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Jonsson, Pär
Publications (10 of 35) Show all publications
Näsström, E., Jonsson, P., Johansson, A., Dongol, S., Karkey, A., Basnyat, B., . . . Baker, S. (2018). Diagnostic metabolite biomarkers of chronic typhoid carriage. PLoS Neglected Tropical Diseases, 12(1), Article ID e0006215.
Open this publication in new window or tab >>Diagnostic metabolite biomarkers of chronic typhoid carriage
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2018 (English)In: PLoS Neglected Tropical Diseases, ISSN 1935-2727, E-ISSN 1935-2735, Vol. 12, no 1, article id e0006215Article in journal (Refereed) Published
Abstract [en]

Background: Salmonella Typhi and Salmonella Paratyphi A are the agents of enteric (typhoid) fever; both can establish chronic carriage in the gallbladder. Chronic Salmonella carriers are typically asymptomatic, intermittently shedding bacteria in the feces, and contributing to disease transmission. Detecting chronic carriers is of public health relevance in areas where enteric fever is endemic, but there are no routinely used methods for prospectively identifying those carrying Salmonella in their gallbladder.

Methodology/Principal findings: Here we aimed to identify biomarkers of Salmonella carriage using metabolite profiling. We performed metabolite profiling on plasma from Nepali patients undergoing cholecystectomy with confirmed S. Typhi or S. Paratyphi A gallbladder carriage (and non-carriage controls) using two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS) and supervised pattern recognition modeling. We were able to significantly discriminate Salmonella carriage samples from non-carriage control samples. We were also able to detect differential signatures between S. Typhi and S. Paratyphi A carriers. We additionally compared carriage metabolite profiles with profiles generated during acute infection; these data revealed substantial heterogeneity between metabolites associated with acute enteric fever and chronic carriage. Lastly, we found that Salmonella carriers could be significantly distinguished from non-carriage controls using only five metabolites, indicating the potential of these metabolites as diagnostic markers for detecting chronic Salmonella carriers.

Conclusions/Significance: Our novel approach has highlighted the potential of using metabolomics to search for diagnostic markers of chronic Salmonella carriage. We suggest further epidemiological investigations of these potential biomarkers in alternative endemic enteric fever settings.

National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-145618 (URN)10.1371/journal.pntd.0006215 (DOI)000424022700063 ()29373578 (PubMedID)
Funder
Swedish Research Council, VR-U 2015-03442
Available from: 2018-04-17 Created: 2018-04-17 Last updated: 2018-06-09Bibliographically approved
Franklin, O., Jonsson, P., Billing, O., Lundberg, E., Öhlund, D., Nyström, H., . . . Sund, M. (2018). Plasma micro-RNA alterations appear late in pancreatic cancer. Annals of Surgery, 267(4), 775-781
Open this publication in new window or tab >>Plasma micro-RNA alterations appear late in pancreatic cancer
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2018 (English)In: Annals of Surgery, ISSN 0003-4932, E-ISSN 1528-1140, Vol. 267, no 4, p. 775-781Article in journal (Refereed) Published
Abstract [en]

Objectives: The aim of this research was to study whether plasma microRNAs (miRNA) can be used for early detection of pancreatic cancer (PC) by analyzing prediagnostic plasma samples collected before a PC diagnosis. Background: PC has a poor prognosis due to late presenting symptoms and early metastasis. Circulating miRNAs are altered in PC at diagnosis but have not been evaluated in a prediagnostic setting. Methods: We first performed an initial screen using a panel of 372 miRNAs in a retrospective case-control cohort that included early-stage PC patients and healthy controls. Significantly altered miRNAs at diagnosis were then measured in an early detection case-control cohort wherein plasma samples in the cases are collected before a PC diagnosis. Carbohydrate antigen 19–9 (Ca 19–9) levels were measured in all samples for comparison. Results: Our initial screen, including 23 stage I-II PC cases and 22 controls, revealed 15 candidate miRNAs that were differentially expressed in plasma samples at PC diagnosis. We combined all 15 miRNAs into a multivariate statistical model, which outperformed Ca 19–9 in receiver-operating characteristics analysis. However, none of the candidate miRNAs, individually or in combination, were significantly altered in prediagnostic plasma samples from 67 future PC patients compared with 132 matched controls. In comparison, Ca 19–9 levels were significantly higher in the cases at <5 years before diagnosis. Conclusion: Plasma miRNAs are altered in PC patients at diagnosis, but the candidate miRNAs found in this study appear late in the course of the disease and cannot be used for early detection of the disease.

