Browsing by Subject "metabolomics"

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  • Holma, Paula (Helsingfors universitet, 2011)
    Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.
  • Hämäläinen, Kreetta (Helsingin yliopisto, 2021)
    Personalized medicine tailors therapies for the patient based on predicted risk factors. Some tools used for making predictions on the safety and efficacy of drugs are genetics and metabolomics. This thesis focuses on identifying biomarkers for the activity level of the drug transporter organic anion transporting polypep-tide 1B1 (OATP1B1) from data acquired from untargeted metabolite profiling. OATP1B1 transports various drugs, such as statins, from portal blood into the hepatocytes. OATP1B1 is a genetically polymorphic influx transporter, which is expressed in human hepatocytes. Statins are low-density lipoprotein cholesterol-lowering drugs, and decreased or poor OATP1B1 function has been shown to be associated with statin-induced myopathy. Based on genetic variability, individuals can be classified to those with normal, decreased or poor OATP1B1 function. These activity classes were employed to identify metabolomic biomarkers for OATP1B1. To find the most efficient way to predict the activity level and find the biomarkers that associate with the activity level, 5 different machine learning models were tested with a dataset that consisted of 356 fasting blood samples with 9152 metabolite features. The models included both a Random Forest regressor and a classifier, Gradient Boosted Decision Tree regressor and classifier, and a Deep Neural Network regressor. Hindrances specific for this type of data was the collinearity between the features and the large amount of features compared to the number of samples, which lead to issues in determining the important features of the neural network model. To adjust to this, the data was clustered according to their Spearman’s rank-order correlation ranks. Feature importances were calculated using two methods. In the case of neural network, the feature importances were calculated with permutation feature importance using mean squared error, and random forest and gradient boosted decision trees used gini impurity. The performance of each model was measured, and all classifiers had a poor ability to predict decreasead and poor function classes. All regressors performed very similarly to each other. Gradient boosted decision tree regressor performed the best by a slight margin, but random forest regressor and neural network regressor performed nearly as well. The best features from all three models were cross-referenced with the features found from y-aware PCA analysis. The y-aware PCA analysis indicated that 14 best features cover 95% of the explained variance, so 14 features were picked from each model and cross-referenced with each other. Cross-referencing highest scoring features reported by the best models found multiple features that showed up as important in many models.Taken together, machine learning methods provide powerful tools to identify potential biomarkers from untargeted metabolomics data.
  • Vogt, Susanne; Wahl, Simone; Kettunen, Johannes; Breitner, Susanne; Kastenmueller, Gabi; Gieger, Christian; Suhre, Karsten; Waldenberger, Melanie; Kratzsch, Juergen; Perola, Markus; Salomaa, Veikko; Blankenberg, Stefan; Zeller, Tanja; Soininen, Pasi; Kangas, Antti J.; Peters, Annette; Grallert, Harald; Ala-Korpela, Mika; Thorand, Barbara (2016)
    Background: Numerous observational studies have observed associations between vitamin D deficiency and cardiometabolic diseases, but these findings might be confounded by obesity. A characterization of the metabolic profile associated with serum 25-hydroxyvitamin D [25(OH)D] levels, in general and stratified by abdominal obesity, may help to untangle the relationship between vitamin D, obesity and cardiometabolic health. Methods: Serum metabolomics measurements were obtained from a nuclear magnetic resonance spectroscopy (NMR)- and a mass spectrometry (MS)-based platform. The discovery was conducted in 1726 participants of the population-based KORA-F4 study, in which the associations of the concentrations of 415 metabolites with 25(OH)D levels were assessed in linear models. The results were replicated in 6759 participants (NMR) and 609 (MS) participants, respectively, of the population-based FINRISK 1997 study. Results: Mean [standard deviation (SD)] 25(OH)D levels were 15.2 (7.5) ng/ml in KORA F4 and 13.8 (5.9) ng/ml in FINRISK 1997; 37 metabolites were associated with 25(OH) D in KORA F4 at P <0.05/415. Of these, 30 associations were replicated in FINRISK 1997 at P <0.05/37. Among these were constituents of (very) large very-low-density lipoprotein and small low-density lipoprotein subclasses and related measures like serum triglycerides as well as fatty acids and measures reflecting the degree of fatty acid saturation. The observed associations were independent of waist circumference and generally similar in abdominally obese and non-obese participants. Conclusions: Independently of abdominal obesity, higher 25(OH)D levels were associated with a metabolite profile characterized by lower concentrations of atherogenic lipids and a higher degree of fatty acid polyunsaturation. These results indicate that the relationship between vitamin D deficiency and cardiometabolic diseases is unlikely to merely reflect obesity-related pathomechanisms.
