not ASD or anxiety, and these associations remained when controlling for ASD symptoms and risk‐group. It has been argued that no neurocognitive or behavioural domain is impaired in ADHD and not in ASD and vice versa; consequently, these disorders must share pathophysiological mechanisms and represent different manifestations of the same underlying condition  , ranging between 71.7% and 99.8% across the four models. The sample size in the current study precluded a detailed psychometric approach using multigroup modelling to assess measurement invariance for the loading of items onto temperament subscales. This will be important in future studies to confirm whether the scales work in a similar way across risk groups. Our high‐risk sample was defined based on risk for ASD symptoms but not specifically for ADHD and anxiety, and a proportion of this sample met diagnostic criteria for ASD. These factors may have influenced our findings since ADHD and anxiety might manifest differently in the context of ASD/high‐risk for ASD. Still, our analysis including risk‐group, ASD symptoms, and ASD outcome as covariates indicated that our ADHD findings were robust to the influence of ASD and ASD‐risk, although this was not the case for anxiety. It will be important for future work to examine developmental pathways to these disorders in population samples and in multirisk group samples to assess the generalisability of our findings. We did not systematically assess the use of interventions in the high‐ or low‐risk groups and it is possible that some high‐risk children had received interventions for ASD or other developmental problems, which may have influenced developmental pathways. Risk for all three disorders was not evenly distributed across high‐ and low‐risk children, although we found no interactions between risk‐group and the early‐life predictors that were associated with ADHD and anxiety respectively. Finally, ASD, ADHD and anxiety tend to be diagnosed at different ages, with ASD in early childhood, ADHD in mid‐childhood, and anxiety in later childhood and adolescence  and anxiety commonly co‐occur in autism spectrum disorder (ASD), but whether these disorders arise from shared or distinct developmental pathways is unclear.Atypical infant and toddler activity levels and inhibitory control predicted mid‐childhood ADHD symptoms and not ASD, suggesting early developmental pathways to ADHD symptoms might be distinct from those that lead to ASD.Atypically high infant and toddler fearfulness and shyness predicted both mid‐childhood anxiety and ASD symptoms, suggesting developmental pathways leading to anxiety may be difficult to distinguish from those leading to ASD.Our findings indicate disorder‐specific early detection and intervention targets for ADHD and highlight that early markers for detecting and treating anxiety may also index ASD.Appendix S1. Participants: assessment of retention biases.Appendix S2. Assessment of ASD symptoms and assignment of research diagnoses of ASD in mid‐childhood.Appendix S3. Correlations between early‐life predictors and mid‐childhood ADHD, anxiety and ASD symptoms.Appendix S4. Interactions with risk‐group in associations between early‐life predictors and mid‐childhood ADHD, anxiety and ASD symptoms.Appendix S5. Interactions between risk‐group and early‐life activity level and fear in association with mid‐childhood ADHD, anxiety and ASD symptoms.Appendix S6. Interactions between risk‐group and early‐life inhibitory control and shyness in association with mid‐childhood ADHD, anxiety and ASD symptoms.Table S1. Example IBQ‐R and ECBQ subscale items.Table S2. Correlation coefficients (Pearson r) for associations between early‐life predictor measures and mid‐childhood ADHD, anxiety and ASD symptoms excluding children with an ASD diagnosis (i.e. in LR and HR No ASD).Click here for additional data file.


N = 43), individuals clinically diagnosed with ADHD (N = 21), ODD/CD (N = 26) and ASD (N = 41)] completed Go/NoGo and Switch tasks. Group differences were tested using analysis of co-variance (ANCOVA) including age, IQ, sex, conduct problems and ADHD symptoms as co-variates. Results indicated some disorder-specificity as only the ASD group demonstrated decreased probability of inhibition in the Go/NoGo task compared to all other groups. However, shared impairments were also found; all three diagnostic groups demonstrated increased reaction time variability (RTV) compared to the TD group, and both the ODD/CD and the ASD group demonstrated increased premature responses. When controlling for ADHD symptoms and conduct problems, group differences in RTV were no longer significant; however, the ASD group continued to demonstrate increased premature responses. No group differences were found in cognitive flexibility in the Switch task. A more varied response style was present across all clinical groups, although this appeared to be accounted for by sub-threshold ODD/CD and ADHD symptoms. Only the ASD group was impaired in response inhibition and premature responsiveness relative to TD adolescents. The findings suggest that some EF impairments typically associated with ADHD may also be found in individuals with ASD.Current diagnostic systems conceptualise attention deficit hyperactivity disorder (ADHD), oppositional defiant/conduct disorder (ODD/CD) and autism spectrum disorder (ASD) as separate diagnoses. However, all three demonstrate executive functioning (EF) impairments. Whether these impairments are trans-diagnostic or disorder-specific remains relatively unexplored. Four groups of 10–16 year-olds [typically developing  contains supplementary material, which is available to authorized users. Current diagnostic systems conceptualise attention deficit hyperactivity disorder (ADHD), oppositional defiant/conduct disorder (ODD/CD) and autism spectrum disorder (ASD) as distinct diagnoses. ADHD is characterised by persistent symptoms of age-inappropriate inattention, hyperactivity and impulsivity; ODD by negative, hostile and defiant behaviour; CD by aggression, destruction of property and serious violations of rules; and ASD by impairments in social communication abilities and the presence of restricted and repetitive behaviours and interests and sensory anomalies .Traditional neuropsychological approaches posit that psychiatric disorders are underpinned by impairments in specific domains of functioning, known as intermediate phenotypes, and said phenotypes discriminate between diagnostic categories. These phenotypes may represent potential risk factors and targets for intervention. However, some have highlighted that the search for discriminative phenotypes has not been as successful as hoped , and sugIn terms of distinct cognitive profiles, increased impulsivity, indexed by both impairments in response inhibition and a premature response style, is thought to be characteristic of individuals with ADHD , 12. HowSome comparative studies of inhibition between individuals with ADHD and those with ASD found that only those with ADHD showed impairment –20; howeSome studies that compared ADHD and ASD groups on cognitive flexibility found that only the ASD group showed impairment , 19, whiIn the third area of potential overlap, RTV, studies have found increased RTV in ADHD and ASD + ADHD groups but not in ASD alone , whereasTo our knowledge, no study has directly compared EF among adolescents with ADHD, ODD/CD and ASD. Furthermore, many prior comparative studies have not controlled for co-occurring symptoms. We compared three disorders, ADHD, ODD/CD and ASD, whilst controlling for conduct problems and ADHD symptoms. We also used a more representative sample of young people with ASD (IQ range of 54–129), as most studies only include those with an IQ ≥ 70, yet around half of children with ASD have an IQ < 70 . InformeAcross the ODD/CD, ADHD and typically developing (TD) groups only those aged 10–16 years were selected from original samples, which had a wider age range. This was to encompass a similar range to the ASD group. All participants had information on ADHD and ODD/CD symptoms, along with measures of neurocognitive task performance. Due to the post hoc nature of the current study, information was not available on ASD symptoms in the ADHD, ODD/CD and TD groups. The ODD/CD group, along with part of the TD and ADHD groups included participants from a larger study contrasting ODD/CD and ADHD . Participants had to have symptoms meeting ADHD criteria in at least one domain , and demonstrate ‘some impairment’ (defined here as above a 20% cut-off based on age-related published norms) in the other domain on the Conners’ ADHD Parent and Teacher Scales . These remained when controlling for age, IQ and sex , ADHD symptoms, age, IQ and sex , and conduct problems, age, IQ and sex .Group differences were found in probability of inhibition , and excluding those who scored above ADHD threshold in the ASD group . Unadjusted post hoc contrasts found that the ASD group had a lower probability of inhibition than the TD, ADHD and ODD/CD groups  = 1.38, p = 0.25], or error  costs. This remained when controlling for possible confounders and in sensitivity analyses.No group differences were found in the Switch task, for either RT . These remained when controlling for age, IQ and sex , ADHD symptoms, age, IQ and sex , and conduct problems, age, IQ and sex .Differences were found in the proportion of participants in each group who demonstrated premature responses on the Go/NoGo task , and excluding those who scored above ADHD threshold in the ASD group . Unadjusted post hoc contrasts found that the ASD (p < 0.01) and ODD/CD (p < 0.05) groups had a higher proportion of individuals showing premature responses than the TD group. The ADHD vs. TD contrast was significant at trend level (p = 0.06). The clinical groups were not significantly different from each other . The ODD/CD vs. TD contrast was at a trend level (p = 0.06). The ADHD vs. TD contrast became non-significant. Only the ASD vs. TD contrast remained significant when controlling for ADHD symptoms, age, IQ and sex (p < 0.05) and when controlling for conduct problems, age, IQ and sex (p < 0.01).Results remained significant in sensitivity analyses excluding those with IQ < 70 , but dropped to a trend level when controlling for age, IQ and sex , but became non-significant when controlling for ADHD symptoms, age, IQ and sex , and conduct problems, age, IQ and sex . Group differences were significant in sensitivity analyses excluding those with IQ < 70  and excluding those who scored above ADHD threshold in the ASD group .Differences were also found in the proportion of participants in each group who demonstrated premature responses on the Switch task . These remained when controlling for age, IQ and sex , and conduct problems, age, IQ and sex . Controlling for ADHD symptoms, age, IQ and sex resulted in findings losing significance . Differences remained significant in sensitivity analyses excluding those with IQ < 70 , and excluding those who scored above ADHD threshold in the ASD group .Group differences in ICV were found on the Go/NoGo task , and remained when controlling for age, IQ and sex . Group differences became non-significant when controlling for ADHD symptoms, age, IQ and sex , and conduct problems, age, IQ, and sex . Sensitivity analyses showed that differences remained significant when excluding those with IQ < 70  and excluding those who scored above ADHD threshold in the ASD group .Group differences in ICV were also found on the Switch task ).To our knowledge this is the first study to directly compare EF among ADHD, ODD/CD and ASD groups. Strengths include accounting for co-occurring ADHD and ODD/CD symptoms, which prior studies e.g., , 19) hav hav19]) n = 4), and so these participants were excluded from the study completely. The low rates of clinically significant conduct problems in the ASD group are consistent with previous studies of co-occurring psychopathology in ASD [Additionally, unlike for the ODD/CD and ADHD groups, we did not have any formal diagnostic information on co-occurring psychopathology in the ASD group and instead used parent-rated symptoms to identify individuals with high levels of hyperactivity and conduct problems. Whether diagnostic assessments would identify the same individuals as parent-rated questionnaires is an open question. We conducted sensitivity analyses excluding participants with ASD and high rates of ADHD symptoms; however, we were not able to conduct theoretically similar analyses with participants with ASD and high levels of conduct problems due to low group numbers Below is the link to the electronic supplementary material.


