The impact of genotyping error on family-based analysis of quantitative traits

Errors in genotyping can substantially influence the power to detect linkage using affected sib-pairs, but it is not clear what effect such errors have on quantitative trait analyses. Here we use Monte Carlo simulation to examine the influence of genotyping error on multipoint vs two-point analysis, variable map density, locus effect size and allele frequency in quantitative trait linkage and association studies of sib-pairs. The analyses are conducted using variance components methods. We contrast the effects of error on quantitative trait analyses with those on the affected sib-pair design. The results indicate that genotyping error influences linkage studies of affected sib pairs more severely than studies of quantitative traits in unselected sibs. In situations of modest effect size, 5% genotyping error eliminates all supporting evidence for linkage to a true susceptibility locus in affected pairs, but may only result in a loss of 15% of linkage information in random pairs. Multipoint analysis does not suffer substantially more than two-point analysis; for moderate error rates (< 5%), multipoint analysis with error is more powerful than two-point with no error. Map density does not appear to be an important factor for linkage analysis. QTL association analyses of common alleles are reasonably robust to genotyping error but power can be affected dramatically with rare alleles.     

Familial resemblance for glucose and insulin metabolism indices derived from an intravenous glucose tolerance test in Blacks and Whites of the HERITAGE Family Study

Type 2 diabetes mellitus (T2DM), characterized by hyperglycemia, is a complex disease primarily caused by impairment in insulin sensitivity (S_I) and insulin secretion. While a strong genetic component for T2DM is well established, there are few reports on racial differences in the magnitude of the genetic effects of T2DM and indices of glucose and insulin metabolism. We report here on the familial resemblance for traits related to glucose metabolism at pre-exercise training levels in 492 members from 99 sedentary White families and 259 members from 108 Black families participating in the multicenter HERITAGE Family Study. All these traits were obtained from the frequently sampled intravenous glucose tolerance test (IVGTT). They include glucose disappearance index (K_g), an overall index for glucose tolerance, acute insulin response to glucose (AIR_Glucose) which is an index for insulin secretion, and those derived from the minimal model including S_I and the disposition index (DI). DI, derived as the product of S_I and AIR_Glucose, is a measure of the activity of the B-cells adjusted for insulin resistance. After adjustment for age, sex, and body mass index, the maximal heritability estimates in Blacks (Whites) are 48±14% (25±8%) for K_g, 44±14% (46±8%) for AIR_Glucose, 38±12% (44±8%) for S_I and 32±14% (24±8%) for DI. Interestingly, Blacks have higher heritability for overall glucose tolerance than Whites but there is no race difference in heritability estimates for insulin sensitivity or insulin secretion.     

Hidden linkage: a comparison of the affected sib pair (ASP) test and transmission/disequilibrium test (TDT)

I compare the transmission/disequilibrium test (TDT) and affected sib pair (ASP) test under a general algebraic model describing a bi-allelic disease locus. Assuming linkage to a bi-allelic marker, I derive two binomial probabilities, one for parental allele 'transmission' (Pt ) which determines the magnitude of the TDT χ² statistic (χ²_tdt), and a second for identity-by-descent (ibd) marker allele 'sharing' ( P _s) which determines the magnitude of the ASP test statistic (χ²_asp). I also consider the ASP test applied to a completely polymorphic marker and demonstrate that the probability of ASP marker allele sharing ( P _s) is identical to P _s observed for a bi-allelic marker in equilibrium with the disease locus. I present a general framework for determining the power of the TDT and ASP test based on expressions for P _t, P _s and the proportion ( H / F ) of ascertained parents who are informative at the marker. Two previous analytic investigations of TDT power based on the work of Ott (1989), and Risch & Merikangas (1996) are shown to be special cases of this general framework. In addition, I show the relationship between the framework I present and a third analytic investigation of TDT power for multi-allelic markers based on the work of Sham & Curtis (1995).     

Randomization tests of disease-marker associations

A powerful test for population association of a disease with alleles at a bi-allelic marker locus is the transmission/disequilibrium test ( TDT ). A generalization of the test to multi-allelic marker locus is proposed which utilizes the maximal association of individual alleles with the disease, given by the maximum TDT statistic, TDT _(max). To overcome the multiple testing problem encountered when using the maximal association to test the null hypothesis of no disease-marker association, a randomization procedure is developed. An investigation of the power of the test suggests that the randomization procedure performs almost as well as a recently proposed likelihood based test of linkage disequilibrium. The advantage of the new test is that it can be applied sequentially, based on a one-sided version of the TDT statistic, for investigating patterns of association of several individual alleles with the disease.     

The effect of genotyping error in sib-pair genomewide linkage scans depends crucially upon the method of analysis

In genomewide linkage scans for complex diseases involving many loci with small genetic effects, it may be the case that no loci reach conventional statistical significance. A complementary method of evaluating linkage results, locus counting, may provide evidence for the existence of a number of genetic loci in these cases. Sib-pair study designs are often used in genomewide linkage scans, but because all genotype configurations are consistent with Mendelian inheritance, genotyping error will go largely undetected. Previous work on the effect of genotyping error has focused on a single disease locus. We considered the effect of two levels of genotyping error on genomewide evidence for linkage by using the simulated GAW 13 data. For affected sib-pair and non-parametric quantitative trait study designs, a 0.5% genotyping error rate reduced the number of independent linkage regions towards that expected under the null hypothesis of no linkage. A 2% genotyping error rate yielded less independent linkage regions than expected under the null hypothesis of no linkage. For a quantitative trait analysed using a parametric regression-based method, there was very little erosion of the linkage signal, even for error rates as high as 2%.     

Hardy–Weinberg quality control

An efficient test of deviation from Hardy–Weinberg frequencies with one degree of freedom was applied to 44 marker loci in a genome scan, and 7 loci had a significant excess of apparent homozygotes (χ²₍₁₎ > 6) suggestive of typing error. In this example evidence for linkage did not increase when outliers were censored. Statistical quality control is an essential part of genotyping, and the effect of mistyping and map error should be considered in evaluating any genome scan.     

Accounting for Genotyping Errors in Tagging SNP Selection

One limitation of the existing tagging SNP selection algorithms is that they assume the reported genotypes are error free. However, genotyping errors are often unavoidable in practice. Many tagging SNP selection methods depend heavily on the estimated haplotype frequencies. Recent studies have demonstrated that even slight genotyping errors can lead to serious consequences with regard to haplotype reconstruction and frequency estimation. Here we present a tagging SNP selection method that allows for genotyping errors. Our method is a modification of the pair-wise r² tagging SNP selection algorithm proposed by Carlson et al. (2004) . We have replaced the standard EM algorithm in Carlson's method with an EM that accounts for genotyping errors, in an attempt to obtain better estimates of the haplotype frequencies and r² measure. Through simulation studies we compared the performance of our modified algorithm with that of the original algorithm. We found that the number of tags selected by both methods increased with increasing genotyping errors, though our method led to smaller increase. The power of haplotype association tests using the selected tags decreased dramatically with increasing genotyping errors. The power of single marker tests also decreased, but the reduction was not as much as the reduction in power of haplotype tests. When restricting the mean number of tags selected by both methods to be similar to the baseline number, Carlson's method and our method led to similar power for the subsequent haplotype and single marker tests. Our results showed that, by accounting for random genotyping errors, our method can select tagging SNPs more efficiently than Carlson's method. The computer program that implements our modified tagging SNP selection algorithm is available at our web site: http://www.personal.psu.edu/tuy104/ .     

Power of Selective Genotyping in Genetic Association Analyses of Quantitative Traits

A power calculation is described in which the power of selective genotyping in genetic association studies of quantitative traits is evaluated. The method of selective genotyping implies the selection of the extremely high and low scoring individuals from the continuous distribution of a quantitative trait. The selected individuals are genotyped and association is tested. In the power calculation the following parameters are varied: total sample size of the phenotyped group (1000, 1500, 2000); selection of extremely high and low scoring individuals (2.5%, 5%, 10%); allele frequency of the risk increasing allele (0.10 to 0.90); mode of inheritance and proportion of variance explained by the quantitative trait locus = 0.01, 0.05, 0.10). We conclude that the method of selective genotyping is a powerful method to detect association for a quantitative trait.     

