Selection and subsequent analysis of sib pair data for QTL detection.

Haseman and Elston (1972) developed a robust regression method for the detection of linkage between a marker and a quantitative trait locus (QTL) using sib pair data. The principle underlying this method is that the difference in phenotypes between pairs of sibs becomes larger as they share a decreasing number of alleles at a particular QTL identical by descent (IBD) from their parents. In this case, phenotypically very different sibs will also on average share a proportion of alleles IBD at any marker linked to the QTL that is lower than the expected value of 0.5. Thus, the deviation of the proportion of marker alleles IBD from the expected value in pairs of sibs selected to be phenotypically different (i.e. discordant) can provide a test for the presence of a QTL. A simple regression method for QTL detection in sib pairs selected for high phenotypic differences is presented here. The power of the analytical method was found to be greater than the power obtained using the standard analysis when samples of sib pairs with high phenotypic differences were used. However, the use of discordant sib pairs was found to be less powerful for QTL detection than alternative selective genotyping schemes based on the phenotypic values of the sibs except with intense selection, when its advantage was only marginal. The most effective selection scheme overall was the use of sib pairs from entire families selected on the basis of high within-family variance for the trait in question. There is little effect of selection on QTL position estimates, which are in good agreement with the simulated values. However, QTL variance estimates are biased to a greater or lesser degree, depending on the selection method.     

Birthweight discordance in multiple pregnancy.

This paper reviews several aspects of discordant growth in multiple pregnancies. Discordant growth is not a chance event and therefore several patterns can be discerned. About 75% of twins exhibit < 15% discordance (concordant), 20% are 15-25% (mildly) discordant, and about 5% are more than 25% (severely) discordant. Higher frequencies and increased severity are seen among triplets. Five observations regarding discordance became generally accepted: (a) not all discordant pairs are similar; (b) the larger the discordance level the greater is the risk for an adverse outcome; (c) discordant growth does not necessarily represent growth restriction; (d) a discordance level may have a different clinical implication in different gestational ages; and (e) the smaller fetuses in severely discordant pairs are at disproportionate risk for neonatal mortality. Mild discordance may represent a normal variation between sibs whereas severely discordant pairs often exhibit patterns of growth restriction. Not infrequently, discordance may represent an adaptation to the limited intrauterine space in order to increase gestational age.     

Mapping quantitative trait loci with extreme discordant sib pairs: sampling considerations.

Elsewhere we have proposed the use of extreme discordant sib pairs (EDSPs) for mapping quantitative trait loci in humans. Here we present sample sizes necessary to achieve a given level of power with this study design, as well as the number of sibs that need to be screened to obtain the required sample. Further, we present simple formulas for adjusting sample sizes to account for variable significance levels and power, as well as the density and informativeness of linkage markers in a multipoint sib-pair analysis. We conclude that with EDSPs, the most powerful study design, the smallest genetic effect detectable with a realistic sample size is approximately 10% of the variance of the trait.     

Search for retroviral related DNA polymorphisms using RAPD PCR in schizophrenia

Random amplification of polymorphic DNA (RAPD) is widely used to detect polymorphisms in many organisms. Individual (or strain) specific amplified bands are generated with single or pairs of primers in PCR reactions and can serve as genetic markers. We have used this method to generate a large number of reproducible bands with single primers, random and retroviral related, on 92 human DNA samples. Theoretically, RAPD PCR presents a logical approach for assessing variability among individuals. We used ten retroviral related primers (12, 20 and 22 bp) and eight random primers (10 bp) to assess individual differences in the context of testing the retroviral hypothesis for schizophrenia. Three pairs of discordant monozygotic twins, four pairs of discordant full sibs and 53 schizophrenic individuals with 25 of their unrelated matched controls were analyzed. Ten of these primers resulted in a total of approx. 850 amplified bands (65-110 bands per primer). Almost all of these bands were identical among each individual analyzed. However, the results are inconclusive with respect to the retroviral hypothesis for schizophrenia. The general lack of RAPD polymorphism in this study may argue for mechanisms other than rearrangements such as inversions, associated with the evolution of the human genome.     

