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  1. Article ; Online: Author Correction: Proteogenomic links to human metabolic diseases.

    Koprulu, Mine / Carrasco-Zanini, Julia / Wheeler, Eleanor / Lockhart, Sam / Kerrison, Nicola D / Wareham, Nicholas J / Pietzner, Maik / Langenberg, Claudia

    Nature metabolism

    2023  Volume 5, Issue 4, Page(s) 710

    Language English
    Publishing date 2023-03-13
    Publishing country Germany
    Document type Published Erratum
    ISSN 2522-5812
    ISSN (online) 2522-5812
    DOI 10.1038/s42255-023-00785-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Multi-omic prediction of incident type 2 diabetes.

    Carrasco-Zanini, Julia / Pietzner, Maik / Wheeler, Eleanor / Kerrison, Nicola D / Langenberg, Claudia / Wareham, Nicholas J

    Diabetologia

    2023  Volume 67, Issue 1, Page(s) 102–112

    Abstract: Aims/hypothesis: The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, ... ...

    Abstract Aims/hypothesis: The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes.
    Methods: We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA
    Results: Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA
    Conclusions/interpretation: Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA
    MeSH term(s) Humans ; Diabetes Mellitus, Type 2/diagnosis ; Diabetes Mellitus, Type 2/epidemiology ; Diabetes Mellitus, Type 2/genetics ; Prediabetic State/complications ; Prospective Studies ; Cohort Studies ; Proteome ; Multiomics ; Risk Factors ; Biomarkers
    Chemical Substances Proteome ; Biomarkers
    Language English
    Publishing date 2023-10-27
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 1694-9
    ISSN 1432-0428 ; 0012-186X
    ISSN (online) 1432-0428
    ISSN 0012-186X
    DOI 10.1007/s00125-023-06027-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 279: Show issues Location:
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  3. Book ; Online ; Thesis: Comprehensive metabolic characterization of thyroid hormone action on human metabolism in population-based and experimental studies

    Pietzner, Maik [Verfasser]

    2017  

    Author's details Maik Pietzner
    Keywords Biowissenschaften, Biologie ; Life Science, Biology
    Subject code sg570
    Language English
    Publisher Universitätsbibliothek Greifswald
    Publishing place Greifswald
    Document type Book ; Online ; Thesis
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  4. Article ; Online: Proteogenomic links to human metabolic diseases.

    Koprulu, Mine / Carrasco-Zanini, Julia / Wheeler, Eleanor / Lockhart, Sam / Kerrison, Nicola D / Wareham, Nicholas J / Pietzner, Maik / Langenberg, Claudia

    Nature metabolism

    2023  Volume 5, Issue 3, Page(s) 516–528

    Abstract: Studying the plasma proteome as the intermediate layer between the genome and the phenome has the potential to identify new disease processes. Here, we conducted a cis-focused proteogenomic analysis of 2,923 plasma proteins measured in 1,180 individuals ... ...

    Abstract Studying the plasma proteome as the intermediate layer between the genome and the phenome has the potential to identify new disease processes. Here, we conducted a cis-focused proteogenomic analysis of 2,923 plasma proteins measured in 1,180 individuals using antibody-based assays. We (1) identify 256 unreported protein quantitative trait loci (pQTL); (2) demonstrate shared genetic regulation of 224 cis-pQTLs with 575 specific health outcomes, revealing examples for notable metabolic diseases (such as gastrin-releasing peptide as a potential therapeutic target for type 2 diabetes); (3) improve causal gene assignment at 40% (n = 192) of overlapping risk loci; and (4) observe convergence of phenotypic consequences of cis-pQTLs and rare loss-of-function gene burden for 12 proteins, such as TIMD4 for lipoprotein metabolism. Our findings demonstrate the value of integrating complementary proteomic technologies with genomics even at moderate scale to identify new mediators of metabolic diseases with the potential for therapeutic interventions.
    MeSH term(s) Humans ; Proteogenomics ; Proteomics ; Diabetes Mellitus, Type 2/genetics ; Quantitative Trait Loci ; Blood Proteins/genetics
    Chemical Substances Blood Proteins
    Language English
    Publishing date 2023-02-23
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2522-5812
    ISSN (online) 2522-5812
    DOI 10.1038/s42255-023-00753-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Integrating Genetics and the Plasma Proteome to Predict the Risk of Type 2 Diabetes.

    Zanini, Julia Carrasco / Pietzner, Maik / Langenberg, Claudia

    Current diabetes reports

    2020  Volume 20, Issue 11, Page(s) 60

    Abstract: Purpose of the review: Proteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable ... ...