  • Eloranta, Katja; Cairo, Stefano; Liljeström, Emmi; Soini, Tea; Kyrönlahti, Antti; Judde, Jean-Gabriel; Wilson, David B.; Heikinheimo, Markku; Pihlajoki, Marjut (2020)
    Background:Hepatoblastoma (HB) is the most common pediatric liver malignancy. Despite advances in chemotherapeutic regimens and surgical techniques, the survival of patients with advanced HB remains poor, underscoring the need for new therapeutic approaches. Chloroquine (CQ), a drug used to treat malaria and rheumatologic diseases, has been shown to inhibit the growth and survival of various cancer types. We examined the antineoplastic activity of CQ in cell models of aggressive HB. Methods:Seven human HB cell models, all derived from chemoresistant tumors, were cultured as spheroids in the presence of relevant concentrations of CQ. Morphology, viability, and induction of apoptosis were assessed after 48 and 96 h of CQ treatment. Metabolomic analysis and RT-qPCR based Death Pathway Finder array were used to elucidate the molecular mechanisms underlying the CQ effect in a 2-dimensional cell culture format. Quantitative western blotting was performed to validate findings at the protein level. Results:CQ had a significant dose and time dependent effect on HB cell viability both in spheroids and in 2-dimensional cell cultures. Following CQ treatment HB spheroids exhibited increased caspase 3/7 activity indicating the induction of apoptotic cell death. Metabolomic profiling demonstrated significant decreases in the concentrations of NAD(+)and aspartate in CQ treated cells. In further investigations, oxidation of NAD(+)decreased as consequence of CQ treatment and NAD(+)/NADH balance shifted toward NADH. Aspartate supplementation rescued cells from CQ induced cell death. Additionally, downregulated expression of PARP1 and PARP2 was observed. Conclusions:CQ treatment inhibits cell survival in cell models of aggressive HB, presumably by perturbing NAD(+)levels, impairing aspartate bioavailability, and inhibiting PARP expression. CQ thus holds potential as a new agent in the management of HB.
  • Lamichhane, Santosh; Ahonen, Linda; Dyrlund, Thomas Sparholt; Dickens, Alex M.; Siljander, Heli; Hyöty, Heikki; Ilonen, Jorma; Toppari, Jorma; Veijola, Riitta; Hyötyläinen, Tuulia; Knip, Mikael; Oresic, Matej (2019)
    Previous studies suggest that children who progress to type 1 diabetes (T1D) later in life already have an altered serum lipid molecular profile at birth. Here, we compared cord blood lipidome across the three study groups: children who progressed to T1D (PT1D; n = 30), children who developed at least one islet autoantibody but did not progress to T1D during the follow-up (P1Ab; n = 33), and their age-matched controls (CTR; n = 38). We found that phospholipids, specifically sphingomyelins, were lower in T1D progressors when compared to P1Ab and the CTR. Cholesterol esters remained higher in PT1D when compared to other groups. A signature comprising five lipids was predictive of the risk of progression to T1D, with an area under the receiver operating characteristic curve (AUROC) of 0.83. Our findings provide further evidence that the lipidomic profiles of newborn infants who progress to T1D later in life are different from lipidomic profiles in P1Ab and CTR.
