Biomedical subjects

Chang-Xing Ma

Publications and source records attributed to Chang-Xing Ma.

At least 19 recordsLinked to original sources

PubMed2006

The risk of birth defects in multiple births: a population-based study.

OBJECTIVES: To determine if multiple births have higher risks of birth defects compared to singletons and to identify types of birth defects that occur more frequently in multiple births, controlling for seven sociodemographic and health-related variables. METHODS: A retrospective cohort study was conducted of all resident live births in Florida during 1996-2000 using data from a population-based surveillance system. Birth defects were defined as in the 9th edition of the International Classification of Diseases-Clinical Modification (ICD-9-CM) code for the 42 reportable categories in the Centers for Disease Control and Prevention (CDC) Birth Defects Registry list and eight major birth defects classifications. Relative risks (RR) before and after adjusting for control variables and 95% confidence intervals (95% CI) were calculated. The control variables included mother's race, age, previous adverse pregnancy experience, education, Medicaid participation during pregnancy, infant's sex and number of siblings. RESULTS: This study included 972,694 live births (27,727 multiple births and 944,967 singletons). Birth defects prevalence per 10,000 live births was 358.50 for multiple births and 250.54 for singletons. After adjusting for control variables, multiple births had a 46% increased risk of birth defects compared to singletons. Higher risks were found in 23 of 40 birth defects for multiple births. Five highest adjusted relative risks for birth defects among multiple births were: anencephalus, biliary atresia, hydrocephalus without spina bifida, pulmonary valve atresia and stenosis, and bladder exstrophy. Increased risks were also found in 6 out of 8 major birth defects classifications. CONCLUSIONS: Multiple births have increased risks of birth defects compared to singletons.

Adult↗

PubMed2005

Functional mapping of quantitative trait loci that interact with the hg mutation to regulate growth trajectories in mice.

The high growth (hg) mutation increases body size in mice by 30-50%. Given the complexity of the genetic regulation of animal growth, it is likely that the effect of this major locus is mediated by other quantitative trait loci (QTL) with smaller effects within a web of gene interactions. In this article, we extend our functional mapping model to characterize modifier QTL that interact with the hg locus during ontogenetic growth. Our model is derived within the maximum-likelihood context, incorporated by mathematical aspects of growth laws and implemented with the EM algorithm. In an F2 population founded by a congenic high growth (HG) line and non-HG line, a highly additive effect due to the hg gene was detected on growth trajectories. Three QTL located on chromosomes 2 and X were identified to trigger significant additive and/or dominant effects on the process of growth. The most significant finding made from our model is that these QTL interact with the hg locus to affect the shapes of the growth process. Our model provides a powerful means for understanding the genetic architecture and regulation of growth rate and body size in mammals.

Age Factors↗

PubMed2005

A general framework for statistical linkage analysis in multivalent tetraploids.

In multivalent polyploids, simultaneous pairings among homologous chromosomes at meiosis result in a unique cytological phenomenon-double reduction. Double reduction casts an impact on chromosome evolution in higher plants, but because of its confounded effect on the pattern of gene cosegregation, it complicates linkage analysis and map construction with polymorphic molecular markers. In this article, we have proposed a general statistical model for simultaneously estimating the frequencies of double reduction, the recombination fraction, and optimal parental linkage phases between any types of markers, both fully and partially informative, or dominant and codominant, for a tetraploid species that undergoes only multivalent pairing. This model provides an in-depth extension of our earlier linkage model that was built upon Fisher's classifications for different gamete formation modes during the polysomic inheritance of a multivalent polyploid. By implementing a two-stage hierarchical EM algorithm, we derived a closed-form solution for estimating the frequencies of double reduction through the estimation of gamete mode frequencies and the recombination fraction. We performed different settings of simulation studies to demonstrate the statistical properties of our model for estimating and testing double reduction and the linkage in multivalent tetraploids. As shown by a comparative analysis, our model provides a general framework that covers existing statistical approaches for linkage mapping in polyploids that are predominantly multivalent. The model will have great implications for understanding the genome structure and organization of polyploid species.

