The effect of non-coding variants on gene transcription in human blood cell types

To understand complex genetic diseases it is necessary to study DNA, its transcription, translation and regulation thereof. In a mechanistic view diseases can be caused by alterations in the DNA sequence or by dysregulation of gene expression. To understand cell regulation, first connections have to be found between elements contributing to gene expression and its regulation. During my PhD I have studied the regulatory effects of human genetic variation. To do so I have processed and analysed datasets measuring effects of genetic variants on transcript levels of genes, identified regulatory variants and put them in bigger biochemical and physiological context. Expression quantitative trait locus (eQTL) studies identify genetically explainable gene expression variation in a tissue and potentially cell type specific manner. I have reprocessed and aggregated eQTL datasets of seven purified blood cell types that were generated by collaborators in different laboratories. I showed that the increased sample size enables the identification of additional associations, also with low-frequency variants, and I compared my cell type specific eQTL results to results from an eQTL study performed on whole blood without cell type purification. Gene regulation is complex and relies on several layers of control, and only one of them is genetic background. To help understand genetic control, I compared my eQTL results across the seven cell types and highlighted cell type specific associations. I put my eQTL results into bigger context, overlapping them with genomic regions, which are known to be important for gene regulation. Apart from the direct interpretation, eQTL results have been used as a tool to help improve the understanding of results from genome-wide association studies (GWAS) by means of colocalisation. I performed a colocalisation analysis and as an example I could show how a GWAS variant mechanistically exerts its effect on plateletcrit - a blood cell index studied in a recent GWAS (Astle et al., 2016). Finally, I drew a link between gene-regulation, three-dimensional chromatin structure and gene constraint against coding loss of function mutations. Complementing association analyses like eQTL and GWAS, recent advances in machine learning can be used to predict in silico the effects of genetic variation. To facilitate the application of published machine learning models on custom data and to predict biological effects of genetic variants, I have developed, in collaboration with a fellow PhD student, Ziga Avsec (Prof. Julien Gagneur's group, TU Munich, Germany), the software Kipoi (www.kipoi.org). The software has been designed to facilitate sharing and re-use of trained machine learning models in genomics. Together with Ziga Avsec I have conceptualised and implemented core elements of the platform. My major contribution in this software project was the implementation of tools and features for the effect estimation of DNA variants

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

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

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

This is the final version of the article. It first appeared from Elsevier (Cell Press) via https://doi.org/10.1016/j.cell.2016.09.03

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility

Immune-Signatures for Lung Cancer Diagnostics: Evaluation of Protein Microarray Data Normalization Strategies

New minimal invasive diagnostic methods for early detection of lung cancer are urgently needed. It is known that the immune system responds to tumors with production of tumor-autoantibodies. Protein microarrays are a suitable highly multiplexed platform for identification of autoantibody signatures against tumor-associated antigens (TAA). These microarrays can be probed using 0.1 mg immunoglobulin G (IgG), purified from 10 µL of plasma. We used a microarray comprising recombinant proteins derived from 15,417 cDNA clones for the screening of 100 lung cancer samples, including 25 samples of each main histological entity of lung cancer, and 100 controls. Since this number of samples cannot be processed at once, the resulting data showed non-biological variances due to “batch effects”. Our aim was to evaluate quantile normalization, “distance-weighted discrimination” (DWD), and “ComBat” for their effectiveness in data pre-processing for elucidating diagnostic immune‑signatures. “ComBat” data adjustment outperformed the other methods and allowed us to identify classifiers for all lung cancer cases versus controls and small-cell, squamous cell, large-cell, and adenocarcinoma of the lung with an accuracy of 85%, 94%, 96%, 92%, and 83% (sensitivity of 0.85, 0.92, 0.96, 0.88, 0.83; specificity of 0.85, 0.96, 0.96, 0.96, 0.83), respectively. These promising data would be the basis for further validation using targeted autoantibody tests

G protein-coupled receptor kinase 5 regulates thrombin signaling in platelets via PAR-1.

The interindividual variation in the functional response of platelets to activation by agonists is heritable. Genome-wide association studies (GWASs) of quantitative measures of platelet function have identified fewer than 20 distinctly associated variants, some with unknown mechanisms. Here, we report GWASs of pathway-specific functional responses to agonism by adenosine 5'-diphosphate, a glycoprotein VI-specific collagen mimetic, and thrombin receptor-agonist peptides, each specific to 1 of the G protein-coupled receptors PAR-1 and PAR-4, in subsets of 1562 individuals. We identified an association (P = 2.75 × 10-40) between a common intronic variant, rs10886430, in the G protein-coupled receptor kinase 5 gene (GRK5) and the sensitivity of platelets to activate through PAR-1. The variant resides in a megakaryocyte-specific enhancer that is bound by the transcription factors GATA1 and MEIS1. The minor allele (G) is associated with fewer GRK5 transcripts in platelets and the greater sensitivity of platelets to activate through PAR-1. We show that thrombin-mediated activation of human platelets causes binding of GRK5 to PAR-1 and that deletion of the mouse homolog Grk5 enhances thrombin-induced platelet activation sensitivity and increases platelet accumulation at the site of vascular injury. This corroborates evidence that the human G allele of rs10886430 is associated with a greater risk for cardiovascular disease. In summary, by combining the results of pathway-specific GWASs and expression quantitative trait locus studies in humans with the results from platelet function studies in Grk5-/- mice, we obtain evidence that GRK5 regulates the human platelet response to thrombin via the PAR-1 pathway

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology

Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes—including cell-type specific measures of granularity, nucleic acid content and reactivity—in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types—variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.

Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types-variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.

Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types-variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology

Abstract Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes—including cell-type specific measures of granularity, nucleic acid content and reactivity—in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types—variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease