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Search: (WFRF:(Uhlén Mathias)) srt2:(2020-2024) > (2021)

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1.
  • Abdellah, Tebani, et al. (author)
  • Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
  • 2021
  • In: Acta neuropathologica communications. - : BioMed Central (BMC). - 2051-5960. ; 9:1
  • Journal article (peer-reviewed)abstract
    • Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.
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2.
  • Adori, Csaba, et al. (author)
  • Disorganization and degeneration of liver sympathetic innervations in nonalcoholic fatty liver disease revealed by 3D imaging
  • 2021
  • In: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:30
  • Journal article (peer-reviewed)abstract
    • Hepatic nerves have a complex role in synchronizing liver metabolism. Here, we used three-dimensional (3D) immunoimaging to explore the integrity of the hepatic nervous system in experimental and human nonalcoholic fatty liver disease (NAFLD). We demonstrate parallel signs of mild degeneration and axonal sprouting of sympathetic innervations in early stages of experimental NAFLD and a collapse of sympathetic arborization in steatohepatitis. Human fatty livers display a similar pattern of sympathetic nerve degeneration, correlating with the severity of NAFLD pathology. We show that chronic sympathetic hyperexcitation is a key factor in the axonal degeneration, here genetically phenocopied in mice deficient of the Rac-1 activator Vav3. In experimental steatohepatitis, 3D imaging reveals a severe portal vein contraction, spatially correlated with the extension of the remaining nerves around the portal vein, enlightening a potential intrahepatic neuronal mechanism of portal hypertension. These fundamental alterations in liver innervation and vasculature uncover previously unidentified neuronal components in NAFLD pathomechanisms.
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3.
  • Altay, Özlem, et al. (author)
  • Combined Metabolic Activators Accelerates Recovery in Mild-to-Moderate COVID-19
  • 2021
  • In: Advanced Science. - : Wiley. - 2198-3844. ; 8:17
  • Journal article (peer-reviewed)abstract
    • COVID-19 is associated with mitochondrial dysfunction and metabolic abnormalities, including the deficiencies in nicotinamide adenine dinucleotide (NAD+) and glutathione metabolism. Here it is investigated if administration of a mixture of combined metabolic activators (CMAs) consisting of glutathione and NAD+ precursors can restore metabolic function and thus aid the recovery of COVID-19 patients. CMAs include l-serine, N-acetyl-l-cysteine, nicotinamide riboside, and l-carnitine tartrate, salt form of l-carnitine. Placebo-controlled, open-label phase 2 study and double-blinded phase 3 clinical trials are conducted to investigate the time of symptom-free recovery on ambulatory patients using CMAs. The results of both studies show that the time to complete recovery is significantly shorter in the CMA group (6.6 vs 9.3 d) in phase 2 and (5.7 vs 9.2 d) in phase 3 trials compared to placebo group. A comprehensive analysis of the plasma metabolome and proteome reveals major metabolic changes. Plasma levels of proteins and metabolites associated with inflammation and antioxidant metabolism are significantly improved in patients treated with CMAs as compared to placebo. The results show that treating patients infected with COVID-19 with CMAs lead to a more rapid symptom-free recovery, suggesting a role for such a therapeutic regime in the treatment of infections leading to respiratory problems.
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4.
  • Altay, Özlem, et al. (author)
  • Revealing the Metabolic Alterations during Biofilm Development of Burkholderia cenocepacia Based on Genome-Scale Metabolic Modeling
  • 2021
  • In: Metabolites. - : MDPI AG. - 2218-1989 .- 2218-1989. ; 11:4
  • Journal article (peer-reviewed)abstract
    • Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.
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5.
  • Arif, Muhammad, et al. (author)
  • INetModels 2.0: An interactive visualization and database of multi-omics data
  • 2021
  • In: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 49:W1, s. W271-W276
  • Journal article (peer-reviewed)abstract
    • It is essential to reveal the associations between various omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics, plasma metabolomics, as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and disease research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.
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6.