  • Louca, Panayiotis; Nogal, Ana; Moskal, Aurelie; Goulding, Neil J.; Shipley, Martin J.; Alkis, Taryn; Lindbohm, Joni; Hu, Jie; Kifer, Domagoj; Wang, Ni; Chawes, Bo; Rexrode, Kathryn M.; Ben-Shlomo, Yoav; Kivimaki, Mika; Murphy, Rachel A.; Yu, Bing; Gunter, Marc J.; Suhre, Karsten; Lawlor, Deborah A.; Mangino, Massimo; Menni, Cristina (2022)
    Hypertension is the main modifiable risk factor for cardiovascular morbidity and mortality but discovering molecular mechanisms for targeted treatment has been challenging. Here we investigate associations of blood metabolite markers with hypertension by integrating data from nine intercontinental cohorts from the COnsortium of METabolomics Studies. We included 44,306 individuals with circulating metabolites (up to 813). Metabolites were aligned and inverse normalised to allow intra-platform comparison. Logistic models adjusting for covariates were performed in each cohort and results were combined using random-effect inverse-variance meta-analyses adjusting for multiple testing. We further conducted canonical pathway analysis to investigate the pathways underlying the hypertension-associated metabolites. In 12,479 hypertensive cases and 31,827 controls without renal impairment, we identified 38 metabolites, associated with hypertension after adjusting for age, sex, body mass index, ethnicity, and multiple testing. Of these, 32 metabolite associations, predominantly lipid (steroids and fatty acyls) and organic acids (amino-, hydroxy-, and keto-acids) remained after further adjusting for comorbidities and dietary intake. Among the identified metabolites, 5 were novel, including 2 bile acids, 2 glycerophospholipids, and ketoleucine. Pathway analysis further implicates the role of the amino-acids, serine/glycine, and bile acids in hypertension regulation. In the largest cross-sectional hypertension-metabolomics study to date, we identify 32 circulating metabolites (of which 5 novel and 27 confirmed) that are potentially actionable targets for intervention. Further in-vivo studies are needed to identify their specific role in the aetiology or progression of hypertension.
  • Manca, Maria Laura; Solini, Anna; Haukka, Jani K.; Sandholm, Niina; Forsblom, Carol; Groop, Per Henrik; Ferrannini, Ele (2021)
    Background: Chronic kidney disease (CKD) shows different clinical features in Types1 (T1D) and 2 diabetes (T2D). Metabolomics have recently provided useful contribution to the identification of biomarkers of CKD progression in either form of the disease. However, no studies have so far compared plasma metabolomics between T1D and T2D in order to identify differential signatures of progression of estimated glomerular filtration rate (eGFR) decline. Methods: We used two large cohorts of T1D (from Finland) and T2D (from Italy) patients followed up to 7 and 3 years, respectively. In both groups, progression was defined as the top quartile of yearly decline in eGFR. Pooled data from the two groups were analysed by univariate and bivariate random forest (RF), and confirmed by bivariate partial least squares (PLS) analysis, the response variables being type of diabetes and eGFR progression. Results: In progressors, yearly eGFR loss was significantly larger in T2D [-5.3 (3.0), median (interquartile range)mL/min/1.73 m2/year] than T1D [-3.7 (3.1) mL/min/1.73 m2/year; P = 0.018]. Out of several hundreds, bivariate RF extracted 22 metabolites associated with diabetes type (all higher in T1D than T2D except for 5-methylthioadenosine, pyruvate and β-hydroxypyruvate) and 13 molecules associated with eGFR progression (all higher in progressors than non-progressors except for sphyngomyelin). Three of the selected metabolites (histidylphenylalanine, leucylphenylalanine, tryptophylasparagine) showed a significant interaction between disease type and progression. Only eight metabolites were common to both bivariate RF and PLS. Conclusions: Identification of metabolomic signatures of CKD progression is partially dependent on the statistical model. Dual analysis identified molecules specifically associated with progressive renal impairment in both T1D and T2D.
  • Luukkonen, Panu K.; Qadri, Sami; Ahlholm, Noora; Porthan, Kimmo; Mannisto, Ville; Sammalkorpi, Henna; Penttilä, Anne K.; Hakkarainen, Antti; Lehtimäki, Tiina E.; Gaggini, Melania; Gastaldelli, Amalia; Ala-Korpela, Mika; Orho-Melander, Marju; Arola, Johanna; Juuti, Anne; Pihlajamäki, Jussi; Hodson, Leanne; Yki-Järvinen, Hannele (2022)
