Genotype-specific recurrence risks as indicators of the genetic architecture of complex diseases

A statistic is introduced that relates discoveries made in genome-wide association (GWA) studies to patterns of disease risks among relatives. The genotype-specific recurrence risk (GSR) is the genotype-specific risk to relatives of known relationship to affected probands. The GSRs can be used for three purposes. (1) They can provide an independent test of whether an allele identified in a GWA study is associated with the disease. (2) They can provide a test of whether interactions among loci affecting the disease are multiplicative. (3) They can be used by genetic counselors to incorporate information from GWA studies for predicting the risk to relatives of known genotype. Under a multiplicative model of disease causation, the GSRs for a locus are the genotypic risks in probands for that locus multiplied by lambda(R)/lambda(jR), where lambda(R) is Risch's recurrence risk ratio and lambda(jR) is the contribution to lambda(R) from the locus of interest. If there is saturation of risk with increasing numbers of causative alleles, then observed GSRs for individuals with high-risk genotypes will be lower than predicted by the multiplicative model.     

Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits

Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type"), which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage) than for a trait with no loci of large effect (overall type), provided the method of analysis takes advantage of the distribution of loci effects.     

雄性不交换条件下F2群体区间标记——QTL定位的相关方法（英文）

提出了雄性不交换条件下F2群体区间标记定位QTL的相关方法,并且对其适用的条件进行了讨论,通过对分子区间标记进行赋值,计算在无交叉干涉条件下分子标记与表型值的简单相关系数,并在此基础上进行连锁检验,在特定条件下可以估计数量性状座位（QTL）与分子标记座位间的连锁值。     

具交叉干涉的三点测交区间标记定位（QTL）的相关方法

本文提出在有交叉干涉条件下,在测交群体中对区间标记座位赋值后求其与待定位的数量性状表型值间的简单相关系数R,以此进行连锁测验,并且在一定条件下用R值求出该数量性状座位（QTL）与各标记座位（ML）间的重组值。     

Familial recurrence-pattern analysis of cleft lip with or without cleft palate.

Cleft lip with or without cleft palate (CL/P) is a common congenital malformation with an incidence in European white populations of about 1/1,000. The familial clustering of CL/P has been extensively characterized, and epidemiological studies have proposed monogenic models (with reduced penetrance), multifactorial/threshold models, and mixed major-gene/multifactorial models to explain its inheritance. The recognition of an association between two RFLPs at the transforming growth factor alpha (TGFA) locus and CL/P supports a major-gene component to the etiology of CL/P. Risch has shown that the recurrence risk ratio lambda R (risk to relatives, vs. population prevalence) is a useful pointer to the mode of inheritance. Here we further develop the use of lambda R to analyze recurrence-risk data for CL/P. Recurrence risks for first-, second-, and third-degree relatives equate well with oligogenic models with as few as four loci. A monogenic/additive model is strongly rejected. The limited available twin data are also consistent with this model. A "major gene" interacting epistatically with an oligogenic background is shown to be a plausible alternative. Power calculations for a linkage study to map the CL/P major-risk locus suggest that a sample of 50 affected sib pairs will be adequate, but linkage to minor-risk loci will require very much larger samples.     

