Erratum to: Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross

BACKGROUND: The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. RESULTS: A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. CONCLUSIONS: In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing insight into the molecular and genetic background of complex traits in cattle and will help to understand molecular networks involved

Assessment of causality of natriuretic peptides and atrial fibrillation and heart failure : a Mendelian randomization study in the FINRISK cohort

Aims Natriuretic peptides are extensively studied biomarkers for atrial fibrillation (AF) and heart failure (HF). Their role in the pathogenesis of both diseases is not entirely understood and previous studies several single-nucleotide poly-morphisms (SNPs) at the NPPA-NPPB locus associated with natriuretic peptides have been identified. We investigated the causal relationship between natriuretic peptides and AF as well as HF using a Mendelian randomization approach. Methods and results N-terminal pro B-type natriuretic peptide (NT-proBNP) (N= 6669), B-type natriuretic peptide (BNP) (N= 6674), and mid-regional pro atrial natriuretic peptide (MR-proANP) (N= 6813) were measured in the FINRISK 1997 cohort. N=30 common SNPs related to NT-proBNP, BNP, and MR-proANP were selected from studies. We performed six Mendelian randomizations for all three natriuretic peptide biomarkers and for both outcomes, AF and HF, separately. Polygenic risk scores (PRSs) based on multiple SNPs were used as genetic instrumental variable in Mendelian randomizations. Polygenic risk scores were significantly associated with the three natriuretic peptides. Polygenic risk scores were not significantly associated with incident AF nor HF. Most cardiovascular risk factors showed significant confounding percentages, but no association with PRS. A causal relation except for small causal betas is unlikely. Conclusion In our Mendelian randomization approach, we confirmed an association between common genetic variation at the NPPA-NPPB locus and natriuretic peptides. A strong causal relationship between natriuretic peptides and incidence of AF as well as HF at the community-level was ruled out. Therapeutic approaches targeting natriuretic peptides will therefore very likely work through indirect mechanisms.Peer reviewe

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation.

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

Extended data: Tissue-specific multi-omics analysis of atrial fibrillation

Summary statistics and result repository for the publication Tissue-specific multi-omics analysis of atrial fibrillation: Assum, I., Krause, J., Scheinhardt, M.O. et al. Tissue-specific multi-omics analysis of atrial fibrillation. Nat Commun 13, 441 (2022). https://doi.org/10.1038/s41467-022-27953-1 For the related source code, see https://doi.org/https://doi.org/10.5281/zenodo.5094276 or https://github.com/heiniglab/symatrial. Ines Assum1,2,†, Julia Krause3,4,†, Markus O. Scheinhardt5, Christian Müller3,4, Elke Hammer6,7, Christin S. Börschel4,8, Uwe Vöker6,7, Lenard Conradi9, Bastiaan Geelhoed4,8,10, Tanja Zeller3,4,*, Renate B. Schnabel4,8,*, Matthias Heinig1,2,11,* † ,* These authors contributed equally. 1 Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany. 2 Department of Informatics, Technical University Munich, München, Germany. 3 University Center of Cardiovascular Science, University Heart and Vascular Center Hamburg, Hamburg, Germany. 4 Partner site Hamburg/Kiel/Lübeck, DZHK (German Center for Cardiovascular Research), Hamburg, Germany. 5 Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany. 6 Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany. 7 Partner site Greifswald, DZHK (German Center for Cardiovascular Research), Greifswald, Germany. 8 Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany. 9 Department of Cardiovascular Surgery, University Heart and Vascular Center Hamburg, Hamburg, Germany. 10 Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 11Partner site Munich, DZHK (German Center for Cardiovascular Research), Munich, Germany. ABSTRACT: Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted transQTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization. This version adds a reference file identifying effect alleles for all QTL results. TABLE OF CONTENTS: Reference for effect alleles map_AFHRI_B_effect_alleles.txt Single-omic cis-QTL results cis-eQTLs (all pairs, incl. LD clump info) eQTL_right_atrial_appendage_allpairs_clump.txt cis-pQTLs (all pairs, incl. LD clump info) pQTL_right_atrial_appendage_allpairs_clump.txt cis-res eQTLs (all pairs, incl. LD clump info) res_eQTL_right_atrial_appendage_allpairs_clump.txt cis-res pQTLs (all pairs, incl. LD clump info) res_pQTL_right_atrial_appendage_allpairs_clump.txt cis-ratioQTLs (all pairs, incl. LD clump info) ratioQTL_right_atrial_appendage_allpairs_clump.txt Functional cis-QTL categories and eQTL/pQTL overlap: All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with a significant eQTL and pQTL (FDR<0.05) Fig2a_source_data_Shared_eQTL_pQTL_clump.txt All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with a significant eQTL but no pQTL (FDR<0.05) Fig2b_source_data_Independent_eQTL_clump.txt All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with no eQTL but a significant pQTL (FDR<0.05) Fig2c_source_data_Independent_pQTL_clump.txt QTS rankings and enrichment results eQTS rankings and enrichments TableS6_source_data_eQTS_ranking.txt TableS7_source_data_eQTS_GSEA_results.txt pQTS rankings and enrichments TableS8_source_data_pQTS_ranking.txt TableS9_source_data_pQTS_GSEA_results.txt Trans-QTLs all tested pairs including trans-pQTLs for trans-eQTLs and trans-eQTLs for trans-pQTLs Table2_source_data_Trans-QTL_results.tx

Extended data: Tissue-specific multi-omics analysis of atrial fibrillation

Summary statistics and result repository for the publication Tissue-specific multi-omics analysis of atrial fibrillation (https://doi.org/10.1101/2020.04.06.021527). For the related source code, see https://doi.org/https://doi.org/10.5281/zenodo.5094276 or https://github.com/heiniglab/symatrial. ABSTRACT: Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted transQTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization