| 1. |
- Pirttilä, Kristian, 1986-
(författare)
-
Development of analytical methods for the determination of the small molecule component of complex biological systems
- 2022
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The research field of untargeted metabolomics aims to determine the relative abundance of all small metabolites in a biological system in order to find biomarkers or make biological inference with regards to the internal or external stimuli. This is no trivial aim, as the small metabolites are both vast in numbers and extremely diverse in their chemical properties. As such, no single analytical method exist that is able to capture the entire metabolome on its own. In addition, the data generated from such experiments is both immense in volume and very complex. This forces researchers to use algorithmic data processing methods to extract the informative part of this data. Such algorithms are, however, both difficult to parametrize and designed to be highly inclusive, the combination of which often leads to errors. One such algorithm is the peak picking procedures used to find chromatographic peaks in liquid chromatography-mass spectrometry (LC-MS) data.In this thesis, four papers are included that focus both on the development of new methods for sample analysis and data processing as well as the application of such, and other, methods in two interdisciplinary research projects. The first paper describes the development and application of a protocol for LC-MS based untargeted analysis of guinea pig perilymph. The focus of the study was to investigate the biochemical processes underlying the protective effect of hydrogen gas on noise-induced hearing loss (NIHL) in guinea pigs exposed to impulse noise. This study sparked two research projects based on limitations observed during the analytical work. The first limitation was that of limited chemical coverage in the analysis when sample volumes are highly limited. The second paper describes the design and validation of a novel separation method for the sequential analysis of both hydrophilic and lipophilic compounds in biological samples. The second limitation observed was the abundance of false peaks reported by peak picking software. These have a negative effect on both downstream data processing as well as data analysis and metabolite identification. The third paper describes the development of a new algorithm for comprehensive peak characterization in untargeted analytical data with the purpose of filtering such false peaks. Both methods presented in the second and third paper were applied to the analysis of guinea pigs perilymph samples in a follow-up study on the attenuating effect of hydrogen gas on NIHL in guinea pigs exposed to broad band continuous noise.
|
|
| 2. |
- Wuolikainen, Anna, 1980-
(författare)
-
Metabolomics studies of ALS : a multivariate search for clues about a devastating disease
- 2009
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease, motor neuron disease (MND) and Lou Gehrig’s disease, is a deadly, adult-onset neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons, resulting in evolving paresis of the linked muscles. ALS is defined by classical features of the disease, but may present as a wide spectrum of phenotypes. About 10% of all ALS cases have been reported as familial, of which about 20% have been associated with mutations in the gene encoding for CuZn superoxide dismutase (SOD1). The remaining cases are regarded as sporadic. Research has advanced our understanding of the disease, but the cause is still unknown, no reliable diagnostic test exists, no cure has been found and the current therapies are unsatisfactory. Riluzole (Rilutek®) is the only registered drug for the treatment of ALS. The drug has shown only a modest effect in prolonging life and the mechanism of action of riluzole is not yet fully understood. ALS is diagnosed by excluding diseases with similar symptoms. At an early stage, there are numerous possible diseases that may present with similar symptoms, thereby making the diagnostic procedure cumbersome, extensive and time consuming with a significant risk of misdiagnosis. Biomarkers that can be developed into diagnostic test of ALS are therefore needed. The high number of unsuccessful attempts at finding a single diseasespecific marker, in combination with the complexity of the disease, indicates that a pattern of several markers is perhaps more likely to provide a diagnostic signature for ALS. Metabolomics, in combination with chemometrics, can be a useful tool with which to study human disease. Metabolomics can screen for small molecules in biofluids such as cerebrospinal fluid (CSF) and chemometrics can provide structure and tools in order to handle the types of data generated from metabolomics. In this thesis, ALS has been studied using a combination of metabolomics and chemometrics. Collection and storage of CSF in relation to metabolite stability have been extensively evaluated. Protocols for metabolomics on CSF samples have been proposed, used and evaluated. In addition, a new feature of data processing allowing new samples to be predicted into existing models has been tested, evaluated and used for metabolomics on blood and CSF. A panel of potential biomarkers has been generated for ALS and subtypes of ALS. An overall decrease in metabolite concentration was found for subjects with ALS compared to their matched controls. Glutamic acid was one of the metabolites found to be decreased in patients with ALS. A larger metabolic heterogeneity was detected among SALS cases compared to FALS. This was also reflected in models of SALS and FALS against their respective matched controls, where no significant difference from control was found for SALS while the FALS samples significantly differed from their matched controls. Significant deviating metabolic patterns were also found between ALS subjects carrying different mutations in the gene encoding SOD1.
|
|
| 3. |
- Elmsjö, Albert, 1986-
(författare)
-
Selectivity in NMR and LC-MS Metabolomics : The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics.
