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Abstract Background The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits. Methods To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs. Results Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection. Conclusions Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.

Identification of gene expression changes between healthy and diseased individuals can reveal mechanistic insights and biomarkers. Here, the authors propose a bi-directional transcriptome-wide Mendelian Randomization approach to assess causal effects between gene expression and complex traits.

Many genetic variants identified in genome-wide association studies are associated with gene expression. Here, Porcu et al. propose a transcriptome-wide summary statistics-based Mendelian randomization approach (TWMR) that, applied to 43 human traits, uncovers hundreds of previously unreported gene–trait associations.

Human immunodeficiency virus (HIV) infection is associated with an increased risk of non-Hodgkin lymphoma (NHL). Even in the era of suppressive antiretroviral treatment, HIV-infected individuals remain at higher risk of developing NHL compared to the general population. To identify potential genetic risk loci, we performed case-control genome-wide association studies and a meta-analysis across three cohorts of HIV+ patients of European ancestry, including a total of 278 cases and 1924 matched controls. We observed a significant association with NHL susceptibility in the C-X-C motif chemokine ligand 12 (CXCL12) region on chromosome 10. A fine mapping analysis identified rs7919208 as the most likely causal variant (P = 4.77e-11), with the G>A polymorphism creating a new transcription factor binding site for BATF and JUND. These results suggest a modulatory role of CXCL12 regulation in the increased susceptibility to NHL observed in the HIV-infected population.

Down syndrome (DS, trisomy 21), is the most common viable chromosomal disorder, with an incidence of 1 in 800 live births. Its phenotypic characteristics include intellectual impairment and several other developmental abnormalities, for the majority of which the pathogenetic mechanisms remain unknown. In this “Data in Brief” paper, we sum up the whole genome analysis by mRNA sequencing of normal and DS induced pluripotent stem cells that was recently published by Hibaoui et al. in EMBO molecular medicine.

DNA methylation is essential in mammalian development. We have hypothesized that methylation differences induced by trisomy 21 (T21) contribute to the phenotypic characteristics and heterogeneity in Down syndrome (DS). In order to determine the methylation differences in T21 without interference of the interindividual genomic variation, we have used fetal skin fibroblasts from monozygotic (MZ) twins discordant for T21. We also used skin fibroblasts from MZ twins concordant for T21, normal MZ twins without T21, and unrelated normal and T21 individuals. Reduced Representation Bisulfite Sequencing (RRBS) revealed 35 differentially methylated promoter regions (DMRs) (Absolute methylation differences = 25%, FDR < 0.001) in MZ twins discordant for T21 that have also been observed in comparison between unrelated normal and T21 individuals. The identified DMRs are enriched for genes involved in embryonic organ morphogenesis (FDR = 1.60 e -03) and include genes of the HOXB and HOXD clusters. These DMRs are maintained in iPS cells generated from this twin pair and are correlated with the gene expression changes. We have also observed an increase in DNA methylation level in the T21 methylome compared to the normal euploid methylome. This observation is concordant with the up regulation of DNA methyltransferase enzymes (DNMT3B and DNMT3L) and down regulation of DNA demethylation enzymes (TET2 and TET3) observed in the iPSC of the T21 versus normal twin. Altogether, the results of this study highlight the epigenetic effects of the extra chromosome 21 in T21 on loci outside of this chromosome that are relevant to DS associated phenotypes.

Schizophrenia (SCZ) is a severe, debilitating mental illness which has a significant genetic component. The identification of genetic factors related to SCZ has been challenging and these factors remain largely unknown. To evaluate the contribution of de novo variants (DNVs) to SCZ, we sequenced the exomes of 53 individuals with sporadic SCZ and of their non-affected parents. We identified 49 DNVs, 18 of which were predicted to alter gene function, including 13 damaging missense mutations, 2 conserved splice site mutations, 2 nonsense mutations, and 1 frameshift deletion. The average number of exonic DNV per proband was 0.88, which corresponds to an exonic point mutation rate of 1.7×10(-8) per nucleotide per generation. The non-synonymous-to-synonymous mutation ratio of 2.06 did not differ from neutral expectations. Overall, this study provides a list of 18 putative candidate genes for sporadic SCZ, and when combined with the results of similar reports, identifies a second proband carrying a non-synonymous DNV in the RGS12 gene.