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Johannes Kettunen

Publications and source records attributed to Johannes Kettunen.

4 recordsLinked to original sources

Genome-wide association study identifies 17 new loci influencing concentrations of circulating cytokines and growth factors

Circulating cytokines and growth factors are regulators of inflammation and have been implicated in autoimmune and metabolic diseases. In this genome-wide association study (GWAS) up to n=8,293 Finns we identified 27 loci with genome-wide association (P-value<1.2x10-9) for one or more cytokines, including 17 unidentified in previous GWASes. Fifteen of the associated SNPs had expression quantitative trait loci in whole blood. We provide strong genetic instruments to clarify the causal roles of cytokine signaling and upstream inflammation in immune-related and other chronic diseases. We further link known autoimmune disease variants including Crohn's disease, multiple sclerosis and ulcerative colitis with new inflammatory markers, which elucidate the molecular mechanisms underpinning these diseases and suggest potential drug targets.

Genomics

Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems

Mergeomics is a computational pipeline (http://mergeomics.research.idre.ucla.edu/Download/Package/) that integrates multidimensional omics-disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. It first identifies biological pathways and tissue-specific gene subnetworks that are perturbed by disease-associated molecular entities. The disease-associated subnetworks are then projected onto tissue-specific gene-gene interaction networks to identify local hubs as potential key drivers of pathological perturbations. The pipeline is modular and can be applied across species and platform boundaries, and uniquely conducts pathway/network level meta-analysis of multiple genomic studies of various data types. Application of Mergeomics to cholesterol datasets revealed novel regulators of cholesterol metabolism.

Systems Biology

Systems medicine links microbial inflammatory response with glycoprotein-associated mortality risk

Integrative analyses of high-throughput omics data have elucidated the aetiology and pathogenesis for complex traits and diseases1-4, and the linking of omics information to electronic health records promises new insights into human health and disease. Recent nuclear magnetic resonance (NMR) spectroscopy biomarker profiling has implicated glycoprotein acetyls (GlycA) as a biomarker for cardiovascular risk5 and all-cause mortality6. To elucidate biological processes contributing to GlycA-associated mortality risk, we leveraged human omics data from three population-based cohorts together with nation-wide Finnish hospital and mortality records. Elevated GlycA was associated with myriad infection-related inflammatory processes. Within individuals, elevated GlycA levels were stable over long time periods, up to a decade, and chronically elevated GlycA was also associated with modest elevation of numerous cytokines. Individuals with elevated GlycA also showed increased expression of a transcriptional sub-network, the Neutrophil Degranulation Module (NDM), suggesting an increased activity of microbe-driven immune response. Subsequent analysis of nation-wide hospitalisation and death records was consistent with a microbial basis for GlycA-associated mortality, with each standard deviation increase in GlycA raising an individuals future risk of hospitalization and death from non-localized infection by 40% and 136%, respectively. These results show that, beyond its established role in acute-phase response7-9, elevated GlycA is more broadly a biomarker for low-grade chronic inflammation and increased neutrophil activity. Further, increased risk of susceptibility to severe microbial-infection events in healthy individuals suggests this inflammation is a contributor to mortality risk. Taken together, this study demonstrates the power of an integrative approach that combines omics data and health records to delineate the biological processes underlying a newly discovered biomarker, providing a model strategy for future systems medicine studies.

Genomics

Cell specific eQTL analysis without sorting cells

Expression quantitative trait locus (eQTL) mapping on tissue, organ or whole organism data can detect associations that are generic across cell types. We describe a new method to focus upon specific cell types without first needing to sort cells. We applied the method to whole blood data from 5,683 samples and demonstrate that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils.

Genetics