Overrepresentation of rare variants in a specific ethnic group may confuse interpretation of association analyses

Abstract

Rare sequence variants may be important in understanding the biology of common diseases, but clearly establishing their association with disease is often difficult. Association studies of such variants are becoming increasingly common as large-scale sequence analysis of candidate genes has become feasible. A recent report suggested SLITRK1 (Slit and Trk-like 1) as a candidate gene for Tourette Syndrome (TS). The statistical evidence for this suggestion came from association analyses of a rare 3'-UTR variant, var321, which was observed in two patients but not observed in more than 2000 controls. We genotyped 307 Costa Rican and 515 Ashkenazi individuals (TS probands and their parents) and observed var321 in five independent Ashkenazi parents, two of whom did not transmit this variant to their affected child. Furthermore, we identified var321 in one subject from an Ashkenazi control sample. Our findings do not support the previously reported association and suggest that var321 is overrepresented among Ashkenazi Jews compared with other populations of European origin. The results further suggest that overrepresentation of rare variants in a specific ethnic group may complicate the interpretation of association analyses of such variants, highlighting the particular importance of precisely matching case and control populations for association analyses of rare variants.

Allele variants in functional MicroRNA target sites of the neurotrophin-3 receptor gene (NTRK3) as susceptibility factors for anxiety disorders

“…Similarly, in a recent report, a rare allelic variant in the 3'UTR of SLITRK1 affecting the binding of miR-189 was only identified in two patients with Tourette syndrome and in none of the controls tested [Abelson, et al, 2005]. It was argued that these results might be confounded because the screening for new causative allelic variants was carried out only in cases [Keen-Kim, et al, 2006]. In order to exclude a possible ascertainment bias due to population stratification, we performed re-sequencing of both, patients and controls, and population homogeneity was assessed.…”

Recent genetic discoveries in osteoporosis, sarcopenia and obesity [Review]

“…Measuring lean body mass by DXA is a good index for the quantity and quality of skeletal muscles [88]. Low lean body mass has a strong genetic component, with heritability ranging over 50% [11,12]. However, the specific genes underlying the variation in low lean body mass are largely unknown.…”

“…This symptom is related to diseases such as sarcopenia, a major skeletal disease characterized by low lean body mass, leading to decreased skeletal strength and increased susceptibility to falls and fractures [9,10]. As with low BMD, low lean body mass has a strong genetic component, with heritability ranging over 50% [11,12]. However, the specific genes underlying the variation in low lean body mass are largely unknown.…”

A Biologically Informed Method for Detecting Associations with Rare Variants

“…One must be careful to match cases and controls since overrepresentation of rare variants in a specific ethnic group may complicate the interpretation of association analyses of such variants. Even though there are many available testing strategies, statistically significant mutations, multiple mutations that are functional and co-segregate with disease, de novo mutations, and/or model organisms are required to prove a link between variation in these genes and disease [47]. Figure 2.…”

“…Direct association testing is plausible, but unlikely to be effective in current common study sizes where the total sample size is < 1000 individuals because rare variants will be scarce and contribute small numbers to the analysis which necessitates cautious interpre-tation [45]. It is difficult and extraordinarily expensive to ascertain large enough data sets to acquire sufficient numbers of cases that carry the same causal rare variant and to be able to detect a difference in allele frequency when the MAF is so low [20,21,22,46,47]. Ignoring this limitation with small sample sizes could lead to unstable estimates of rare variant effects on disease and be uninformative [49].…”