Low birth weight (LBW) is an important risk factor for neonatal and infant mortality and morbidity in adults.. However, no large scale study on the prevalence of LBW and related maternal risk factors in China has been published. To explore the effects of maternal factors on LBW for term birth in China, we conducted a hospital-based retrospective study of 55, 633 Chinese pregnancy cases between 2001 and 2008. Maternal sociodemographic data, history of infertility and contraceptive use were obtained. Their medical status and diseases during pre-pregnancy were examined by physical examination at the first antenatal care visit. Maternal medical status before childbirth and pregnancy outcomes, including body weight, infant gender, multiple pregnancy and congenital anomalies, were recorded. Univariate and multivariate logistic regression, and linear regression were used to investigate the relationship between maternal factors and term LBW. The general incidence of term LBW was 1.70% in the developed area of China. After preliminary analysis using the univariate model, low primary education, anemia, hypertensive disorders, placental previa, oligohydramnios and premature rupture of membrane were predicted as independent factors of term LBW in the multivariate model. Furthermore, the decrease in annual frquencies of these risk factors were major causes of gradual decline in the incidence of LBW (from 2.43% in 2001 to 1.21% in 2008). The study demonstrated that among maternal factors, primary education, anemia and hypertensive disorders could contribute to LBW for term birth even in the most developed area of China. Low birth weight (LBW), regardless of gestational age, is a multifaceted public health problem with significant individual and societal impact worldwide, especially in developing countriesIn China, as family planning policy was initiated in the 1970s, the health issue of children has gradually become a major concern, not only for individual families but also for the entire society. However, the currently high incidence of LBW is problematic. The high rates of mortality and morbidity arise from LBW, which impose an immense burden on health resources, education, social services and familiesLBW is not only related to basic maternal characteristics during pre-pregnancy, but also related to potential risk factors during pregnancy including maternal age, educational attainment, lifestyle, health status and diseasesLBW can result from preterm birth (born before 37 weeks of gestation) or intrauterine growth restriction (IUGR). However, the definition of IUGR remains elusive as growth potential cannot be precisely quantified. Therefore, most cases of growth restriction are also considered small for their gestational age (SGA), but birth weight or estimated fetal weight can also be used as a surrogateTo more precisely determine the maternal risk factors associated with LBW, we examined the relationship between birth weight and maternal characteristics ) in a cohort of 55,633 pregnant Chinese women who had a single full-term delivery between 2001 and 2008. The results may protect infants from these factors in maternal pre-pregnancy and through gestation..This was a hospital-based retrospective study conducted between 2001 and 2008 at Wuxi Maternal and Child Health Hospital, affiliated with Nanjing Medical University, Wuxi, Jiangsu, China. All pregnant women whom came from Wuxi and its suburbs were asked to register when they first arrived at the hospital. Subsequently, each pregnant woman was asked to complete a structured questionnaire to provide individual information and a medical history. A series of regular medical examinations were conducted during pregnancy until delivery. A total of 61, 242 women participated in the investigation during the 8 years, of which 798 (1.3%) were excluded because of missing data, moving and spontaneous or induced abortion. Women with preterm delivery, post-term pregnancy (> 41 weeks) and multiple pregnancies (twins or more) were not included in the study as the data would interfere with LBW data. Thus, 55,633 pregnant women were enrolled in the study The 8 year data for enrolled pregnant women were obtained from digital record database of the authors' hospital. In brief, each woman completed structured questionnaire to provide individual information, such as maternal sociodemographic data , history of infertility and contraceptive use. Their medical status and diseases  during pre-pregnancy were examined by physical examination at the first antenatal care visit in the hospital. Maternal medical status before childbirth, such as hyperemesis gravidarum, fever, anemia, blood pressure, TORCH , anomaly of the uterus, abnormalities of the amniotic fluid and uteroplacental disorders, were recorded and followed up until the babies were born and left the hospital. Pregnancy outcomes, including body weight, infant gender, multiple pregnancies and congenital anomalies, were also regularly recorded. All live newborns were evaluated by determining Apgar scores at 1 and 5 min. The data from the antenatal care unit and delivery room were collected. The present study was approved by the Institutional Review Board of Nanjing Medical University , and all procedures were in accordance with prevailing ethical principles.+ on dipstick in two samples taken 6 h apart or > 300 mg in a 24 h urine collection); 3) severe preeclampsia . Anemia during pregnancy was defined as a hemoglobin concentration < 10 g/dL, which was tested after 8–10 weeks of gestation. Oligohydramnios was identified as an amniotic fluid volume < 300 mL. Polyhydramnios was defined as an amniotic fluid volume > 2,000 mL.In the present study, LBW was defined as delivery of single live newborn with birth weight < 2,500 g after a regular gestational period of 37–41 w. Hyperemesis gravidarum was defined as severe vomiting combined with positive urine ketone. Hypertensive disorders during pregnancy were divided into three specific subtypes: 1) gestational hypertension (blood pressure < 140/90 mmHg without proteinuria after 20 weeks of gestation); 2) mild preeclampsia , they would be selected for further analysis of independent effects on LBW by using a multivariate analysis model with confounding variables controlled. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by use of both univariate and multivariate analyses. Additionally, linear regression was applied to show variables including different years, LBW and related factors. regression coefficients and significance levels were also calculated.CData were entered into computer and double-checked before analysis. All statistical analyses were performed using the SPSS 13.0 package . LBW incidence associated with each factor was compared by χAs shown in P < 0.05 or P < 0.01). The results indicated that the above factors were related to higher risks for LBW. Among these risk factors, diabetes mellitus was associated with the highest incidence of LBW, which was approximately 8.4-fold higher than that of women without diabetes mellitus (14.29% vs. 1.70%).P < 0.01). Uterine rupture  and PROM  also had a certain risk for LBW (P < 0.05). Among these risk factors, severe preeclampsia in hypertensive disorders was associated with the highest incidence of LBW, which was approximately 10-fold higher than that in normotensive women (15.04% vs. 1.50%).The influence of disorders during pregnancy on LBW was also investigated. As shown in P ≤ 0.10, candidate factors or exposures during pre-pregnancy and perinatal stage were selected to analyze their individual influence on the incidence of LBW by using a multivariate regression model. P < 0.01), indicating that high education level may decrease the incidence of LBW, especially in China. Other factors including anemia, placental previa, oligohydramnios and PROM also increased the incidence of LBW by 31%–200% (P < 0.05).Based on a significance level of P < 0.01) . Compared with normotensive status, the incidence of LBW associated with gestational hypertension, mild preeclampsia and severe preeclampsia were 5.03% (OR = 3.35), 7.24% (OR = 4.83), and 15.04% (OR = 10.03), respectively (P < 0.01), which showed a positive relationship between symptoms and risk , Fig 3A. This association was also found in multivariate regression analysis. Regardless of whether the data were adjusted by infant gender, hypertensive disorders increased the risk for LBW , anemia, hypertensive disorders during pregnancy, placental previa, oligohydramnios and PROM were found to contribute to the incidence of LBW in the multivariate regression model, adjusted for maternal age and infant gender.Anemia is a common nutritional deficiency disorder and is very usual in pregnant women worldwideHydramnios and oligohydramnios are defined as excessive or deficient amniotic fluid. They are associated with an increase in perinatal mortality and have been correlated with smaller gestational age and lower birth weightP < 0.01) . Except for the number of women with diabetes is very low (14 vs. 55619), two women with LBW were included in women with hypertensive disorder, which suggested that diabetes might be an adjunctive factor of hypertensive disorder rather than an independent factor of LBW.Approximately 6%–8% of all pregnancies are complicated by hypertensive disordersThe incidence of term singleton infants with LBW in Wuxi was 1.70%. When preterm birth data were included in analysis, the incidence was 3.30%, which seemed lower than the average level in China and worldwide. Nonetheless, the incidence of LBW gradually declined from 2.43%  in 2001 to 1.21%  in 2008, which showed a significant linear regression. Interestingly, the incidences of the selected factors, such as low educational level, anemia and hypertensive disorders have decreased annually, which seem to be a good explanation for the decline of the incidence of LBW in this area. These changes further proved that the incidence of LBW was strongly associated with the given risk factors.To our knowledge, our cohort size was the largest of the studies that have analyzed the effects of maternal factors on the incidence of LBW for term birth in China. LBW is a multifactorial outcome and remains a public health problem. It might be a potential risk factor for poor growth and development in children and some diseases in adults. Therefore, a follow-up epidemiologic investigation has been planned, which will help protect healthy children from the influence of LBW, as health of children is the most concerned problem for families since Chinese family planning policy was initiated, especially in the most developed area of China.


Attention-Deficit/Hyperactivity Disorder (ADHD) is a complex and heterogeneous childhood disorder that often coexists with other psychiatric and somatic disorders. Recently, a link between ADHD and body weight dysregulation has been reported and often interpreted as impaired self-regulation that is shared between the two conditions. The objective of this study is to investigate the relation between body weight/BMI and cognitive, emotional and motor characteristics in children with ADHD.284 ADHD children were stratified by weight status/BMI according to WHO classification and compared with regard to their neurocognitive characteristics, motivational style, and motor profile as assessed by a comprehensive battery of tests. All comparisons were adjusted for demographic characteristics of relevance including, socioeconomic status (SES).Both Obese and overweight ADHD children exhibited significantly lower SES compared to normal weight ADHD children. No significant differences were observed between the three groups with regards to their neurocognitive, emotional and motor profile.Our findings provide evidence that differences in weight/BMI are not accounted for by cognitive, motivational and motor profiles. Socio-economic characteristics are strongly associated with overweight and obesity in ADHD children and may inform strategies aimed at promoting healthier weight. Attention-Deficit/Hyperactivity Disorder (ADHD) is an etiologically complex, highly heritable, common childhood psychiatric disorder with approximately 5% prevalence worldwide Recently, ADHD has been associated with body weight dysregulation From a psychological point of view, both ADHD and childhood obesity have been conceptualized as disorders of impaired self-regulation In addition to EFs, self-regulation depends critically on motivational systems that may be dysregulated in both ADHD and obesity. In this regard, mesolimbic dopaminergic neurotransmission has been firmly implicated in the regulation of saliency of behavioral tasks These neurocognitive/emotional parallels between ADHD and obesity are also supported by neuroimaging studies in ADHD and obese subjects The present study aims at testing the hypothesis that self-regulation deficits are associated with obesity in children with ADHD. Further, our study controls for socioeconomic status, consists of a large sample size, and utilizes a comprehensive assessment battery.The research protocol was approved by the Research Ethics Board of the Douglas Mental Health University Institute (DMHUI). Children with ADHD and their parents were explained the study procedures in detail, and provided verbal assent and written consent respectively.Two hundred and eighty four children with ADHD , ages 6–12 , were recruited from the severe disruptive behaviours program and ADHD outpatient clinic at the DMHUI. These children were referred to the aforementioned secondary care mental health facilities from different sources including, school teachers, pediatricians, family physicians, and community social workers. Thus the children participating in the current study are reflective of the general ADHD population.All children included in this study met DSM-IV diagnosis criteria for ADHD. A comprehensive clinical evaluation was used to establish the diagnosis of ADHD [see details in DSM-IV criteria for the combined subtype, 42.3% were diagnosed with the inattentive and 8.1% with the hyperactive subtypes of ADHD. A total of 30.3% were previously receiving medication for their ADHD symptoms and the rest were medication naive. Among comorbid disorders, 41.9% had oppositional defiant disorder, 11.3% had conduct disorder (CD), and 40.1% had an anxiety disorder.Among the total sample of affected ADHD children, 73.9% were male, and 18.0% belonged to families with an annual income of less than CN$20,000, 49.3% met All the clinical and self-regulation assessments were completed while the children were not taking any medication. In cases where children were on medication prior to their inclusion in the study, these assessments were carried out at the end of a one-week washout period.A comprehensive neuropsychological (NP) battery of tests specifically designed for children was used to study different executive function domains. Amongst the NP test battery, the Wechsler Intelligence Scale (WISC) Motivational style was first evaluated by using the choice delay task (CDT), a test specifically designed to assess the ADHD children's aversion to delay In addition to the CDT, the Restricted Academic Situation Scale (RASS) On the day of the testing, overall motor activity of children with ADHD was evaluated using actigraphy using a small electronic device (Actiwatch®) worn on the non-dominant hand, which is sensitive to acceleration. It records the subject's movements each 30 sec time period and expresses it as motor activity counts. Patients put on the Actiwatch® in the morning and kept it until the end of their testing in the early afternoon. The average motor activity was calculated and considered in the analyses as reflective of the overall motor activity of the child.All anthropometric measurements were taken by trained research assistants. Height of children with ADHD was measured using a wall-mounted chart with the subjects being bare-footed. Similarly, body weight was measured using a doctor's clinical scale with subjects clad in regular casual attire and being bare-footed.2)”. BMI was calculated for all children with ADHD, and then converted to age- and gender-specific percentiles according to the criterion available in the World Health Organization (WHO) website (http://www.who.int/en/). The WHO defines “normal weight” as ranging between 3rd to 84th percentile, “overweight” as ranging between 85th to 96th percentile, and “obesity” as equal or greater than 97th percentile.Body mass index (BMI) is a simple index of weight-for-height used to classify children into normal, overweight and obese categories. It is defined as “weight in kilograms divided by the square of the height in meters , overweight (n = 57), and obese (n = 59). Socio-demographic variables associated with BMI at a significance level of p<0.05 were used as covariates in subsequent analyses. Second, neurocognitive, emotional and motor outcome measures were compared between three weight/BMI groups using univariate ANOVA for continuous variables and chi-squared tests for categorical variables. Main effects were further explored by Post Hoc pairwise comparisons and the Bonferroni correction was used to protect from type I error.2,261 = 5.14, p = 0.006; F2,233 = 4.55, p = 0.01, respectively; all pair-wise p-values comparing the normal weight group to the other two groups were ≤0.01). In addition, compared to others, children in the overweight and obese groups belonged to a lower family income group , and were also exposed to higher severity of maternal smoking during pregnancy .As shown in 2 = 6.15, df  = 2, p = 0.04; With regards to previous medication status, ADHD children within the obese group were significantly less likely to be previously on medication (20.3%) compared to subjects in the overweight (25.0%), and normal weight (36.1%) groups  and prior history of treatment with psychostimulants.Additionally, as shown in It has been reported that children with ADHD have elevated risk for obesity in both epidemiological Different theoretical models have proposed that ADHD and body mass regulation disorders share common pathophysiological underpinnings. From a neuropsychological point of view, it is suggested that ADHD and obesity stem from impairments in individual's self-regulation z-scores (overweight and obese) compared with children who performed better on the neuropsychological battery. Several factors may explain this discrepancy between the two studies. Compared to Graziano and colleagues, the current study has a much larger sample size (n = 80 versus n = 284), the participants have a narrower age range (4.5–18 years versus 6–12 years), and the neurocognitive assessment is more comprehensive in the present study. Unlike Graziano and colleagues, our participants were not taking any psychostimulant medication for at least one week prior to the neurocognitive assessments. Further, our statistical analysis model used parental (both mothers and fathers) age at child birth, family income status, MSDP, and prior history of treatment with psychostimulants as covariates to prevent potential confounding effects on the result outcomes, which was not the case in Graziano et al. study. In addition, the use of different neuropsychological tests indexing various EF domains in children with ADHD could also contribute to incongruent results. Contrary to Graziano et al. study where all cognitive domains were reduce into one single factor, in the present study; we elected to explore separately all performances assessed by various tests in order to identify any specific differences between the three groups. These analyses did not identify any significant differences, including in neuropsychological tests common to our study and Graziano and colleagues' work (Color-Word Interference Test).The primary objective of the present study was to investigate the relation between body weight and cognitive, emotional, and motor activity characteristics in a large sample of children with ADHD. Results from our study do not identify statistically significant differences between weight groups  in children with ADHD with respect to neurocognitive measures tapping in executive functions, motivational style indices, and overall motor activity. These findings contrast with the results of the only other study examining the association between EF and weight in children with ADHD The present study identified a strong association between socioeconomic (SE) characteristics and overweight and obesity status in children with ADHD, including parental age at child birth, MSDP and annual family income. These results are in line with results of previous reports in children from the general population exploring the role of socioeconomic, geographic and environmental factors in influencing body weight gain and fat distribution Like ADHD Our study has a number of strengths. First, to our knowledge, this is the largest and most comprehensive study examining the relations between weight status/BMI and neurocognitive profiles, motivational status and motor activity in children with ADHD. In addition, all clinical, neurocognitive, motivational and motor activity assessments were carried out while the children were not taking any medication (1 week wash out period).The main limitations of this study also need to be considered. This study could not investigate the moderating effects of physical activity patterns To summarize, our results show that childhood obesity in ADHD is associated with specific socioeconomic characteristics but not associated with impairments in self-regulation characteristics. These results do not support previous theories suggesting that impaired self-regulation promotes obesity in ADHD. Consequently, changing unhealthy life style amongst low SES children should receive more attention in future research, particularly those aiming at preventing childhood obesity amongst ADHD with children.


The aims of this study were to assess the prevalence of a comorbid Attention Deficit Hyperactivity Disorder (ADHD) diagnosis in Borderline Personality Disorder (BPD), and its impact on the clinical presentation of BPD in adolescents, and to determine which type of impulsivity specifically characterizes adolescents with BPD-ADHD.ADHD diagnoses were sought in a sample of 85 DSM-IV BPD adolescents drawn from the EURNET BPD. Axis-I and -II disorders were determined with the K-SADS-PL and the SIDP-IV, respectively. Impulsivity was assessed with the BIS-11. and a non-significant trend for a higher prevalence of other cluster B personality disorders . Regression analyses revealed a significant association between Attentional/Cognitive impulsivity scores and ADHD  = 2.02, CI 95% 1.19-3.45).11% (N = 9) of BPD participants had a current ADHD diagnosis. BPD-ADHD adolescents showed higher prevalence of Disruptive disorders Comorbid ADHD influences the clinical presentation of adolescents with BPD and is associated with higher rates of disruptive disorders, with a trend towards a greater likelihood of cluster B personality disorders and with higher levels of impulsivity, especially of the attentional/cognitive type. A subgroup of BPD patients may exhibit developmentally driven impairments of the inhibitory system persisting since childhood. Specific interventions should be recommended for this subsample of BPD adolescents. Borderline personality disorder (BPD) is an impairing mental disorder that concerns 1-2% of the general population. It is characterized by a pervasive pattern of instability in affect regulation, impulse control, interpersonal relationships, and self-image -5. AmongImpulsivity, along with inattention and hyperactivity, is also one of the core symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD). ImpulsiThus, ADHD and BPD share dysregulation in emotional and impulse control, with a possible mediating role of a dysfunction of neuronal inhibitory systems. Interestingly, several reports concerning the greater-than-chance co-occurrence of these two disorders have been published -21. SincThe study sample was drawn from a European research project investigating the phenomenology of BPD in adolescence . The resDiagnosis of BPD was ascertained through the Structured Interview for DSM-IV Personality (SIDP-IV), a semi-structured interview assessing each of the ten DSM-IV personality disorders, including BPD . The relADHD diagnosis and other comorbid DSM-IV axis-I disorders were assessed using the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-PL), which is a semi-structured diagnostic interview designed to assess current and past episodes of psychopathology in children and adolescents according to DSM-IV criteria . The intDiagnostic interviews were conducted by a research team of five doctoral or master's level clinicians (psychologists or psychiatrists) familiar with DSM-IV Axis-I/II disorders and trained in the assessment and treatment of adolescents with psychiatric disorders. To reach high levels of reliability, the research evaluation team participated in several training sessions, including commented scoring of videotaped interviews and a training session conducted by the developers of the K-SADS . Concerning BPD diagnosis. special attention was paid to the question of the one-year duration of the symptoms and to the pervasive and persistent nature of the traits, unlikely to be limited to episodes of an Axis-I disorder. Final diagnoses were established by the best-estimate method on the basis of the interviews and any additional relevant data from the clinical record according to the LEAD standard . Inter-rImpulsive behaviors were investigated using the French validation of the Barratt Impulsiveness Scale (BIS-11). The BISTo explore a possible influence of ADHD on the clinical presentation of borderline personality disorder, BPD adolescents with (BPD-ADHD) and without (BPD) current comorbid ADHD disorder were compared for sociodemographic and clinical characteristics . To take into account the variability between centers, we used the Mantel-Haenszel chi-square statistic for categorical variables, preceded by the Breslow-Day test to assess the homogeneity of the odds ratios of the recruitment centres. For the continuous variables, we used the nested ANOVA statistic controlling for the recruitment centers. To reduce the number of statistical comparisons and comparisons with few observations, Axis-I and Axis-II diagnoses were included as groups of related disorders. Finally, to explore which type of impulsivity was specifically associated with BPD-ADHD adolescents, a logistic backward stepwise regression analysis was performed with presence or absence of ADHD as a dependent variable and with the three scores on the Barratt Impulsiveness Scale and the recruitment centers as independent variables. For all the analyses, the significance level was set at p = .05, 2-sided. Statistical analyses were performed using the 18th version of the Statistical Package for Social Sciences .This study was approved by the ethics committee of the Hôtel Dieu Hospital in Paris (authorization n° 0611259). Results were collected in an anonymous database according to the requirements of the French national committee for private freedoms. All participants, adolescents and parents, signed informed consent after receiving a full description of the study, explanation of its purpose, and information about the confidentiality of the data.One-hundred and seven adolescents with a DSM-IV clinical diagnosis of BPD were referred to the study by their psychiatrists. Of these subjects, 85 fulfilled SIDP-IV criteria for a BPD and composed the final sample of the study. There were no significant differences between the recruitment centres in terms of subject age and educational level, numbers of borderline criteria and in/outpatient ratio. The mean age of the sample was 16.3 ± 1.4 yrs; 74 (87%) were girls. The sample had a severe clinical profile: 67% (n = 89) of the subjects were recruited from inpatient units and had a mean score of 17.6 ± 3.9 on the SIDP-IV borderline diagnostic criteria (minimum required score being 15 with a maximum of 27). The most frequently endorsed criteria (more than 85% of the sample) were Impulsivity, Suicidal/self-mutilating behavior, Affective instability and Inappropriate anger. The majority of adolescents met the criteria for at least one Axis-I disorder . Mood disorders were the most frequently observed comorbidity  followed by eating disorders , disruptive behavior disorders , and substance use disorders . The sample showed a severe impairment in the overall level of psychosocial functioning with a mean GAF score of 47.2 ± 14. 76% of the samples were currently under medication. Antidepressants and antipsychotics were the most commonly prescribed drugs. No patients were currently taking stimulants, although 2 patients had been under methylphenidate treatment during childhood.Table 2 = 1.04, p = 0.79) and was mostly related to a higher prevalence of Oppositional defiant disorders in BPD-ADHD adolescents . No other significant difference was found for the prevalence of Axis-I groups of related disorders. Axis-II clusters of personality disorders were evenly distributed between BPD-ADHD and ADHD adolescents, with only a non significant association between BPD-ADHD adolescents and the other personality disorders of the cluster B . The non significant results of the nested anova concerning the recruitment centres imply that is unlikely that the differences between BPD adolescents with and without ADHD could be explained by differences in the centres. BPD and BPD-ADHD adolescents showed a similar level of family dysfunction and a similar overall level of psychosocial functioning Table . FinallyThe aim of this study was to explore the prevalence of a comorbid ADHD-BPD diagnosis and its impact on the clinical presentation of borderline personality disorder adolescents, and to explore which type of impulsivity is specifically associated with BPD-ADHD adolescents. To our knowledge, this is the first study investigating ADHD in BPD in this specific age group.Concerning the prevalence of ADHD diagnosis in our sample, we found a current rate of 11%. This result is close to the 16% rate found by Philipsen and colleagues in a sample of adult BPD female patients , notwithThe results of this study also show that the presence of a comorbid ADHD diagnosis influences the clinical presentation of BPD in adolescents. ADHD in BPD was significantly associated with a greater likelihood of disruptive disorders (particularly ODD) and with a trend for a greater likelihood of other cluster B personality disorders . This result is not surprising since in longitudinal studies, ODD in childhood as well as antisocial behaviours in adolescence and adulthood have been frequently observed as main outcomes for ADHD children ,42. ImpuSome limitations of the current study must be taken into consideration when interpreting the findings.First, the main limit of the study is its cross-sectional design with data on childhood ADHD diagnosis collected retrospectively. Only longitudinal studies can directly support the identification of the developmental pathways leading from childhood to adult psychopathology. This is even more important if we consider that these diagnostic constructs tend to overlap, particularly in the realm of impulsivity. However cross-sectional studies on comorbid disorders in specific populations, such as adolescents, can shed light on their clinical presentation and help identifying their specific therapeutic needs. Moreover, although indirectly, the high diagnostic stability between past and current ADHD diagnosis found in our study supports the hypothesis of a subtype of BPD with a childhood history of ADHD, hypothesis that has been recently confirmed by Stepp and colleagues in their longitudinal study on adolescent girls .The second limit concerns the small sample size of the study and the potential sample selection bias of the screening phase conducted by the consulting clinicians without performing a systematic between-center inter-rater reliability. This may have reduced the statistical power of the analyses and the generalizability of the results.For instance, our sample included a majority of female patients. It is commonly agreed that ADHD is less frequent in females, with a predominance of purely inattentional forms. It is possible that the high levels of impulsive features associated with ADHD could be due to a referral bias of our specific clinical sample composed of severe forms of BPD female adolescents. Although the size of the sample of BPD participants was reasonable compared to other studies, particularly since it was limited to adolescents with a well-characterized BPD diagnosis, results should be interpreted with caution as to know what the likelihood might be that the sample is actually representative of BPD adolescents.Finally, to assess impulsivity, we used the validated adult version of the Barratt Impulsiveness Scale. Although the use of the adult version of the BIS-11 in adolescents can be found in the literature on impulsivity ,57, it cNotwithstanding these limitations, the results of this study confirm, in an adolescent sample, previous studies conducted in adult samples  showing ADHD: Attention Deficit Hyperactivity Disorder; BPD: Borderline Personality Disorder; BPD-ADHD: Borderline Personality Disorder with Attention Deficit Hyperactivity Disorder; ODD: Oppositional Defiant Disorder; ASP: Antisocial Personality Disorder.The authors declare that they have no competing interests.All the authors listed in the manuscript have contributed sufficiently to the project to be included as authors. MS intiated and designed the protocol, collected data, participated in data analysis and interpretation and writing and revising the manuscript. ARL participated in data analysis and interpretation and revising the manuscript. SC participated in revising the manuscript. APS and MC participated in designing the protocol, and revising the manuscript. BF participated in data analysis and interpretation and in revising the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/158/prepub


