A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease

Abstract Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16, P = 5.6 × 10− 4 in the discovery and OR = 1.30, P = 1.8 × 10− 6 in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52–2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94–1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology

Epidemiological investigations of circulating biomarkers for cardiometabolic diseases

Abstract Cardiometabolic diseases are a leading cause of morbidity and mortality worldwide. Although common risk factors are well known, there has been no success in changing the growing trend in these diseases. An earlier detection of underlying harmful changes in the body, as well as a deeper understanding of the biological changes related to these diseases, could help in the early prevention and development of novel treatment strategies. Different omics technologies combined with a large population and clinical cohorts allow for a more detailed exploration of the biological changes related to various diseases. In the current thesis, these methodologies were first utilised to explore the metabolic changes associated with incident stroke and its subtypes. The first study identified 10 metabolic measures associated with incident strokes. Second, metabolomic data, together with clinical variables, were used to investigate the metabolic characteristics of mortality risk among coronary angiography patients. Furthermore, the predictive properties of metabolic measures in mortality risk prediction were assessed. The second study demonstrated that metabolic changes associated with all-cause mortality were present also when controlling for important clinical variables. The metabolic measures slightly improved discrimination at the cost of calibration compared to clinical variables when assessing the utility of these measures in the prediction of all-cause mortality. Third, the potential role of circulating inflammatory cytokines as mediators in the pathway from increased adiposity measured by body mass index to relevant disease outcomes was assessed. The third study identified three cytokines driven by body mass index. Only weak associations were seen when further assessing the causal role of the identified cytokines in different inflammatory-related diseases. In conclusion, this thesis illustrates the utility of the application of omics data in three different epidemiological settings to study the mechanisms related to cardiometabolic diseases.Tiivistelmä Kardiometaboliset sairaudet ovat suurimpia sairastavuuden ja kuolleisuuden aiheuttajia maailmanlaajuisesti. Vaikka yleisimmät riskitekijät näille sairauksille tunnetaan hyvin, kasvavaa trendiä näiden sairauksien osalta ei ole kyetty muuttamaan. Kehossa olevien piilevien muutosten aikaisempi tunnistaminen sekä näihin sairauksiin liittyvien biologisten muutosten syvempi ymmärtäminen voisi auttaa varhaisessa ehkäisyssä sekä uusien hoitomuotojen kehittämisessä. Erilaiset omiikkateknologiat yhdistettyinä suuriin kliinisiin ja väestöaineistoihin mahdollistavat sairauksiin liittyvien erilaisten biologisten muutosten entistä tarkemman tarkastelun. Tässä väitöskirjassa näitä menetelmiä on hyödynnetty ensinnäkin aivohalvauksiin ja sen alatyyppeihin liittyvien aineenvaihduntamuutosten selvittämiseen. Ensimmäinen osatyö tunnisti kymmenen aineenvaihduntamuuttujaa, jotka olivat yhteydessä aivohalvauksiin. Toisessa työssä aineenvaihduntamuuttujia käytettiin kuolleisuuteen yhteydessä olevien metabolisten muutoksien selvittämiseen sydämen varjoainekuvauspotilailla. Lisäksi metabolisten muuttujien tuomaa lisähyötyä kliinisten muuttujien lisäksi kuolleisuusriskin ennustamisessa arvioitiin. Toinen osatyö osoitti, että aineenvaihduntamuutoksia on havaittavissa, vaikka analyysissä huomioitaisiin tärkeät kliiniset muuttujat. Aineenvaihduntamuuttujat paransivat hieman ennustemallin erottelukykyä kokonaiskuolleisuuden ennustamisessa, mutta samalla systemaattinen harha hieman lisääntyi verrattuna pelkkien kliinisten muuttujien käyttöön. Kolmanneksi verenkierron tulehdusproteiinien roolia painoindeksillä mitatun liikalihavuuden ja erilaisten relevanttien sairauksien syy-seuraussuhteiden välittäjinä arvioitiin. Kolmas osatyö tunnisti kolme painoindeksiin yhteydessä olevaa tulehdusproteiinia. Arvioitaessa näiden tulehdusproteiinien syy-seuraussuhteita eri tulehduksellisiin sairauksiin, nähtiin vain heikkoja yhteyksiä. Yhteenvetona tämä väitöskirjatyö osoittaa erilaisten omiikka-aineistojen soveltamisen hyödyn kardiometabolisiin sairauksiin liittyvien mekanismien tutkimisessa kolmea eri epidemiologista tutkimusasetelmaa hyödyntäen

Association of Circulating Metabolites in Plasma or Serum and Risk of Stroke Meta-analysis From 7 Prospective Cohorts

Objective To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings. Methods We investigated the association of metabolites with risk of stroke in 7 prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by nuclear magnetic resonance technology. The relationship between metabolites and stroke was assessed with Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately. Results The analyses revealed 10 significant metabolite associations. Amino acid histidine (hazard ratio [HR] per SD 0.90, 95% confidence interval [CI] 0.85, 0.94; p = 4.45 x 10-5), glycolysis-related metabolite pyruvate (HR per SD 1.09, 95% CI 1.04, 1.14; p = 7.45 x 10-4), acute-phase reaction marker glycoprotein acetyls (HR per SD 1.09, 95% CI 1.03, 1.15; p = 1.27 x 10-3), cholesterol in high-density lipoprotein (HDL) 2, and several other lipoprotein particles were associated with risk of stroke. When focused on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD 1.12, 95% CI 1.05, 1.19; p = 4.13 x 10-4) and total and free cholesterol in large HDL particles. Conclusions We found association of amino acids, glycolysis-related metabolites, acute-phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke.Peer reviewe

Genome-wide association study identifies seven novel loci associating with circulating cytokines and cell adhesion molecules in Finns

Abstract Background: Inflammatory processes contribute to the pathophysiology of multiple chronic conditions. Genetic factors play a crucial role in modulating the inflammatory load, but the exact mechanisms are incompletely understood. Objective: To assess genetic determinants of 16 circulating cytokines and cell adhesion molecules (inflammatory phenotypes) in Finns. Methods: Genome-wide associations of the inflammatory phenotypes were studied in Northern Finland Birth Cohort 1966 (N=5284). A subsequent meta-analysis was completed for 10 phenotypes available in a previous genome-wide association study, adding up to 13 577 individuals in the study. Complementary association tests were performed to study the effect of the ABO blood types on soluble adhesion molecule levels. Results: We identified seven novel and six previously reported genetic associations (p<3.1×10−9). Three loci were associated with soluble vascular cell adhesion molecule-1 (sVCAM-1) level, one of which was the ABO locus that has been previously associated with soluble E-selectin (sE-selectin) and intercellular adhesion molecule-1 (sICAM-1) levels. Our findings suggest that the blood type B associates primarily with sVCAM-1 level, while the A1 subtype shows a robust effect on sE-selectin and sICAM-1 levels. The genotypes in the ABO locus associating with higher soluble adhesion molecule levels tend to associate with lower circulating cholesterol levels and lower cardiovascular disease risk. Conclusion: The present results extend the knowledge about genetic factors contributing to the inflammatory load. Our findings suggest that two distinct mechanisms contribute to the soluble adhesion molecule levels in the ABO locus and that elevated soluble adhesion molecule levels per se may not increase risk for cardiovascular disease

The role of inflammatory cytokines as intermediates in the pathway from increased adiposity to disease

Abstract Objective: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease. Methods: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI‐driven cytokines on risk of obesity‐related diseases. Results: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein‐1 (MCP‐1), and tumor necrosis factor–related apoptosis‐inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08‐1.19), 1.08 (95% CI: 1.04‐1.14), and 1.13 (95% CI: 1.04‐1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00‐1.06). There was inconsistent evidence for a protective role of MCP‐1 against inflammatory bowel diseases. Conclusions: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI‐driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation

Association of circulating metabolites in plasma or serum and risk of stroke:meta-analysis from seven prospective cohorts

Abstract Objective: To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings. Methods: We investigated the association of metabolites with risk of stroke in 7 prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by nuclear magnetic resonance technology. The relationship between metabolites and stroke was assessed with Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately. Results: The analyses revealed 10 significant metabolite associations. Amino acid histidine (hazard ratio [HR] per SD 0.90, 95% confidence interval [CI] 0.85, 0.94; p = 4.45 × 10−5), glycolysis-related metabolite pyruvate (HR per SD 1.09, 95% CI 1.04, 1.14; p = 7.45 × 10−4), acute-phase reaction marker glycoprotein acetyls (HR per SD 1.09, 95% CI 1.03, 1.15; p = 1.27 × 10−3), cholesterol in high-density lipoprotein (HDL) 2, and several other lipoprotein particles were associated with risk of stroke. When focused on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD 1.12, 95% CI 1.05, 1.19; p = 4.13 × 10−4) and total and free cholesterol in large HDL particles. Conclusions: We found association of amino acids, glycolysis-related metabolites, acute-phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke

Additional file 1 of A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease

Additional file 1