Testing for familial correlation in age-at-onset

The analysis of family-study data sometimes focuses on whether a dichotomous trait tends to cluster in families. For traits with variable age-at-onset, it may be of interest to investigate whether age-at-onset itself also exhibits familial clustering. A complication in such investigations is that censoring by age-at-ascertainment can induce artifactual familial correlation in the age-at-onset of affected members. A further complication can be that sample inclusion criteria involve the affection status of family members. The purpose here is to present an approach to testing for correlation that is not confounded by censoring by age-at-ascertainment and may be applied with a broad range of inclusion criteria. The approach involves regression statistics in which subjects's covariate terms are chosen to reflect age-at-onset information from the subjects's affected family members. The results of analyses of data from a family-study of panic disorder illustrate the approach.     

Testing concordance of clinical characteristics in familial studies with application to inflammatory bowel diseases

The etiology of chronic Inflammatory Bowel Diseases (IBD) remains unknown, with both genetic and environmental risk factors having been implicated. A recent collaborative study of IBD provides clinical data from families with three or more affected first-degree relatives. The scientific question is whether specific clinical characteristics aggregate among affected individuals within families. Gastroenterological researchers have examined the number of concordant familial pairs in familial aggregation studies, but methods and results have been discrepant. This article investigates concepts of concordance and gives a comprehensive statistical treatment for testing concordance of various clinical traits in familial studies. For dichotomous traits, the distribution of this statistic under the null hypothesis of no familial aggregation is obtained by three methods: asymptotic, probability generating function, and permutation. The permutation method is extended to analyze aggregation for non-dichotomous traits and co-aggregations between two traits. We apply the permutation method to analyze the aforementioned multiply-affected IBD family data. Evidence is found for familial clustering of various traits, some of which are not revealed in existing studies. Such analyses provide a basis for investigating the dependence of trait aggregation upon genetic or environmental risk factors.     

Structured exploratory data analysis (SEDA) of finger ridge-count inheritance: II. Association arrays in parent-offspring and sib-sib pairs

Familial similarity of the dermatoglyphic trait values of finger ridge-count scores and pattern intensity index is examined for 125 nuclear families from the Velanadu Brahmin population of Southern India by the method of association arrays. This methodology assesses parent-offspring and sibship similarity through a collection of measures of dependence that is sensitive to a variety of nonlinear trends and stochastic relationships between trait values. The method is used in conjunction with various weights to determine the relationship between family size and the level and form of dependence. These analyses reveal that siblings are most strongly associated for ridge-counts of the middle digit and less associated for the thumb and fifth digit ridge-counts. Further, sibship similarity for ridge-counts increases with family size for the thumb and fifth digit but remains relatively constant over all family sizes for the middle finger. Family size effects are also observed for total ridge-counts of the left hand, right hand, and both hands combined, and for the pattern intensity index. These effects of family size may be due to the most pronounced changes occurring in the amniotic environment between the first and second pregnancy, which are most strongly manifested in the sibship associations of smaller families.     

基于16S rRNA部分序列中国蝙蝠科蝙蝠系统发生分析

蝙蝠科蝙蝠遍布全世界,是蝙蝠中种类最多的一个科.尽管从形态学、胚胎学和分子生物学等方面认为蝙蝠科内长翼蝠亚科应该提升到科、鼠耳蝠属应该提升到亚科的分类地位,但是其科内的系统关系长期以来一直处于争议之中.本文对蝙蝠科11种38个标本线粒体16S rRNA部分序列进行了测序,并结合以前报道的13种(属于7科13属)蝙蝠的线粒体16S rRNA部分序列构建了系统树,结果表明:长翼蝠亚科可以提升到科的分类地位、鼠耳蝠属提升到亚科的分类地位,这与前人报道的结果一致;相对于由鼠耳蝠亚科、彩蝠亚科和管鼻蝠亚科构成的分支,蝙蝠亚科和Antrozoinae是一个并系群.蝙蝠亚科内的亲缘关系也进行了进一步的讨论.     