Algorithms↗

PubMed2005

Sex differences in birth defects: a study of opposite-sex twins.

BACKGROUND: Sex differences in structural birth defects are often confounded by environmental risk factors. Opposite-sex twins provide a unique model for detecting sex differences in birth defects while maximally controlling environmental risk factors in a natural setting. METHODS: Population data from the Florida Birth Defects Registry were analyzed. A total of 4,768 pairs of twins who were discordant for sex and born between 1996 and 2001 were analyzed. The McNemar test was used to compare the differences between a male twin and his twin sister for the risk of developing specific defects and organ-system defects. RESULTS: Of 4,768 twin pairs, 225 males (4.72%) and 175 females (3.67%) had birth defects. Among opposite-sex twin pairs, males had a 29% higher risk for birth defects than their twin sisters. Compared to their twin sisters, males had a 5.4 times higher risk for pyloric stenosis and a 2.4 times higher risk for obstructive genitourinary defect, but only one-tenth the risk for congenital hip dislocation. CONCLUSIONS: Sex differences in birth defects exist between opposite-sex twins.

Congenital Abnormalities↗

PubMed2005

Mechanistic mapping of ontogenetic growth based on biological principles.

Ontogenetic growth can be described by mathematical equations constructed on the goodness of fit. Recently, the biological mechanism underlying mathematical growth equations has been explored using basic cellular properties. Here, we derive a general statistical model for understanding the genetic regulation of ontogenetic growth by integrating those biologically-proven meaningful growth equations into a quantitative trait locus (QTL) mapping framework. We can characterize the dynamic patterns of effects of QTL governing growth curves and estimate the global effect of the underlying QTL throughout the entire course of growth. The model provides the basis for deciphering genetic relationships for growth rates and the timing of life history events for any kind of organisms.

Animals↗

PubMed2004

FunMap: functional mapping of complex traits.

SUMMARY: FunMap is a Web-based user interface designed to map quantitative trait loci (QTL) affecting function-valued traits or infinite-dimensional traits in well-structured pedigrees or natural populations. User input includes three files: longitudinal trait data, marker genotypes and/or a linkage map. This software allows for a systematic genome-wide scan and significance test of QTL throughout the map. The dynamic change of QTL effects during the time course of growth is automatically drawn, from which specific biological hypotheses regarding the genetic control mechanisms of growth and development can be tested. AVAILABILITY: http://web.biostat.ufl.edu/~cma/genetics/software.html

Chromosome Mapping↗

PubMed2004

Risk factors for infant maltreatment: a population-based study.

CONTEXT: Of the approximately 900,000 children who were determined to be victims of abuse or neglect by US child protective services in 2002, the birth-to-3 age group had the highest rate of victimization (1.6%) and children younger than 1 accounted for the largest percentage of victims (9.6%). OBJECTIVE: To identify perinatal and sociodemographic risk factors associated with maltreatment of infants up to 1 year of age. DESIGN AND SETTING: Observational cohort study. PARTICIPANTS: 189,055 children born in 1996 in Florida. MAIN OUTCOME MEASURE: Infant maltreatment, defined as a verified report of abuse, neglect, or threatened harm that occurred between day 3 of life and 1 year. RESULTS: 1,602 children (.85%) of the 1996 birth cohort had verified instances of maltreatment by age 1. Of 15 perinatal and sociodemographic variables studied, 11 were found to be significantly related to infant maltreatment. Five factors had adjusted relative risks (RR) of two or greater: Mother smoked during pregnancy (RR 2.8); more than two siblings (RR 2.7); Medicaid beneficiary (RR 2.1); unmarried marital status (RR 2.0); low birth weight infant (RR 2.0). Infants who had four of these five risk factors had a maltreatment rate seven times higher than the population average. CONCLUSIONS: Data on nearly all risk factors found to be significantly associated with infant maltreatment are available on the birth certificate. Such information can be incorporated into a population-based risk-assessment tool that could identify subpopulations at highest risk for infant maltreatment. Because resources are limited, these groups should be given priority for enrollment in child abuse prevention programs.

