Studying parents and grandparents to assess genetic contributions to early-onset disease

Suppose DNA is available from affected individuals, their parents, and their grandparents. Particularly for early-onset diseases, maternally mediated genetic effects can play a role, because the mother determines the prenatal environment. The proposed maximum-likelihood approach for the detection of apparent transmission distortion treats the triad consisting of the affected individual and his or her two parents as the outcome, conditioning on grandparental mating types. Under a null model in which the allele under study does not confer susceptibility, either through linkage or directly, and when there are no maternally mediated genetic effects, conditional probabilities for specific triads are easily derived. A log-linear model permits a likelihood-ratio test (LRT) and allows the estimation of relative penetrances. The proposed approach is robust against genetic population stratification. Missing-data methods permit the inclusion of incomplete families, even if the missing person is the affected grandchild, as is the case when an induced abortion has followed the detection of a malformation. When screening multiple markers, one can begin by genotyping only the grandparents and the affected grandchildren. LRTs based on conditioning on grandparental mating types (i.e., ignoring the parents) have asymptotic relative efficiencies that are typically >150% (per family), compared with tests based on parents. A test for asymmetry in the number of copies carried by maternal versus paternal grandparents yields an LRT specific to maternal effects. One can then genotype the parents for only the genes that passed the initial screen. Conditioning on both the grandparents' and the affected grandchild's genotypes, a third log-linear model captures the remaining information, in an independent LRT for maternal effects.     

Detection of disease genes by use of family data. I. Likelihood-based theory

We present a class of likelihood-based score statistics that accommodate genotypes of both unrelated individuals and families, thereby combining the advantages of case-control and family-based designs. The likelihood extends the one proposed by Schaid and colleagues (Schaid and Sommer 1993, 1994; Schaid 1996; Schaid and Li 1997) to arbitrary family structures with arbitrary patterns of missing data and to dense sets of multiple markers. The score statistic comprises two component test statistics. The first component statistic, the nonfounder statistic, evaluates disequilibrium in the transmission of marker alleles from parents to offspring. This statistic, when applied to nuclear families, generalizes the transmission/disequilibrium test to arbitrary numbers of affected and unaffected siblings, with or without typed parents. The second component statistic, the founder statistic, compares observed or inferred marker genotypes in the family founders with those of controls or those of some reference population. The founder statistic generalizes the statistics commonly used for case-control data. The strengths of the approach include both the ability to assess, by comparison of nonfounder and founder statistics, the potential bias resulting from population stratification and the ability to accommodate arbitrary family structures, thus eliminating the need for many different ad hoc tests. A limitation of the approach is the potential power loss and/or bias resulting from inappropriate assumptions on the distribution of founder genotypes. The systematic likelihood-based framework provided here should be useful in the evaluation of both the relative merits of case-control and various family-based designs and the relative merits of different tests applied to the same design. It should also be useful for genotype-disease association studies done with the use of a dense set of multiple markers.     

Less is more, except when less is less: Studying joint effects

Most diseases are complex in that they are caused by the joint action of multiple factors, both genetic and environmental. Over the past few decades, the mathematical convenience of logistic regression has served to enshrine the multiplicative model, to the point where many epidemiologists believe that departure from additivity on a log scale implies that two factors interact in causing disease. Other terminology in epidemiology, where students are told that inequality of relative risks across levels of a second factor should be seen as "effect modification," reinforces an uncritical acceptance of multiplicative joint effect as the biologically meaningful no-interaction null. Our first task, when studying joint effects, is to understand the limitations of our definitions for "interaction," and recognize that what statisticians mean and what biologists might want to mean by interaction may not coincide. Joint effects are notoriously hard to identify and characterize, even when asking a simple and unsatisfying question, like whether two effects are log-additive. The rule of thumb for such efforts is that a factor-of-four sample size is needed, compared with that needed to demonstrate main effects of either genes or exposures. So strategies have been devised that focus on the most informative individuals, either through risk-based sampling for a cohort, or case-control sampling, extreme phenotype sampling, pooling, two-stage sampling, exposed-only, or case-only designs. These designs gain efficiency, but at a cost of flexibility in models for joint effects. A relatively new approach avoids population controls by genotyping case-parent triads. Because it requires parents, the method works best for diseases with onset early in life. With this design, the role of autosomal genetic variants is assessed by in effect treating the nontransmitted parental alleles as controls for affected offspring. Despite advantages for looking at genetic effects, the triad design faces limitations when examining joint effects of genetic and environmental factors. Because population-based controls are not included, main effects for exposures cannot be estimated, and consequently one only has access to inference related to a multiplicative null. We have proposed a hybrid approach that offers the best features of both case-parent and case-control designs. Through genotyping of parents of population-based controls and assuming Mendelian transmission, power is markedly enhanced. One can also estimate main effects for exposures and now flexibly assess models for joint effects.     

Correction of population stratification in large multi-ethnic association studies

Background

The vast majority of genetic risk factors for complex diseases have, taken individually, a small effect on the end phenotype. Population-based association studies therefore need very large sample sizes to detect significant differences between affected and non-affected individuals. Including thousands of affected individuals in a study requires recruitment in numerous centers, possibly from different geographic regions. Unfortunately such a recruitment strategy is likely to complicate the study design and to generate concerns regarding population stratification.

Methodology/Principal Findings

We analyzed 9,751 individuals representing three main ethnic groups - Europeans, Arabs and South Asians - that had been enrolled from 154 centers involving 52 countries for a global case/control study of acute myocardial infarction. All individuals were genotyped at 103 candidate genes using 1,536 SNPs selected with a tagging strategy that captures most of the genetic diversity in different populations. We show that relying solely on self-reported ethnicity is not sufficient to exclude population stratification and we present additional methods to identify and correct for stratification.

Conclusions/Significance

Our results highlight the importance of carefully addressing population stratification and of carefully “cleaning” the sample prior to analyses to obtain stronger signals of association and to avoid spurious results.     

A unified association analysis approach for family and unrelated samples correcting for stratification

There are two common designs for association mapping of complex diseases: case-control and family-based designs. A case-control sample is more powerful to detect genetic effects than a family-based sample that contains the same numbers of affected and unaffected persons, although additional markers may be required to control for spurious association. When family and unrelated samples are available, statistical analyses are often performed in the family and unrelated samples separately, conditioning on parental information for the former, thus resulting in reduced power. In this report, we propose a unified approach that can incorporate both family and case-control samples and, provided the additional markers are available, at the same time corrects for population stratification. We apply the principal components of a marker matrix to adjust for the effect of population stratification. This unified approach makes it unnecessary to perform a conditional analysis of the family data and is more powerful than the separate analyses of unrelated and family samples, or a meta-analysis performed by combining the results of the usual separate analyses. This property is demonstrated in both a variety of simulation models and empirical data. The proposed approach can be equally applied to the analysis of both qualitative and quantitative traits.     

Methods for detection of parent-of-origin effects in genetic studies of case-parents triads.

When affected probands and their biological parents are genotyped at a candidate gene or a marker, the resulting case-parents-triad data enable powerful tests for linkage in the presence of association. When linkage disequilibrium has been detected in such a study, the investigator may wish to look further for possible parent-of-origin effects. If, for example, the transmission/disequilibrium test restricted to fathers is statistically significant, whereas that restricted to mothers is not, the investigator might interpret this as evidence for nonexpression of the maternally derived disease gene-that is, imprinting. This report reviews existing methods for detection of parent-of-origin effects, showing that each can be invalid under certain scenarios. Two new methods are proposed, based on application of likelihood-based inference after stratification on both the parental mating type and the inherited number of copies of the allele under study. If there are no maternal genetic effects expressed prenatally during gestation, the parental-asymmetry test is powerful and provides valid estimation of a parent-of-origin parameter. For diseases for which there could be maternal effects on risk, the parent-of-origin likelihood-ratio test provides a robust alternative. Simulations based on an admixed population demonstrate good operating characteristics for these procedures, under diverse scenarios.     

Limiting inbreeding in disjunct and isolated populations of a woody shrub

Pollen movements and mating patterns are key features that influence population genetic structure. When gene flow is low, small populations are prone to increased genetic drift and inbreeding, but naturally disjunct species may have features that reduce inbreeding and contribute to their persistence despite genetic isolation. Using microsatellite loci, we investigated outcrossing levels, family mating parameters, pollen dispersal, and spatial genetic structure in three populations of Hakea oldfieldii, a fire‐sensitive shrub with naturally disjunct, isolated populations prone to reduction in size and extinction following fires. We mapped and genotyped a sample of 102 plants from a large population, and all plants from two smaller populations (28 and 20 individuals), and genotyped 158–210 progeny from each population. We found high outcrossing despite the possibility of geitonogamous pollination, small amounts of biparental inbreeding, a limited number of successful pollen parents within populations, and significant correlated paternity. The number of pollen parents for each seed parent was moderate. There was low but significant spatial genetic structure up to 10 m around plants, but the majority of successful pollen came from outside this area including substantial proportions from distant plants within populations. Seed production varied among seven populations investigated but was not correlated with census population size. We suggest there may be a mechanism to prevent self‐pollination in H. oldfieldii and that high outcrossing and pollen dispersal within populations would promote genetic diversity among the relatively small amount of seed stored in the canopy. These features of the mating system would contribute to the persistence of genetically isolated populations prone to fluctuations in size.     

Genetic liability to schizophrenia in Oceanic Palau: a search in the affected and maternal generation

While liability to schizophrenia (Scz) is due to genetic and environmental factors, specific factors are largely unknown. We postulate a two-hit model for Scz, in which initial liability is generated during fetal brain development: this “hit” is precipitated by environmental stressors biologically interacting with maternal genetic vulnerability to the stress. Additional liability to Scz is generated by individual genetic vulnerability. To evaluate these putative levels of vulnerability, we search in the genome of both affected individuals and their mothers for variation that differs, statistically, from that in the general population. For parental analyses, mothers were treated as “affected,” rather than their offspring, and the fathers were treated as “controls”. We used a sample from the Palauan population: 175 individuals diagnosed with Scz, broadly defined; 87 mothers and 45 fathers of affected individuals. Pedigree and diagnostic data were available on 2,953 living and deceased subjects. DNA from 553 individuals was genotyped for short tandem repeats (STR) spaced approximately every 10 cM across the genome. We tested for association between affection status and STR alleles; such an approach was reasonable, despite the widely spaced markers, because this population has far-ranging linkage disequilibrium (LD). Results for the truly affected individuals were modest, whereas results from the maternal generation were promising. For a recessive model and a test for excess allele matching across mothers, significant findings occurred for D20S481, D10S1221, D6S1021, D13S317, and D18S976. Regions in which at least two adjacent markers produced substantial association statistics include 2p12-11.2, 2q24.1-32.1, 6q12-14.1, 10q23.2-24.21, 12q23.2-24.21 and 17q23.2-23.3.     

Optimised parent selection and minimum inbreeding mating in small aquaculture breeding schemes: a simulation study

The effectiveness of low cost breeding scheme designs for small aquaculture breeding programmes were assessed for their ability to achieve genetic gain while managing inbreeding using stochastic simulation. Individuals with trait data were simulated over 15 generations with selection on a single trait. Combinations of selection methods, mating strategies and genetic evaluation options were evaluated with and without the presence of common environmental effects. An Optimal Parent Selection (OPS) method using semi-definite programming was compared with a truncation selection (TS) method. OPS constrains the rate of inbreeding while maximising genetic gain. For either selection method, mating pairs were assigned from the selected parents by either random mating (RM) or Minimum Inbreeding Mating (MIM), which used integer programming to determine mating pairs. Offspring were simulated for each mating pair with equal numbers of offspring per pair and these offspring were the candidates for selection of parents of the next generation. Inbreeding and genetic gain for each generation were averaged over 25 replicates. Combined OPS and MIM led to a similar level of genetic gain to TS and RM, but inbreeding levels were around 75% lower than TS and RM after 15 generations. Results demonstrate that it would be possible to manage inbreeding over 15 generations within small breeding programmes comprised of 30 to 40 males and 30 to 40 females with the use of OPS and MIM. Selection on breeding values computed using Best Linear Unbiased Prediction (BLUP) with all individuals genotyped to obtain pedigree information resulted in an 11% increase in genetic merit and a 90% increase in the average inbreeding coefficient of progeny after 15 generations compared with selection on raw phenotype. Genetic evaluation strategies using BLUP wherein elite individuals by raw phenotype are genotyped to obtain parentage along with a range of different samples of remaining individuals did not increase genetic progress in comparison to selection on raw phenotype. When common environmental effects on full-sib families were simulated, performance of small breeding scheme designs was little affected. This was because the majority of selection must anyway be applied within family due to inbreeding constraints.     

Testing gene-gene interactions in the case-parents design

The case-parents design has been widely used to detect genetic associations as it can prevent spurious association that could occur in population-based designs. When examining the effect of an individual genetic locus on a disease, logistic regressions developed by conditioning on parental genotypes provide complete protection from spurious association caused by population stratification. However, when testing gene-gene interactions, it is unknown whether conditional logistic regressions are still robust. Here we evaluate the robustness and efficiency of several gene-gene interaction tests that are derived from conditional logistic regressions. We found that in the presence of SNP genotype correlation due to population stratification or linkage disequilibrium, tests with incorrectly specified main-genetic-effect models can lead to inflated type I error rates. We also found that a test with fully flexible main genetic effects always maintains correct test size and its robustness can be achieved with negligible sacrifice of its power. When testing gene-gene interactions is the focus, the test allowing fully flexible main effects is recommended to be used.     

Use of unlinked genetic markers to detect population stratification in association studies.

We examine the issue of population stratification in association-mapping studies. In case-control studies of association, population subdivision or recent admixture of populations can lead to spurious associations between a phenotype and unlinked candidate loci. Using a model of sampling from a structured population, we show that if population stratification exists, it can be detected by use of unlinked marker loci. We show that the case-control-study design, using unrelated control individuals, is a valid approach for association mapping, provided that marker loci unlinked to the candidate locus are included in the study, to test for stratification. We suggest guidelines as to the number of unlinked marker loci to use.     

Multiple Paternity in Norway Lobster (<Emphasis Type="Italic">Nephrops norvegicus</Emphasis> L.) Assessed with Microsatellite Markers

We investigated genetic diversity and the mating system of the Norway lobster (Nephrops norvegicus) in a wild population off the Portuguese coast. Approximately 100 individuals were screened for 2 microsatellite loci. For 11 ovigerous lobsters both the female and a sample of her offspring (24 eggs) were genotyped. High genetic diversity was observed for the 2 markers in the population. Paternity within broods was analyzed by comparing multilocus genotypes of each egg with the corresponding mother, and the male parent contribution was then deduced. Multiple paternity was observed in 6 of the 11 broods studied. In those cases, 2 to 3 male parents were likely to have contributed to the fertilization of the eggs. When multiple paternity was involved, the comparative reproductive success of the male parents was quite even. This is the first report of multiple paternity in the Norway lobster. Comparisons with other taxa are presented, and consequences of multiple paternity are discussed.     

Inbreeding depression from selfing and mating between relatives in the Neotropical tree <Emphasis Type="Italic">Cariniana legalis</Emphasis> Mart. Kuntze

Selfing or mating between related individuals in self-compatible hermaphroditic tree species may lead to inbreeding depression (ID) due to homozygosis in recessive, identical by descent alleles. In general, studies of ID in tree species have been based on comparisons of selfed individuals (produced by controlled pollination) with outcrossed individuals for quantitative traits in progeny tests. However, this approach requires a long time to quantify the extent of ID. Thus, we used an approach based on genetic markers to estimate coancestry coefficients between assigned parents from paternity analysis in two populations of the Neotropical tree Cariniana legalis. Using this method, we were able to determine which seedlings in a nursery trial originated from; (i) outcrossing between un-related trees, (ii) mating between related trees and (iii) selfing. We detected a low selfing rate (<10 %), but a substantial quantity of seedlings from mating between related parents (minimum of 35.7 %). In general, the outcrossed seedlings from unrelated parents exhibited significantly greater genetic diversity than those resulting from selfing and mating among relatives. The extent of ID varied among traits and populations. Outcrossed seedlings originating from unrelated trees generally showed greater survival than seedlings originating from selfing and related parents. Inbreeding depression was greater in the selfed seedlings than in those from mating among related parents. The results are discussed in terms of implications for genetic conservation, breeding and environmental restoration using the species.     

African ancestry is associated with risk of asthma and high total serum IgE in a population from the Caribbean Coast of Colombia

African descended populations exhibit an increased prevalence of asthma and allergies compared to Europeans. One approach to distinguish between environmental and genetic explanations for this difference is to study relationships of asthma risk to individual admixture. We aimed to determine the admixture proportions of a case-control sample from the Caribbean Coast of Colombia currently participating in genetic studies for asthma, and to test for population stratification and association between African ancestry and asthma and total serum IgE levels (tIgE). We genotyped 368 asthmatics and 365 non-asthmatics for 52 autosomal ancestry informative markers, six mtDNA haplogroups and nine haplogroups and five microsatellites in Y chromosome. Autosomal admixture proportions, population stratification, and associations between ancestry and the phenotypes were estimated by ADMIXMAP. The average admixture proportions among asthmatics were 42.8% European, 39.9% African and 17.2% Native American and among non-asthmatics they were 44.2% (P = 0.068), 37.6% (P = 0.007) and 18.1% (P = 0.050), respectively. In the total sample, the paternal contributions were 71% European, 25% African and 4.0% Native American and the maternal lineages were 56.8% Native American, and 20.2% African; 22.9% of the individuals carried other non-Native American mtDNA haplogroups. African ancestry was significantly associated with asthma (OR: 2.97; 95% CI: 1.08–8.08), high tIgE (OR: 1.9; 95% CI: 1.17–3.12) and socioeconomic status (OR = 0.64; 95% CI: 0.47–0.87). Significant population stratification was observed in this sample. Our findings indicate that genetic factors can explain the association between asthma and African ancestry and suggest that this sample is a useful resource for performing admixture mapping for asthma.     

A Statistical Approach for Rare-Variant Association Testing in Affected Sibships

Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.     

A comparative study of sibship tests of linkage and/or association.

Population-based tests of association have used data from either case-control studies or studies based on trios (affected child and parents). Case-control studies are more prone to false-positive results caused by inappropriate controls, which can occur if, for example, there is population admixture or stratification. An advantage of family-based tests is that cases and controls are well matched, but parental data may not always be available, especially for late-onset diseases. Three recent family-based tests of association and linkage utilize unaffected siblings as surrogates for untyped parents. In this paper, we propose an extension of one of these tests. We describe and compare the four tests in the context of a complex disease for both biallelic and multiallelic markers, as well as for sibships of different sizes. We also examine the consequences of having some parental data in the sample.     

Rapid Range Expansion Is Not Restricted by Inbreeding in a Sexually Cannibalistic Spider

Few studies investigated whether rapid range expansion is associated with an individual''s short-term fitness costs due to an increased risk of inbred mating at the front of expansion. In mating systems with low male mating rates both sexes share potential inbreeding costs and general mechanisms to avoid or reduce these costs are expected. The spider Argiope bruennichi expanded its range recently and we asked whether rapid settlement of new sites exposes individuals to a risk of inbreeding. We sampled four geographically separated subpopulations, genotyped individuals, arranged matings and monitored hatching success. Hatching success was lowest in egg-sacs derived from sibling pairs and highest in egg-sacs derived from among-population crosses, while within-population crosses were intermediate. This indicates that inbreeding might affect hatching success in the wild. Unlike expected, differential hatching success of within- and among-population crosses did not correlate with genetic distance of mating pairs. In contrast, we found high genetic diversity based on 16 microsatellite markers and a fragment of the mitochondrial COI gene in all populations. Our results suggest that even a very recent settlement secures the presence of genetically different mating partners. This leads to costs of inbreeding since the population is not inbred.     

Implications of social dominance and multiple paternity for the genetic diversity of a captive-bred reptile population (tuatara)

Captive breeding is an integral part of many species recovery plans. Knowledge of the genetic mating system is essential for effective management of captive stocks and release groups, and can help to predict patterns of genetic diversity in reintroduced populations. Here we investigate the poorly understood mating system of a threatened, ancient reptile (tuatara) on Little Barrier Island, New Zealand and discuss its impact on the genetic diversity. This biologically significant population was thought to be extinct, due to introduced predators, until 8 adults (4 males, 4 females) were rediscovered in 1991/92. We genotyped these adults and their 121 captively-bred offspring, hatched between 1994 to 2005, at five microsatellite loci. Multiple paternity was found in 18.8% of clutches. Male variance in reproductive success was high with one male dominating mating (77.5% of offspring sired) and one male completely restricted from mating. Little Barrier Island tuatara, although clearly having undergone a demographic bottleneck, are retaining relatively high levels of remnant genetic diversity which may be complemented by the presence of multiple paternity. High variance in reproductive success has decreased the effective size of this population to approximately 4 individuals. Manipulation to equalize founder representation was not successful, and the mating system has thus had a large impact on the genetic diversity of this recovering population. Although population growth has been successful, in the absence of migrants this population is likely at risk of future inbreeding and genetic bottleneck.     

Wild sorghum from different eco-geographic regions of Kenya display a mixed mating system

Knowledge of mating systems is required in order to understand the genetic composition and evolutionary potential of plant populations. Outcrossing in a population may co-vary with the ecological and historical factors influencing it. However, literature on the outcrossing rate is limited in terms of wild sorghum species coverage and eco-geographic reference. This study investigated the outcrossing rates in wild sorghum populations from different ecological conditions of Kenya. Twelve wild sorghum populations were collected in four sorghum growing regions. Twenty-four individuals per population were genotyped using six polymorphic simple sequence repeat (SSR) markers to compute their indirect equilibrium estimates of outcrossing rate as well as population structure. In addition, the 12 populations were planted in a field in a randomised block design with five replications. Their progeny (250 individuals per population) were genotyped with the six SSR markers to estimate multi-locus outcrossing rates. Equilibrium estimates of outcrossing rates ranged from 7.0 to 75.0%, while multi-locus outcrossing rates (t _m) ranged from 8.9 to 70.0% with a mean of 49.7%, indicating that wild sorghum exhibits a mixed mating system. The wide range of estimated outcrossing rates in wild sorghum populations indicate that environmental conditions may exist under which fitness is favoured by outcrossing and others under which selfing is more advantageous. The genetic structure of the populations studied is concordant with that expected for a species displaying mixed mating system.     

How much can parentage analyses tell us about precapture dispersal?

Estimating rates of movement among populations is never simple, and where young animals cannot all be captured at their birth sites, traditional field methods potentially underestimate dispersal rates. Genetic assignment tests appear to hold promise for detecting 'precapture' dispersal, and recent evidence suggests that even on the scale of dispersal between populations, genetic parentage analyses can also be informative. Herein, we examine the performance of both types of analysis with data from a 17-year study of dispersal in banner-tailed kangaroo rats Dipodomys spectabilis. We compare estimates of precapture dispersal from (i) the commonly used parentage analysis program cervus (ii) a pedigree-reconstruction program, MasterBayes, that combines genetic with spatial and other nongenetic information and (iii) genetic assignment procedures implemented by the program geneclass2, with (iv) rates of dispersal observed through recapture of a subset of animals initially marked shortly after weaning. geneclass2 estimates a larger proportion of precapture dispersers than MasterBayes, but both approaches as well as those based on field data alone, suggest that approximately 10% of adults in local populations are immigrants and that interpopulation dispersal is slightly female-biassed. All genetic procedures detect precapture dispersal between populations, but dispersers identified by MasterBayes are particularly compatible with what is independently known about body mass at dispersal, dispersal distance and distance between parents. Parentage analyses have considerable potential to infer the value of this otherwise elusive demographic parameter when most candidate parents can be genotyped and when nongenetic information, especially the distance separating candidate mothers and fathers, can be incorporated into the procedure.