DNA polymorphisms at fibrinogen loci and plasma fibrinogen concentration

Associations have been reported between restriction fragment length polymorphisms (RFLPs) at fibrinogen loci and plasma fibrinogen concentration, in a British study. We have examined a series of unrelated Norwegians. We found no association between plasma fibrinogen concentration and any genotype in either of two fibrinogen polymorphisms examined (one at the α-fibrinogen locus, the other at the β-fibrinogen locus). We have also examined monozygotic twins and evaluated heritability of fibrinogen level by the intraclass correlation coefficient. We arrived at an unimpressive estimate of heritability. With such a low level of heritability, it would have been surprising if we had found an association with a single gene marker in a relatively limited series of people. The reason for the discrepancy between the British and the Norwegian study is unknown. Great care has to be exercised in interpreting disease associations, since with DNA variations being examined at an increasing number of "candidate loci", the risk of finding spurious associations increases with the number of analyses conducted.     

Allowing for Genotyping Error in Analysis of Unmatched Case-Control Studies

A commonly‐used method for testing for association between disease and a single‐nucleotide polymorphism (SNP) is to compare the frequencies of the SNP genotypes in a sample of unrelated cases to those in a sample of unrelated controls drawn from the same population (an unmatched case‐control study). A drawback of such a study is that it is impossible to detect genotyping errors, and few methods have been developed to allow for the presence of undetected genotyping errors. In this paper, we obtain analytic formulae for estimates of genotypic relative risks in terms of error probability (e). In general, e will be unknown. We investigate the effect of assuming both correct and incorrect values of e on power and type I error, and also on the genotypic relative risk estimates. The choice of e was found to have no effect on power or Type I error probability (provided a 2df test was used, allowing relative risks of homozygotes and heterozygotes to differ). However, overestimating e in the presence of a true association was found in general to bias relative risk estimates away from the null, with underestimates of e having the opposite effect. Although e is unknown, it may be estimated from an external “validation” study, such as genotyping a sample of unrelated individuals twice and counting the discrepancies. Simulation results suggest that, for such a study, 25 individuals would be sufficient to give approximately unbiased estimates of relative risks.     

Minimal genetic influences on plasma fibrinogen level in adult males in the NHLBI twin study

Plasma fibrinogen was determined in 189 twins participating at the Indiana center during the third examination of the NHLBI twin study with a mean age of 63 years. Moderate heritability estimates were obtained from 44 complete MZ pairs and 39 complete DZ pairs. After adjustment of fibrinogen levels for age and other confounding variables related to cardiovascular disease risk, the maximum likelihood heritability estimate was only 30% (p = 0.03). Plasma fibrinogen was most strongly associated with smoking and the presence of diabetes. Omitting all subjects with diabetes or cardiovascular disease further reduced the heritability estimates slightly, and most path models including genetic parameters provided no significant improvement in fit over a model determined solely by random environmental effects. Our results are consistent with the environment rather than genetic influences having a greater influence on the level of plasma fibrinogen.     

Detection of common single nucleotide polymorphisms synthesizing quantitative trait association of rarer causal variants

Genome-wide association (GWA) studies have identified hundreds of common (minor allele frequency ≥5%) single nucleotide polymorphisms (SNPs) associated with phenotype traits or diseases, yet causal variants accounting for the association signals have rarely been determined. A question then raised is whether a GWA signal represents an "indirect association" as a proxy of a strongly correlated causal variant with similar frequency, or a "synthetic association" of one or more rarer causal variants in linkage disequilibrium (D' ≈ 1, but r(2) not large); answering the question generally requires extensive resequencing and association analysis. Instead, we propose to test statistically whether a quantitative trait (QT) association of an SNP represents a synthetic association or not by inspecting the QT distribution at each genotype, not requiring the causal variant(s) to be known. We devised two test statistics and assessed the power by mathematical analysis and simulation. Testing the heterogeneity of variance was powerful when low-frequency causal alleles are linked mostly to one SNP allele, while testing the skewness outperformed when the causal alleles are linked evenly to either of the SNP alleles. By testing a statistic combining these two in 5000 individuals, we could detect synthetic association of a GWA signal when causal alleles sum up to 3% in frequency. Such signal only partially explains the heritability contributed by the whole locus. The proposed test is useful for designing fine mapping after studying association of common SNPs exhaustively; we can prioritize which GWA signal and which individuals to be resequenced, and identify the causal variants efficiently.     

Pedigree linkage disequilibrium mapping of quantitative trait loci

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.     

