Biology subjects

Schierding, W.

Publications and source records attributed to Schierding, W..

12 recordsLinked to original sources

bioRxiv2025

Mendelian randomizations with spatial gene networks reveal shared and distinct drivers of risk in major skin cancer types

Skin cancer is the most common malignancy worldwide, comprising three major types: melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). A critical goal in advancing our understanding of skin cancer is to identify the shared and distinct biological mechanisms that drive the risk profiles for each skin cancer type. In this study, we integrated tissue-specific chromatin conformation and expression quantitative trait loci data (spatial eQTL) to construct gene regulatory networks (GRNs) for melanocytes, sun-exposed skin, not sun-exposed skin, and blood. These GRNs, which capture spatially regulated gene expressions, were used as instrumental variables along with GWAS summary statistics for melanoma, BCC and SCC, to infer causal relationships between specific gene expression changes and each type of skin cancer. These Mendelian randomization analyses identified 82, 62, and 125 causal genes for melanoma, BCC, and SCC, respectively, with many of these genes not evident from the GWAS data alone. Our analyses revealed distinct mechanisms for each skin cancer type: telomere maintenance and nevus pathways in melanoma, inherited immune traits in BCC, and p53 dysfunction in SCC. Notably, apoptosis and pigmentation emerged as shared biological processes across skin cancers. These findings provide new insights into the genetic drivers of three distinct skin cancers, highlighting new gene targets which can be used to increase diagnostic precision, as well as potential therapeutic targets.

bioinformatics↗

bioRxiv2024

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes

Investigations of the non-coding region are essential for uncovering the full spectrum of genetic drivers in melanoma. Here, we map distal, non-coding, promoter-interacting regulatory elements using Hi-C data from melanoma cells and integrating these with whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes. We identified eight recurrently mutated hotspots that are melanoma-specific, alter transcription factor binding motifs, and affect the expression of genes (e.g. HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumor suppressors/oncogenes. Our study integrates multiple levels of biological data to uncover novel melanoma-specific non-coding candidate drivers beyond the well-characterized TERT promoter.

genomics↗

bioRxiv2021

Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

Background & AimsNon-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. MethodsHere, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and ConclusionsWe demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

genetics↗

bioRxiv2021

Genetic Variation as a Long-Distance Modulator of RAD21 Expression in Humans

Mutations and changes in expression in RAD21 are common across cancers types and outside of cancer can result in cohesinopathy. As such, exploration of variants that modify RAD21 enhancer activity, across the genome, may also provide insights into mechanisms by which distinct variants impact healthy human development and disease. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes, enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions which impact cancer onset and a potential for diagnostics.

bioinformatics↗

bioRxiv2021

Establishing gene regulatory networks from Parkinson's disease risk loci

The latest meta-analysis of genome wide association studies (GWAS) identified 90 independent single nucleotide polymorphisms (SNPs) across 78 genomic regions associated with Parkinsons disease (PD), yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with PD-SNPs, we utilised an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci; eQTL) data. We identified 518 genes subject to regulation by 76 PD-SNPs across 49 tissues, that encompass 36 peripheral and 13 CNS tissues. Notably, one third of these genes were regulated via trans-acting mechanisms (distal; risk locus-gene separated by > 1Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-eQTL-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and PD GWAS loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neuro-development specific eQTL-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of PD. Through utilising Louvain clustering we extracted nine significant and highly intra-connected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with PD. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of PD-SNPs, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of PD.

genetics↗

bioRxiv2021

Unravelling the shared genetic mechanisms underlying 18 autoimmune diseases using a systems approach

Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.

systems biology↗

bioRxiv2020

A transcription regulatory network within the ACE2 locus may promote a pro-viral environment for SARS-CoV-2 by modulating expression of host factors.

IntroductionA novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was recently identified as the pathogen responsible for the COVID-19 outbreak. SARS-CoV-2 triggers severe pneumonia, which leads to acute respiratory distress syndrome and death in severe cases. As reported, SARS-CoV-2 is 80% genetically identical to the 2003 SARS-CoV virus. Angiotensin-converting enzyme 2 (ACE2) has been identified as the main receptor for entry of both SARS-CoV and SARS-CoV-2 into human cells. ACE2 is normally expressed in cardiovascular and lung type II alveolar epithelial cells, where it positively modulates the RAS system that regulates blood flow, pressure, and fluid homeostasis. Thus, virus-induced reduction of ACE2 gene expression is considered to make a significant contribution to severe acute respiratory failure. Chromatin remodeling plays a significant role in the regulation of ACE2 gene expression and the activity of regulatory elements within the genome. MethodsHere, we integrated data on physical chromatin interactions within the genome organization (captured by Hi-C) with tissue-specific gene expression data to identify spatial expression quantitative trait loci (eQTLs) and thus regulatory elements located within the ACE2 gene. ResultsWe identified regulatory elements within ACE2 that control the expression of PIR, CA5B, and VPS13C in the lung. The gene products of these genes are involved in inflammatory responses, de novo pyrimidine and polyamine synthesis, and the endoplasmic reticulum, respectively. ConclusionOur study, although limited by the fact that the identification of the regulatory interactions is putative until proven by targeted experiments, supports the hypothesis that viral silencing of ACE2 alters the activity of gene regulatory regions and promotes an intra-cellular environment suitable for viral replication.

