A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. / Methods: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared. / Results: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively. / Conclusions: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other

Investigation of Gamma-aminobutyric acid (GABA) A receptors genes and migraine susceptibility

Background Migraine is a neurological disorder characterized by recurrent attacks of severe headache, affecting around 12% of Caucasian populations. It is well known that migraine has a strong genetic component, although the number and type of genes involved is still unclear. Prior linkage studies have reported mapping of a migraine gene to chromosome Xq 24–28, a region containing a cluster of genes for GABA A receptors (GABRE, GABRA3, GABRQ), which are potential candidate genes for migraine. The GABA neurotransmitter has been implicated in migraine pathophysiology previously; however its exact role has not yet been established, although GABA receptors agonists have been the target of therapeutic developments. The aim of the present research is to investigate the role of the potential candidate genes reported on chromosome Xq 24–28 region in migraine susceptibility. In this study, we have focused on the subunit GABA A receptors type ε (GABRE) and type θ (GABRQ) genes and their involvement in migraine. Methods We have performed an association analysis in a large population of case-controls (275 unrelated Caucasian migraineurs versus 275 controls) examining a set of 3 single nucleotide polymorphisms (SNPs) in the coding region (exons 3, 5 and 9) of the GABRE gene and also the I478F coding variant of the GABRQ gene. Results Our study did not show any association between the examined SNPs in our test population (P > 0.05). Conclusion Although these particular GABA receptor genes did not show positive association, further studies are necessary to consider the role of other GABA receptor genes in migraine susceptibility

Genetics of migraine in the age of genome-wide association studies

Genetic factors importantly contribute to migraine. However, unlike for rare monogenic forms of migraine, approaches to identify genes for common forms of migraine have been of limited success. Candidate gene association studies were often negative and positive results were often not replicated or replication failed. Further, the significance of positive results from linkage studies remains unclear owing to the inability to pinpoint the genes under the peaks that may be involved in migraine. Problems hampering these studies include limited sample sizes, methods of migraine ascertainment, and the heterogeneous clinical phenotype. Three genome-wide association studies are available now and have successfully identified four new genetic variants associated with migraine. One new variant (rs1835740) modulates glutamate homeostasis, thus integrates well with current concepts of neurotransmitter disturbances. This variant may be more specific for severe forms of migraine such as migraine with aura than migraine without aura. Another variant (rs11172113) implicates the lipoprotein receptor LRP1, which may interact with neuronal glutamate receptors, thus also providing a link to the glutamate pathway. In contrast, rs10166942 is in close proximity to TRPM8, which codes for a cold and pain sensor. For the first time this links a gene explicitly implicated in pain related pathways to migraine. The potential function of the fourth variant rs2651899 (PRDM16) in migraine is unclear. All these variants only confer a small to moderate change in risk for migraine, which concurs with migraine being a heterogeneous disorder. Ongoing large international collaborations will likely identify additional gene variants for migraine

Common variants in the regulative regions of GRIA1 and GRIA3 receptor genes are associated with migraine susceptibility

<p>Abstract</p> <p>Background</p> <p>Glutamate is the principal excitatory neurotransmitter in the central nervous system which acts by the activation of either ionotropic (AMPA, NMDA and kainate receptors) or G-protein coupled metabotropic receptors. Glutamate is widely accepted to play a major role in the path physiology of migraine as implicated by data from animal and human studies. Genes involved in synthesis, metabolism and regulation of both glutamate and its receptors could be, therefore, considered as potential candidates for causing/predisposing to migraine when mutated.</p> <p>Methods</p> <p>The association of polymorphic variants of <it>GRIA1</it>-<it>GRIA4 </it>genes which encode for the four subunits (GluR1-GluR4) of the alpha-amino-3- hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptor for glutamate was tested in migraineurs with and without aura (MA and MO) and healthy controls.</p> <p>Results</p> <p>Two variants in the regulative regions of <it>GRIA1 </it>(rs2195450) and <it>GRIA3 </it>(rs3761555) genes resulted strongly associated with MA (P = 0.00002 and P = 0.0001, respectively), but not associated with MO, suggesting their role in cortical spreading depression. Whereas the rs548294 variant in <it>GRIA1 </it>gene showed association primarily with MO phenotype, supporting the hypothesis that MA and MO phenotypes could be genetically related. These variants modify binding sites for transcription factors altering the expression of <it>GRIA1 </it>and <it>GRIA3 </it>genes in different conditions.</p> <p>Conclusions</p> <p>This study represents the first genetic evidence of a link between glutamate receptors and migraine.</p

