Predicting attention-deficit/hyperactivity disorder severity from psychosocial stress and stress-response genes: a random forest regression approach

Accelerometer-based sleep metrics and gut microbiota during adolescence: Association findings from a Brazilian population-based birth cohort

BACKGROUND

Sleep and gut microbiota are emerging putative risk factors for several physical, mental, and cognitive conditions. Sleep deprivation has been shown to be linked with unhealthy microbiome environments in animal studies. However, in humans, the results are mixed. Epidemiological studies evaluating the effect of accelerometer-based sleep measures on gut microbiome are scarce. This study aims to explore the relationship between sleep duration and efficiency with the gut microbiota in adolescence.

METHODS

A subsample of 352 participants from the 2004 Pelotas (Brazil) Birth Cohort Study with sleep and fecal microbiota data available were included in the study. Sleep duration and sleep efficiency were obtained from actigraphy information at 11 years old whereas microbiota information from fecal samples was collected at 12 years. The fecal microbiota was analyzed via Illumina MiSeq (16S rRNA V3-V4 region) and the UNOISE pipeline. Alpha was assessed in QIIME2. Association measures for sleep variables and microbial α-diversity, and bacterial relative abundance were assessed through generalized models (linear and logistic regression), adjusting for maternal and child variables confounders.

RESULTS

Adjusted models showed that sleep duration was positively associated with Simpson index of α-diversity (β = 0.003; CI95 %: 0.00004; 0.01). Both sleep duration (OR = 0.43; CI95 % 0.25; 0.74) and efficiency (OR = 0.55; CI95 % 0.38; 0.78) were associated with lower Bacteroidetes abundance.

CONCLUSION

Our results suggest that sleep duration and efficiency are linked to gut microbiota diversity and composition even with 1-2 years gap from exposure to outcome. The findings support the role of sleep in the gut-brain axis as well as provide insights on how to improve microbiota health.

A novel approach to risk exposure and epigenetics-the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health

BACKGROUND

Each mother-child dyad represents a unique combination of genetic and environmental factors. This constellation of variables impacts the expression of countless genes. Numerous studies have uncovered changes in DNA methylation (DNAm), a form of epigenetic regulation, in offspring related to maternal risk factors. How these changes work together to link maternal-child risks to childhood cardiometabolic and neurocognitive traits remains unknown. This question is a key research priority as such traits predispose to future non-communicable diseases (NCDs). We propose viewing risk and the genome through a multidimensional lens to identify common DNAm patterns shared among diverse risk profiles.

METHODS

We identified multifactorial Maternal Risk Profiles (MRPs) generated from population-based data (n = 15,454, Avon Longitudinal Study of Parents and Children (ALSPAC)). Using cord blood HumanMethylation450 BeadChip data, we identified genome-wide patterns of DNAm that co-vary with these MRPs. We tested the prospective relation of these DNAm patterns (n = 914) to future outcomes using decision tree analysis. We then tested the reproducibility of these patterns in (1) DNAm data at age 7 and 17 years within the same cohort (n = 973 and 974, respectively) and (2) cord DNAm in an independent cohort, the Generation R Study (n = 686).

RESULTS

We identified twenty MRP-related DNAm patterns at birth in ALSPAC. Four were prospectively related to cardiometabolic and/or neurocognitive childhood outcomes. These patterns were replicated in DNAm data from blood collected at later ages. Three of these patterns were externally validated in cord DNAm data in Generation R. Compared to previous literature, DNAm patterns exhibited novel spatial distribution across the genome that intersects with chromatin functional and tissue-specific signatures.

CONCLUSIONS

To our knowledge, we are the first to leverage multifactorial population-wide data to detect patterns of variability in DNAm. This context-based approach decreases biases stemming from overreliance on specific samples or variables. We discovered molecular patterns demonstrating prospective and replicable relations to complex traits. Moreover, results suggest that patterns harbour a genome-wide organisation specific to chromatin regulation and target tissues. These preliminary findings warrant further investigation to better reflect the reality of human context in molecular studies of NCDs.