Linkage mapping of melanoma (MLM) using 172 microsatellite markers

The incidence of malignant melanoma is currently increasing faster than any other cancer and in 5-12% of cases occurs in a familial context in which the disease cosegregates as an autosomal dominant trait. To identify the location of genes that predipose individuals to familial melanoma (MLM), we have carried out linkage analysis in three large Australian melanoma pedigrees using 172 microsatellite markers spread across all autosomes. Three additional smaller families were typed for 70 of the same markers. In five of the six families we found lod scores between 1.0 and 2.3, which may provide evidence for the location of melanoma genes in proximity to some of these markers. If this turns out to be the case, these data potentially demonstrate that MLM is genetically heterogeneous since there was no marker for which all families gave significantly high LODs. These data provide the foundation for an exclusion map for melanoma and, more importantly, high-light areas of the genome for others to substantiate the potential positions of some of the genes that may be responsible for susceptibility to MLM.     

The embryology of angiosperms: Its broad application to the systematic and evolutionary study

Embryology allows one to work with a wide array of characters (more than 50 in general) for each taxon of angiosperms. This paper, while providing a brief review of recent studies on Myrtales and associated families by me and my co-workers, discusses evidence for the general utility of embryological characters for the study of plant systematics. In particular, evidence is given that characters of seed coat anatomy may be best applied to the study of specific and sectional (and even familial) relationships, those of seed appendages as well as of integumentary morphology and histogenesis to the study of generic relationships, and other major characters to the study of familial relationships. Embryology thus provides many features that are complex and, when properly applied along with evidence from other sources, offers good indications of relationships at various taxonomic level, from the ordinal to the specific level. Despite its evident systematic value and increasing need, however, information on embryological characters is still lacking for a majority of genera, and even at the family level, data is lacking or insufficiently available for more than 30% of families. Recipient of the Botanical Society Award for Young Scientists, 1987.     

Osteopenia in 37 members of seven families: analysis based on a model of dominant inheritance.

BACKGROUND: The genetic factors involved in determining bone mineral density (BMD) have not been fully elucidated. We have begun genetic linkage analysis of seven families in which many members are osteopenic, in order to identify chromosomal loci that are potentially involved in determining BMD. MATERIALS AND METHODS: Spine BMD was measured in 143 members of seven kindred with familial osteopenia. The absolute BMD values for the spine (L2-L4) were converted to the age-, gender-, and weight-adjusted Z scores, and this corrected value was used as the quantitative trait on which to base subsequent genetic analyses. Simulations of linkage were performed in order to determine the information content of the pedigree set, and actual linkage analysis was conducted using polymorphic markers either within or near three candidate loci: COL1A1, COL1A2, and vitamin D receptor (VDR). RESULTS: The distribution of the corrected Z scores was bimodal (p = 0.001) suggesting a monogenic mode of inheritance of the low BMD trait. Simulation of linkage analysis suggested that the family data set was sufficient to detect linkage under a single major gene model. Actual linkage analysis did not support linkage to the three candidate loci. In addition, the VDR genotype was not statistically associated with low bone density at the spine. CONCLUSIONS: Loci other than COL1A1, COL1A2 and VDR are very likely responsible for the low BMD trait observed in these families. These families are suitable for a genome-wide screen using microsatellite repeats in order to identify the loci that are involved in osteopenia.     

