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  • Review Article
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Family-based designs for genome-wide association studies

Key Points

  • Linkage analysis has been hugely successful in identifying the genetic basis of many Mendelian disorders and the genetic contribution to some complex conditions. However, these approaches have been superseded in the past 15 years by association mapping and, more recently, by genome-wide association (GWA) studies.

  • Present GWA approaches have difficulty detecting rare risk variants through linkage disequilibrium (LD) with common SNP markers; however, such variants can be found by linkage analysis. For example, BRCA1 and BRCA2, which are the most predominant of the known breast cancer susceptibility genes, were previously identified through linkage analysis but have not been identified by GWA studies.

  • Typical linkage study designs include: parent–offspring trios, affected sibling pairs (sib-pairs), unselected sib-pairs or related individuals selected from the extremes of a quantitative trait distribution (for example, concordant or discordant sib-pairs), extended pedigrees with multiple affected individuals, consanguineous families and families obtained from isolated populations.

  • A combination of linkage and association methodologies should provide the most accurate and powerful approach for identifying and characterizing the full range of disease-susceptibility variants. Family study designs offer: the ability to enrich for genetic loci containing rare variants; methods to control for heterogeneity and population stratification; direct estimates of the genetic contribution of different loci; the opportunity to examine the transmission of variants with phenotypes; and the ability to reveal the effects of parental origin of alleles.

  • The problem of population heterogeneity is essentially non-existent in linkage analysis, so it has been tempting to use related individuals in genetic association studies as they are necessarily of the same ethnic origin (family-based as opposed to population-based controls). Another advantage of using family-based controls is that only family-based data will potentially exhibit genotyping errors in the form of Mendelian inconsistencies.

  • These considerations motivate the search for a general framework to evaluate linkage and association simultaneously, taking combinations of data from pedigrees with different relationship structures (such as extended pedigrees, sibships or transmission disequilibrium test (TDT) families) and case–control samples. Such an approach is likely to be the most powerful approach for identifying new genetic factors related to trait loci, beyond those that can be readily detected by GWA in case–control designs.

  • Prime examples of traits for which linkage and association mapping have been essential are Crohn's disease and fetal haemoglobin levels in adults.

Abstract

Association mapping has successfully identified common SNPs associated with many diseases. However, the inability of this class of variation to account for most of the supposed heritability has led to a renewed interest in methods — primarily linkage analysis — to detect rare variants. Family designs allow for control of population stratification, investigations of questions such as parent-of-origin effects and other applications that are imperfectly or not readily addressed in case–control association studies. This article guides readers through the interface between linkage and association analysis, reviews the new methodologies and provides useful guidelines for applications. Just as effective SNP-genotyping tools helped to realize the potential of association studies, next-generation sequencing tools will benefit genetic studies by improving the power of family-based approaches.

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Acknowledgements

We are grateful to J. Terwilliger for providing us with unpublished results on his pseudomarker method. Our work was partially supported by the National Natural Science Foundation of China (NSFC) grant no. 30730057 to J.O.

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Glossary

Linkage analysis

A family-based method to search for the chromosomal location of a trait locus by demonstrating co-segregation of the disease with genetic markers of known chromosomal location.

Linkage disequilibrium

(LD). The nonrandom combinations of alleles at different loci on a chromosome. LD arises from the evolutionary history of the population and decays across generations at a rate proportional to the degree of linkage between the loci.

Genome-wide association studies

(GWA studies). An approach that tests the whole genome for a statistical association between a marker and a trait in unrelated cases and controls. It is designed to identify associations with traits, such as common diseases.

Imputation

The process of inferring genotypes and/or haplotypes at untyped loci based on neighbouring loci in strong linkage disequilibrium with the untyped loci. The assumption is made that no recombination has occurred between these closely spaced loci.

Heterogeneity

Substructure within a population. This may be due to population admixture (with different allele frequencies occurring in subpopulations), different environmental contributing conditions or different genetic factors leading to disease.

Population stratification

Heterogeneity within a population.

Likelihood methods

Methods that are based on statistical models and that estimate parameters in those models

Conditioning

In likelihood analysis, conditioning on relatives is based on calculating conditional probabilities when given known or assumed information on relatives of an individual.

Hidden Markov model

A statistical model that assumes an underlying (unobserved) Markov process; that is, a sequence of events such that a specific event depends only on the one immediately preceding it.

Markov chain Monte Carlo algorithms

(MCMC algorithms). Computer-based random processes that simulate Markov models.

Segregation analysis

This refers to estimating segregation ratios (the ratio of presence versus absence of a heritable trait among offspring of a specific set of parents) and testing whether they are equal to some ratios expected under Mendelian laws. For example, when one of two parents is affected with a rare dominant Mendelian disorder and the other is not, the expected segregation ratio among their offspring is 1:1.

Ascertainment

The process used to find or select subjects for inclusion in a genetic study.

Penetrances

The conditional probability of a phenotype (specifically, the probability of being affected with disease), given an underlying genotype.

Recombination mapping

The process that assigns a trait locus to a restricted genomic region by genetic linkage analysis.

Multiplex families

Families that contain more than one affected individual.

Identity-by-descent

Two alleles in a genotype (individual) are called identical-by-descent when they are copies of one allele in an ancestor (identical-by-descent is often abbreviated to IBD, but in this article IBD stands for inflammatory bowel disease). By contrast, two alleles that are identical by state just 'look' the same but could have originated from different ancestors.

Homozygosity mapping

A form of recombination mapping that allows the localization of rare recessive traits by identifying unusually long stretches of homozygosity at consecutive markers.

Phase

The sequence of alleles at multiple loci inherited from one parent. For an individual who is heterozygous at two loci (Aa and Bb), there are two ways (phases) in which the two alleles, one at each locus, can be inherited from the same parent (BA/ba or Ba/bA).

McNemar-type statistic

A test that focuses on paired data (either two tests on a specific individual or one test on paired individuals), in which the test has a yes/no outcome. It is of interest to see whether the yes/no distribution is the same for the two members of the pair. For example, two raters may carry out a diagnosis of schizophrenia on a group of probands; the McNemar-type statistic is used to test whether the two raters obtain the same numbers of 'affected' and 'unaffected' individuals.

Type 1 error

The conditional probability of obtaining a significant result in the absence of any effect tested; it is also called the probability of a false-positive result.

Genotype relative risk

The ratio of the probability of a trait or disease occurring in an at-risk group to the probability of it occurring in a population that is not considered to be at risk. For example, a risk of 1.2 in heterozygotes that are relative to common homozygotes implies that the heterozygotes are 20% more likely to suffer from the disease.

Class D regressive model

Regressive models account for major genes and residual familial patterns of dependence, in terms of correlations between relatives, without necessarily introducing a particular scheme of causality for the residual patterns. The class D regressive model incorporates four correlations which may have distinct values to account for residual familial patterns: father–mother, father–offspring, mother–offspring and sibling–sibling. Likelihoods are calculated by successively conditioning on ancestral phenotypes and major genes.

Lod score

(Base 10 'logarithm of the odds' or 'log-odds'). A statistical estimate of whether two loci are likely to lie near each other on a chromosome and are, therefore, likely to be inherited together. A lod score of three or more is generally taken to indicate that the two loci are close.

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Ott, J., Kamatani, Y. & Lathrop, M. Family-based designs for genome-wide association studies. Nat Rev Genet 12, 465–474 (2011). https://doi.org/10.1038/nrg2989

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