Multiple testing for SNP-SNP interactions

Most genetic diseases are complex, i.e. associated to combinations of SNPs rather than individual SNPs. In the last few years, this topic has often been addressed in terms of SNP-SNP interaction patterns given as expressions linked by logical operators. Methods for multiple testing in high-dimensional settings can be applied when many SNPs are considered simultaneously. However, another less well-known multiple testing problem arises within a fixed subset of SNPs when the logic expression is chosen optimally. In this article, we propose a general asymptotic approach for deriving the distribution of the maximally selected chi-square statistic in various situations. We show how this result can be used for testing logic expressions - in particular SNP-SNP interaction patterns - while controlling for multiple comparisons. Simulations show that our method provides multiple testing adjustment when the logic expression is chosen such as to maximize the statistic. Its benefit is demonstrated through an application to a real dataset from a large population-based study considering allergy and asthma in KORA. An implementation of our method is available from the Comprehensive R Archive Network (CRAN) as R package 'SNPmaxsel'

Temporal Changes in Total Serum Immunoglobulin E Levels in East German Children and the Effect of Potential Predictors

Background: Elevated total serum immunoglobulin E (IgE) levels are a prominent feature of allergic and parasitic diseases. An epidemiologic study was conducted in East German children to describe trends in the development of total serum IgE levels and analyze the impact of potential determinants. Methods: The study consisted of three cross-sectional surveys in 1992-1993, 1995-1996 and 1998-1999 and was conducted in three areas of the former German Democratic Republic. In total, 8,051 questionnaires were completed by the parents of children aged 5-14 years, supplying information on allergic symptoms and potential risk factors. A total of 5,918 measurements of total serum IgE and specific IgE to 5 common aeroallergens were available from 4,353 schoolchildren. Generalized estimating equations were applied to data from all children and stratified for atopic and nonatopic children to identify trends and estimate the effect of potential determinants on total IgE. Results: Total serum IgE levels decreased significantly with a linear trend in East German schoolchildren between 1992 and 1999, the effect being stronger in nonatopic children. The following factors were associated with lower total serum IgE levels: female gender, living in a household with fewer than 4 people, no history of helminth infestation, younger age group (5-7 years), no parental allergy and high socioeconomic status. No association was seen for `smoking at home' and close contact to pets. Conclusion: Total serum IgE declined parallel to helminth infestation; however, the latter explained the decrease only in part. Furthermore, total IgE developed in an opposite direction to specific IgE, indicating that it has determinants other than allergic sensitization. Copyright (C) 2011 S. Karger AG, Base

Missing Heritability in the Tails of Quantitative Traits? A Simulation Study on the Impact of Slightly Altered True Genetic Models

Objective: Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. Methods: We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Results: Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Conclusions: Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright (C) 2011 S. Karger AG, Base

Air temperature and inflammatory and coagulation responses in men with coronary or pulmonary disease during the winter season

Background and Objective Air temperature changes are associated with increased cardiovascular and respiratory risk, but the roles of inflammatory and coagulation markers are not well understood. We investigated the associations between temperature and several blood markers in patients with coronary heart disease (CHD) and pulmonary disease (PD). Methods Two studies were conducted in Erfurt, Germany, over two successive winters. 578 and 381 repeated blood measurements were collected from 57 CHD and 38 PD patients, respectively. Data on patient characteristics and disease history were gathered at baseline. Meteorological data were collected from existing networks. Associations were analysed using additive mixed models with random patient effects. Effect modification by diabetes status was investigated only in CHD patients, as only two PD patients had diabetes. Results Mean daily air temperature varied between -13 degrees C and 16 degrees C in both study periods. A 10 degrees C decrease in the 5-day temperature average before blood withdrawal led to an increase in platelet counts (% change from the mean: 3.0%, 95% CI 0.6% to 5.5%) and fibrinogen (5.5%, 1.3% to 9.7%), no change in C-reactive protein in PD patients, and a decrease in C-reactive protein in CHD patients. A 2-day delayed increase in factor VII associated with temperature decrease was seen in CHD patients (4.9%; 0.7% to 9.2%), while PD patients showed no effect. `Effects in CHD patients without diabetes' into `Effects on factor VII in CHD patients without diabetes'. Conclusions This study suggests that temperature decrease is associated with change in several blood parameters. The complex interplay of blood markers at low temperature may contribute to the observed association between cold and cardiovascular mortality and morbidity

Reference values of impulse oscillometric lung function indices in adults of advanced age.

