Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis

Most multipoint linkage programs assume linkage equilibrium among the markers being studied. The assumption is appropriate for the study of sparsely spaced markers with intermarker distances exceeding a few centimorgans, because linkage equilibrium is expected over these intervals for almost all populations. However, with recent advancements in high-throughput genotyping technology, much denser markers are available, and linkage disequilibrium (LD) may exist among the markers. Applying linkage analyses that assume linkage equilibrium to dense markers may lead to bias. Here, we demonstrated that, when some or all of the parental genotypes are missing, assuming linkage equilibrium among tightly linked markers where strong LD exists can cause apparent oversharing of multipoint identity by descent (IBD) between sib pairs and false-positive evidence for multipoint model-free linkage analysis of affected sib pair data. LD can also mimic linkage between a disease locus and multiple tightly linked markers, thus causing false-positive evidence of linkage using parametric models, particularly when heterogeneity LOD score approaches are applied. Bias can be eliminated by inclusion of parental genotype data and can be reduced when additional unaffected siblings are included in the analysis.

Complex segregation analysis reveals a multigene model for lung cancer

Lung cancer risk is largely attributed to tobacco exposure, but genetic predisposition also plays an etiologic role. Several studies have investigated the involvement of genetic predisposition in lung cancer aggregation in affected families, although with inconsistent results. Some studies have provided evidence for Mendelian inheritance, whereas others have suggested that environmental models are most appropriate for lung cancer aggregation in families. To examine the genetic basis of lung cancer, we performed segregation analysis on 14,378 individuals from 1,561 lung cancer case families, allowing for the effects of smoking, sex, and age. Both a Mendelian decreasing model and a Mendelian codominant model were found to be the best fitting models for susceptibility. However, when we modeled age-of-onset, all Mendelian models and the environmental model were rejected suggesting that multiple genetic factors (possibly multiple genetic loci and interactions) contribute to the age-of-onset of lung cancer. The results provide evidence that multiple genetic factors contribute to lung cancer and may act as a guide in further studies to localize susceptibility genes in lung cancer.

Androgen receptor polymorphisms and risk of biochemical failure among prostatectomy patients

BACKGROUND

Little is known about the role of inherited genotypes in prostate cancer (PC) progression. This prospective study evaluated the predictive value of androgen receptor (AR) polymorphisms (CAG and GGC repeats) among prostatectomy patients.

METHODS

We studied 354 patients registered at M. D. Anderson Cancer Center from 1991 to 2001. Kaplan-Meier and Cox proportional hazard analyses were used.

RESULTS

During an average follow-up of 56 months, 66 (19%) post-prostatectomy patients experienced biochemical failure (BF). Patients with higher CAG repeats (CAG > or = 24) had significantly longer BF-free survival (BFFS) than those with fewer repeats (CAG < or = 23) (P = 0.04). Higher CAG repeats were significantly associated with lower BF risk among Whites and African Americans. Among Whites, longer CAG repeats (relative risk (RR) = 0.45, P = 0.03) and Gleason score > or = 8 (RR = 19.33, P = 0.005) remained significant BFFS predictors in multivariate analysis. GGC repeats were not associated with BF.

CONCLUSIONS

Our data showed that an inherited polymorphism (CAG repeats) in the AR is related to differences in genetic susceptibility to BF, supporting the hypothesis that increased AR activity may play a role in PC progression.

Effect of winsorization on power and type 1 error of variance components and related methods of QTL detection

Variance components analysis provides an efficient method for performing linkage analysis for quantitative traits. However, power and type 1 error of variance components-based likelihood ratio testing may be affected when phenotypic data are nonnormally distributed (especially with high values of kurtosis) and there is moderate to high correlation among the siblings. Winsorization can reduce the effect of outliers on statistical analyses. Here, we considered the effect of winsorization on variance components-based tests. We considered the likelihood ratio test (LRT), the Wald test, and some robust variance components tests. We compared these tests with Haseman-Elston least squares-based tests. We found that power to detect linkage is significantly increased after winsorization of the nonnormal phenotypes. Winsorization does not greatly diminish the type 1 error for the variance components-based tests for markedly nonnormal data. A robust version of the LRT that adjusts for sample kurtosis showed the best power for nonnormal data. Finally, phenotype winsorization of nonnormal data reduces the bias in estimation of the major gene variance component.

