Frequency of KLK3 gene deletions in the general population.

Background One of the kallikrein genes ( KLK3) encodes prostate-specific antigen, a key biomarker for prostate cancer. A number of factors, both genetic and non-genetic, determine variation of serum prostate-specific antigen concentrations in the population. We have recently found three KLK3 deletions in individuals with very low prostate-specific antigen concentrations, suggesting a link between abnormally reduced KLK3 expression and deletions of KLK3. Here, we aim to determine the frequency of kallikrein gene 3 deletions in the general population. Methods The frequency of KLK3 deletions in the general population was estimated from the 1958 Birth Cohort sample ( n = 3815) using amplification ratiometry control system. In silico analyses using PennCNV were carried out in the same cohort and in NBS-WTCCC2 in order to provide an independent estimation of the frequency of KLK3 deletions in the general population. Results Amplification ratiometry control system results from the 1958 cohort indicated a frequency of KLK3 deletions of 0.81% (3.98% following a less stringent calling criterion). From in silico analyses, we found that potential deletions harbouring the KLK3 gene occurred at rates of 2.13% (1958 Cohort, n = 2867) and 0.99% (NBS-WTCCC2, n = 2737), respectively. These results are in good agreement with our in vitro experiments. All deletions found were in heterozygosis. Conclusions We conclude that a number of individuals from the general population present KLK3 deletions in heterozygosis. Further studies are required in order to know if interpretation of low serum prostate-specific antigen concentrations in individuals with KLK3 deletions may offer false-negative assurances with consequences for prostate cancer screening, diagnosis and monitoring.

Combined analysis of CHRNA5, CHRNA3 and CYP2A6 in relation to adolescent smoking behaviour.

CYP2A6 influences smoking uptake in adolescence. Genetic variation in the CHRNA5-CHRNA3 region influences smoking behaviour in adults. However, their combined effects on smoking in adolescence have not been tested to date. We present data on 1450 adolescents from the Ten Towns Heart Health Study (TTHHS) extensively phenotyped for smoking-related traits during adolescence. Single nucleotide polymorphisms from CHRNA5 and CHRNA3 (previously associated with smoking), were typed in our study population, previously genotyped for CYP2A6. Association analyses between each genotype and both smoking status and behavioural markers of smoking were performed. rs16969968 in CHRNA5 was associated both at 13-15 years and 18 years with current smoking amongst adolescents who had tried smoking (OR = 1.82, CI = 1.10-3.01, p = 0.02 at age 13-15; OR = 2.39, CI = 1.37-4.17, p = 0.002 at age 18). No association was found for rs578776 in CHRNA3. The effects of CHRNA5 and CYP2A6 genotypes in TTHHS appeared to be independent, with each approximately doubling the odds of being a regular smoker by age 18 years. CYP2A6 genotype insufficiency increases adolescent likelihood of being a regular smoker but increases later life quitting likelihood and reduces average consumption. In contrast, CHRNA5 genotype, acting recessively, affects smoking similarly in adolescents and older adults. These contrasting actions, in digenic combination, illustrate behavioural genetic complexity.

Cubic exact solutions for the estimation of pairwise haplotype frequencies: implications for linkage disequilibrium analyses and a web tool 'CubeX'.

BACKGROUND: The frequency of a haplotype comprising one allele at each of two loci can be expressed as a cubic equation (the 'Hill equation'), the solution of which gives that frequency. Most haplotype and linkage disequilibrium analysis programs use iteration-based algorithms which substitute an estimate of haplotype frequency into the equation, producing a new estimate which is repeatedly fed back into the equation until the values converge to a maximum likelihood estimate (expectation-maximisation). RESULTS: We present a program, "CubeX", which calculates the biologically possible exact solution(s) and provides estimated haplotype frequencies, D', r2 and chi2 values for each. CubeX provides a "complete" analysis of haplotype frequencies and linkage disequilibrium for a pair of biallelic markers under situations where sampling variation and genotyping errors distort sample Hardy-Weinberg equilibrium, potentially causing more than one biologically possible solution. We also present an analysis of simulations and real data using the algebraically exact solution, which indicates that under perfect sample Hardy-Weinberg equilibrium there is only one biologically possible solution, but that under other conditions there may be more. CONCLUSION: Our analyses demonstrate that lower allele frequencies, lower sample numbers, population stratification and a possible |D'| value of 1 are particularly susceptible to distortion of sample Hardy-Weinberg equilibrium, which has significant implications for calculation of linkage disequilibrium in small sample sizes (eg HapMap) and rarer alleles (eg paucimorphisms, q < 0.05) that may have particular disease relevance and require improved approaches for meaningful evaluation.