Functional polymorphisms in a candidate gene for atherothrombosis: unraveling the complex fabric of a polygenic phenotype.
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Arteriosclerosis↗
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Results for “Multifactorial Inheritance”
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Patterns of recurrence of congenital heart disease: an analysis of 6,640 consecutive pregnancies evaluated by detailed fetal echocardiography.
OBJECTIVES: We sought to investigate the pattern of recurrence of congenital heart disease (CHD) where there is one or more affected first-degree relative. BACKGROUND: There are little data on patterns of recurrence of different types of CHD. Analysis of a fetal series allows a high ascertainment of affected cases. METHODS: We performed an analysis of referrals for detailed fetal echocardiography to a tertiary fetal cardiology unit, where there was a first-degree family history of CHD from 1990 to the end of 1999. Data were entered prospectively on a computerized database. Recurrences were exactly concordant if CHD was identical to the index case, and concordant for the group if belonging to a similar group of CHD. RESULTS: A recurrence of CHD was seen in 178 (2.7%) of 6,640 pregnancies. The referral numbers for sibling, maternal, or paternal CHD cases were 5,151, 1,119, and 370, respectively. Exact concordance was seen in 37% of cases (range 0% to 80%), and group concordance was seen in 44%. In families where there were two or more recurrences, the exact concordance rate was 55%. Exact concordance rates were particularly high for isolated atrioventricular septal defects (4 of 5 [80%]) and laterality defects (7 of 11 [64%]). CONCLUSIONS: The concordance rates of different types of CHD vary widely. Accurate diagnosis of the index case is essential for reliable counseling on patterns of recurrence. Minor CHD in the index case does not exclude more severe disease in recurrences. There appears to be significant under-referral for fetal echocardiography in paternal CHD.
Echocardiography↗
Etiology and pathophysiology of stroke as a complex trait.
Stroke (brain attack) is currently the third leading cause of death in Western societies. Recent advances in molecular genetics have finally demonstrated what has long been suggested by the clinical observation, that is, stroke is not only the complication of major pathologic conditions such as atherosclerosis, hypertension, or cardiac diseases, but rather it represents a complex trait itself. Thus, the pathogenesis of stroke is often the result of the combined effects of genes exerting a direct contributory role and of their interactions with several environmental determinants. A genetic dissection of stroke has been attempted in suitable animal models and in humans. With this approach, the genetic defects underlying monogenic disorders associated with stroke were identified. Moreover, important findings have recently highlighted the contribution of genes encoding cardiovascular hormones, such as the atrial natriuretic peptide, for the pathogenesis of multifactorial, polygenic forms of stroke. A more thorough understanding of the fine mechanisms, dependent from mutations within stroke susceptibility genes and underlying the disease pathogenesis, may help to introduce new specific tools to achieve better prevention and treatment of stroke.
Animals↗
Genetics of the hydrophilic surfactant proteins A and D.
The use of candidate genes has increased the ability to identify genetic factors involved in diseases with complex and multifactorial etiology. The surfactant proteins (SP) A and D are involved in host defense and inflammatory processes of the lung, which are often components of pulmonary disease. Therefore, the SP-A and SP-D genes make particularly good candidates to study factors contributing to pulmonary disease etiopathogenesis. Moreover, SP-A also plays a role in the surface tension lowering abilities of pulmonary surfactant, which is essential for normal lung function. Although genetic variability at the SP-D locus may exist among humans, allelic variants have not yet been characterized. On the other hand, the human SP-A genes (SP-A1 and SP-A2) are characterized by genetically dependent splice variants at the 5' untranslated region and allelic variants. The polymorphisms that give rise to SP-A1 and SP-A2 alleles are contained within coding regions, potentially having an effect on protein function. There appears to be a correlation between SP-A genotype and SP-A mRNA content. Furthermore, one SP-A2 allele (1A0) shown to associate with low SP-A mRNA levels is found with higher frequency in a subgroup with respiratory distress syndrome. The evidence gathered thus far indicates that SP-A, possibly by interacting with other surfactant components, may play a role (e.g. be a susceptibility factor) in the development of respiratory disease.
Alternative Splicing↗
Metabolomics and microarrays for improved understanding of phenotypic characteristics controlled by both genomics and environmental constraints.
Advances in our understanding of functional genomics are best addressed by integrative studies that include measurements of mRNA, proteins, and low molecular weight metabolites over time and varied conditions. Bioinformatics can then be used to relate this data to the genome. Current technology allows for comprehensive and rapid mRNA expression profiling and mass spectrophotometric measurement of low molecular weight intermediates and metabolic products. In prokaryotic organisms, this combination provides a potentially powerful tool for identifying gene function and regulatory networks even in the absence of a combined proteomic approach.
