Evidence map›Paper›PMID 29370075›Full record

ReviewGenes2018

Another Round of "Clue" to Uncover the Mystery of Complex Traits.

Shefali Setia Verma, Marylyn D Ritchie

Abstract readReview
In one paragraph

Review in Genes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Review
  5. Article
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.

Shefali Setia VermaThe Huck Institute of Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA. shefali.setiaverma@pennmedicine.upenn.edu.
Marylyn D RitchieThe Huck Institute of Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA. marylyn@upenn.edu.

Funding

Pharmacogenomics of HIV TherapyR01AI077505 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HAAS, DAVID W · 2008 to 2025
$12.3M
Biomedical Computing and Informatics Strategies for Infectious Disease ResearchR01AI116794 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H. · 2016 to 2020
$2.9M
NIAID NIH HHS R01 AI077505NIAID NIH HHS R01 AI116794
6 · The paper itself

Abstract

A plethora of genetic association analyses have identified several genetic risk loci. Technological and statistical advancements have now led to the identification of not only common genetic variants, but also low-frequency variants, structural variants, and environmental factors, as well as multi-omics variations that affect the phenotypic variance of complex traits in a population, thus referred to as complex trait architecture. The concept of heritability, or the proportion of phenotypic variance due to genetic inheritance, has been studied for several decades, but its application is mainly in addressing the narrow sense heritability (or additive genetic component) from Genome-Wide Association Studies (GWAS). In this commentary, we reflect on our perspective on the complexity of understanding heritability for human traits in comparison to model organisms, highlighting another round of clues beyond GWAS and an alternative approach, investigating these clues comprehensively to help in elucidating the genetic architecture of complex traits.

Indexed as

complex traitsgame of “Clue”heritabilitymeta-dimensional analysismulti-omics datasets

Identifiers

PMID29370075
PMCPMC5852557

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.