ADHD characteristics: I. Concurrent co-morbidity patterns in children & adolescents

<p>Abstract</p> <p>Objective</p> <p>342 Caucasian subjects with attention deficit/hyperactivity disorder (ADHD) were recruited from pediatric and behavioral health clinics for a genetic study. Concurrent comorbidity was assessed to characterize the clinical profile of this cohort.</p> <p>Methods</p> <p>Subjects 6 to 18 years were diagnosed with the Schedule for Affective Disorders & Schizophrenia for School aged Children (K-SADS-P IVR).</p> <p>Results</p> <p>The most prevalent diagnoses co-occurring with ADHD were Oppositional Defiant Disorder (ODD) (40.6%), Minor Depression/Dysthymia (MDDD) (21.6%), and Generalized Anxiety Disorder (GAD) (15.2%). In Inattentive ADHD (n = 106), 20.8% had MDDD, 20.8% ODD, and 18.6% GAD; in Hyperactive ADHD (n = 31) 41.9% had ODD, 22.2% GAD, and 19.4% MDDD. In Combined ADHD, (n = 203), 50.7% had ODD, 22.7% MDDD and 12.4% GAD. MDDD and GAD were equally prevalent in the ADHD subtypes but, ODD was significantly more common among Combined and Hyperactive ADHD compared to Inattentive ADHD. The data suggested a subsample of Irritable prepubertal children exhibiting a diagnostic triad of ODD, Combined ADHD, and MDDD may account for the over diagnosing of Bipolar Disorder.</p> <p>Conclusion</p> <p>Almost 2/3^rdof ADHD children have impairing comorbid diagnoses; Hyperactive ADHD represents less than 10% of an ADHD sample; ODD is primarily associated with Hyperactive and Combined ADHD; and, MDDD may be a significant morbidity for ADHD youths from clinical samples.</p

Clinical Management of Pediatric Acute-Onset Neuropsychiatric Syndrome: Part I—Psychiatric and Behavioral Interventions

Abstract Objective: This article outlines the consensus guidelines for symptomatic treatment for children with Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS) and Pediatric Autoimmune Neuropsychiatric Syndrome Associated with Streptococcal Infection (PANDAS). Methods: Extant literature on behavioral, psychotherapeutic, and psychopharmacologic treatments for PANS and PANDAS was reviewed. Members of the PANS Research Consortium pooled their clinical experiences to find agreement on treatment of PANS and PANDAS symptoms. Results: Current guidelines result from consensus among the Consortium members. Conclusion: While underlying infectious and inflammatory processes in PANS and PANDAS patients are treated, psychiatric and behavioral symptoms need simultaneous treatment to decrease suffering and improve adherence to therapeutic intervention. Psychological, behavioral, and psychopharmacologic interventions tailored to each child's presentation can provide symptom improvement and improve functioning during both the acute and chronic stages of illness. In general, typical evidence-based interventions are appropriate for the varied symptoms of PANS and PANDAS. Individual differences in expected response to psychotropic medication may require marked reduction of initial treatment dose. Antimicrobials and immunomodulatory therapies may be indicated, as discussed in Parts 2 and 3 of this guideline series

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Metabolic profiling stratifies colorectal cancer and reveals adenosylhomocysteinase as a therapeutic target

The genomic landscape of colorectal cancer (CRC) is shaped by inactivating mutations in tumour suppressors such as APC, and oncogenic mutations such as mutant KRAS. Here we used genetically engineered mouse models, and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that untargeted metabolic profiling can be applied to stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-deficient CRC. Loss of Apc in the mouse intestine was found to be sufficient to drive expression of one of its enzymes, adenosylhomocysteinase (AHCY), which was also found to be transcriptionally upregulated in human CRC. Targeting of AHCY function impaired growth of APC-deficient organoids in vitro, and prevented the characteristic hyperproliferative/crypt progenitor phenotype driven by acute deletion of Apc in vivo, even in the context of mutant Kras. Finally, pharmacological inhibition of AHCY reduced intestinal tumour burden in ApcMin/+ mice indicating its potential as a metabolic drug target in CRC

A genetic investigation of sex bias in the prevalence of attention-deficit/hyperactivity disorder

Background Attention-deficit/hyperactivity disorder (ADHD) shows substantial heritability and is 2-7 times more common in males than females. We examined two putative genetic mechanisms underlying this sex bias: sex-specific heterogeneity and higher burden of risk in female cases. Methods We analyzed genome-wide autosomal common variants from the Psychiatric Genomics Consortium and iPSYCH Project (20,183 cases, 35,191 controls) and Swedish populationregister data (N=77,905 cases, N=1,874,637 population controls). Results Genetic correlation analyses using two methods suggested near complete sharing of common variant effects across sexes, with rg estimates close to 1. Analyses of population data, however, indicated that females with ADHD may be at especially high risk of certain comorbid developmental conditions (i.e. autism spectrum disorder and congenital malformations), potentially indicating some clinical and etiological heterogeneity. Polygenic risk score (PRS) analysis did not support a higher burden of ADHD common risk variants in female cases (OR=1.02 [0.98-1.06], p=0.28). In contrast, epidemiological sibling analyses revealed that the siblings of females with ADHD are at higher familial risk of ADHD than siblings of affected males (OR=1.14, [95% CI: 1.11-1.18], p=1.5E-15). Conclusions Overall, this study supports a greater familial burden of risk in females with ADHD and some clinical and etiological heterogeneity, based on epidemiological analyses. However, molecular genetic analyses suggest that autosomal common variants largely do not explain the sex bias in ADHD prevalence

Optimization Frameworks for the Design, Synthesis, Supply Chain, and Strategic Planning of Novel Hybrid Energy Processes

Increasing demand for transportation fuels in the United States and efforts to reduce reliance on petroleum imports put pressure on the development of domestic energy sources such as coal, biomass, and natural gas. Coal and natural gas have lower costs than biomass, but biomass can reduce the greenhouse gas emissions during cultivation. Hybrid energy systems that synergistically combine these feedstocks can yield competitive economic and environmental performance with petroleum-based processes. This research develops frameworks for the design, synthesis, supply chain, and strategic planning of novel hybrid energy systems using mathematical modeling and optimization approaches. The developed process thermochemically converts coal, biomass, and natural gas to gasoline, diesel, and kerosene (CBGTL). The optimization framework is developed on two levels, the design of a stand-alone refinery and the identification of an optimal supply chain network. The conceptual design of the CBGTL process is first simulated, integrated and economically evaluated. In a process synthesis framework, the design is expanded into a superstructure that includes multiple technologies and the topology is optimized to give the lowest overall cost of fuel production. Simultaneous heat, power, and water integration is incorporated into the model and a rigorous deterministic global optimization strategy is applied to guarantee valid lower and upper bounds on the optimal solution. Given the individually optimized refineries, a supply chain framework is developed to identify the optimal locations and capacities for the refineries with respect to the the feedstocks, demand, water resources, electricity requirement, and CO2 sequestration profiles, to replace petroleum fuels in the United States. The framework can be applied to single feedstock energy supply chains, adapted for a ranking methodology, and solved for various geographical scopes. A multi period strategic planning model is also developed for the supply chain problem. On both the single plant and supply chain level, solutions from the models elucidate economic and environmental trade-offs between multiple scenarios. Results suggest that high quality fuels from domestic sources can be produced in an economically competitive manner compared to petroleum fuels, with better environmental performances (i.e., lower life cycle emissions) when biomass is included