| 1. |
- Idborg, Helena, et al.
(författare)
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STRATIFICATION OF SLE PATIENTS FOR IMPROVED DIAGNOSIS AND TREATMENT
- 2013
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 72, s. A80-A80
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background. Systemic autoimmune diseases (SAIDs) affect about 2% of the population in Western countries. Sufficient diagnostic criteria are lacking due to the heterogeneity within diagnostic categories and apparent overlap regarding symptoms and patterns of autoantibodies between different diagnoses. Systemic lupus erythematosus (SLE) is regarded as a prototype for SAIDs and we hypothesise that subgroups of patients with SLE may have different pathogenesis and should consequently be subject to different treatment strategies.Objectives. Our goal is to find new biomarkers to be used for the identification of more homogenous patient populations for clinical trials and to identify sub-groups of patients with high risk of for example cardiovascular events.Methods. In this study we have utilised 320 SLE patients from the Karolinska lupus cohort and 320 age and gender matched controls. The SLE cohort was characterised based on clinical, genetic and serological data and combined by multivariate data analysis in a systems biology approach to study possible subgroups. A pilot study was designed to verify and investigate suggested subgroups of SLE. Two main subgroups were defined: One group was defined as having SSA and SSB antibodies and a negative lupus anticoagulant test (LAC), i.e., a “Sjögren-like” group. The other group was defined as being negative for SSA and SSB antibodies but positive in the LAC test.i.e. an “APS-like” group. EDTA-plasma from selected patients in these two groups and controls were analysed using a mass spectrometry (MS) based proteomic and metabolomic approach. Pathway analysis was then performed on the obtained data.Results. Our pilot study showed that differences in levels of proteins and metabolites could separate disease groups from population controls. The profile/pattern of involved factors in the complement system supported a division of SLE in two major subgroups, although each individual factor was not significantly different between subgroups. Complement factor 2 (C2) and membrane attack complex (MAC) were analysed in the entire cohort with complementary methods and C2 verifies our results while the levels of MAC did not differ between SLE subgroups. The generated metabolomics data clearly separated SLE patients from controls in both gas chromatography (GC)-MS and liquid chromatography (LC)-MS data. We found for example that tryptophan was lower in the SLE patients compared to controls.Conclusions. Our systems biology approach may lead to a better understanding of the disease and its pathogenesis, and assigning patients into subgroups will result in improved diagnosis and better outcome measures of SLE.
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| 2. |
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| 3. |
- Madsen, Rasmus Kirkegaard, 1979-, et al.
(författare)
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Diagnostic properties of metabolic perturbations in rheumatoid arthritis
- 2011
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Ingår i: Arthritis Research & Therapy. - : Springer Science and Business Media LLC. - 1478-6354 .- 1478-6362. ; 13:1, s. R19-
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: The aim of the study was to assess the feasibility of diagnosing early rheumatoid arthritis (RA) by measuring selected metabolic biomarkers. METHODS: We compared the metabolic profile of patients with RA with those of healthy controls and patients with psoriatic arthritis (PsoA). The metabolites were measured using two different chromatography-mass spectrometry platforms, thereby giving a broad overview of serum metabolites. The metabolic profiles of patient and control groups were compared using multivariate statistical analysis. The findings were validated in a follow-up study of RA patients and healthy volunteers. RESULTS: RA patients were diagnosed with a sensitivity of 93 % and a specificity of 70 % in a validation study using detection of 52 metabolites. Patients with RA or PsoA could be distinguished with a sensitivity of 90 % and a specificity of 94 %. Glyceric acid, D-ribofuranoise and hypoxanthine were increased in RA patients, whereas histidine, threonic acid, methionine, cholesterol, asparagine and threonine were all decreased when compared with healthy controls. CONCLUSIONS: Metabolite profiling (metabolomics) is a potentially useful technique for diagnosing RA. The predictive value was irrespective of the presence of antibodies against cyclic citrullinated peptides (ACPA).
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| 4. |
- Pinto, Rui Climaco, et al.
(författare)
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Advantages of orthogonal inspection in chemometrics
- 2012
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Ingår i: Journal of Chemometrics. - : Wiley. - 0886-9383 .- 1099-128X. ; 26:6, s. 231-235
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Tidskriftsartikel (refereegranskat)abstract
- The demand for chemometrics tools and concepts to study complex problems in modern biology and medicine has prompted chemometricians to shift their focus away from a traditional emphasis on model predictive capacity toward optimizing information exchange via model interpretation for biological validation. The interpretation of projection-based latent variable models is not straightforward because of its confounding of different systematic variations in the model components. Over the last 15?years, this has spurred the development of orthogonal-based methods that are capable of separating the correlated variation (to Y) from the noncorrelated (orthogonal to Y) variations in a single model. Here, we aim to provide a conceptual explanation of the advantages of orthogonal variation inspection in the context of Partial Least Squares (PLS) in multivariate classification and calibration. We propose that by inspecting the orthogonal variation, both model interpretation and information quality are improved by enhancement of the resulting level of knowledge. Although the predictive capacity of PLS using orthogonal methods may be identical to that of PLS alone, the combined result can be superior when it comes to the model interpretation. By discussing theory and examples, several new advantages revealed by inspection of orthogonal variation are highlighted. Copyright (c) 2012 John Wiley & Sons, Ltd.