  • Arif, Muhammad, et al. (author)
  • Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction
  • 2021
  • In: Elife. - : eLife Sciences Publications, Ltd. - 2050-084X. ; 10
  • Journal article (peer-reviewed)abstract
    • Myocardial infarction (MI) promotes a range of systemic effects, many of which are unknown. Here, we investigated the alterations associated with MI progression in heart and other metabolically active tissues (liver, skeletal muscle, and adipose) in a mouse model of MI (induced by ligating the left ascending coronary artery) and sham-operated mice. We performed a genomewide transcriptomic analysis on tissue samples obtained 6- and 24 hr post MI or sham operation. By generating tissue-specific biological networks, we observed: (1) dysregulation in multiple biological processes (including immune system, mitochondrial dysfunction, fatty-acid beta-oxidation, and RNA and protein processing) across multiple tissues post MI and (2) tissue-specific dysregulation in biological processes in liver and heart post MI. Finally, we validated our findings in two independent MI cohorts. Overall, our integrative analysis highlighted both common and specific biological responses to MI across a range of metabolically active tissues.
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7.
  • Bayraktar, Abdulahad, et al. (author)
  • Revealing the Molecular Mechanisms of Alzheimer's Disease Based on Network Analysis
  • 2021
  • In: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 22:21
  • Journal article (peer-reviewed)abstract
    • The complex pathology of Alzheimer's disease (AD) emphasises the need for comprehensive modelling of the disease, which may lead to the development of efficient treatment strategies. To address this challenge, we analysed transcriptome data of post-mortem human brain samples of healthy elders and individuals with late-onset AD from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MayoRNAseq) studies in the AMP-AD consortium. In this context, we conducted several bioinformatics and systems medicine analyses including the construction of AD-specific co-expression networks and genome-scale metabolic modelling of the brain in AD patients to identify key genes, metabolites and pathways involved in the progression of AD. We identified AMIGO1 and GRPRASP2 as examples of commonly altered marker genes in AD patients. Moreover, we found alterations in energy metabolism, represented by reduced oxidative phosphorylation and ATPase activity, as well as the depletion of hexanoyl-CoA, pentanoyl-CoA, (2E)-hexenoyl-CoA and numerous other unsaturated fatty acids in the brain. We also observed that neuroprotective metabolites (e.g., vitamins, retinoids and unsaturated fatty acids) tend to be depleted in the AD brain, while neurotoxic metabolites (e.g., beta-alanine, bilirubin) were more abundant. In summary, we systematically revealed the key genes and pathways related to the progression of AD, gained insight into the crucial mechanisms of AD and identified some possible targets that could be used in the treatment of AD.
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8.
  • Bosley, J. R., et al. (author)
  • Informing Pharmacokinetic Models With Physiological Data: Oral Population Modeling of L-Serine in Humans
  • 2021
  • In: Frontiers in Pharmacology. - : Frontiers Media SA. - 1663-9812. ; 12
  • Journal article (peer-reviewed)abstract
    • To determine how to set optimal oral L-serine (serine) dose levels for a clinical trial, existing literature was surveyed. Data sufficient to set the dose was inadequate, and so an (n = 10) phase I-A calibration trial was performed, administering serine with and without other oral agents. We analyzed the trial and the literature data using pharmacokinetic (PK) modeling and statistical analysis. The therapeutic goal is to modulate specific serine-related metabolic pathways in the liver using the lowest possible dose which gives the desired effect since the upper bound was expected to be limited by toxicity. A standard PK approach, in which a common model structure was selected using a fit to data, yielded a model with a single central compartment corresponding to plasma, clearance from that compartment, and an endogenous source of serine. To improve conditioning, a parametric structure was changed to estimate ratios (bioavailability over volume, for example). Model fit quality was improved and the uncertainty in estimated parameters was reduced. Because of the particular interest in the fate of serine, the model was used to estimate whether serine is consumed in the gut, absorbed by the liver, or entered the blood in either a free state, or in a protein- or tissue-bound state that is not measured by our assay. The PK model structure was set up to represent relevant physiology, and this quantitative systems biology approach allowed a broader set of physiological data to be used to narrow parameter and prediction confidence intervals, and to better understand the biological meaning of the data. The model results allowed us to determine the optimal human dose for future trials, including a trial design component including IV and tracer studies. A key contribution is that we were able to use human physiological data from the literature to inform the PK model and to set reasonable bounds on parameters, and to improve model conditioning. Leveraging literature data produced a more predictive, useful model.
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9.
