Evidence map›Paper›PMID 33707768›Full record

ReviewNature reviews. Cardiology2021

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development.

Michael V Holmes, Tom G Richardson, Brian A Ference, Neil M Davies, George Davey Smith

Open access · greenAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed, 5 pooled it
24.2field-weighted citation impact, top 1% 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

106 citing papers in PubMed, 5 syntheses or guidelines pooled it, 194 citations in OpenAlex.

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46 more citing papers are in PubMed but not listed here.

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

5 authors at 4 institutions in 2 countries.

Michael V HolmesMedical Research Council Population Health Research Unit, University of Oxford, Oxford, UK. michael.holmes@ndph.ox.ac.uk.ORCID http://orcid.org/0000-0001-6617-0879
Tom G RichardsonMedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID http://orcid.org/0000-0002-7918-2040
Brian A FerenceCentre for Naturally Randomised Trials, University of Cambridge, Cambridge, UK.
Neil M DaviesMedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
George Davey SmithMedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
University of Bristol · GBNorwegian University of Science and Technology · NOUniversity of Cambridge · GBUniversity of Oxford · GB

Funding

British Heart Foundation FS/18/23/33512Cancer Research UK 16896Medical Research Council MC_UU_00011/1Medical Research Council MR/S003886/1
6 · The paper itself

Abstract

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

Indexed as

BiomarkersCardiovascular AgentsCardiovascular DiseasesDrug DevelopmentGenomicsHumansBiomarkersCardiovascular Agents

Identifiers

PMID33707768
OpenAlexW3080477490

What Socratic holds

Textmetadata
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 Socratic graph.