genomics↗

bioRxiv2020

Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways

Variants in DNA regulatory elements can alter the regulation of distant genes through spatial-regulatory connections. In humans, these spatial-regulatory connections are largely set during early development, when the cohesin complex plays an essential role in genome organisation and cell division. A full complement of the cohesin complex and its regulators is important for normal development, since heterozygous mutations in genes encoding these components are often sufficient to produce a disease phenotype. The implication that genes encoding the cohesin complex and cohesin regulators must be tightly controlled and resistant to variability in expression has not yet been formally tested. Here, we identify spatial-regulatory connections with potential to regulate expression of cohesin loci, including linking their expression to that of other genes. Connections that centre on the cohesin ring subunits (Mitotic: SMC1A, SMC3, STAG1, STAG2, RAD21/RAD21-AS; Meiotic: SMC1B, STAG3, REC8, RAD21L1), cohesin-ring support genes (NIPBL, MAU2, WAPL, PDS5A and PDS5B), and CTCF provide evidence of coordinated regulation that has little tolerance for perturbation. We identified transcriptional changes across a set of genes co-regulated with the cohesin loci that include biological pathways such as extracellular matrix production and proteasome-mediated protein degradation. Remarkably, many of the genes that are co-regulated with cohesin loci are themselves intolerant to loss-of-function. The results highlight the importance of robust regulation of cohesin genes, indicating novel pathways that may be important in the human cohesinopathy disorders.

bioinformatics↗

bioRxiv2019

Shared regulatory pathways reveal novel genetic correlations between grip strength and neuromuscular disorders

BackgroundMuscle weakness and muscle wasting can be a consequence of aging (sarcopenia) and neuromuscular disorders (NMD). Genome-wide association (GWA) studies have identified genetic variants associated with grip strength (GS, an inverse measure of muscle weakness) and NMD (multiple sclerosis (MS), myasthenia gravis (MG) and amyotrophic lateral sclerosis (ALS)). However, how these variants contribute to the muscle weakness caused by aging or NMD remains obscure.\n\nMethodsWe have integrated GS and NMD associated SNPs in a multimorbid analysis that leverages high-throughput chromatin interaction (Hi-C) data and expression quantitative trait loci (eQTL) data to identify allele-specific gene regulation (i.e. eGenes). Pathways and shared drug targets that are enriched by colocalised eGenes were then identified using pathway and drug enrichment analysis.\n\nResultsWe identified gene regulatory mechanisms (eQTL-eGene effects) associated with GS, MG, MS and ALS. The eQTLs associated with GS regulate a subset of eGenes that are also regulated by the eQTLs of MS, MG and ALS. Yet, we did not find any eGenes commonly regulated by all four phenotypes associated eQTLs. By contrast, we identified three pathways (mTOR signaling, axon guidance, and alcoholism) that are commonly affected by the gene regulatory mechanisms associated with all four phenotypes. 13% of the eGenes we identified were known drug targets, and GS shares at least one druggable eGene and pathway with each of the NMD phenotypes.\n\nConclusionsCollectively, these findings identify significant biological overlaps between GS and NMD, demonstrating the potential for spatial genetic analysis to identify mechanisms underlying muscle weakness due to aging and NMD.

genetics↗

bioRxiv2019

Reconstructing the blood metabolome and genotype using long-range chromatin interactions

The mechanisms of metabolism comprise a large number of biochemical pathways with a myriad of poorly characterised genetic influences. In this study, we perform a systematic integration of chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated single nucleotide polymorphisms (SNPs). We identify 577 genes that are regulated via chromatin looping to 130 distal and proximal SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. These novel SNP-gene-metabolite associations are a valuable resource for understanding the molecular mechanisms guiding pathologic metabolite levels in human tissues, and for further investigation into disease diagnosis and therapy.

molecular biology↗

bioRxiv2018

Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities

Clinical studies of non-communicable diseases identify multimorbidities that reflect our relatively limited fixed metabolic capacity. Despite the fact that we have [~]24000 genes, we do not understand the genetic pathways that contribute to the development of multimorbid non-communicable disease. We created a \"multimorbidity atlas\" of traits based on pleiotropy of spatially regulated genes using convex biclustering. Using chromatin interaction and expression Quantitative Trait Loci (eQTL) data, we analysed 20,782 variants (p < 5 x 10-6) associated with 1,351 phenotypes, to identify 16,248 putative eQTL-eGene pairs that are involved in 76,013 short- and long-range regulatory interactions (FDR < 0.05) in different human tissues. Convex biclustering of eGenes that are shared between phenotypes identified complex inter-relationships between nominally different phenotype associated SNPs. Notably, the loci at the centre of these inter-relationships were subject to complex tissue and disease specific regulatory effects. The largest cluster, 40 phenotypes that are related to fat and lipid metabolism, inflammatory disorders, and cancers, is centred on the FADS1-FADS3 locus (chromosome 11). Our novel approach enables the simultaneous elucidation of variant interactions with genes that are drivers of multimorbidity and those that contribute to unique phenotype associated characteristics.

bioinformatics↗

bioRxiv2017

Variants at the ADAMTS13, BGALT5, SSBP2 and TKT Loci are associated with Post-term birth.

Gestation is a crucial timepoint in human development. Deviation from a term gestational age correlates with both acute and long-term adverse health effects for the child. Both being born pre and post-term, i.e. having short and long gestational ages, are heritable and influenced by the pre- and perinatal environment. Despite the obvious heritable component, specific genetic influences underlying differences in gestational age are poorly understood. Here we identify one globally significant intronic genetic variant within the ADAMTS13 gene that is associated with prolonged gestation in 9,141 white European individuals from the 1966 and 1986 Northern Finland birth cohorts. Additional variants that reached suggestive levels of significance were identified within introns at the TKT, and ARGHAP42 genes, and in the upstream (5) intergenic regions of the B3GALT5 and SSBP2 genes. The variants near the ADAMTS13, B3GALT5, SSBP2 and TKT loci are linked to alterations in gene expression levels (cis-eQTLs). Luciferase assays confirmed the allele specific enhancer activity for the BGALT5 and TKT loci. Our findings provide the first evidence of a specific genetic influence associated with prolonged gestation.

genetics↗