Inherited risk for autism through maternal and paternal lineage

BACKGROUND: Autism spectrum disorder (ASD) is highly familial, with a positively skewed male-to-female ratio that is purported to arise from the so-called female protective effect. A serious implication of a female protective effect is that familial ASD liability would be expected to aggregate asymptomatically in sisters of affected probands, who would incur elevated rates of ASD among their offspring. Currently, there exist no data on second-generation recurrence rates among families affected by ASD. METHODS: We analyzed data from the Swedish National Patient Register and the Multi-Generation Register for a cohort of children born between 2003 and 2012. ASD was ascertained in both the child and parental generations. RESULTS: Among 847,732 children, 13,103 (1.55%) children in the cohort were diagnosed with ASD. Among their maternal/paternal aunts and uncles, 1744 (0.24%) and 1374 (0.18%) were diagnosed with ASD, respectively. Offspring of mothers with a sibling(s) diagnosed with ASD had higher rates of ASD than the general population (relative risk, 3.05; 95% confidence interval, 2.52-3.64), but not more than would be predicted for second-degree relatives within a generation, and only slightly more than was observed for fathers with siblings with ASD (relative risk, 2.08; 95% confidence interval, 1.53-2.67). Models adjusting for temporal trends and for psychiatric history in the parental generation did not alter the results. CONCLUSIONS: These findings establish a robust general estimate of ASD transmission risk for siblings of individuals affected by ASD, the first ever reported. Our findings do not suggest female protective factors as the principal mechanism underlying the male sex bias in ASD

Recurrence Risk of Autism in Siblings and Cousins: A Multinational, Population-Based Study

Objective:Familial recurrence risk is an important population-level measure of the combined genetic and shared familial liability of autism spectrumdisorder (ASD). Objectives were to estimate ASD recurrence risk among siblings and cousins by varying degree of relatedness and by sex.Method:This is a population-based cohort study of livebirths from 1998 to 2007 in California, Denmark, Finland, Israel, Sweden and WesternAustralia followed through 2011 to 2015. Subjects were monitored for an ASD diagnosis in their older siblings or cousins (exposure) and for their ASDdiagnosis (outcome). The relative recurrence risk was estimated for different sibling and cousin pairs, for each site separately and combined, and by sex.Results:During follow-up, 29,998 cases of ASD were observed among the 2,551,918 births used to estimate recurrence in ASD and 33,769 cases ofchildhood autism (CA) were observed among the 6,110,942 births used to estimate CA recurrence. Compared with the risk in unaffected families, therewas an 8.4-fold increase in the risk of ASD following an older sibling with ASD and a 17.4-fold increase in the risk of CA following an older sibling withCA. A 2-fold increase in the risk for cousin recurrence was observed for the 2 disorders. There also was a significant difference in sibling ASD recurrencerisk by sex.Conclusion:The present estimates of relative recurrence risks for ASD and CA will assist clinicians and families in understanding autism risk in thecontext of other families in their population. The observed variation by sex underlines the need to deepen the understanding of factors influencing ASD familial risk.</p

Guidance on how to identify impacts of hydromorphological degradation on riparian ecosystems. Deliverable 3.4 of REFORM (REstoring rivers FOR effective catchment Management), a collaborative project (large-scale integrating project) funded by the European Commission within the 7th Framework Grant Agreement 282656

The aim of this deliverable is to address the impact of hydromorphological degradation on floodplain and riparian ecosystems, with specific focus on vegetation, fish and invertebrate responses and to provide guidance on how to identify those impacts

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

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

A Ray Tracer to Visualize Higher Dimensional Julia Sets

Artists, scientists and mathematicians have been collaborating on a variety of projects at the Electronic Visualization Laboratory for over thirty years. In 1989, a ray tracer was created to visualize higher dimensional Julia Sets, involving and contributing to advances in all three fields. 1. Background The creation of the ray tracer to visualize higher dimensional Julia Sets described here took place in a research environment called the Electronic Visualization Laboratory (EVL). EVL is a shared facility o