Child Abuse↗

PubMed2004

A mixed polyploid model for linkage analysis in outcrossing tetraploids using a pseudo-test backcross design.

Based on how chromosomes pair at meiosis, the nature of polyploids can be described by bivalent polyploids, multivalent polyploids, and mixed polyploids. In bivalent polyploids, only two chromosomes pair, during which two more similar chromosomes have a higher pairing probability (preferential pairing) than two less similar chromosomes, whereas in multivalent polyploids more than two chromosomes pair at a time, which results in double reduction. Preferential chromosome pairings and double reduction affect the frequencies of gamete formation and, therefore, linkage analysis of polymorphic markers in bivalent and multivalent polyploids, respectively. For mixed polyploids, in which both bivalent and multivalent formations occur simultaneously, linkage analysis is affected by both preferential pairings and double reduction. In this study, we develop a hierarchical maximum likelihood model for discerning gamete genotypes derived from different pairing mechanisms and different formation modes. The first-stage model in the hierarchy is formulated to characterize the relative frequencies of bivalent and multivalent pairing configurations in terms of the preferential pairing factor. The second-stage model is derived to rule out identical gamete genotypes into their different formation modes with relative probabilities determined by the recombination fraction. The first-stage pairing mechanism and second-stage formation mode are integrated to provide the simultaneous maximum likelihood estimates of the preferential pairing factor, the frequency of double reduction, and the recombination fraction, by implementing the EM algorithm. We performed extensive simulation studies to demonstrate the statistical properties of our hierarchical model for linkage analysis in tetraploids. The implications of our model for polyploid linkage mapping are discussed.

Algorithms↗

PubMed2004

Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model.

The incorporation of developmental control mechanisms of growth has proven to be a powerful tool in mapping quantitative trait loci (QTL) underlying growth trajectories. A theoretical framework for implementing a QTL mapping strategy with growth laws has been established. This framework can be generalized to an arbitrary number of time points, where growth is measured, and becomes computationally more tractable, when the assumption of variance stationarity is made. In practice, however, this assumption is likely to be violated for age-specific growth traits due to a scale effect. In this article, we present a new statistical model for mapping growth QTL, which also addresses the problem of variance stationarity, by using a transform-both-sides (TBS) model advocated by Carroll and Ruppert (1984, Journal of the American Statistical Association 79, 321-328). The TBS-based model for mapping growth QTL cannot only maintain the original biological properties of a growth model, but also can increase the accuracy and precision of parameter estimation and the power to detect a QTL responsible for growth differentiation. Using the TBS-based model, we successfully map a QTL governing growth trajectories to a linkage group in an example of forest trees. The statistical and biological properties of the estimates of this growth QTL position and effect are investigated using Monte Carlo simulation studies. The implications of our model for understanding the genetic architecture of growth are discussed.

Biometry↗

PubMed2004

A fast algorithm for functional mapping of complex traits.

By integrating the underlying developmental mechanisms for the phenotypic formation of traits into a mapping framework, functional mapping has emerged as an important statistical approach for mapping complex traits. In this note, we explore the feasibility of using the simplex algorithm as an alternative to solve the mixture-based likelihood for functional mapping of complex traits. The results from the simplex algorithm are consistent with those from the traditional EM algorithm, but the simplex algorithm has considerably reduced computational times. Moreover, because of its nonderivative nature and easy implementation with current software, the simplex algorithm enjoys an advantage over the EM algorithm in the dynamic modeling and analysis of complex traits.

Algorithms↗

PubMed2004

A bivalent polyploid model for mapping quantitative trait loci in outcrossing tetraploids.