利用eQTL构建基因-基因网络挖掘类风湿性关节炎风险基因

目的：类风湿性关节炎是一种全身的慢性炎症型疾病,可能影响许多组织和器官,主要发作于灵活的关节。全世界人群中大约有1％会患有类风湿性关节炎。目前已经证实了一些基因与类风湿性关节炎相关,但是这些基因只能解释一小部分遗传风险,因此我们需要新的策略和方法来解决这个问题。方法：表达数量性状位点（eQTL）是指能够调控基因或蛋白质表达的基因组位点,本文采用了eQTL数据构建基因一基因网络并挖掘候选类风湿性关节炎风险基因。结果：首先,利用eQTL数据,基于基因之间的共调控系数,建立基因-基因网络,我们建立了5个不同阈值（0、O．2、0．4、0．6和0．8）的基因-基因网络;然后,在OMIM和GAD数据库中搜索已经证实的与类风湿性关节炎相关的186个基因;最后我们将已证实与类风湿性关节炎相关的186个基因分别投入到这5个网络中,利用基因与基因之间的相关性来挖掘到一些可能与类风湿性关节炎相关的候选风险基因。结论：本文基于eQTL构建了基因．基因网络,结合已知类风湿性关节炎风险基因,挖掘未知风险基因,得到了较好的结果,证明了本方法的有效性,且对于类风湿性关节炎的发病机制研究具有重要价值。除了类风湿性关节炎外,本方法还可推广到其它复杂疾病中,因此本方法对人类复杂疾病的研究具有很强的学术理论价值和应用价值。     

Intracranial aneurysm risk locus 5q23.2 is associated with elevated systolic blood pressure

Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n(FIN) = 11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n = 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p(FIN) = 3.01E-05, p(ICBP-GWAS) = 0.0007, p(ALL) = 8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.     

Power to detect risk alleles using genome-wide tag SNP panels

Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ~ 1.8–2.0). Relative risks as low as λ ~ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.     

Nonequivalent Loci and the distribution of mutant effects

It has been observed repeatedly that the distribution of new mutations of a quantitative trait has a kurtosis (a statistical measure of the distribution's shape) that is systematically larger than that of a normal distribution. Here we suggest that rather than being a property of individual loci that control the trait, the enhanced kurtosis is highly likely to be an emergent property that arises directly from the loci being mutationally nonequivalent. We present a method of incorporating nonequivalent loci into quantitative genetic modeling and give an approximate relation between the kurtosis of the mutant distribution and the degree of mutational nonequivalence of loci. We go on to ask whether incorporating the experimentally observed kurtosis through nonequivalent loci, rather than at locus level, affects any biologically important conclusions of quantitative genetic modeling. Concentrating on the maintenance of quantitative genetic variation by mutation-selection balance, we conclude that typically nonequivalent loci yield a genetic variance that is of order 10% smaller than that obtained from the previous approaches. For large populations, when the kurtosis is large, the genetic variance may be <50% of the result of equivalent loci, with Gaussian distributions of mutant effects.     

Mode of inheritance of nonsyndromic cleft lip with or without cleft palate: a reanalysis.

Nonsyndromic cleft lip with or without cleft palate (CL +/- P) is traditionally recognized as a multifactorial threshold trait (MFT). Recently, however, evidence for the involvement of a major gene in the etiology of CL +/- P has been reported. To assess the potential for major-gene involvement in the etiology of this trait, familial recurrence patterns from several family studies of CL +/- P were reanalyzed. The recurrence patterns in first-degree relatives of CL +/- P probands were found to be compatible with the expectations for either an MFT or a generalized single-major-locus (gSML) trait. The use of multiple thresholds based on proband sex, defect bilaterality, or palatal involvement did not help to discriminate between these models. However, the pattern of recurrence among MZ twins and more remote relatives of CL +/- P probands is not consistent with gSML inheritance but is compatible with either an MFT model or a model specifying multiple interacting loci. For such a model, no single locus can account for more than a sixfold increase in risk to first-degree relatives. These findings have important implications with regard to the feasibility of detecting linkage to loci conferring susceptibility to CL +/- P.     

Solitary epileptic seizure--the risk of recurrence

Patients experiencing solitary unprovoked epileptic seizure have different risks of recurrence. The possible risk factors include in particular: structural cerebral lesion and its cause, history of febrile seizures, family history of epilepsy, the type of seizure, epileptiform EEG discharges and the problem of initiation or (or not initiation) of antiepileptic treatment after the first paroxysm. The factors shown above were evaluated in a group of 30 patients with solitary unprovoked epileptic seizure. Regarding recurrence of epileptic seizure, the only significant factor appeared to be initiation of treatment after the first unprovoked paroxysm (p<0.001). We observed a 30% and 33.33% risk of recurrence following the initial epileptic seizure in patients after the first unprovoked seizure in less than 1 and 3 years, respectively.     

