Cited by 62

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Genetic Factors of the Disease Course after Sepsis: A Genome-Wide Study for 28Day Mortality

Scherag, André, Schöneweck, Franziska, Kesselmeier, Miriam, Taudien, Stefan, Platzer, Matthias, Felder, Marius, Sponholz, Christoph, Rautanen, Anna, Hill, Adrian V.S., Hinds, Charles J., Hossain, Hamid, Suttorp, Norbert, Kurzai, Oliver, Slevogt, Hortense, Giamarellos-Bourboulis, Evangelos J., Armaganidis, Apostolos, Trips, Evelyn, Scholz, Markus, Brunkhorst, Frank M.·2016·EBioMedicine

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.ebiom.2016.08.043

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Discovery GWAS: a) Manhattan plot for the analysis of 28 day mortality in patients with treated sepsis (additive genetic model). The blue line represents the significance level for a suggestive association signal (i.e. p ≤ 1 × 10− 5) and the red line is the level for a genome-wide association signal (i.e. p ≤ 5 × 10− 8). b) Quantile–quantile (Q–Q) plot of all the GWAS p-values (λ = 1.0079) from the analysis of 28 day mortality in patients with treated sepsis (additive genetic model).
Fig. 1 Discovery GWAS: a) Manhattan plot for the analysis of 28 day mortality in patients with treated sepsis (additive genetic model). The blue line represents the significance level for a suggestive association signal (i.e. p ≤ 1 × 10− 5) and the red line is the level for a genome-wide association signal (i.e. p ≤ 5 × 10− 8). b) Quantile–quantile (Q–Q) plot of all the GWAS p-values (λ = 1.0079) from the analysis of 28 day mortality in patients with treated sepsis (additive genetic model).CC BY-NC-ND · PubMed Central
Fig. 2 Regional association plot for a) the chromosome 9q21.2 locus (centered around the lead SNP rs117983287) and b) the chromosome 16 locus (centered around the lead SNP rs2641697) in the analysis of 28 day mortality in patients with treated severe sepsis/septic shock (additive genetic model). Colors indicate the correlation (r2 in 1000 Genomes data for Utah residents with northern or western European ancestry (CEU); phase 1, version 3) with the alleles of rs117983287/rs2641697.
Fig. 2 Regional association plot for a) the chromosome 9q21.2 locus (centered around the lead SNP rs117983287) and b) the chromosome 16 locus (centered around the lead SNP rs2641697) in the analysis of 28 day mortality in patients with treated severe sepsis/septic shock (additive genetic model). Colors indicate the correlation (r2 in 1000 Genomes data for Utah residents with northern or western European ancestry (CEU); phase 1, version 3) with the alleles of rs117983287/rs2641697.CC BY-NC-ND · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Research works printed but not linked: 35