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| 5. |
- Brynolfsson, Patrik, et al.
(författare)
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ADC texture-An imaging biomarker for high-grade glioma?
- 2014
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Ingår i: Medical physics (Lancaster). - : Wiley. - 0094-2405. ; 41:10, s. 101903-
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Tidskriftsartikel (refereegranskat)abstract
- Purpose:Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers.Methods:Twenty-three consecutive high-grade glioma patients were treated with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression.Results:The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified: one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001.Conclusions:By combining PCA and texture analysis, ADC texture characteristics were identified, which seems to hold pretreatment prognostic information, independent of known prognostic factors such as age, stage, and surgical procedure. These findings encourage further studies with a larger patient cohort. (C) 2014 Author(s).
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| 6. |
- Dumarey, Melanie, 1982-, et al.
(författare)
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Combining experimental design and orthogonal projections to latent structures to study the influence of microcrystalline cellulose properties on roll compaction
- 2011
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Ingår i: International Journal of Pharmaceutics. - : Elsevier. - 0378-5173 .- 1873-3476. ; 416:1, s. 110-119
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Tidskriftsartikel (refereegranskat)abstract
- Roll compaction is gaining importance in pharmaceutical industry for the dry granulation of heat or moisture sensitive powder blends with poor flowing properties prior to tabletting. We studied the influence of microcrystalline cellulose (MCC) properties on the roll compaction process and the consecutive steps in tablet manufacturing. Four dissimilar MCC grades, selected by subjecting their physical characteristics to principal components analysis, and three speed ratios, i.e. the ratio of the feed screw speed and the roll speed of the roll compactor, were included in a full factorial design. Orthogonal projection to latent structures was then used to model the properties of the resulting roll compacted products (ribbons, granules and tablets) as a function of the physical MCC properties and the speed ratio. This modified version of partial least squares regression separates variation in the design correlated to the considered response from the variation orthogonal to that response. The contributions of the MCC properties and the speed ratio to the predictive and orthogonal components of the models were used to evaluate the effect of the design variation. The models indicated that several MCC properties, e.g. bulk density and compressibility, affected all granule and tablet properties, but only one studied ribbon property: porosity. After roll compaction, Ceolus KG 1000 resulted in tablets with obvious higher tensile strength and lower disintegration time compared to the other MCC grades. This study confirmed that the particle size increase caused by roll compaction is highly responsible for the tensile strength decrease of the tablets.
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| 7. |
- Dumarey, Melanie, et al.
(författare)
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OPLS methods for the analysis of hyperspectral images—comparison with MCR-ALS
- 2014
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Ingår i: Journal of Chemometrics. - : John Wiley & Sons. - 0886-9383 .- 1099-128X. ; 28:8, s. 687-696
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Tidskriftsartikel (refereegranskat)abstract
- Two new orthogonal projections to latent structures (OPLS) based methods were proposed to analyze hyperspectral images, enabling the visualization ofmultiple chemical compounds in onematrix without the need of extensive preprocessing. Both proposed methods delivered images representing the chemical distribution in the ribbon similar to the more traditional multivariate curve resolution–alternating least squares (MCR-ALS) method, but their image background was less dynamic resulting in a stronger chemical contrast. This indicated that the methods successfully removed structured variation orthogonal to the chemical information (pure spectra of individual compounds), which was confirmed by the fact that physical scattering effects caused by grooves and edges were captured in the images visualizing the orthogonal components of the model. Hereby, the OPLS-based method employing the pure spectra as weights in the OPLS algorithm was more successful in distinguishing compounds with a similar spectral signal than the transposed OPLS algorithm(pure spectra of individual compounds were used as response in OPLS model). It should be noted that for the main compounds, the MCR-ALS method enabled easier visual interpretation compared to the OPLS-based methods by setting all values below zero to zero, resulting in a higher contrast between pixels containing the studied compound and pixels not containing that compound.
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| 8. |
- Eliasson, Mattias, et al.
(författare)
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From data processing to multivariate validation : essential steps in extracting interpretable information from metabolomics data
- 2011
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Ingår i: Current Pharmaceutical Biotechnology. - : Bentham Science Publishers. - 1389-2010 .- 1873-4316. ; 12:7, s. 996-1004
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Forskningsöversikt (refereegranskat)abstract
- In metabolomics studies there is a clear increase of data. This indicates the necessity of both having a battery of suitable analysis methods and validation procedures able to handle large amounts of data. In this review, an overview of the metabolomics data processing pipeline is presented. A selection of recently developed and most cited data processing methods is discussed. In addition, commonly used chemometric and machine learning analysis methods as well as validation approaches are described.
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| 9. |
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| 10. |
- Eliasson, Mattias, et al.
(författare)
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Strategy for optimizing LC-MS data processing in Metabolomics : A design of experiments approach
- 2012
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 84:15, s. 6869-6876
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Tidskriftsartikel (refereegranskat)abstract
- A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and integrated peak areas. The reliability index metric, used to define peak quality, simultaneously favors reliable peaks and disfavors unreliable peaks using a weighted ratio between peaks with high and low response linearity. DoE optimization resulted in the case studies in more than 57% improvement in the reliability index compared to the use of the default settings. The proposed strategy can be applied to any other data processing software involving parameters to be tuned, e.g., MZmine 2. It can also be fully automated and used as a module in a complete metabolomics data processing pipeline.
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