Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Variance components analyses of multiple asthma traits in a large sample of Australian families ascertained through a twin proband

Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.

A major quantitative trait locus for CD4-CD8 ratio is located on chromosome 11

CD4-CD8 ratio is an important diagnostic measure of immune system functioning. In particular, CD4-CD8 ratio predicts the time taken for progression of HIV infection to acquired immune deficiency syndrome (AIDS) and the long-term survival of AIDS patients. To map genes that regulate differences between healthy individuals in CD4-CD8 ratio, we typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 cM across the genome in 405 pairs of dizygotic twins at ages 12, 14 and 16. We used multipoint variance components linkage analysis to test for linkage between marker loci and CD4-CD8 ratio at each age. We found suggestive evidence of linkage on chromosome 11p in 12-year-old twins (LOD=2.55, P=0.00031) and even stronger evidence of linkage in the same region at age 14 (LOD 3.51, P=0.00003). Possible candidate genes include CD5 and CD6, which encode cell membrane proteins involved in the positive selection of thymocytes. We also found suggestive evidence of linkage at other areas of the genome including regions on chromosomes 1, 3, 4, 5, 6, 12, 13, 15, 17 and 22.

Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

A genome scan for eye color in 502 twin families: Most variation is due to a QTL on chromosome 15q

We have rated eye color on a 3-point scale (1=blue/grey, 2=hazel/green, 3=brown) in 502 twin families and carried out a 5-10 cM genome scan (400-757 markers). We analyzed eye color as a threshold trait and performed multipoint sib pair linkage analysis using variance components analysis in Mx. A lod of 19.2 was found at the marker D15S1002, less than 1 cM from OCA2, which has been previously implicated in eye color variation. We estimate that 74% of variance in eye color liability is due to this QTL and a further 18% due to polygenic effects. However, a large shoulder on this peak suggests that other loci affecting eye color may be telomeric of OCA2 and inflating the QTL estimate. No other peaks reached genome-wide significance, although lods >2 were seen on 5p and 14q and lods >1 were additionally seen on chromosomes 2, 3, 6, 7, 8, 9, 17 and 18. Most of these secondary peaks were reduced or eliminated when we repeated the scan as a two locus analysis with the 15q linkage included, although this does not necessarily exclude them as false positives. We also estimated the interaction between the 15q QTL and the other marker locus but there was only minor evidence for additive x additive epistasis. Elaborating the analysis to the full two-locus model including non-additive main effects and interactions did not strengthen the evidence for epistasis. We conclude that most variation in eye color in Europeans is due to polymorphism in OCA2 but that there may be modifiers at several other loci.

Exploring the Etiology of the Association Between Birthweight and IQ in an Adolescent Twin Sample

The negative effects of very low birthweight on intellectual development have been well documented, and more recently this effect has been shown to generalise to birthweights within the normal range. In this study we investigate the etiology of this relationship by using a classical twin design to disentangle the contributions of genes and environment. A previous Dutch study (Boomsma et al., 2001) examining these effects indicated that genes were important in mediating the association of birthweight to full IQ measured at ages 7 and 10, but not at ages 5 and 12. Here the association between birthweight and IQ at age 16 is considered (N = 523 twin pairs). Using variance components modeling we found that the genetic variance in birthweight (4%) completely overlapped with that in verbal IQ but not performance or full IQ. Results further showed the importance of shared environmental effects on birthweight (similar to 60%) but not on IQ (with genes explaining up to 72% of IQ variance). Models incorporating a direction of causation parameter between birthweight and IQ provided adequate fit to the data in either causal direction for performance and full IQ, but the model with verbal 10 causing birthweight was preferred to one in which birthweight influenced verbal IQ. As the measurement of birthweight precedes the measurement of twins' IQ at age 16, the influence of verbal IQ might be better considered as a proxy for parents' 10 or education, and it is possible that brighter mothers provide better prenatal environments for their children.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Major quantitative trait locus for eosinophil count is located on chromosome 2q

Background: Eosinophils are granulocytic white blood cells implicated in asthma and atopic disease. The degree of eosinophilia in the blood of patients with asthma correlates with the severity of asthmatic symptoms. Quantitative trait loci (QTL) linkage analysis of eosinophil count may be a more powerful strategy of mapping genes involved in asthma than linkage analysis using affected relative pairs. 1 Objective: To identify QTLs responsible for variation in eosinophil count in adolescent twins. Methods: We measured eosinophil count longitudinally in 738 pairs of twins at 12, 14, and 16 years of age. We typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 centimorgans across the genome. We then used multipoint variance components linkage analysis to test for linkage between marker loci and eosinophil concentrations at each age across the genome. Results: We found highly significant linkage on chromosome 2q33 in 12-year-old twins (logarithm of the odds = 4.6; P = .000002) and suggestive evidence of linkage in the same region in 14-year-olds (logarithm of the odds = 1.0; P = .016). We also found suggestive evidence of linkage at other areas of the genome, including regions on chromosomes 2, 3, 4, 8, 9, 11, 12, 17, 20, and 22. Conclusion: A QTL for eosinophil count is present on chromosome 2q33. This QTL might represent a gene involved in asthma pathophysiology.