Presence of multiple independent effects in risk loci of common complex human diseases

Many genetic loci and SNPs associated with many common complex human diseases and traits are now identified. The total genetic variance explained by these loci for a trait or disease, however, has often been very small. Much of the "missing heritability" has been revealed to be hidden in the genome among the large number of variants with small effects. Several recent studies have reported the presence of multiple independent SNPs and genetic heterogeneity in trait-associated loci. It is therefore reasonable to speculate that such a phenomenon could be common among loci known to be associated with a complex trait or disease. For testing this hypothesis, a total of 117 loci known to be associated with rheumatoid arthritis (RA), Crohn disease (CD), type 1 diabetes (T1D), or type 2 diabetes (T2D) were selected. The presence of multiple independent effects was assessed in the case-control samples genotyped by the Wellcome Trust Case Control Consortium study and imputed with SNP genotype information from the HapMap Project and the 1000 Genomes Project. Eleven loci with evidence of multiple independent effects were identified in the study, and the number was expected to increase at larger sample sizes and improved statistical power. The variance explained by the multiple effects in a locus was much higher than the variance explained by the single reported SNP effect. The results thus significantly improve our understanding of the allelic structure of these individual disease-associated loci, as well as our knowledge of the general genetic mechanisms of common complex traits and diseases.     

Estimation of variance components of quantitative traits in inbred populations

Use of variance-component estimation for mapping of quantitative-trait loci in humans is a subject of great current interest. When only trait values, not genotypic information, are considered, variance-component estimation can also be used to estimate heritability of a quantitative trait. Inbred pedigrees present special challenges for variance-component estimation. First, there are more variance components to be estimated in the inbred case, even for a relatively simple model including additive, dominance, and environmental effects. Second, more identity coefficients need to be calculated from an inbred pedigree in order to perform the estimation, and these are computationally more difficult to obtain in the inbred than in the outbred case. As a result, inbreeding effects have generally been ignored in practice. We describe here the calculation of identity coefficients and estimation of variance components of quantitative traits in large inbred pedigrees, using the example of HDL in the Hutterites. We use a multivariate normal model for the genetic effects, extending the central-limit theorem of Lange to allow for both inbreeding and dominance under the assumptions of our variance-component model. We use simulated examples to give an indication of under what conditions one has the power to detect the additional variance components and to examine their impact on variance-component estimation. We discuss the implications for mapping and heritability estimation by use of variance components in inbred populations.     

Accounting for Genetic Architecture Improves Sequence Based Genomic Prediction for a Drosophila Fitness Trait

The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.     

Investigation on circular asymmetry of geographical distribution in cancer mortality of Hiroshima atomic bomb survivors based on risk maps: analysis of spatial survival data

While there is a considerable number of studies on the relationship between the risk of disease or death and direct exposure from the atomic bomb in Hiroshima, the risk for indirect exposure caused by residual radioactivity has not yet been fully evaluated. One of the reasons is that risk assessments have utilized estimated radiation doses, but that it is difficult to estimate indirect exposure. To evaluate risks for other causes, including indirect radiation exposure, as well as direct exposure, a statistical method is described here that evaluates risk with respect to individual location at the time of atomic bomb exposure instead of radiation dose. In addition, it is also considered to split the risks into separate risks due to direct exposure and other causes using radiation dose. The proposed method is applied to a cohort study of Hiroshima atomic bomb survivors. The resultant contour map suggests that the region west to the hypocenter has a higher risk compared to other areas. This in turn suggests that there exists an impact on risk that cannot be explained by direct exposure.     

Recurrence risk of a new dominant mutation in children of unaffected parents.

Extensions to models originally described by Hartl for predicting the recurrence risk of new dominant mutations are developed in this paper. Additions to the models are (1) possible somatic mosaicism in a parent in some families, (2) the possibility that the parental origin of the mutation may or may not be known, and (3) mutation rates which change as a function of sex and/or time. The models indicate that recurrence risks are most critically affected by (a) the amount of somatic mosaicism which can be tolerated in the parent without manifesting disease and (b) knowledge of the parental origin of the mutation. In addition, there is a moderate effect on recurrence risks if mutation rates increase in the father as a function of time. Recurrence risks are at least as large as the risk of trisomy 21 in a child of a mother of age 35 years or older, probably much higher (5%-10%) when the mutation is known to be of maternal origin or if substantial somatic mosaicism in the parent is compatible with a normal phenotype. The recurrence risk of a new mutation is high because of a very high ascertainment bias of families with substantial germ-line mosaicism.     

Linkage strategies for genetically complex traits. I. Multilocus models

In order to investigate linkage detection strategies for genetically complex traits, multilocus models of inheritance need to be specified. Here, two types of multilocus model are described: (1) a multiplicative model, representing epistasis (interaction) among loci, and (2) an additive model, which is shown to closely approximate genetic heterogeneity, which is characterized by no interlocus interaction. A ratio lambda R of risk for type R relatives that is compared with population prevalence is defined. For a single-locus model, lambda R - 1 decreases by a factor of two with each degree of relationship. The same holds true for an additive multilocus model. For a multiplicative (epistasis) model, lambda R - 1 decreases more rapidly than by a factor of two with degree of relationship. Examination of lambda R values for various classes of relatives can potentially suggest the presence of multiple loci and epistasis. For example, data for schizophrenia suggest multiple loci in interaction. It is shown in the second paper of this series that lambda R is the critical parameter in determining power to detect linkage by using affected relative pairs.     

应用贝叶斯理论推断DNA分子标记基因型

引入贝叶斯理论用以从DNA分子标记的表现型（电泳谱带）推断其基因型（DNA来源）。结果表明,根据标记座位独立贫富而确定的遗传信息不完全标记的基因型概率,与根据邻近的遗传信息完全标记的基因型和有关重组率算得的相应贝叶斯概率,通常都有很大的差异,所以在进行数量性状基因定位和标记辅助选择等工作前前,应当计算每一个体基因组上所有遗传信息不完全座位的有关基因型的贝叶斯概率,文中列出计算未知基因型的贝叶斯概率的详细过程,也讨论了贝叶斯概率的若干推广应用。     

Change in Genetic Variance under Selection in a Self-Fertilizing Population

In this study we show how the genetic variance of a quantitative trait changes in a self-fertilizing population under repeated cycles of truncation selection, with the analysis based on the infinitesimal model in which it is assumed that the trait is determined by an infinite number of unlinked loci without epistasis. The genetic variance is reduced not as a consequence of the genotypic frequency change but due to the build-up of linkage disequilibrium under truncation selection in this model. We assume that the order of the genotypic contribution from each locus is n(-1/2), where n is the number of loci involved, and investigate the change in linkage disequilibrium resulting from selection and self-fertilization using genotypic frequency dynamics in order to analyze the change in the genetic variance. Our analysis gives recurrence relations of genetic variance among the succeeding generations for the three cases of gene action, i.e., purely additive action, pure dominance without additive effect and the presence of both additive effect and dominance, respectively. Numerical examples are also given as a check on the recurrence formulas.     

Therapeutic modulation of low-density lipoprotein size

Small, dense LDL particles have been linked to atherosclerosis, often in a cluster of risk factors and affecting approximately 20% of adults. Over the past year, studies confirmed that small dense LDL is an autosomal dominant trait, influenced mainly by hypertriglyceridaemia and obesity, insulin resistance and diabetes mellitus and some incompletely investigated genetic loci. Compositional and functional differences have been observed in small LDL. Evidence is emerging that lifestyle as well as pharmacological intervention can modulate LDL size, but there is no proof yet that this is of clinical benefit.