Impulse oscillometry (IOS) is a non-demanding lung function test. Its diagnostic use may be particularly useful in patients of advanced age with physical or mental limitations unable to perform spirometry. Only few reference equations are available for Caucasians, none of them covering the old age. Here, we provide reference equations up to advanced age and compare them with currently available equations. IOS was performed in a population-based sample of 1990 subjects, aged 45-91 years, from KORA cohorts (Augsburg, Germany). From those, 397 never-smoking, lung healthy subjects with normal spirometry were identified and sex-specific quantile regression models with age, height and body weight as predictors for respiratory system impedance, resistance, reactance, and other parameters of IOS applied. Women (n = 243) showed higher resistance values than men (n = 154), while reactance at low frequencies (up to 20 Hz) was lower (p<0.05). A significant age dependency was observed for the difference between resistance values at 5 Hz and 20 Hz (R5-R20), the integrated area of low-frequency reactance (AX), and resonant frequency (Fres) in both sexes whereas reactance at 5 Hz (X5) was age dependent only in females. In the healthy subjects (n = 397), mean differences between observed values and predictions for resistance (5 Hz and 20 Hz) and reactance (5 Hz) ranged between -1% and 5% when using the present model. In contrast, differences based on the currently applied equations (Vogel & Smidt 1994) ranged between -34% and 76%. Regarding our equations the indices were beyond the limits of normal in 8.1% to 18.6% of the entire KORA cohort (n = 1990), and in 0.7% to 9.4% with the currently applied equations. Our study provides up-to-date reference equations for IOS in Caucasians aged 45 to 85 years. We suggest the use of the present equations particularly in advanced age in order to detect airway dysfunction

CONAN: copy number variation analysis software for genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.</p> <p>Results</p> <p>CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data.</p> <p>Conclusions</p> <p>CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at <url>http://genepi-conan.i-med.ac.at</url>.</p

Associations between BMI and the FTO Gene Are Age Dependent: Results from the GINI and LISA Birth Cohort Studies up to Age 6 Years

Objective: The association between polymorphisms in intron 1 of the fat mass and obesity associated gene (FTO) and obesity-related traits is one of the most robust associations reported for complex traits and is established both in adults and children. However, little is known about the longitudinal dynamics of these polymorphisms on body mass index (BMI), overweight, and obesity. Methods: This study is based on the 2,732 full-term neonates of the German GINI-plus and LISA-plus birth cohorts, for whom genotyping data on the FTO variants rs1558902 (T>A) or rs9935401 (G>A) were available. Children were followed from birth up to age 6 years. Up to 9 anthropometric measurements of BMI were obtained. Fractional-Polynomial-Generalized-Estimation-Equation modeling was used to assess developmental trends and their potential dependence on genotype status. Results: We observed no evidence for BMI differences between genotypes of both variants for the first 3 years of life. However, from age 3 years onwards, we noted a higher BMI for the homozygous minor alleles carriers in comparison to the other two genotype groups. However, evidence for statistical significance was reached from the age of 4 years onwards. Conclusions: This is one of the first studies investigating in detail the development of BMI depending on FTO genotype between birth and the age of 6 years in a birth cohort not selected for the phenotype studied. We observed that the association between BMI and FTO genotype evolves gradually and becomes descriptively detectable from the age of 3 years onwards

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Population-genetic comparison of the Sorbian isolate population in Germany with the German KORA population using genome-wide SNP arrays

<p>Abstract</p> <p>Background</p> <p>The Sorbs are an ethnic minority in Germany with putative genetic isolation, making the population interesting for disease mapping. A sample of N = 977 Sorbs is currently analysed in several genome-wide meta-analyses. Since genetic differences between populations are a major confounding factor in genetic meta-analyses, we compare the Sorbs with the German outbred population of the KORA F3 study (N = 1644) and other publically available European HapMap populations by population genetic means. We also aim to separate effects of over-sampling of families in the Sorbs sample from effects of genetic isolation and compare the power of genetic association studies between the samples.</p> <p>Results</p> <p>The degree of relatedness was significantly higher in the Sorbs. Principal components analysis revealed a west to east clustering of KORA individuals born in Germany, KORA individuals born in Poland or Czech Republic, Half-Sorbs (less than four Sorbian grandparents) and Full-Sorbs. The Sorbs cluster is nearest to the cluster of KORA individuals born in Poland. The number of rare SNPs is significantly higher in the Sorbs sample. FST between KORA and Sorbs is an order of magnitude higher than between different regions in Germany. Compared to the other populations, Sorbs show a higher proportion of individuals with runs of homozygosity between 2.5 Mb and 5 Mb. Linkage disequilibrium (LD) at longer range is also slightly increased but this has no effect on the power of association studies.</p> <p>Oversampling of families in the Sorbs sample causes detectable bias regarding higher FST values and higher LD but the effect is an order of magnitude smaller than the observed differences between KORA and Sorbs. Relatedness in the Sorbs also influenced the power of uncorrected association analyses.</p> <p>Conclusions</p> <p>Sorbs show signs of genetic isolation which cannot be explained by over-sampling of relatives, but the effects are moderate in size. The Slavonic origin of the Sorbs is still genetically detectable.</p> <p>Regarding LD structure, a clear advantage for genome-wide association studies cannot be deduced. The significant amount of cryptic relatedness in the Sorbs sample results in inflated variances of Beta-estimators which should be considered in genetic association analyses.</p