Evidence map›Paper›PMID 25505972›Full record

ArticleClinical & translational immunology2014

Grouping of large populations into few CTL immune 'response-types' from influenza H1N1 genome analysis.

Sumanta Mukherjee, Nagasuma Chandra

Abstract read
In one paragraph

Article in Clinical & translational immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Sumanta MukherjeeIISc Mathematics Initiative, Indian Institute of Science , Bangalore, India.
Nagasuma ChandraIISc Mathematics Initiative, Indian Institute of Science , Bangalore, India ; Department of Biochemistry, Indian Institute of Science , Bangalore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite extensive work on influenza, a number of questions still remain open about why individuals are differently susceptible to the disease and why only some strains lead to epidemics. Here we study the effect of human leukocyte antigen (HLA) genotype heterogeneity on possible cytotoxic T-lymphocyte (CTL) response to 186 influenza H1N1 genomes. To enable such analysis, we reconstruct HLA genotypes in different populations using a probabilistic method. We find that epidemic strains in general correlate with poor CTL response in populations. Our analysis shows that large populations can be classified into a small number of groups called response-types, specific to a given viral strain. Individuals of a response-type are expected to exhibit similar CTL responses. Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity. Overall, our analysis presents a conceptual advance towards understanding how genetic heterogeneity influences disease susceptibility in individuals and in populations. We also obtain lists of top-ranking epitopes and proteins, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which provide ready short-lists for rational vaccine design. Our method is fairly generic and has the potential to be applied for studying other viruses.

Identifiers

PMID25505972
PMCPMC4232073

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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.