Keywords
blood samples, early detection, micro-RNA, miRNA, pancreatic cancer
National Category
Clinical Laboratory Medicine Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-127998 (URN)10.1097/SLA.0000000000002124 (DOI)000435846900046 ()28425921 (PubMedID)2-s2.0-85044257717 (Scopus ID)
Note

Originally included in thesis in manuscript form.

Available from: 2016-11-21 Created: 2016-11-21 Last updated: 2018-09-27Bibliographically approved
Björkblom, B., Wibom, C., Jonsson, P., Mörén, L., Andersson, U., Johannesen, T. B., . . . Melin, B. (2016). Metabolomic screening of pre-diagnostic serum samples identifies association between alpha- and gamma-tocopherols and glioblastoma risk. OncoTarget, 7(24), 37043-37053
Open this publication in new window or tab >>Metabolomic screening of pre-diagnostic serum samples identifies association between alpha- and gamma-tocopherols and glioblastoma risk
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2016 (English)In: OncoTarget, ISSN 1949-2553, E-ISSN 1949-2553, Vol. 7, no 24, p. 37043-37053Article in journal (Refereed) Published
Abstract [en]

Glioblastoma is associated with poor prognosis with a median survival of one year. High doses of ionizing radiation is the only established exogenous risk factor. To explore new potential biological risk factors for glioblastoma, we investigated alterations in metabolite concentrations in pre-diagnosed serum samples from glioblastoma patients diagnosed up to 22 years after sample collection, and undiseased controls. The study points out a latent biomarker for future glioblastoma consisting of nine metabolites (gamma-tocopherol, alpha-tocopherol, erythritol, erythronic acid, myo-inositol, cystine, 2-keto-L-gluconic acid, hypoxanthine and xanthine) involved in antioxidant metabolism. We detected significantly higher serum concentrations of alpha-tocopherol (p=0.0018) and gamma-tocopherol (p=0.0009) in future glioblastoma cases. Compared to their matched controls, the cases showed a significant average fold increase of alpha- and gamma-tocopherol levels: 1.2 for alpha-T (p=0.018) and 1.6 for gamma-T (p=0.003). These tocopherol levels were associated with a glioblastoma odds ratio of 1.7 (alpha-T, 95% CI: 1.0-3.0) and 2.1 (gamma-T, 95% CI: 1.2-3.8). Our exploratory metabolomics study detected elevated serum levels of a panel of molecules with antioxidant properties as well as oxidative stress generated compounds. Additional studies are necessary to confirm the association between the observed serum metabolite pattern and future glioblastoma development.

Keywords
population-based, serum metabolite, vitamin E, antioxidants, brain tumor
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-123973 (URN)10.18632/oncotarget.9242 (DOI)000377756800119 ()
Available from: 2016-11-15 Created: 2016-07-07 Last updated: 2018-06-09Bibliographically approved
Wuolikainen, A., Jonsson, P., Ahnlund, M., Antti, H., Marklund, S. L., Moritz, T., . . . Trupp, M. (2016). Multi-platform mass spectrometry analysis of the CSF and plasma metabolomes of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects. Molecular Biosystems, 12(4), 1287-1298
Open this publication in new window or tab >>Multi-platform mass spectrometry analysis of the CSF and plasma metabolomes of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects
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2016 (English)In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 12, no 4, p. 1287-1298Article in journal (Refereed) Published
Abstract [en]

Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) are protein-aggregation diseases that lack clear molecular etiologies. Biomarkers could aid in diagnosis, prognosis, planning of care, drug target identification and stratification of patients into clinical trials. We sought to characterize shared and unique metabolite perturbations between ALS and PD and matched controls selected from patients with other diagnoses, including differential diagnoses to ALS or PD that visited our clinic for a lumbar puncture. Cerebrospinal fluid (CSF) and plasma from rigorously age-, sex- and sampling-date matched patients were analyzed on multiple platforms using gas chromatography (GC) and liquid chromatography (LC)-mass spectrometry (MS). We applied constrained randomization of run orders and orthogonal partial least squares projection to latent structure-effect projections (OPLS-EP) to capitalize upon the study design. The combined platforms identified 144 CSF and 196 plasma metabolites with diverse molecular properties. Creatine was found to be increased and creatinine decreased in CSF of ALS patients compared to matched controls. Glucose was increased in CSF of ALS patients and alpha-hydroxybutyrate was increased in CSF and plasma of ALS patients compared to matched controls. Leucine, isoleucine and ketoleucine were increased in CSF of both ALS and PD. Together, these studies, in conjunction with earlier studies, suggest alterations in energy utilization pathways and have identified and further validated perturbed metabolites to be used in panels of biomarkers for the diagnosis of ALS and PD.

National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-119312 (URN)10.1039/c5mb00711a (DOI)000372612600023 ()26883206 (PubMedID)
Available from: 2016-04-17 Created: 2016-04-15 Last updated: 2018-06-07Bibliographically approved
Wu, J., Wuolikainen, A., Trupp, M., Jonsson, P., Marklund, S. L., Andersen, P. M., . . . Öhman, A. (2016). NMR analysis of the CSF and plasma metabolome of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects. Metabolomics, 12(6), Article ID 101.
Open this publication in new window or tab >>NMR analysis of the CSF and plasma metabolome of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects
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2016 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, no 6, article id 101Article in journal (Refereed) Published
Abstract [en]

Introduction: Amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are two severe neurodegenerative disorders for which the disease mechanisms are poorly understood and reliable biomarkers are absent.

Objectives: To identify metabolite biomarkers for ALS and PD, and to gain insights into which metabolic pathways are involved in disease.

Methods: Nuclear magnetic resonance (NMR) metabolomics was utilized to characterize the metabolite profiles of cerebrospinal fluid (CSF) and plasma from individuals in three age, gender, and sampling-date matched groups, comprising 22 ALS, 22 PD and 28 control subjects.

Results: Multivariate analysis of NMR data generated robust discriminatory models for separation of ALS from control subjects. ALS patients showed increased concentrations of several metabolites in both CSF and plasma, these are alanine (CSF fold change = 1.22, p = 0.005), creatine (CSF-fc = 1.17, p = 0.001), glucose (CSF-fc = 1.11, p = 0.036), isoleucine (CSF-fc = 1.24, p = 0.002), and valine (CSF-fc = 1.17, p = 0.014). Additional metabolites in CSF (creatinine, dimethylamine and lactic acid) and plasma (acetic acid, glutamic acid, histidine, leucine, pyruvate and tyrosine) were also important for this discrimination. Similarly, panels of CSF-metabolites that discriminate PD from ALS and control subjects were identified.

Conclusions: The results for the ALS patients suggest an affected creatine/creatinine pathway and an altered branched chain amino acid (BCAA) metabolism, and suggest links to glucose and energy metabolism. Putative metabolic markers specific for ALS (e.g. creatinine and lactic acid) and PD (e.g. 3-hydroxyisovaleric acid and mannose) were identified, while several (e.g. creatine and BCAAs) were shared between ALS and PD, suggesting some overlap in metabolic alterations in these disorders.