Association studies of QTL for multi-allele markers by mixed models

In this paper, we extend association study methods of both Fan et al. [Hum Hered 2002;53:130-145], in which a quantitative trait locus (QTL) and a multi-allele marker are considered for trio families, and Fan and Xiong [Biostatistics 2003, in press], in which a QTL and a bi-allelic marker are considered for nuclear families. The objective is to build mixed models for association study between a QTL and a multi-allelic marker for nuclear families with any number of offspring. Two types of nuclear family data are considered: the first is genetic data of offspring from at least one heterozygous parents, and the second is genetic data of offspring of nuclear family. (1) For the data of offspring from at least one heterozygous parents, we assume that at least one parent is heterozygous at the marker locus, and we may infer clearly the transmission of parental marker alleles to the offspring. We show that it can be used in association study in the presence of linkage. The theoretical basis is the difference between the conditional mean of trait value given an allele is transmitted and the conditional mean of trait value given the allele is not transmitted from a heterozygous parent. To build valid models, we calculate the variance covariance structure of trait values of offspring. Besides, the reduction of the number of parameters is discussed under an assumption of tight linkage between the trait locus and the marker. (2) For the data of offspring of nuclear family, we show that it can be used in general association study. In this case, the theoretical basis is the difference between the conditional mean of trait values given an allele is transmitted from a parent and the population mean. Then, we calculate variance-covariance structure of trait values of offspring. (3) Based on the theoretical analysis, mixed models are built for each type of the data, and related test statistics are proposed for association study. By power calculation and comparison, we show that, in some instances, the proposed test statistics have higher power than that by collapsing alleles to be new ones. The proposed models are used to analyze chromosomes 4 and chromosome 16 data of the Oxford asthma data, Genetic Analysis Workshop 12.     

Tracking of familial resemblance for resting blood pressure over time in the Québec Family Study

The etiology of familial resemblance for systolic (SBP) and diastolic (DBP) blood pressure, both within a single time point as well as across time points, was assessed to determine how familial etiologies underlying a trait may change across time. SBP and DBP measurements were taken roughly 12 years apart in family members participating in the longitudinal Québec Family Study. A longitudinal (bivariate) familial correlation model yields 3 types of correlations: intraindividual cross-time (e.g., father's BP at time 1 with his own BP at time 2); interindividual within-time (e.g., father time 1 with child time 1); and interindividual cross-time (e.g., father time 1 with child time 2). In addition, the change in BP across time (i.e., time 1-time 2) is examined using a univariate family correlation model. This combined method is useful in assessing the degree to which the same familial factors are operating across time (interindividual cross-time correlations), as well as the degree to which different heritable components are involved across time (change score). Maximal heritabilities for SBP were about 70% at each time point, while for DBP the heritability was larger at time 1 (87%) than time 2 (39%). Both the change scores (48% for SBP and 54% for DBP) and the cross-time comparisons (58% to 72% for SBP and 63% to 65% for DBP) evidenced significant familial resemblance. These results illustrate how simple methodologies can be used to specify how familial etiologies underlying a trait may change across time. For BP, the model includes unique familial factors that are specific to each time measurement, and an additional familial factor which is common to both time points. The factors leading to differences in longitudinal familial resemblance for BP (i.e., the unique factors) may be primarily genetic in origin, while those leading to stability across time may include both genetic and familial environmental effects. Sex and/or age interactions with the genotypes are also suggested.     

The Contribution of GWAS Loci in Familial Dyslipidemias

Familial combined hyperlipidemia (FCH) is a complex and common familial dyslipidemia characterized by elevated total cholesterol and/or triglyceride levels with over five-fold risk of coronary heart disease. The genetic architecture and contribution of rare Mendelian and common variants to FCH susceptibility is unknown. In 53 Finnish FCH families, we genotyped and imputed nine million variants in 715 family members with DNA available. We studied the enrichment of variants previously implicated with monogenic dyslipidemias and/or lipid levels in the general population by comparing allele frequencies between the FCH families and population samples. We also constructed weighted polygenic scores using 212 lipid-associated SNPs and estimated the relative contributions of Mendelian variants and polygenic scores to the risk of FCH in the families. We identified, across the whole allele frequency spectrum, an enrichment of variants known to elevate, and a deficiency of variants known to lower LDL-C and/or TG levels among both probands and affected FCH individuals. The score based on TG associated SNPs was particularly high among affected individuals compared to non-affected family members. Out of 234 affected FCH individuals across the families, seven (3%) carried Mendelian variants and 83 (35%) showed high accumulation of either known LDL-C or TG elevating variants by having either polygenic score over the 90^th percentile in the population. The positive predictive value of high score was much higher for affected FCH individuals than for similar sporadic cases in the population. FCH is highly polygenic, supporting the hypothesis that variants across the whole allele frequency spectrum contribute to this complex familial trait. Polygenic SNP panels improve identification of individuals affected with FCH, but their clinical utility remains to be defined.     

