Browsing by Subject "metabolomics"

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  • 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.
  • Sliz, Eeva; Kettunen, Johannes; Holmes, Michael V.; Williams, Clare Oliver; Boachie, Charles; Wang, Qin; Maennikkoe, Minna; Sebert, Sylvain; Walters, Robin; Lin, Kuang; Millwood, Iona Y.; Clarke, Robert; Li, Liming; Rankin, Naomi; Welsh, Paul; Delles, Christian; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Perola, Markus; Salomaa, Veikko; Jaervelin, Marjo-Riitta; Chen, Zhengming; Lawlor, Debbie A.; Ala-Korpela, Mika; Danesh, John; Davey Smith, George; Sattar, Naveed; Butterworth, Adam; Würtz, Peter (2018)
    Background: Both statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors lower blood low-density lipoprotein cholesterol levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these 2 lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial. Methods: Two hundred twenty-eight circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5359 individuals (2659 on treatment) in the PROSPER (Prospective Study of Pravastatin in the Elderly at Risk) trial at 6 months postrandomization. The corresponding metabolic measures were analyzed in 8 population cohorts (N=72 185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors. Results: Scaled to an equivalent lowering of low-density lipoprotein cholesterol, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R-2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of very-low-density lipoprotein cholesterol compared with statin therapy (54% versus 77% reduction, relative to the lowering effect on low-density lipoprotein cholesterol; P=2x10(-7) for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA), whereas statin treatment weakly lowered GlycA levels. Conclusions: Genetic inhibition of PCSK9 had similar metabolic effects to statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on very-low-density lipoprotein lipids compared with statins for an equivalent lowering of low-density lipoprotein cholesterol, which potentially translate into smaller reductions in cardiovascular disease risk.
  • Puhka, Maija; Takatalo, Maarit; Nordberg, Maria-Elisa; Valkonen, Sami; Nandania, Jatin; Aatonen, Maria; Yliperttula, Marjo; Laitinen, Saara; Velagapudi, Vidya; Mirtti, Tuomas; Kallioniemi, Olli; Rannikko, Antti; Siljander, Pia R-M; Af Hallstrom, Taija Maria (2017)
    Body fluids are a rich source of extracellular vesicles (EVs), which carry cargo derived from the secreting cells. So far, biomarkers for pathological conditions have been mainly searched from their protein, (mi) RNA, DNA and lipid cargo. Here, we explored the small molecule metabolites from urinary and platelet EVs relative to their matched source samples. As a proof-of-concept study of intra-EV metabolites, we compared alternative normalization methods to profile urinary EVs from prostate cancer patients before and after prostatectomy and from healthy controls. Methods: We employed targeted ultra-performance liquid chromatography-tandem mass spectrometry to profile over 100 metabolites in the isolated EVs, original urine samples and platelets. We determined the enrichment of the metabolites in the EVs and analyzed their subcellular origin, pathways and relevant enzymes or transporters through data base searches. EV-and urine-derived factors and ratios between metabolites were tested for normalization of the metabolomics data. Results: Approximately 1 x 10(10) EVs were sufficient for detection of metabolite profiles from EVs. The profiles of the urinary and platelet EVs overlapped with each other and with those of the source materials, but they also contained unique metabolites. The EVs enriched a selection of cytosolic metabolites including members from the nucleotide and spermidine pathways, which linked to a number of EV-resident enzymes or transporters. Analysis of the urinary EVs from the patients indicated that the levels of glucuronate, D-ribose 5-phosphate and isobutyryl-L-carnitine were 2-26-fold lower in all pre-prostatectomy samples compared to the healthy control and post-prostatectomy samples (p <0.05). These changes were only detected from EVs by normalization to EV-derived factors or with metabolite ratios, and not from the original urine samples. Conclusions: Our results suggest that metabolite analysis of EVs from different samples is feasible using a high-throughput platform and relatively small amount of sample material. With the knowledge about the specific enrichment of metabolites and normalization methods, EV metabolomics could be used to gain novel biomarker data not revealed by the analysis of the original EV source materials.