A twin study of aryl hydrocarbon hydroxylase (AHH) inducibility in cultured lymphocytes

Aryl hydrocarbon hydroxylase (AHH) inducibility was studied in cultured lymphocytes from 28 monozygotic (MZ) and 19 dizygotic (DZ) twin pairs. The results indicate that the induced level of AHH activity as well as inducibility (expressed as the ratio between levels in induced and non-induced cells) are inherited. The best (h²) estimate of heritability is 0.7. There was no suggestion that non-induced AHH activity level is an inherited trait. Inducibility of AHH was not normally distributed and the distribution observed in this limited series might even be trimodal. The results of the study appear to confirm previous reports that AHH inducibility is an inherited trait, and do not exclude the possibility that the major part of the variation is controlled by one locus.     

Inhibition of HERG K+ Current and Prolongation of the Guinea-Pig Ventricular Action Potential by 4-Aminopyridine

4-Aminopyridine (4-AP) has been used extensively to study transient outward K⁺ current ( I _TO,1) in cardiac cells and tissues. We report here inhibition by 4-AP of HERG (the human ether-à-go-go -related gene) K⁺ channels expressed in a mammalian cell line, at concentrations relevant to those used to study I _TO,1. Under voltage clamp, whole cell HERG current ( I _HERG) tails following commands to +30 mV were blocked with an IC₅₀ of 4.4 ± 0.5 m m . Development of block was contingent upon HERG channel gating, with a preference for activated over inactivated channels. Treatment with 5 m m 4-AP inhibited peak I _HERG during an applied action potential clamp waveform by ∼59 %. It also significantly prolonged action potentials and inhibited resurgent I _K tails from guinea-pig isolated ventricular myocytes, which lack an I _TO,1. We conclude that by blocking the α-subunit of the I _Kr channel, millimolar concentrations of 4-AP can modulate ventricular repolarisation independently of any action on I _TO,1.     

Bronchial hyperresponsiveness in two populations of Australian schoolchildren. I. Relation to respiratory symptoms and diagnosed asthma

In order to explore the relationship between bronchial hyperresponsiveness (BHR) to inhaled histamine, respiratory symptoms and diagnosed asthma in children, we undertook a cross-sectional study of 2363 Australian schoolchildren aged 8–11 years. The methods used included a self-administered questionnaire to parents, which was shown to have a high degree of repeatability, and a histamine inhalation test to measure bronchial responsiveness (BR). The study showed that 17.9% of children had BHR, defined as a 20% fall in FEV₁ at a provoking dose of histamine (PD₂₀ FEV₁) of less than 7.8 μmol. The distribution of PD₂₀ FEV₁ appeared to be continuous. Most children with PD₂₀ FEV₁ values < 1.0μmol had symptoms of asthma. However, 6.7% of children had BHR without symptoms or a previous diagnosis of asthma and 5.6% had had a diagnosis of asthma but had no BHR. Although there was a good association between BHR and respiratory symptoms, questionnaire data of wheeze and diagnosed asthma do not reflect accurately the level of BHR in the community. We conclude that cross-sectional studies of BR to identify children with BHR probably do not reflect the prevalence of asthma in populations of children. However, the strong association between BHR and symptoms, particularly in children with severe and moderate BHR, suggests that measurements of BR in populations are useful for defining a group of children whose airways behave differently from those of the majority. Prospective studies are needed to define the level of BHR that is associated with important sequelae.     

The Interaction between Beta 2-Microglobulin (ßm) and Purified Class-I Major Histocompatibility (MHC) Antigen

The function of MHC class-I molecules is to sample peptides from the intracellular environment and present them to CD8⁺ cytotoxic T lymphocytes. To understand the molecular details of the assembly (and disassembly) of peptide-ß₂m-class-I complexes a biochemical peptidc-class-I binding assay has been generated recently and this paper reports on a similar assay for the interaction between ß₂m and class I. As a model system human ß₂m binding to mouse class I was used. The assay is strictly biochemical using purified reagents which interact in solution and complex formation is determined by size separation. It is specific and highly sensitive. The observed affinity of the interaction, K_D, is close to 0.4 nw. The rate of association at 37 C is very fasi (the k_a is around 5 × 10⁴/M/s) whereas the dissociation is slow (the k_d is around 8 × 10⁻⁶/s); the ratio of dissociation to association yields a calculated K_D close to the observed value. At 37° C almost all of the purified class I participates in binding of the exogenously offered ß₂m showing that a considerable exchange of the endogenous ß₂m occurs. Finally, it was demonstrated that exogenous ß₂m enhances binding to MHC class-I of short perfectly-matching peplides as well as longer peptides.     