HER-2 gene amplification can be acquired as breast cancer progresses

Amplification and overexpression of the HER-2 oncogene in breast cancer is felt to be stable over the course of disease and concordant between primary tumor and metastases. Therefore, patients with HER-2-negative primary tumors rarely will receive anti-Her-2 antibody (trastuzumab, Herceptin) therapy. A very sensitive blood test was used to capture circulating tumor cells (CTCs) and evaluate their HER-2 gene status by fluorescence in situ hybridization. The HER-2 status of the primary tumor and corresponding CTCs in 31 patients showed 97% agreement, with no false positives. In 10 patients with HER-2-positive tumors, the HER-2/chromosome enumerator probe 17 ratio in each tumor was about twice that of the corresponding CTCs (mean 6.64 +/- 2.72 vs. 2.8 +/- 0.6). Hence, the ratio of the CTCs is a reliable surrogate marker for the expected high ratio in the primary tumor. Her-2 protein expression of 10 CTCs was sufficient to make a definitive diagnosis of the HER-2 gene status of the whole population of CTCs in 19 patients with recurrent breast cancer. Nine of 24 breast cancer patients whose primary tumor was HER-2-negative each acquired HER-2 gene amplification in their CTCs during cancer progression, i.e., 37.5% (95% confidence interval of 18.8-59.4%). Four of the 9 patients were treated with Herceptin-containing therapy. One had a complete response and 2 had a partial response.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests using the non-transformed, skewed phenotypes, from 7.5 to 20.1% after Winsorizing and from 12.6 to 33.2% after Box-Cox transformation. Likewise, power (adjusted for empirical type 1 error) using leptokurtic phenotypes at the 0.01 alpha level ranged from 4.4 to 12.5% across all tests with no transformation, from 7 to 19.2% after Winsorizing and from 4.5 to 13.8% after Box-Cox transformation. Thus the Box-Cox transformation apparently provided the best type 1 error control and maximal power among the procedures we considered for analyzing a non-normal, skewed distribution (chi2) while Winzorizing worked best for the non-normal, kurtic distribution (Laplace). We repeated the same simulations using a larger sample size (200 sib pairs) and found similar results.

Adding further power to the Haseman and Elston method for detecting linkage in larger sibships: weighting sums and differences

Haseman and Elston (H-E) proposed a robust test to detect linkage between a quantitative trait and a genetic marker. In their method the squared sib-pair trait difference is regressed on the estimated proportion of alleles at a locus shared identical by descent by sib pairs. This method has recently been improved by changing the dependent variable from the squared difference to the mean-corrected product of the sib-pair trait values, a significantly positive regression indicating linkage. Because situations arise in which the original test is more powerful, a further improvement of the H-E method occurs when the dependent variable is changed to a weighted average of the squared sib-pair trait difference and the squared sib-pair mean-corrected trait sum. Here we propose an optimal method of performing this weighting for larger sibships, allowing for the correlation between pairs within a sibship. The optimal weights are inversely proportional to the residual variances obtained from the two different regressions based on the squared sib-pair trait differences and the squared sib-pair mean-corrected trait sums, respectively, allowing for correlations among sib pairs. The proposed method is compared with the existing extension of the H-E approach for larger sibships. Control of the type I error probabilities for sibships of any size can be improved by using a generalized estimating equation approach and the robust sandwich estimate of the variance, or a Monte-Carlo permutation test.