    Background & Aims: There is substantial inter-individual variability in the risk of non-alcoholic fatty liver disease (NAFLD). Part of which is explained by insulin resistance (IR) ('MetComp') and part by common modifiers of genetic risk ('GenComp'). We examined how IR on the one hand and genetic risk on the other contribute to the pathogenesis of NAFLD. Methods: We studied 846 individuals: 492 were obese patients with liver histology and 354 were individuals who underwent intrahepatic triglyceride measurement by proton magnetic resonance spectroscopy. A genetic risk score was calculated using the number of risk alleles in PNPLA3, TM6SF2, MBOAT7, HSD17B13 and MARC1. Substrate concentrations were assessed by serum NMR metabolomics. In subsets of participants, non-esterified fatty acids (NEFAs) and their flux were assessed by D-5-glycerol and hyperinsulinemic-euglycemic clamp (n = 41), and hepatic de novo lipogenesis (DNL) was measured by D2O (n = 61). Results: We found that substrate surplus (increased concentrations of 28 serum metabolites including glucose, glycolytic intermediates, and amino acids; increased NEFAs and their flux; increased DNL) characterized the 'MetComp'. In contrast, the 'GenComp' was not accompanied by any substrate excess but was characterized by an increased hepaticmitochondrial redox state, as determined by serum beta-hydroxybutyrate/acetoacetate ratio, and inhibition of hepatic pathways dependent on tricarboxylic acid cycle activity, such as DNL. Serum beta-hydroxybutyrate/acetoacetate ratio correlated strongly with all histological features of NAFLD. IR and hepatic mitochondrial redox state conferred additive increases in histological features of NAFLD. Conclusions: These data show that the mechanisms underlying 'Metabolic' and 'Genetic' components of NAFLD are fundamentally different. These findings may have implications with respect to the diagnosis and treatment of NAFLD. Lay summary: The pathogenesis of non-alcoholic fatty liver disease can be explained in part by a metabolic component, including obesity, and in part by a genetic component. Herein, we demonstrate that the mechanisms underlying these components are fundamentally different: the metabolic component is characterized by hepatic oversupply of substrates, such as sugars, lipids and amino acids. In contrast, the genetic component is characterized by impaired hepatic mitochondrial function, making the liver less able to metabolize these substrates. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver.
  • Wang, Qin; Wurtz, Peter; Auro, Kirsi; Morin-Papunen, Laure; Kangas, Antti J.; Soininen, Pasi; Tiainen, Mika; Tynkkynen, Tuulia; Joensuu, Anni; Havulinna, Aki S.; Aalto, Kristiina; Salmi, Marko; Blankenberg, Stefan; Zeller, Tanja; Viikari, Jorma; Kahonen, Mika; Lehtimaki, Terho; Salomaa, Veikko; Jalkanen, Sirpa; Jarvelin, Marjo-Riitta; Perola, Markus; Raitakari, Olli T.; Lawlor, Debbie A.; Kettunen, Johannes; Ala-Korpela, Mika (2016)
    Background: Hormonal contraception is commonly used worldwide, but its systemic effects across lipoprotein subclasses, fatty acids, circulating metabolites and cytokines remain poorly understood. Methods: A comprehensive molecular profile (75 metabolic measures and 37 cytokines) was measured for up to 5841 women (age range 24-49 years) from three population-based cohorts. Women using combined oral contraceptive pills (COCPs) or progestin-only contraceptives (POCs) were compared with those who did not use hormonal contraception. Metabolomics profiles were reassessed for 869 women after 6 years to uncover the metabolic effects of starting, stopping and persistently using hormonal contraception. Results: The comprehensive molecular profiling allowed multiple new findings on the metabolic associations with the use of COCPs. They were positively associated with lipoprotein subclasses, including all high-density lipoprotein (HDL) subclasses. The associations with fatty acids and amino acids were strong and variable in direction. COCP use was negatively associated with albumin and positively associated with creatinine and inflammatory markers, including glycoprotein acetyls and several growth factors and interleukins. Our findings also confirmed previous results e.g. for increased circulating triglycerides and HDL cholesterol. Starting COCPs caused similar metabolic changes to those observed cross-sectionally: the changes were maintained in consistent users and normalized in those who stopped using. In contrast, POCs were only weakly associated with metabolic and inflammatory markers. Results were consistent across all cohorts and for different COCP preparations and different types of POC delivery. Conclusions: Use of COCPs causes widespread metabolic and inflammatory effects. However, persistent use does not appear to accumulate the effects over time and the metabolic perturbations are reversed upon discontinuation. POCs have little effect on systemic metabolism and inflammation.