Attention deficit/hyperactivity disorder (ADHD) often presents as an impairing lifelong condition in adults; yet it is currently underdiagnosed and undertreated in many European countries. This analysis examines the characteristics of adult patients with ADHD in a European (EUR) and non-European (NE) patient population.N=2017; EUR, n=1217; NE, n=800) were examined. All patients who were enrolled were included in the baseline analyses.Baseline data from the open-label treatment period of a randomized trial of atomoxetine in adult patients with ADHD (p=.0049). Scores on the Conners’ Adult ADHD Rating Scale-Investigator Rated: Screening Version with adult ADHD prompts  were comparable. The adult ADHD Quality of Life-Life Outlook and Life Productivity domain scores were significantly different between groups (p≤.0004). The EuroQol-5 Dimension United Kingdom and United States population-based index scores and Health State score were comparable between groups.The demographics for patients in the EUR and NE groups were comparable. Patients in the EUR group had a somewhat lower percentage of prior exposure to psychostimulants compared with the NE group (32.7% vs. 38.9%, Adults with ADHD in Europe present similar demographics and baseline characteristics to those outside Europe and hence, study results outside Europe may be generalizable to patients in Europe.NCT00700427Clinicaltrials.gov,  Attention deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder that begins in childhood. This disorder persists into adulthood in around one-third to two-thirds of children with ADHD -9. EpideAttention deficit/hyperactivity disorder remains a poorly understood disorder in adults and often presents as an impairing lifelong disorder currently underdiagnosed and undertreated in many European (EUR) countries ,15,16. IOne reason for underdiagnosis and undertreatment of ADHD in adults is that ADHD symptoms differ throughout the patient’s lifespan. Adult patients experience more subtle symptoms such as impairments in executive function , difficulties in relationships, poor motor vehicle driving skills, and psychiatric comorbidities including substance abuse disorders ,17,18. ATaking the differences in diagnosis and treatment of adult ADHD in many EUR regions into account, additional information on the characteristics of adult ADHD patients within Europe is needed ,19,21. TThe purpose of this analysis was to examine the characteristics of adult patients with ADHD in a large patient population in Europe as well as those outside Europe.N=2017; EUR, n=1217 [60%]; non-European [NE], n=800 [40%]). The majority (60%) of patients in the study were from Europe; of the remaining patients, the overwhelming majority (75%) were from the US. The numbers from other countries were relatively smaller and hence, we combined them with the US as non-European. Additionally, we carefully considered in which group to include Russia, which is considered part of Europe but is also part of Asia. However, since Russia is not part of the European Union, we chose not to include Russia in the EUR group. In addition, there were only 6 patients from Russia, so most likely the influence of Russian patients, overall, was limited. The NE group consisted of patients in the US (n=602), Canada (n=60), Mexico (n=53), Puerto Rico (n=52), Argentina (n=27) and Russia (n=6). The EUR group consisted of patients in Germany (n=434), Spain (n=153), Belgium (n=137), Sweden (n=112), Austria (n=109), Netherlands (n=71), France (n=65), Finland (n=52), Italy (n=32), Denmark (n=15), United Kingdom (UK) (n=27), Switzerland (n=7), and Portugal (n=3). Any excluded medications were tapered off and/or stopped during this study period.The subjects in this analysis included adults with ADHD who participated in a multicenter, multinational, randomized withdrawal trial of atomoxetine with 3 study periods: screening/washout, open-label acute treatment, and a randomized, double-blind, placebo-controlled withdrawal. Study Period I was a screening/washout period that consisted of a minimum of 3 days and a maximum of 28 days. Study Period II was a 12-week open-label treatment period (An informed consent document (ICD) approved by an Ethical Review Board or similar body was signed by the patient and/or representative deemed appropriate, according to local laws and regulations. Informed consent was obtained before any changes were made to the patient’s medical treatment plan for the purpose of study participation and before any study procedures were performed. The study was conducted in accordance with the Declaration of Helsinki and the applicable laws and regulations of the study countries and regions. The study is currently ongoing; the primary outcome of this trial will be reported upon study completion.Eligible patients were adults  with ADHD, as established by the Conners’ Adult ADHD Diagnostic Interview for Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM-IV) (CAADID), who had ADHD symptoms in childhood and scored ≥2 on at least 6 items of either the inattentive and/or hyperactive/impulsive core subscales of the Conners’ Adult ADHD Rating Scale (CAARS)-Investigator Rated: Screening Version (CAARS-Inv:SV). CAARS-Inv:SV is a 30-item scale containing 2 subscales (inattentive and hyperactive/impulsive) and the ADHD index . The inaThe CGI-ADHD-S is a single-item clinician rating of the clinician’s assessment of the overall severity of the patient’s ADHD in relation to the clinician’s total experience with ADHD patients. Severity is rated on a 7-point scale  . ClinicaAll raters were trained in administration of the CAADID and CAARS-Inv:SV with adult prompts via standard training procedures . Before Exclusion criteria stated that patients should be excluded from the study if they met the following criteria: Patients met full DSM-IV-Text Revision™ (DSM-IV-TR™) diagnostic criteria for any history of bipolar disorder, current major depression, a current anxiety disorder , or any history of a psychotic disorder. Additional exclusion criteria were as follows: Patients were currently using alcohol, drugs of abuse, or any prescribed or over-the-counter medication in a manner that the investigator considered indicative of chronic abuse or met DSM-IV-TR criteria for alcohol or other substance dependence.All patients who were enrolled in the open-label acute treatment period were included in this analysis of ADHD characteristics. Data at baseline were used in the current analysis.N=2017), some comparisons were too sensitive and detected unsubstantial differences. Hence, p-values were used as references only and standardized differences were used to determine clinical relevance as described below. Data on education level difference and family history were analyzed post hoc. The overall relationship of education level to prior stimulant use was assessed with a chi-square test, while Fisher’s exact test was used to test prior stimulant use for each individual level of education. The relationship of adult ADHD Quality of Life (AAQoL) scores to education level was assessed with analysis of variance (ANOVA). All tests were 2-sided and employed a significance level of 0.05. Statistical analyses were performed using SAS version 9.1.Continuous baseline patient characteristics were summarized by mean, median, standard deviation, minimum, and maximum. Categorical baseline characteristics were summarized as percentages. Statistical comparisons were conducted using t-tests for continuous data and Fisher’s exact test or a chi-square test for categorical data; however, due to a large sample size  Index, and AAQoL scores. The standardized differences between groups were calculated with the following formula: ([the mean for the EUR group] minus [the mean for the NE group]) divided by the pooled  standard deviation, thus mirroring the calculation of Cohen’s d . The stap<.0008). The CAARS-Inv:SV total score was significantly different (p<.0001), and it seemed to be due to the lower scores in Russia (mean=27.3) compared with North America (mean=39.6) and South America (mean=42.0). The CGI-ADHD-S analysis was not significantly different across regions (p=.0761) and neither was the AAQoL total score (p=.2662). Only CAARS-Inv:SV total score showed any potentially meaningful differences among North America, South America, and Russia, while all of the others did not; also, Russia’s sample was thought to be too small (N=6) to skew the NE data as a whole, justifying the grouping of these regions. In addition, Russia's sample (N=6) was too small to be a stand-alone region.Baseline demographics were first compared among North America (N=767), South America (N=27) and Russia (N=6) to ensure homogeneity within NE, and ensure that differences between NE regions did not skew data. Age, gender, and ADHD subtype were examined but were not statistically different across the sub-regions . The CAARS-Inv:SV total score, CGI-ADHD-S score, and AAQoL total score were compared among regions. All 3 CAARS scores  were examined and all were significant (p<.0001). Mean height was 173.8 cm for EUR patients and 171.7 cm for NE patients (p<.0001). Patients in the EUR group had a lower percentage of exposure to psychostimulants (32.7%) compared with patients in the NE group . The ADHD combined subtype comprised 71.7% of the EUR group and 77.9% of the NE group, while the inattentive subtype comprised 24.5% of the EUR group and 21.0% of the NE group (p=.0001). Family history of ADHD in the patient’s mother  or father  was reported to be of similar frequency in the EUR and NE groups. Family history of ADHD in siblings was greater in the NE group (18.3%) compared with the EUR group . Family history of ADHD in children was greater in the EUR group (25.3%) compared with the NE group .The demographics for patients in the EUR region and NE regions were compared Table . The meap<.0001). The CGI-ADHD-S score at baseline was severe , which suggests that the patients had significant impairment. When evaluated with standardized differences, the CGI-ADHD-S score was moderately different .The CAARS-Inv:SV ADHD index score was statistically significantly different between groups, as were the investigator-rated Hyperactivity-Impulsivity and Inattention subscale scores, and total ADHD symptom score Table . The scop≤.0004), with the NE group having a higher score on Life Outlook  and the EUR group having a higher score on Life Productivity, . Life Outlook and Life Productivity section scores were not clinically meaningfully different using standardized differences .The AAQoL total score was also comparable between groups . The AAQoL total score had a 0.8-point difference between groups ; the AAQoL total score and section score can range from 0 to 100. Psychological Health  and Relationships  section scores were not significantly different between the EUR and NE groups. The differences between EUR and NE groups on the Life Outlook and Life Productivity section scores were significantly different (p≤.0003), but the differences were very small between groups and not clinically meaningful when calculated with standardized differences  [p<.0001). When the standardized difference was examined (-0.253), the differences between groups on the EQ-5D UK and US population-based index scores were not clinically meaningful.The EQ-5D UK population-based index score and US population-based index score were statistically significantly different ( -0.143) . The HeaThere were some statistically significant differences between the EUR and NE groups in education (highest grade completed) Table . As compp=.411). Only some college and university education were significantly related to prior stimulant use. Patients who reported their highest education level as some college were more likely to report prior stimulant use . Prior stimulant use was reported in fewer patients with university education compared to no prior stimulant use .To determine if education level was the cause of the difference in prior stimulant use between EUR and NE, education level  was compared with respect to prior exposure to psychostimulants. Overall, prior stimulant use was not related to education level (p≤.001); however, both scores were affected by a few outliers. There was no substantial difference across education levels in any AAQoL measure.We