  • Wurtz, Peter; Wang, Qin; Soininen, Pasi; Kangas, Antti J.; Fatemifar, Ghazaleh; Tynkkynen, Tuulia; Tiainen, Mika; Perola, Markus; Tillin, Therese; Hughes, Alun D.; Mantyselka, Pekka; Kahonen, Mika; Lehtimaki, Terho; Sattar, Naveed; Hingorani, Aroon D.; Casas, Juan-Pablo; Salomaa, Veikko; Kivimaki, Mika; Jarvelin, Marjo-Riitta; Smith, George Davey; Vanhala, Mauno; Lawlor, Debbie A.; Raitakari, Olli T.; Chaturvedi, Nish; Kettunen, Johannes; Ala-Korpela, Mika (2016)
    BACKGROUND Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized. OBJECTIVES This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways. METHODS Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts. RESULTS Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R-2 = 0.94, slope 1.00 +/- 0.03). CONCLUSIONS Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects, and pharmacological mechanisms. (C) 2016 by the American College of Cardiology Foundation.
  • Tikkanen, Emmi; Minicocci, Ilenia; Hällfors, Jenni; Di Costanzo, Alessia; D'Erasmo, Laura; Poggiogalle, Eleonora; Donini, Lorenzo Maria; Wurtz, Peter; Jauhiainen, Matti; Olkkonen, Vesa M.; Arca, Marcello (2019)
    Objective- Loss-of-function (LOF) variants in the ANGPTL3 (angiopoietin-like protein 3) have been associated with low levels of plasma lipoproteins and decreased coronary artery disease risk. We aimed to determine detailed metabolic effects of genetically induced ANGPTL3 deficiency in fasting and postprandial state. Approach and Results- We studied individuals carrying S17X LOF mutation in ANGPTL3 (6 homozygous and 32 heterozygous carriers) and 38 noncarriers. Nuclear magnetic resonance metabolomics was used to quantify 225 circulating metabolic measures. We compared metabolic differences between LOF carriers and noncarriers in fasting state and after a high-fat meal. In fasting, ANGPTL3 deficiency was characterized by similar extent of reductions in LDL (low-density lipoprotein) cholesterol (0.74 SD units lower concentration per LOF allele [95% CI, 0.42-1.06]) as observed for many TRL (triglyceride-rich lipoprotein) measures, including VLDL (very-low-density lipoprotein) cholesterol (0.75 [95% CI, 0.45-1.05]). Within most lipoprotein subclasses, absolute levels of cholesterol were decreased more than triglycerides, resulting in the relative proportion of cholesterol being reduced within TRLs and their remnants. Further, beta-hydroxybutyrate was elevated (0.55 [95% CI, 0.21-0.89]). Homozygous ANGPTL3 LOF carriers showed essentially no postprandial increase in TRLs and fatty acids, without evidence for adverse compensatory metabolic effects. Conclusions- In addition to overall triglyceride- and LDL cholesterol-lowering effects, ANGPTL3 deficiency results in reduction of cholesterol proportion within TRLs and their remnants. Further, ANGPTL3 LOF carriers had elevated ketone body production, suggesting enhanced hepatic fatty acid beta-oxidation. The detailed metabolic profile in human knockouts of ANGPTL3 reinforces inactivation of ANGPTL3 as a promising therapeutic target for decreasing cardiovascular risk.
  • Ellul, Susan; Wake, Melissa; Clifford, Susan A.; Lange, Katherine; Würtz, Peter; Juonala, Markus; Dwyer, Terence; Carlin, John B.; Burgner, David P.; Saffery, Richard (2019)
    Objectives Nuclear magnetic resonance (NMR) metabolomics is high throughput and cost-effective, with the potential to improve the understanding of disease and risk. We examine the circulating metabolic profile by quantitative NMR metabolomics of a sample of Australian 11-12 year olds children and their parents, describe differences by age and sex, and explore the correlation of metabolites in parent-child dyads. Design The population-based cross-sectional Child Health CheckPoint study nested within the Longitudinal Study of Australian Children. Setting Blood samples collected from CheckPoint participants at assessment centres in seven Australian cities and eight regional towns; February 2015-March 2016. Participants 1180 children and 1325 parents provided a blood sample and had metabolomics data available. This included 1133 parent-child dyads (518 mother-daughter, 469 mother-son, 68 father-daughter and 78 father-son). Outcome measures 228 metabolic measures were obtained for each participant. We focused on 74 biomarkers including amino acid species, lipoprotein subclass measures, lipids, fatty acids, measures related to fatty acid saturation, and composite markers of inflammation and energy homeostasis. Results We identified differences in the concentration of specific metabolites between childhood and adulthood and in metabolic profiles in children and adults by sex. In general, metabolite concentrations were higher in adults than children and sex differences were larger in adults than in children. Positive correlations were observed for the majority of metabolites including isoleucine (CC 0.33, 95% CI 0.27 to 0.38), total cholesterol (CC 0.30, 95% CI 0.24 to 0.35) and omega 6 fatty acids (CC 0.28, 95% CI 0.23 to 0.34) in parent-child comparisons. Conclusions We describe the serum metabolite profiles from mid-childhood and adulthood in a population-based sample, together with a parent-child concordance. Differences in profiles by age and sex were observed. These data will be informative for investigation of the childhood origins of adult non-communicable diseases and for comparative studies in other populations.