  • Määttä, Anne; Salminen, Aino; Pietiäinen, Milla; Leskelä, Jaakko; Palviainen, Teemu; Sattler, Wolfgang; Sinisalo, Juha; Salomaa, Veikko; Kaprio, Jaakko; Pussinen, Pirkko (2021)
    Our aim was to analyze whether endotoxemia, i.e. translocation of LPS to circulation, is reflected in the serum metabolic profile in a general population and in participants with cardiometabolic disorders. We investigated three Finnish cohorts separately and in a meta-analysis (n = 7178), namely population-based FINRISK97, FinnTwin16 consisting of young adult twins, and Parogene, a random cohort of cardiac patients. Endotoxemia was determined as serum LPS activity and metabolome by an NMR platform. Potential effects of body mass index (BMI), smoking, metabolic syndrome (MetS), and coronary heart disease (CHD) status were considered. Endotoxemia was directly associated with concentrations of VLDL, IDL, LDL, and small HDL lipoproteins, VLDL particle diameter, total fatty acids (FA), glycoprotein acetyls (GlycA), aromatic and branched-chain amino acids, and Glc, and inversely associated with concentration of large HDL, diameters of LDL and HDL, as well as unsaturation degree of FAs. Some of these disadvantageous associations were significantly stronger in smokers and subjects with high BMI, but did not differ between participants with different CHD status. In participants with MetS, however, the associations of endotoxemia with FA parameters and GlycA were particularly strong. The metabolic profile in endotoxemia appears highly adverse, involving several inflammatory characters and risk factors for cardiometabolic disorders.
  • Heinonen, Hanna-Riikka; Mehine, Miika; Mäkinen, Netta; Pasanen, Annukka; Pitkänen, Esa; Karhu, Auli; Sarvilinna, Nanna S.; Sjöberg, Jari; Heikinheimo, Oskari; Bützow, Ralf; Aaltonen, Lauri A.; Kaasinen, Eevi (2017)
    Background: Uterine leiomyomas can be classified into molecularly distinct subtypes according to their genetic triggers: MED12 mutations, HMGA2 upregulation, or inactivation of FH. The aim of this study was to identify metabolites and metabolic pathways that are dysregulated in different subtypes of leiomyomas. Methods: We performed global metabolomic profiling of 25 uterine leiomyomas and 17 corresponding myometrium specimens using liquid chromatography-tandem mass spectroscopy. Results: A total of 641 metabolites were detected. All leiomyomas displayed reduced homocarnosine and haeme metabolite levels. We identified a clearly distinct metabolomic profile for leiomyomas of the FH subtype, characterised by metabolic alterations in the tricarboxylic acid cycle and pentose phosphate pathways, and increased levels of multiple lipids and amino acids. Several metabolites were uniquely elevated in leiomyomas of the FH subtype, including N6-succinyladenosine and argininosuccinate, serving as potential biomarkers for FH deficiency. In contrast, leiomyomas of the MED12 subtype displayed reduced levels of vitamin A, multiple membrane lipids and amino acids, and dysregulation of vitamin C metabolism, a finding which was also compatible with gene expression data. Conclusions: The study reveals the metabolomic heterogeneity of leiomyomas and provides the requisite framework for strategies designed to target metabolic alterations promoting the growth of these prevalent tumours.
  • Ottka, Claudia; Vapalahti, Katariina; Määttä, Ann-Marie; Huuskonen, Nanna; Sarpanen, Sinikka; Jalkanen, Liisa; Lohi, Hannes (2021)
    Background The kidneys have many essential metabolic functions, and metabolic disturbances during decreased renal function have not been studied extensively. Objectives To identify metabolic changes in blood samples with increased serum creatinine concentration, indicating decreased glomerular filtration. Animals Clinical samples analyzed using a nuclear magnetic resonance (NMR) based metabolomics platform. The case group consisted of 23 samples with serum creatinine concentration >125 mu mol/L, and the control group of 873 samples with serum creatinine concentration within the reference interval. Methods Biomarker association with increased serum creatinine concentration was evaluated utilizing 3 statistical approaches: Wilcoxon rank-sum test, logistic regression analysis (false discovery rate (FDR)-corrected P-values), and random forest classification. Medians of the biomarkers were compared to reference intervals. A heatmap and box plots were used to represent the differences. Results All 3 statistical approaches identified similar analytes associated with increased serum creatinine concentrations. The percentages of citrate, tyrosine, branched-chain amino acids, valine, leucine, albumin, linoleic acid and the ratio of phenylalanine to tyrosine differed significantly using all statistical approaches, acetate differed using the Wilcoxon test and random forest, docosapentaenoic acid percentage only using logistic regression (P <.05), and alanine only using random forest. Conclusions and Clinical Importance We identified several metabolic changes associated with increased serum creatinine concentrations, including prospective diagnostic markers and therapeutic targets. Further research is needed to verify the association of these changes with the clinical state of the dog. The NMR metabolomics test is a promising tool for improving diagnostic testing and management of renal diseases in dogs.
