Evidence map›Paper›PMID 32059761›Full record

ArticleAmerican journal of human genetics2020

Influence of Genetic Ancestry on Human Serum Proteome.

Jennifer Sjaarda, Hertzel C Gerstein, Zoltan Kutalik, Pedrum Mohammadi-Shemirani, Marie Pigeyre, Sibylle Hess, Guillaume Paré

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.4field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 40 citations in OpenAlex.

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  10. Assessing polyomic risk to predict Alzheimer's disease using a machine learning model.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 3 countries.

Jennifer SjaardaPopulation Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON L8S 4K1, Canada; Institute of Social and Preventative Medicine, Lausanne University Hospital, Lausanne, 1010, Switzerland; Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
Hertzel C GersteinPopulation Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton ON L8S 4K1, Canada.
Zoltan KutalikInstitute of Social and Preventative Medicine, Lausanne University Hospital, Lausanne, 1010, Switzerland; Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
Pedrum Mohammadi-ShemiraniPopulation Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON L8S 4K1, Canada.
Marie PigeyrePopulation Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON L8S 4K1, Canada.
Sibylle HessSanofi Aventis Deutschland GmbH, Research and Development Division, Translational Medicine and Early Development, Biomarkers and Clinical Bioanalyses, Frankfurt 65926, Germany.
Guillaume ParéPopulation Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON L8S 4K1, Canada; Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton ON L8S 4K1, Canada; Department of Biochemistry, McMaster University, 1280 Main Street West, Hamilton ON L8S 4K1, Canada. Electronic address: pareg@mcmaster.ca.
Population Health Research Institute · CASIB Swiss Institute of Bioinformatics · CHSanofi (Germany) · DE

Funding

CIHR 125794
6 · The paper itself

Abstract

Disease risk varies significantly between ethnic groups, however, the clinical significance and implications of these observations are poorly understood. Investigating ethnic differences within the human proteome may shed light on the impact of ancestry on disease risk. We used admixture mapping to explore the impact of genetic ancestry on 237 cardiometabolic biomarkers in 2,216 Latin Americans within the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study. We developed a variance component model in order to determine the proportion of variance explained by inter-ancestry differences, and we applied it to the biomarker panel. Multivariable linear regression was used to identify and localize genetic loci affecting biomarker variability between ethnicities. Variance component analysis revealed that 5% of biomarkers were significantly impacted by genetic admixture (p < 0.05/237), including C-peptide, apolipoprotein-E, and intercellular adhesion molecule 1. We also identified 46 regional associations across 40 different biomarkers (p < 1.13 × 10

Indexed as

ProteomeBiomarkersBlood ProteinsHumansPopulation GroupsBiomarkersBlood ProteinsProteomeadmixtureancestrybiomarkerproteome

Identifiers

PMID32059761
PMCPMC7058828
OpenAlexW3006646039

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.