further examined whether the difference in level of education as opposed to region was responsible for the differences between groups in AAQoL scores. The Life Outlook score and Life Productivity score were significantly different among education levels (p<.001) and generalized anxiety disorder , and current diagnosis of depressive disorder , dysthymic disorder , and social phobia .The summary of present and lifetime diagnosis of comorbid diseases at baseline is shown in Table N=2017) made finding statistically significant differences more likely, but many of these were small in absolute magnitude and were not clinically meaningful.This analysis of adults with ADHD was the first randomized clinical trial of this size analyzing patient characteristics across multiple countries. Results of these analyses of adults with ADHD in the EUR and NE regions indicate that the characteristics of adult patients with ADHD are comparable between the regions. There were some subtle differences, but further evaluation indicates consistency between the EUR and NE groups. The large sample size , but comparable with scores observed in previous US adult ADHD studies -32. The The AAQoL Life Outlook and Life Productivity section scores were statistically significantly different, but arguably of questionable clinical significance. The EQ-5D UK population-based index score, US population-based index score, and Health State score were statistically significantly different, but also arguably of questionable clinical significance.The NE group primarily included North American countries. Since it also included a small number of patients from Russia and Argentina, a sensitivity analysis was performed to test whether removal of Russian (n=6) and Argentinian (n=27) patient data from the NE data set would change the conclusions of the manuscript; results from this analysis confirmed that, if data from these 33 patients were removed from the NE data set, none of the conclusions would change. Therefore, we kept Russia and Argentina in the NE group to be complete.The major difference between the EUR and NE groups was prior exposure to psychostimulants. This difference may be due in part to differences in treatment in the EUR and NE regions. In some parts of Europe the use of stimulants to treat adults with ADHD has been controversial and stimulants are not approved for use in adults with ADHD . The 200Current and lifetime diagnoses of comorbid diseases at baseline were comparable. This may be due in part to the exclusion criteria, which stated that patients should be excluded from the study if they met the criteria for several comorbid conditions. Childhood and adulthood diagnoses of ADHD were also comparable across regions. This could be due in part to the inclusion criteria stating that, to be eligible for the study, patients must meet DSM-IV-TR criteria for current ADHD and for a historical diagnosis of ADHD during childhood, as assessed by the CAADID.The findings of these analyses on baseline characteristics of the adult ADHD patient in the EUR and NE regions were similar to the conclusion of the previous analyses on the characteristics of children and adolescents with ADHD outside North America ,35. In PN=2017), some comparisons between groups were statistically significant despite the absolute differences being small and not clinically meaningful; hence, p-values were used as references only, and interpretation of data was based on the magnitude of the findings rather than the p-value. Finally, this study did not look at treatment effects. Despite the limitations of this study, this analysis serves to help define/clarify who the adult ADHD patient is not only in the US, but across several countries.Several limitations of our study must be acknowledged. This is a clinical trial patient population that is based on inclusion and exclusion criteria. Due to the homogeneity of the sampling method, the data may not be representative of patients with comorbidities. Though, community-based studies on the prevalence of adult ADHD as part of the World Health Organization World Mental Health Survey found fairly similar prevalence rates of adult ADHD throughout the countries that were surveyed (mean = 3.4% range = 1.2% to 7.3%) . There iIn summary, the results reported here show that the characteristics of adult ADHD patients are generally comparable across EUR and NE regions. Although studies in the EUR population may be needed to address specific issues, the results suggest that research findings in adults with ADHD in NE regions can be generalized to adult patients with ADHD in the EUR region.Doctors Upadhyaya, Tanaka, Escobar, and Allen are full-time employees of Eli Lilly and Company and stockholders of Eli Lilly and Company. Dr. Arsenault and Mr. Williams are full-time employees of PharmaNet/i3, an inVentiv Health Company. Dr. Arsenault is also a former employee of, and minor stockholder in, Eli Lilly and Company.Dr. Adler has received royalty payments (as an inventor) from New York University. He receives/d grant research support from Abbott Laboratories, Bristol-Myers Squibb, Chelsea Therapeutics, Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Shire, Eli Lilly and Company, Ortho-McNeil/Janssen/Johnson & Johnson, New River Pharmaceuticals, Cephalon Inc, Organon, and National Institute of Drug Abuse. He is/has been on the advisory board and consulted for Alcobra Pharmaceuticals, AstraZeneca, Shire, Eli Lilly and Company, Mindsite, Major League Baseball, and i3 Research. He is/has been a consultant for Epi-Q, INC Research, United Biosource, Otsuka, Major League Baseball Players Association, Ortho-McNeil/Janssen/Johnson & Johnson, Psychogenics, and Theravance.Dr. Casas has received travel grants from Eli Lilly and Company, Janssen Cilag, Shire, and Laboratorios Rubió. He receives/d grant research support from Janssen Cilag, Shire, Laboratorios Rubió, and Eli Lilly and Company. He is/has been on the advisory board for Janssen Cilag, Shire, Laboratorios Rubió, and Eli Lilly and Company. He is/has been a consultant for Janssen Cilag, Shire, Laboratorios Rubió, and Eli Lilly and Company.Dr Kutzelnigg has received travel grants from Eli Lilly and Company, Affiris AG, Novartis Pharmaceuticals Corporation, and AstraZeneca and payment for lectures including service on speakers’ bureaus from Eli Lilly and Company, Novartis Pharmaceuticals Corporation, and Affiris AG, and serves as a consultant for Eli Lilly and Company.HU made substantial contributions to the analysis and interpretation of the data, was involved in drafting the manuscript and revising the intellectual content of this manuscript. LAA made substantial contributions to the analysis and interpretation of the data, was involved in drafting the manuscript and revising the intellectual content of this manuscript. MC was involved in drafting the manuscript and revising the intellectual content of this manuscript. AK made substantial contributions to the analysis and interpretation of the data, was involved in drafting the manuscript and revising the intellectual content of this manuscript. YT made substantial contributions to the design of the study, performed the statistical analysis, and was involved in drafting the manuscript and revising the intellectual content of this manuscript. DW performed the statistical analysis, and was involved in drafting the manuscript and revising the intellectual content of this manuscript. JA was involved in drafting the manuscript and revising the intellectual content of this manuscript. RE made substantial contributions to the design of the study, analysis and interpretation of the data, and was involved in drafting the manuscript and revising the intellectual content of this manuscript. AJA made substantial contributions to the design of the study, analysis and interpretation of the data, and was involved in drafting the manuscript and revising the intellectual content of this manuscript. All authors read and approved the final manuscript.


The aims of this study were to determine the time course of improvements in attention deficit hyperactivity disorder (ADHD) clinical symptoms and neurocognitive function in a realistic clinical setting, and the differences in ADHD symptom improvement using different classifications of ADHD subtypes.The Child Behavior Checklist (CBCL) was completed by parents of ADHD children at the initial visit. The computerized Continuous Performance Test (CPT), Swanson, Nolan, and Pelham, and Version IV Scale for ADHD (SNAP-IV), and ADHD Rating Scale (ADHD-RS) were performed at baseline, one month, three months, and six months later, respectively. Patient care including drug therapy was performed at the discretion of the psychiatrist. The ADHD patients were divided into DSM-IV subtypes , and were additionally categorized into aggressive and non-aggressive subtypes by aggression scale in CBCL for comparisons.There were 50 ADHD patients with a mean age of 7.84 ± 1.64 years; 15 of them were inattentive type, 11 were hyperactive-impulsive type, and 24 were combined type. In addition, 28 of the ADHD patients were grouped into aggressive and 22 into non-aggressive subtypes. There were significant improvements in clinical symptoms of hyperactivity and inattention, and impulsivity performance in CPT during the 6-month treatment. The clinical hyperactive symptoms were significantly different between ADHD patients sub-grouping both by DSM-IV and aggression. Non-aggressive patients had significantly greater changes in distraction and impulsivity performances in CPT from baseline to month 6 than aggressive patients.We found that ADHD symptoms, which included impulsive performances in CPT and clinical inattention and hyperactivity dimensions, had improved significantly over 6 months under pragmatic treatments. The non-aggressive ADHD patients might have a higher potential for improving in CPT performance than aggressive ones. However, it warrant further investigation whether the different classifications of ADHD patients could be valid for predicting the improvements in ADHD patients' clinical symptoms and neurocognitive performance. Attention deficit hyperactivity disorder (ADHD), which occurs in 3% to 10% of school-age children, is one of the most common child and adolescent psychiatric disorders . ADHD inEarly concerns about ADHD classification were raised over whether it is a broad sense of conduct disorder or a distinct externalizing category . Some stBased on the current Diagnostic and Statistical Manual, Fourth Edition (DSM-IV) , ADHD isOf the stimulant medications, MPH is the most widely used in the pharmacological management of children with ADHD . Some stTherefore, the aims of the present study were to determine: First, whether there are sustainable improvements in ADHD clinical symptoms and neurocognitive function in realistic clinical settings. Second, whether the differences in ADHD clinical symptoms and neurocognitive functions between ADHD subtypes exist along with the course of treatment. And, whether there were differences in improvements in ADHD symptoms between different classifications of ADHD patients.This observational-prospective study was conducted at the Child and Adolescent Psychiatry Out-patient Department of Chang Gung Memorial Hospital, Keelung, from May 2008 to June 2009. The study was approved by the Institutional Review Board (IRB) of Chang Gung Memorial Hospital. We recruited patients aged between 6 and 12 years old who met the criteria for ADHD outlined in the DSM-IV . The diaPatients were interviewed by a clinician using the ADHD Rating Scale (ADHD-RS) and a computerized Continuous Performance Test (CPT). The social and behavioral competence and ADHD symptoms of patients were evaluated with the Child Behavior Checklist (CBCL), Swanson, Nolan, and Pelham, and Version IV Scale for ADHD (SNAP-IV), which the parents of the patients completed.is a questionnaire completed by parents and teachers that evaluates the social and behavioral competence in the past 6 months of children aged between 4 and 16 years old ,26. The by DuPaul et al. (1998) is a validated instrument with which clinicians assign ratings on the basis of information from the parent(s) and child . It is ais a 26-item questionnaire in a 4-point