Differentiating population stratification from genotyping error using family data

Identifying population stratification and genotyping error are important for candidate gene association studies using the Transmission Disequilibrium Test (TDT). Although the TDT retains the prespecified Type I error in the presence of population stratification, the test may have decreased power in the presence of population stratification. Genotyping error can also cause the TDT to have an elevated Type I error. Differentiating population stratification from genotyping error remains a challenge for geneticists. Both genotyping error and population stratification can result in an increase in the observed homozygosity of a sample relative to that expected assuming Hardy-Weinberg Equilibrium (HWE). We show that when family data are available, even if a limited number of markers are genotyped, evaluating the markers that show statistically significant deviation from HWE with the Mating Type Distortion Test (MTDT)--a test based on the mating type distribution--can reliably differentiate genotyping error from population stratification. We simulate data based on several models of genotyping error in previously published literature, and show how this method could be used in practice to assist in differentiating population stratification from systematic genotyping error.     

Combined Segregation and Linkage Analysis of Fibrinogen Variability in Israeli Families: Evidence for Two Quantitative-trait Loci, One of Which is Linked to a Functional Variant (−58G > A) in the Promoter of the α-fibrinogen Gene

The association of α‐ and β‐fibrinogen polymorphisms with plasma fibrinogen levels was examined in a sample of 452 family members from 80 Israeli kindreds. The measured genotype analysis indicated that the β‐fibrinogen ?455G > A polymorphism was not associated with fibrinogen levels, while the α‐fibrinogen ?58G > A locus showed a significant association with fibrinogen levels (χ²= 17.7; df = 3; p < 0.001) , with the ?58A allele being associated with higher levels. Segregation analysis in this sample suggested a recessive quantitative‐trait locus (QTL) with a major effect that controlled the sex‐ and age‐adjusted fibrinogen levels. Results from a combined segregation/linkage analysis indicated that a single QTL influencing plasma fibrinogen is in gametic equilibrium with the β‐fibrinogen ?455G > A and α‐fibrinogen ?58G > A polymorphisms. An extended analysis with a two‐QTL model significantly improved the fit of the model (p ≤ 0.001) , and gave support for linkage between the fibrinogen QTL and the α‐fibrinogen polymorphism. In vitro analysis with a DNA fragment containing this variant, linked to a reporter gene, showed 2‐fold higher expression of the A allele compared to the G allele in the liver cell line HepG2, both under basal conditions and after stimulation with interleukin 6. These results demonstrate that two QTLs are jointly involved in determining plasma fibrinogen levels in this sample of families, one of which is located close to a functional variant in the α‐fibrinogen locus.     

Molecular correlates of the M-current in cultured rat hippocampal neurons

M-type K⁺ currents ( I _K(M)) play a key role in regulating neuronal excitability. In sympathetic neurons, M-channels are thought to be composed of a heteromeric assembly of KCNQ2 and KCNQ3 K⁺ channel subunits. Here, we have tried to identify the KCNQ subunits that are involved in the generation of I _K(M) in hippocampal pyramidal neurons cultured from 5- to 7-day-old rats. RT-PCR of either CA1 or CA3 regions revealed the presence of KCNQ2, KCNQ3, KCNQ4 and KCNQ5 subunits. Single-cell PCR of dissociated hippocampal pyramidal neurons gave detectable signals for only KCNQ2, KCNQ3 and KCNQ5; where tested, most also expressed mRNA for the vesicular glutamate transporter VGLUT1. Staining for KCNQ2 and KCNQ5 protein showed punctate fluorescence on both the somata and dendrites of hippocampal neurons. Staining for KCNQ3 was diffusely distributed whereas KCNQ4 was undetectable. In perforated patch recordings, linopirdine, a specific M-channel blocker, fully inhibited I _K(M) with an IC₅₀ of 3.6 ± 1.5 μM. In 70 % of these cells, TEA fully suppressed I _K(M) with an IC₅₀ of 0.7 ± 0.1 m m . In the remaining cells, TEA maximally reduced I _K(M) by only 59.7 ± 5.2 % with an IC₅₀ of 1.4 ± 0.3 m m ; residual I _K(M) was abolished by linopirdine. Our data suggest that KCNQ2, KCNQ3 and KCNQ5 subunits contribute to I _K(M) in these neurons and that the variations in TEA sensitivity may reflect differential expression of KCNQ2, KCNQ3 and KCNQ5 subunits.