- 2017
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Until now, most metabolomics protocols have been optimized towards high sample throughput and high metabolite coverage, parameters considered to be highly important for identifying influenced biological pathways and to generate as many potential biomarkers as possible. From an analytical point of view this can be troubling, as neither sample throughput nor the number of signals relates to actual quality of the detected signals/metabolites. However, a method’s selectivity for a specific signal/metabolite is often closely associated to the quality of that signal, yet this is a parameter often neglected in metabolomics.This thesis demonstrates the importance of considering selectivity when developing NMR and LC-MS metabolomics methods, and introduces a novel approach for measuring chromatographic and signal selectivity in LC-MS metabolomics.Selectivity for various sample preparations and HILIC stationary phases was compared. The choice of sample preparation affected the selectivity in both NMR and LC-MS. For the stationary phases, selectivity differences related primarily to retention differences of unwanted matrix components, e.g. inorganic salts or glycerophospholipids. Metabolites co-eluting with these matrix components often showed an incorrect quantitative signal, due to an influenced ionization efficiency and/or adduct formation.A novel approach for measuring selectivity in LC-MS metabolomics has been introduced. By dividing the intensity of each feature (a unique mass at a specific retention time) with the total intensity of the co-eluting features, a ratio representing the combined chromatographic (amount of co-elution) and signal (e.g. in-source fragmentation) selectivity is acquired. The calculated co-feature ratios have successfully been used to compare the selectivity of sample preparations and HILIC stationary phases.In conclusion, standard approaches in metabolomics research might be unwise, as each metabolomics investigation is often unique. The methods used should be adapted for the research question at hand, primarily based on any key metabolites, as well as the type of sample to be analyzed. Increased selectivity, through proper choice of analytical methods, may reduce the risks of matrix-associated effects and thereby reduce the false positive and false negative discovery rate of any metabolomics investigation.
|
|
| 4. |
- Madsen, Rasmus Kirkegaard, 1979-
(författare)
-
Metabolic variation in autoimmune diseases
- 2012
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The human being and other animals contain immensely complex biochemical processes that govern their function on a cellular level. It is estimated that several thousand small molecules (metabolites) are produced by various biochemical pathways in humans. Pathological processes can introduce perturbations in these biochemical pathways which can lead to changes in the amounts of some metabolites.Developments in analytical chemistry have made it possible measure a large number metabolites in a single blood sample, which gives a metabolic profile. In this thesis I have worked on establishing and understanding metabolic profiles from patients with rheumatoid arthritis (RA) and from animal models of the autoimmune diseases diabetes mellitus type 1 (T1D) and RA.Using multivariate statistical methods it is possible to identify differences between metabolic profiles of different groups. As an example we identified differences between patients with RA and healthy volunteers. This can be used to elucidate the biochemical processes that are active in a given pathological condition.Metabolite concentrations are affected by a many other things than the presence or absence of a disease. Both genomic and environmental factors are known to influence metabolic profiles. A main focus of my work has therefore been on finding strategies for ensuring that the results obtained when comparing metabolic profiles were valid and relevant. This strategy has included repetition of experiments and repeated measurement of individuals’ metabolic profiles in order to understand the sources of variation.Finding the most stable and reproducible metabolic effects has allowed us to better understand the biochemical processes seen in the metabolic profiles. This makes it possible to relate the metabolic profile differences to pathological processes and to genes and proteins involved in these.The hope is that metabolic profiling in the future can be an important tool for finding biomarkers useful for disease diagnosis, for identifying new targets for drug design and for mapping functional changes of genomic mutations. This has the potential to revolutionize our understanding of disease pathology and thus improving health care.