  1. Almansa, 2015, Transcriptomic correlates of organ failure extent in sepsis, The Journal of Infection, 70, 445, 10.1016/j.jinf.2014.12.010 · DOI
  2. An, 2012, Frameshift mutations of vacuolar protein sorting genes in gastric and colorectal cancers with microsatellite instability, Hum. Pathol., 43, 40, 10.1016/j.humpath.2010.03.015 · DOI
  3. Angus, 2011, The search for effective therapy for sepsis: back to the drawing board?, JAMA, 306, 2614, 10.1001/jama.2011.1853 · DOI
  4. Angus, 2001, Epidemiology of sepsis: an update, Crit. Care Med., 29, 109, 10.1097/00003246-200107001-00035 · DOI · Paper page
  5. Brunkhorst, 2012, Effect of empirical treatment with moxifloxacin and meropenem vs meropenem on sepsis-related organ dysfunction in patients with severe sepsis: a randomized trial, JAMA, 307, 2390, 10.1001/jama.2012.5833 · DOI · Paper page
  6. Camprubí-Rimblas, 2015, An overview of proteomics on sepsis, Journal of Physical Chemistry & Biophysics, 5, 183, 10.4172/2161-0398.1000183 · DOI
  7. Clark, 2006, A systematic review of the quality of genetic association studies in human sepsis, Intensive Care Med., 32, 1706, 10.1007/s00134-006-0327-y · DOI
  8. Cohen, 2015, Sepsis: a roadmap for future research, Lancet Infect. Dis., 15, 581, 10.1016/S1473-3099(15)70112-X · DOI
  9. Davenport, 2016, Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study, The Lancet Respiratory Medicine., 4, 259, 10.1016/S2213-2600(16)00046-1 · DOI
  10. DePristo, 2011, A framework for variation discovery and genotyping using next-generation DNA sequencing data, Nat. Genet., 43, 491, 10.1038/ng.806 · DOI
  11. Engel, 2007, Epidemiology of sepsis in Germany: results from a national prospective multicenter study, Intensive Care Med., 33, 606, 10.1007/s00134-006-0517-7 · DOI
  12. Fanos, 2014, Metabolomics in the diagnosis of sepsis, Ital. J. Pediatr., 40, A11, 10.1186/1824-7288-40-S1-A11 · DOI
  13. Geisel, 2016, Update of the effect estimates for common variants associated with carotid intima media thickness within four independent samples: the Bonn IMT Family Study, the Heinz Nixdorf Recall Study, the SAPHIR Study and the Bruneck Study, Atherosclerosis, 249, 83, 10.1016/j.atherosclerosis.2016.03.042 · DOI
  14. GTEx Consortium, 2015, Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans, Science, 348, 648, 10.1126/science.1262110 · DOI · Paper page
  15. Kircher, 2014, A general framework for estimating the relative pathogenicity of human genetic variants, Nat. Genet., 46, 310, 10.1038/ng.2892 · DOI · Paper page
  16. Köttgen, 2010, New loci associated with kidney function and chronic kidney disease, Nat. Genet., 42, 376, 10.1038/ng.568 · DOI
  17. Lee, 2012, Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies, Am. J. Hum. Genet., 91, 224, 10.1016/j.ajhg.2012.06.007 · DOI
  18. Levy, 2003, 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference, Intensive Care Med., 29, 530, 10.1007/s00134-003-1662-x · DOI
  19. Man, 2013, Beyond single-marker analyses: mining whole genome scans for insights into treatment responses in severe sepsis, The Pharmacogenomics Journal, 13, 218, 10.1038/tpj.2012.1 · DOI
  20. Martin, 2003, The epidemiology of sepsis in the United States from 1979 through 2000, N. Engl. J. Med., 384, 1546, 10.1056/NEJMoa022139 · DOI · Paper page
  21. Mijiti, 2015, Preliminary evidence of an interaction between the CRISPLD2 gene and non-syndromic cleft lip with or without cleft palate (nsCL/P) in Xinjiang Uyghur population, China, Int. J. Pediatr. Otorhinolaryngol., 79, 94, 10.1016/j.ijporl.2014.10.043 · DOI
  22. Muñoz-Braceras, 2015, TipC and the chorea-acanthocytosis protein VPS13A regulate autophagy in Dictyostelium and human HeLa cells, Autophagy, 11, 918, 10.1080/15548627.2015.1034413 · DOI
  23. Petersen, 2010, Genetic influences on incidence and case-fatality of infectious disease', PLoS ONE, 5, e10603, 10.1371/journal.pone.0010603 · DOI
  24. Rautanen, 2015, Genome-wide association study of survival from sepsis due to pneumonia: an observational cohort study, The Lancet Respiratory Medicine, 3, 53, 10.1016/S2213-2600(14)70290-5 · DOI
  25. Rosenbloom, 2013, ENCODE data in the UCSC genome browser: year 5 update, Nucleic Acids Res., 41, D56
  26. Schneider, 2014, Autophagy and human disease: emerging themes, Curr. Opin. Genet. Dev., 26, 16, 10.1016/j.gde.2014.04.003 · DOI
  27. Schöneweck, 2015, Common genomic variation in the FER gene: useful to stratify patients with sepsis due to pneumonia?, Intensive Care Med., 41, 1379, 10.1007/s00134-015-3829-7 · DOI
  28. Seymour, 2016, Assessment of clinical criteria for sepsis: for the third international consensus definitions for sepsis and septic shock (sepsis-3), JAMA, 315, 762, 10.1001/jama.2016.0288 · DOI · Paper page
  29. Shimo, 2011, Comprehensive analysis of the genes responsible for neuroacanthocytosis in mood disorder and schizophrenia, Neurosci. Res., 69, 196, 10.1016/j.neures.2010.12.001 · DOI
  30. Singer, 2016, The third international consensus definitions for sepsis and septic shock (sepsis-3), JAMA, 315, 801, 10.1001/jama.2016.0287 · DOI · Paper page
  31. Sørensen, 1988, Genetic and environmental influences on premature death in adult adoptees, N. Engl. J. Med., 318, 727, 10.1056/NEJM198803243181202 · DOI
  32. Sun, 2014, How to use a subgroup analysis: users' guide to the medical literature, JAMA, 311, 405, 10.1001/jama.2013.285063 · DOI · Paper page
  33. Taudien, 2016, Genetic factors of the disease course after sepsis: rare deleterious variants are predictive, RBioMedicine, 12, 239
  34. Wang, 2013, CRISPLD2 is expressed at low levels during septic shock and is associated with procalcitonin, PLoS ONE, vol. 8, e65743, 10.1371/journal.pone.0065743 · DOI
  35. Welter, 2014, The NHGRI GWAS catalog, a curated resource of SNP-trait associations, Nucleic Acids Res., 42, D1001, 10.1093/nar/gkt1229 · DOI · Paper page