Keywords
Amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), NMR metabolomics, Biomarker, rebrospinal fluid (CSF), Plasma
National Category
Neurosciences
Identifiers
urn:nbn:se:umu:diva-124194 (URN)10.1007/s11306-016-1041-6 (DOI)000378752900006 ()
Available from: 2016-08-04 Created: 2016-07-28 Last updated: 2018-06-07Bibliographically approved
Figueira, J., Jonsson, P., Nordin Adolfsson, A., Adolfsson, R., Nyberg, L. & Öhman, A. (2016). NMR analysis of the human saliva metabolome distinguishes dementia patients from matched controls. Molecular Biosystems, 12(8), 2562-2571
Open this publication in new window or tab >>NMR analysis of the human saliva metabolome distinguishes dementia patients from matched controls
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2016 (English)In: Molecular Biosystems, ISSN 1742-206X, E-ISSN 1742-2051, Vol. 12, no 8, p. 2562-2571Article in journal (Refereed) Published
Abstract [en]

Saliva is a biofluid that is sensitive to metabolic changes and is straightforward to collect in a non-invasive manner, but it is seldom used for metabolite analysis when studying neurodegenerative disorders. We present a procedure for both an untargeted and targeted analysis of the saliva metabolome in which nuclear magnetic resonance (NMR) spectroscopy is used in combination with multivariate data analysis. The applicability of this approach is demonstrated on saliva samples selected from the 25 year prospective Betula study, including samples from dementia subjects with either Alzheimer's disease (AD) or vascular dementia at the time of sampling or who developed it by the next sampling/assessment occasion five years later, and age-, gender-, and education-matched control individuals without dementia. Statistically significant multivariate models were obtained that separated patients with dementia from controls and revealed seven discriminatory metabolites. Dementia patients showed significantly increased concentrations of acetic acid (fold change (fc) = 1.25, p = 2 x 10(-5)), histamine (fc = 1.26, p = 0.019), and propionate (fc = 1.35, p = 0.002), while significantly decreased levels were observed for dimethyl sulfone (fc = 0.81, p = 0.005), glycerol (fc = 0.79, p = 0.04), taurine (fc = 0.70, p = 0.007), and succinate (fc = 0.62, p = 0.008). Histamine, succinate, and taurine are known to be important in AD, and acetic acid and glycerol are involved in related pathways. Dimethyl sulfone and propionate originate from the diet and bacterial flora and might reflect poorer periodontal status in the dementia patients. For these seven metabolites, a weak but statistically significant pre-diagnostic value was observed. Taken together, we present a robust and general NMR analysis approach for studying the saliva metabolome that has potential use for screening and early detection of dementia.

National Category
Clinical Laboratory Medicine Neurology
Identifiers
urn:nbn:se:umu:diva-124525 (URN)10.1039/c6mb00233a (DOI)000379873100022 ()27265744 (PubMedID)
Available from: 2016-08-17 Created: 2016-08-15 Last updated: 2018-06-07Bibliographically approved
Jonsson, P., Wuolikainen, A., Thysell, E., Chorell, E., Stattin, P., Wikström, P. & Antti, H. (2015). Constrained randomization and multivariate effect projections improve information extraction and biomarker pattern discovery in metabolomics studies involving dependent samples. Metabolomics, 11(6), 1667-1678
Open this publication in new window or tab >>Constrained randomization and multivariate effect projections improve information extraction and biomarker pattern discovery in metabolomics studies involving dependent samples
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2015 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 11, no 6, p. 1667-1678Article in journal (Refereed) Published
Abstract [en]

Analytical drift is a major source of bias in mass spectrometry based metabolomics confounding interpretation and biomarker detection. So far, standard protocols for sample and data analysis have not been able to fully resolve this. We present a combined approach for minimizing the influence of analytical drift on multivariate comparisons of matched or dependent samples in mass spectrometry based metabolomics studies. The approach is building on a randomization procedure for sample run order, constrained to independent randomizations between and within dependent sample pairs (e.g. pre/post intervention). This is followed by a novel multivariate statistical analysis strategy allowing paired or dependent analyses of individual effects named OPLS-effect projections (OPLS-EP). We show, using simulated data that OPLS-EP gives improved interpretation over existing methods and that constrained randomization of sample run order in combination with an appropriate dependent statistical test increase the accuracy and sensitivity and decrease the false omission rate in biomarker detection. We verify these findings and prove the strength of the suggested approach in a clinical data set consisting of LC/MS data of blood plasma samples from patients before and after radical prostatectomy. Here OPLS-EP compared to traditional (independent) OPLS-discriminant analysis (OPLS-DA) on constrained randomized data gives a less complex model (3 versus 5 components) as well a higher predictive ability (Q2 = 0.80 versus Q2 = 0.55). We explain this by showing that paired statistical analysis detects 37 unique significant metabolites that were masked for the independent test due to bias, including analytical drift and inter-individual variation.

