Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the ...correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r
). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples (Formula: see text for cis-eQTLs and Formula: see text for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.
Previous transcriptome studies of the human endometrium have revealed hundreds of simultaneously up- and down-regulated genes that are involved in endometrial receptivity. However, the overlap ...between the studies is relatively small, and we are still searching for potential diagnostic biomarkers. Here we perform a meta-analysis of endometrial-receptivity associated genes on 164 endometrial samples (76 from 'pre-receptive' and 88 from mid-secretory, 'receptive' phase endometria) using a robust rank aggregation (RRA) method, followed by enrichment analysis, and regulatory microRNA prediction. We identify a meta-signature of endometrial receptivity involving 57 mRNA genes as putative receptivity markers, where 39 of these we confirm experimentally using RNA-sequencing method in two separate datasets. The meta-signature genes highlight the importance of immune responses, the complement cascade pathway and the involvement of exosomes in mid-secretory endometrial functions. Bioinformatic prediction identifies 348 microRNAs that could regulate 30 endometrial-receptivity associated genes, and we confirm experimentally the decreased expression of 19 microRNAs with 11 corresponding up-regulated meta-signature genes in our validation experiments. The 57 identified meta-signature genes and involved pathways, together with their regulatory microRNAs could serve as promising and sought-after biomarkers of endometrial receptivity, fertility and infertility.
Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five ...different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10
, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10
, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10
, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10
, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
The inner uterine lining (endometrium) is a unique tissue going through remarkable changes each menstrual cycle. Endometrium has its characteristic DNA methylation profile, although not much is known ...about the endometrial methylome changes throughout the menstrual cycle. The impact of methylome changes on gene expression and thereby on the function of the tissue, including establishing receptivity to implanting embryo, is also unclear. Therefore, this study used genome-wide technologies to characterize the methylome and the correlation between DNA methylation and gene expression in endometrial biopsies collected from 17 healthy fertile-aged women from pre-receptive and receptive phase within one menstrual cycle. Our study showed that the overall methylome remains relatively stable during this stage of the menstrual cycle, with small-scale changes affecting 5% of the studied CpG sites (22,272 out of studied 437,022 CpGs, FDR < 0.05). Of differentially methylated CpG sites with the largest absolute changes in methylation level, approximately 30% correlated with gene expression measured by RNA sequencing, with negative correlations being more common in 5' UTR and positive correlations in the gene 'Body' region. According to our results, extracellular matrix organization and immune response are the pathways most affected by methylation changes during the transition from pre-receptive to receptive phase.
The expression of genes in female reproductive organs is influenced by the cyclic changes in hormone levels during the menstrual cycle. While the molecular changes in the endometrium that facilitate ...embryo implantation have been extensively studied, there is limited knowledge about the impact of the menstrual cycle on cervical cells. Cervical cells can be easily and routinely collected using a cytobrush during gynecological examination, offering a standardized approach for diagnostic testing. In this study we investigated how the transcriptome of cervical cells changes during the menstrual cycle and assessed the utility of these cells to determine endometrial receptivity.
Endocervical cells were collected with cytobrushes from 16 healthy women at different menstrual cycle phases in natural cycles and from four women undergoing hormonal replacement cycles. RNA sequencing was applied to gain insight into the transcriptome of cervical cells.
Transcriptome analysis identified four differentially expressed genes (DEGs) between early- and mid-secretory samples, suggesting that the transcriptome of cervical cells does not change significantly during the opening of the implantation window. The most differences appeared during the transition to the late secretory phase (2136 DEGs) before the onset of menstruation. Cervical cells collected during hormonal replacement cycles showed 1899 DEGs enriched in immune system processes.
The results of our study suggested that cervical cells undergo moderate transcriptomic changes throughout the menstrual cycle; however, these changes do not reflect the gene expression pattern of endometrial tissue and offer little or no potential for endometrial receptivity diagnostics.
Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and ...trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 ...controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants.
Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap ...with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.
Abstract
STUDY QUESTION
Does cellular composition of the endometrial biopsy affect the gene expression profile of endometrial whole-tissue samples?
SUMMARY ANSWER
The differences in epithelial and ...stromal cell proportions in endometrial biopsies modify the whole-tissue gene expression profiles and affect the results of differential expression analyses.
