Evidence map›Paper›PMID 26047609›Full record

ArticleJournal of translational medicine2015

Combined genetic effects of EGLN1 and VWF modulate thrombotic outcome in hypoxia revealed by Ayurgenomics approach.

Shilpi Aggarwal, Atish Gheware, Anurag Agrawal, Saurabh Ghosh, Bhavana Prasher, Mitali Mukerji, Indian Genome Variation Consortium

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. A scoping review of clinicalFrontiers in medicine · 2026
    Pooled it
  2. Trial
  3. Screening and analysis of plasma differential lncRNA/mRNA in early pregnancy of preeclampsia.Malawi medical journal : the journal of Medical Association of Malawi · 2025
    Article
  4. Review
  5. Article
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  8. Article
  9. Article
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  12. Ayurgenomics and Modern Medicine.Medicina (Kaunas, Lithuania) · 2020
    Review
  13. Effect ofBioMed research international · 2020
    Article
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  17. Observational
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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 2 institutions in 1 country.

Shilpi AggarwalGenomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, India. shilpi.aggarwal@igib.in.
Atish GhewareCSIR's Ayurgenomics Unit-TRISUTRA (Translational Research and Innovative Science ThRough Ayurgenomics), CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110 020, India. atish.gheware@igib.in.
Anurag AgrawalGenomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, India. a.agrawal@igib.res.in.
Saurabh GhoshIndian Statistical Institute, Kolkata, India. saurabh@isical.ac.in.
Bhavana PrasherCSIR's Ayurgenomics Unit-TRISUTRA (Translational Research and Innovative Science ThRough Ayurgenomics), CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, 110 020, India. bhavana.p@igib.res.in.
Mitali MukerjiGenomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi, India. mitali@igib.res.in.
Indian Genome Variation Consortium
Institute of Genomics and Integrative Biology · INIndian Statistical Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExtreme constitution "Prakriti" types of Ayurveda exhibit systemic physiological attributes. Our earlier genetic study has revealed differences in EGLN1, key modulator of hypoxia axis between Prakriti types. This was associated with differences in high altitude adaptation and susceptibility to high altitude pulmonary edema (HAPE). In this study we investigate other molecular differences that contribute to systemic attributes of Prakriti that would be relevant in predictive marker discovery.

methodsGenotyping of 96 individuals of the earlier cohort was carried out in a panel of 2,800 common genic SNPs represented in Indian Genomic Variation Consortium (IGVC) panel from 24 diverse populations. Frequency distribution patterns of Prakriti differentiating variations (FDR correction P < 0.05) was studied in IGVC and 55 global populations (HGDP-CEPH) panels. Genotypic interactions between VWF, identified from the present analysis, and EGLN1 was analyzed using multinomial logistic regression in Prakriti and Indian populations from contrasting altitudes. Spearman's Rank correlation was used to study this genotypic interaction with respect to altitude in HGDP-CEPH panel. Validation of functional link between EGLN1 and VWF was carried out in a mouse model using chemical inhibition and siRNA studies.

resultSignificant differences in allele frequencies were observed in seven genes (SPTA1, VWF, OLR1, UCP2, OR6K3, LEPR, and OR10Z1) after FDR correction (P < 0.05). A non synonymous variation (C/T, rs1063856) associated with thrombosis/bleeding susceptibility respectively, differed significantly between Kapha (C-allele) and Pitta (T-allele) constitution types. A combination of derived EGLN1 allele (HAPE associated) and ancestral VWF allele (thrombosis associated) was significantly high in Kapha group compared to Pitta (p < 10(-5)). The combination of risk-associated Kapha alleles was nearly absent in natives of high altitude. Inhibition of EGLN1 using (DHB) and an EGLN1 specific siRNA in a mouse model lead to a marked increase in vWF levels as well as pro-thrombotic phenotype viz. reduced bleeding time and enhanced platelet count and activation.

conclusionWe demonstrate for the first time a genetic link between EGLN1 and VWF in a constitution specific manner which could modulate thrombosis/bleeding susceptibility and outcomes of hypoxia. Integration of Prakriti in population stratification may help assemble common variations in key physiological axes that confers differences in disease occurrence and patho-phenotypic outcomes.

Indexed as

Genetic Predisposition to DiseaseGenomicsMedicine, AyurvedicAdaptation, PhysiologicalAllelesAltitudeAnimalsDisease Models, AnimalGene FrequencyGene Knockdown TechniquesHomozygoteHumansHypoxiaHypoxia-Inducible Factor-Proline DioxygenasesIndiaMaleEGLN1 protein, humanEgln1 protein, mouseHypoxia-Inducible Factor-Proline Dioxygenasesvon Willebrand Factor

Identifiers

PMID26047609
PMCPMC4457985
OpenAlexW1590865012

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Registered trials

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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 OpenQuestion graph.