Carbon Radioisotopes↗
A bias-ed assessment of the use of SNPs in human complex traits.
Although many biotechnological advancements have been made in the past decade, there has been very limited success in unraveling the genetic component of complex traits. Heavily invested research has been initiated based on etiological models of unrealistic simplicity and conducted under poor experimental designs, on data sets of insufficient size, leading to an overestimation of the effect sizes of genetic variants and the quantity and quality of linkage disequilibrium (LD). Arguments about whether families or unrelated individuals provide more power for gene mapping have been erroneously debated as issues of whether linkage or LD are more detectable sorts of correlation. Although the latter issue may be subject to debate, there is no doubt that family-based analysis is more powerful for detecting linkage and/or LD. If the recent advances in biotechnology are to be exploited effectively, vastly improved study designs will be imperative, as the reasons for the lack of success to date have much more to do with biology than technology, an issue that has become increasingly clear with the findings of the past years.
Bias↗
Finding genes underlying risk of complex disease by linkage disequilibrium mapping.
Identification of genes that harbor variation associated with inter-individual differences in risk of complex diseases remains one of the most challenging and important problems in human genetics. For genetic variants that are sufficiently common and have sufficiently large effects, direct tests of association through linkage disequilibrium with anonymous SNPs may prove effective. But the two critical parameters - the frequency of risk-inflating alleles and the magnitudes of their effect on risk - remain largely unknown. In this review we consider the latest information regarding the likely efficacy of the linkage disequilibrium mapping approach.
Chromosome Mapping↗
SNP analysis to dissect human traits.
The analysis of complex human diseases has been spurred by the number of published genomic sequence variants - many identified in the course of sequencing the human genome. But, to be useful for genetic analysis, variants have to be mapped accurately, their frequencies in various populations determined, and automated high-throughput assay techniques developed. Recently proposed methods address these issues: the use of 'reduced representation shotgun' methods for more efficient detection of single nucleotide polymorphisms (SNPs), the employment of high-throughput genotyping techniques, the development of SNP maps that incorporate information about linkage disequilibrium, and the use of SNPs in identifying susceptibility genes for common illnesses.
Chromosome Mapping↗
Disease model: hyperinsulinemia and insulin resistance. Part B--polygenic and other animal models.
Deficiency of leptin or its receptor produces hyperinsulinemia with marked obesity. Paradoxically, severe insulin resistance also accompanies lipodystrophy. Animal models of these contrasting conditions have enabled us to observe the profound and complicated aspects of the underlying pathologies. In addition, conventional polygenic rodents with known genetic backgrounds, such as the spontaneously hypertensive rat and the Goto-Kakisaki rat, have also been used to investigate these abnormalities.
Animals↗
Rethinking genetic strategies to study complex diseases.
Understanding the genetic basis of complex diseases is turning out to be difficult, prompting a widespread (re-)evaluation of the relevant issues. 'Forward' and 'reverse' genetics strategies have been applied arguably in a manner only suitable for much simpler diseases. It would now be beneficial to pay detailed attention to experimental design, and to increase study scales dramatically. Ultimately, this would lead to completely hypothesis-free, truly comprehensive, multi-platform investigations. Such studies would maximize the chances of finding data patterns indicative of real etiology, although many aspects of complex disease causation might simply be too intricate and inconsistent to ever be deciphered. Therefore, considerable technology development is an immediate priority, along with parallel advances in bioinformatics and biostatistics systems aimed at discriminating between marginal signals and background noise within extremely large, diverse and complex data sets. Community standards and open data sharing will be essential ingredients for success in this exciting 21st-century challenge.
Genetic Diseases, Inborn↗
Nonsyndromic cleft lip and palate: complex genetics and environmental effects.
Nonsyndromic cleft lip and palate (CL/P) is a common craniofacial malformation with a complex genetic component. Attempts at identifying susceptibility loci via family and case-control studies have proved inconsistent. It is likely that initial predictions of the complex interactions involved in facial development were underestimated. The candidate gene list for CL/P is getting longer and the need for an impartial, systematic screening technique, to implicate or refute the inclusion of particular loci, is apparent. Large-scale multi-centre collaborations will also be necessary if we are to pursue the avenues of gene-environment interactions, which have opened up over recent years. So we are faced with the question 'Can this complex trait be too complex?'
