Objective To conduct a genome-wide association study (GWAS) of anorexia nervosa and to calculate genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method Following uniform quality control and imputation using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, we performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression (LDSC) was used to calculate genome-wide common variant heritability [ hSNP2, partitioned heritability, and genetic correlations (rg)] between anorexia nervosa and other phenotypes. Results Results were obtained for 10,641,224 single nucleotide polymorphisms (SNPs) and insertion-deletion variants with minor allele frequency > 1% and imputation quality scores > 0.6. The hSNP2 of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. We identified one genome-wide significant locus on chromosome 12 (rs4622308, p=4.3×10−9) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high density lipoprotein (HDL) cholesterol, and significant negative genetic correlations between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Conclusions Anorexia nervosa is a complex heritable phenotype for which we have found the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. Our results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci.

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 3 10 À8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Future of clinical development is on the verge of a major transformation due to convergence of large new digital data sources, computing power to identify clinically meaningful patterns in the data using efficient artificial intelligence and machine-learning algorithms, and regulators embracing this change through new collaborations. This perspective summarizes insights, recent developments, and recommendations for infusing actionable computational evidence into clinical development and health care from academy, biotechnology industry, nonprofit foundations, regulators, and technology corporations. Analysis and learning from publically available biomedical and clinical trial data sets, real-world evidence from sensors, and health records by machine-learning architectures are discussed. Strategies for modernizing the clinical development process by integration of AI- and ML-based digital methods and secure computing technologies through recently announced regulatory pathways at the United States Food and Drug Administration are outlined. We conclude by discussing applications and impact of digital algorithmic evidence to improve medical care for patients.

DBA/2J (D2) and C57BL/6J (B6) mice exhibit differential sensitivity to seizures induced by various chemical and physical methods, with D2 mice being relatively sensitive and B6 mice relatively resistant. We conducted studies in mature D2, B6, F1, and F2 intercross mice to investigate behavioral seizure responses to pentylenetetrazol (PTZ) and to map the location of genes that influence this trait. Mice were injected with PTZ and observed for 45 min. Seizure parameters included latencies to focal clonus, generalized clonus, and maximal seizure. Latencies were used to calculate a seizure score that was used for quantitative mapping. F2 mice (n = 511) exhibited a wide range of latencies with two-thirds of the group expressing maximal seizure. Complementary statistical analyses identified loci on proximal (near D1Mit11) and distal chromosome 1 (near D1Mit17) as having the strongest and most significant effects in this model. Another locus of significant effect was detected on chromosome 5 (near D5Mit398). Suggestive evidence for additional PTZ seizure-related loci was detected on chromosomes 3, 4, and 6. Of the seizure-related loci identified in this study, those on chromosomes 1 (distal), 4, and 5 map close to loci previously identified in a similar F2 population tested with kainic acid. Results document that the complex genetic influences controlling seizure response in B6 and D2 mice are partially independent of the nature of the chemoconvulsant stimulus with a locus on distal chromosome 1 being of fundamental importance.

The genetics of schizophrenia has been approached utilizing a variety of methods. One emerging strategy is the use of endophenotypes in order to understand and identify the functional importance of genetically transmitted, brainbased deficits across schizophrenia kindreds. The endophenotype strategy is a topic of this issue of Schizophrenia Bulletin. Endophenotypes are quantitative, heritable, traitrelated deficits typically assessed by laboratory-based methods rather than clinical observation. Endophenotypes are seen as closer to genetic variation than are clinical symptoms of schizophrenia, and are therefore closely linked to heritable risk factors. There has been a broad expansion of opportunities available to psychiatric neuroscientists who use the endophenotype strategy to understand the genetic basis of schizophrenia. In this context, genetic variation such as single nucleotide polymorphisms (SNPs) induces abnormalities in endophenotypic domains such as neurocognition, neurodevelopment, metabolism, and neurophysiology. This article discusses the challenges that abound in genetic research of schizophrenia, including issues in ascertainment, epistasis, ethnic diversity, and the potentially normalizing effects of secondgeneration antipsychotic medications on neurocognitive and neurophysiological measures. Robust strategies for meeting these challenges are discussed in this review and the subsequent articles in this issue. This article summarizes conceptual advances and progress in the measurement and use of endophenotypes in schizophrenia that form the basis of the multisite National Institute of Mental Health Consortium on the Genetics of Schizophrenia. The endophenotype strategy offers powerful and exciting opportunities to understand the genetically conferred neurobiological vulnerabilities and possible new strong inference and molecularly based treatments for schizophrenia.

BACKGROUND Coronary angioplasty is frequently performed in the United States, with more than 300,000 procedures in 1990. Despite the high rate of use of the procedure, there have been few studies addressing practice patterns. METHODS AND RESULTS From a private insurance claims data base of 5.4 million individuals, a total of 2,101 patients who underwent coronary angioplasty during 1988-1989 were identified. Using their 4,578 hospital admission records and 87,578 outpatient claim records, with an average follow-up of 332 +/- 182 days, we compared patients' outcomes and charges according to whether they had an exercise stress test before the procedure, by sex, by region of the country, and by whether the angioplasty was performed in an institution with a training program. Only 29% of the study cohort had exercise testing before angioplasty; patients in the West (p = 0.001), those undergoing multivessel angioplasty (p = 0.00001), and those whose procedures were performed at sites with training programs (p = 0.04) were more likely to have a screening test, whereas women (p = 0.008) and those with a recent myocardial infarction (p = 0.00001) were less likely to have a screening test. The average length of stay for patients without myocardial infarction as a primary diagnosis was 5.6 days, with a total hospital charge of $15,027. In follow-up, 15.1% had coronary artery bypass surgery and 15% had at least one additional angioplasty procedure; the average follow-up charges were $4,879. Charges varied according to sex, region of the country, and academic status of the angioplasty institution. Certain outcomes showed variation by region of the country and academic status of the angioplasty institution. CONCLUSIONS The relative lack of an objective definition of myocardial ischemia and the marked variability of use of procedures according to geographic region suggest the need for further implementation of established guidelines.

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