Composite statistics for QTL mapping with moderately discordant sibling pairs

Extreme discordant sibling-pair (EDSP) designs have been shown in theory to be very powerful for mapping quantitative-trait loci (QTLs) in humans. However, their practical applicability has been somewhat limited by the need to phenotype very large populations to find enough pairs that are extremely discordant. In this paper, we demonstrate that there is also substantial power in pairs that are only moderately discordant, and that designs using moderately discordant pairs can yield a more practical balance between phenotyping and genotyping efforts. The power we demonstrate for moderately discordant pairs stems from a new statistical result. Statistical analysis in discordant-pair studies is generally done by testing for reduced identity by descent (IBD) sharing in the pairs. By contrast, the most commonly-used statistical methods for more standard QTL mapping are Haseman-Elston regression and variance-components analysis. Both of these use statistics that are functions of the trait values given IBD information for the pedigree. We show that IBD sharing statistics and "trait value given IBD" statistics contribute complementary rather than redundant information, and thus that statistics of the two types can be combined to form more powerful tests of linkage. We propose a simple composite statistic, and test it with simulation studies. The simulation results show that our composite statistic increases power only minimally for extremely discordant pairs. However, it boosts the power of moderately discordant pairs substantially and makes them a very practical alternative. Our composite statistic is straightforward to calculate with existing software; we give a practical example of its use by applying it to a Genetic Analysis Workshop (GAW) data set.     

Mapping quantitative-trait loci in humans by use of extreme concordant sib pairs: selected sampling by parental phenotypes.

In two previous articles, we have considered sample sizes required to detect linkage for mapping quantitative-trait loci in humans, using extreme discordant sib pairs. Here, we examine further the use of extreme concordant sib pairs but consider the effect of parents' phenotypes. Sample sizes necessary to obtain a power of 80% with concordant sib pairs at a significance level of .0001 are given, stratified by parental phenotypes. When there is no residual correlation between sibs, the parental phenotypes have little impact on the sample sizes. When residual correlations between sibs exist, we show, however, that power can be considerably reduced by including extreme sib pairs when the parents also have similarly extreme values. Thus, we recommend the exclusion of such pairs from linkage studies. This recommendation reduces the required sample sizes by 3- to 28-fold. The degree of saving in the required sample sizes varies among different models and allele frequencies. The reduction is most dramatic (a 28-fold reduction) for a rare recessive gene.     

Recent advances in human quantitative-trait-locus mapping: comparison of methods for discordant sibling pairs

Extreme discordant sibling pairs (EDSPs) are theoretically powerful for the mapping of quantitative-trait loci (QTLs) in humans. EDSPs have not been used much in practice, however, because of the need to screen very large populations to find enough pairs that are extreme and discordant. Given appropriate statistical methods, another alternative is to use moderately discordant sibling pairs (MDSPs)--pairs that are discordant but not at the far extremes of the distribution. Such pairs can be powerful yet far easier to collect than extreme discordant pairs. Recent work on statistical methods for QTL mapping in humans has included a number of methods that, though not developed specifically for discordant pairs, may well be powerful for MDSPs and possibly even EDSPs. In the present article, we survey the new statistics and discuss their applicability to discordant pairs. We then use simulation to study the type I error and the power of various statistics for EDSPs and for MDSPs. We conclude that the best statistic(s) for discordant pairs (moderate or extreme) is (are) to be found among the new statistics. We suggest that the new statistics are appropriate for many other designs as well-and that, in fact, they open the way for the exploration of entirely novel designs.     

The power to detect linkage disequilibrium with quantitative traits in selected samples

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.     

Combining disease models to test for gene-environment interaction in nuclear families

It is useful to have robust gene-environment interaction tests that can utilize a variety of family structures in an efficient way. This article focuses on tests for gene-environment interaction in the presence of main genetic and environmental effects. The objective is to develop powerful tests that can combine trio data with parental genotypes and discordant sibships when parents' genotypes are missing. We first make a modest improvement on a method for discordant sibs (discordant on phenotype), but the approach does not allow one to use families when all offspring are affected, e.g., trios. We then make a modest improvement on a Mendelian transmission-based approach that is inefficient when discordant sibs are available, but can be applied to any nuclear family. Finally, we propose a hybrid approach that utilizes the most efficient method for a specific family type, then combines over families. We utilize this hybrid approach to analyze a chronic obstructive pulmonary disorder dataset to test for gene-environment interaction in the Serpine2 gene with smoking. The methods are freely available in the R package fbati.     

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.     

A linkage strategy for detection of human quantitative-trait loci. II. Optimization of study designs based on extreme sib pairs and generalized relative risk ratios.

We are concerned here with practical issues in the application of extreme sib-pair (ESP) methods to quantitative traits. Two important factors-namely, the way extreme trait values are defined and the proportions in which different types of ESPs are pooled, in the analysis-are shown to determine the power and the cost effectiveness of a study design. We found that, in general, combining reasonable numbers of both extremely discordant and extremely concordant sib pairs that were available in the sample is more powerful and more cost effective than pursuing only a single type of ESP. We also found that dividing trait values with a less extreme threshold at one end or at both ends of the trait distribution leads to more cost-effective designs. The notion of generalized relative risk ratios (the lambda methods, as described in the first part of this series of two articles) is used to calculate the power and sample size for various choices of polychotomization of trait values and for the combination of different types of ESPs. A balance then can be struck among these choices, to attain an optimum design.     

A Discordant-Sibship Test for Disequilibrium and Linkage: No Need for Parental Data

The sibship disequilibrium test (SDT) is designed to detect both linkage in the presence of association and association in the presence of linkage (linkage disequilibrium). The test does not require parental data but requires discordant sibships with at least one affected and one unaffected sibling. The SDT has many desirable properties: it uses all the siblings in the sibship; it remains valid if there are misclassifications of the affectation status; it does not detect spurious associations due to population stratification; asymptotically it has a chi2 distribution under the null hypothesis; and exact P values can be easily computed for a biallelic marker. We show how to extend the SDT to markers with multiple alleles and how to combine families with parents and data from discordant sibships. We discuss the power of the test by presenting sample-size calculations involving a complex disease model, and we present formulas for the asymptotic relative efficiency (which is approximately the ratio of sample sizes) between SDT and the transmission/disequilibrium test (TDT) for special family structures. For sib pairs, we compare the SDT to a test proposed both by Curtis and, independently, by Spielman and Ewens. We show that, for discordant sib pairs, the SDT has good power for testing linkage disequilibrium relative both to Curtis''s tests and to the TDT using trios comprising an affected sib and its parents. With additional sibs, we show that the SDT can be more powerful than the TDT for testing linkage disequilibrium, especially for disease prevalence >.3.     

Cost-effective sib-pair designs in the mapping of quantitative-trait loci.

The extreme discordant-sib-pair design has been found to be the most powerful, across most genetic models. In this paper, we address two of the most frequently asked questions related to this design. First, under the extreme discordant-sib-pair design, a large number of people have to be screened for the phenotype of interest, before the desired number of discordant sibs can be collected for genotyping and linkage analysis. When the phenotyping cost is not negligible compared with the genotyping cost, such methods might not be cost effective. The second question is how sensitive the cost is to the genetic model and allele frequency. In this paper, we compare the cost under different sampling strategies, different genetic models, and different phenotyping:genotyping cost ratios. Because our knowledge of the underlying genetic model for a trait is limited, the discordant-sib-pair design proves to be the most robust. When the cost for screening probands is not included, the design that genotypes sibs with one sib in the top 10% and the other sib in the bottom 30% of the population with respect to the trait of interest is, across most models studied, the optimum among the designs considered in this paper. The cost under this design, across different genetic models, appears to be relatively robust to allele frequency and model type, whether additive or dominant. If probands initially must be screened as well, then 25% appears to be the optimal portions of the upper and lower distributions to be studied.     

Optimal designs for linkage disequilibrium mapping and candidate gene association tests in livestock populations

Simulation was used to evaluate the performance of different selective genotyping strategies when using linkage disequilibrium across large half-sib families to position a QTL within a previously defined genomic region. Strategies examined included standard selective genotyping and different approaches of discordant and concordant sib selection applied to arbitrary or selected families. Strategies were compared as a function of effect and frequency of QTL alleles, heritability, and phenotypic expression of the trait. Large half-sib families were simulated for 100 generations and 2% of the population was genotyped in the final generation. Simple ANOVA was applied and the marker with the greatest F-value was considered the most likely QTL position. For traits with continuous phenotypes, genotyping the most divergent pairs of half-sibs from all families was the best strategy in general, but standard selective genotyping was somewhat more precise when heritability was low. When the phenotype was distributed in ordered categories, discordant sib selection was the optimal approach for positioning QTL for traits with high heritability and concordant sib selection was the best approach when genetic effects were small. Genotyping of a few selected sibs from many families was generally more efficient than genotyping many individuals from a few highly selected sires.     

Notes on Testing Equality in Dichotomous Data with Matched Pairs

In attempting to improve the efficiency of McNemar's test statistic, we develop two test procedures that account for the information on both the discordant and concordant pairs for testing equality between two comparison groups in dichotomous data with matched pairs. Furthermore, we derive a test procedure derived from one of the most commonly‐used interval estimators for odds ratio. We compare these procedures with those using McNemar's test, McNemar's test with the continuity correction, and the exact test with respect to type I error and power in a variety of situations. We note that the test procedures using McNemar's test with the continuity correction and the exact test can be quite conservative and hence lose much efficiency, while the test procedure using McNemar's test can actually perform well even when the expected number of discordant pairs is small. We also find that the two test procedures, which incorporate the information on all matched pairs into hypothesis testing, may slightly improve the power of using McNemar's test without essentially losing the precision of type I error. On the other hand, the test procedure derived from an interval estimator of adds ratio with use of the logarithmic transformation may have type I error much larger than the nominal α‐level when the expected number of discordant pairs is not large and therefore, is not recommended for general use.     