Genomic BLUP Decoded: A Look into the Black Box of Genomic Prediction

Genomic best linear unbiased prediction (BLUP) is a statistical method that uses relationships between individuals calculated from single-nucleotide polymorphisms (SNPs) to capture relationships at quantitative trait loci (QTL). We show that genomic BLUP exploits not only linkage disequilibrium (LD) and additive-genetic relationships, but also cosegregation to capture relationships at QTL. Simulations were used to study the contributions of those types of information to accuracy of genomic estimated breeding values (GEBVs), their persistence over generations without retraining, and their effect on the correlation of GEBVs within families. We show that accuracy of GEBVs based on additive-genetic relationships can decline with increasing training data size and speculate that modeling polygenic effects via pedigree relationships jointly with genomic breeding values using Bayesian methods may prevent that decline. Cosegregation information from half sibs contributes little to accuracy of GEBVs in current dairy cattle breeding schemes but from full sibs it contributes considerably to accuracy within family in corn breeding. Cosegregation information also declines with increasing training data size, and its persistence over generations is lower than that of LD, suggesting the need to model LD and cosegregation explicitly. The correlation between GEBVs within families depends largely on additive-genetic relationship information, which is determined by the effective number of SNPs and training data size. As genomic BLUP cannot capture short-range LD information well, we recommend Bayesian methods with t-distributed priors.     

Taxon sampling, correlated evolution, and independent contrasts

Independent contrasts are widely used to incorporate phylogenetic information into studies of continuous traits, particularly analyses of evolutionary trait correlations, but the effects of taxon sampling on these analyses have received little attention. In this paper, simulations were used to investigate the effects of taxon sampling patterns and alternative branch length assignments on the statistical performance of correlation coefficients and sign tests; "full-tree" analyses based on contrasts at all nodes and "paired-comparisons" based only on contrasts of terminal taxon pairs were also compared. The simulations showed that random samples, with respect to the traits under consideration, provide statistically robust estimates of trait correlations. However, exact significance tests are highly dependent on appropriate branch length information; equal branch lengths maintain lower Type I error than alternative topological approaches, and adjusted critical values of the independent contrast correlation coefficient are provided for use with equal branch lengths. Nonrandom samples, with respect to univariate or bivariate trait distributions, introduce discrepancies between interspecific and phylogenetically structured analyses and bias estimates of underlying evolutionary correlations. Examples of nonrandom sampling processes may include community assembly processes, convergent evolution under local adaptive pressures, selection of a nonrandom sample of species from a habitat or life-history group, or investigator bias. Correlation analyses based on species pairs comparisons, while ignoring deeper relationships, entail significant loss of statistical power and as a result provide a conservative test of trait associations. Paired comparisons in which species differ by a large amount in one trait, a method introduced in comparative plant ecology, have appropriate Type I error rates and high statistical power, but do not correctly estimate the magnitude of trait correlations. Sign tests, based on full-tree or paired-comparison approaches, are highly reliable across a wide range of sampling scenarios, in terms of Type I error rates, but have very low power. These results provide guidance for selecting species and applying comparative methods to optimize the performance of statistical tests of trait associations.     

A parametric copula model for analysis of familial binary data

Modeling the joint distribution of a binary trait (disease) within families is a tedious challenge, owing to the lack of a general statistical model with desirable properties such as the multivariate Gaussian model for a quantitative trait. Models have been proposed that either assume the existence of an underlying liability variable, the reality of which cannot be checked, or provide estimates of aggregation parameters that are dependent on the ordering of family members and on family size. We describe how a class of copula models for the analysis of exchangeable categorical data can be incorporated into a familial framework. In this class of models, the joint distribution of binary outcomes is characterized by a function of the given marginals. This function, referred to as a "copula," depends on an aggregation parameter that is weakly dependent on the marginal distributions. We propose to decompose a nuclear family into two sets of equicorrelated data (parents and offspring), each of which is characterized by an aggregation parameter (alphaFM and alphaSS, respectively). The marginal probabilities are modeled through a logistic representation. The advantage of this model is that it provides estimates of the aggregation parameters that are independent of family size and does not require any arbitrary ordering of sibs. It can be incorporated easily into segregation or combined segregation-linkage analysis and does not require extensive computer time. As an illustration, we applied this model to a combined segregation-linkage analysis of levels of plasma angiotensin I-converting enzyme (ACE) dichotomized into two classes according to the median. The conclusions of this analysis were very similar to those we had reported in an earlier familial analysis of quantitative ACE levels.     