Positional Identification of Microdeletions with Genetic Markers

The positional identification of genetic factors for both simple and complex diseases is difficult. There is increasing evidence that small deletions are a fairly common cause for many genetic diseases and some complex diseases. To date, no statistical basis has been available for the identification of microdeletions in family studies. Here, we present an approach to the identification of novel microdeletions for parent-affected offspring trios. We present several different approaches that can be applied to identify microdeletions and also evaluate the statistical behavior of one of these methods in simulated data. The results show that for the study of single nucleotide polymorphisms, the error rate has an approximately linear effect in decreasing the ability to identify microdeletions. On the other hand, heterogeneity of causation, with only some families showing a microdeletion had a more severe influence upon the ability to identify de novo microdeletions.

The worldwide distribution of the VHL 598C>T mutation indicates a single founding event

The first congenital defect of hypoxia-sensing homozygosity for VHL 598C>T mutation was recently identified in Chuvash polycythemia. Subsequently, we found this mutation in 11 unrelated individuals of diverse ethnic backgrounds. To address the question of whether the VHL 598C>T substitution occurred in a single founder or resulted from recurrent mutational events in human evolution, we performed haplotype analysis of 8 polymorphic markers covering 340 kb spanning the VHL gene on 101 subjects bearing the VHL 598C>T mutation, including 72 homozygotes (61 Chuvash and 11 non-Chuvash) and 29 heterozygotes (11 Chuvash and 18 non-Chuvash), and 447 healthy unrelated individuals from Chuvash and other ethnic groups. The differences in allele frequencies for each of the 8 markers between 447 healthy controls (598C) and 101 subjects bearing the 598T allele (P < 10(-7)) showed strong linkage disequilibrium. Haplotype analysis indicated a founder effect. We conclude that the VHL 598C>T mutation, the most common defect of congenital polycythemia yet found, was spread from a single founder 1,000 to 62,000 years ago.

Uniformly minimum variance unbiased estimation of gene diversity

Gene diversity is an important measure of genetic variability in inbred populations. The survival of species in changing environments depends on, among other factors, the genetic variability of the population. In this communication, I have derived the uniformly minimum variance unbiased estimator of gene diversity. The proposed estimator of gene diversity does not assume that the inbreeding coefficient is known. I have also provided the approximate variance of this estimator according to Fisher's method. In addition, I have developed a numerical resampling-based method for obtaining variances and confidence intervals based on the maximum likelihood estimator and the uniformly minimum variance unbiased estimator. Efficiency in estimation of the gene diversity based on these two estimators is discussed. In accordance with the simulation results, I found that the uniformly minimum variance estimator developed in this report is more accurate for estimation of gene diversity than the maximum likelihood estimator.

Genomic imprinting and linkage test for quantitative-trait Loci in extended pedigrees

Genomic imprinting is a mechanism in which only one of the two copies of a gene is expressed. Some genes that affect development and behavior in mammals are known to be imprinted. Deregulation of imprinted genes has been found in a number of human diseases. Incorporating imprinting information into linkage analysis results in a more powerful test for linkage. Here, we propose an efficient method to test for linkage and imprinting of quantitative traits in extended pedigrees. We compared the results obtained by using the extended-pedigree-analysis approach proposed in this study with other existing approaches. We found that the proposed method is more powerful and uses extended-pedigree information most efficiently.

From genotype to phenotype: correlating XRCC1 polymorphisms with mutagen sensitivity