Caught you: threats to confidentiality due to the public release of large-scale genetic data sets

<p>Abstract</p> <p>Background</p> <p>Large-scale genetic data sets are frequently shared with other research groups and even released on the Internet to allow for secondary analysis. Study participants are usually not informed about such data sharing because data sets are assumed to be anonymous after stripping off personal identifiers.</p> <p>Discussion</p> <p>The assumption of anonymity of genetic data sets, however, is tenuous because genetic data are intrinsically self-identifying. Two types of re-identification are possible: the "Netflix" type and the "profiling" type. The "Netflix" type needs another small genetic data set, usually with less than 100 SNPs but including a personal identifier. This second data set might originate from another clinical examination, a study of leftover samples or forensic testing. When merged to the primary, unidentified set it will re-identify all samples of that individual.</p> <p>Even with no second data set at hand, a "profiling" strategy can be developed to extract as much information as possible from a sample collection. Starting with the identification of ethnic subgroups along with predictions of body characteristics and diseases, the asthma kids case as a real-life example is used to illustrate that approach.</p> <p>Summary</p> <p>Depending on the degree of supplemental information, there is a good chance that at least a few individuals can be identified from an anonymized data set. Any re-identification, however, may potentially harm study participants because it will release individual genetic disease risks to the public.</p

Serotonin tranporter methylation and response to cognitive behaviour therapy in children with anxiety disorders

Anxiety disorders that are the most commonly occurring psychiatric disorders in childhood, are associated with a range of social and educational impairments and often continue into adulthood. Cognitive behaviour therapy (CBT) is an effective treatment option for the majority of cases, although up to 35-45% of children do not achieve remission. Recent research suggests that some genetic variants may be associated with a more beneficial response to psychological therapy. Epigenetic mechanisms such as DNA methylation work at the interface between genetic and environmental influences. Furthermore, epigenetic alterations at the serotonin transporter (SERT) promoter region have been associated with environmental influences such as stressful life experiences. In this study, we measured DNA methylation upstream of SERT in 116 children with an anxiety disorder, before and after receiving CBT. Change during treatment in percentage DNA methylation was significantly different in treatment responders vs nonresponders. This effect was driven by one CpG site in particular, at which responders increased in methylation, whereas nonresponders showed a decrease in DNA methylation. This is the first study to demonstrate differences in SERT methylation change in association with response to a purely psychological therapy. These findings confirm that biological changes occur alongside changes in symptomatology following a psychological therapy such as CBT

A note on the use of the generalized odds ratio in meta-analysis of association studies involving bi- and tri-allelic polymorphisms

<p>Abstract</p> <p>Background</p> <p>The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease.</p> <p>Findings</p> <p>For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects.</p> <p>Conclusions</p> <p>For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.</p

How can photo sharing inspire sharing genomes?

People usually are aware of the privacy risks of publish-ing photos online, but these risks are less evident when sharing humangenomes. Modern photos and sequenced genomes are both digital rep-resentations of real lives. They contain private information that maycompromise people’s privacy, and still, their highest value is most oftimes achieved only when sharing them with others. In this work, wepresent an analogy between the privacy aspects of sharing photos andsharing genomes, which clarifies the privacy risks in the latter to thegeneral public. Additionally, we illustrate an alternative informed modelto share genomic data according to the privacy-sensitivity level of eachportion. This article is a call to arms for a collaborative work between ge-neticists and security experts to build more effective methods to system-atically protect privacy, whilst promoting the accessibility and sharingof genome