Eml-R1) and hybrid dwarfness (Hdw-R1) was carried out in hybrids of Chinese Spring wheat with recombinant inbred lines as well as interline rye hybrids. Eml-R1 and Hdw-R1 could be mapped proximal and distal of two closely linked EST-SSR markers, Xgrm902 and Xgrm959, on rye chromosome 6R. Both rye genes are located on a segment of chromosome 6R that contains a breakpoint of evolutionary translocation between the ancestral chromosomes of homeologous groups 6 and 3. The obtained results are discussed in relation to genes interacting in developmental pathways as a class of causal genes of RI.The post-zygotic reproductive isolation (RI) in plants is frequently based on the negative interaction of the parental genes involved in plant development. Of special interest is the study of such types of interactions in crop plants, because of the importance of distant hybridization in plant breeding. This study is devoted to map rye genes that are incompatible with wheat, determining the development of the shoot apical meristem in wheat–rye hybrids. Linkage analysis of microsatellite loci, as well as genes of embryo lethality ( Eml-A1) and rye (Eml-R1) genes lead to ungerminating hybrid seeds. Mature seeds have normal endosperm, but hybrid embryos may be lacking, or are varying in size from small to normal, and are comprising of dead tissues, undifferentiated in the region of shoot apical meristem (SAM) [Hdw-R1b) affects the shoot apical meristem in wheat–rye hybrids at the transition from vegetative to reproductive phases of development [Eml-R1 and Hdw-R1 by their position in the rye genome. Here, we report on the identification of expressed sequence tag (EST) derived microsatellite markers, which are linked to both genes. Comparative mapping allowed to integrate the target interval in the barley genome sequence as a prerequisite for fine mapping and subsequent positional cloning.Post-zygotic incompatibility in plants is often expressed in an autoimmune reaction (tissue necrosis) and disturbances of plant development, leading to a decrease in the viability or death of hybrids. Immunity and ontogenesis are controlled by many interacting genes. The interaction of genes is the basis of the canonical scheme (Bateson–Dobzhansky–Muller model), explaining the emergence and functioning of post-zygotic incompatibility. In cultivated and wild plants, a large number of genes controlling hybrid incompatibility in accordance with the classic two-locus scheme have been described . The comem (SAM) . Anotherelopment . As a reelopment , and in elopment ,7. Theseelopment  togetherelopment  provide Eml-R1, has been localized previously on chromosome 6R [Xgwm1103/Xgwm732. In the present study, we have mapped Eml-R1 distal of Xgwm1103/Xgwm732, and closely linked to Xgrm959 and Xgrm902 in hybrids of Chinese Spring (CS) wheat, and a set of rye recombinant inbred lines (RILs) originating from the cross between L2 × L7  cross. The markers revealed linkage to Hdw-R1. This gene, compared with Eml-R1, is located distal of the linked markers Xgrm959–Xgrm902 , CS × F1 (L2 × V1), and CS × F1 (L2 × V10) were divided into five phenotypic classes .Eml-R1 and Hdw-R1. If these genes are not linked (segregate independently), we will observe monohybrid gametic segregation 1 (Hdw-R1a):1 (Hdw-R1b). In reality, we observed a case that was attributed to the tight linkage of the studied genes, which follows from their map position  among all of the hybrid plants . This frequency is equal to 6.5 ± 1.7%  corresponds to the expected monohybrid segregation in all of the studied hybrids. The segregation for the gene of hybrid dwarfness  can be oposition a,b. A laposition . Gametes5 ± 1.7% d, 3.2 ± Eml-R1 on chromosome 6RL based on linkage to the genomic wheat microsatellite markers Xgwm1103/Xgwm732 [Eml-R1 is linked to another gene controlling post-zygotic reproductive isolation between wheat and rye, Hdw-R1. Furthermore, the integration of EST-derived rye SSR marker enabled comparative mapping, and revealed that both genes are located on an interstitial region on chromosome 6RL, covering a previously reported 3L/6L translocation breakpoint [Eml-R1 is residing on a segment that is homeologous with barley chromosome 6H, Hdw-R1 maps distally from Eml-R1 on a 6RL segment that is homeologous with the long arm of 3H. The 3L/6L translocation breakpoint is located within a 0.8-cM interval defined by Xgrm959 and Xgrm902, respectively. The localization of both genes on different ancestral segments shaping the modern chromosome 6R is further supported by the genomic wheat microsatellite loci Xgwm751, Xgwm1103, and Xgwm732. The co-segregating microsatellite markers Xgwm1103/Xgwm732 in wheat are located on chromosomes 6A [Xgwm751 was mapped in wheat close to the centromere on chromosome arm 3AL, and on the long arm of chromosome 3B [Eml-R1 and Hdw-R1 with respect to the position of translocation breakpoints is important in terms of understanding the mechanisms of reproductive isolation and the evolution of the rye karyotype. In Saccharomyces cerevisiae, chromosomal rearrangements have been identified as a major mechanism to reproductively isolate different strains [Eml-R1 and Hdw-R1 reside at the 3L/6L translocation in rye, and highlight that the fitness of wheat/rye hybrids can be genetically affected via embryogenesis or the vegetative development, respectively. As a consequence, both genes might have contributed to the speciation of rye, which diverged from Triticum aestivum approximately three to four million years ago [Eml-R1 as well as Hdw-R1 genes and a sophisticated phenotyping system based on test-crosses with wheat enables a forward genetics approach to isolate genes involved in the reproductive isolation of Triticeae species. With the recent availability of a draft genome sequence of rye [In an initial attempt, we have mapped eakpoint ,13. Whilsomes 6A  and 6D [somes 6A . In contosome 3B . The pro strains . In plan strains . Recentl strains . Eml-R1 ears ago . The molears ago . The natTriticum turgidum ssp. durum, AABB genome) variety Langdon, and two wheat diploid relatives, Aegilops tauschii (DD genome) and Aegilops umbellata (UU genome). F1 hybrids of wheat with some accessions of both wild relatives show one of two developmental abnormalities: severe growth abortion (SGA), which may be considered as seedling lethality, and grass-clump dwarfness/hybrid necrosis. Both have some features closely resembling the morphological expression of the wheat–rye dwarfness. Lethal at a three-leaf stage and temperature independent SGA connected with the down-regulation of numerous transcription factors, including the KNOTTED1-like homeobox gene, maintaining SAM, and the cell cycle-related genes functioning in SAM and leaf primordia. The temperature-dependent grass-clump dwarfness is explained by the down-regulation of the APETALA-like MADS box genes, known as flowering promoters, and by increased miR156 transcription, leading to a reduced level of target mRNA of SPL genes (Squamosa promoter binding protein-box transcription factors), some of which promote tillering. It is very interesting that the grass-clump dwarf phenotype is characteristic of hybrids, growing under normal temperature conditions. The same hybrids at low temperature express a typical autoimmune response connecting with the repression of cell division. Transcription factors, such as small RNA, are capable of physically interacting with target DNA and RNA, correspondingly, and their genes can be considered as the most likely for the role of candidate genes. It is worth noting that the cited authors revealed the presence of compatible and non-compatible genotypes in all of the parents, but carried out the segregation analysis and mapped only one of the genes (Net2) in Aegilops tauschii. We found only incompatible alleles in Chinese Spring bread wheat and both types of alleles in the rye inbred lines. The wheat gene Eml-A1, which is complementary to rye incompatible allele Eml-R1b in the expression of hybrid embryo lethality, was mapped on the distal part of the long arm of chromosome 6A with the aid of the deletion lines of CS [Eml genes may have orthologs on the chromosomes of homeologous group 6 in different species of the tribe Triticeae, including one with sequenced genomes. The comprehensive study of our, and the cited, examples of genome incompatibility would resolve the subject under discussion. Namely, would the genes of developmental pathways be considered as a separate class of plant genes that is capable of serving as causal genes for reproductive isolation? The progress in this direction is closely connected with genome sequencing in species of tribe Triticeae. Rye now does not limit the comparative studies, owing to new genomic resources [There are numerous examples of hybrid incompatibility manifesting itself as an arrest of plant development at different stages . They ines of CS . One wouesources .Eml-R1a and Hdw-R1a). Line L2 carries the incompatible allele Eml-R1b, which leads to embryo lethality in hybrids with Chinese Spring wheat. Lines V1 and V10 carry the incompatible allele of hybrid dwarfness Hdw-R1b. To produce wheat–rye hybrid seeds, wheat spikes were emasculated 1–2 days before anthesis, and pollinated 2–4 days later with freshly collected rye pollen. Wheat plants were pollinated by pollen collected from individual