Estimation of individual genetic and environmental profiles in longitudinal designs

Parameter estimates obtained in the genetic analysis of longitudinal data can be used to construct individual genetic and environmental profiles across time. Such individual profiles enable the attribution of individual phenotypic change to changes in the underlying genetic or environmental processes and may lead to practical applications in genetic counseling and epidemiology. Simulations show that individual estimates of factor scores can be reliably obtained. Decomposition of univariate, and to a lesser extent of bivariate, phenotypic time series may yield estimates of independent individual G(t) and E(t), however, that are intercorrelated. The magnitude of these correlations depends somewhat on the autocorrelation structure of the underlying series, but to obtain completely independent estimates of genetic and environmental individual profiles, at least three measured indicators are needed at each point in time. KEY WORDS: longitudinal genetic analysis; environmental profiles; genetic profiles; factor scores; Kalman filter

LISREL analysis of twin data with structured means

Introduces a method to test the hypothesis that the phenotypic means and the phenotypic covariances can be modeled with the same common genetic and environmental factors. LISREL can be used to implement the method. An illustration with simulated twin data is provided

Application of nonlinear factor analysis to genotype-environment interaction

The intention of this paper is to show how the methods of nonlinear factor analysis as developed by McDonald (Br. J. Math. Stat. Psychol. 20:205-215, 1967) can be used to study genotype-environment interaction. The method is applied to the interaction of genotype and within-family en-vironmental influences. Simulated twin data are used to illustrate how this type of interaction may be detected and estimated. It is shown that estimates of genetic influences are not affected by G x E interaction. KEY WORDS: genotype-environment interaction; nonlinear factor analysis; twin data

Automated approach for optimizing dynamic systems

The optimal design of nonlinear dynamic systems can be formulated as a multicriteria optimization problem. On the basis of a multibody system model integral type objective functions are defined evaluating the dynamic behavior of the system under consideration. Multicriteria optimization methods reduce the problem to nonlinear programming problems which can be solved with standard algorithms like the SQP method. The gradients required for such an efficient optimization procedure are computed by solving, additional differential equations resulting from an adjoint variable approach. The whole design process can be highly automated by using computer algebra packages

Simultaneous genetic analysis of longitudinal means and covariance structure in the simplex model using twin data

A longitudinal model based on the simplex model is presented to analyze simultaneously means and covariance structure using univariate longitudinal twin data. The objective of the model is to decompose the mean trend into components which can be attributed to those genetic and environmental factors which give rise to phenotypic individual differences and a component of unknown constitution which does not involve individual differences. Illustrations are given using simulated data and repeatedly measured weight obtained in a sample of 82 female twin pairs on sbc occasions. KEY WORDS: repeated measures; genetic and environmental covariance structure; mean trend; longitudinal twin data; genetic simplex mode; LISREL

Measurement scheduling for recursive team estimation

We consider a decentralized LQG measurement scheduling problem in which every measurement is costly, no communication between observers is permitted, and the observers' estimation errors are coupled quadratically. This setup, motivated by considerations from organization theory, models measurement scheduling problems in which cost, bandwidth, or security constraints necessitate that estimates be decentralized, although their errors are coupled. We show that, unlike the centralized case, in the decentralized case the problem of optimizing the time integral of the measurement cost and the quadratic estimation error is fundamentally stochastic, and we characterize the ε-optimal open-loop schedules as chattering solutions of a deterministic Lagrange optimal control problem. Using a numerical example, we describe also how this deterministic optimal control problem can be solved by nonlinear programming.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45246/1/10957_2005_Article_BF02275352.pd

Development of a planar multi-body model of the human knee joint

The aim of this work is to develop a dynamic model for the biological human knee joint. The model is formulated in the framework of multibody systems methodologies, as a system of two bodies, the femur and the tibia. For the purpose of describing the formulation, the relative motion of the tibia with respect to the femur is considered. Due to their higher stiffness compared to that of the articular cartilages, the femur and tibia are considered as rigid bodies. The femur and tibia cartilages are considered to be deformable structures with specific material characteristics. The rotation and gliding motions of the tibia relative to the femur can not be modeled with any conventional kinematic joint, but rather in terms of the action of the knee ligaments and potential contact between the bones. Based on medical imaging techniques, the femur and tibia profiles in the sagittal plane are extracted and used to define the interface geometric conditions for contact. When a contact is detected, a continuous non-linear contact force law is applied which calculates the contact forces developed at the interface as a function of the relative indentation between the two bodies. The four basic cruciate and collateral ligaments present in the knee are also taken into account in the proposed knee joint model, which are modeled as non-linear elastic springs. The forces produced in the ligaments, together with the contact forces, are introduced into the system’s equations of motion as external forces. In addition, an external force is applied on the center of mass of the tibia, in order to actuate the system mimicking a normal gait motion. Finally, numerical results obtained from computational simulations are used to address the assumptions and procedures adopted in this study.Fundação para a Ciência e a Tecnologia (FCT