Evidence map›Paper›PMID 9634509›Full record

ArticleAmerican journal of human genetics1998

Mapping genes that underlie ethnic differences in disease risk: methods for detecting linkage in admixed populations, by conditioning on parental admixture.

P M McKeigue

Abstract read
In one paragraph

Article in American journal of human genetics, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing 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

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

  1. Pooled it
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  10. Population Stratification in Genetic Association Studies.Current protocols in human genetics · 2017
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47 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

1 author.

P M McKeigueEpidemiology Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. p.mckeigue@lshtm.ac.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes that underlie ethnic differences in disease risk can be mapped in affected individuals of mixed descent if the ancestry of the alleles at each marker locus can be assigned to one of the two founding populations. Linkage can be detected by testing for association of the disease with the ancestry of alleles at the marker locus, by conditioning on the admixture (defined as the proportion of genes that have ancestry from the high-risk population) of both parents. With regard to exploiting the effects of admixture, this test is more flexible and powerful than the transmission-disequilibrium test. Under the assumption of a multiplicative model, the statistical power for a given sample size depends only on parental admixture and the risk ratio r between populations that is generated by the locus. The most informative families are those in which mean parental admixture is .2-.7 and in which admixture is similar in both parents. The number of markers required for a genome search depends on the number of generations since admixture and on the information content for ancestry (f) of the markers, defined as a function of allele frequencies in the two founding populations. Simulations using a hidden Markov model suggest that, when admixture has occurred 2-10 generations earlier, a multipoint analysis using 2,000 biallelic markers, with f values of 30%, can extract 70%-90% of the ancestry information for each locus. Sets of such markers could be selected from libraries of single-nucleotide polymorphisms, when these become available.

Indexed as

RiskAllelesChromosome MappingGenetic Diseases, InbornGenetic LinkageGenetic MarkersHumansMarkov ChainsModels, GeneticPedigreePolymorphism, GeneticGenetic Markers

Identifiers

PMID9634509
PMCPMC1377232

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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.