An algorithm to construct genetically similar subsets of families with the use of self-reported ethnicity information

Genotype-based matching to correct for population stratification in large-scale case-control genetic association studies

Genome-wide association studies are helping to dissect the etiology of complex diseases. Although case-control association tests are generally more powerful than family-based association tests, population stratification can lead to spurious disease-marker association or mask a true association. Several methods have been proposed to match cases and controls prior to genotyping, using family information or epidemiological data, or using genotype data for a modest number of genetic markers. Here, we describe a genetic similarity score matching (GSM) method for efficient matched analysis of cases and controls in a genome-wide or large-scale candidate gene association study. GSM comprises three steps: (1) calculating similarity scores for pairs of individuals using the genotype data; (2) matching sets of cases and controls based on the similarity scores so that matched cases and controls have similar genetic background; and (3) using conditional logistic regression to perform association tests. Through computer simulation we show that GSM correctly controls false-positive rates and improves power to detect true disease predisposing variants. We compare GSM to genomic control using computer simulations, and find improved power using GSM. We suggest that initial matching of cases and controls prior to genotyping combined with careful re-matching after genotyping is a method of choice for genome-wide association studies.

Are RGS2 gene polymorphisms associated with high blood pressure in an ethnicity- and gender-specific manner?

BACKGROUND

Polymorphisms in the Regulator of G-protein Signaling 2 (RGS2) gene have been reported to be associated with hypertension (HT) in Japanese women and black Americans of either gender but not in white Americans or Japanese men. We have tested whether these proposed ethnicity- and gender-specific associations between RGS2 gene polymorphisms and HT can be confirmed in an independent population of male and female blacks, whites, and south Asians.

METHODS

A population-based sample of 1379 black, white Dutch, and south Asian subjects from the Amsterdam area was genotyped for eight polymorphisms in the RGS2 gene. All analyses were done separately per ethnic group. The phenotype high blood pressure was defined as a dichotomous variable comparing HT vs. normotension (NT) and as a linear variable using systolic blood pressure (SBP) in a multiple regression analysis with concomitant antihypertensive medication, age and body mass index as coexplanatory variables.

RESULTS

Ethnic differences in the frequency of polymorphisms and haplotypes (HAPs) derived thereof were in line with previous studies. Our data do not confirm previously reported ethnicity- or gender-specific associations regardless which phenotype definition was used. While the D allele of 1891-1892TC insertion/deletion polymorphism showed association in several groups, they differed from previously reported ones. Haplotype-phenotype analysis was not more sensitive to detect genotype-phenotype associations than individual alleles.

CONCLUSIONS

Previously reported ethnicity- and gender-specific associations of RGS2 genotype and hypertensive phenotype are not robust. Nevertheless, the 1891-1892TC insertion/deletion polymorphism warrants further investigation.

Estimating ethnic admixture from pedigree data

This paper introduces a likelihood method of estimating ethnic admixture that uses individuals, pedigrees, or a combination of individuals and pedigrees. For each founder of a pedigree, admixture proportions are calculated by conditioning on the pedigree-wide genotypes at all ancestry-informative markers. These estimates are then propagated down the pedigree to the nonfounders by a simple averaging process. The large-sample standard errors of the founders' proportions can be similarly transformed into standard errors for the admixture proportions of the descendants. These standard errors are smaller than the corresponding standard errors when each individual is treated independently. Both hard and soft information on a founder's ancestry can be accommodated in this scheme, which has been implemented in the genetic software package Mendel. The utility of the method is demonstrated on simulated data and a real data example involving Mexican families of mixed Amerindian and Spanish ancestry.

Reduction of sample heterogeneity through use of population substructure: an example from a population of African American families with sarcoidosis

Sarcoidosis is a granulomatous inflammatory disorder of complex etiology with significant linkage to chromosome 5, and marginal linkage was observed to five other chromosomes in African Americans (AAs) in our previously published genome scan. Because genetic factors underlying complex disease are often population specific, genetic analysis of samples with diverse ancestry (i.e., ethnic confounding) can lead to loss of power. Ethnic confounding is often addressed by stratifying on self-reported race, a controversial and less-than-perfect construct. Here, we propose linkage analysis stratified by genetically determined ancestry as an alternative approach for reducing ethnic confounding. Using data from the 380 microsatellite markers genotyped in the aforementioned genome scan, we clustered AA families into subpopulations on the basis of ancestry similarity. Evidence of two genetically distinct groups was found: subpopulation one (S1) comprised 219 of the 229 families, subpopulation two (S2) consisted of six families (the remaining four families were a mixture). Stratified linkage results suggest that only the S1 families contributed to previously identified linkage signals at 1p22, 3p21-14, 11p15, and 17q21 and that only the S2 families contributed to those found at 5p15-13 and 20q13. Signals on 2p25, 5q11, 5q35, and 9q34 remained significant in both subpopulations, and evidence of a new susceptibility locus at 2q37 was found in S2. These results demonstrate the usefulness of stratifying on genetically determined ancestry, to create genetically homogeneous subsets--more reliable and less controversial than race-stratified subsets--in which to identify genetic factors. Our findings support the presence of sarcoidosis-susceptibility genes in regions identified elsewhere but indicate that these genes are likely to be ancestry specific.

Developing and optimizing a decisional instrument using self-reported ancestry for carrier screening in a multi-ethnic society

PURPOSE

To develop a decisional instrument for ancestry-based cystic fibrosis and/or hemoglobinopathies carrier couple screening in The Netherlands.

METHODS

A flowchart (Instrument A) and a questionnaire with maps of geographical areas with originally high cystic fibrosis and hemoglobinopathies carrier frequencies (Instrument B), were developed to support participants in self-assessing their eligibility as a couple for carrier screening for cystic fibrosis and/or hemoglobinopathies. The outcome was compared to the self-reported origin of both partners' ancestors during an in-depth interview. Furthermore, preference for Instrument A or B was determined.

RESULTS

Of the 112 participants, 88% (99/112, 95% CI 82-94%) (Instrument A) and 91% (102/112, 95% CI 86-96%) (Instrument B), respectively, arrived at a decision in accordance with their ancestral origin, and 57% (64/112, 95% CI 48-66%) preferred Instrument B. A false negative proportion of 5.5% suggests that some carriers will exclude themselves from screening. Results might improve with minor changes in the instruments with regard to geographic specification, and availability of translated versions.

CONCLUSION

A decisional instrument to assess ancestry-based eligibility for cystic fibrosis and/or hemoglobinopathies carrier screening, is now available and can with slight adaptations be used in other countries. The instrument also takes into account the possibility of mixed ancestry.