Likert scale that is used to evaluate ADHD symptoms and severity, and it is completed by parents and teachers ,31. The The computerized CPT involves the presentation of target and non-target stimuli. The test runs for 14 minutes and primarily assesses attention and impulse control ,34. BrieThis investigation comprised a 24-week, non-randomized, observational, prospective study. At visit 1 (baseline), each ADHD patient performed the CPT at around 9:00 AM; this took place in a room dedicated to testing so that test condition variability was minimized. The CBCL and SNAP-IV were completed by the patients' parents, and ADHD-RS ratings were made by a child psychiatrist. At visit 2 (one month from baseline), patients performed the CPT at 9:00 AM, around 1 to 2 hours after they had taken MPH. The SNAP-IV was completed by the patients' parents, and ADHD-RS ratings were made by the same rater. At visit 3 (3 months from baseline) and visit 4 (6 months from baseline), the same procedure as visit 2 was repeated.Subjects were prescribed MPH at a dose range of 5 to 15 mg/day at visit 1 (V1), based on the severity of their clinical symptoms, and their age, height and body weight. Other concomitant medications were not allowed. Patients were advised to take MPH at least on weekday, but drug holiday was permitted. We confirmed the drug compliance at each visit according to the reports of patients' parents and the remnant drug. To ensure the study reflected real-life clinical practice, patient care was performed at the discretion of the psychiatrist. Modification of the MPH dose could take place at visit 2 (V2), visit 3 (V3) or visit 4 (V4). No treatment instructions were given other than that the psychiatrist should manage the subjects per their usual practice. Follow-up of the subjects was not limited by the study's schedule of assessments.The data were analyzed with the statistical software package SPSS, Version 16. Variables are presented as either mean ± standard deviation (SD) or frequency.t-test or One-way analysis of variance (ANOVA) was used to compare the demographic data and the CBCL, SNAP-IV, ADHD-RS, and CPT scores between ADHD subtypes.The ADHD patients were divided into DSM-IV subtypes , and were also categorized into aggressive and non-aggressive subtypes, based on the aggression scale of the CBCL, with a cutoff point of 60. Chi-square was used to compare the rate of lost to follow-up between subtypes. The Student's t-test was applied for examine the significant differences of these changes between subtypes.Patients with a baseline assessment and at least 1 follow-up assessment were included in the efficacy analyses. Missing data were accounted for using the method of last observation carried forward (LOCF). The ADHD measures, except oppositional scores of SNAP-IV, were reduced by means of a principal components analysis (PCA) with a set of weights for a composite ADHD score for each subject. The composite score for each factor and oppositional scores of SNAP-IV were applied to the analysis for repeated-measure analysis of variance (ANOVA), followed by a post-hoc Least Significant Difference (LSD) test. We investigated the extent of the differences in changes of these composite ADHD scores for each factor between ADHD subtypes, also by repeated-measure analysis of variance (ANOVA), using average MPH dosage/body weight during 6 month as a covariate. The hypothesis that there is a differential change over 6 months would be supported by significant subtype × visit interactions on dependent measures. The factors which showed a significant interaction between subtypes and visits were taken into further analyzed. The changes from the baseline to the endpoint of these factors were computed, and the Student's Two-tailed p values < 0.05 were considered statistically significant.There were 50 ADHD patients (40 boys and 10 girls) with a mean age of 7.84 ± 1.64 years. Fifteen of them were inattentive type, 11 were hyperactive-impulsive type, and 24 were combined type. Using a cutoff point of 60 on the aggression scale of the CBCL, patients were also categorized into aggressive and non-aggressive subtypes: 28 into the aggressive subtype and 22 into the non-aggressive subtype. There was no significant difference in the categorization rates of patients with aggression between the DSM-IV subtypes. Table Among the 50 ADHD patients at the initial visit, 42, 33, and 30 patients remained in the study at visit 2, 3, and 4, respectively. The reasons for premature discontinuation were adverse events (N = 3), non-compliance (N = 4), withdrawal of consent (N = 2), and lost to follow-up (N = 11). There were no significant differences in discontinuation rates between DSM-IV subtypes ADHD patients (p = 0.905), or between aggressive and non-aggressive patients (p = 0.606). All patients were drug-free at visit 1 (baseline). The mean dose of MPH was 9.87 ± 5.09 mg (0.37 ± 0.20 mg/kg) at visit 2, 14.88 ± 6.97 mg (0.48 ± 0.29 mg/kg) at visit 3, and 13.00 ± 7.52 mg (0.46 ± 0.24 mg/kg) at visit 4, respectively.To condense the number of ADHD measures and reduce type I errors, a principal components analysis was performed. Four factors yielding eigenvalues greater than 1.00 were retained for varimax rotation. The weights for the measures of each factor are listed in Table During the 6-month treatment, there were significant improvements in CPT impulsivity , clinical hyperactivity , and clinical inattention . However, CPT distraction was not improved , and there were no significant differences between any paired visits. For the rest three factors aforementioned, the trends of changes were the same during 6 months. There were significant improvements from V1 to V2, and V2 to V3, but no significant differences from V3 to V4. The oppositional scores of SNAP-IV significantly changed over 6 months , and there were significant differences from V1 to V2, and V3 to V4.In terms of the differences between DSM-IV subtypes, Figure For the differences between aggressive and non-aggressive patients, the results were more diverse in each factor. Figure The results of our study showed significant improvements in clinical hyperactivity, inattention, and CPT impulsivity composited scores, but not in CPT distraction scores during the 6 months of real-world clinical treatment. There were significant differences in clinical hyperactivity between ADHD patients sub-grouping both by DSM-IV subtype and by CBCL aggressive scale. There were no interactions between DSM-IV subtypes and visits in these 4 dimensions of clinical symptoms and cognitive performance among ADHD patients. Nevertheless, the interactions between sub-grouping by CBCL aggressive scale and visits were significant in the CPT performance.Optimal performance on the CPT is achieved by responding quickly and not making mistakes . Some stDifferences in the neuropsychological profiles and effects of MPH between DSM-IV subtyping ADHD patients have been reported ,17. ChhaDifferent characteristics of behavioral and neurocognitive performance were investigated between aggressive and non-aggressive ADHD patients, and classified by the IOWA Conners or CBCL ,12,41. KThese results also supported the hypothesis that aggressive and non-aggressive ADHD patients might have different underlying determinants. Diminished central serotonergic (5-HT) activity has been linked to impulsivity and aggression . CatechoThe course of ADHD symptom improvement has been demonstrated in some studies. However, most of these studies focused on the acute effects of MPH on neuropsychological tests ,20. OtheSome limitations of this study need to be considered. First, this was an open labeled, non-randomized study, so the placebo effects, rating bias, and reporting bias could not be ruled out. In addition, there was no data of ADHD patients on placebo or non-medicated for comparison; hence, we could not certainly justify these results derived from effects of MPH or time. Second, the aggressive and non-aggressive ADHD patients were roughly divided by the aggressive behavior scales of the CBCL with a cutoff point of 60. A suitable index has been suggested for two standard deviations above the normal mean on the Aggressive scale (T score > 70) . HoweverWhile having limitations, our study has strengths relative to studies on similar topics. First, we used longitudinal evidence of changes in ADHD symptoms, rather than a cross-sectional observation or an acute response to MPH. Second, we measured many dimensions of ADHD symptomatology, with scores derived from information provided by the patients' parents (SNAP-IV) and clinical observers (ADHD-RS), and from performance on a neurocognitive test (CPT). Last, we used different categories in comparing ADHD symptom improvements.We suggest ADHD symptoms, which include impulsivity performance in the CPT and clinical inattention and hyperactivity dimensions, were significantly improved during 6 months in realistic clinical settings. The non-aggressive ADHD patients might have a higher potential for improving in CPT performance than aggressive ones. However, it warrant further investigation whether the different classifications of ADHD patients could be valid for predicting the improvements in ADHD patients' clinical symptoms and neurocognitive performance.The authors declare that they have no competing interests.LJW, YSH and YLC conceived the study, recruited the participants, and wrote the paper. CCH and ZYS gathered and analyzed the data. CKC carried out the literature search and helped to draft the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/65/prepub


Bartonella spp. and Leptospira spp. as a model.Emerging bacterial zoonoses in bats and rodents remain relatively understudied. We conduct the first comparative host–pathogen coevolutionary analyses of bacterial pathogens in these hosts, using Bartonella genotypes from 24 bat species, 129 Bartonella from 38 rodents, and 26 Leptospira from 20 bats. We generated maximum likelihood and Bayesian phylogenies for hosts and bacteria, and tested for coevoutionary congruence using programs ParaFit, PACO, and Jane. Bartonella spp. and their bat hosts had a significant coevolutionary fit . Bartonella spp. and rodent hosts also indicated strong overall patterns of cospeciation . In contrast, we were unable to reject independence of speciation events in Leptospira and bats . Separate analyses of New World and Old World data subsets yielded results congruent with analysis from entire datasets. We also conducted event-based cophylogeny analyses to reconstruct likely evolutionary histories for each group of pathogens and hosts. Leptospira and bats had the greatest number of host switches per parasite (0.731), while Bartonella and rodents had the fewest (0.264).We used published genetic data for 51 Bartonella exhibits significant coevolution with minimal host switching, while Leptospira in bats lacks evolutionary congruence with its host and has high number of host switches. Reasons underlying these variable coevolutionary patterns in host range are likely due to differences in disease-specific transmission and host ecology. Understanding the coevolutionary patterns and frequency of host-switching events between bacterial pathogens and their hosts will allow better prediction of spillover between mammal reservoirs, and ultimately to humans.In both bat and rodent hosts,  Bartonella and Leptospira, along with their bat and rodent hosts. We found that Bartonella had a significant pattern of coevolution with both bat and rodent hosts, while Leptospira in bats showed a lack of congruence with its bat hosts and a high number of host switching events. Our statistically driven approach to understand the frequency of host switching events in these mammal–bacterial systems can be easily applied to other host–pathogen systems, including viruses, to assess the likelihood of zoonotic spillover.Bats and rodents are important hosts for emerging human diseases. While a large body of research has focused on viral pathogens in these hosts, the diversity, evolution, and transmission of their bacterial pathogens remains relatively unstudied. We conducted co-evolutionary analyses of two bacterial genera know to be pathogenic in humans,  Bats and rodents are the two most diverse and