Two major aspects have made the genetic and genomic study of polyploids extremely difficult. First, increased allelic or nonallelic combinations due to multiple alleles result in complex gene actions and interactions for quantitative trait loci (QTL) in polyploids. Second, meiotic configurations in polyploids undergo a complex biological process including either bivalent or multivalent formation, or both. For bivalent polyploids, different degrees of preferential chromosome pairings may occur during meiosis. In this article, we develop a maximum-likelihood-based model for mapping QTL in tetraploids by considering the quantitative inheritance and meiotic mechanism of bivalent polyploids. This bivalent polyploid model is implemented with the EM algorithm to simultaneously estimate QTL position, QTL effects, and QTL-marker linkage phases by incorporating the impact of a cytological parameter determining bivalent chromosome pairings (the preferential pairing factor). Simulation studies are performed to investigate the performance and robustness of our statistical method for parameter estimation. The implication and extension of the bivalent polyploid model are discussed.

Algorithms↗

PubMed2004

A general framework for analyzing the genetic architecture of developmental characteristics.

The genetic architecture of growth traits plays a central role in shaping the growth, development, and evolution of organisms. While a limited number of models have been devised to estimate genetic effects on complex phenotypes, no model has been available to examine how gene actions and interactions alter the ontogenetic development of an organism and transform the altered ontogeny into descendants. In this article, we present a novel statistical model for mapping quantitative trait loci (QTL) determining the developmental process of complex traits. Our model is constructed within the traditional maximum-likelihood framework implemented with the EM algorithm. We employ biologically meaningful growth curve equations to model time-specific expected genetic values and the AR(1) model to structure the residual variance-covariance matrix among different time points. Because of a reduced number of parameters being estimated and the incorporation of biological principles, the new model displays increased statistical power to detect QTL exerting an effect on the shape of ontogenetic growth and development. The model allows for the tests of a number of biological hypotheses regarding the role of epistasis in determining biological growth, form, and shape and for the resolution of developmental problems at the interface with evolution. Using our newly developed model, we have successfully detected significant additive x additive epistatic effects on stem height growth trajectories in a forest tree.

Algorithms↗

PubMed2003

Functional mapping for quantitative trait loci governing growth rates: a parametric model.

Are there-specific quantitative trait loci (QTL) governing growth rates in biology? This is emerging as an exciting but challenging question for contemporary developmental biology, evolutionary biology, and plant and animal breeding. In this article, we present a new statistical model for mapping QTL underlying age-specific growth rates. This model is based on the mechanistic relationship between growth rates and ages established by a variety of mathematical functions. A maximum likelihood approach, implemented with the EM algorithm, is developed to provide the estimates of QTL position, growth parameters characterized by QTL effects, and residual variances and covariances. Based on our model, a number of biologically important hypotheses can be formulated concerning the genetic basis of growth. We use forest trees as an example to demonstrate the power of our model, in which a QTL for stem growth diameter growth rates is successfully mapped to a linkage group constructed from polymorphic markers. The implications of the new model are discussed.

Age Factors↗

PubMed2003

Exponential mapping of quantitative trait loci governing allometric relationships in organisms.

Allometric scaling relationships or quarter-power rules, as a universal biological law, can be viewed as having some genetic component, and the particular genes (or quantitative trait loci, QTL) underlying these allometric relationships can be mapped using molecular markers. We develop a mathematical and statistical model for mapping allometric QTL on the basis of nonlinear power functions using Taylor's approximation theory. Simulation studies indicate that the QTL position and effect can be estimated using our model, but the estimation precision can be improved from the higher- over lower-order approximation when the sample size used and gene effects are small. The application of our approach in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship between 3rd-year stem height and 3rd-year stem biomass. It is expected that our model will have broad implications for genetic, evolutionary, biomedical and breeding research.

Algorithms↗

PubMed2003

Quantitative trait loci for growth trajectories in Populus.