Place, publisher, year, edition, pages
Springer, 2015
Keywords
Metabolomics, Chemometrics, Dependent samples, Analytical drift, Run order design, Effect projections
National Category
Chemical Sciences Endocrinology and Diabetes
Identifiers
urn:nbn:se:umu:diva-111340 (URN)10.1007/s11306-015-0818-3 (DOI)000363040600017 ()
Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2018-06-07Bibliographically approved
Nordin, A., Akimoto, C., Wuolikainen, A., Alstermark, H., Jonsson, P., Birve, A., . . . Andersen, P. M. (2015). Extensive size variability of the GGGGCC expansion in C9orf72 in both neuronal and non-neuronal tissues in 18 patients with ALS or FTD. Human Molecular Genetics, 24(11), 3133-3142
Open this publication in new window or tab >>Extensive size variability of the GGGGCC expansion in C9orf72 in both neuronal and non-neuronal tissues in 18 patients with ALS or FTD
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2015 (English)In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 24, no 11, p. 3133-3142Article in journal (Refereed) Published
Abstract [en]

A GGGGCC-repeat expansion in C9orf72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) among Caucasians. However, little is known about the variability of the GGGGCC expansion in different tissues and whether this correlates with the observed phenotype. Here, we used Southern blotting to estimate the size of hexanucleotide expansions in C9orf72 in neural and non-neural tissues from 18 autopsied ALS and FTD patients with repeat expansion in blood. Digitalization of the Southern blot images allowed comparison of repeat number, smear distribution and expansion band intensity between tissues and between patients. We found marked intra-individual variation of repeat number between tissues, whereas there was less variation within each tissue group. In two patients, the size variation between tissues was extreme, with repeat numbers below 100 in all studied non-neural tissues, whereas expansions in neural tissues were 20-40 times greater and in the same size range observed in neural tissues of the other 16 patients. The expansion pattern in different tissues could not distinguish between diagnostic groups and no correlation was found between expansion size in frontal lobe and occurrence of cognitive impairment. In ALS patients, a less number of repeats in the cerebellum and parietal lobe correlated with earlier age of onset and a larger number of repeats in the parietal lobe correlated with a more rapid progression. In 43 other individuals without repeat expansion in blood, we find that repeat sizes up to 15 are stable, as no size variation between blood, brain and spinal cord was found.

National Category
Medical Genetics Cell and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-103256 (URN)10.1093/hmg/ddv064 (DOI)000355674000011 ()25712133 (PubMedID)
Available from: 2015-05-19 Created: 2015-05-19 Last updated: 2018-06-07Bibliographically approved
Trupp, M., Jonsson, P., Öhrfelt, A., Zetterberg, H., Obudulu, O., Malm, L., . . . Forsgren, L. (2014). Metabolite and peptide levels in plasma and CSF differentiating healthy controls from patients with newly diagnosed Parkinson's disease. Journal of Parkinson's Disease, 4(3), 549-560
Open this publication in new window or tab >>Metabolite and peptide levels in plasma and CSF differentiating healthy controls from patients with newly diagnosed Parkinson's disease
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2014 (English)In: Journal of Parkinson's Disease, ISSN 1877-7171, E-ISSN 1877-718X, Vol. 4, no 3, p. 549-560Article in journal (Refereed) Published
Abstract [en]