  • Oh, Sehyun; Cho, Youngup; Chang, Minsun; Park, Sunghyouk; Kwon, Hyuk Nam (2021)
    The biguanide drug metformin has been widely used for the treatment of type 2 diabetes, and there is evidence supporting the anticancer effect of metformin despite some controversy. Here, we report the growth inhibitory activity of metformin in the breast cancer (MCF-7) cells, both in vitro and in vivo, and the associated metabolic changes. In particular, a decrease in a well-known oncometabolite 2-hydroxyglutarate (2-HG) was discovered by a metabolomics approach. The decrease in 2-HG by metformin was accompanied by the reduction in histone methylation, consistent with the known tumorigenic mechanism of 2-HG. The relevance of 2-HG inhibition in breast cancer was also supported by a higher level of 2-HG in human breast cancer tissues. Genetic knockdown of PHGDH identified the PHGDH pathway as the producer of 2-HG in the MCF-7 cells that do not carry isocitrate dehydrogenase 1 and 2 (IDH1/IDH2) mutations, the conventional producer of 2-HG. We also showed that metformin's inhibitory effect on the PHGDH-2HG axis may occur through the regulation of the AMPK-MYC pathway. Overall, our results provide an explanation for the coherent pathway from complex I inhibition to epigenetic changes for metformin's anticancer effect.
  • Talman, Virpi; Teppo, Jaakko Sakari; Pöhö, Päivi Anneli; Movahedi, Parisa; Vaikkinen, Anu; Karhu, Suvi Tuuli; Trošt, Kajetan; Suvitaival, Tommi; Heikkonen, Jukka; Pahikkala, Tapio; Kotiaho, Ahti Antti Tapio; Kostiainen, Risto Kalervo; Varjosalo, Markku Tapio; Ruskoaho, Heikki Juhani (2018)
    Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource of mRNA, protein, and metabolite changes in the neonatal heart for identification of metabolism‐related mechanisms associated with cardiac regeneration. Methods and Results Methods and results Mouse ventricular tissue samples taken on postnatal day 1 (P01), P04, P09, and P23 were analyzed with RNA sequencing and global proteomics and metabolomics. Gene ontology analysis, KEGG pathway analysis, and fuzzy c‐means clustering were used to identify up‐ or downregulated biological processes and metabolic pathways on all 3 levels, and Ingenuity pathway analysis (Qiagen) was used to identify upstream regulators. Differential expression was observed for 8547 mRNAs and for 1199 of 2285 quantified proteins. Furthermore, 151 metabolites with significant changes were identified. Differentially regulated metabolic pathways include branched chain amino acid degradation (upregulated at P23), fatty acid metabolism (upregulated at P04 and P09; downregulated at P23) as well as the HMGCS (HMG‐CoA [hydroxymethylglutaryl‐coenzyme A] synthase)–mediated mevalonate pathway and ketogenesis (transiently activated). Pharmacological inhibition of HMGCS in primary neonatal cardiomyocytes reduced the percentage of BrdU‐positive cardiomyocytes, providing evidence that the mevalonate and ketogenesis routes may participate in regulating the cardiomyocyte cell cycle. Conclusions This study is the first systems‐level resource combining data from genomewide transcriptomics with global quantitative proteomics and untargeted metabolomics analyses in the mouse heart throughout the early postnatal period. These integrated data of molecular changes associated with the loss of cardiac regeneration may open up new possibilities for the development of regenerative therapies
  • Soderholm, Sandra; Fu, Yu; Gaelings, Lana; Belanov, Sergey; Yetukuri, Laxma; Berlinkov, Mikhail; Cheltsov, Anton V.; Anders, Simon; Aittokallio, Tero; Nyman, Tuula A.; Matikainen, Sampsa; Kainov, Denis E. (2016)
    Human influenza A viruses (IAVs) cause global pandemics and epidemics. These viruses evolve rapidly, making current treatment options ineffective. To identify novel modulators of IAV-host interactions, we re-analyzed our recent transcriptomics, metabolomics, proteomics, phosphoproteomics, and genomics/virtual ligand screening data. We identified 713 potential modulators targeting 199 cellular and two viral proteins. Anti-influenza activity for 48 of them has been reported previously, whereas the antiviral efficacy of the 665 remains unknown. Studying anti-influenza efficacy and immuno/neuro-modulating properties of these compounds and their combinations as well as potential viral and host resistance to them may lead to the discovery of novel modulators of IAV-host interactions, which might be more effective than the currently available anti-influenza therapeutics.