geographically widespread orders of mammals Bats and rodents are evolutionarily ancient orders of mammals, with periods of diversification dating back 75 and 85 million years ago, respectively, thus allowing ample time for pathogens and hosts to coevolve Bartonella spp. and Leptospira spp., known to cause neglected tropical diseases in humans.The evolutionary patterns of hosts and their known pathogens can be used to quantify the frequency of spillover events within and between reservoir hosts, and is a crucial first step for developing predictive models for zoonotic disease emergence. Previous research has demonstrated how these coevolutionary studies can shed light on specific instances of host switching, cospeciation, and other events in coronaviruses and their bat hosts Bartonella consists of globally distributed and highly diverse alpha-proteobacteria that infects a wide-range of mammals. After infection, the bacteria eventually enters erythrocytes and endothelial cells and can persist asymptomatically in a wide range of mammalian reservoir hosts Bartonella species in mammals is the result of a complex relationship between multiple hosts, vectors, and pathogens. Bartonella has been reported with high prevalence and genetic diversity from numerous recent studies in bats Bartonella is recognized as a neglected tropical disease, and there are indications of human infections derived from neighboring wildlife populations. In Thailand, genetic studies have indicated highly similar Bartonella strains between infected humans and nearby rodent populations The genus Leptospira is a genus of spirochete bacteria which also has a wide geographical distribution Leptospira in Madagascar, Australia, Peru, and Brazil, and seroprevalence has been recorded to be as high as 35% Bartonella spp., Leptospira spp. are not vector-borne, and transmission to humans and other hosts is primarily through contact with water and environments contaminated with infected animal urine Bartonella and Leptospira in bat and rodent hosts, we compiled available genetic information from hosts and bacterial pathogens to determine cophylogenetic patterns on a global scale. Evidence of cophylogeny can be used to test hypotheses of coevolution, and a lack of congruence between host and pathogen phylogenies can identify pathogen spillover, or interspecific transmission, events Bartonella was observed in Old World bats in Kenya Bartonella-bat relationships Bartonella in rodents, with host-specificity apparent in both Old and New World In order to better understand the evolutionary dynamics of Bartonella and Leptospira as case studies. We specifically test for evolutionary congruence between bat host species and Bartonella and Leptospira, as well as rodent host species and Bartonella. Analysis of rodent Leptospira was unfortunately excluded due to a lack of comparable sequence datasets and host taxonomic diversity. Although there is a long history of research on leptospirosis in rodents, the publicly available sequence data that has been obtained thus far covers only a handful of rodent host species distributed across 3 genes: secY, flab,and lipL3 BartonellaThe primary goal of this paper is to examine the global co-evolutionary patterns of bats, rodents and their associated bacterial pathogens – using Bartonella*” and “Leptospir*” combined with “bat OR Chiroptera*” or “rodent*”. All Bartonella and Leptospira sequences from bat or rodent hosts identified to the species level were compiled into our datasets  from 24 bat species , and 129  Bartonella genotypes from 38 rodent species . We also compiled sequences from 26 Leptospira genotypes  from 20 bat species . Insufficient genetic data of one gene for Leptospira in rodents precluded their use in the analysis; therefore only Leptospira in bat hosts was examined.In total, we compiled sequences from 51 Bartonella was Brucella melitensisLeptospira was Leptonema illiniOrnithorhynchus anatinus HQ379861 Bartonella sequences, and 1,246 bp for 16S Leptospira sequences.Bacterial and host species sequences were imported from GenBank into Geneious Pro 5.0.4. Sequences for each bacterial genus and their corresponding bat and rodent hosts were each aligned using default parameters in MUSCLE www.phylo.org) using the substitution model GTRMIX, which determines an optimal tree by comparing likelihood scores under a GTR+G model. The number of bootstrap replicates were determined using the previously described stopping criteria. In order to corroborate the phylogenies as determined through ML, Bayesian inference (BI) host phylogenies were also generated using MrBayes 3.1.2 th generation with 4 heated chains and a burn in length of 1,000,000.Maximum likelihood (ML) phylogenetic trees were generated using RAxML 7.0.4 To visualize host-bacteria associations, tanglegrams were generated from the best ML trees in TreeMap 3.0 Global-fit methods were used to quantify the degree of congruence between two given host and parasite topologies, and identify the individual associations contributing to the cophylogenetic structure As ParaFit tends to be liberal with its values, we also implemented newly developed program Procrustean Approach to Cophylogeny (PACo) We then used event-based program Jane 4 The topology of the BI tree was identical to that of the ML tree, except for a few branches with low support values. Thus, only the ML trees are presented here and used for further cophylogenetic analyses. Phylogenies tend to be well supported for more recent divergence events, but not deeper nodes. Nodes with bootstrap values ≥50 are labeled on all tanglegrams –6.Bartonella and bats provided evidence for significant co-evolution between Bartonella and bat hosts . Twenty-six of the 51 individual host-parasite links are significant based on either a ParaFit1 or Parafit2 value of P≤0.05. While there was evidence of overall cospeciation, a substantial proportion of specific host-parasite links were non-significant.Overall, both ParaFit and PACo analyses of Bartonella both indicated evidence for overall coevolution with host species. In the New World dataset, global values from both ParaFit and PACo were significant  and 29/38 individual were significant  and 4/13 individual links were significant . For the entire rodent-Bartonella dataset, 94/140 individual host-parasite links were significant based on ParaFit1 values and P≤0.05.Both ParaFit and PACo analyses of Bartonella both also indicated evidence for significant overall coevolution. In the New World dataset, global values from both ParaFit and PACo were significant  and all 20 individual links were significant  and 79/120 individual links were significant . Based on ParaFit1 values, only 1 of 26 individual host-parasite links is significant based on P≤0.05. The separate analyses for the New World and Old World bat hosts with associated Bartonella both also indicated no evidence for overall coevolution. In the New World dataset, global values from both ParaFit and PACo were non-significant  and none of the 19 individual links were significant  and none of the 7 individual links were significant (In contrast to nificant . For thenificant .Leptospira and bat host associations have the greatest number of host switches per parasite (0.731), while Bartonella and rodent host associations have the fewest (0.264). Leptospira and bat host associations also have the greatest number of cospeciations per parasite (0.231), while Bartonella and rodent host associations have the fewest (0.132).Based on a default cost setting, we calculated the optimal number of each type of coevolutionary event, to minimize total cost, for each host-pathogen association . In ordeBartonella had nearly twice as many host switches per parasite in New World (0.474) as compared to Old World bats (0.278). Bartonella in rodents had the opposite trend, with more than twice as many host switches per parasite in Old World (0.339) as compared to New World rodents (0.150). There were also approximately three times as many cospeciation events per parasite for Bartonella in the Old World for both groups of hosts  compared to the New World . For Leptospira, the differences between Old and New World cophylogenetic patterns for both host switches and cospeciations were minimal.We also compared cophylogenetic fit between bacteria and Old World vs. New World host species. Bartonella in New World bats and Old World rodents.We explored a wide-range of cost parameters in order to determine the effect of removing different evolutionary event options from each analysis . IncreasBartonella and both their rodent and bat hosts at a global level, while the relationship between Leptospira and their bat hosts was non-significant. Event-cost results support the global-fit findings, with the rodent-Bartonella and bat-Bartonella associations having the least number of host switches per parasite, which indicates greater evolutionary congruence over time. Co-evolution of bartonellae and their mammalian hosts also remains significant when New and Old World datasets are analyzed separately. The evolutionary pattern in bat hosts is driven mostly by a few strong host-parasite interactions, with 51% of individual associations significant. In comparison, a greater proportion, 67%, of the individual rodent-bacteria associations are significant, indicating stronger coevolutionary interactions throughout these lineages. In fact, in the New World association of rodents and Bartonella, a full 100% of the host-parasite links were significant. In contrast, for Leptospira and their bat hosts, there is only 1 significant individual in analysis of the entire data set, and no significant host-parasite links when the data are analyzed separately as Old vs. New World. We note that the sample sizes for Bartonella in New World rodents and Leptospira in Old World bats are both small, and that the observed patterns could change with the addition of more data. Similarly, the relatively short sequence available of only one gene for both Bartonella and Leptospira may limit the resolution and nodal support for the pathogen phylogenies we obtained. These issues can only be addressed with additional sampling and genetic sequencing to complement these sparse datasets. For example, while our analysis of Bartonella-host relationships was limited by the availability of gltA fragments, the use of multi-gene phylogenies would be a more robust approach given the confounding effect of recombination We found significant coevolutionary congruence between Leptospira and bats. Interestingly, the number of cospeciations per parasite is also the highest for Leptospira and bats, although they also have the highest number of host switches per parasite. Since their overall coevolutionary relationship is nonsignificant, this suggests that for the bat-Leptospira system, coevolutionary relationships are driven mostly strongly by the host switching events rather than cospeciation. Exploring the parameter space of cost structures further supports our findings. For all associations, maximizing the cost of host switching results in the largest overall change in the total cost  and bacterial (blue) disease research in bats (dotted) and rodents (solid) in each year from 1993 to 2012. Data from Web of Science keyword search for all publications from 1993 onwards using combinations of keywords bat OR Chiroptera*, rodent*, bacteria*, virus* OR vira*. Bacterial studies in bats are the most understudied category to date.(DOCX)Click here for additional data file.Table S1gltA GenBank accession numbers for studied Bartonella sequences in bat hosts.(DOCX)Click here for additional data file.Table S2gltA GenBank accession numbers for studied Bartonella sequences in rodent hosts.(DOCX)Click here for additional data file.Table S316S GenBank accession numbers for studied Leptospira sequences in bat hosts.(DOCX)Click here for additional data file.Table S4Cytochrome b GenBank accession numbers of bat species host to studied bacteria.(DOCX)Click here for additional data file.Table S5Cytochrome b GenBank accession numbers of rodent species host to studied Bartonella.(DOCX)Click here for additional data file.Table S6Results from event-based cophylogeny Jane, using different cost-settings.(DOCX)Click here for additional data file.


