Mammalian reverse genetics without crossing reveals Nr3a as a short-sleeper gene

The identification of molecular networks at the system level in mammals is accelerated by next-generation mammalian genetics without crossing, which requires both the efficient production of whole-body biallelic knockout (KO) mice in a single generation and high-performance phenotype analyses. Here, we show that the triple targeting of a single gene using the CRISPR/Cas9 system achieves almost perfect KO efficiency (96%–100%). In addition, we developed a respiration-based fully automated noninvasive sleep phenotyping system, the Snappy Sleep Stager (SSS), for high-performance (95.3% accuracy) sleep/wake staging. Using the triple-target CRISPR and SSS in tandem, we reliably obtained sleep/wake phenotypes, even in double-KO mice. By using this system to comprehensively analyze all of the N-methyl-D-aspartate (NMDA) receptor family members, we found Nr3a as a short-sleeper gene, which is verified by an independent set of triple-target CRISPR. These results demonstrate the application of mammalian reverse genetics without crossing to organism-level systems biology in sleep research.

Shared genetics underlying epidemiological association between endometriosis and ovarian cancer

Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18–0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07–0.89 and 0.40, 95% CI = 0.05–0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11–0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.

A genome-wide association study of Cloninger's temperament scales: implications for the evolutionary genetics of personality

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

The shared genetics of migraine and anxious depression

OBJECTIVES To investigate: - (1) whether shared genetic factors influence migraine and anxious depression; - (2) whether the genetic architecture of migraine depends on anxious depression; - (3) whether the association between migraine and anxious depression is causal. BACKGROUND Migraine and anxious depression frequently occur together, but little is known about the mechanisms causing this association. METHODS A twin study was conducted to model the genetic architecture of migraine and anxious depression and the covariance between them. Anxious depression was also added to the model as a moderator variable to examine whether anxious depression affects the genetic architecture of migraine. Causal models were explored with the co-twin control method. RESULTS Modest but significant phenotypic (rP=0.28), genetic (rG=0.30), and nonshared environmental (rE=0.26) correlations were found between the 2 traits. Interestingly, the heritability of migraine depended on the level of anxious depression: the higher the anxious depression score, the lower the relative contribution of genetic factors to the individual differences in migraine susceptibility. The observed risk patterns in discordant twins are most consistent with a bidirectional causal relationship. CONCLUSIONS These findings confirm the genetic association between migraine and anxious depression and are consistent with a syndromic association between the 2 traits. This highlights the importance of taking comorbidity into account in genetic studies of migraine, especially in the context of selection for large-scale genotyping efforts. Genetic studies may be most effective when migraine with and without comorbid anxious depression are treated as separate phenotypes.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Tax compliance and psychic costs: Behavioral experimental evidence using a physiological marker

Although paying taxes is a key element of a well-functioning society, there is still limited understanding as to why people actually pay their taxes. Models emphasizing that taxpayers make strategic, financially motivated compliance decisions seemingly assume an overly restrictive view of human nature. Law abidance may be more accurately explained by social norms, a concept that has gained growing importance as research attempts to understand the tax compliance puzzle. This study analyzes the influence of psychic stress generated by the possibility of breaking social norms in the tax compliance context. We measure psychic stress using heart rate variability (HRV), which captures the psychobiological or neural equivalents of psychic stress that may arise from the contemplation of real or imagined actions, producing immediate physiologic discomfort. The results of our laboratory experiments provide empirical evidence of a positive correlation between psychic stress and tax compliance, thus underscoring the importance of moral sentiments for tax compliance. We also identify three distinct types of individuals who differ in their levels of psychic stress, tax morale, and tax compliance.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

The genetic associations of acute anterior uveitis and their overlap with the genetics of ankylosing spondylitis

Acute anterior uveitis (AAU) involves inflammation of the iris and ciliary body of the eye. It occurs both in isolation and as a complication of ankylosing spondylitis (AS). It is strongly associated with HLA-B*27, but previous studies have suggested that further genetic factors may confer additional risk. We sought to investigate this using the Illumina Exomechip microarray, to compare 1504 cases with AS and AAU, 1805 with AS but no AAU and 21 133 healthy controls. We also used a heterogeneity test to test the differences in effect size between AS with AAU and AS without AAU. In the analysis comparing AS+AAU+ cases versus controls, HLA-B*27 and HLA-A*02:01 were significantly associated with the presence of AAU (P<10−300 and P=6 × 10−8, respectively). Secondary independent association with PSORS1C3 (P=4.7 × 10−5) and TAP2 (P=1.1 × 10−5) were observed in the major histocompatibility complex. There was a new suggestive association with a low-frequency variant at zinc-finger protein 154 in the AS without AAU versus control analysis (zinc-finger protein 154 (ZNF154), P=2.2 × 10−6). Heterogeneity testing showed that rs30187 in ERAP1 has a larger effect on AAU compared with that in AS alone. These findings also suggest that variants in ERAP1 have a differential impact on the risk of AAU when compared with AS, and hence the genetic risk for AAU differs from AS.

Genetics of ankylosing spondylitis - Insights into pathogenesis

Ankylosing spondylitis (AS), an immune-mediated arthritis, is the prototypic member of a group of conditions known as spondyloarthropathies that also includes reactive arthritis, psoriatic arthritis and enteropathic arthritis. Patients with these conditions share a clinical predisposition for spinal and pelvic joint dysfunction, as well as genetic associations, notably with HLA-B*27. Spondyloarthropathies are characterized by histopathological inflammation in entheses (regions of high mechanical stress where tendons and ligaments insert into bone) and in the subchondral bone marrow, and by abnormal osteoproliferation at involved sites. The association of AS with HLA-B*27, first described >40 years ago, led to hope that the cause of the disease would be rapidly established. However, even though many theories have been advanced to explain how HLA-B*27 is involved in AS, no consensus about the answers to this question has been reached, and no successful treatments have yet been developed that target HLA-B27 or its functional pathways. Over the past decade, rapid progress has been made in discovering further genetic associations with AS that have shed new light on the aetiopathogenesis of the disease. Some of these discoveries have driven translational ideas, such as the repurposing of therapeutics targeting the cytokines IL-12 and IL-23 and other factors downstream of this pathway. AS provides an excellent example of how hypothesis-free research can lead to major advances in understanding pathogenesis and to the development of innovative therapeutic strategies.

The genetics of osteoporosis

Introduction: Osteoporosis is the commonest metabolic bone disease worldwide. The clinical hallmark of osteoporosis is low trauma fracture, with the most devastating being hip fracture, resulting in significant effects on both morbidity and mortality. Sources of data: Data for this review have been gathered from the published literature and from a range of web resources. Areas of agreement: Genome-wide association studies in the field of osteoporosis have led to the identification of a number of loci associated with both bone mineral density and fracture risk and further increased our understanding of disease. Areas of controversy: The early strategies for mapping osteoporosis disease genes reported only isolated associations, with replication in independent cohorts proving difficult. Neither candidate gene or linkage studies showed association at genome-wide level of significance. Growing points: The advent of massive parallel sequencing technologies has proved extremely successful in mapping monogenic diseases and thus leading to the utilization of this new technology in complex disease genetics. Areas timely for developing research: The identification of novel genes and pathways will potentially lead to the identification of novel therapeutic options for patients with osteoporosis. © 2014 The Author.