Evidence map›Paper›PMID 28213088›Full record

ReviewPharmacology & therapeutics2017

Personalized medicine: Genetic risk prediction of drug response.

Ge Zhang, Daniel W Nebert

Erratum issuedAbstract readReview
In one paragraph

Review in Pharmacology & therapeutics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
7.4field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 71 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. The Use of AI for Phenotype-Genotype Mapping.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  8. Review
  9. Article
  10. Review
  11. Unlocking Genetic Profiles with a Programmable DNA-Powered Decoding Circuit.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Pharmacogenetics of asparaginase in acute lymphoblastic leukemia.Cancer drug resistance (Alhambra, Calif.) · 2019
    Review
  18. Needles, Haystacks and Next-Generation Genetic Sequencing.Health matrix (Cleveland, Ohio : 1991) · 2018
    Article
  19. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Ge ZhangDivision of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229-3039, United States. Electronic address: ge.zhang@cchmc.org.
Daniel W NebertDivision of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229-3039, United States; Department of Environmental Health and Center for Environmental Genetics, University of Cincinnati School of Medicine, Cincinnati, OH 45267-0056, United States. Electronic address: dan.nebert@uc.edu.
Cincinnati Children's Hospital Medical Center · USUniversity of Cincinnati · US

Funding

REPRODUCTIVE AND DEVELOPMENTAL TOXICOLOGY RESEARCHP30ES006096 · NIEHS · UNIVERSITY OF CINCINNATI · PI PINNEY, SUSAN MENGEL · 1992 to 2022
$35.4M
Better Outcomes for Children: Promoting Excellence in Healthcare Genomics to Inform PolicyU01HG008666 · NHGRI · CINCINNATI CHILDRENS HOSP MED CTR · PI HARLEY, JOHN BARKER · 2015 to 2019
$4.2M
NHGRI NIH HHS U01 HG008666NIEHS NIH HHS P30 ES006096
6 · The paper itself

Abstract

Pharmacogenomics (PGx), a substantial component of "personalized medicine", seeks to understand each individual's genetic composition to optimize drug therapy -- maximizing beneficial drug response, while minimizing adverse drug reactions (ADRs). Drug responses are highly variable because innumerable factors contribute to ultimate phenotypic outcomes. Recent genome-wide PGx studies have provided some insight into genetic basis of variability in drug response. These can be grouped into three categories. [a] Monogenic (Mendelian) traits include early examples mostly of inherited disorders, and some severe (idiosyncratic) ADRs typically influenced by single rare coding variants. [b] Predominantly oligogenic traits represent variation largely influenced by a small number of major pharmacokinetic or pharmacodynamic genes. [c] Complex PGx traits resemble most multifactorial quantitative traits -- influenced by numerous small-effect variants, together with epigenetic effects and environmental factors. Prediction of monogenic drug responses is relatively simple, involving detection of underlying mutations; due to rarity of these events and incomplete penetrance, however, prospective tests based on genotype will have high false-positive rates, plus pharmacoeconomics will require justification. Prediction of predominantly oligogenic traits is slowly improving. Although a substantial fraction of variation can be explained by limited numbers of large-effect genetic variants, uncertainty in successful predictions and overall cost-benefit ratios will make such tests elusive for everyday clinical use. Prediction of complex PGx traits is almost impossible in the foreseeable future. Genome-wide association studies of large cohorts will continue to discover relevant genetic variants; however, these small-effect variants, combined, explain only a small fraction of phenotypic variance -- thus having limited predictive power and clinical utility.

Indexed as

PharmacogeneticsPrecision MedicineDrug LabelingGenotypeHumansTreatment OutcomeComplex PGx traitsGenetic architectureGenetic risk predictionMonogenic (Mendelian) PGx traitsPharmacogeneticsPharmacogenomics (PGx)Predominantly oligogenetic PGx traits

Identifiers

PMID28213088
PMCPMC5653378
OpenAlexW2587781379

What OpenQuestion holds

Textmetadata
LicenceTDM
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.