Evidence map›Paper›PMID 29051702›Full record

ArticleBioinformatics and biology insights2017

Finding the Sources of Missing Heritability within Rare Variants Through Simulation.

Baishali Bandyopadhyay, Veda Chanda, Yupeng Wang

Abstract read
In one paragraph

Article in Bioinformatics and biology insights, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Association between Interleukin-6 Gene Polymorphism (BioMed research international · 2024
    Article
  3. Article
  4. Review
  5. Genetic and epigenetic analyses of panic disorder in the post-GWAS era.Journal of neural transmission (Vienna, Austria : 1996) · 2020
    Review
  6. Article
  7. Gene-gene interaction: the curse of dimensionality.Annals of translational medicine · 2019
    Review
  8. Analyses of epithelial NaThe Journal of biological chemistry · 2019
    Article
  9. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Baishali BandyopadhyayBDX Research & Consulting LLC, Fairfax, VA, USA.
Veda ChandaBDX Research & Consulting LLC, Fairfax, VA, USA.
Yupeng WangBDX Research & Consulting LLC, Fairfax, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thousands of genome-wide association studies (GWAS) have been conducted to identify the genetic variants associated with complex disorders. However, only a small proportion of phenotypic variances can be explained by the reported variants. Moreover, many GWAS failed to identify genetic variants associated with disorders displaying hereditary features. The "missing heritability" problem can be partly explained by rare variants. We simulated a causality scenario that gestational ages, a quantitative trait that can distinguish preterm (<37 weeks) and term births, were significantly correlated with the rare variant aggregations at 1000 single-nucleotide polymorphism loci. These 1000 simulated causal rare variants were embedded into randomly selected subsets of 9642 promoter regions from the 1000 Genomes Project genotypic data according to different proportions of causal rare variants within the embedded promoters. Through analysis of the correlations between rare variant aggregations and gestational ages, we found that the embedded promoters as a whole showed weaker genetic association when the proportion of causal rare variants decreased, and no individual embedded promoters showed genetic association when the proportion of causal rare variants was smaller than 0.4. Our analyses indicate that association signals can be greatly diluted when causal rare variants are dispersedly and sparsely distributed in the genome, accounting for an important source of missing heritability.

Indexed as

causal variantMissing heritabilitypreterm birthrare variantsimulation

Identifiers

PMID29051702
PMCPMC5638154

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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.