plants of corresponding F1 hybrids, or each of 74 RIL plants.For segregation analysis, the wheat–rye hybrid seeds were produced in two types of crosses. The female parent in both cases was bread wheat of the Chinese Spring variety, as the male parents were interline rye F1 hybrids, or the set of 74 L2 × L7 RILs were used. It was shown previously that rye lines L6 and L7 carry normal (compatible) alleles in both studied genes  and four rye ones  were used for mapping. Segregation for each marker corresponded to the expected gametic ratio of 1:1 (p > 0.05) in hybrids of wheat with RILs and with rye F1 L6 × V1. The segregation for the markers Xgrm173 and Xgrm130, which were studied in hybrids CS × (V1 × L2), differed to a large extent from the monohybrid ratio. In this hybrid, markers may be studied only in segregating dwarf plants and rare recombinant plants with normal phenotypes. Information for the used wheat microsatellite (GWM) belongs to the Institute of Plant Genetics and Crop Plant Research . A set of EST-derived rye microsatellites (GRM) were used according to Martis et al. [Mature wheat–rye caryopses were soaked in water, and 3–4 days later, the embryos were classified as normal (completely differentiated) or abnormal (undifferentiated or without embryos). To study the segregation for dwarfness, the seeds with normal alive embryos were sown in the soil, and one month old plants were differentiated as either dwarf or normal. DNA was isolated from the leaves of grown plants using the CTAB method . For eacosome 6R ,9. In als et al. . Electro2. Linkage groups for different hybrids were built by MultiPoint3.3 . A recombination frequency in percent was used as a measure of the genetic distance. For comparison purposes, RF per single meiosis was calculated for RILs. To identify the orthologous Eml-R1 and Hdw-R1 segments in the genomes of barley and rye, rye EST assemblies representing the GRM markers [http://webblast.ipk-gatersleben.de/).Segregation for the studied genes and markers were tested by χ markers  were com markers  as well  markers  using BL


Objective: The aim of this study was to evaluate the effectiveness of mothers’ Group psychoeducation on Quality of Life (QoL) of children with Attention Deficit Hyperactivity Disorder. Method: In this clinical trial, 60 mothers of ADHD children were randomly divided into two groups (30 participants in each group). An educational program based on Positive Parenting Program (Triple P) was performed for the intervention group, while only pharmacotherapy was provided for the control group. Pediatric Quality of Life Inventory (Peds QL) was completed by all 60 mothers before, eight week, and three months after intervention. Data were analyzed using mean and standard deviation, and K-square or paired t test were used for data analysis.Results: A total of 60 mothers participated in this study. Of their children, 80% were boys and 20% were girls. The mean of the total score of QoL increased significantly in the intervention group at week eight and three months after the intervention. Also, the mean scores of emotional, social, school and psychosocial domains, but not physical domain of QoL, found to be higher in ADHD children after intervention (p< 0.05). The total score of QoL and mean scores of domains increased in the posttest in the control group, but it was not significant (p> 0.05).Conclusion: A significant increase in the total score of QoL was reported by mothers in the posttest compared to the pretest in the experimental group, which showed that educating parents can improve the QoL of their ADHD children. Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in children and adolescents . ADHD isADHD increases low self-esteem, poor academic function, family and peer relationships problems, and disruptive behaviors in children and adolescent .Considering the pervasive symptoms of ADHD, children with diagnosis of ADHD, experience impaired well-being or quality of life compared to healthy children .According to the definition of World Health Organization (WHO), one of the comprehensive assessments for youths with ADHD based on the multidimensional view of health is health- related quality of life (HRQOL) , 4. HRQOThe results of a meta-analysis of quality of life in children with ADHD indicated that ADHD impact a child or adolescent HRQOL negativity, with moderate effect in physical and severe effect in psychosocial domains, including emotional and social aspects and school performance . DanckaeMany studies concluded that pharmacological treatments are effective for managing the ADHD core symptoms . In receStudies examined the effectiveness of triple p on Iranian mothers of ADHD children and showed significant improvement in parenting style, mother-child relationship, and lower rates of child misbehavior reported by mothers , 12. Qol is an important measure of outcome in children’s mental health  and the Considering the effectiveness of non-drug treatment and its good compliance as reported by the parents of children with ADHD as well as the importance of mother-child interaction in enhancing the QoL of these children, this study was conducted to assess the effectiveness of mother’s educational group therapy in enhancing parenting skills on Peds QL of ADHD children.This was a semi-experimental (pretest – posttest) with a control group. The study was approved by the Ethical Committee at Research Center of Guilan University of Medical Sciences and in accordance with Declaration of Helsinki (IRCT ID: IRCT201701297237N2).Participants and ProcedureParticipants were recruited from mothers of children and adolescents who had the diagnosis of ADHD based on a diagnostic interview by a child and adolescent psychiatrist according to Diagnostic and Statistical Manual Disorders, Fifth Edition (DSM – 5) criteria in an outpatient child and adolescent psychiatric clinic in Rasht, a city in the north of Iran in 2015-2016. Sample consisted of 60 mothers of 8-12 year-old ADHD children who were on drug treatment with methylphenidate, with therapeutic and effective dose started at least 2 months prior to the study. Mothers of ADHD children without any comorbidity were included in this study to eliminate the effects of other psychiatric disorders on parenting skills. Eligible participants were mothers who applied for educational parenting group. They did not have any psychiatric or active medical disorder based on a diagnostic interview by a child and adolescent psychiatrist according to Diagnostic and Statistical Manual Disorders, Fifth Edition (DSM – 5) criteria. After providing complete explanation and obtaining written informed consent, pretests were administered for all of mothers, then, they were randomly divided into experimental and control groups. Posttests were performed for experimental and control mothers after 8 sessions of educational parenting program and 3 months later. The control group were mothers in a waiting list whose ADHD children received the usual treatment (methylphenidate with therapeutic and effective dose) and were monthly visited by a child and adolescence psychiatrist. After data collection, the program was also performed for the control group. The educational program was a performed by a child and adolescent psychiatrist and a psychiatry resident as a co-therapist.InterventionThe educational program used in this study was based on Positive Parenting Program (Triple P), conducted in groups of 10-15 parents. The program consists of 8 two-hour sessions with the opportunity for parents to learn by observation, discussion, practice, and feedback , 14. TheMeasuresPediatric Quality of Life Inventory (Peds QL) is a 23-item questionnaire for 8-12-year-old children and include child report and parent report. In this study, parent report form was used to assess the QoL of ADHD children. The Peds QL measures HRQOL with physical functioning (5 items), emotional functioning (5 items), social functioning (5 items), and school functioning (5 items) using a 5-point scale . Then, these items are reserved to scores 0 to 100, with higher scores indicating better QoL (1 5). The psychometric properties of the Peds QL  for studies conducted in countries whose native language is not English is acceptable . This instrument is a comprehensive questionnaire that includes various areas of a child's performance and evaluates different areas of his/ her physical, emotional, social, and school performance . Statistical AnalysisData were analyzed using SPSS software version 22. Also, mean and standard deviation were used for descriptive statics, and K-square or paired t test used for data analysis.In this study, 70 mothers were assessed for participation, and of their children, 80% were boys and 20% were girls. At the beginning of the study, 10 mothers were excluded because they did not fulfill the inclusion criteria or provide consent. Then, 60 mothers were randomly divided into 2 groups. From the 30 mothers in the experimental and control groups, 21 and 24 mothers completed the sessions, respectively . The results revealed that the mean of total score of QoL increased significantly in the experimental group at week 8 and 3 months after intervention. Similarly, the mean scores of emotional, social, school, and psychosocial domains of quality of life were higher in ADHD children after intervention .According to There were no differences between the 2 groups in the mean scores for each item and the total QoL before intervention, at week 8 and 3 months after intervention (p> 0.05). The aim of this study was to investigate the effectiveness of mother’s group psychoeducation on QoL of children with ADHD. To our knowledge, this was the first study to evaluate the relationship between a multidimensional and validated measure of health and non-pharmacological intervention for ADHD patients in Iran.The most important finding of this study was a significant increase in the total score of QoL reported by parents in the posttest compared to the pretest in the experimental group, while this difference was not significant in the control group. Using effective parenting skills, better understanding of the disorder, and reducing the stress of parents through group discussion can lead to better parent-child interaction and may reduce punishment and improve QoL of children from the perspective of parents.The increase in QoL scores in the intervention group was significant in all domains, except for the physical domain, which is justifiable due to the psychological nature of the disorder, and it is consistent with the results of Lee et al’s meta-analysis .The mean of baseline QoL scores based on parents' report in the intervention and nonintervention group was 58 and 62, respectively, which is lower than the healthy population of 8-17-year-old youths without a history of this disorder or other problems, using the same quality of life assessment tool in Iran. In a study, the mean of the total score of parents reports of QoL was 77 . This fiAccording to the results of this study, the total scores of QoL in both intervention and not interventional groups were higher in the second and third follow-ups compared to the baseline. There was no significant difference between the 2 groups in improving the scores of QoL, but the difference between the 2 groups 3 months after intervention was less than 8 weeks after the intervention, and it seems that the effect of parenting education on mothers was initially more powerful . This caNo significant difference was found between the 2 groups after the intervention. Considering that drug therapy is the most important part of treatment for ADHD and that both interventional and non-interventional groups were under drug treatment with methylphenidate, this result confirmed the role of drug therapy in improving QoL in children with ADHD , 19.Few studies have focused on the impact of non-pharmacological treatments on the QoL of children with ADHD. In the meta-analysis conducted in 2010 on the QoL of these children, there was only 1 study on the effect of psychological training on QoL, which indicated improvement in the QoL scores in the first 3 months after the onset of treatment and they emphasized the greater impact of drug therapies . PerhapsIn this study, the severity of ADHD symptoms and subgroups of ADHD were not considered. Although the instrument used was comprehensive, it would have been better if we had used several tools.Significant increase was observed in the total score of QoL reported by mothers in the posttest compared to the pretest in the experimental group, indicating that providing education to mothers can improve the QoL of their ADHD children.


AbstractTriticale  is the first artificial species created by crossing wheat (Triticum spp.) and rye  and has a great potential as a grain and forage crop. Remote hybridization is a stress factor that causes a rapid reorganization of the parental genomes in hybrid progeny (“genomic shock”) and is accompanied by abnormalities in the chromosome set of hybrids. The formation of the hybrid genome and its subsequent stabilization are directly related to the normalization of meiosis and the correct chromosome segregation. The aim of this work was to cytogenetically characterize triticale  obtained by crossing Triticumaestivum Linnaeus, 1753. Triple Dirk D × Secalecereale L. Korotkostebel’naya 69 in F3–F6 generations of hybrids, and to trace the process of genetic stabilization of hybrid genomes. Also, a comparative analysis of the nucleotide sequences of the centromeric histone CENH3 genes was performed in wheat-rye allopolyploids of various ploidy as well as their parental forms. In the hybrid genomes of octoploid triticale an increased expression of the rye CENH3 variants was detected. The octoploid triticale plants contain complete chromosome sets of the parental subgenomes maintaining the chromosome balance and meiotic stability. For three generations the percentage of aneuploids in the progeny of such plants has been gradually decreasing, and they maintain a complete set of the paternal rye chromosomes. However, the emergence of hexaploid and new aneuploid plants in F5 and F6 generations indicates that stabilization of the hybrid genome is not complete yet. This conclusion was confirmed by the analysis of morphological features in hybrid plants: the progeny of one plant having the whole chromosome sets of parental subgenomes showed significant morphological variations in awn length and spike density. Thus, we expect that the results of our karyotyping of octoploid triticales obtained by crossing hexaploid wheat to diploid rye supplemented by comparative analysis of CENH3 sequences will be applicable to targeted breeding of stable octo- and hexaploid hybrids.Alloploidization resulting from remote (interspecific or intergeneric) hybridization is one of the main factors in plant evolution, leading to the formation of new species.  Triticale, derived from crossing wheat (Triticum spp.) and rye  was the first synthetic allopolyploid cereal. It incorporates favorable alleles from both progenitor species (wheat and rye), enabling adaptation to environments that are less favorable for wheat yet providing better biomass yield and forage quality  Triple Dirk D (genome AABBDD) with diploid rye  cultivar Korotkostebel’naya 69 (genome RR)  with a 16h day length.Octoploid triticales (genome constitution AABBDDRR) were created by crossing the near isogenic line of common wheat (nome RR) . GerminaFor chromosome counts in triticale somatic cells, root-tips of seedlings were treated with saturated α-bromonaphthalene solution and visualized through Feulgen staining . Ten metCENH3 gene from rye, wheat  and triticale cDNA had been designed in  and treated with RQRNaseFree DNase  according to manufacturers’ recommendations. RNA was reverse-transcribed to cDNA with a RevertAid H Minus First Strand cDNA Synthesis Kit (Thermoscientific). Amplification primers specific to the N-terminal tail of the αigned in . The ampal Omega  at http:3 generation showed that the number of chromosomes in their somatic cells varies from 53 to 56 , F5 and F6 (TDK 96). The progeny of the aneuploid plant TDK94F3  and a plant with 49 chromosomes (TDK 96.3)  in octoploid triticale hybrid plants in F3–F5 and in the parental forms. Sequencing of randomly selected clones (15–20 clones for each plant studied) of the CENH3NTT showed that the nucleotide sequences of wheat and rye are 99% identical, differences were observed only in a few positions. For wheat CENH3, these are positions 82 and 84, and for rye – positions 73 and 145. Based on the frequency of specific substitutions in hybrid plants  in generations F3-F5, the number of αCENH3 copies carrying this substitution increases from 16 to 57%. The hybrid plants TDK94.2 (54 chromosomes in the karyotype) and TDK92.4 (52 chromosomes in the karyotype) without substitution at the position 73 in the nucleotide sequence of αCENH3 were sterile. It can be assumed that this substitution affects the formation of the CENH3 structure and is possibly associated with the maintenance of a viable hybrid genome.Intergeneric hybridization in plants is often accompanied by elimination of some chromosomes or whole genomes. One of the putative ways to the emergence of aneuploid plants is disturbances in the functioning of centromeres of one of the parents owing to the differences in the molecular structure of centromeric histones . In this 1R Fig.  in all h 1R Fig. . The rye3 plants, except one, were aneuploids with different numbers of eliminated chromosomes  identity , which is typical only for CENH3 clones obtained from the rye genome. Of great importance for the discussion of these data is an extensive analysis of the expression of rye genes in cDNA isolated from various tissues of hybrid allohexaploid triticale plants obtained by crossing T.turgidum × S.cereale (Triticum species than 200 randomly selected rye genes. Thus, rye genes with a low similarity to their homeologs in Triticum genomes are more likely to be repressed or absent due to deletions in the allopolyploid genomes. This conclusion is in good agreement with our results. High identity of rye and wheat CENH3 sequences does not inhibit the expression of both parental forms in the hybrid genomes of octoploid triticale.Our results on ts Table  indicatecereale . The clacereale . It is i


Current data about Attention Deficit Hyperactivity Deficiency (ADHD) guideline use in the Netherlands are absent. This study analysed ADHD guideline use among different healthcare workers, and the use of key elements from these guidelines to diagnose ADHD.A survey assessing ADHD guideline use was distributed throughout the Netherlands to various health care professionals. Only professionals involved during the diagnostic process were included.Response rate among GPs was low (111/1450), but high among other health care professionals (251/287). A total of 362 surveys were analysed, 186 responders (51%) were involved during the diagnostic process. Overall guideline use was 64.5%; the national multidisciplinary guideline or a guideline made by a professional’s own institution were most used. Psychiatrists, psychologists and paediatricians reported compliance with key elements of the guidelines such as gathering information from a third party (> 90%) and carrying out a developmental history (> 88%). Use of a standardized interview (< 52% often use) was low. Only paediatricians performed a physical examination regularly (88%).Despite low general use of guidelines, psychiatrists, psychologists and paediatricians use similar key elements of ADHD guidelines. This study provides opportunities to improve care through increasing familiarity with ADHD guidelines and the use of standardized interviews. Attention-Deficit Hyperactive Disorder (ADHD) is a neurodevelopmental disorder, affecting people of all ages with an onset in childhood. According to the most recent meta-analyses, worldwide prevalence in children and adolescents is estimated between 3.4 and 7.2% , 29, 39.To gain more insight into the increase of  care use in the Netherlands due to ADHD symptoms, it is important to know whether important elements of an ADHD diagnosis are sufficiently taken into account by  care professionals to avoid misdiagnosis. For example, consideration should be given to the presence of ADHD behavior in different settings. In addition, it is useful to know if problems are adequately detected in primary health care. The first step is to gain insight into the use of the existing guidelines by different  care professionals, and to evaluate if these guidelines are applied correctly. The objective of this study was therefore 1) to describe the use of different ADHD guidelines among healthcare professionals for children in the Netherlands and 2) to determine whether diagnosing ADHD is in accordance with key elements of these guidelines.This cross-sectional study was conducted between March 2017 and August 2017 at the paediatric department of the Maastricht University Medical Centre. A survey was designed using the online questionnaire platform Qualtrics . A wide A 27-question survey based on the different Dutch guidelines was developed, focusing on elements used during the diagnostic process. The first part of the survey consisted of 4 questions assessing involvement of the individual healthcare professional during the diagnostic phase of ADHD. Respondents not belonging to the target group were excluded after finishing this part. The following 16 questions related to the use of guidelines in general and evaluated the practice patterns with regard to an ADHD diagnosis. Survey items assessed adherence to five diagnostic key elements specified in the Dutch multidisciplinary guideline, the Dutch guideline for GPs and the youth healthcare guideline (Table Questions about diagnostic instruments and (re) screening too1ls were tailored to the Dutch situation. Questionnaires advised by different guidelines and askes for in the survey were: 1. ‘ADHD Vragenlijst’ , a Dutch behavioural questionnaire for children aged 4 to 18 years that is based on the Conners’ Rating Scale for ADHD . 2. The The last 7 questions assessed the characteristics of the health care professionals, like gender, age, work experience and experience with diagnosing ADHD in children. A question about the location of the institution was included to determine geographic diversity.Responses were converted to IBM SPSS Statistics version 22 for Mac for further analysis . First, Response rate of GPs was low; 111 of the 1450 surveys returned. In contrast, the response rate of other health care professionals was high; 251 of 287 surveys were returned. In total 362 questionnaires were returned . Of respondents who indicated that they did not use a guideline, 18.3% used their own protocol, and 17.2% used no protocol at all. Table .4%. Of rAs data about ADHD guideline use in the Netherlands was lacking, this study analysed ADHD guideline use among different healthcare workers, and the use of key elements from these guidelines to diagnose ADHD. The use of national approved Dutch guidelines was low, but was in accordance with the results of studies in other countries , 31, 44.There were some striking features. Overall use of semi-structured interviews was low. ADHD is a best practice diagnosis, but diagnostic clinical structured interviews showed high values for sensitivity and specificity in relation to the comprehensive best practice diagnosis . Low useCurrently various healthcare professionals in the Netherlands diagnose ADHD. Despite the introduction of several ADHD guidelines for primary healthcare workers, the majority of GPs and youth health care workers indicated to refer children with ADHD symptoms to other professionals. The National Health Statistics Report of the United States of America showed a high involvement of paediatricians; in their study almost 40% of the parents were told by a paediatrician that their child had ADHD , 42. ManThis transformation of youth care was part of the new Child and Youth Act, which formed the basics of a plan of action made by all professionals involved in the care for children with (symptoms of) ADHD in 2015 . The thrThis study has several limitations. It was impossible to include professionals randomly by inviting the targeted group, because no exact data of professionals involved in ADHD care in the Netherlands was available. This has created various risks for selection bias. First, it is not clear whether a good reflection of care providers has received the questionnaire. Second, respondent bias was possible due to self-selection of the respondents; most likely professionals who felt involved in ADHD care completed the survey. Another limitation was the low number of some professionals. Response rate in the GP group was extremely low and the number of GPs involved in ADHD care even lower. As a result, no conclusions could be made concerning ADHD care by GPs. As opposed to all other professionals who were located all over the Netherlands, GPs from only two provinces could be approached. These provinces were representative for a part of the Netherlands, but not for provinces were the major cities are located. Finally the survey focussed on the diagnostic process and did not include treatment . It was a deliberate choice to exclude professionals who were not involved in the diagnostic process at the beginning of the survey. This was to prevent people who were not involved in ADHD diagnostics from completing the questionnaire and thus influencing the results negatively. Retrospectively, it would have been interesting to know whether the group that was excluded at the beginning of the questionnaire was involved in the treatment of ADHD. According to the guidelines, ADHD symptoms must be regularly evaluated during treatment, to determine to what extent ADHD symptoms still lead to dysfunction. In order to evaluate ADHD symptoms properly, sufficient knowledge about the disorder is essential; the question is whether this knowledge is sufficient if you do not participate in diagnosing ADHD. Further research is necessary to gain insight in the knowledge of professionals who only treat children with ADHD.ADHD is a best-practice diagnosis. This was a quantitative study and no statements can be made about the quality of the ADHD diagnosis made by individual health care professionals or the possible impact on the increased demand for ADHD care. However, practice variations were identified which generated new hypotheses. Involvement of (relatively cheap) primary care was low. Response rate from the GPs was very low. The Dutch government wants a prominent role for GPs in the diagnostic process of ADHD so it is important to conduct more research on the involvement and knowledge of ADHD in this group.Use of (expensive) additional testing was high, which may be linked to easy access to these resources, different demands of the referred patient group or low use of nationwide guidelines. Implications of these patterns cannot be derived from this study but are of interest for further investigation, especially directed to proper use of additional (neuro) psychological testing. Finally, more attention should be paid to the use of standardized interviews, for example by incorporating them in new guidelines.Various health care professionals, working in primary, secondary and tertiary care, diagnose ADHD in children in the Netherlands differently. In particular mental health care workers and specialized pediatricians are involved in the diagnostic process. A slight majority is using a nationwide guideline or a protocol of the professional’s own institution based on national approved guidelines. Adherence to guidelines differs per health care profession, but the use of diagnostic key elements, like use of information from a third party and a developmental history, is high among professionals with the highest response rate. Use of semi-structured interviews and physical examination is low, raising opportunities for improvement.


Dyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders . Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders.p < .001, k = 50) and more lenient  thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls .We conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia  or ADHD  were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (Results showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity.The current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis. Dyslexia  and Attention-deficit/hyperactivity disorder (ADHD) are both prevalent developmental disorders 5–10%) with a high, bidirectional comorbidity rate 25–40%)  OR dyslex* OR reading disab* OR reading disorder*) AND (“voxel-based” OR “voxel based” OR VBM OR “gray matter” OR “grey matter”) AND (“1999/01/01”[Date - Publication]“2018/04/30”[Date - Publication]) AND English[Language]. The PubMed search syntax for ADHD was as follows: (Attention Deficit Disorder with Hyperactivity [MeSH] OR ADHD OR attention*deficit) AND (“voxel-based” OR “voxel based” OR VBM OR “gray matter” OR “gray matter”) AND (“1999/01/01”[Date - Publication]: “2018/04/30”[Date - Publication]) AND English[Language]. To ensure that we had identified all relevant studies, we also cross-referenced our searches with previous VBM meta-analyses for dyslexia ).The current results should be considered in light of a few limitations. As with any meta-analysis, our analysis is constrained by the design and statistical decisions of the primary studies. While the neuroimaging field is moving toward larger samples in general, Table Relatedly, the ALE meta-analytic approach relies on modeling the peak coordinates reported in studies and does not account for the extent of statistically significant findings . It is possible that this approach leads to a more conservative estimation of potential sample overlap in the cases of studies reporting large clusters which extend well beyond the region that would be modeled by the ALE approach.Recruitment across studies for dyslexia and ADHD was heterogeneous. For dyslexia, some studies included participants with a previous clinical diagnosis while others established their own empirical criteria on standardized reading measures. Similarly, for ADHD, studies varied in whether they employed clinical diagnoses, standardized diagnostic interviews and/or behavioral rating scales. These recruitment differences likely add to the heterogeneity of the clinical populations, potentially making it more difficult to identify consistent gray matter correlates within disorders, and thereby making it more difficult to discern overlaps between the disorders.It was beyond the scope of this meta-analysis to examine medication effects in ADHD (for a review see ), but weLastly, it is important to consider the role of publication bias in this meta-analysis. Analytic strategies for identifying publication bias in the neuroimaging literature are still emerging because of the unique challenges associated with this type of data e.g., , 130). F. F130]).To our knowledge, the current study is the first to meta-analyze the overlap of gray matter correlates of dyslexia and ADHD. The overall pattern was one of largely distinctive gray matter correlates, although we identified a region of overlap in the right caudate when using our more lenient statistical thresholds. This overlap in the right caudate may be related to shared cognitive correlates in executive functions and/or procedural learning. Our goal was to identify shared gray matter differences in order to contribute to a multi-level understanding to the dyslexia-ADHD comorbidity that spans the genetic, neural, and cognitive levels of analysis. This framework is important not only for the dyslexia-ADHD comorbidity specifically, but also for the broader field of neurodevelopmental disorders where comorbidity is pervasive.Additional file 1. Checklist for neuroimaging meta-analysesAdditional file 2. Detailed characteristics of studies included in the meta-analysis.Additional file 3. Gray matter differences in ADHD and dyslexia in adults and children Additional file 4. GingerALE meta-analysis script for ADHD > TD.Additional file 5. GingerALE meta-analysis script for Dylexia > TD.Additional file 6. GingerALE meta-analysis script for Dyslexia < TD.Additional file 7. GingerALE meta-analysis script for ADHD < TD.


N = 39, age 12–16, all male except for one female per group) to study reward-related OFC responses and how they relate to behavioral dysfunction in ADHD. During fMRI data acquisition, participants performed a simple decision-making task, allowing us to image expectation-related responses to small and large monetary outcomes. Across all participants, we observed significant signal increases to large versus small expected rewards in the OFC. These responses were significantly enhanced in ADHD relative to TD participants. Moreover, stronger reward-related activity was correlated with individual differences in hyperactive/impulsive symptoms in the ADHD group, whereas high cognitive ability was associated with normalized OFC responses. These results provide evidence for the importance of OFC dysfunctions in the neuropathology of ADHD, highlighting the role of OFC-dependent goal-directed control mechanisms in this disorder.Alterations in motivated behavior are a hallmark of attention-deficit/hyperactivity disorder (ADHD), one of the most common psychiatric disorders in children and adolescents. The orbitofrontal cortex (OFC) plays a key role in controlling goal-directed behavior, but the link between OFC dysfunction and behavioral deficits in ADHD, particularly in adolescence, remains poorly understood. Here we used advanced high-resolution functional magnetic resonance imaging (fMRI) of the human OFC in adolescents with ADHD and typically developing (TD) controls (SIGNIFICANCE STATEMENT Attention-deficit/hyperactivity disorder (ADHD) is characterized by alterations in motivated behavior which can be understood as diminished goal-directed control. The orbitofrontal cortex (OFC) plays a key role in controlling goal-directed behavior, but its potential contribution to ADHD symptomatology remains poorly understood. Using high-resolution fMRI, we show that adolescent ADHD patients display enhanced OFC signaling of future rewards and that these increased reward-related responses are correlated with the severity of hyperactivity/impulsivity. These findings suggest that an inability to adequately evaluate future outcomes may translate into maladaptive behavior in ADHD patients. They also challenge the idea that dysfunctions in dopaminergic brain areas are the sole contributor to reward-related symptoms in ADHD and point to a central contribution of goal-directed control circuits in hyperactivity. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common childhood psychiatric disorders . In addiThese behavioral alterations have been interpreted as reflecting increased reward sensitivity and impulsivity, and, thus, previous work on the neuropathology of reward processing in ADHD has focused primarily on dopaminergic brain regions. For instance, reward anticipation in adolescents  and adulHowever, deficits in reward-related behavior in ADHD could also reflect deficient goal-directed control of behavior. The orbitofrontal cortex (OFC) is a key region supporting goal-directed behavior . OFC neuHowever, evidence linking OFC activity to ADHD is sparse and inconsistent, particularly in adolescent populations. Some studies have found that OFC responses to monetary outcomes  and rewaInconsistent findings relating OFC function to ADHD could be due, in part, to technical difficulties in imaging the human OFC using functional magnetic resonance imaging fMRI; . Due to In this study, we used advanced high-resolution rFOV fMRI of the OFC and a simple decision-making task  to test N = 19) consisted of 10 patients who fulfilled the diagnostic criteria for the combined subtype of ADHD, 7 patients who fulfilled criteria for the inattentive subtype, and 2 patients of the hyperactive-impulsive subtype. All subjects in the final sample were male, except for one female participant in each group.Forty-nine children and adolescents  aged between 12 and 16 years participated in the study. They were recruited through local newspaper advertisements and the Department of Child and Adolescent Psychiatry and Psychotherapy at Otto von Guericke University Magdeburg. All participants and their parents underwent clinical interviews with the Revised Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version  = −2.67, p = 0.011). Although these estimates do not provide insight into the immediate finances of the adolescents , they can serve as a proxy for the financial situation of the family and might therefore correlate with the subjective value of the monetary outcomes used in the experiment. Parental ratings of aggressive and dissocial behaviors were significantly higher in the ADHD group than the TD group  discontinued the intake at least 48 h before the experiment. Based on the information about parental employment from the CBCL questionnaire, the estimated household income of ADHD patients was lower compared to TD families  in addition to their earnings from the experimental task.B). These CSs were associated with large and small monetary rewards . CSs were counterbalanced across subjects such that for half of the participants, red upward and green downward triangles were associated with large rewards, and red downward and green upward triangles were associated with small rewards. On each trial, one CS was presented for 2 s, and participants were instructed to remember the color and orientation of the CS for a variable delay (4–8 s). This delay allowed us to dissociate CS- and outcome-evoked activity. Participants then had to report either the color or orientation of the CS by button press with the right index or middle finger within an interval of 1.5 s to gain the monetary reward predicted by the CS. The chosen response was briefly surrounded by a white frame to indicate the participant's selection, and feedback about the monetary outcome was presented if the response was correct . If the response was incorrect or too slow, feedback of 0¢ was presented.Participants completed a decision-making task in which four different triangle shapes served as visual conditioned stimuli . Subsequently, subjects performed 7 runs with 24 trials each (six presentations of each triangle in pseudorandomized order) while fMRI data were acquired. At the end of each experimental run, the total gain was displayed. The entire experimental session, including the instructions, training, anatomical scan, and behavioral task, lasted ∼1.5 h.MRI data were collected on a Siemens Prisma 3 Tesla system with a 64-channel head/neck coil. An Original Pillow Junior (Tempur World) was placed on the base of the coil surrounding the sides and the back of the head for comfort and to prevent movement.3 voxel size, 256 × 256 × 192 matrix, 2.82 ms echo time, 2.5 s repetition time (TR), 1.1 s inversion time, 7° flip angle, 140 Hz pixel bandwidth, 7/8 partial Fourier, and