Background: Parkinson's disease (PD) is a progressive, multi-focal neurodegenerative disease for which there is no effective disease modifying treatment. A critical requirement for designing successful clinical trials is the development of robust and reproducible biomarkers identifying PD in preclinical stages. Objective: To investigate the potential for a cluster of biomarkers visualized with multiple analytical platforms to provide a clinically useful tool. Methods: Gas Chromatography-Mass Spectrometry (GC-TOFMS) based metabolomics and immunoassay-based protein/peptide analyses on samples from patients with PD diagnosed in Northern Sweden. Low molecular weight compounds from both plasma and cerebrospinal fluid (CSF) from 20 healthy subjects (controls) and 20 PD patients at the time of diagnosis (baseline) were analyzed. Results: In plasma, we found a significant increase in several amino acids and a decrease in C16-C18 saturated and unsaturated fatty acids in patients as compared to control subjects. We also observed an increase in plasma levels of pyroglutamate and 2-oxoisocaproate (ketoleucine) that may be indicative of increased metabolic stress in patients. In CSF, there was a generally lower level of metabolites in PD as compared to controls, with a specific decrease in 3-hydroxyisovaleric acid, tryptophan and creatinine. Multivariate analysis and modeling of metabolites indicates that while the PD samples can be separated from control samples, the list of detected compounds will need to be expanded in order to define a robust predictive model. CSF biomarker immunoassays of candidate peptide/protein biomarkers revealed a significant decrease in the levels of A beta-38 and A beta-42, and an increase in soluble APP alpha in CSF of patients. Furthermore, these peptides showed significant correlations to each other, and positive correlations to the CSF levels of several 5- and 6-carbon sugars. However, combining these metabolites and proteins/peptides into a single model did not significantly improve the statistical analysis. Conclusions: Together, this metabolomics study has detected significant alterations in plasma and CSF levels of a cluster of amino acids, fatty acids and sugars based on clinical diagnosis and levels of known protein and peptide biomarkers.

Place, publisher, year, edition, pages
Taylor & Francis, 2014
Keywords
Parkinson's, CSF, metabolomics, Abeta peptides, alpha-synuclein, GC-TOFMS, multivariate analysis, amino acids, long-chain fatty acids, carbohydrates
National Category
Neurology Neurosciences
Identifiers
urn:nbn:se:umu:diva-94567 (URN)10.3233/JPD-140389 (DOI)000341594600028 ()
Available from: 2014-11-04 Created: 2014-10-13 Last updated: 2018-06-07Bibliographically approved
Mousavi, M., Jonsson, P., Antti, H., Adolfsson, R., Nordin, A., Bergdahl, J., . . . Nyberg, L. (2014). Serum metabolomic biomarkers of dementia. Dementia and geriatric cognitive disorders extra, 4(2), 252-62
Open this publication in new window or tab >>Serum metabolomic biomarkers of dementia
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2014 (English)In: Dementia and geriatric cognitive disorders extra, E-ISSN 1664-5464, Vol. 4, no 2, p. 252-62Article in journal (Refereed) Published
Abstract [en]

Aims: This study compared serum metabolites of demented patients (Alzheimer's disease and vascular dementia) and controls, and explored serum metabolite profiles of nondemented individuals 5 years preceding the diagnosis. Methods: Cognitively healthy participants were followed up for 5-20 years. Cognitive assessment, serum sampling, and diagnosis were completed every 5 years. Multivariate analyses were conducted on the metabolite profiles generated by gas chromatography/time-of-flight mass spectrometry. Results: A significant group separation was found between demented patients and controls, and between incident cases and controls. Metabolites that contributed in both analyses were 3,4-dihydroxybutanoic acid, docosapentaenoic acid, and uric acid. Conclusions: Serum metabolite profiles are altered in demented patients, and detectable up to 5 years preceding the diagnosis. Blood sampling can make an important contribution to the early prediction of conversion to dementia.

Keywords
Memory, Early diagnosis, Alzheimer’s disease, Vascular dementia, Gas chromatography
National Category
Clinical Medicine
Identifiers
urn:nbn:se:umu:diva-92543 (URN)10.1159/000364816 (DOI)
Available from: 2014-08-28 Created: 2014-08-28 Last updated: 2018-06-07Bibliographically approved
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