Assessment of the Genetic Characteristics of a Generation Born during a Long-Term Socioeconomic Crisis

BACKGROUND

A socioeconomic crisis in Russia lasted from 1991 to 1998 and was accompanied by a sharp drop in the birth rate. The main factor that influenced the refusal to have children during this period is thought to be prolonged social stress.

METHODS

comparing frequencies of common gene variants associated with stress-induced diseases among generations born before, after, and during this crisis may show which genes may be preferred under the pressure of natural selection during periods of increased social stress in urban populations.

RESULTS

In the "crisis" group, a statistically significant difference from the other two groups was found in rs6557168 frequency (p = 0.001); rs4522666 was not in the Hardy-Weinberg equilibrium in this group, although its frequency did not show a significant difference from the other groups (p = 0.118). Frequencies of VNTRs in SLC6A3 and MAOA as well as common variants rs17689918 in CRHR1, rs1360780 in FKBP5, rs53576 in OXTR, rs12720071 and rs806377 in CNR1, rs4311 in ACE, rs1800497 in ANKK1, and rs7412 and rs429358 in APOE did not differ among the groups.

CONCLUSIONS

a generation born during a period of prolonged destructive events may differ from the rest of the gene pool of the population in some variants associated with personality traits or stress-related disorders.

Polymorphism of Estrogen Receptor Genes and Its Interactions With Neurodevelopmental Genes in Attention Deficit Hyperactivity Disorder Among Chinese Han Descent

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD) is a polygenic neurodevelopmental disorder with significant gender differences. The sexual dimorphism of ADHD may be associated with estrogen acting through estrogen receptors (ESR). This study investigates the impact of ESR gene polymorphism and its interactions with neurodevelopmental genes on ADHD susceptibility.

METHODS

The study compared genotyping data of single nucleotide polymorphisms in ESR1 and ESR2 in 1,035 ADHD cases and 962 controls. The gene-gene interactions between ESR genes and three neurodevelopmental genes (brain-derived neurotrophic factor [BDNF], synaptosomal-associated protein of 25 kDa gene [SNAP25], and cadherin-13 [CDH13]) in ADHD were investigated using generalized multifactor dimensionality reduction and verified by logistic regression analysis.

RESULTS

The G allele of rs960070/ESR2 (empirical p=0.0076) and the A allele of rs8017441/ESR2 (empirical p=0.0426) were found significantly higher in ADHD cases than in the controls but not in male or female subgroups. Though no difference was found in all subjects or females, the A allele of rs9340817/ESR1 (empirical p=0.0344) was found significantly higher in ADHD cases than controls in males. We also found genetic interaction models between ESR2 gene, neurodevelopmental genes and ADHD susceptibility in males (ESR2 rs960070/BDNF rs6265/BDNF rs2049046/SNAP25 rs362987/CDH13 rs6565113) and females (ESR2 rs960070/BDNF rs6265/BDNF rs2049046) separately, though it was negative in overall subjects.

CONCLUSION

The ESR gene polymorphism associates with ADHD among Chinese Han children, with interactions between ESR genes and neurodevelopmental genes potentially influencing the susceptibility of ADHD.

Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelopmental disorder in children and has a high chance of persisting in adulthood. The development of individualized, efficient, and reliable treatment strategies is limited by the lack of understanding of the underlying neural mechanisms. Diverging and inconsistent findings from existing studies suggest that ADHD may be simultaneously associated with multivariate factors across cognitive, genetic, and biological domains. Machine learning algorithms are more capable of detecting complex interactions between multiple variables than conventional statistical methods. Here we present a narrative review of the existing machine learning studies that have contributed to understanding mechanisms underlying ADHD with a focus on behavioral and neurocognitive problems, neurobiological measures including genetic data, structural magnetic resonance imaging (MRI), task-based and resting-state functional MRI (fMRI), electroencephalogram, and functional near-infrared spectroscopy, and prevention and treatment strategies. Implications of machine learning models in ADHD research are discussed. Although increasing evidence suggests that machine learning has potential in studying ADHD, extra precautions are still required when designing machine learning strategies considering the limitations of interpretability and generalization.