parallel imaging with a Generalized Autocalibrating Partial Parallel Acquisition (GRAPPA) factor of 3.T1-weighted structural images were acquired with an MPRAGE sequence using the following parameters: 1 × 1 × 1 mm2 rFOV, 1.25 × 1.25 mm2 in-plane voxel size, 30 ms echo time, 2 s TR, 90° flip angle, 1 mT/m · ms z shim, 0.73 ms echo spacing, and GRAPPA factor of 2. The transversal slice block was tilted 20° with respect to the anterior commissure–posterior commissure line as shown in Figure 1C. An example of a mean functional image for one participant is shown in Figure 1D.For high-resolution functional imaging, we used a combination  of rFOV To facilitate anatomical registration of the rFOV imaging data, we also acquired 10 whole-brain EPI volumes. To keep geometrical distortions within the rFOV part of the whole brain data set identical to the functional scans, the shim settings were copied and the FOV and matrix size in phase direction as well as the GRAPPA factor were doubled.SCR_007037, Wellcome Trust Centre for Neuroimaging, London, UK). For preprocessing, all functional rFOV echoplanar images were realigned to the first volume. Independent sample t tests on mean absolute head motion revealed group differences in translation (t(37) = 4.36, p < 0.001) and rotation (t(37) = 4.27, p < 0.001). To control for potential signal differences induced by head motion, motion parameters were included in first- and second-level statistical models .All analyses of the MRI data were conducted using SPM12  space using the six tissue probability map provided by SPM12. Deformation fields were applied to the functional rFOV echoplanar images. The normalized images were smoothed with a 6 mm FWHM Gaussian kernel.For each participant, a general linear model (GLM) was fitted to the normalized and smoothed functional rFOV EPI data. The GLM included the following six event-related regressors: the onsets of the visual CSs , button presses, and outcomes . These regressors were convolved with a canonical hemodynamic response function. The GLM also included the following nuisance regressors to account for head motion: six realignment parameters, their squares, their derivatives, and their squared derivatives . In addition, within-volume motion was estimated using the absolute difference between odd and even slices, as well as the variance across slices, and included in the GLM. Within-volume motion estimates were also used to identify volumes with excessive motion (more than four times SD), which were modeled separately using additional volume-specific regressors.t tests across all participants for group analysis. To account for differences in head motion, we included absolute head motion as a covariate of no interest.Voxelwise parameter estimates from this GLM reflect the amplitude of the BOLD signal in response to events of interest (CSs and outcomes). The BOLD signal is related to the overall level of neural activity evoked by these events. Individual contrast images for CSs predicting large versus small rewards (expectation) and large versus small outcomes (outcome) were computed based on these parameter estimates. The outcome contrast included correct responses only as incorrect trials were modeled in a separate regressor (no reward). Contrasts were entered into one-sample p < 0.05, familywise error (FWE) corrected at the voxel-level. Individual parameter estimates were extracted from the OFC  and compared between groups using an ANOVA with group (ADHD vs TD) and reward value (high vs low) as factors.We used an inclusive mask of the OFC, defined as the conjunction of an anatomical OFC mask  and a gray matter (GM) mask . Significant clusters were defined using a statistical threshold of T values for dissocial behavior and aggression (CBCL). For variables included in the final regression model, Pearson's correlations coefficients between the parameter estimates and these variables were computed.To relate OFC activity to IQ and ADHD symptomatology, we used a stepwise multiple linear regression analysis. The initial regression model included age, IQ, number of hyperactive/impulsive and inattentive symptoms , and http://www.neuro.uni-jena.de/cat/): each image was automatically normalized into template space and segmented into GM, white matter, and CSF. The individual whole-brain volume for each tissue type and total intracranial volume (TIV) was extracted. After a quality check of the individual images and a check for homogeneity between the groups, the images were smoothed with an 8 mm FWHM Gaussian kernel. Finally, the groups were compared using independent-sample t tests, with TIV as a covariate to correct for overall differences in brain volume. Furthermore, we performed automatic segmentation of regions of interest based on Hammer's atlas as provided by CAT12. GM volume in left and right OFC was compared between groups (independent-sample t test) and related to age (Pearson's correlation).We tested for group differences in GM volume using VBM . The pret test against 50% chance, t(38) = 46.54, p < 0.001). A two-way ANOVA with the factors reward value (2¢ vs 10¢) and group (ADHD vs TD) on the percentage of correct responses revealed an overall inferior performance of the ADHD group compared to TD participants  = 12.4, p = 0.001), but no effect of reward value  = 0.58, p = 0.45) and no group-by-value interaction  = 0.02, p = 0.89; Fig. 2A). Analysis of response times (RTs) showed that ADHD patients responded slower than TD participants  = 4.13, p = 0.049). However, RTs in both groups were shorter in the high-value than in the low-value condition  = 5.08, p = 0.03), with no group-by-value interaction  = 0.02, p = 0.89), demonstrating that CS-induced reward expectations had comparable effects on behavioral responses in both groups . Overall, these results suggest that even though ADHD patients showed unspecific behavioral deficits (possibly related to deficits in attention or working memory) relative to TD participants, all participants were able to perform the task, and that the value of expected rewards had comparable behavioral effects on both groups. Importantly, the absence of group-by-value interactions indicates that subsequent analyses of the imaging data are not confounded by behavioral group differences.Participants reported the correct color or orientation with high accuracy, indicating that they attended to the task  = 5.79, pFWE = 0.004; Fig. 3A). Additional bilateral OFC clusters did not survive correction for multiple comparisons . We did not find regions in the OFC that were more responsive to small compared to large expected rewards.In a first step, we tested whether OFC responses differed between CSs predicting large versus small outcomes across the entire group of participants. This analysis revealed a significant cluster in the left OFC  = 5.76, p = 0.022). As illustrated in Figure 3B, OFC responses to large versus small expected rewards were stronger in the ADHD group, and there was no significant main effect of group  = 0.01, p = 0.92). We confirmed this finding using non-parametric statistical tests . Note that this analysis is unbiased, such that the OFC cluster in which responses were compared between groups was defined independently of group differences (t(36) = 1.68, p = 0.10, two-tailed). However, ADHD and lower cognitive ability, as measured by IQ tests, are genetically codetermined (t(36) = 2.22, p = 0.033), suggesting that potential differences in the subjective value of the monetary rewards did not account for our results  = 5.23, pFWE = 0.017; Fig. 3C) in response to small compared to large outcomes.In a second step, we examined OFC responses to reward feedback. Across all subjects, we found significantly increased activity in the right lateral OFC  = 0.77, p = 0.39; group by outcome value interaction, F = 2.33, p = 0.14). We did not find regions in the OFC that were more responsive to large compared to small reward outcomes.However, a two-way ANOVA on parameter estimates extracted from this OFC cluster revealed no significant differences between groups .R2 = 0.573, F = 9.375, p = 0.003) by a combination of IQ  and the number of hyperactive/impulsive symptoms . None of the other variables including age, inattentiveness, and aggressive and dissocial behaviors significantly increased the model fit. Subsequent correlation analyses confirmed a negative correlation between the expectation-related OFC responses and IQ  and a positive correlation with the number of hyperactive/impulsive symptoms  in the ADHD group. These findings suggest that hyperactivity/impulsivity is related to alterations in OFC reward processing, whereas cognitive capacity is associated with reduced OFC activity during reward expectation.Using stepwise linear regression, we found that fMRI responses to large versus small expected rewards were best explained . However, there were no significant group differences between TD and ADHD adolescents in either whole-brain or OFC GM volumes . This suggests that ongoing structural brain organization affects ADHD and TD adolescents to a comparable degree. In addition, controlling for age, OFC responses to large versus small expected rewards did not correlate with GM volume in the OFC  or the whole brain .In a final step, we examined whether group differences in reward-related responses could be explained by differences in GM volume. Whole-brain and left OFC GM volume were negatively correlated with age across all participants  and react with stimulation seeking as compensation . Future Imaging of the OFC is challenging because this area is highly susceptible to signal drop-out and geometric distortions . These dConsistent with some  but not In addition, CS-evoked OFC responses were not related to aggressive or antisocial behaviors. Given that none of our patients fulfilled the diagnostic criteria for CD, this null result might be due to insufficient variance in our sample. However, it could also indicate that impulsivity associated with ADHD may rely on altered OFC encoding of value, whereas impulsivity underlying CD could rely on overall decreased OFC activity . In lineOur results suggest a normalizing effect of intellectual ability on aberrant OFC responses in ADHD. This adds to previous studies reporting that differences in OFC activity between patients and TD peers were no longer evident when controlling for IQ . HoweverImportantly, our results cannot be explained by differences in prefrontal development. VBM analyses confirmed that GM volume was comparable between ADHD and TD participants, ruling out an effect of potential delays in brain maturation in this ADHD sample .In conclusion, our study provides insights into how the OFC may contribute to altered reward-related behavior in adolescent ADHD. We show that enhanced OFC encoding of reward is associated with symptoms of hyperactivity/impulsivity. Our findings thus challenge the idea that dysfunctions in dopaminergic brain areas are the sole contributor to reward-related behavioral symptoms and suggest that aberrant activity in goal-directed control circuits may lie at the core of hyperactive/impulsive symptoms in ADHD.


