Genetically-Informed Patient Selection for iPSC Studies of Complex Diseases May Aid in Reducing Cellular Heterogeneity

Induced pluripotent stem cell (iPSC) technology is more and more used for the study of genetically complex human disease but is challenged by variability, sample size and polygenicity. We discuss studies involving iPSC-derived neurons from patients with Schizophrenia (SCZ), to exemplify that heterogeneity in sampling strategy complicate the detection of disease mechanisms. We offer a solution to controlling variability within and between iPSC studies by using specific patient selection strategies

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

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

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

Genetically-Informed Patient Selection for iPSC Studies of Complex Diseases May Aid in Reducing Cellular Heterogeneity

Induced pluripotent stem cell (iPSC) technology is more and more used for the study of genetically complex human disease but is challenged by variability, sample size and polygenicity. We discuss studies involving iPSC-derived neurons from patients with Schizophrenia (SCZ), to exemplify that heterogeneity in sampling strategy complicate the detection of disease mechanisms. We offer a solution to controlling variability within and between iPSC studies by using specific patient selection strategies

Generation of Isogenic Controls for In Vitro Disease Modelling of X-Chromosomal Disorders

Generation of proper controls is crucial in induced pluripotent stem cell (iPSC) studies. X-chromosomal disorders offer the potential to develop isogenic controls due to random X-chromosomal inactivation (XCI). However, the generation of such lines is currently hampered by skewed X-inactivation in fibroblast lines and X-chromosomal reactivation (XCR) after reprogramming. Here we describe a method to generate a pure iPSC population with respect to the specific inactivated X-chromosome (Xi). We used fibroblasts from Rett patients, who all have a causal mutation in the X-linked MeCP2 gene. Pre-sorting these fibroblasts followed by episomal reprogramming, allowed us to overcome skewness in fibroblast lines and to retain the X-chromosomal state, which was unpredictable with lentiviral reprogramming. This means that fibroblast pre-sorting followed by episomal reprogramming can be used to reliably generate iPSC lines with specified X-chromosomal phenotype such as Rett syndrome

Systematic assessment of variability in the proteome of iPSC derivatives

The use of induced pluripotent stem cells (iPSC) to model human complex diseases is gaining popularity as it allows investigation of human cells that are otherwise sparsely available. However, due to its laborious and cost intensive nature, iPSC research is often plagued by limited sample size and putative large variability between clones, decreasing statistical power for detecting experimental effects. Here, we investigate the source and magnitude of variability in the proteome of parallel differentiated astrocytes using mass spectrometry. We compare three possible sources of variability: inter-donor variability, inter- and intra-clonal variability, at different stages of maturation. We show that the interclonal variability is significantly smaller than the inter-donor variability, and that including more donors has a much larger influence on statistical power than adding more clones per donor. Our results provide insight into the sources of variability at protein level between iPSC samples derived in parallel and will aid in optimizing iPSC studies

Carte des îles de Ré et d'Olleron

Objective: Letters from the hospital to the general practitioner are important for maintaining continuity of care. Although doctors feel letters are important, they are often not written on time. To improve the number and timeliness of letters sent from the hospital outpatient department to the general practitioner using an email-based intervention evaluated in a randomized controlled trial. Materials and methods: Users were interviewed to determine the requirements for the intervention. Due to high between-doctor variation at baseline, doctors were matched for baseline performance and pair-randomized. The effectiveness of the intervention was assessed using meta-analytic methods. The primary outcome was the numbe