DNA methylation-based age prediction with bloodstains using pyrosequencing and random forest regression

The use of DNA methylation to predict chronological age has shown promising potential for obtaining additional information in forensic investigations. To date, several studies have reported age prediction models based on DNA methylation in body fluids with high DNA content. However, it is often difficult to apply these existing methods in practice due to the low amount of DNA present in stains of body fluids that are part of a trace material. In this study, we present a sensitive and rapid test for age prediction with bloodstains based on pyrosequencing and random forest regression. This assay requires only 0.1 ng of genomic DNA and the entire procedure can be completed within 10 h, making it practical for forensic investigations that require a short turnaround time. We examined the methylation levels of 46 CpG sites from six genes using bloodstain samples from 128 males and 113 females aged 10-79 years. A random forest regression model was then used to construct an age prediction model for males and females separately. The final age prediction models were developed with seven CpG sites (three for males and four for females) based on the performance of the random forest regression. The mean absolute deviation was less than 3 years for each model. Our results demonstrate that DNA methylation-based age prediction using pyrosequencing and random forest regression has potential applications in forensics to accurately predict the biological age of a bloodstain donor.

Evaluation of the Regulatory Role of Circadian Rhythm Related Long Non-Coding RNAs in ADHD Etiogenesis

OBJECTIVE

ADHD is associated with increased sleep problems and circadian rhythm disturbances. This study aimed to examine ADHD patients and healthy controls in terms of chronotypic features and expression levels of CLOCK, PER1, lncRNA HULC, lncRNA UCA1.

METHOD

Eighty-three children were included (43 ADHD). Conner's Parent Rating Scale-Revised Short Form, Childhood Chronotype Questionnaire, Children's Sleep Disorders Scale were administered. Gene expression levels were studied from peripheral blood.

RESULTS

Evening chronotype, sleep initiation/maintenance disorder, sleep-wake transition disorder, excessive sleepiness disorder were higher in the ADHD group compared to the controls in the scales reported by the parents. Expression levels of all examined genes were statistically significantly higher in the ADHD group. There was no significant relationship between genes and sleep parameters in the ADHD group.

CONCLUSION

Our study provides the first evidence that lncRNA HULC and lncRNA UCA1 might have a role in the etiology of ADHD.

Machine learning identifies prominent factors associated with cardiovascular disease: findings from two million adults in the Kashgar Prospective Cohort Study (KPCS)

BACKGROUND

Identifying factors associated with cardiovascular disease (CVD) is critical for its prevention, but this topic is scarcely investigated in Kashgar prefecture, Xinjiang, northwestern China. We thus explored the CVD epidemiology and identified prominent factors associated with CVD in this region.

METHODS

A total of 1,887,710 adults at baseline (in 2017) of the Kashgar Prospective Cohort Study were included in the analysis. Sixteen candidate factors, including seven demographic factors, 4 lifestyle factors, and 5 clinical factors, were collected from a questionnaire and health examination records. CVD was defined according to International Clinical Diagnosis (ICD-10) codes. We first used logistic regression models to investigate the association between each of the candidate factors and CVD. Then, we employed 3 machine learning methods-Random Forest, Random Ferns, and Extreme Gradient Boosting-to rank and identify prominent factors associated with CVD. Stratification analyses by sex, ethnicity, education level, economic status, and residential setting were also performed to test the consistency of the ranking.

RESULTS

The prevalence of CVD in Kashgar prefecture was 8.1%. All the 16 candidate factors were confirmed to be significantly associated with CVD (odds ratios ranged from 1.03 to 2.99, all p values < 0.05) in logistic regression models. Further machine learning-based analysis suggested that age, occupation, hypertension, exercise frequency, and dietary pattern were the five most prominent factors associated with CVD. The ranking of relative importance for prominent factors in stratification analyses showed that the factor importance generally followed the same pattern as that in the overall sample.

CONCLUSIONS

CVD is a major public health concern in Kashgar prefecture. Age, occupation, hypertension, exercise frequency, and dietary pattern might be the prominent factors associated with CVD in this region.In the future, these factors should be given priority in preventing CVD in future.

Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives

Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other 'omics data, and mapping of effects from gene to brain to behavior across the lifespan.

Childhood trauma in adults with ADHD is associated with comorbid anxiety disorders and functional impairment

BACKGROUND

Child and adolescent psychological trauma exposure is associated with psychopathology in the adult population in general, but literature on childhood trauma (CT) in adults with ADHD is scarce.

AIMS

To determine the prevalence of CT among adult patients with ADHD, and whether a history of CT implies different adult outcomes of psychiatric comorbidities, and functional impairment than without.

METHOD

Previously unmedicated adult outpatients with ADHD (n = 250, median age 32 years) entered the study. Participants were diagnosed with ADHD using the Diagnostic Interview for ADHD in Adults, second edition (DIVA 2.0), and were assessed by historical data, validated questionnaires, and structured clinical interviews for CT and mental disorders including post-traumatic stress disorder (PTSD) and functional impairment. Analyses compared ADHD patients with and without CT.

RESULTS

Prevalence of CT was 44%. Of those with PTSD (n = 21), many had CT (85%, p < 0.001). In binary logistic regression analyses, CT was linked to an increased likelihood of concomitant panic disorder (unadjusted odds ratio, OR = 3.0, p < 0.001, and adjusted OR = 2.7, p < 0.01) and any anxiety disorders and two or more comorbid psychiatric disorders (adjusted OR = 1.9, p < 0.05 and OR = 1.7, p < 0.05, respectively), and was associated with significant functional impairment.

CONCLUSIONS

These findings suggest that awareness of child and adolescent trauma is clinically relevant among young to middle-aged adult ADHD patients, and implications for earlier detection of CT and treatment warrant further studies.

The effects of persistent sleep disturbances during early childhood over adolescent ADHD, and the mediating effect of attention-related executive functions: Data from the 2004 Pelotas Birth Cohort

OBJECTIVE

Investigate effects of persistent sleep disturbances during early childhood over ADHD during the adolescence, and the potential attention-related executive functions mediating this effect.

METHODS

We used data from the 2004 Pelotas Birth Cohort. Children's Sleep disturbances were reported by their mothers at 12, 24, and 48 months of age, whereas the Test-of-Everyday-Attention-for-Children (TEA-Ch) and the Development and Well Being Assessment (DAWBA) were applied at 11 years of age to evaluate attention-related executive functions and ADHD, respectively. Persistent sleep problems were defined as reporting have two or more points of difficulty to sleep, nightmares, restless sleeps, and/or <10h/24h sleep duration. Logistic regression and mediation models were used, adjusting for maternal and child sociodemographic, behavior and health related variables.

RESULTS

The highest prevalence of adolescent ADHD (15.4%) was on the group who reported having nightmares at 2,4 and 6 years. In adjusted models, we observed an odd of ADHD in the adolescence 2.26 higher in those who reported persistent nightmares (CI95% 1.33, 4.01) compared to those reported transitory or no nightmares. Persistent difficulty to sleep (OR=1.74 CI95% 1.13, 2.66) and restless sleep (OR=1.80, CI95% 1.23, 2.64) during childhood also increased ADHD odds at 11 years. No indirect effect through attention related executive functions was found using mediating models.

DISCUSSION

Persistent early sleep disturbances may increase odds of ADHD among adolescents and could be consider as early marker of such disorder, specially nightmares problems. These effects were not mediated by attention-related executive functions. Nevertheless, we had 75% of cohort inception response.

The role of glucocorticoid receptor gene in the association between attention deficit-hyperactivity disorder and smaller brain structures

ADHD is associated with smaller subcortical brain volumes and cortical surface area, with greater effects observed in children than adults. It is also associated with dysregulation of the HPA axis. Considering the effects of the glucocorticoid receptor (NR3C1) in neurophysiology, we hypothesize that the blurred relationships between brain structures and ADHD in adults could be partly explained by NR3C1 gene variation. Structural T1-weighted images were acquired on a 3 T scanner (N = 166). Large-scale genotyping was performed, and it was followed by quality control and pruning procedures, which resulted in 48 independent NR3C1 gene variants analyzed. After a stringent Bonferroni correction, two SNPs (rs2398631 and rs72801070) moderated the association between ADHD and accumbens and amygdala volumes in adults. The significant SNPs that interacted with ADHD appear to have a role in gene expression regulation, and they are in linkage disequilibrium with NR3C1 variants that present well-characterized physiological functions. The literature-reported associations of ADHD with accumbens and amygdala were only observed for specific NR3C1 genotypes. Our findings reinforce the influence of the NR3C1 gene on subcortical volumes and ADHD. They suggest a genetic modulation of the effects of a pivotal HPA axis component in the neuroanatomical features of ADHD.

Evolutionary conservations, changes of circadian rhythms and their effect on circadian disturbances and therapeutic approaches

The circadian rhythm is essential for the interaction of all living organisms with their environments. Several processes, such as thermoregulation, metabolism, cognition and memory, are regulated by the internal clock. Disturbances in the circadian rhythm have been shown to lead to the development of neuropsychiatric disorders, including attention-deficit hyperactivity disorder (ADHD). Interestingly, the mechanism of the circadian rhythms has been conserved in many different species, and misalignment between circadian rhythms and the environment results in evolutionary regression and lifespan reduction. This review summarises the conserved mechanism of the internal clock and its major interspecies differences. In addition, it focuses on effects the circadian rhythm disturbances, especially in cases of ADHD, and describes the possibility of recombinant proteins generated by eukaryotic expression systems as therapeutic agents as well as CRISPR/Cas9 technology as a potential tool for research and therapy. The aim is to give an overview about the evolutionary conserved mechanism as well as the changes of the circadian clock. Furthermore, current knowledge about circadian rhythm disturbances and therapeutic approaches is discussed.

Mapping relationships between ADHD genetic liability, stressful life events, and ADHD symptoms in healthy adults

Attention-deficit/hyperactivity disorder (ADHD) symptoms are continuously distributed in the general population, where both genetic and environmental factors play roles. Stressful life events (SLEs) have been associated with ADHD diagnosis, but the relationship between ADHD genetic liability, SLEs, and ADHD symptoms in healthy individuals is less clear. Using a sample of 1,531 healthy adults (average age 26.9 years; 55.8% female), we investigated relationships between ADHD polygenic risk scores (ADHD-PRSs), SLEs, and ADHD symptoms in a general population sample. Confirming earlier findings in an overlapping sample, all SLE-measures assessed (lifetime SLEs, recent SLEs, and childhood trauma (CT)) were significantly correlated with total ADHD, inattention (IA), and hyperactivity-impulsivity (HI) scores (r² range = .08-.15; all p < .005). ADHD-PRSs was associated with HI (R²_best-fit  = .37%), lifetime SLEs (R²_best-fit  = .56%), and CT (R²_best-fit  = .40%). Mediation analyses showed that lifetime SLEs partially mediated the association between ADHD-PRSs and HI (indirect effect: β = 68.6, bias corrected accelerated 95% confident interval (BCa95%CI) [11.9, 131.0], p = .016, proportion mediated (P_M ) =19.5%), with strongest effects contributed by CT (β = 34.4, BCa95%CI [0.4, 76.5], p = .040, P_M  = 9.8%). On the other hand, HI partially mediated the association between the ADHD-PRSs and lifetime SLEs (β = 42.9, BCa95%CI [7.3, 83.9], p = .014, P_M  = 18.8%). Our study observed a complex relationship of genetic and environmental risk factors contributing to ADHD symptoms in the healthy adult population.

Intermediate lengths of the C9ORF72 hexanucleotide repeat expansion may synergistically contribute to attention deficit hyperactivity disorder in child and his father: case report

We have summarized the abstract section as follows: "We report a son and his father affected by Attention Deficit Hyperactivity Disorder (ADHD). They belonged to a larger cohort (116 ADHD children, 20 related parents, 77 controls) wholly genotyped forC9ORF72 expansion. Ten ADHD susceptibility genes were further investigated in the family. We revealed that son and father shared an intermediateC9ORF72 expansion and common variants inCDH23, ITGAE and MTRR. Bioinformatics highlighted aC9ORF72-MTRR interaction. This case-report underlines that in relatives with ADHD, carrying variants in ADHD susceptibility genes, the intermediateC9ORF72 repeats might have a potentially pathogenetic synergistic effect, supporting the multifactorial polygenic aetiopathogenetic profile of disease".