Infection-Triggered Familial or Recurrent Cases of Acute Necrotizing Encephalopathy Caused by Mutations in a Component of the Nuclear Pore, RANBP2

Acute necrotizing encephalopathy (ANE) is a rapidly progressive encephalopathy that can occur in otherwise healthy children after common viral infections such as influenza and parainfluenza. Most ANE is sporadic and nonrecurrent (isolated ANE). However, we identified a 7 Mb interval containing a susceptibility locus (ANE1) in a family segregating recurrent ANE as an incompletely penetrant, autosomal-dominant trait. We now report that all affected individuals and obligate carriers in this family are heterozygous for a missense mutation (c.1880C→T, p.Thr585Met) in the gene encoding the nuclear pore protein Ran Binding Protein 2 (RANBP2). To determine whether this mutation is the susceptibility allele, we screened controls and other patients with ANE who are unrelated to the index family. Patients from 9 of 15 additional kindreds with familial or recurrent ANE had the identical mutation. It arose de novo in two families and independently in several other families. Two other patients with familial ANE had different RANBP2 missense mutations that altered conserved residues. None of the three RANBP2 missense mutations were found in 19 patients with isolated ANE or in unaffected controls. We conclude that missense mutations in RANBP2 are susceptibility alleles for familial and recurrent cases of ANE.     

Family affiliation,sex ratio and sporophyte frequency in unisexual mosses

Patterns of sex expression and sex ratios are key features of the life histories of organisms. Bryophytes are the only haploid‐dominant land plants. In contrast with seed plants, more than half of bryophyte species are dioecious, with rare sexual expression and sporophyte formation and a commonly female‐biased sex ratio. We asked whether variation in sex expression, sex ratio and sporophyte frequency in ten dioecious pleurocarpous wetland mosses of two different families was best explained by assuming that character states evolved: (1) in ancestors within the respective families or (2) at the species level as a response to recent habitat conditions. Lasso regression shrinkage identified relationships between family membership and sex ratio and sporophyte frequency, whereas environmental conditions were not correlated with any investigated reproductive trait. Sex ratio and sporophyte frequency were correlated with each other. Our results suggest that ancestry is more important than the current environment in explaining reproductive patterns at and above the species level in the studied wetland mosses, and that mechanisms controlling sex ratio and sporophyte frequency are phylogenetically conserved. Obviously, ancestry should be considered in the study of reproductive character state variation in plants. © 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2014, 174 , 163–172.     

Linkage analysis of a cluster-based quantitative phenotype constructed from pulmonary function test data in 27 multigenerational families with multiple asthmatic members

OBJECTIVE: To identify genes involved in phenotypes that increase one's risk for developing asthma, a complex disease that is likely genetically heterogeneous. Unlike other approaches to locus discovery in the presence of heterogeneity, this method seeks loci that segregate in all or most ascertained families while recognizing that other genes and environmental factors that modify the action of the common gene may vary across families. METHODS: The method is based on seeking groups of families that differ, between groups, in the way affected individuals express the genotype. Then we use the distance of each individual to the cluster center for his family to define a quantitative trait. This quantitative trait is then subjected to a genome scan using variance components methods. RESULTS: The method is applied to a data set of 27 multigenerational families with asthma, and a novel locus at 2q33 (at 210 cM) is identified. CONCLUSIONS: The proposed method has the potential to identify loci near genes that increase risk for asthma related phenotypes. The method could be used for other complex disorders that exhibit locus heterogeneity.     

