Biology subjects

Mannisto, S.

Publications and source records attributed to Mannisto, S..

3 recordsLinked to original sources

bioRxiv2019

Search for early pancreatic cancer blood biomarkers in five European prospective population biobanks using metabolomics

Background and aimMost patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. MethodsThe low incidence rate complicates prospective biomarker studies. Here, we took advantage of the availability of biobanked samples from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian biobank, Rotterdam Study) and identified prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between one month and seventeen years after blood sampling, and compared these with age- and gender-matched controls from the same cohorts. We applied 1H-NMR-based metabolomics on the Nightingale platform on these samples and applied logistic regression to assess the predictive value of individual metabolite concentrations, with gender, age, body mass index, smoking status, type 2 diabetes mellitus status, fasting status, and cohort as covariates. ResultsAfter quality assessment, we retained 356 cases and 887 controls. We identified two interesting hits, glutamine (p=0.011) and histidine (p=0.012), and obtained Westfall-Young family-wise error rate adjusted p-values of 0.43 for both. Stratification in quintiles showed a 1.5x elevated risk for the lowest 20% of glutamine and a 2.2x increased risk for the lowest 20% of histidine. Stratification by time to diagnosis (<2 years, 2-5 years, >5 years) suggested glutamine to be involved in an earlier process, tapering out closer to onset, and histidine in a process closer to the actual onset. Lasso-penalized logistic regression showed a slight improvement of the area under the Receiver Operator Curves when including glutamine and histidine in the model. Finally, our data did not support the earlier identified branched-chain amino acids as potential biomarkers for pancreatic cancer in several American cohorts. ConclusionWhile identifying glutamine and histidine as early biomarkers of potential biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

epidemiology↗

bioRxiv2018

The landscape of incident disease risk for the biomarker GlycA and its mortality stratification in angiography patients

Integration of systems-level biomolecular information with electronic health records has led to the discovery of robust blood-based biomarkers predictive of future health and disease. Of recent intense interest is the GlycA biomarker, a complex nuclear magnetic resonance (NMR) spectroscopy signal reflective of acute and chronic inflammation, which predicts long term risk of diverse outcomes including cardiovascular disease, type 2 diabetes, and all-cause mortality. To systematically explore the specificity of the disease burden indicated by GlycA we analysed the risk for 468 common incident hospitalization and mortality outcomes occurring during an 8-year follow-up of 11,861 adults from Finland. Our analyses of GlycA replicated known associations, identified associations with specific cardiovascular disease outcomes, and uncovered new associations with risk of alcoholic liver disease (meta-analysed hazard ratio 2.94 per 1-SD, P=5x10-6), chronic renal failure (HR=2.47, P=3x10-6), glomerular diseases (HR=1.95, P=1x10-6), chronic obstructive pulmonary disease (HR=1.58, P=3x10-5), inflammatory polyarthropathies (HR=1.46, P=4x10-8), and hypertension (HR=1.21, P=5x10-5). We further evaluated GlycA as a biomarker in secondary prevention of 12-year cardiovascular mortality in 900 angiography patients with suspected coronary artery disease. We observed hazard ratios of 4.87 and 5.00 for 12-year mortality in angiography patients in the fourth and fifth quintiles by GlycA levels demonstrating the prognostic potential of GlycA for identification of high mortality-risk individuals. Both GlycA and C-reactive protein had shared as well as independent contributions to mortality hazard, emphasising the importance of chronic inflammation in secondary prevention of cardiovascular disease.

epidemiology↗

bioRxiv2016

An interaction map of circulating metabolites, immune gene networks and their genetic regulation

The interaction between metabolism and the immune system plays a central role in many cardiometabolic diseases. We integrated blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts, including a subset with 7-year follow-up sampling. We identified topologically robust gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules showed complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) revealed five modules with mQTLs of both cis and trans effects. The strongest mQTL was in ARHGEF3 (rs1354034) and affected a module enriched for platelet function. Mast cell/basophil and neutrophil function modules maintained their metabolite associations during 7-year follow-up, while our strongest mQTL in ARHGEF3 also displayed clear temporal stability. This study provides a detailed map of natural variation at the blood immuno-metabolic interface and its genetic basis, and facilitates subsequent studies to explain inter-individual variation in cardiometabolic disease.

genomics↗