Intrauterine growth restriction in like-sex twins discordant for structural defects

BACKGROUND: An increased risk for intrauterine growth restriction in the affected member of like-sex twin pairs discordant for hypospadias has been reported. The purpose of this study was to document patterns of birth weight disparities in like-sex twins discordant for a variety of structural defects in order to determine if this is a general phenomenon seen in twins who are discordant for any malformation, is seen only in pairs discordant for certain specific malformations, or is unique to hypospadias. METHODS: Data were extracted from the Latin American Collaborative Study of Congenital Malformations (ECLAMC). Between 1967 and 1999, all like-sex twin pairs discordant for hypospadias or any other isolated defect that met the criteria of at least 5 discordant pairs for which birth weight was available on both twins were selected. All nonmalformed like-sex twin pairs in the ECLAMC data base collected over the same study years were selected as controls. RESULTS: A total of 216 discordant malformed like-sex twin pairs in 13 defect categories and 328 nonmalformed like-sex twin pairs met the criteria for inclusion. The proportion of affected infants who were > or =20% smaller than their co-twin was statistically significantly different from controls for hypospadias, heart defects, anencephaly, and esophageal atresia. CONCLUSIONS: Intrauterine growth restriction seen in the affected member of like-sex twin pairs discordant for hypospadias is not unique, but occurs as well in at least 3 additional structural malformations.     

Epigenetic signature of birth weight discordance in adult twins

Background

A low birth weight has been extensively related to poor adult health outcomes. Birth weight can be seen as a proxy for environmental conditions during prenatal development. Identical twin pairs discordant for birth weight provide an extraordinary model for investigating the association between birth weight and adult life health while controlling for not only genetics but also postnatal rearing environment. We performed an epigenome-wide profiling on blood samples from 150 pairs of adult monozygotic twins discordant for birth weight to look for molecular evidence of epigenetic signatures in association with birth weight discordance.

Results

Our association analysis revealed no CpG site with genome-wide statistical significance (FDR < 0.05) for either qualitative (larger or smaller) or quantitative discordance in birth weight. Even with selected samples of extremely birth weight discordant twin pairs, no significant site was found except for 3 CpGs that displayed age-dependent intra-pair differential methylation with FDRs 0.014 (cg26856578, p = 3.42e-08), 0.0256 (cg15122603, p = 1.25e-07) and 0.0258 (cg16636641, p = 2.05e-07). Among the three sites, intra-pair differential methylation increased with age for cg26856578 but decreased with age for cg15122603 and cg16636641. There was no genome-wide statistical significance for sex-dependent effects on intra-pair differential methylation in either the whole samples or the extremely discordant twins.

Conclusions

Genome-wide DNA methylation profiling did not reveal epigenetic signatures of birth weight discordance although some sites displayed age-dependent intra-pair differential methylation in the extremely discordant twin pairs.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1062) contains supplementary material, which is available to authorized users.     

Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism

Several theoretical studies have suggested that large samples of randomly ascertained siblings can be used to ascertain phenotypically extreme individuals and thereby increase power to detect genetic linkage in complex traits. Here, we report a genetic linkage scan using extremely discordant and concordant sibling pairs, selected from 34,580 sibling pairs in the southwest of England who completed a personality questionnaire. We performed a genomewide scan for quantitative-trait loci (QTLs) that influence variation in the personality trait of neuroticism, or emotional stability, and we established genomewide empirical significance thresholds by simulation. The maximum pointwise P values, expressed as the negative logarithm (base 10), were found on 1q (3.95), 4q (3.84), 7p (3.90), 12q (4.74), and 13q (3.81). These five loci met or exceeded the 5% genomewide significance threshold of 3.8 (negative logarithm of the P value). QTLs on chromosomes 1, 12, and 13 are likely to be female specific. One locus, on chromosome 1, is syntenic with that reported from QTL mapping of rodent emotionality, an animal model of neuroticism, suggesting that some animal and human QTLs influencing emotional stability may be homologous.     

Linkage analysis of quantitative trait loci: sib pairs or sibships?

Sib pair linkage studies are now widely used to investigate the genetic factors implicated in complex quantitative traits. To increase the power of these approaches, it has been proposed to select extremely discordant (ED) sib pairs which are expected to contain the highest linkage information. However, it is known that sibships of larger size contain more linkage information than independent sib pairs. In this paper we compare, in terms of power and cost considerations, the ED strategy, which uses information on sib pairs only, to the recently developed 'Maximum Likelihood Binomial' sibship-oriented method performed on the whole sibships from which the ED sib pairs have been extracted. We show that the use of these whole sibships is an efficient alternative to approaches focusing on ED sib pairs only.