  • Ding, Mei, et al. (author)
  • Secretome screening reveals immunomodulating functions of IFNα-7, PAP and GDF-7 on regulatory T-cells
  • 2021
  • In: Scientific Reports. - : Springer Nature. - 2045-2322. ; , s. 16767-
  • Journal article (peer-reviewed)abstract
    • Regulatory T cells (Tregs) are the key cells regulating peripheral autoreactive T lymphocytes. Tregs exert their function by suppressing effector T cells. Tregs have been shown to play essential roles in the control of a variety of physiological and pathological immune responses. However, Tregs are unstable and can lose the expression of FOXP3 and suppressive functions as a consequence of outer stimuli. Available literature suggests that secreted proteins regulate Treg functional states, such as differentiation, proliferation and suppressive function. Identification of secreted proteins that affect Treg cell function are highly interesting for both therapeutic and diagnostic purposes in either hyperactive or immunosuppressed populations. Here, we report a phenotypic screening of a human secretome library in human Treg cells utilising a high throughput flow cytometry technology. Screening a library of 575 secreted proteins allowed us to identify proteins stabilising or destabilising the Treg phenotype as suggested by changes in expression of Treg marker proteins FOXP3 and/or CTLA4. Four proteins including GDF-7, IL-10, PAP and IFNα-7 were identified as positive regulators that increased FOXP3 and/or CTLA4 expression. PAP is a phosphatase. A catalytic-dead version of the protein did not induce an increase in FOXP3 expression. Ten interferon proteins were identified as negative regulators that reduced the expression of both CTLA4 and FOXP3, without affecting cell viability. A transcriptomics analysis supported the differential effect on Tregs of IFNα-7 versus other IFNα proteins, indicating differences in JAK/STAT signaling. A conformational model experiment confirmed a tenfold reduction in IFNAR-mediated ISG transcription for IFNα-7 compared to IFNα-10. This further strengthened the theory of a shift in downstream messaging upon external stimulation. As a summary, we have identified four positive regulators of FOXP3 and/or CTLA4 expression. Further exploration of these Treg modulators and their method of action has the potential to aid the discovery of novel therapies for both autoimmune and infectious diseases as well as for cancer.
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10.
  • Doran, S., et al. (author)
  • Multi-omics approaches for revealing the complexity of cardiovascular disease
  • 2021
  • In: Briefings in bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 22:5
  • Journal article (peer-reviewed)abstract
    • The development and progression of cardiovascular disease (CVD) can mainly be attributed to the narrowing of blood vessels caused by atherosclerosis and thrombosis, which induces organ damage that will result in end-organ dysfunction characterized by events such as myocardial infarction or stroke. It is also essential to consider other contributory factors to CVD, including cardiac remodelling caused by cardiomyopathies and co-morbidities with other diseases such as chronic kidney disease. Besides, there is a growing amount of evidence linking the gut microbiota to CVD through several metabolic pathways. Hence, it is of utmost importance to decipher the underlying molecular mechanisms associated with these disease states to elucidate the development and progression of CVD. A wide array of systems biology approaches incorporating multi-omics data have emerged as an invaluable tool in establishing alterations in specific cell types and identifying modifications in signalling events that promote disease development. Here, we review recent studies that apply multi-omics approaches to further understand the underlying causes of CVD and provide possible treatment strategies by identifying novel drug targets and biomarkers. We also discuss very recent advances in gut microbiota research with an emphasis on how diet and microbial composition can impact the development of CVD. Finally, we present various biological network analyses and other independent studies that have been employed for providing mechanistic explanation and developing treatment strategies for end-stage CVD, namely myocardial infarction and stroke.
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  • Result 1-10 of 40
Type of publication
journal article (39)
research review (1)
Type of content
peer-reviewed (39)
other academic/artistic (1)
Author/Editor
Uhlén, Mathias (40)
Mardinoglu, Adil (13)
Arif, Muhammad (13)
Borén, Jan, 1963 (11)
Nielsen, Jens B, 196 ... (10)
Zhang, Cheng (10)
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Altay, Özlem (9)
Li, Xiangyu (9)
Turkez, Hasan (8)
Mardinoglu, Adil, 19 ... (8)
Edfors, Fredrik (7)
Fagerberg, Linn (7)
Turkez, H. (6)
Zhong, Wen (5)
Zhang, C. (5)
Shoaie, Saeed (5)
Oksvold, Per (4)
Abdellah, Tebani (4)
Sivertsson, Åsa (4)
Nilsson, Peter (4)
Yang, Hong (4)
Kim, Woonghee (4)
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von Feilitzen, Kalle (3)
Schwenk, Jochen M. (3)
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Doran, S (3)
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University
Royal Institute of Technology (39)
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