Animals↗
Mapping quantitative effects of oligogenes by allelic association.
Regression analysis of a quantitative trait as a function of a single diallelic polymorphism has been extended to allelic association by composite likelihood under the Malecot model for multiple markers. We applied the method to 10 single nucleotide polymorphisms (SNPs) spanning 27 kb of the angiotensin-I converting enzyme (ACE) gene in British families, localising a causal SNP between G2530A and 4656(CT)3/2 in the 3' region, at a distance of 21.6+/-0.9 kb from the most proximal SNP T-5491C. Neither they nor the I/D polymorphism is causal. To clarify genetic parameters we applied combined segregation, linkage and association analysis. Stronger evidence for the 3' region was obtained, with significant evidence of a lesser 5' effect as reported in French and Nigerian families. However, rigorous confirmation requires that the causal SNPs be identified. Both Malecot and parametric analysis appear to have high power by comparison with alternative methods for localizing oligogenes and their causal polymorphisms.
Chromosome Mapping↗
Power of a simplified multivariate test for genetic linkage.
In this paper we compare the power of the multivariate Haseman-Elston (MHE) test proposed earlier by Amos et al. (1990) and a computationally rapid new version of the multivariate Haseman-Elston test (NMHE) (Elston et al. 2000). We show that the power of NMHE was, for different simulation setups, identical or higher than that of MHE. In the bivariate case, the power of the NMHE method was somewhat less than that of the computationally intensive maximum likelihood variance components method (Amos et al. 2001). We present comparisons of the empirical distributions of the NMHE test to its limiting distributions for a range of numbers of traits. The distribution of the NMHE test appeared to conform satisfactorily to its limiting asymptotic distribution in large samples. Otherwise, empirical critical values for NMHE are somewhat higher than predicted, i.e. the test proposed by Elston et al. (2000) is non-conservative. The use of empirical critical values is therefore recommended for limited sample sizes (less than several hundred families). We also present the results of a linkage analysis performed by the NMHE method on a set of 4 body size-related traits. The method identified meaningful combinations of traits that showed significant linkage on chromosome 2 and suggestive linkage to regions on chromosomes 16 and 17.
Body Constitution↗
Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs.
A generalized interval mapping (GIM) method to map quantitative trait loci (QTL) for binary polygenic traits in a multi-family half-sib design is developed based on threshold theory and implemented using a Newton-Raphson algorithm. Statistical power and bias of QTL mapping for binary traits by GIM is compared with linear regression interval mapping (RIM) using simulation. Data on 20 paternal half-sib families were simulated with two genetic markers that bracketed an additive QTL. Data simulated and analysed were: (1) data on the underlying normally distributed liability (NDL) scale, (2) binary data created by truncating NDL data based on three thresholds yielding data sets with three different incidences, and (3) NDL data with polygenic and QTL effects reduced by a proportion equal to the ratio of the heritabilities on the binary versus NDL scale (reduced-NDL). Binary data were simulated with and without systematic environmental (herd) effects in an unbalanced design. GIM and RIM gave similar power to detect the QTL and similar estimates of QTL location, effects and variances. Presence of fixed effects caused differences in bias between RIM and GIM, where GIM showed smaller bias which was affected less by incidence. The original NDL data had higher power and lower bias in QTL parameter estimates than binary and reduced-NDL data. RIM for reduced-NDL and binary data gave similar power and estimates of QTL parameters, indicating that the impact of the binary nature of data on QTL analysis is equivalent to its impact on heritability.
Algorithms↗
The power of the transmission disequilibrium test (TDT) with both case-parent and control-parent trios.
The transmission disequilibrium test (TDT) customarily uses affected children and their parents (often case-parent trios, TDTD). Control-parent trios are necessary to guard against spurious significant results due to segregation distortion but are not generally utilized in the identification of disease susceptibility loci (DSL). Controls are often easy to recruit and the TDT can easily be extended to include control-parent trios into the analyses with unrelated case-parent trios. We present an extension of the TDT (TDTDC) that incorporates unrelated cases and controls and their parents into a single analysis. We develop a simple and accurate analytical method for computing the statistical power of various TDT (e.g. the TDTD, TDTDC, TDTDC and TDTC that employ control-parent trios only) under any genetic model. We investigated the power of these TDT, and particularly compared the relative power of the TDTD and TDTDC. We found that the TDTDC is almost always more powerful than the TDTC and TDTD. The relative power of the TDTDC and TDTD depends largely upon a number of parameters identified in the study. This study provides a basis for efficient use of control-parent trios in DSL identification.
Case-Control Studies↗
On flexible finite polygenic models for multiple-trait evaluation.
Finite polygenic models (FPM) might be an alternative to the infinitesimal model (TIM) for the genetic evaluation of pedigreed multiple-generation populations for multiple quantitative traits. I present a general flexible Bayesian method that includes the number of genes in the FPM as an additional random variable. Markov-chain Monte Carlo techniques such as Gibbs sampling and the reversible jump sampler are used for implementation. Sampling of genotypes of all genes in the FPM is done via the use of segregation indicators. A broad range of FPM models, some combined with TIM, are empirically tested for the estimation of variance components and the number of genes in the FPM. Four simulation scenarios were studied, including genetic models with 5 or 50 additive independent diallelic genes affecting the traits, and random selection or selection on one of the traits was performed. The results in this study were based on ten replicates per simulation scenario. In the case of random selection, uniform priors on additive gene effects led to posterior mean estimates of genetic variance that were positively correlated with the number of genes fitted in the FPM. In the case of trait selection, assuming normal priors on gene effects also led to genetic variance estimates for the selected trait that were negatively correlated with the number of genes in the FPM. This negative correlation was not observed for the unselected trait. Treating the number of genes in the FPM as random revealed a positive correlation between prior and posterior mean estimates of this number, but the prior hardly affected the posterior estimates of genetic variance. Posterior inferences about the number of genes should be considered to be indicative where trait selection seems to improve the power of distinguishing between TIM and FPM. Based on the results of this study, I suggest not replacing TIM by the FPM, but combining TIM and FPM with the number of genes treated as random, to facilitate a highly flexible and thereby robust method for variance component estimation in pedigreed populations. Further study is required to explore the full potential of these models under different genetic model assumptions.
Analysis of Variance↗
Gene-environment interactions in complex diseases: genetic models and methods for QTL mapping in multiple half-sib populations.
An interval quantitative trait locus (QTL) mapping method for complex polygenic diseases (as binary traits) showing QTL by environment interactions (QEI) was developed for outbred populations on a within-family basis. The main objectives, within the above context, were to investigate selection of genetic models and to compare liability or generalized interval mapping (GIM) and linear regression interval mapping (RIM) methods. Two different genetic models were used: one with main QTL and QEI effects (QEI model) and the other with only a main QTL effect (QTL model). Over 30 types of binary disease data as well as six types of continuous data were simulated and analysed by RIM and GIM. Using table values for significance testing, results show that RIM had an increased false detection rate (FDR) for testing interactions which was attributable to scale effects on the binary scale. GIM did not suffer from a high FDR for testing interactions. The use of empirical thresholds, which effectively means higher thresholds for RIM for testing interactions, could repair this increased FDR for RIM, but such empirical thresholds would have to be derived for each case because the amount of FDR depends on the incidence on the binary scale. RIM still suffered from higher biases (15-100% over- or under-estimation of true values) and high standard errors in QTL variance and location estimates than GIM for QEI models. Hence GIM is recommended for disease QTL mapping with QEI. In the presence of QEI, the model including QEI has more power (20-80% increase) to detect the QTL when the average QTL effect is small (in a situation where the model with a main QTL only is not too powerful). Top-down model selection is proposed in which a full test for QEI is conducted first and then the model is subsequently simplified. Methods and results will be applicable to human, plant and animal QTL mapping experiments.
Animals↗
Palliating the impact of fixation of a major gene on the genetic variation of artificially selected polygenes.
Selective sweeps of variation caused by fixation of major genes may have a dramatic impact on the genetic gain from background polygenic variation, particularly in the genome regions closely linked to the major gene. The response to selection can be restrained because of the reduced selection intensity and the reduced effective population size caused by the increase in frequency of the major gene. In the context of a selected population where fixation of a known major gene is desired, the question arises as to which is the optimal path of increase in frequency of the gene so that the selective sweep of variation resulting from its fixation is minimized. Using basic theoretical arguments we propose a frequency path that maximizes simultaneously the effective population size applicable to the selected background and the selection intensity on the polygenic variation by minimizing the average squared selection intensity on the major gene over generations up to a given fixation time. We also propose the use of mating between carriers and non-carriers of the major gene, in order to promote the effective recombination between the major gene and its linked polygenic background. Using a locus-based computer simulation assuming different degrees of linkage, we show that the path proposed is more effective than a similar path recently published, and that the combination of the selection and mating methods provides an efficient way to palliate the negative effects of a selective sweep.
Computer Simulation↗