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques

The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potential risk factors: genetics, dietary and physical activity habits, socio-economic environment, lifestyle, etc. In addition, all these factors are expected to exert their influence through a specific and especially convoluted way during childhood, given the fast growth along this period. Machine Learning methods are the appropriate tools to model this complexity, given their ability to cope with high-dimensional, non-linear data. Here, we have analyzed by Machine Learning a sample of 221 children (6–9 years) from Madrid, Spain. Both Random Forest and Gradient Boosting Machine models have been derived to predict the body mass index from a wide set of 190 multidomain variables (including age, sex, genetic polymorphisms, lifestyle, socio-economic, diet, exercise, and gestation ones). A consensus relative importance of the predictors has been estimated through variable importance measures, implemented robustly through an iterative process that included permutation and multiple imputation. We expect this analysis will help to shed light on the most important variables associated to childhood obesity, in order to choose better treatments for its prevention.

Effects of maternal immune activation in porcine transcript isoforms of neuropeptide and receptor genes

The prolonged effects of maternal immune activation in response stressors during gestation on the offspring's molecular pathways after birth are beginning to be understood. An association between maternal immune activation and neurodevelopmental and behavior disorders such as autism and schizophrenia spectrum disorders has been detected in long-term gene dysregulation. The incidence of alternative splicing among neuropeptides and neuropeptide receptor genes, critical cell-cell signaling molecules, associated with behavior may compromise the replicability of reported maternal immune activation effects at the gene level. This study aims to advance the understanding of the effect of maternal immune activation on transcript isoforms of the neuropeptide system (including neuropeptide, receptor and connecting pathway genes) underlying behavior disorders later in life. Recognizing the wide range of bioactive peptides and functional receptors stemming from alternative splicing, we studied the effects of maternal immune activation at the transcript isoform level on the hippocampus and amygdala of three-week-old pigs exposed to maternal immune activation due to viral infection during gestation. In the hippocampus and amygdala, 29 and 9 transcript isoforms, respectively, had maternal immune activation effects (P-value < 0.01). We demonstrated that the study of the effect of maternal immune activation on neuropeptide systems at the isoform level is necessary to expose opposite effects among transcript isoforms from the same gene. Genes were maternal immune activation effects have also been associated with neurodevelopmental and behavior disorders. The characterization of maternal immune activation effects at the transcript isoform level advances the understanding of neurodevelopmental disorders and identifies precise therapeutic targets.

Use of machine learning to classify adult ADHD and other conditions based on the Conners' Adult ADHD Rating Scales

A reliable diagnosis of adult Attention Deficit/Hyperactivity Disorder (ADHD) is challenging as many of the symptoms of ADHD resemble symptoms of other disorders. ADHD is associated with gambling disorder and obesity, showing overlaps of about 20% with each diagnosis. It is important for clinical practice to differentiate between conditions displaying similar symptoms via established diagnostic instruments. Applying the LightGBM algorithm in machine learning, we were able to differentiate subjects with ADHD, obesity, problematic gambling, and a control group using all 26 items of the Conners' Adult ADHD Rating Scales (CAARS-S: S) with a global accuracy of .80; precision (positive predictive value) ranged between .78 (gambling) and .92 (obesity), recall (sensitivity) between .58 for obesity and .87 for ADHD. Models with the best 5 and best 10 items resulted in less satisfactory fits. The CAARS-S seems to be a promising instrument to be applied in clinical practice also for multiclassifying disorders displaying symptoms resembling ADHD.