WHAT IS ALREADY KNOWN
Each cell type has its unique gene expression profile. The proportions of epithelial and stromal cells vary in endometrial tissue during the menstrual cycle, along with individual and technical variation due to the method and tools used to obtain the tissue biopsy.
STUDY DESIGN, SIZE, DURATION
Using cell-population specific transcriptome data and computational deconvolution approach, we estimated the epithelial and stromal cell proportions in whole-tissue biopsies taken during early secretory and mid-secretory phases. The estimated cellular proportions were used as covariates in whole-tissue differential gene expression analysis. Endometrial transcriptomes before and after deconvolution were compared and analysed in biological context.
PARTICIPANTS/MATERIAL, SETTING, METHODS
Paired early- and mid-secretory endometrial biopsies were obtained from 35 healthy, regularly cycling, fertile volunteers, aged 23-36 years, and analysed by RNA sequencing. Differential gene expression analysis was performed using two approaches. In one of them, computational deconvolution was applied as an intermediate step to adjust for the proportions of epithelial and stromal cells in the endometrial biopsy. The results were then compared to conventional differential expression analysis. Ten paired endometrial samples were analysed with qPCR to validate the results.
MAIN RESULTS AND THE ROLE OF CHANCE
The estimated average proportions of stromal and epithelial cells in early secretory phase were 65% and 35%, and during mid-secretory phase, 46% and 54%, respectively, correlating well with the results of histological evaluation (r = 0.88, P = 1.1 × 10−6). Endometrial tissue transcriptomic analysis showed that approximately 26% of transcripts (n = 946) differentially expressed in receptive endometrium in cell-type unadjusted analysis also remain differentially expressed after adjustment for biopsy cellular composition. However, the other 74% (n = 2645) become statistically non-significant after adjustment for biopsy cellular composition, underlining the impact of tissue heterogeneity on differential expression analysis. The results suggest new mechanisms involved in endometrial maturation, involving genes like LINC01320, SLC8A1 and GGTA1P, described for the first time in context of endometrial receptivity.
LARGE-SCALE DATA
The RNA-seq data presented in this study is deposited in the Gene Expression Omnibus database with accession number GSE98386.
LIMITATIONS REASONS FOR CAUTION
Only dominant endometrial cell types were considered in gene expression profile deconvolution; however, other less frequent endometrial cell types also contribute to the whole-tissue gene expression profile.
WIDER IMPLICATIONS OF THE FINDINGS
The better understanding of molecular processes during transition from pre-receptive to receptive endometrium serves to improve the effectiveness and personalization of assisted reproduction protocols. Biopsy cellular composition should be taken into account in future endometrial 'omics' studies, where tissue heterogeneity could potentially influence the results.
STUDY FUNDING/COMPETING INTEREST(S)
This study was funded by: Estonian Ministry of Education and Research (grant IUT34-16); Enterprise Estonia (EU48695); the EU-FP7 Eurostars program (NOTED, EU41564); the EU-FP7 Marie Curie Industry-Academia Partnerships and Pathways (SARM, EU324509); Horizon 2020 innovation program (WIDENLIFE, EU692065); MSCA-RISE-2015 project MOMENDO (No 691058) and the Miguel Servet Program Type I of Instituto de Salud Carlos III (CP13/00038); Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and European Regional Development Fund (FEDER): grants RYC-2016-21199 and ENDORE SAF2017-87526. Authors confirm no competing interests.
Introduction
Implantation failure after transferring morphologically “good‐quality” embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired ...endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short‐term or long‐term implantation outcomes (ie success or failure).
Material and methods
Mid‐luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA‐sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone LH‐day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short‐term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long‐term analysis included 46/107 women (23 ‘fertile’ group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo‐timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation).
Results
There were no significantly differentially expressed genes between implantation failure and success groups in either the short‐term or long‐term analyses. Principal component analysis initially showed two clusters in the long‐term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non‐pregnant group compared with the ongoing pregnant group in the short‐term analysis.
Conclusions
No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.
No distinct endometrial transcriptome profile associated with either implantation failure or success in infertile women in either the short term and long term was found, but there may be differences in the extent to which the window of implantation is displaced.
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