  • Lamichhane, Santosh; Siljander, Heli; Salonen, Marja; Ruohtula, Terhi; Virtanen, Suvi M.; Ilonen, Jorma; Hyötyläinen, Tuulia; Knip, Mikael; Oresic, Matej (2022)
    Background: Current evidence suggests that the composition of infant formula (IF) affects the gut microbiome, intestinal function, and immune responses during infancy. However, the impact of IF on circulating lipid profiles in infants is still poorly understood. The objectives of this study were to (1) investigate how extensively hydrolyzed IF impacts serum lipidome compared to conventional formula and (2) to associate changes in circulatory lipids with gastrointestinal biomarkers including intestinal permeability. Methods: In a randomized, double-blind controlled nutritional intervention study (n = 73), we applied mass spectrometry-based lipidomics to analyze serum lipids in infants who were fed extensively hydrolyzed formula (HF) or conventional, regular formula (RF). Serum samples were collected at 3, 9, and 12 months of age. Child's growth (weight and length) and intestinal functional markers, including lactulose mannitol (LM) ratio, fecal calprotectin, and fecal beta-defensin, were also measured at given time points. At 3 months of age, stool samples were analyzed by shotgun metagenomics. Results: Concentrations of sphingomyelins were higher in the HF group as compared to the RF group. Triacylglycerols (TGs) containing saturated and monounsaturated fatty acyl chains were found in higher levels in the HF group at 3 months, but downregulated at 9 and 12 months of age. LM ratio was lower in the HF group at 9 months of age. In the RF group, the LM ratio was positively associated with ether-linked lipids. Such an association was, however, not observed in the HF group. Conclusion: Our study suggests that HF intervention changes the circulating lipidome, including those lipids previously found to be associated with progression to islet autoimmunity or overt T1D.
  • Kivelä, Jemina; Sormunen-Harju, Heidi; Girchenko, Polina; Huvinen, Emilia; Stach-Lempinen, Beata; Kajantie, Eero; Villa, Pia M.; Reynolds, Rebecca M.; Hämäläinen, Esa K.; Lahti-Pulkkinen, Marius; Murtoniemi, Katja K.; Laivuori, Hannele; Eriksson, Johan G.; Räikkönen, Katri; Koivusalo, Saila B. (2021)
    Context: Comprehensive assessment of metabolism in maternal obesity and pregnancy disorders can provide information about the shared maternal-fetal milieu and give insight into both maternal long-term health and intergenerational transmission of disease burden. Objective: To assess levels, profiles, and change in the levels of metabolic measures during pregnancies complicated by obesity, gestational diabetes (GDM), or hypertensive disorders. Design, Setting and Participants: A secondary analysis of 2 study cohorts, PREDO and RADIEL, including 741 pregnant women. Main Outcome Measures: We assessed 225 metabolic measures by nuclear magnetic resonance in blood samples collected at median 13 [interquartile range (IQR) 12.4-13.7], 20 (IQR 19.3-23.0), and 28 (27.0-35.0) weeks of gestation. Results: Across all 3 time points women with obesity [body mass index (BMI) >= 30 kg/m(2)] in comparison to normal weight (BMI 18.5-24.99 kg/m(2)) had significantly higher levels of most very-low-density lipoprotein-related measures, many fatty and most amino acids, and more adverse metabolic profiles. The change in the levels of most metabolic measures during pregnancy was smaller in obese than in normal weight women. GDM, preeclampsia, and chronic hypertension were associated with metabolic alterations similar to obesity. The associations of obesity held after adjustment for GDM and hypertensive disorders, but many of the associations with GDM and hypertensive disorders were rendered nonsignificant after adjustment for BMI and the other pregnancy disorders. Conclusions: This study shows that the pregnancy-related metabolic change is smaller in women with obesity, who display metabolic perturbations already in early pregnancy. Metabolic alterations of obesity and pregnancy disorders resembled each other suggesting a shared metabolic origin.