Effect of environment and genotype on bread-making quality of spring-sown spring wheat cultivars in China

Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

Phylogeography of the scarab beetle Antitrogus parvulus Britton (Coleoptera : Scarabaeidae) in south-eastern Queensland, Australia

This study surveys the population genetic structure of Childers canegrub, Antitrogus parvulus, to elucidate its population dynamics and gene flow. Antitrogus parvulus is a pest of sugarcane in the Bundaberg region and this knowledge can be used to optimise integrated pest management practices. Here, base-pair differences in the cytochrome oxidase II gene (COII) were used to characterise haplotypic diversity, infer levels of gene flow, and phylogenetic relationships of alleles and their phylogeographical structure. There were 28 unique haplotypes among the 70 sequenced individuals from the seven locations. All three variance components (among regions, among populations, within populations) are highly significant, with highest genetic diversity among regions and lowest among populations within regions. A positive correlation between migration rates and geographical distance and significant phylogeographical structure between four main geographical regions. The main implication of these findings for pest management is that if a grower can eliminate an existing infestation within a field, then reinvasion will be slow and further outbreaks within that field are unlikely to occur. The low dispersal ability of females also means that any resistance to insecticides that develops is likely to remain localised, but will rapidly become dominant within the affected population.

A genome scan for epidermal skin pattern in adolescent twins reveals suggestive linkage on 12p13.31

Deterioration in stratum corneum reticular patterning (skin pattern or skin wrinkling) has been associated with increased rates of solar keratoses and skin cancer. A previous analysis of data from the twin sample used in this investigation has shown that 86% of the variation in skin pattern is genetic at age 12 and 62% in an adult sample (mean age 47.5). Variation due to genetic influences is likely to be influenced by more than one locus. Here, we present results of a genome-wide linkage scan of skin pattern in adolescent twins and siblings from 428 nuclear twin families. Sib-pair linkage analysis was performed on skin pattern data collected from twins at age 12 (378 informative families) and 14 (316 families). Suggestive linkage was found at marker D12S397 (12p13.31, logarithm of the odds (lod) 1.94), when the effect of the trait locus was modelled to influence the skin pattern equally at both ages 12 and 14. In the same analysis, a peak was seen at 4q23 with a lod score of 1.55. A possible candidate for the peak at 12p13.31 is the protease inhibitor, alpha-2-macroglobulin.

Genome-wide scan of IQ finds significant linkage to a quantitative trait locus on 2q

A genome-wide linkage scan of 795 microsatellite markers (761 autosomal, 34 X chromosome) was performed on Multidimensional Aptitude Battery subtests and verbal, performance and full scale scores, the WAIS-R Digit Symbol subtest, and two word-recognition tests (Schonell Graded Word Reading Test, Cambridge Contextual Reading Test) highly predictive of IQ. The sample included 361 families comprising 2-5 siblings who ranged in age from 15.7 to 22.2 years; genotype, but not phenotype, data were available for 81% of parents. A variance components analysis which controlled for age and sex effects showed significant linkage for the Cambridge reading test and performance IQ to the same region on chromosome 2, with respective LOD scores of 4.15 and 3.68. Suggestive linkage (LOD score > 2.2) for various measures was further supported on chromosomes 6, 7, 11, 14, 21 and 22. Where location of linkage peaks converged for IQ subtests within the same scale, the overall scale score provided increased evidence for linkage to that region over any individual subtest. Association studies of candidate genes, particularly those involved in neural transmission and development, will be directed to genes located under the linkage peaks identified in this study.

Familial aggregation of human infection with Schistosoma japonicum in the Poyang Lake region, China

Despite the success of extensive control measures that have been implemented in China for over 50 years, the number of individuals infected with Schistosoma japonicum remains high in the existing endemic areas. A variance components analysis was undertaken to estimate the heritable and environmental components that contribute to S. japonicum infection in the Poyang Lake region of Jiangxi Province, PR China. The total target population was 3148 from four separate administrative villages. Two thousand seven hundred and five of these comprised 400 families ranging in size from 3 to 188. After adjustments were made for gender, water contact and past history of having had schistosomiasis, the heritable component was estimated to account for as much as 58% of the phenotype variation under the polygenic model. Household was not shown to be an important environmental factor. Incorporating village effects indicated that the results were valid for the total population. We conclude that genetic heritability in this region is high and plays an important role in determining risk of infection with S. japonicum. (c) 2005 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.