This study correlated the extent of induced in vitro chromosomal damage, assessed by the mutagen sensitivity assay, with genotypes of the X-ray repair cross complementing group 1 (XRCC1) gene, which encodes for a base excision repair protein. There are two common polymorphisms that cause amino acid substitutions in XRCC1, one at codon 194 in exon 6 and another at codon 399 in exon 10. We genotyped these two polymorphisms in 524 healthy subjects and performed mutagen sensitivity assays using both bleomycin and benzo[a]pyrene-diol-epoxide (BPDE) as challenge mutagens. Our results showed that individuals with the wildtype exon 6 Arg/Arg exhibited significantly higher values of chromosomal breaks per cell (b/c) than those with one or two variant Trp alleles (P=0.005 for bleomycin and P=0.05 for BPDE). For the exon 10 polymorphism, subjects who were Gln/Gln homozygotes had higher b/c than did those with other genotypes, with evidence of a gene dosage effect. When we combined the two polymorphic sites and used the exon 6 Arg/Trp and Trp/Trp and exon 10 Arg/Arg genotypes as the reference category, these differences were enhanced for bleomycin sensitivity (P for trend = 0.032), but not for BPDE sensitivity (P for trend = 0.821). These data are biologically plausible since codon 399 is located within the BRCA1 C-terminus functional domain and codon 194 is in the linker region of the XRCC1 N-terminal functional domain. To our knowledge, this is the largest study conducted evaluating the functional relevance of these polymorphisms.

Genetic linkage and imprinting effects on body mass index in children and young adults

Body mass index (BMI) is used as a measure of fatness. Here we performed a genome-wide scan for genes related to BMI, while allowing for the possible effects of imprinting. We applied a sib pair linkage analysis to a sample of primarily children and young adults by using the Haseman-Elston method, which we modified to model the separate effects of paternally and maternally derived genetic factors. After stratification of sib pairs according to age, a number of regions showing linkage with BMI were identified. Most linkage and imprinting effects were found in children 5-11 years of age. Strongest evidences for linkage in children were found on chromosome 20 at 20p11.2-pter near the marker D20S851 (LOD(Total)=4.08, P=0.000046) and near the marker D20S482 (LOD(Total) =3.55, P=0.00016), and Chromosome 16 at 16p13 near the marker ATA41E04 (LOD(Total) =3.12, P=0.00025), and those loci did not show significant evidence for imprinting. Six regions showing evidence of imprinting were 3p23-p24 (paternal expression), 4q31.1-q32 (maternal expression), 10p14-q11 (paternal expression), and 12p12-pter (paternal expression) in children, and 4q31-qter (paternal expression) and 8p (paternal expression) in adults.

A note on the optimal measure of allelic association

Association of pairs of loci due to departure of gamete frequencies from expected frequencies is called allelic association. This measure is useful for fine-scale mapping. There are several measures of allelic association in the literature. With the availability of a SNP map, the use of linkage disequilibrium to map genes is one of the central issues in the human genome project. The size of linkage disequilibrium blocks is of considerable interest. In this note, we investigate the statistical properties of a measure which is known to have the strongest theoretical population basis and be least sensitive to the marker allele frequencies. In particular, we have shown that this measure has intuitive appeal and the estimator for this measure has several statistically optimal properties such as consistency, asymptotic unbiasedness and asymptotic efficiency.

Improving the power of sib pair quantitative trait loci detection by phenotype winsorization

OBJECTIVES

In sib pair studies, quantitative trait loci (QTL) identification may be adversely affected by non-normality in the phenotypic distribution, particularly when subjects falling in the tails of the distribution bias the trait mean or variance. We evaluated the robustness and power of reducing the influence of subjects with extreme phenotypic values by Winsorizing non-normal distributions in three versions of Haseman-Elston regression-based methods of QTL linkage analysis.

METHODS

Data were simulated for normal and non-normal distributions. Phenotypic values that correspond to cutoff points at the omega and 1 - omega percentiles of the distribution were identified, and phenotypic values falling outside the boundaries of the omega and 1 - omega cutoff points were replaced by the omega and 1 - omega values, respectively. One million replications were performed for the three tests of linkage for Winsorized and non-Winsorized data.

RESULTS

Winsorization reduced conservatism in the tails of the empirical type I error rate for the vast majority of the tests of linkage, increased the power of QTL detection in non-normal data and created a slight negative bias in symmetrical phenotypic distributions.