Effects of natural and socioeconomic factors on dengue transmission in two cities of China from 2006 to 2017

Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, in China, DF still poses an increasing threat to public health in many cities; but the incidence shows significant spatiotemporal differences. The purpose of this study was to identify the key factors affecting the spatial and temporal distribution of DF. We collected natural environmental and socio-economic data for two adjacent cities, Guangzhou (73 variables) and Foshan (71 variables), with the most DF cases in China. We performed random forest modelling to rank the factors according to their level of importance, and used negative binomial regression analysis to compare the risk factors between outbreak years and non-outbreak years. The natural environmental factors contributing to DF incidence for Guangzhou were temperature (relative risk (RR) = 18.80, 95% confidence interval (CI) = 3.11-113.67), humidity (RR = 1.85, 95% CI = 1.17-2.90) and green area (RR = 12.11, 95% CI = 6.14-55.50), and for Foshan was forest coverage (RR = 5.83, 95% CI = 2.72-12.45). Socio-economic impact were shown in Guangzhou with foreign visitor (RR = 1.18, 95% CI = 1.05-1.34) and oversea air passenger transport (RR = 7.34, 95% CI = 2.26-23.86); in Foshan, with oversea tourism (RR = 1.65, 95% CI = 1.34-2.04); and in Guangzhou-Foshan, with the development of intercity metro (RR = 1.26, 95% CI = 1.10-1.44). The difference between the two cities was the greater impact of the foreign visitor, green spaces and climate factor on DF in Guangzhou; the impact of the construction of intercity metro; and the more significant impact of oversea tourism on DF in Foshan. Our results suggest meaningful clues to public health authorities implementing joint interventions on DF prevention and early warning, to increase health education on DF prevention for international visitors and oversea travelers, and cross-city metro passengers; using rapid body temperature detection in public places such as airports, metros and parks can help detect cases early.

Challenges in ADHD care for ethnic minority children: A review of the current literature

While attention deficit hyperactivity disorder (ADHD) has been extensively studied in the past decades, the role of social and cultural practices in its assessment, diagnosis, and treatment has been often overlooked. This selective review provides an overview of research that explores social and cultural influences on help-seeking behavior in ethnic minority children with ADHD. Studies were selected that address cultural diversity in three areas of ADHD help-seeking: problem recognition, access to mental health services, and treatment. Special attention was given to studies of treatment selection and adherence in minority groups. Findings suggested that cultural disparities in ADHD care among ethnic minority children occur in the early stages of problem recognition, through service selection, and in the quality of treatment. Ethnic minority children were less likely than their nonminority counterparts to be diagnosed with ADHD and its comorbid conditions and less likely to be prescribed and adhere to stimulant drug treatment. These differences reflect cultural diversity in norms and attitudes towards mental health issues (e.g., fear of social stigma) as well as limited access to qualified health care. Paradoxically, cultural, racial, and language bias may also lead to the overidentification of ethnic minority children as disabled and to higher ratings of ADHD symptoms. This review highlights the importance of sociocultural factors in understanding developmental psychopathology and help-seeking behavior. In addition, it further supports calls for increasing cultural competence in communications during clinical assessment, diagnosis, and treatment in minority communities. Clinical, theoretical, and methodological considerations for future research are discussed.

ADHD 24/7: Circadian clock genes, chronotherapy and sleep/wake cycle insufficiencies in ADHD

Objectives: The current paper addresses the evidence for circadian clock characteristics associated with attention-deficit hyperactivity disorder (ADHD), and possible therapeutic approaches based on chronomodulation through bright light (BL) therapy.Methods: We review the data reported in ADHD on genetic risk factors for phase-delayed circadian rhythms and on the role of photic input in circadian re-alignment.Results: Single nucleotide polymorphisms in circadian genes were recently associated with core ADHD symptoms, increased evening-orientation and frequent sleep problems. Additionally, alterations in exposure and response to photic input may underlie circadian problems in ADHD. BL therapy was shown to be effective for re-alignment of circadian physiology toward morningness, reducing sleep disturbances and bringing overall improvement in ADHD symptoms. The susceptibility of the circadian system to phase shift by timed BL exposure may have broad cost-effective potential implications for the treatment of ADHD.Conclusions: We conclude that further research of circadian function in ADHD should focus on detection of genetic markers (e.g., using human skin fibroblasts) and development of BL-based therapeutic interventions.