MTHFR) gene and behaviors related to attention- deficit/hyperactivity disorder (ADHD) in individuals with myelomeningocele. The rationale for the study was twofold: folate metabolizing genes, (e.g. MTHFR), are important not only in the etiology of neural tube defects but are also critical to cognitive function; and individuals with myelomeningocele have an elevated incidence of ADHD. Here, we tested 478 individuals with myelomeningocele for attention-deficit hyperactivity disorder behavior using the Swanson Nolan Achenbach Pelham-IV ADHD rating scale. Myelomeningocele participants in this group for whom DNAs were available were genotyped for seven single nucleotide polymorphisms (SNPs) in the MTHFR gene. The SNPs were evaluated for an association with manifestation of the ADHD phenotype in children with myelomeningocele. The data show that 28.7% of myelomeningocele participants exhibit rating scale elevations consistent with ADHD; of these 70.1% had scores consistent with the predominantly inattentive subtype. In addition, we also show a positive association between the SNP rs4846049 in the 3′-untranslated region of the MTHFR gene and the attention-deficit hyperactivity disorder phenotype in myelomeningocele participants. These results lend further support to the finding that behavior related to ADHD is more prevalent in patients with myelomeningocele than in the general population. These data also indicate the potential importance of the MTHFR gene in the etiology of the ADHD phenotype.The objective of this study was to examine the relation between the 5, 10-methylenetetrahydrofolate reductase ( Spina bifida (SB) is the most common disabling birth defect in North America, with a frequency of ∼3–4 in every 10,000 live births et al. showed similar results Attention deficits in MM individuals have been identified via attention deficit hyperactivity disorder (ADHD) ratings. Children with MM are more likely than controls to show clinically significant elevations on ratings of ADHD  Folic acid is a B vitamin important in relation to MM, as well. Studies show that folic acid supplementation decreases both the occurrence and recurrence of neural tube defects by 72% in seven countries DRD4 is one of the most replicated genes identified to associate with ADHD Folic acid is critical to cellular processes including nucleotide synthesis and methylation. The enzyme, 5, 10-methylenetetrahydrofolate reductase (MTHFR) functions in the pathway that converts folate into metabolites that may be used for cellular processes including methylation of gene promoter enhancers and proteins, RNA, DNA, amino acid and phospholipids synthesis see Figure 1MTHFR have been associated with MM Genetic variants in et al. showed that, relative to controls, individuals with low folate had significantly reduced memory function Several studies link folate/homocysteine levels with cognitive functions. For example, patients with folate deficiencies in the central nervous system exhibit cognitive deficits MTHFR was associated with manifestation of the ADHD behavioral phenotype in children with MM.In this study we tested whether genetic variation in the folate metabolism enzyme et al. MTHFR gene consisted of 262 MM individuals. Fifty percent of these individuals were White and 50% were Hispanic. The sample consisted of 53% females and 47% males and median age was 12.4 years.The participants in this study were an expanded population from that used in Burmeister Parent rating scales for ADHD were also completed on additional patients for whom DNA was not available. These patients were used to compare frequency of positive ADHD test results in MM individuals versus positive ADHD tests in controls. For this comparison, the group sizes were as follows: the MM sample consisted of 478 patients and the control sample consisted of 196 control individuals not affected with MM. Ethnicity of individuals with MM and the control individuals without MM are listed in These experiments were undertaken with the understanding and written consent of each subject abiding by the Code of Ethics of the World Medical Association. The study was approved by the University of Texas Health Science Center at Houston's Institutional Review Board under approval number HSC-MS-00-0001 and The Hospital for Sick Children Research Ethics Board approval number 1000006149.www.adhd.net) rating scale to assess ADHD status. The SNAP-IV scale consists of 18 items, 9 representing behaviors associated with inattention and 9 with hyperactivity-impulsivity. It is designed to align with the criteria in the Diagnostic and Statistical Manual-IV (DSM-IV), widely accepted as a gold standard for diagnosis of ADHD. Parents rated their child's behavior on a four point scale, from zero  to three (very much), as previously described The parents of each participant completed the Swanson Nolan Achenbach Pelham-IV  from the University of California Santa Cruz (UCSC) Genome Browser dbSNP Build132 database as well as the HapMap3 public release #27. SNPs were prioritized for genotyping based on potential function (e.g. if the variant changes the amino acid), gene location, and a minor allele frequency greater than 0.05. A total of 7 SNPs in the MTHFR gene were selected . Genotype calls were performed using the GeneMapper v4.0 software from ABI. For case-control analyses, MM participants with scores consistent with ADHD were defined as affected and were compared to MM participants without evidence of ADHD behavior.p≤0.05 and multiple testing effect was evaluated via permutation of disease status to generate empirical p-values. Linkage disequilibrium (LD) between two SNPs was evaluated using Haploview4.2 and significant LD is concluded with a correlation coefficient (r∧2) ≥0.8. Association of haplotypes of the six SNPs is examined using Haploview4.2 and the significance is evaluated by the 10,000 permutations.Genotype-phenotype association was examined by logistic regression using PLINK Results of ADHD assessment showed that of the 478 MM participants rated, 137 had clinically significant elevations on the SNAP-IV (28.7%). Of the MM participants with scores consistent with ADHD thresholds, the vast majority had elevations on the inattention scale associated with “ADHD Predominantly Inattentive-Type” . Only 17 MM participants had elevations on the hyperactive-impulsive scale (12.4%) and 24 had elevations on both scales (21%). Of the 197 controls not affected by MM, 17 had significant elevations on any one or both of the SNAP-IV scales (8.6%). Of these 17 control individuals, 7 had elevations on inattention scale (38.9%), 3 had elevations on the hyperactive-impulsive scale (16.7%) and 7 had elevations on both scales (38.9%).MTHFR SNPs were evaluated for deviation from Hardy-Weinberg equilibrium (HWE) expectations (p≤0.05). All SNP genotypes were in HWE except rs9651118 in Hispanics (p<0.01), and this SNP was therefore eliminated from further analysis in that group  than in the general population (approximately 8%) MTHFR A1298C allele and ADHD are small, limited and inconclusive. Children affected by ALL are known to have deficits in IQ scores MTHFR is implied to associate with ADHD risk in 11 cases among 48 ALL patients Association studies of the MTHFR transcript in addition to the presence of the thermolabile variants 677C>T and/or 1298A>C. Secondly, analysis of linkage disequilibrium of the reference HapMap CEU population shows that the rs4846049 SNP is in linkage disequilibrium  with the A1298C (rs1801131) (see 2  = 0.634) nor in Hispanics with MM (r∧2  = 0.702) in our MM cohort suggesting the present of complex LD correlations among individuals affected by MM.In our cohort of MM individuals, the C677T and A1298C variants did not associate with the ADHD phenotype, in contrast to the observation reported by Krull et al. 131) see Table 6.MTHFR rs4846049 at the 3′-UTR Mthfr and Mat1a in rat liver epithelial cells MTHFR is unknown. There are two known SNPs (rs45482794 and rs35737219) located 91bp and 145bp respectively upstream to the miR-22 site in the 3′-UTR of MTHFR. Unfortunately, the rare allele frequencies of these two SNPs are too low (∼1 and 3% respectively) to be used in an association study. Further investigations are necessary to verify how individual alleles of rs4846049 affect miR-22 or mir-149 in regulating the expression level of MTHFR.The rare allele T of rs4846049 is demonstrated to have biological function. A recent study of micro-RNA has shown miR-149 inhibiting the expression of the luciferase reporter engineered with the T allele of the et al. showed that there is no difference in level of treatment or treatment revisions, such as hydrocephalus and shunting, between individuals who test positive for ADHD and individuals who do not It seems unlikely that elevated ratings on the SNAP-IV, or other tests for ADHD, are simply related to IQ or severity of disease. Burmeister MTHFR gene variants. A second limitation of the study is the confounding factors present in the mixed ethnic backgrounds of the study participants. For example, the rare allele frequencies of C677T and A1298C are significantly different between Whites and Hispanics  are likely involved in the etiology of ADHD behavior in MM individuals.In summary, this study demonstrated a positive association between the ADHD phenotype in MM individuals and one SNP, rs4846049, in the 3′-UTR of the