  • Herrala, Maria; Turunen, Soile; Hanhineva, Kati; Lehtonen, Marko; Mikkonen, Jopi J. W.; Seitsalo, Hubertus; Lappalainen, Reijo; Tjäderhane, Leo; Niemelä, Raija K.; Salo, Tuula; Myllymaa, Sami; Kullaa, Arja M.; Kärkkäinen, Olli (2021)
    Saliva is a complex oral fluid, and plays a major role in oral health. Primary Sjogren's syndrome (pSS), as an autoimmune disease that typically causes hyposalivation. In the present study, salivary metabolites were studied from stimulated saliva samples (n = 15) of female patients with pSS in a group treated with low-dose doxycycline (LDD), saliva samples (n = 10) of non-treated female patients with pSS, and saliva samples (n = 14) of healthy age-matched females as controls. Saliva samples were analyzed with liquid chromatography mass spectrometry (LC-MS) based on the non-targeted metabolomics method. The saliva metabolite profile differed between pSS patients and the healthy control (HC). In the pSS patients, the LDD treatment normalized saliva levels of several metabolites, including tyrosine glutamine dipeptide, phenylalanine isoleucine dipeptide, valine leucine dipeptide, phenylalanine, pantothenic acid (vitamin B5), urocanic acid, and salivary lipid cholesteryl palmitic acid (CE 16:0), to levels seen in the saliva samples of the HC. In conclusion, the data showed that pSS is associated with an altered saliva metabolite profile compared to the HC and that the LLD treatment normalized levels of several metabolites associated with dysbiosis of oral microbiota in pSS patients. The role of the saliva metabolome in pSS pathology needs to be further studied to clarify if saliva metabolite levels can be used to predict or monitor the progress and treatment of pSS.
  • Tikkanen, Emmi; Jagerroos, Vilma; Holmes, Michael; Sattar, Naveed; Ala-Korpela, Mika; Jousilahti, Pekka; Lundqvist, Annamari; Perola, Markus; Salomaa, Veikko; Wurtz, Peter (2021)
    Background Peripheral artery disease (PAD) and coronary artery disease (CAD) represent atherosclerosis in different vascular beds. We used detailed metabolic biomarker profiling to identify common and discordant biomarkers and clarify pathophysiological differences for these vascular diseases. Methods and Results We used 5 prospective cohorts from Finnish population (FINRISK 1997, 2002, 2007, and 2012, and Health 2000; n=31 657; median follow-up time of 14 years) to estimate associations between >200 metabolic biomarkers and incident PAD and CAD. Metabolic biomarkers were measured with nuclear magnetic resonance, and disease events were obtained from nationwide hospital records. During the follow-up, 498 incident PAD and 2073 incident CAD events occurred. In age- and sex-adjusted Cox models, apolipoproteins and cholesterol measures were robustly associated with incident CAD (eg, hazard ratio [HR] per SD for higher apolipoprotein B/A-1 ratio, 1.30; 95% CI, 1.25-1.36), but not with incident PAD (HR per SD for higher apolipoprotein B/A-1 ratio, 1.04; 95% CI, 0.95-1.14; P-heterogeneity0.05). Lower proportion of polyunsaturated fatty acids relative to total fatty acids, and higher concentrations of monounsaturated fatty acids, glycolysis-related metabolites, and inflammatory protein markers were strongly associated with incident PAD, and many of these associations were stronger for PAD than for CAD (P-heterogeneity
  • Wurtz, Peter; Cook, Sarah; Wang, Qin; Tiainen, Mika; Tynkkynen, Tuulia; Kangas, Antti J.; Soininen, Pasi; Laitinen, Jaana; Viikari, Jorma; Kahonen, Mika; Lehtimaki, Terho; Perola, Markus; Blankenberg, Stefan; Zeller, Tanja; Mannisto, Satu; Salomaa, Veikko; Jarvelin, Marjo-Riitta; Raitakari, Olli T.; Ala-Korpela, Mika; Leon, David A. (2016)
    Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults. Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24-45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P<0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R-2 = 0.83, slope = 0.7260.04). Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.
  • Palviainen, Mari; Saari, Heikki; Kärkkäinen, Olli; Pekkinen, Jenna; Auriola, Seppo; Yliperttula, Marjo; Puhka, Maija; Hanhineva, Kati; Siljander, Pia R-M (2019)
    One of the greatest bottlenecks in extracellular vesicle (EV) research is the production of sufficient material in a consistent and effective way using in vitro cell models. Although the production of EVs in bioreactors maximizes EV yield in comparison to conventional cell cultures, the impact of their cell growth conditions on EVs has not yet been established. In this study, we grew two prostate cancer cell lines, PC-3 and VCaP, in conventional cell culture dishes and in two-chamber bioreactors to elucidate how the growth environment affects the EV characteristics. Specifically, we wanted to investigate the growth condition-dependent differences by non-targeted metabolite profiling using liquid chromatography-mass spectrometry (LC-MS) analysis. EVs were also characterized by their morphology, size distribution, and EV protein marker expression, and the EV yields were quantified by NTA. The use of bioreactor increased the EV yield >100 times compared to the conventional cell culture system. Regarding morphology, size distribution and surface markers, only minor differences were observed between the bioreactor-derived EVs (BR-EVs) and the EVs obtained from cells grown in conventional cell cultures (C-EVs). In contrast, metabolomic analysis revealed statistically significant differences in both polar and non-polar metabolites when the BR-EVs were compared to the C-EVs. The results show that the growth conditions markedly affected the EV metabolite profiles and that metabolomics was a sensitive tool to study molecular differences of EVs. We conclude that the cell culture conditions of EV production should be standardized and carefully detailed in publications and care should be taken when EVs from different production platforms are compared with each other for systemic effects.
