| 1. |
- Demichev, Vadim, et al.
(author)
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A proteomic survival predictor for COVID-19 patients in intensive care
- 2022
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In: PLOS Digital Health. - : Public Library of Science (PLoS). - 2767-3170. ; 1:1 January
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Journal article (peer-reviewed)abstract
- Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.
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| 2. |
- Demichev, Vadim, et al.
(author)
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A time-resolved proteomic and prognostic map of COVID-19
- 2021
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In: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 12:8, s. 780-794.e7
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Journal article (peer-reviewed)abstract
- COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
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| 3. |
- Donis, Daphne, et al.
(author)
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Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer
- 2021
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In: Limnology and Oceanography. - : John Wiley & Sons. - 0024-3590 .- 1939-5590. ; 66:12, s. 4314-4333
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Journal article (peer-reviewed)abstract
- To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L-1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4 degrees C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature.
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| 4. |
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| 5. |
- Keller, Maria, et al.
(author)
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THOC5 : A novel gene involved in HDL-cholesterol metabolism
- 2013
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In: Journal of Lipid Research. - 0022-2275. ; 54:11, s. 3170-3176
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Journal article (peer-reviewed)abstract
- Although numerous genes are known to regulate serum lipid traits, identified variants explain only a small proportion of the expected heritability. We intended to identify further genetic variants associated with lipid phenotypes in a self-contained population of Sorbs in Germany. We performed a genome-wide association study (GWAS) on LDL-cholesterol, HDL-cholesterol (HDL-C), and triglyceride (TG) levels in 839 Sorbs. All single-nucleotide polymorphisms with a P value <0.01 were subjected to a meta-analysis, including an independent Swedish cohort (Diabetes Genetics Initiative; n = ∼ 3,100). Novel association signals with the strongest effects were subjected to replication studies in an additional German cohort (Berlin, n = 2,031). In the initial GWAS in the Sorbs, we identified 14 loci associated with lipid phenotypes reaching P values <10 -5 and confirmed significant effects for 18 previously reported loci. The combined meta-analysis of the three study cohorts (n(HDL) = 6041; n (LDL) = 5,995; n(TG) = 6,087) revealed a novel association for a variant in THOC5 (rs8135828) with serum HDL-C levels (P = 1.78 × 10-7; Z -score = -5.221). Consistently, the variant was also associated with circulating APOA1 levels in Sorbs. The small interfering RNA-mediated mRNA silencing of THOC5 in HepG2 cells resulted in lower mRNA levels of APOA1, SCARB1, and ABCG8 (all P < 0.05). We propose THOC5 to be a novel gene involved in the regulation of serum HDL-C levels.
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| 6. |
- Mantzouki, Evanthia, et al.
(author)
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Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins
- 2018
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In: Toxins. - : MDPI. - 2072-6651. ; 10:4
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Journal article (peer-reviewed)abstract
- Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
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| 7. |
- Messner, Christoph B., et al.
(author)
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Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection
- 2020
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In: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 11:1, s. 11-24.E4
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Journal article (peer-reviewed)abstract
- The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.
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| 8. |
- Toenjes, Anke, et al.
(author)
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Genetic variation in GPR133 is associated with height: genome wide association study in the self-contained population of Sorbs
- 2009
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 18:23, s. 4662-4668
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Journal article (peer-reviewed)abstract
- Recently, associations of several common genetic variants with height have been reported in different populations. We attempted to identify further variants associated with adult height in a self-contained population (the Sorbs in Eastern Germany) as discovery set. We performed a genome wide association study (GWAS) (similar to 390 000 genetic polymorphisms, Affymetrix gene arrays) on adult height in 929 Sorbian individuals. Subsequently, the best SNPs (P < 0.001) were taken forward to a meta-analysis together with two independent cohorts [Diabetes Genetics Initiative, British 1958 Birth Cohort, (58BC, publicly available)]. Furthermore, we genotyped our best signal for replication in two additional German cohorts (Leipzig, n = 1044 and Berlin, n = 1728). In the primary Sorbian GWAS, we identified 5 loci with a P-value < 10(-5) and 455 SNPs with P-value < 0.001. In the meta-analysis on those 455 SNPs, only two variants in GPR133 (rs1569019 and rs1976930; in LD with each other) retained a P-value at or below 10(-6) and were associated with height in the three cohorts individually. Upon replication, the SNP rs1569019 showed significant effects on height in the Leipzig cohort (P = 0.004, beta = 1.166) and in 577 men of the Berlin cohort (P = 0.049, beta = 1.127) though not in women. The combined analysis of all five cohorts (n = 6,687) resulted in a P-value of 4.7 x 10(-8) (beta = 0.949). In conclusion, our GWAS suggests novel loci influencing height. In view of the robust replication in five different cohorts, we propose GPR133 to be a novel gene associated with adult height.
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| 9. |
- Åsman, Barbro, et al.
(author)
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The ATLAS Level-1 Calorimeter Trigger : PreProcessor implementation and performance
- 2012
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In: Journal of Instrumentation. - 1748-0221. ; 7
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Journal article (peer-reviewed)abstract
- The PreProcessor system of the ATLAS Level-1 Calorimeter Trigger (L1Calo) receives about 7200 analogue signals from the electromagnetic and hadronic components of the calorimetric detector system. Lateral division results in cells which are pre-summed to so-called Trigger Towers of size 0.1 x 0.1 along azimuth (phi) and pseudorapidity (eta). The received calorimeter signals represent deposits of transverse energy. The system consists of 124 individual PreProcessor modules that digitise the input signals for each LHC collision, and provide energy and timing information to the digital processors of the L1Calo system, which identify physics objects forming much of the basis for the full ATLAS first level trigger decision. This paper describes the architecture of the PreProcessor, its hardware realisation, functionality, and performance.
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| 10. |
- Aad, G, et al.
(author)
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- 2015
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swepub:Mat__t
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