0000000001320296

AUTHOR

Christian Herder

showing 7 related works from this author

Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

2022

Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…

Data Integrationeducation.field_of_studyComputer scienceScale (chemistry)Bayesian probabilityPopulationQuantitative Trait LociBiological databaseInferenceData Integration ; Machine Learning ; Multi-omics ; Network Inference ; Personalized Medicine ; Prior Information ; Simulation ; Systems BiologyComputational biologyQuantitative trait locusReplication (computing)Machine LearningPrior probabilityCohortGeneticsMolecular MedicineHumans:Medicine [Science]Gene Regulatory NetworkseducationTranscriptomeMolecular BiologyGenetics (clinical)Genome medicine
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Duffy antigen receptor for chemokines (Darc) polymorphism regulates circulating concentrations of monocyte chemoattractant protein-1 and other inflam…

2010

AbstractTo identify the genetic basis of circulating concentrations of monocyte chemoattractant protein-1 (MCP-1), we conducted genome-wide association analyses for MCP-1 in 3 independent cohorts (n = 9598). The strongest association was for serum MCP-1 with a nonsynonymous polymorphism, rs12075 (Asp42Gly) in DARC, the gene for Duffy antigen receptor for chemokines, a known vascular reservoir of proinflammatory cytokines (minor allele frequency, 45.6%; P < 1.0 * 10−323). This association was supported by family-based genetic linkage at a locus encompassing the DARC gene (genome-wide P = 8.0 * 10−13). Asp42Gly accounted for approximately 20% of the variability in serum MCP-1 concentration…

AdultMaleCCR2ChemokineErythrocytesImmunologyReceptors Cell SurfacePolymorphism Single NucleotideBiochemistryProinflammatory cytokineCohort StudiesmedicineHumansCytokine bindingReceptorInterleukin 6Chemokine CCL2biologyMonocyteCell BiologyHematologyMiddle AgedMolecular biologymedicine.anatomical_structureChromosomes Human Pair 1Genetic LociImmunologybiology.proteinFemaleInterleukin 18Inflammation MediatorsDuffy Blood-Group SystemGenome-Wide Association StudyBlood
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Transcriptome-Wide Analysis Identifies Novel Associations With Blood Pressure.

2017

Hypertension represents a major cardiovascular risk factor. The pathophysiology of increased blood pressure (BP) is not yet completely understood. Transcriptome profiling offers possibilities to uncover genetics effects on BP. Based on 2 populations including 2549 individuals, a meta-analyses of monocytic transcriptome-wide profiles were performed to identify transcripts associated with BP. Replication was performed in 2 independent studies of whole-blood transcriptome data including 1990 individuals. For identified candidate genes, a direct link between long-term changes in BP and gene expression over time and by treatment with BP-lowering therapy was assessed. The predictive value of pro…

0301 basic medicineMaleCandidate geneGene ExpressionGenome-wide association studyBlood Pressure030204 cardiovascular system & hematologyCardiorespiratory Medicine and HaematologyCardiovascularLMNATranscriptome0302 clinical medicineRisk FactorsCEBPAGene expression2.1 Biological and endogenous factorsAetiologyGeneticsMyelin and Lymphocyte-Associated Proteolipid ProteinsBlood Pressure ; Gene Expression ; Genome-wide Association Study ; Hypertension ; Transcriptomeblood pressureGenomicsSingle NucleotideLIM Domain Proteinsblood pressure; gene expression; genome-wide association study; hypertension; transcriptomeStrokeHeart DiseaseHypertensionPublic Health and Health ServicesBiomarker (medicine)FemaleEssential HypertensionPoly(ADP-ribose) PolymerasesBiotechnologyAdulthypertensionClinical SciencesNucleoside Transport ProteinsBiologyPolymorphism Single NucleotideArticle03 medical and health sciencesClinical ResearchInternal MedicineGeneticsHumansPolymorphismgenome-wide association studyGene Expression ProfilingHuman GenomeBlood Pressure DeterminationGene expression profiling030104 developmental biologyGood Health and Well BeingCardiovascular System & Hematologygene expressionCCAAT-Enhancer-Binding ProteinsCarrier ProteinstranscriptomeTranscription Factors
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Analyzing Illumina Gene Expression Microarray Data from Different Tissues: Methodological Aspects of Data Analysis in the MetaXpress Consortium

2012

Microarray profiling of gene expression is widely applied in molecular biology and functional genomics. Experimental and technical variations make meta-analysis of different studies challenging. In a total of 3358 samples, all from German population-based cohorts, we investigated the effect of data preprocessing and the variability due to sample processing in whole blood cell and blood monocyte gene expression data, measured on the Illumina HumanHT-12 v3 BeadChip array. Gene expression signal intensities were similar after applying the log(2) or the variance-stabilizing transformation. In all cohorts, the first principal component (PC) explained more than 95% of the total variation. Technic…

MicroarraysArray ProcessingClinical Research DesignScienceGene ExpressionSingle-nucleotide polymorphismBiologyPolymorphism Single NucleotideMolecular Genetics03 medical and health sciencesEngineering0302 clinical medicineGenome Analysis ToolsGermanyWhite blood cellGene expressionGenome-Wide Association StudiesGeneticsmedicineHumansGenome SequencingStatistical MethodsBiologyOligonucleotide Array Sequence Analysis030304 developmental biologyWhole bloodGenetics0303 health sciencesMultidisciplinaryGene Expression ProfilingQRComputational BiologyReproducibility of ResultsHuman GeneticsGenomicsGene expression profilingMinor allele frequencymedicine.anatomical_structure030220 oncology & carcinogenesisSignal ProcessingMedicineRNA extractionFunctional genomicsResearch ArticlePLoS ONE
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Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study

2021

Abstract It is still unclear how genetic information, provided as single‐nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population‐based case‐cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo); selection of the most predictive SNPs among these literature‐co…

Oncologymedicine.medical_specialtyEpidemiologyFramingham Risk Score ; Metabochip ; Coronary Heart Disease ; Genomic Risk Prediction ; Priority-lassoPopulationCoronary DiseaseSingle-nucleotide polymorphismKoronare HerzkrankheitPolymorphism Single NucleotideRisk AssessmentCohort Studies03 medical and health sciencesRisk FactorsInternal medicinemedicineHumansgenomic risk predictionddc:610coronary heart diseaseMetabochipGenetikeducationGenotypingGenetics (clinical)030304 developmental biologypriority‐Lasso0303 health scienceseducation.field_of_studyFramingham Risk ScoreModels GeneticProportional hazards modelbusiness.industry030305 genetics & heredityGenomicsConfidence intervalddc:Coronary disease; GeneticsRisk factorsCohortFramingham risk scorebusinessDDC 610 / Medicine & healthPredictive modelling
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Additional file 1 of Network reconstruction for trans acting genetic loci using multi-omics data and prior information

2022

Additional file 1 Supplementary material, supporting figures and tables.

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Additional file 2 of Network reconstruction for trans acting genetic loci using multi-omics data and prior information

2022

Additional file 2 Supplementary tables, large supporting tables with table titles as tabs.

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