Identification of gene co-expression modules from zebrafish brain data: Applications in psychiatry illustrated through alcohol-related traits.

Cumulative evidence suggests that zebrafish is a useful model in psychiatric research. Weighted Gene Co-expression Network Analysis (WGCNA) enables the reduction of genome-wide expression data to modules of highly co-expressed genes, which are hypothesized to interact within molecular networks. In this study, we first applied WGCNA to zebrafish brain expression data across different experimental conditions. Then, we characterized the different co-expression modules by gene-set enrichment analysis and hub gene-phenotype association. Finally, we analyzed association of polygenic risk scores (PRSs) based on genes of some interesting co-expression modules with alcohol dependence in 524 patients and 729 controls from Galicia, using competitive tests. Our approach revealed 34 co-expression modules in the zebrafish brain, with some showing enrichment in human synaptic genes, brain tissues, or brain developmental stages. Moreover, certain co-expression modules were enriched in psychiatry-related GWAS and comprised hub genes associated with psychiatry-related traits in both human GWAS and zebrafish models. Expression patterns of some co-expression modules were associated with the tested experimental conditions, mainly with substance withdrawal and cold stress. Notably, a PRS based on genes from co-expression modules exclusively associated with substance withdrawal in zebrafish showed a stronger association with human alcohol dependence than PRSs based on randomly selected brain-expressed genes. In conclusion, our analysis led to the identification of co-expressed gene modules that may model human brain gene networks involved in psychiatry-related traits. Specifically, we detected a cluster of co-expressed genes whose expression was exclusively associated with substance withdrawal in zebrafish, which significantly contributed to alcohol dependence susceptibility in humans.

Genetic susceptibility for schizophrenia after adjustment by genetic susceptibility for smoking: implications in identification of risk genes and genetic correlation with related traits.

BACKGROUND: Prevalence of smoking in schizophrenia (SCZ) is larger than in general population. Genetic studies provided some evidence of a causal effect of smoking on SCZ. We aim to characterize the genetic susceptibility to SCZ affected by genetic susceptibility to smoking. METHODS: Multi-trait-based conditional and joint analysis was applied to the largest European SCZ genome-wide association studies (GWAS) to remove genetic effects on SCZ driven by smoking, estimated by generalized summary data-based Mendelian randomization. Enrichment analysis was performed to compare original v. conditional GWAS. Change in genetic correlation between SCZ and relevant traits after conditioning was assessed. Colocalization analysis was performed to identify specific loci confirming general findings. RESULTS: Conditional analysis identified 19 new risk loci for SCZ and 42 lost loci whose association with SCZ may be partially driven by smoking. These results were strengthened by colocalization analysis. Enrichment analysis indicated a higher association of differentially expressed genes at prenatal brain stages after conditioning. Genetic correlation of SCZ with substance use and dependence, attention deficit-hyperactivity disorder, and several externalizing traits significantly changed after conditioning. Colocalization of association signal between SCZ and these traits was identified for some of the lost loci, such as CHRNA2, CUL3, and PCDH7. CONCLUSIONS: Our approach led to identification of potential new SCZ loci, loci partially associated to SCZ through smoking, and a shared genetic susceptibility between SCZ and smoking behavior related to externalizing phenotypes. Application of this approach to other psychiatric disorders and substances may lead to a better understanding of the role of substances on mental health.

A polygenic approach to the association between smoking and schizophrenia.

Smoking prevalence in schizophrenia is considerably larger than in general population, playing an important role in early mortality. We compared the polygenic contribution to smoking in schizophrenic patients and controls to assess if genetic factors may explain the different prevalence. Polygenic risk scores (PRSs) for smoking initiation and four genetically correlated traits were calculated in 1108 schizophrenic patients (64.4% smokers) and 1584 controls (31.1% smokers). PRSs for smoking initiation, educational attainment, body mass index and age at first birth were associated with smoking in patients and controls, explaining a similar percentage of variance in both groups. Attention-deficit hyperactivity disorder (ADHD) PRS was associated with smoking only in schizophrenia. This association remained significant after adjustment by psychiatric cross-disorder PRS. A PRS combining all the traits was more explanative than smoking initiation PRS alone, indicating that genetic susceptibility to the other traits plays an additional role in smoking behaviour. Smoking initiation PRS was also associated with schizophrenia in the whole sample, but the significance was lost after adjustment for smoking status. This same pattern was observed in the analysis of specific SNPs at the CHRNA5-CHRNA3-CHRNB4 cluster associated with both traits. Overall, the results indicate that the same genetic factors are involved in smoking susceptibility in schizophrenia and in general population and are compatible with smoking acting, directly or indirectly, as a risk factor for schizophrenia that contributes to the high prevalence of smoking in these patients. The contrasting results for ADHD PRS may be related to higher ADHD symptomatology in schizophrenic patients.

Colocalization of association signals at nicotinic acetylcholine receptor genes between schizophrenia and smoking traits.

BACKGROUND: Epidemiological data suggest that smoking may be a risk factor for schizophrenia (SCZ), but more evidence is needed. Two regions coding nicotinic acetylcholine receptor (nAchR) subunits, atCHRNA2 and the CHRNA5/A3/B4 cluster, were associated with SCZ in genome-wide association studies (GWAS). Additionally, a signal at CHRNA4 is near significance. CHRNA2 was also associated with cannabis use disorder (CUD). These regions were also associated with smoking behaviors. If tobacco is a risk factor, the GWAS signals at smoking behaviors and SCZ have to be due to the same causal variants, i.e. they have to colocalize, although colocalization does not necessarily imply causality. Here, we present colocalization analysis at these loci between SCZ and smoking behaviors. METHODS: The Bayesian approach implemented in coloc was used to check for posterior probability of colocalization versus independent signals at the three loci with some evidence of association with SCZ and smoking behaviors, using GWAS summary statistics. Colocalization was also assessed for positive control traits and CUD. Three different sensibility analyses were used to confirm the results. A visualization tool, LocusCompare, was used to facilitate interpretation of the coloc results. RESULTS: Evidence for colocalization of GWAS signals between SCZ and smoking behaviors was found for CHRNA2. Evidence for independent causal variants was found for the other two loci. CUD GWAS signal at CHRNA2 colocalizes with SCZ and smoking behaviors. CONCLUSIONS: Overall, the results indicate that the association between some nAchR subunit genes and SCZ cannot be solely explained by their effect on smoking behaviors.

Is the "Habsburg jaw" related to inbreeding?

Background: The "Habsburg jaw" has long been associated with inbreeding due to the high prevalence of consanguineous marriages in the Habsburg dynasty. However, it is thought that mandibular prognathism (MP) is under the influence of a dominant major gene.Aim: To investigate the relationship between the "Habsburg jaw" and the pedigree-based inbreeding coefficient (F) as a relative measure of genome homozygosity.Subjects and methods: The degree of MP and maxillary deficiency (MD) of 15 members of the Habsburg dynasty was quantified through the clinical analysis of 18 dysmorphic features diagnosed from 66 portraits.Results: A statistically significant correlation (r = 0.711, p = 0.003) between MP and MD was observed among individuals. Only MP showed a statistically significant positive regression on F as evidenced from univariate analysis (b = 6.36 ± 3.34, p = 0.040) and multivariate analysis (PCA) performed from single dysmorphic features (b = 14.10 ± 6.62, p = 0.027, for the first PC).Conclusion: Both MP and MD are generally involved in the "Habsburg jaw." The results showed a greater sensitivity to inbreeding for the lower third of the face and suggest a positive association between the "Habsburg jaw" and homozygosity and therefore a basically recessive inheritance pattern.