Evidence map›Paper›PMID 11741273›Full record

ReviewAAPS pharmSci2001

Genetic variations in human G protein-coupled receptors: implications for drug therapy.

W Sadee, E Hoeg, J Lucas, D Wang

Open access · bronzeAbstract readReview
In one paragraph

Review in AAPS pharmSci, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 44 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

W SadeeDepartment of Biopharmaceutical Sciences, University of California San Francisco, San Francisco CA 94143-0446, USA. sadee@cgl.ucsf.edu
E Hoeg
J Lucas
D Wang
University of San Francisco · USNGM Biopharmaceuticals (United States) · USUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous genes encode G protein-coupled receptors (GPCRs)-a main molecular target for drug therapy. Estimates indicate that the human genome contains approximately 600 GPCR genes. This article addresses therapeutic implications of sequence variations in GPCR genes. A number of inactivating and activating receptor mutations have been shown to cause a variety of (mostly rare) genetic disorders. However, pharmacogenetic and pharmacogenomic studies on GPCRs are scarce, and therapeutic relevance of variant receptor alleles often remains unclear. Confounding factors in assessing the therapeutic relevance of variant GPCR alleles include 1) interaction of a single drug with multiple closely related receptors, 2) poorly defined binding pockets that can accommodate drug ligands in different orientations or at alternative receptor domains, 3) possibility of multiple receptor conformations with distinct functions, and 4) multiple signaling pathways engaged by a single receptor. For example, antischizophrenic drugs bind to numerous receptors, several of which might be relevant to therapeutic outcome. Without knowing accurately what role a given receptor subtype plays in clinical outcome and how a sequence variation affects drug-induced signal transduction, we cannot predict the therapeutic relevance of a receptor variant. Genome-wide association studies with single nucleotide polymorphisms could identify critical target receptors for disease susceptibility and drug efficacy or toxicity.

Indexed as

Genetic VariationDrug TherapyGTP-Binding ProteinsHumansPolymorphism, GeneticReceptors, Cell SurfaceSignal TransductionGTP-Binding ProteinsReceptors, Cell Surface

Identifiers

PMID11741273
PMCPMC2751017
OpenAlexW2016895167

What OpenQuestion 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 OpenQuestion graph.