Will family studies return to prominence in human genetics and genomics? Rare variants and linkage analysis of complex traits

Abstract

A major focus of modern human genetics has been the search for genetic variations that contribute to human disease. These studies originated in families and used linkage methods as a primary analytical tool. With continued technical improvements, these family-based linkage studies have been very powerful in identifying genes contributing to monogenic disorders. When these methods were applied to disorders with complex, non-Mendelian patterns of inheritance they largely failed. The development of effective capabilities for Genome Wide Association Studies (GWAS) relegated family-based studies to a peripheral role in human genetics research. Despite the remarkable record of GWAS discoveries, common variations identified in GWAS account for a limited (frequently less than 10%) proportion of the heritable risk of qualitative traits or variance of quantitative traits. Next generation sequencing is facilitating a re-examination of family-based methods with surprising and intriguing results. We propose that rare variants of large effect underlie many linkage peaks, including complex quantitative phenotypes, and review the issues underlying this proposed basis for complex traits.Mutations underlying inherited traits have now been identified in over 3700 different genes (Cooper, 2010). These discoveries document the extraordinary genetic diversity of the human population. Many of these genes and underlying mutations have been identified by family-based studies employing linkage analysis and positional cloning to locate and identify the genes and related mutations (Botstein and Risch, 2003). The method of applying linkage analysis and positional cloning in family-based cohorts has been extraordinarily productive for identifying genes underlying traits with Mendelian patterns of inheritance. With variations, such as homozygosity mapping for rare recessive traits (Alkuraya, 2010), these family-based approaches are likely to continue to be the fundamental approach for gene discovery for traits with clear patterns of Mendelian segregation. Based on the success of these approaches investigators presumed that extensions of these methods should be successful when applied to complex traits and common diseases (Botstein and Risch, 2003). Family-based methods for identifying complex disease genesComplex traits, either in the form of common disease phenotypes or quantitative traits in the population, can be defined as inherited traits which do not exhibit clear patterns of Mendelian segregation. Initially searches for genes underlying such traits followed a path which was successful for identification of Mendelian traits by first locating chromosomal regions by linkage analysis. Identication of linkage was often followed by targeted analysis of specific functional candidate genes and/or association studies using high density single nucleotide polymorphism (SNP) maps across the linkage region. These high density SNP or microsatellite polymorphism maps were made up of polymorphisms which are common variations, i.e. variation is frequent...

Genome‐Wide Family‐Based Linkage Analysis of Exome Chip Variants and Cardiometabolic Risk

“…In contrast, Genome‐Wide Association Studies (GWAS) have been highly successful in identifying trait or disease associated common genetic variants. However, in most cases, GWAS have identified variants of relatively small effect sizes [Bodmer and Bonilla, ; Bowden, ] that contribute minimally to the variance in disease or quantitative traits. Investigators have speculated that low frequency variants, especially previously untested coding variants, will have larger effect sizes and contribute meaningfully to the variance in complex traits and common diseases [Kiezun et al., ].…”

A Family-Based Rare Haplotype Association Method for Quantitative Traits

“…These features of family-based approaches make them highly attractive for haplotype association studies. Moreover, it has recently been argued that linkage peaks detected by family-based methods may be attributed to rare variants with large effects, and as family data can avoid heterogeneity, they hold great potential for uncovering rare causal variants [22, 23]. …”

Analysis of Whole Exome Sequencing with Cardiometabolic Traits Using Family-Based Linkage and Association in the IRAS Family Study

“…However, GWAS approaches have limitations. Notably, the majority of GWAS have been performed in European‐derived populations, and thus far, the loci identified by these studies have, in many cases, provided limited information about trait‐ or disease‐associated variants in other ethnicities (Rosenberg et al., ; Bowden, ). In addition, GWAS require very large sample sizes to achieve sufficient power and, with few exceptions, primarily identify common genetic variants that account for a small proportion of the heritability of most complex diseases (Manolio et al., ).…”

“…In addition, GWAS require very large sample sizes to achieve sufficient power and, with few exceptions, primarily identify common genetic variants that account for a small proportion of the heritability of most complex diseases (Manolio et al., ). A major advantage of family‐based linkage analysis is its inherent potential to identify high‐impact variants, especially low‐frequency (i.e., minor allele frequency [MAF] > 0.005) variants in moderately sized familial cohorts (Bowden, ). Additionally, family‐based linkage can be a powerful tool even in moderately sized families for detecting loci near causal variants.…”