| 1. |
- Shiryaeva, Liudmila, 1970-, et al.
(författare)
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Pair-wise multicomparison and OPLS analyses of cold-acclimation phases in Siberian spruce
- 2012
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Ingår i: Metabolomics. - : Springer. - 1573-3882 .- 1573-3890. ; 8:Suppl 1, s. 123-130
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of metabolomics data often goes beyond the task of discovering biomarkers and can be aimed at recovering other important characteristics of observed metabolomic changes. In this paper we explore different methods to detect the presence of distinctive phases in seasonal-responsive changes of metabolomic patterns of Siberian spruce (Picea obovata) during cold acclimation occurred in the period from mid-August to January. Multivariate analysis, specifically orthogonal projection to latent structures discriminant analysis (OPLSDA), identified time points where the metabolomic patterns underwent substantial modifications as a whole, revealing four distinctive phases during acclimation. This conclusion was re-examined by a univariate analysis consisting of multiple pair-wise comparisons to identify homogeneity intervals for each metabolite. These tests complemented OPLS-DA, clarifying biological interpretation of the classification: about 60% of metabolites found responsive to the cold stress indeed changed at one or more of the time points predicted by OPLS-DA. However, the univariate approach did not support the proposed division of the acclimation period into four phases: less than 10% of metabolites altered during the acclimation had homogeneous levels predicted by OPLS-DA. This demonstrates that coupling the classification found by OPLS-DA and the analysis of dynamics of individual metabolites obtained by pair-wise multicomparisons reveals a more correct characterization of biochemical processes in freezing tolerant trees and leads to interpretations that cannot be deduced by either method alone. The combined analysis can be used in other ‘omics’-studies, where response factors have a causal dependence (like the time in the present work) and pairwise multicomparisons are not conservative.
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| 2. |
- Ruhal, Rohit, et al.
(författare)
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A multivariate approach to correlate bacterial surface properties to biofilm formation by lipopolysaccharide mutants of Pseudomonas aeruginosa
- 2015
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Ingår i: Colloids and Surfaces B. - : Elsevier. - 0927-7765 .- 1873-4367. ; 127:0, s. 182-191
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Tidskriftsartikel (refereegranskat)abstract
- Abstract Bacterial biofilms are involved in various medical infections and for this reason it is of great importance to better understand the process of biofilm formation in order to eradicate or mitigate it. It is a very complex process and a large range of variables have been suggested to influence biofilm formation. However, their internal importance is still not well understood. In the present study, a range of surface properties of Pseudomonas aeruginosa lipopolysaccharide mutants were studied in relation to biofilm formation measured in different kinds of multi-well plates and growth conditions in order to better understand the complexity of biofilm formation. Multivariate analysis was used to simultaneously evaluate the role of a range of physiochemical parameters under different conditions. Our results suggest the presence of serum inhibited biofilm formation due to changes in twitching motility. From the multivariate analysis it was observed that the most important parameters, positively correlated to biofilm formation on two types of plates, were high hydrophobicity, near neutral zeta potential and motility. Negative correlation was observed with cell aggregation, as well as formation of outer membrane vesicles and exopolysaccharides. This work shows that the complexity of biofilm formation can be better understood using a multivariate approach that can interpret and rank the importance of different factors being present simultaneously under several different environmental conditions, enabling a better understanding of this complex process.
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| 3. |
- Wibom, Carl, 1977-, et al.
(författare)
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Metabolomic patterns in glioblastoma and changes during radiotherapy : a clinical microdialysis study
- 2010
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 9:6, s. 2909-2919
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Tidskriftsartikel (refereegranskat)abstract
- We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.
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| 4. |
- Antti, Henrik, 1970-, et al.
(författare)
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Metabolic effects of an aspartate aminotransferase-inhibitor on two T-cell lines
- 2018
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 13:12
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Tidskriftsartikel (refereegranskat)abstract
- An emerging method to help elucidate the mode of action of experimental drugs is to use untargeted metabolomics of cell-systems. The interpretations of such screens are however complex and more examples with inhibitors of known targets are needed. Here two T-cell lines were treated with an inhibitor of aspartate aminotransferase and analyzed with untargeted GC-MS. The interpretation of the data was enhanced by the use of two different cell-lines and supports aspartate aminotransferase as a target. In addition, the data suggest an unexpected off-target effect on glutamate decarboxylase. The results exemplify the potency of metabolomics to provide insight into both mode of action and off-target effects of drug candidates.
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| 5. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 6. |
- Hoffman, Daniel E., et al.
(författare)
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Changes in diurnal patterns within the Populus transcriptome and metabolome in response to photoperiod variation
- 2010
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Ingår i: Plant, Cell and Environment. - : Wiley. - 0140-7791 .- 1365-3040. ; 33:8, s. 1298-1313
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Tidskriftsartikel (refereegranskat)abstract
- Changes in seasonal photoperiod provides an important environmental signal that affects the timing of winter dormancy in perennial, deciduous, temperate tree species, such as hybrid aspen (Populus tremula x Populus tremuloides). In this species, growth cessation, cold acclimation and dormancy are induced in the autumn by the detection of day-length shortening that occurs at a given critical day length. Important components in the detection of such day-length changes are photoreceptors and the circadian clock, and many plant responses at both the gene regulation and metabolite levels are expected to be diurnal. To directly examine this expectation and study components in these events, here we report transcriptomic and metabolomic responses to a change in photoperiod from long to short days in hybrid aspen. We found about 16% of genes represented on the arrays to be diurnally regulated, as assessed by our pre-defined criteria. Furthermore, several of these genes were involved in circadian-associated processes, including photosynthesis and primary and secondary metabolism. Metabolites affected by the change in photoperiod were mostly involved in carbon metabolism. Taken together, we have thus established a molecular catalog of events that precede a response to winter.
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| 7. |
- Kilpeläinen, Tuomas O, et al.
(författare)
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Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
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| 8. |
- Loo, Ruey Leng, et al.
(författare)
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Strategy for improved characterization of human metabolic phenotypes using a COmbined Multi-block Principal components Analysis with Statistical Spectroscopy (COMPASS)
- 2020
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 36:21, s. 5229-5236
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Large-scale population omics data can provide insight into associations between gene-environment interactions and disease. However, existing dimension reduction modelling techniques are often inefficient for extracting detailed information from these complex datasets.Results: Here, we present an interactive software pipeline for exploratory analyses of population-based nuclear magnetic resonance spectral data using a COmbined Multi-block Principal components Analysis with Statistical Spectroscopy (COMPASS) within the R-library hastaLaVista framework. Principal component analysis models are generated for a sequential series of spectral regions (blocks) to provide more granular detail defining sub-populations within the dataset. Molecular identification of key differentiating signals is subsequently achieved by implementing Statistical TOtal Correlation SpectroscopY on the full spectral data to define feature patterns. Finally, the distributions of cross-correlation of the reference patterns across the spectral dataset are used to provide population statistics for identifying underlying features arising from drug intake, latent diseases and diet. The COMPASS method thus provides an efficient semi-automated approach for screening population datasets.
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| 9. |
- Löding, Sebastian, et al.
(författare)
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Blood based metabolic markers of glioma from pre-diagnosis to surgery
- 2024
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Gliomas are highly complex and metabolically active brain tumors associated with poor prognosis. Recent reports have found altered levels of blood metabolites during early tumor development, suggesting that tumor development could be detected several years before clinical manifestation. In this study, we performed metabolite analyses of blood samples collected from healthy controls and future glioma patients, up to eight years before glioma diagnosis, and on the day of glioma surgery. We discovered that metabolites related to early glioma development were associated with an increased energy turnover, as highlighted by elevated levels of TCA-related metabolites such as fumarate, malate, lactate and pyruvate in pre-diagnostic cases. We also found that metabolites related to glioma progression at surgery were primarily high levels of amino acids and metabolites of amino acid catabolism, with elevated levels of 11 amino acids and two branched-chain alpha-ketoacids, ketoleucine and ketoisoleucine. High amino acid turnover in glioma tumor tissue is currently utilized for PET imaging, diagnosis and delineation of tumor margins. By examining blood-based metabolic progression patterns towards disease onset, we demonstrate that this high amino acid turnover is also detectable in a simple blood sample. These findings provide additional insight of metabolic alterations during glioma development and progression.
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| 10. |
- Mörén, Lina, 1985-, et al.
(författare)
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Metabolomic screening of tumor tissue and serum in glioma patients reveals diagnostic and prognostic information
- 2015
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Ingår i: Metabolites. - : MDPI. - 2218-1989. ; 5:3, s. 502-520
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Tidskriftsartikel (refereegranskat)abstract
- Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, in the clinical reality, large variations exist in the survival of patients concerning both glioblastomas and low-grade gliomas. Thus, there is a need for biomarkers for a more reliable classification of glioma tumors as well as for prognosis. We analyzed relative metabolite concentrations in serum samples from 96 fasting glioma patients and 81 corresponding tumor samples with different diagnosis (glioblastoma, oligodendroglioma) and grade (World Health Organization (WHO) grade II, III and IV) using gas chromatography-time of flight mass spectrometry (GC-TOFMS). The acquired data was analyzed and evaluated by pattern recognition based on chemometric bioinformatics tools. We detected feature patterns in the metabolomics data in both tumor and serum that distinguished glioblastomas from oligodendrogliomas (p(tumor) = 2.46 × 10(-8), p(serum) = 1.3 × 10(-5)) and oligodendroglioma grade II from oligodendroglioma grade III (p(tumor) = 0.01, p(serum) = 0.0008). Interestingly, we also found patterns in both tumor and serum with individual metabolite features that were both elevated and decreased in patients that lived long after being diagnosed with glioblastoma compared to those who died shortly after diagnosis (p(tum)(o)(r) = 0.006, p(serum) = 0.004; AUROCC(tumor) = 0.846 (0.647-1.000), AUROCC(serum) = 0.958 (0.870-1.000)). Metabolic patterns could also distinguish long and short survival in patients diagnosed with oligodendroglioma (p(tumor) = 0.01, p(serum) = 0.001; AUROCC(tumor) = 1 (1.000-1.000), AUROCC(serum) = 1 (1.000-1.000)). In summary, we found different metabolic feature patterns in tumor tissue and serum for glioma diagnosis, grade and survival, which indicates that, following further verification, metabolomic profiling of glioma tissue as well as serum may be a valuable tool in the search for latent biomarkers for future characterization of malignant glioma.
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