Coding single-nucleotide polymorphisms associated with complex vs. Mendelian disease: Evolutionary evidence for differences in molecular effects

Abstract

Most Mendelian diseases studied to date arise from mutations that lead to a single amino acid change in an encoded protein. An increasing number of complex diseases have also been associated with amino acid-changing single-nucleotide polymorphisms (coding SNPs, cSNPs), suggesting potential similarities between Mendelian and complex diseases at the molecular level. Here, we use two different evolutionary analyses to compare Mendelian and complex disease-associated cSNPs. In the first, we estimate the likelihood that a specific amino acid substitution in a protein will affect the protein's function, by using amino acid substitution scores derived from an alignment of related protein sequences and statistics from hidden Markov models. In the second, we use standard Ka͞Ks ratios to make comparisons at the gene, rather than the individual amino acid, level. We find that Mendelian disease cSNPs have a very strong tendency to occur at highly conserved amino acid positions in proteins, suggesting that they generally have a severe impact on the function of the protein. Perhaps surprisingly, the distribution of amino acid substitution scores for complex disease cSNPs is dramatically different from the distribution for Mendelian disease cSNPs, and is indistinguishable from the distribution for ''normal'' human variation. Further, the distributions of Ka͞Ks ratios for human and mouse orthologs indicate greater positive selection (or less negative selection) pressure on complex disease-associated genes, on average. These findings suggest that caution should be exercised when using Mendelian disease as a model for complex disease, at least with respect to molecular effects on protein function. O ver the past few decades, rapid progress has been made by using genetics to identify the molecular cause of human disease. Most of these diseases are rare, highly penetrant, traits that are found to follow Mendelian rules of inheritance in families, and are therefore often referred to as ''Mendelian diseases.'' Linkage methods for mapping Mendelian traits are well established and have resulted in the identification of the molecular causes of hundreds of diseases. The most common cause of Mendelian disease is a single-nucleotide polymorphism (SNP) that results in a single amino acid change in the protein encoded by that gene (coding SNP, or cSNP).Complex traits, on the other hand, are caused by a number of factors both genetic and environmental, and therefore do not follow simple Mendelian rules of inheritance. Finding the molecular causes of complex traits has become the focus of increasing attention. Association studies are rapidly gaining ground for human disease, with the human Haplotype Map Project being funded to support it. Quantitative trait locus (QTL) mapping, especially in mice, is also now beginning to bear fruit (1). A number of researchers have suggested that most SNPs that underlie complex traits may be found in regulatory elements of the genome (2, 3). However, to date, most of the reported SNPs associated with complex ...

A Functional Polymorphism under Positive Evolutionary Selection in ADRB2 is Associated with Human Intelligence with Opposite Effects in the Young and the Elderly

“…Alternative strategies to identify potentially functional genetic variants are therefore clearly needed. Because speciation involves phenotypic divergence in adaptive, usually complex, traits it is tempting to hypothesize that the genetic changes during speciation should involve loci that remain to control phenotypic variation in the relevant phenotypes within the newly emerged species (Thomas and Kejariwal 2004). Next to the obvious implications for evolutionary genetics, this assumption opens up the intriguing possibility of ascertaining the genetic basis of phenotypic variation in humans from a comparative genomic analysis.…”

“…Deleterious mutations tend to be localized at conserved protein residues Arbiza et al 2006;Miller and Kumar 2001). More interestingly, a comparison of genes involved in ''normal'' genetic variation, Mendelian disease and complex disorders showed that genes involved in complex traits exhibit a higher rate of protein evolution (Thomas and Kejariwal 2004). Apparently, genes involved in the adaptive evolution of our species are more likely to harbor functional polymorphisms that affect variation in complex traits between humans.…”

“…Following the identification of positively selected genes that are expressed in the central nervous system (CNS) we conducted a second step of the analysis where non-synonymous coding SNPs in these genes were ascertained at positions that differ between the human and chimpanzee reference sequences. This approach differs from other approaches (Clark et al 2003;Nielsen et al 2005;Dorus et al 2004) and is based on the assumption that genes involved in recent adaptive evolution of our species are more likely to harbor functional variants in the extant human population (as suggested by Bustamante et al 2005;Arbiza et al 2006;Miller and Kumar 2001;Thomas and Kejariwal 2004). We therefore identify amino acid changes specific to humans that are obvious candidates to have a functional effect on a brain related phenotype that has diverged during primate evolution.…”

The proportion of mutations predicted to have a deleterious effect differs between gain and loss of function genes in neurodegenerative disease

“…Homology searches are also performed to determine if the substitution is conserved across species. The Panther program analyzes variants and provides subPSEC scores that range from -10 (most severe) to 0 (least severe) (Thomas, et al, 2003;Thomas and Kejariwal, 2004). It then uses a hidden Markov model based on position specific independent counts to convert this data into a probability score that the particular amino acid substitution is damaging.…”

Evolutionary genetics of affective disorders

“…(1) Genes, alleles, and haplotypes inferred as being subject to positive selection in humans can be chosen as markers to evaluate their potential associations with the risk of psychotic-affective or other polygenic disorders (Thomas and Kejariwal 2004;Crespi et al 2007). The beauty of this approach is that alleles subject to positive selection are predicted to be functional (McVean and Spencer 2006), which should increase the likelihood that associations will be ascertained (Biswas and Akey 2006).…”