CONCLUSIONS

Winsorizing can improve the power of QTL detection with certain non-normal distributions but can also introduce bias into the estimate of the QTL effect.

Haplotypes of two variants in p16 (CDKN2/MTS-1/INK4a) exon 3 and risk of squamous cell carcinoma of the head and neck: a case-control study

The frequent loss or promoter methylation of the tumor suppressor gene p16 in head and neck cancer suggests an etiologic role of p16 in this disease. Two adjacent polymorphisms of p16 exon 3, C540G and C580T, were identified recently. C540G is associated with low expression of p53, and both polymorphisms are associated with tumor aggressiveness, suggesting a possible functional relevance. We hypothesized that these two polymorphisms, particularly their haplotypes, are associated with the risk of developing squamous cell carcinoma of the head and neck (SCCHN). To test this hypothesis, we conducted a hospital-based case-control study of 208 patients with SCCHN and 224 cancer-free control subjects to evaluate the association between p16 genotypes/haplotypes and the risk of SCCHN, using a PCR-single strand conformation polymorphism-based genotyping assay. However, our results suggested that no significant differences exist in the distribution of p16 C540G and C580T genotypes between cases and controls. For the C540G polymorphism, the CC, CG, and GG genotype frequencies were 76.9%, 22.1%, and 1.0%, respectively, in the cases, compared with 76.8%, 21.9%, and 1.3%, respectively, for the controls. For the C580T polymorphism, the CC, CT, and TT genotype frequencies were 83.6%, 15.9%, and 0.5%, respectively, in the cases, compared with 82.6%, 16.5%, and 0.9%, respectively, for the controls. The frequencies of three predominant 540C/580C, 540G/580C, and 540C/580T haplotype alleles were distributed similarly in the cases (79.6%, 12.0%, and 8.4%) and in the controls (78.6%, 12.3%, and 9.1%). None of these differences were statistically significant. We conclude that these polymorphic p16 genotypes or haplotypes may not play a major role in the etiology of SCCHN, if any. However, our limited sample size and power call for larger studies for additional verification of our findings.

p53 Genotypes and Haplotypes Associated With Lung Cancer Susceptibility and Ethnicity

BACKGROUND

The p53 tumor suppressor protein is important in cell-cycle control, apoptosis, and DNA repair. Mutations in p53 have been associated with inherited cancer susceptibility. Because there is a difference in the risk of lung cancer among different ethnic groups, we examined associations between ethnicity and three polymorphisms in p53 (one exonic and two intronic) and haplotypes for the three loci and risk of lung cancer. We also examined the functionality of the p53 variants in apoptosis and DNA repair.

METHODS

In a case-control study, we frequency matched (by age, sex, and ethnicity) 635 lung cancer case patients and 635 control subjects. p53 genotypes and haplotypes at the three polymorphic sites were determined by restriction fragment length polymorphism analysis of lymphocyte DNA. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between genotype or haplotype and lung cancer risk were determined by logistic regression analysis. Apoptosis and DNA repair capacity were measured in 22 lymphoblastoid cell lines to determine the functional effects of the polymorphisms. All statistical tests were two-sided.

RESULTS

Genotype and haplotype frequency distributions were strongly dependent on ethnicity; variant allele frequencies were highest in African-Americans (29.1%) and lowest in Mexican-Americans (12.2%). Each of the three polymorphisms was associated with an increased risk of lung cancer among all ethnic groups. Moreover, for all three polymorphisms, increased variant allele copy number was associated with increased risk of lung cancer. Similarly, the variant haplotypes were also associated with an increased risk for lung cancer. Lymphoblastoid cell lines with all wild-type alleles at the three loci had statistically significantly higher apoptotic indices (13.66%, 95% CI = 8.61% to 18.71%) and DNA repair capacity (27.63%, 95% CI = 21.72% to 33.53%) than cell lines with at least one variant allele at all three loci (3.50%, 95% CI = 1.08% to 5.91%; and 17.48%, 95% CI = 7.99% to 26.96%, respectively).