    Abstract Purpose of the review: Proteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable profiling of the plasma proteome with the potential to improve prediction and mechanistic understanding of type 2 diabetes (T2D).
    Recent findings: Technological and analytical advancements have enabled identification of novel protein biomarkers and signatures that help to address challenges of existing approaches to predict and screen for T2D. Genetic studies have so far revealed putative causal roles for only few of the proteins that have been linked to T2D, but ongoing large-scale genetic studies of the plasma proteome will help to address this and increase our understanding of aetiological pathways and mechanisms leading to diabetes. Studies of the human plasma proteome have started to elucidate its potential for T2D prediction and biomarker discovery. Future studies integrating genomic and proteomic data will provide opportunities to prioritise drug targets and identify pathways linking genetic predisposition to T2D development.
    MeSH term(s) Diabetes Mellitus, Type 2/genetics ; Humans ; Pharmaceutical Preparations ; Plasma ; Proteome/genetics ; Proteomics
    Chemical Substances Pharmaceutical Preparations ; Proteome
    Keywords covid19
    Language English
    Publishing date 2020-10-08
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 2065167-3
    ISSN 1539-0829 ; 1534-4827
    ISSN (online) 1539-0829
    ISSN 1534-4827
    DOI 10.1007/s11892-020-01340-w
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5628: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
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  6. Thesis ; Online: Versuchsumfangsplanung zur Bestimmung der LD50

    Pietzner, Maik

    2013  

    Keywords ddc:510
    Language German
    Publishing country de
    Document type Thesis ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Thesis ; Online: Versuchsumfangsplanung zur Bestimmung der LD50

    Pietzner, Maik

    2013  

    Keywords Text ; ddc:510
    Language German
    Publisher o. Verl.
    Publishing country de
    Document type Thesis ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Optimizing Linear Ion-Trap Data-Independent Acquisition toward Single-Cell Proteomics.

    Phlairaharn, Teeradon / Ye, Zilu / Krismer, Elena / Pedersen, Anna-Kathrine / Pietzner, Maik / Olsen, Jesper V / Schoof, Erwin M / Searle, Brian C

    Analytical chemistry

    2023  Volume 95, Issue 26, Page(s) 9881–9891

    Abstract: A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass ... ...

    Abstract A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.
    MeSH term(s) Proteomics/methods ; Tandem Mass Spectrometry/methods ; Peptides/chemistry
    Chemical Substances Peptides
    Language English
    Publishing date 2023-06-20
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.3c00842
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 4033: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  9. Article: Optimizing linear ion trap data independent acquisition towards single cell proteomics.

    Phlairaharn, Teeradon / Ye, Zilu / Krismer, Elena / Pedersen, Anna-Kathrine / Pietzner, Maik / Olsen, Jesper V / Schoof, Erwin M / Searle, Brian C

    bioRxiv : the preprint server for biology

    2023  

    Abstract: A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass ... ...

    Abstract A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.
    Language English
    Publishing date 2023-02-21
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.02.21.529444
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Systemic proteome adaptions to 7-day complete caloric restriction in humans.

    Pietzner, Maik / Uluvar, Burulça / Kolnes, Kristoffer J / Jeppesen, Per B / Frivold, S Victoria / Skattebo, Øyvind / Johansen, Egil I / Skålhegg, Bjørn S / Wojtaszewski, Jørgen F P / Kolnes, Anders J / Yeo, Giles S H / O'Rahilly, Stephen / Jensen, Jørgen / Langenberg, Claudia

    Nature metabolism

    2024  

    Abstract: Surviving long periods without food has shaped human evolution. In ancient and modern societies, prolonged fasting was/is practiced by billions of people globally for religious purposes, used to treat diseases such as epilepsy, and recently gained ... ...

    Abstract Surviving long periods without food has shaped human evolution. In ancient and modern societies, prolonged fasting was/is practiced by billions of people globally for religious purposes, used to treat diseases such as epilepsy, and recently gained popularity as weight loss intervention, but we still have a very limited understanding of the systemic adaptions in humans to extreme caloric restriction of different durations. Here we show that a 7-day water-only fast leads to an average weight loss of 5.7 kg (±0.8 kg) among 12 volunteers (5 women, 7 men). We demonstrate nine distinct proteomic response profiles, with systemic changes evident only after 3 days of complete calorie restriction based on in-depth characterization of the temporal trajectories of ~3,000 plasma proteins measured before, daily during, and after fasting. The multi-organ response to complete caloric restriction shows distinct effects of fasting duration and weight loss and is remarkably conserved across volunteers with >1,000 significantly responding proteins. The fasting signature is strongly enriched for extracellular matrix proteins from various body sites, demonstrating profound non-metabolic adaptions, including extreme changes in the brain-specific extracellular matrix protein tenascin-R. Using proteogenomic approaches, we estimate the health consequences for 212 proteins that change during fasting across ~500 outcomes and identified putative beneficial (SWAP70 and rheumatoid arthritis or HYOU1 and heart disease), as well as adverse effects. Our results advance our understanding of prolonged fasting in humans beyond a merely energy-centric adaptions towards a systemic response that can inform targeted therapeutic modulation.
    Language English
    Publishing date 2024-03-01
    Publishing country Germany
    Document type Journal Article
    ISSN 2522-5812
    ISSN (online) 2522-5812
    DOI 10.1038/s42255-024-01008-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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