|
|
| 5. |
- Torell, Frida, 1988-
(författare)
-
Multivariate data analysis of metabolomic multi-tissue samples
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Multi-tissue metabolomics involves characterisation of the metabolome of several tissue types. The metabolome consists of small chemical entities of low molecular weight called metabolites, which are constantly produced and interchanged through a vast variety of biochemical reactions occurring throughout living organisms. Metabolome alterations can be attributed to genetics, environment, and diseases. We used gas chromatography timeof-flight mass spectrometry (GC TOF-MS) to characterise the metabolome of mouse organ samples: gut, kidney, liver, muscle, pancreas and plasma. Samples were obtained from wild-type mice and mice carrying a mutation in the hepatocyte nuclear factor 1b (HNF1b) gene, referred to as MODY5/RCAD (for maturity onset diabetes of the young 5/renal cysts and diabetes syndrome) mice. MODY is a class of hereditary diabetes mellitus, and MODY5 is caused by mutations in HNF1B, resulting in a wide range of manifestations, including renal diseases, kidney and genitourinary malformation, and elevation of liver enzymes. Today, MODY5 in humans is diagnosed using genetic tests, and varying referral rates and manifestations have resulted in misdiagnosis. Our main focus was therefore to increase understanding of the metabolism associated with MODY5/RCAD by studying the metabolic profiles of individual organs and plasma (Paper I) from MODY5/RCAD mutant and wildtype mice. The mouse model displayed an overall metabolic pattern consistent with the presumed outcome of the mutation in humans, making the MODY5/RCAD model suitable for studies of HNF1B-associated diseases. An understanding of metabolite origin would be beneficial for understanding the plasma profile associated with MODY5/RCAD. We used hierarchical modelling to provide an understanding of metabolite origin by detecting how metabolites from the organs contributed to the plasma metabolic profile (Paper II). Both specific and overall organ metabolite contributions to the plasma metabolic profile were studied. Further exploration of the dataset involved study of its innate variation using joint and unique multiblock analysis (JUMBA; Paper III). In addition, we explored the effects of improper sample handling for metabolomic multi-tissue data, and we studied the similarities and differences in the responses to thawing between organ tissues (Paper IV) and plasma samples (Paper V), thus identifying metabolic profiles that could indicate compromised samples. These profiles could be beneficial for large-scale collaborations that involve sample exposure to unsuitable conditions. Altogether, we have contributed to an increased understanding of the MODY5/RCAD multi-tissue metabolomic dataset and worked up protocols and strategies for how small datasets should be handled.
|
|
| 6. |
- Abdellah, Tebani, et al.
(författare)
-
Integration of molecular profiles in a longitudinal wellness profiling cohort.
- 2020
-
Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies andimmune cell profiling, complementedwith gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.
|
|
| 7. |
- Furukawa, Toshi A., et al.
(författare)
-
Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression : a systematic review and component network meta-analysis using individual data
- 2021
-
Ingår i: Lancet psychiatry. - London, United Kingdom : Elsevier. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
-
Forskningsöversikt (refereegranskat)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
|
|
| 8. |
|
|
| 9. |
- Jurca, Manuela, et al.
(författare)
-
Biotechnological adaptation of seasonal growth using high yielding Populus gibberellin overproducing trees
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Tree growth is central to terrestrial ecology and the forestry industry. The overproduction by biotechnological means of hormones such as gibberellins (GAs) has been used as a powerful toolto greatly increase tree yield and wood properties. However, for trees in temperate and boreal regions, overexpressing GAs prevents the ability to induce vegetative dormancy, and results in reduced yield and tree loss over time. Since Populus trees are using an internal 24-h (circadian) clock to synchronize their metabolism and growth with local, predictable changes in the external environment, we focused on circadian control of GA metabolism, to showcase the principle of seasonal growth adaptation. To obtain both maintained growth benefits and a seasonally timed growth, we set out to modulate levels of bioactive GAs by using the endogenous Populus tremula× P. tremuloides CycD3 promoter. We show that both high yield and biotechnical seasonal growth adaptation is obtained with this promoter, which is coordinated by the clock protein LATE ELONGATED HYPOCOTYL 2 (PttLHY2). This work paves the way for future precision breeding of trees with local adaptation and increased yield.
|
|
| 10. |
- Karyotaki, Eirini, et al.
(författare)
-
Internet-Based Cognitive Behavioral Therapy for Depression : A Systematic Review and Individual Patient Data Network Meta-analysis
- 2021
-
Ingår i: JAMA psychiatry. - : American Medical Association. - 2168-6238 .- 2168-622X. ; 78:4, s. 361-371
-
Forskningsöversikt (refereegranskat)abstract
- IMPORTANCE: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them.OBJECTIVE: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information.DATA SOURCES: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019.STUDY SELECTION: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization.DATA EXTRACTION AND SYNTHESIS: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression.MAIN OUTCOMES AND MEASURES: Patient Health Questionnaire-9 (PHQ-9) scores.RESULTS: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9.CONCLUSIONS AND RELEVANCE: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.
|
|