CONCLUSIONS

p53 polymorphisms may be associated with increased lung cancer risk and may affect p53 function.

Adaptations of linkage and association methods for the study of asthma, a complex trait

Early studies that found significant linkage between markers on 5q and asthma and IgE have not been reproduced. In an attempt to improve the power of these studies we performed a variance components linkage analysis and transmission-disequilibrium tests (TDT) with haplotypes using markers on 5q, using the Southampton and Perth data sets supplied by GAW. The linkage analysis with covariates revealed a maximum lod of 1.57 in the Perth families. The addition of age and RAST significantly improved the fit of the null models but did not improve the lod scores. The TDT tests showed a marginally significant association with D5S393 and D5S399 and with three markers together (IL9, IL4, D5S393). We conclude that further studies are needed to delineate the environmental contribution to this disease so that the genetic factors can be more easily identified. In addition, haplotype analysis may help to identify specific genetic effects.

Variance components analysis for genetic linkage of time to onset for disease

We compared two variance components methods for detecting genes that influence time to onset for a complex disease using simulated data. We first divided the extended families into nuclear families. The first method fitted variance components to the martingale residuals, which were obtained from first fitting a proportional hazards model to the time to onset data for the trait, allowing for the quantitative traits Q1-Q5, sex, age, and the environmental factor. The second method treated time to onset among the affected individuals as a quantitative trait adjusting for the same factors as in the first method. Power of these analyses were similar for either approach. However, we found an excess of false-positive results when fitting the martingale residual model or the affected-only model to identify genetic factors linked to chromosome 6. Applying a power transformation to the martingale residuals decreased the type I error rate and increased the power of tests for genetic linkage. We also found that robust variance correction lead to test with a slightly lower type I error rate, perhaps because the robust variance correction adjusts for the fact that we did not specifically model the effects of the mitochondrial factor in our analysis.

Individual-specific liability groups in genetic linkage, with applications to kindreds with Li-Fraumeni syndrome

In this report, we present a simple and powerful way to incorporate individual-specific liability classes into linkage analysis. The proposed method is applicable to both quantitative and qualitative traits. In linkage studies, we may have information about different covariates. Incorporation of these covariates along with the estimates of residual familial effects, age-at-onset effects, and susceptibility in the definition of liability classes can increase the power to detect genetic linkage. In this study, we show how one can form individual-specific liability classes and use these classes in standard linkage-analysis programs, such as the widely used LINKAGE package, to perform more powerful genetic linkage analysis. Our simulation study shows that this approach yields higher LOD scores and more-accurate estimates of the recombination fraction in the families showing linkage. The proposed method is also applied to kindreds collected, at the M. D. Anderson Cancer Center, through probands with childhood soft-tissue sarcoma. Confirmed germ-line mutations in the p53 tumor-suppressor gene have been identified in these families. Application of our method to these families yielded significantly higher LOD scores and more-accurate recombination fractions than did analysis that did not account for individual-specific covariate information.

Testing for genetic linkage in families by a variance-components approach in the presence of genomic imprinting

Some genes that affect development and behavior in mammals are known to be imprinted; and > or = 1% of all mammalian genes are imprinted. Hence, incorporating an imprinting parameter into linkage analysis may increase the power to detect linkage for these traits. Here we propose theoretical justifications for a recently developed model for testing of linkage, in the presence of genetic imprinting, between a quantitative-trait locus and a polymorphic marker; this is achieved in the variance-components framework. We also incorporate sex-specific recombination fractions into this model. We discuss the effects that imprinting and nonimprinting have on the power of the usual variance-components method and on the variance-components method that incorporates an imprinting parameter. We provide noncentrality parameters that can be used to determine the sample size necessary to attain a specified power for a given significance level, which is useful in the planning of a linkage study. Optimal strategies for a genome scan of potentially imprinted traits are discussed.