  • Muktadir, Md Abdul; Adhikari, Kedar Nath; Merchant, Andrew; Belachew, Kiflemariam; Vandenberg, Albert; Stoddard, Fred; Khazaei, Hamid (2020)
    Grain legumes are commonly used for food and feed all over the world and are the main source of protein for over a billion people worldwide, but their production is at risk from climate change. Water deficit and heat stress both significantly reduce the yield of grain legumes, and the faba bean is considered particularly susceptible. The genetic improvement of faba bean for drought adaptation (water deficit tolerance) by conventional methods and molecular breeding is time-consuming and laborious, since it depends mainly on selection and adaptation in multiple sites. The lack of high-throughput screening methodology and low heritability of advantageous traits under environmental stress challenge breeding progress. Alternatively, selection based on secondary characters in a controlled environment followed by field trials is successful in some crops, including faba beans. In general, measured features related to drought adaptation are shoot and root morphology, stomatal characteristics, osmotic adjustment and the efficiency of water use. Here, we focus on the current knowledge of biochemical and physiological markers for legume improvement that can be incorporated into faba bean breeding programs for drought adaptation.
  • Kwon, Hyuk Nam; Lee, Hyuk; Park, Ji Won; Kim, Young-Ho; Park, Sunghyouk; Kim, Jae J. (2020)
    The early detection of gastric cancer (GC) could decrease its incidence and mortality. However, there are currently no accurate noninvasive markers for GC screening. Therefore, we developed a noninvasive diagnostic approach, employing urine nuclear magnetic resonance (NMR) metabolomics, to discover putative metabolic markers associated with GC. Changes in urine metabolite levels during oncogenesis were evaluated using samples from 103 patients with GC and 100 age- and sex-matched healthy controls. Approximately 70% of the patients with GC (n = 69) had stage I GC, with the majority (n = 56) having intramucosal cancer. A multivariate statistical analysis of the urine NMR data well discriminated between the patient and control groups and revealed nine metabolites, including alanine, citrate, creatine, creatinine, glycerol, hippurate, phenylalanine, taurine, and 3-hydroxybutyrate, that contributed to the difference. A diagnostic performance test with a separate validation set exhibited a sensitivity and specificity of more than 90%, even with the intramucosal cancer samples only. In conclusion, the NMR-based urine metabolomics approach may have potential as a convenient screening method for the early detection of GC and may facilitate consequent endoscopic examination through risk stratification.
  • Walker, Hannah K.; Ottka, Claudia; Lohi, Hannes; Handel, Ian; Clements, Dylan N.; Gow, Adam G.; Mellanby, Richard J. (2022)
    Background Metabolic profiling identifies seasonal variance of serum metabolites in humans. Despite the presence of seasonal disease patterns, no studies have assessed whether serum metabolites vary seasonally in dogs. Hypothesis There is seasonal variation in the serum metabolite profiles of healthy dogs. Animals Eighteen healthy, client-owned dogs. Methods A prospective cohort study. Serum metabolomic profiles were assessed monthly in 18 healthy dogs over a 12-month period. Metabolic profiling was conducted using a canine-specific proton nuclear magnetic resonance spectroscopy platform, and the effects of seasonality were studied for 98 metabolites using a cosinor model. Seasonal component was calculated, which describes the seasonal variation of each metabolite. Results We found no evidence of seasonal variation in 93 of 98 metabolites. Six metabolites had statistically significant seasonal variance, including cholesterol (mean 249 mg/dL [6.47 mmol/L] with a seasonal component amplitude of 9 mg/dL [0.23 mmol/L]; 95% confidence interval [CI] 6-13 mg/dL [0.14-0.33 mmol/L], P < .008), with a peak concentration of 264 mg/dL (6.83 mmol/L) in June and trough concentration of 236 mg/dL (6.12 mmol/L) in December. In contrast, there was a significantly lower concentration of lactate (mean 20 mg/dL [2.27 mmol/L] with a seasonal component amplitude of 4 mg/dL [0.42 mmol/L]; 95% CI 2-6 mg/dL [0.22-0.62 mmol/L], P < .001) during the summer months compared to the winter months, with a peak concentration of 26 mg/dL (2.9 mmol/L) in February and trough concentration of 14 mg/dL (1.57 mmol/L) in July. Conclusions and Clinical Importance We found no clear evidence that seasonal reference ranges need to be established for serum metabolites of dogs.