Growth trajectories are a biological process important to plant and animal breeding, and to evolutionary genetic studies. In this article, we report the detection of quantitative trait loci (QTLs) responsible for growth trajectories in poplars that are used as a model system for the study of forest biology. These QTLs were localized on a genetic linkage map of polymorphic markers using a statistical mapping method incorporating growth-curve models. The effects of the QTLs on growth are described as a function of age, so that age-specific changes in QTL effects can be readily projected throughout the entire growth process. The QTLs identified display increased effects on growth when trees age, yet the timing of QTL activation is earlier for stem height than diameter, which is consistent with the ecological viewpoint of canopy competition. The implications of the results for breeding and silviculture are discussed.

Genetic Linkage↗

PubMed2002

An improved genetic model generates high-resolution mapping of QTL for protein quality in maize endosperm.

The genetic mapping of polymorphic markers in a cross between two inbred plant lines has proven to be a powerful method for detecting quantitative trait loci (QTL) underlying complex traits. However, existing methods of QTL mapping were developed for disomic inheritance of both marker and QTL loci in a diploid population. To map QTL influencing traits expressed in the endosperm, a triploid embryo-nourishing tissue resulting from double fertilization, existing QTL mapping models require modification to consider the trisomic inheritance of the endosperm and the generation difference between the mapping population and the endosperm. Such a model requires simultaneous use of two successive generations, which theoretically can lead to an increase in resolution for QTL mapping compared with the use of a single backcross or F(2) generation. Using a newly developed model based on these considerations, we demonstrate the improved resolution of QTL, influencing protein quality traits in maize endosperm. The increased resolution made possible with this approach makes identified QTL accessible to positional cloning.

Chromosome Mapping↗

PubMed2002

A hierarchical statistical model for estimating population properties of quantitative genes.

BACKGROUND: Earlier methods for detecting major genes responsible for a quantitative trait rely critically upon a well-structured pedigree in which the segregation pattern of genes exactly follow Mendelian inheritance laws. However, for many outcrossing species, such pedigrees are not available and genes also display population properties. RESULTS: In this paper, a hierarchical statistical model is proposed to monitor the existence of a major gene based on its segregation and transmission across two successive generations. The model is implemented with an EM algorithm to provide maximum likelihood estimates for genetic parameters of the major locus. This new method is successfully applied to identify an additive gene having a large effect on stem height growth of aspen trees. The estimates of population genetic parameters for this major gene can be generalized to the original breeding population from which the parents were sampled. A simulation study is presented to evaluate finite sample properties of the model. CONCLUSIONS: A hierarchical model was derived for detecting major genes affecting a quantitative trait based on progeny tests of outcrossing species. The new model takes into account the population genetic properties of genes and is expected to enhance the accuracy, precision and power of gene detection.

Algorithms↗

PubMed2002

Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing species.

With the advent of new molecular marker technologies, it is now feasible to initiate genome projects for outcrossing plant species, which have not received much attention in genetic research, despite their great agricultural and environmental value. Because outcrossing species typically have heterogeneous genomes, data structure for molecular markers representing an entire genome is complex: some markers may have more alleles than others, some markers are codominant whereas others are dominant, and some markers are heterozygous in one parent but fixed in the other parent whereas the opposite can be true for other markers. A major difficulty in analyzing these different types of marker at the same time arises from uncertainty about parental linkage phases over markers. In this paper, we present a general maximum-likelihood-based algorithm for simultaneously estimating linkage and linkage phases for a mixed set of different marker types containing fully informative markers (segregating 1:1:1:1) and partially informative markers (or missing markers, segregating 1:2:1, 3:1, and 1:1) in a full-sib family derived from two outbred parent plants. The characterization of linkage phases is based on the posterior probability distribution of the assignment of alternative alleles at given markers to two homologous chromosomes of each parent, conditional on the observed phenotypes of the markers. Two- and multi-point analyses are performed to estimate the recombination fraction and determine the most likely linkage phase between different types of markers. A numerical example is presented to demonstrate the statistical properties of the model for characterizing the linkage phase between markers.

Algorithms↗