Genome-wide association studies: a primer

There have been nearly 400 genome-wide association studies (GWAS) published since 2005. The GWAS approach has been exceptionally successful in identifying common genetic variants that predispose to a variety of complex human diseases and biochemical and anthropometric traits. Although this approach is relatively new, there are many excellent reviews of different aspects of the GWAS method. Here, we provide a primer, an annotated overview of the GWAS method with particular reference to psychiatric genetics. We dissect the GWAS methodology into its components and provide a brief description with citations and links to reviews that cover the topic in detail

Prevalence and correlates of psychotic experiences amongst children of depressed parents

Psychotic experiences in young people are substantially more common than psychotic disorders, and are associated with distress and functional impairment. Family history of depression as well as of schizophrenia increases risk for psychotic experiences, but the prevalence of such experiences and their clinical relevance in offspring of depressed parents is unknown. Our objectives were to explore i) the prevalence of psychotic experiences amongst offspring of parents with recurrent unipolar depression and ii) the relationship between psychotic experiences and other psychopathology. Data were drawn from the ‘Early Prediction of Adolescent Depression’ longitudinal study of high-risk offspring (aged 9–17 years at baseline) of 337 parents with recurrent depression. Three assessments were conducted over four years. Psychopathology was assessed using the Child and Adolescent Psychiatric Assessment. Seventy-eight percent of families (n=262) had complete data on psychotic experiences at each of the three time points. During the study, 8.4% (n=22; 95% CI 5.0%, 11.8%) of offspring reported psychotic experiences on at least one occasion, and these were associated with psychiatric disorder, specifically mood and disruptive disorders, and suicidal thoughts/behaviour. Psychotic experiences amongst offspring of depressed parents index a range of psychopathology. Further research is needed to examine their clinical significance and long-term consequences

Investigation of the genetic association between quantitative measures of psychosis and schizophrenia:A polygenic risk score analysis

The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom scores were available. The genetic risk score of schizophrenia was significantly associated with case-control status (p<0.0001). In the case-control sample, the five psychosis dimensions were found to be significantly associated with genetic risk scores; the correlations ranged between.15 and.27 (all p<.001). However, these correlations were not significant in schizophrenia cases or controls separately. While this study confirms the presence of a genetic risk for schizophrenia as categorical diagnostic trait, we did not find evidence for the genetic risk underlying quantitative schizophrenia symptom dimensions. This does not necessarily imply that a genetic basis is nonexistent, but does suggest that it is distinct from the polygenic risk score for schizophrenia

Posttransplant MRD and T-cell chimerism status predict outcomes in patients who received allografts for AML/MDS

Allogeneic stem-cell transplant allows for the delivery of curative graft-versus-leukemia (GVL) in patients with acute myeloid leukemia/myelodysplasia (AML/MDS). Surveillance of T-cell chimerism, measurable residual disease (MRD) and blast HLA-DR expression may inform whether GVL effectiveness is reduced. We report here the prognostic impact of these biomarkers in patients allografted for AML/MDS. One hundred eighty-seven patients from FIGARO, a randomized trial of reduced-intensity conditioning regimens in AML/MDS, were alive and relapse-free at the first MRD time-point and provided monitoring samples for flow cytometric MRD and T-cell chimerism, requested to month+12. Twenty-nine (15.5%) patients had at least 1 MRD-positive result posttransplant. MRD-positivity was associated with reduced overall survival (OS) (hazard ratio [HR], 2.18; P = .0028) as a time-varying Cox variable and remained significant irrespective of pretransplant MRD status in multivariate analyses (P < .001). Ninety-four patients had sequential MRD with T-cell chimerism results at months+3/+6. Patients with full donor T-cell chimerism (FDTC) had an improved OS as compared with patients with mixed donor T-cell chimerism (MDTC) (adjusted HR=0.4; P = .0019). In patients with MDTC (month+3 or +6), MRD-positivity was associated with a decreased 2-year OS (34.3%) vs MRD-negativity (71.4%) (P = .001). In contrast, in the group with FDTC, MRD was infrequent and did not affect the outcome. Among patients with posttransplant MRD-positivity, decreased HLA-DR expression on blasts significantly reduced OS, supporting this as a mechanism for GVL escape. In conclusion, posttransplant MRD is an important predictor of the outcome in patients allografted for AML/MDS and is most informative when combined with T-cell chimerism results, underlining the importance of a GVL effect in AML/MDS

Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P(meta)<1 × 10⁻⁴, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available

Re-evaluation of putative rheumatoid arthritis susceptibility genes in the post-genome wide association study era and hypothesis of a key pathway underlying susceptibility

Rheumatoid arthritis (RA) is an archetypal, common, complex autoimmune disease with both genetic and environmental contributions to disease aetiology. Two novel RA susceptibility loci have been reported from recent genome-wide and candidate gene association studies. We, therefore, investigated the evidence for association of the STAT4 and TRAF1/C5 loci with RA using imputed data from the Wellcome Trust Case Control Consortium (WTCCC). No evidence for association of variants mapping to the TRAF1/C5 gene was detected in the 1860 RA cases and 2930 control samples tested in that study. Variants mapping to the STAT4 gene did show evidence for association (rs7574865, P = 0.04). Given the association of the TRAF1/C5 locus in two previous large case–control series from populations of European descent and the evidence for association of the STAT4 locus in the WTCCC study, single nucleotide polymorphisms mapping to these loci were tested for association with RA in an independent UK series comprising DNA from >3000 cases with disease and >3000 controls and a combined analysis including the WTCCC data was undertaken. We confirm association of the STAT4 and the TRAF1/C5 loci with RA bringing to 5 the number of confirmed susceptibility loci. The effect sizes are less than those reported previously but are likely to be a more accurate reflection of the true effect size given the larger size of the cohort investigated in the current study

Rare Variant Analysis of Human and Rodent Obesity Genes in Individuals with Severe Childhood Obesity

A. Palotie on työryhmän UK10K Consortium jäsen.Obesity is a genetically heterogeneous disorder. Using targeted and whole-exome sequencing, we studied 32 human and 87 rodent obesity genes in 2,548 severely obese children and 1,117 controls. We identified 52 variants contributing to obesity in 2% of cases including multiple novel variants in GNAS, which were sometimes found with accelerated growth rather than short stature as described previously. Nominally significant associations were found for rare functional variants in BBS1, BBS9, GNAS, MKKS, CLOCK and ANGPTL6. The p.S284X variant in ANGPTL6 drives the association signal (rs201622589, MAF similar to 0.1%, odds ratio = 10.13, p-value = 0.042) and results in complete loss of secretion in cells. Further analysis including additional case-control studies and population controls (N = 260,642) did not support association of this variant with obesity (odds ratio = 2.34, p-value = 2.59 x 10(-3)), highlighting the challenges of testing rare variant associations and the need for very large sample sizes. Further validation in cohorts with severe obesity and engineering the variants in model organisms will be needed to explore whether human variants in ANGPTL6 and other genes that lead to obesity when deleted in mice, do contribute to obesity. Such studies may yield druggable targets for weight loss therapies.Peer reviewe