Genetic Intersections of Language and Neuropsychiatric Conditions

PURPOSE OF REVIEW

To better understand the shared basis of language and mental health, this review examines the behavioral and neurobiological features of aberrant language in five major neuropsychiatric conditions. Special attention is paid to genes implicated in both language and neuropsychiatric disorders, as they reveal biological domains likely to underpin the processes controlling both.

RECENT FINDINGS

Abnormal language and communication are common manifestations of neuropsychiatric conditions, and children with impaired language are more likely to develop psychiatric disorders than their peers. Major themes in the genetics of both language and psychiatry include master transcriptional regulators, like FOXP2; key developmental regulators, like AUTS2; and mediators of neurotransmission, like GRIN2A and CACNA1C.

Predicting post-experiment fatigue among healthy young adults: Random forest regression analysis

The current study utilized a random forest regression analysis to predict post-experiment fatigue in a sample of 212 healthy participants (mean age = 20.5, SD = 2.21; 52% women) between the ages of 18 and 30 following a mildly stressful experiment. We used a total of 30 features of demographic variables, lifestyle variables, alcohol and other drug use behaviors and problems, state anxiety and depressive symptoms, and physiological indicators that were lab assessed or self-reported. A random forest regression analysis with 10-fold cross-validation resulted in accurate prediction of post-experiment fatigue (R² equivalent = 0.93) with the average "out-of-bag" (OOB) R² = 0.52. Not surprisingly, self-reported pre-experiment fatigue was the most important variable (54%) in the prediction of post-experiment fatigue. Feeling anxious (state anxiety) pre- and post-experiment (3%, 7%), feeling less vigorous post experiment (3%), systolic and diastolic blood pressure (3%, 2%) and LF HRV (2%) assessed at baseline, and self-reported alcohol-related problems (3%) and sleep (2%) additionally contributed to the prediction of post-experiment fatigue. Other remaining input variables had relatively minimal importance. Substantively, this study suggests that complex interactions across multiple systems domains that support regulation may be linked to fatigue. A random forest regression analysis can relatively easily be implemented with a built-in cross-validation function and reveal a web of connections undergirding health behavior and risks.

A Neurodevelopmental Model of Combined Pyrethroid and Chronic Stress Exposure

Attention-deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood and previous studies indicate the dopamine system plays a major role in ADHD pathogenesis. Two environmental exposures independently associated with dopaminergic dysfunction and ADHD risk include exposure to deltamethrin, a pyrethroid insecticide, and chronic stress. We hypothesized that combined neurodevelopmental exposure to both deltamethrin and corticosterone (CORT), the major stress hormone in rodents, would result in additive changes within the dopamine system. To study this, we developed a novel dual exposure paradigm and exposed pregnant C57BL/6 dams to 3 mg/kg deltamethrin through gestation and weaning, and their offspring to 25 μg/mL CORT dissolved in the drinking water through adulthood. Midbrain RNA expression as well as striatal and cortical protein expression of key dopaminergic components were investigated, in addition to ADHD-like behavioral tasks and electrochemical dopamine dynamics via fast-scan cyclic voltammetry. Given the well-described sexual dimorphism of ADHD, males and females were assessed separately. Males exposed to deltamethrin had significantly decreased midbrain Pitx3 expression, decreased cortical tyrosine hydroxylase (TH) expression, increased activity in the Y maze, and increased dopamine uptake rate in the dorsal striatum. These effects did not occur in males exposed to CORT only, or in males exposed to both deltamethrin and CORT, suggesting that CORT may attenuate these effects. Additionally, deltamethrin- and CORT-exposed females did not display these dopaminergic features, which indicates these changes are sex-specific. Our results show dopaminergic changes from the RNA through the functional level. Moreover, these data illustrate the importance of testing multiple environmental exposures together to better understand how combined exposures that occur in certain vulnerable populations could affect similar neurodevelopmental systems, as well as the importance of studying sex differences of these alterations.