  • Värri, Miika; Niskanen, Leo; Tuomainen, Tomi-Pekka; Honkanen, Risto; Kröger, Heikki; Tuppurainen, Marjo T. (2020)
    Purpose: Atherosclerosis (AS) and osteoporosis (OP) are common causes of morbidity and mortality in postmenopausal women and are connected via an unknown mechanistic link. Metabolite profiling of blood samples may allow the identification of new biomarkers and pathways for this enigmatic association. Patients and Methods: We studied the difference in 148 metabolite levels from serum samples in postmenopausal women with AS and OP compared with those in healthy participants in this cross-sectional study. Quantitative AS was assessed by carotid artery intima-media thickness (cIMT) and carotid artery calcifications (CACs) by ultrasound, as well as OP by femoral neck (FN) bone mineral density (BMD) and 148 metabolic measures with high-throughput proton (H-1) nuclear magnetic resonance (NMR) in serum samples from 280 postmenopausal (PM) women. Subjects were a randomly selected subsample from the population-based Kuopio Osteoporosis Risk Factor and Prevention (OSTPRE) study. The final study population included the following groups: OP with CAC (n=16, group I), non-OP with no CAC (n=59, group II), high cIMT tertile with OP (n=11, group III) and low cIMT tertile without OP (n=48, group IV). Results: There were differences in several metabolite levels between groups I and II. The acetate level was lower in group I compared to that in group II (group I mean +/- SD: 0.033 +/- 0.0070; group II: 0.041 +/- 0.014, CI95%: 0.018.0.15, p=0.014). The result was similar with diacylglycerol (p=0.002), leucine (p=0.031), valine (p=0.022) and several very low-density lipoprotein (VLDL) metabolite levels, which were lower in group I compared to those in group II. However, no associations were found in adjusted analyses with total body (TB) fat mass (FM), age and statin use (p>0.05). Conclusion: Our novel study found differences in the metabolite profiling of altered amino acid and lipoprotein metabolism in participants with OP and AS compared with those in healthy women. The causative mechanisms remain unknown and further studies are needed.
  • Buzkova, Jana; Nikkanen, Joni; Ahola, Sofia; Hakonen, Anna H.; Sevastianova, Ksenia; Hovinen, Topi; Yki-Järvinen, Hannele; Pietiläinen, Kirsi H.; Lönnqvist, Tuula; Velagapudi, Vidya; Carroll, Christopher J.; Suomalainen, Anu (2018)
    Mitochondrial disorders (MDs) are inherited multi-organ diseases with variable phenotypes. Inclusion body myositis (IBM), a sporadic inflammatory muscle disease, also shows mitochondrial dysfunction. We investigated whether primary and secondary MDs modify metabolism to reveal pathogenic pathways and biomarkers. We investigated metabolomes of 25 mitochondrial myopathy or ataxias patients, 16 unaffected carriers, six IBM and 15 non-mitochondrial neuromuscular disease (NMD) patients and 30 matched controls. MD and IBM metabolomes clustered separately from controls and NMDs. MDs and IBM showed transsulfuration pathway changes; creatine and niacinamide depletion marked NMDs, IBM and infantile-onset spinocerebellar ataxia (IOSCA). Low blood and muscle arginine was specific for patients with m.3243A>G mutation. A four-metabolite blood multi-biomarker (sorbitol, alanine, myoinositol, cystathionine) distinguished primary MDs from others (76% sensitivity, 95% specificity). Our omics approach identified pathways currently used to treat NMDs and mitochondrial stroke-like episodes and proposes nicotinamide riboside in MDs and IBM, and creatine in IOSCA and IBM as novel treatment targets. The disease-specific metabolic fingerprints are valuable "multi-biomarkers" for diagnosis and promising tools for follow-up of disease progression and treatment effect.