  • Walker, Hannah K.; Boag, Alisdair M.; Ottka, Claudia; Lohi, Hannes; Handel, Ian; Gow, Adam G.; Mellanby, Richard J. (2022)
    Background Metabolic profiles differ between healthy humans and those with inflammatory bowel disease. Few studies have examined metabolic profiles in dogs with chronic enteropathy (CE). Hypothesis Serum metabolic profiles of dogs with CE are significantly different from those of healthy dogs. Animals Fifty-five dogs with CE and 204 healthy controls. Methods A cross-sectional study. The serum concentrations of 99 metabolites measured using a canine-specific proton nuclear magnetic resonance spectroscopy platform were studied. A 2-sample unpaired t-test was used to compare the 2 study samples. The threshold for significance was set at P < .05 with a Bonferroni correction for each metabolite group. Results Nineteen metabolites and 18 indices of lipoprotein composition were significantly different between the CE and healthy dogs. Four metabolites were significantly higher in dogs with CE, including phenylalanine (mean and SD) (healthy: 0.0417 mmol/L; [SD] 0.0100; CE: 0.0480 mmol/L; SD: 0.0125; P value:
  • Ahonen, Linda; Jäntti, Sirkku; Suvitaival, Tommi; Theilade, Simone; Risz, Claudia; Kostiainen, Risto; Rossing, Peter; Oresic, Matej; Hyötyläinen , Tuulia (2019)
    Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities, and complications. Here, we report the development and validation of a novel, quantitative method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. We selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings. We validated the method in terms of limits of detection (LOD) and quantitation (LOQ), linearity (R-2), and intra- and inter-day repeatability of each metabolite. The method's performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes, as well as specific bile acids, were associated with macro-albuminuria. Additionally, specific bile acids were associated with glycemic control, anti-hypertensive medication, statin medication, and clinical lipid measurements. The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.
  • Ján , Labuda; Richard P. , Bowater; Miroslav , Fojta; Günter , Gauglitz; Zdeněk, Glatz; Ivan , Hapala; Jan, Havliš; Ferenc , Kilar; Aniko , Kilar; Lenka, Malinovská; Siren, Heli Marja Marita; Petr , Skládal; Federico , Torta; Martin , Valachovič; Michaela , Wimmerová; Zbyněk , Zdráhal; David Brynn, Hibbert (2018)
    Recommendations are given concerning the terminology of methods of bioanalytical chemistry. With respect to dynamic development particularly in the analysis and investigation of biomacromolecules, terms related to bioanalytical samples, enzymatic methods, immunoanalytical methods, methods used in genomics and nucleic acid analysis, proteomics, metabolomics, glycomics, lipidomics, and biomolecules interaction studies are introduced.
  • Velagapudi, Vidya R.; Hezaveh, Rahil; Reigstad, Christopher S.; Gopalacharyulu, Peddinti; Yetukuri, Laxman; Islam, Sama; Felin, Jenny; Perkins, Rosie; Boren, Jan; Oresic, Matej; Backhed, Fredrik (2010)
  • Nandania, Jatin; Peddinti, Gopal; Pessia, Alberto; Kokkonen, Meri; Velagapudi, Vidya (2018)
    The use of metabolomics profiling to understand the metabolism under different physiological states has increased in recent years, which created the need for robust analytical platforms. Here, we present a validated method for targeted and semiquantitative analysis of 102 polar metabolites that cover major metabolic pathways from 24 classes in a single 17.5-min assay. The method has been optimized for a wide range of biological matrices from various organisms, and involves automated sample preparation and data processing using an inhouse developed R-package. To ensure reliability, the method was validated for accuracy, precision, selectivity, specificity, linearity, recovery, and stability according to European Medicines Agency guidelines. We demonstrated an excellent repeatability of retention times (CV <4%), calibration curves (R-2 > 0.980) in their respective wide dynamic concentration ranges (CV <3%), and concentrations (CV <25%) of quality control samples interspersed within 25 batches analyzed over a period of one year. The robustness was demonstrated through a high correlation between metabolite concentrations measured using our method and the NIST reference values (R-2 = 0.967), including cross-platform comparability against the BIOCRATES AbsoluteIDQp180 kit (R-2 = 0.975) and NMR analyses (R-2 = 0.884). We have shown that our method can be successfully applied in many biomedical research fields and clinical trials, including epidemiological studies for biomarker discovery. In summary, a thorough validation demonstrated that our method is reproducible, robust, reliable, and suitable for metabolomics studies.