Modulation of repair of ultraviolet damage in the host-cell reactivation assay by polymorphic XPC and XPD/ERCC2 genotypes

DNA repair capacity (DRC) plays an important role in genetic susceptibility to cancer. Polymorphisms of a number of DNA repair genes involved in several distinct pathways have been identified. However, their effects on repair function have not been well characterized. We demonstrated previously that DRC for removal of benzo[a]pyrene diol epoxide-induced DNA damage measured by a host-cell reactivation assay was modulated by two XPD/ERCC2 polymorphisms in lung cancer. In this report, we investigated the association between the repair phenotype of ultraviolet (UV)-induced damage and genotypes of three DNA repair genes, XPC and XPD [involved in nucleotide excision repair (NER)] and XRCC1 [involved in base excision repair (BER)]. We measured DRC for removal of UV photoproducts by the host-cell reactivation assay in cryopreserved lymphocytes from 102 healthy non-Hispanic white subjects. We also typed these subjects for five polymorphisms in these three DNA repair genes (at intron 9 of XPC; exons 6, 10 and 23 of XPD and exon 10 of XRCC1). Compared with wild-type homozygotes, subjects homozygous for polymorphisms of the two NER genes consistently had suboptimal DRC. The DRC was consistently lower in subjects homozygous for XPC, XPD or both than in subjects with other genotypes, although the difference was not statistically significant for XPD variants. In contrast, the polymorphic allele of the BER gene, XRCC1, had no consistent effect on DRC. We concluded that these NER polymorphisms may modulate DRC and may be useful biomarkers for identifying individuals at risk of developing cancer.

Modulation of nucleotide excision repair capacity by XPD polymorphisms in lung cancer patients

Sequence variations have been identified in a number of DNA repair genes, including XPD, but the effect of these polymorphisms on DNA repair capacity (DRC) is uncertain. We therefore examined XPD polymorphisms at Lys751Gln and Asp312Asn in 341 white lung cancer cases and 360 age-, sex-, ethnicity-, and smoking-matched controls accrued in a hospital-based molecular epidemiological study of susceptibility markers for lung cancer. As previously reported, DRC was statistically significantly lower in the cases than in the controls (7.8% versus 9.5%; P < 0.001), which represents an average 18% reduction among the cases. The variant Lys751Gln and Asp312Asn allele frequencies were 0.36 and 0.29, respectively, for the cases and 0.33 and 0.27, respectively, for the controls. For subjects homozygous for the variant genotype at either locus, the adjusted odds ratio [95% confidence interval (CI)] was 1.84 (1.11-3.04; P = 0.018, for trend). Both cases and controls with the wild-type genotypes exhibited the most proficient DRC. The risk (95% CI) for suboptimal DRC (defined as less than the median DRC value among the controls) was 1.57 (0.74-3.35) for those with the Gln/Gln751 genotype. For cases with the Asn/Asn312 genotype, the risk (95% CI) was 3.50 (1.06-11.59). For cases who were homozygous at either locus, the risk was 2.29 (1.03-5.12; P = 0.048, for trend). The pattern was less evident among the controls, although there was a nonsignificant 41% increase in the risk of suboptimal DRC for controls who were homozygous at either locus. These results suggest that the two XPD polymorphisms have a modulating effect on DRC, especially in the cases.

Syringoma of the vulva

A 12-year old girl presented with asymptomatic multiple skin-colored grouped papules on the vulva. Histopathology revealed features of syringoma.

On estimating the heterozygosity and polymorphism information content value

The polymorphism information content (PIC) value is commonly used in genetics as a measure of polymorphism for a marker locus used in linkage analysis. In this communication we have derived the uniformly minimum variance unbiased estimator of PIC along with its exact variance. We have also calculated the exact variance of the maximum likelihood estimator of PIC which is asymptotically an unbiased estimator. In order to find this variance we have derived a recursive formula to calculate the moments of any polynomial in a set of variables that are multinomially distributed.