Different primary studies in Ethiopia showed the burden of low birth weight. However, variation among those studies was seen. This study was aimed to estimate the national prevalence and associated factors of low birth weight in Ethiopia.PubMed, Web of Science, Cochrane library, and Google Scholar were searched. A funnel plot and Egger’s regression test were used to see publication bias. I-squared statistic was applied to check heterogeneity of studies. A weighted inverse variance random-effects model was applied to estimate the national prevalence and the effect size of associated factors. The subgroup analysis was conducted by region, study design, and year of publication.2 , and gestational age < 37 weeks at birth  were identified factors of LBW.A total of 30 studies with 55,085 participants were used for prevalence estimation. The pooled prevalence of LBW was 17.3% (95% CI: 14.1–20.4). Maternal age < 20 years , pregnancy interval < 24 months , BMI < 18.5 kg/mThe prevalence of low birth weight in Ethiopia remains high. This review may help policy-makers and program officers to design low birth weight preventive interventions. Globally, low birth weight (LBW) is one of the major public health problems of newborns  that preGlobally, 15 to 20% of newborns were LBW ; 13% in Despite these preventive strategies, many studies in different settings of the world revealed the contributing factors of LBW as the maternal –16, prenSimilarly, in Ethiopia, globally recommended strategies have been implemented. Variety of studies were conducted to estimate the prevalence of LBW in this country. However, prevalence of LBW ranges from 8%  to 55.9%The results of this review were reported based on the Preferred Reporting Items for Systematic Review and Meta-Analysis statement (PRISMA) guideline   AND (Ethiopia)].Retrieved studies were exported to reference manager software, Endnote version 7 to remove duplicate studies. Three independent reviewers screened the title and abstract. The disagreement was handled based on established article selection criteria. Three independent authors conducted the abstract and full-text review.Three independent authors appraised the quality of studies. The Joanna Briggs Institute (JBI) quality appraisal checklist was used . The disTwo independent reviewers extracted data using a structured data extraction form. Whenever variations of extracted data observed, the phase was repeated. If discrepancies between data extractors continued, third reviewer was involved. The name of the first author and year, the study region, the study design, the target population, the sample size, prevalence of LBW, and AOR of associated factors were collected.LBW was considered, when newborn weight recorded below 2500 g .Publication bias was checked by funnel plot and more objectively through Egger’s regression test . HeterogThe search strategy retrieved 288 from PubMed, 31 from Cochrane library, 13 from Web of Science, and 47 from Google Scholar. After duplication removed, 291 remained. Finally, 41 studies were screened for full-text review and 33 were to the prevalence and/ or associated factors analysis .The estimated overall prevalence of LBW is presented in a forest plot Fig. . The oveThe subgroup analysis based on the region, study design, and year was done. Based on this, the prevalence of LBW found to be 22% in Addis Ababa, 23% in the cohort studies, and 17.7% between the year 2010 and 2017   compared to married women , daily lThe pooled effects of three studies , 56, 60 Malaria attack during pregnancy  , historyInfants born from mothers with normal hemoglobin   were lesMaternal weight < 50 kg   and matePrimipara   and unwaThose mothers taking extra meal during pregnancy   were lesBaseline maternal CD4 counts below 200 cells/mm3 , and 201–350 CD4  as compared to> 350, and maternal exposure to Highly Active Antiret-roviral Treatment (HAART)   were assOne research showed  that thoThe pooled effect of maternal hypertension , 39, beiBased on the pooled effects of two studies , 59, beiThe pooled effects of four studies , 45, 47 Only one study  found, uFigure The Millennium Development Goal-4 was aimed to reduce mortality of under-5 children by two-thirds . It is cThis meta-analysis was estimated the national prevalence of LBW in Ethiopia. Accordingly, the national pooled prevalence of LBW was 17.7% (14.1–20.4%). This result was higher than studies conducted in Indonesia (12.9%), Armenia (9.0%), and Tanzania (13.9%) . This miFurthermore, the time-trend analysis showed that the burden of LBW in Ethiopia was not decreased significantly. This might be due to a slow progress in the quality of healthcare services, like institutional delivery, postnatal services, ANC coverages, and immunization coverage still need further improvement. Moreover, many of the people are in low economic status that has impacts on maternal nutritional status before and during pregnancy and birth complication would be apparent as a result.Based on the subgroup analysis, the prevalence of LBW was high in Addis Ababa as compared to other regions. Those studies included in this meta-analysis were conducted in governmental hospitals and data from private hospitals didn’t found. In Addis Ababa, there many private clinics and hospitals are avail. The probability of those mothers who had middle and high economic income delivered at private clinics would be high. As a result, the prevalence of LBW might vary as well.2, and gestational age of the baby at birth < 37 weeks (preterm delivery) were associated with LBW.Based on the pooled analysis of two or more AOR of studies, maternal age < 20 years, pregnancy interval < 24 months, maternal BMI < 18.5 kg/mThe odds of infants born from mothers whose age < 20 years were nearly two times more risk to have LBW. This finding supported by other studies conducted in Nigeria  and BrazThe odds of infants born within < 24 months birth interval were nearly three times to have LBW. This finding was in lined with a study in Sudan , Qatar , Iran 8, China , and Uni2 were more than five times risk to give LBW infants. Studies from Japan [2 indicates the presence of chronic malnutrition, in which fetal growth might be impaired. Therefore, LBW could be easily happen. Poor maternal nutritional status during pregnancy has also been associated with reduced placental weight and surface area, which could limit nutrient transfer from the placental circulation to the fetus. Moreover, undernutrition of mothers might leads to a reduction of serum concentrations of hormones, like leptin and estrogen, which results fetal growth impairment.Those mothers who had BMI < 18.5 kg/mom Japan , China [om Japan , and Thaom Japan  are inagThe odds of being premature birth was six times higher risk to be below normal birth weight. The finding from another study in India , Iran 1, and BraThis study identified important risk factors with independent effects on the burden of LBW in Ethiopia. National and regional policy and decision makers have work to improve these specific risk factors. Different strategies with appropriate community-based interventions on these factors need to be considered for improving overall child health in Ethiopia.This systematic review and meta-analysis is the national estimation conducted in Ethiopia. It may be lacked national representativeness because no data were found from Benishangul Gumuz, Afar, Gambella, Somalia, Dire Dawa, and Harare regions. Time-trend analysis might not reflect the exact trend because all the years didn’t have reported data.The prevalence of low birth weight in Ethiopia remains high. This review may help policy-makers and program officers to design interventions on preventing low birth weight.