Relative Age Effects on Attention-Deficit/Hyperactivity Disorder Symptoms and Educational Achievement:A Longitudinal UK Cohort Study

ObjectiveBeing among the youngest in a school class increases the risk for worse educational outcomes and attention-deficit/hyperactivity disorder (ADHD) symptoms, but questions remain about the nature and persistence of such effects. We investigated this “relative age effect” on educational achievement at age 15 to 16 years and on ADHD symptoms from age 7 to age 21 years. Furthermore, we examined whether being young-in-class is linked to a greater reduction in ADHD symptoms from childhood to adulthood and a lower genetic propensity to ADHD.MethodWe identified 3,928 young-in-class and 4,580 old-in-class participants from the Twins’ Early Development Study. Educational achievement was measured with mathematics and English examination grades at age 15 to 16 years, and ADHD symptoms were measured using 2 different scales and different raters, from age 7 to 21 years, with effects tested using regression.ResultsA relative age effect emerged for English but not mathematics examination grades, and for the majority of parent and teacher ratings on ADHD symptoms, most consistently in middle childhood. Being young-in-class was associated with a greater reduction in parent-rated ADHD symptoms from childhood to adulthood when measured with a brief scale, but the comparable result from a longer scale was non-significant (after multiple testing correction). No interaction emerged between relative age and ADHD polygenic scores.ConclusionOur results emphasise the need to improve support for the children who start school younger than most, and to ensure that developmental comparisons take children’s precise age into account. Future research would benefit from in-depth analyses of individual trajectories and their variability among the young-in-class children.</div

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

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large‐scale studies. In response, we used cross‐sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to infer age‐related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta‐analysis and one‐way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes

Tietopaketti koirien ja kissojen hammashoidoista ja suukirurgiasta

E-kirjan kopiointi ja tulostus on estetty teknisen suojauksen avull

Predicting ovulation in the mare on the basis of follicular growth and serum oestrone sulphate and progesterone levels

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Radiographic outcome of root canal treatment of canine teeth in cats: 32 cases (1998-2016).

OBJECTIVE To describe the radiographic outcome of root canal treatment (RCT) of canine teeth of cats. DESIGN Retrospective case series. ANIMALS 32 cats with 37 canine teeth with complicated crown fractures that underwent RCT. PROCEDURES Medical record databases of 5 referral veterinary hospitals were searched to identify cats that underwent RCT between 1998 and 2016. Only cats that had at least 1 follow-up examination during which radiographs were obtained of the treated canine tooth or teeth were included in the study. Dental radiographs obtained before and immediately after RCT and during all follow-up examinations were reviewed. Treatment was considered successful if the periodontal ligament space was within reference limits and preoperative external inflammatory root resorption (EIRR), if present, had stabilized. Treatment was considered to have no evidence of failure if preoperative EIRR had stabilized and preexisting periapical lucency was stable or decreased in size but had not resolved. Treatment was considered to have failed if periapical lucency or EIRR developed subsequent to RCT or preexisting periapical lucency increased in size or preoperative EIRR progressed following RCT. RESULTS Follow-up time after RCT ranged from 3 to 72 months. The RCT was successful for 18 (49%) of the 37 treated teeth, had no evidence of failure for 12 (32%), and failed for 7 (19%). Preexisting EIRR and patient age ≥ 5 years significantly increased the rate of RCT failure. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that RCT was a viable treatment option to salvage endodontically diseased canine teeth in cats