Cited by

Sorted by citations

See all 62

Metadata

Authors
Scherag, A., Schöneweck, F., Kesselmeier, M., Taudien, S., Platzer, M., Felder, M., Sponholz, C., Rautanen, A., Hill, A. V. S., Hinds, C. J., Hossain, H., Suttorp, N., Kurzai, O., Slevogt, H., Giamarellos-Bourboulis, E. J., Armaganidis, A., Trips, E., Scholz, M., & Brunkhorst, F. M.
Venue
EBioMedicine
Publisher
Elsevier BV
Published
2016-10
Volume
12
Pages
239-246
ISSN
2352-3964
Cited by
62
References
4
Language
en
Funders
  • Bayer HealthCare
  • European Commission
  • Thüringer Ministerium für Bildung, Wissenschaft und Kultur (PE 108-2)
  • Bundesministerium für Bildung und Forschung (01KI07113, 01KI07111, 01KI07110, 01KI1010D, 01KI07114, 01KI1010I, 01 KI 0106, 01 EO 1502, 01 EO 1002)
  • Center for Sepsis Control and Care
  • Novo Nordisk
  • National and Kapodistrian University of Athens

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Genetic Factors of the Disease Course after Sepsis: A Genome-Wide Study for 28Day Mortality. https://app.cochat.ai/papers/10.1016/j.ebiom.2016.08.043
The paper
Scherag, A., Schöneweck, F., Kesselmeier, M., Taudien, S., Platzer, M., Felder, M., Sponholz, C., Rautanen, A., Hill, A. V. S., Hinds, C. J., Hossain, H., Suttorp, N., Kurzai, O., Slevogt, H., Giamarellos-Bourboulis, E. J., Armaganidis, A., Trips, E., Scholz, M., & Brunkhorst, F. M. (2016). Genetic Factors of the Disease Course after Sepsis: A Genome-Wide Study for 28Day Mortality. EBioMedicine. https://doi.org/10.1016/j.ebiom.2016.08.043