Multivariate Extensions of the Mixed Model for Quantitative Traits

The mixed model for complex segregation analysis of quantitative data from three-generational nuclear families is extended to the multivariate case. Likelihood functions for hypothesis testing are derived for two types of conditional analysis of multiple traits: first when entry to the study depends on the index case's values of all the quantitative traits that are of interest, and second when entry depends on only one trait, but other correlated traits are to be studied simultaneously. Using direct products of covariance matrices, these functions are seen to be direct multivariate equivalence of the univariate functions.     

Elevational trends of biodiversity and plant traits do not converge—a test in the Helan Range, NW China

When elevational gradients include combinations of different climatic gradients, such as a decline in temperature combined with an increase in moisture, vegetation and plant trait responses are difficult to explain. Here, we used plant species richness and morphometric traits data across steep elevational gradients in the Helan Range of Northwestern China in an attempt to separate general trends (temperature related) from regional peculiarity (moisture related). Based on the floristic data of the Helan Range as well as plot-based data, both drought (at low elevation) and low temperature (high elevation) are associated with low species richness presumably also explaining the peak in diversity at mid-elevation, where climatic conditions are moderate. However, this mid-elevation peak in diversity is not mirrored in trends of plant traits such as leaf size and inflorescence size, which show either unidirectional trends or no change with elevation (with impacts of drought and low temperature perhaps gradually replacing each other). Our analysis illustrated the taxonomic and plant functional type (PFT)-related biases in functional trait studies and showed that consistent patterns only emerge after careful data stratification, with taxonomy (family level) holding more promises than PFTs. Inflorescence size increased with elevation in major insect-pollinated families, a trend not seen in wind-pollinated (graminoid) families. However, the reproductive effort expressed as inflorescence/leaf length ratio increases with elevation in the majority of plant families, irrespective of their pollination system. The fact that these biometric responses to elevation do not correlate with responses in species richness (which peaks at mid-elevation) may reflect contrasting drivers of trait selection and biodiversity. Based on our plot-based data, this analysis also confirmed the usefulness of floristic archive data for testing ecological theory related to elevational gradients.     

Association of the heart fatty acid-binding protein (FABP3) gene with milk traits in Manchega breed sheep

The ovine fatty acid-binding protein type 3 gene has been chosen as a functional candidate gene for milk traits. Two different single nucleotide polymorphisms (SNPs) of ovine FABP3 gene have been tested in a daughter design comprising 13 families. No association was found between estimated breeding values for milk yield, protein and fat contents (FC) and genotypes across families using anova and transmission disequilibrium test (TDT). In within-family analysis, one family showed a significant effect for FC. These results could indicate linkage disequilibrium between the FABP3 gene and a quantitative trait loci (QTL) for FC, with the heterozygous genotype associated with a positive effect in this trait.     

The Allometry of Bee Proboscis Length and Its Uses in Ecology

Allometric relationships among morphological traits underlie important patterns in ecology. These relationships are often phylogenetically shared; thus quantifying allometric relationships may allow for estimating difficult-to-measure traits across species. One such trait, proboscis length in bees, is assumed to be important in structuring bee communities and plant-pollinator networks. However, it is difficult to measure and thus rarely included in ecological analyses. We measured intertegular distance (as a measure of body size) and proboscis length (glossa and prementum, both individually and combined) of 786 individual bees of 100 species across 5 of the 7 extant bee families (Hymenoptera: Apoidea: Anthophila). Using linear models and model selection, we determined which parameters provided the best estimate of proboscis length. We then used coefficients to estimate the relationship between intertegular distance and proboscis length, while also considering family. Using allometric equations with an estimation for a scaling coefficient between intertegular distance and proboscis length and coefficients for each family, we explain 91% of the variance in species-level means for bee proboscis length among bee species. However, within species, individual-level intertegular distance was a poor predictor of individual proboscis length. To make our findings easy to use, we created an R package that allows estimation of proboscis length for individual bee species by inputting only family and intertegular distance. The R package also calculates foraging distance and body mass based on previously published equations. Thus by considering both taxonomy and intertegular distance we enable accurate estimation of an ecologically and evolutionarily important trait.