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

Incorporating InSAR kinematics into rock glacier inventories : insights from 11 regions worldwide

This research was funded by the European Space Agency Permafrost-CCI project (grant number 4000123681/18/I-NB).Rock glaciers are landforms related to permafrost creep that are sensitive to climate variability and change. Their spatial distribution and kinematic behaviour can be critical for managing water resources and geohazards in periglacial areas. Rock glaciers have been inventoried for decades worldwide, often without assessment of their kinematics. The availability of remote sensing data however makes the inclusion of kinematic information potentially feasible, but requires a common methodology in order to create homogeneous inventories. In this context, the International Permafrost Association (IPA) Action Group on rock glacier inventories and kinematics (2018-2023), with the support of the European Space Agency (ESA) Permafrost Climate Change Initiative (CCI) project, is defining standard guidelines for the inclusion of kinematic information within inventories. Here, we demonstrate the feasibility of applying common rules proposed by the Action Group in 11 regions worldwide. Spaceborne interferometric synthetic aperture radar (InSAR) was used to characterise identifiable moving areas related to rock glaciers, applying a manual and a semi-automated approach. Subsequently, these areas were used to assign kinematic information to rock glaciers in existing or newly compiled inventories. More than 5000 moving areas and more than 3600 rock glaciers were classified according to their kinematics. The method and the preliminary results were analysed. We identified drawbacks related to the intrinsic limitations of InSAR and to various applied strategies regarding the integration of non-moving rock glaciers in some investigated regions. This is the first internationally coordinated work that incorporates kinematic attributes within rock glacier inventories at a global scale. The results show the value of designing standardised inventorying procedures for periglacial geomorphology. Copyright: © 2022 Aldo Bertone et al.Publisher PDFPeer reviewe

Analysis of Shared Heritability in Common Disorders of the Brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology