Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: A genome-wide association and polygenic scoring study.

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome-wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome-wide studies for SA were conducted in the RADIANT and GSK-Munich recurrent depression samples and London Bipolar Affective Disorder Case-Control Study (BACCs) then meta-analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta-analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis. © 2014 Wiley Periodicals, Inc.

Evidence for polygenic adaptation to pathogens in the human genome.

Most approaches aiming at finding genes involved in adaptive events have focused on the detection of outlier loci, which resulted in the discovery of individually "significant" genes with strong effects. However, a collection of small effect mutations could have a large effect on a given biological pathway that includes many genes, and such a polygenic mode of adaptation has not been systematically investigated in humans. We propose here to evidence polygenic selection by detecting signals of adaptation at the pathway or gene set level instead of analyzing single independent genes. Using a gene-set enrichment test to identify genome-wide signals of adaptation among human populations, we find that most pathways globally enriched for signals of positive selection are either directly or indirectly involved in immune response. We also find evidence for long-distance genotypic linkage disequilibrium, suggesting functional epistatic interactions between members of the same pathway. Our results show that past interactions with pathogens have elicited widespread and coordinated genomic responses, and suggest that adaptation to pathogens can be considered as a primary example of polygenic selection.

Generation mean analysis in relation to polygenic systems with epistasis and fixed genes

Epistatic effects involving genic combinations of fixed and non fixed genes are shown to contribute to the genotypic mean of any population. These effects define specific additive x additive and additive x dominant epistatic components. As such components are not estimable, their relative importance cannot be assessed. These epistatic effects can cause bias in the estimates of the additive and dominance components to which they are confounded. The magnitude of the bias depends on the relative values of the epistatic effects, comparatively to deviations d and h, type of prevailing epistasis and direction of dominance.

Polygenic determinants of white matter volume derived from GWAS lack reproducibility in a replicate sample

A recent publication reported an exciting polygenic effect of schizophrenia (SCZ) risk variants, identified by a large genome-wide association study (GWAS), on total brain and white matter volumes in schizophrenic patients and, even more prominently, in healthy subjects. The aim of the present work was to replicate and then potentially extend these findings. According to the original publication, polygenic risk scores using single nucleotide polymorphism (SNP) information of SCZ GWAS (polygenic SCZ risk scores; PSS) were calculated in 122 healthy subjects, enrolled in a structural magnetic resonance imaging (MRI) study. These scores were computed based on P-values and odds ratios available through the Psychiatric GWAS Consortium. In addition, polygenic white matter scores (PWM) were calculated, using the respective SNP subset in the original publication. None of the polygenic scores, either PSS or PWM, were found to be associated with total brain, white matter or gray matter volume in our replicate sample. Minor differences between the original and the present study that might have contributed to lack of reproducibility (but unlikely explain it fully), are number of subjects, ethnicity, age distribution, array technology, SNP imputation quality and MRI scanner type. In contrast to the original publication, our results do not reveal the slightest signal of association of the described sets of GWAS-identified SCZ risk variants with brain volumes in adults. Caution is indicated in interpreting studies building on polygenic risk scores without replication sample.

A novel technique to produce polygenic resistance to anthracnose in Stylosanthes capitata

An improved cultivar, based on 17 genotypes of S. capitata and six of S.macrocephala, was developed at the wEmbrapa Beef Cattle Research Center, Campo Grande, Brazil. The aim was to create durable, race non-specific resistance to anthracnose controlled by polygenic factors. A mass hybridisation technique was employed to produce a high degree of genetic diversity and sizeable quantities of seed of hybrid-derived progenies of Brazilian and Venezuelan genotypes of S. capitata. Outcrossing resulted in a significant improvement in the forage production of progeny of Venezuelan accessions. The multicross was evaluated in multilocational trials, each representing a large tract of country in the Cerrados ecosystem along a north-south transect from lat.6degrees S to 20degrees S. The genetic shift that occurred in S. capitata was a key element in the formation of the new cultivar. It is a complex mixture of two species, and a recombination of much desired forage traits of Brazilian x Venezuelan genotypes, high forage and seed yields coupled with anthracnose resistance. The new cultivar with its diverse genetic make-up has a wide application in the acid-soil savannas of tropical America. It was released by Embrapa for the Cerrados in 2000.

A polygenic mouse model of psoriasiform skin disease in CD18-deficient mice.

Previously, a hypomorphic mutation in CD18 was generated by gene targeting, with homozygous mice displaying increased circulating neutrophil counts, defects in the response to chemically induced peritonitis, and delays in transplantation rejection. When this mutation was backcrossed onto the PL/J inbred strain, virtually all homozygous mice developed a chronic inflammatory skin disease with a mean age of onset of 11 weeks after birth. The disease was characterized by erythema, hair loss, and the development of scales and crusts. The histopathology revealed hyperplasia of the epidermis, subcorneal microabscesses, orthohyperkeratosis, parakeratosis, and lymphocyte exocytosis, which are features in common with human psoriasis and other hyperproliferative inflammatory skin disorders. Repetitive cultures failed to demonstrate bacterial or fungal organisms potentially involved in the pathogenesis of this disease, and the dermatitis resolved rapidly after subcutaneous administration of dexamethasone. Homozygous mutant mice on a (PL/J x C57BL/6J)F1 background did not develop the disease and backcross experiments suggest that a small number of genes (perhaps as few as one), in addition to CD18, determine susceptibility to the disorder. This phenotype provides a model for inflammatory skin disorders, may have general relevance to polygenic human inflammatory diseases, and should help to identify genes that interact with the beta2 integrins in inflammatory processes.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R(2 ) = 0.0021; P = 0.00331; P-value threshold <0.4). Estimates of variability in disease liability attributable to the aggregate effect of genome-wide SNPs were significantly greater for family history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031). We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by previous epidemiological studies.

Polygenic Interactions with Environmental Adversity in the Aetiology of Major Depressive Disorder

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10−6). SLEs and CT were also associated with MDD status (p = 2.19 × 10−4 and p = 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.