Contributions of inherited mtDNA to longevity: evidence from extended pedigrees with 176 million kinship pairs.

Background: Mitochondria are bacteria-like organelles with their own DNA (mtDNA) that exist in the cellular cytoplasm of almost every cell in the human body. Because mitochondria are critical for sustaining life, it follows that inherited mtDNA could be a key aetiologic element underlying longevity. Unfortunately, biometric approaches able to quantify heritable contributions of mtDNA have not been available.

Detecting mtDNA Effects with an Extended Pedigree Model: An Analysis of Statistical Power and Estimation Bias.

Mitochondrial DNA (mtDNA) plays a crucial role in numerous cellular processes, yet its impact on human complex behavior remains underexplored. The current paper proposes a novel covariance structure model with seven parameters to specifically isolate and quantify mtDNA effects on human complex traits. This approach uses extended pedigrees to obtain estimates of mtDNA variance while controlling for other genetic and environmental influences.

Measurement Model Misspecification in Dynamic Structural Equation Models: Power, Reliability, and Other Considerations.

Dynamic Structural Equation Models (DSEMs) integrate multilevel modeling, time series analysis, and structural equation modeling within a Bayesian estimation framework, offering a versatile tool for analyzing intensive longitudinal data (ILD). However, the impact of measurement structure misspecification in DSEMs, especially under varying reliability conditions and model complexities, remains underexplored. Our Monte Carlo simulation revealed that omitting measurement errors when present led to severe biases in dynamic parameters regardless of reliability conditions, though power remained high.

Drinking Water NaCl Is Associated With Hypertension and Albuminuria: A Panel Study.

Background: Salt leaching into freshwater is an emerging global environmental health concern. We tested the associations between drinking water salinity and blood pressure, hypertension, and albuminuria.

Methods: We conducted a 2-year panel study in 2022 and 2023 with 434 observations among 327 Daasanach adults aged >18 years in northern Kenya.

Unsupervised Model Construction in Continuous-Time.

Many of the advancements reconciling individual- and group-level results have occurred in the context of a discrete-time modeling framework. Discrete-time models are intuitive and offer relatively simple interpretations for the resulting dynamic structures; however, they do not possess the flexibility of models fitted in the continuous-time framework. We introduce ct-gimme, a continuous-time extension of the group iterative multiple model estimation (GIMME; Gates & Molenaar, 2012) procedure which enables researchers to fit complex, high dimensional dynamic networks in continuous-time.

Show Me Some ID: A Universal Identification Program for Structural Equation Models.

With models and research designs ever increasing in complexity, the foundational question of model identification is more important than ever. The determination of whether or not a model can be fit at all or fit to some particular data set is the essence of model identification. In this article, we pull from previously published work on data-independent model identification applicable to a broad set of structural equation models, and extend it further to include extremely flexible exogenous covariate effects and also to include data-dependent empirical model identification.

Detecting mtDNA effects with an Extended Pedigree Model: An Analysis of Statistical Power and Estimation Bias.

Mitochondrial DNA (mtDNA) plays a crucial role in numerous cellular processes, yet its impact on human behavior remains underexplored. The current paper proposes a novel covariance structure model with seven parameters to specifically isolate and quantify mtDNA effects on human behavior. This approach uses extended pedigrees to obtain estimates of mtDNA variance while controlling for other genetic and environmental influences.

Structured Estimation of Heterogeneous Time Series.

How best to model structurally heterogeneous processes is a foundational question in the social, health and behavioral sciences. Recently, Fisher et al. introduced the multi-VAR approach for simultaneously estimating multiple-subject multivariate time series characterized by common and individualizing features using penalized estimation.

Modeling the dynamics of addiction relapse via the double-well potential system.

Substance use relapse is difficult to define, and previous work has used one-size-fits-all ad hoc definitions. Researchers have called for a dynamic and personalized understanding of relapse as a concept and model, necessitating novel statistical tools. We aimed to develop and validate a novel statistical model of latent relapse processes: the double-well potential model (DWPM).

What ergodicity means for you.

This paper explores the relation between within-person and between-person research designs using the concept of ergodicity from statistical mechanics in physics. We demonstrate the consequences of ergodicity using several real data examples from previously published studies. We then create several simulated examples that illustrate the independence of within-person processes from between-person differences, and pair these examples with analytic results that reinforce our conclusions.

BGmisc: An R Package for Extended Behavior Genetics Analysis.

Behavior genetics is a field that studies how our genes and environment contribute to differences in behavior and traits among individuals. Traditionally, twin studies have long been a cornerstone of this field, helping researchers understand how genetics influence behavior. Recently, the focus has expanded to include studies with more complex family structures, e.

Products of Variables in Structural Equation Models.

A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands. The result is a new category of SEM which we call a Products of Variables Model (PoV). Some useful and practical features of PoV models include estimation of interactions between latent variables, latent variable moderators, manifest moderators with missing values, and manifest or latent squared terms.

Characterizing affect dynamics with a damped linear oscillator model: Theoretical considerations and recommendations for individual-level applications.

People show stable differences in the way their affect fluctuates over time. Within the general framework of dynamical systems, the damped linear oscillator (DLO) model has been proposed as a useful approach to study affect dynamics. The DLO model can be applied to repeated measures provided by a single individual, and the resulting parameters can capture relevant features of the person's affect dynamics.

State Space Mixture Modeling: Finding People with Similar Patterns of Change.

Increasingly, behavioral scientists encounter data where several individuals were measured on multiple variables over numerous occasions. Many current methods combine these data, assuming all individuals are randomly equivalent. An extreme alternative assumes no one is randomly equivalent.

Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter.

Many intensive longitudinal measurements are collected at irregularly spaced time intervals, and involve complex, possibly nonlinear and heterogeneous patterns of change. Effective modelling of such change processes requires continuous-time differential equation models that may be nonlinear and include mixed effects in the parameters. One approach of fitting such models is to define random effect variables as additional latent variables in a stochastic differential equation (SDE) model of choice, and use estimation algorithms designed for fitting SDE models, such as the continuous-discrete extended Kalman filter (CDEKF) approach implemented in the dynr R package, to estimate the random effect variables as latent variables.

Conversion Total Hip Arthroplasty in the Era of Bundled Care Payments: Impacts on Costs of Care.

Background: Conversion hip arthroplasty is defined as a patient who has had prior open or arthroscopic hip surgery with or without retained hardware that is removed and replaced with arthroplasty components. Currently, it is classified under the same diagnosis-related group as primary total hip arthroplasty (THA); however, it frequently requires a higher cost of care.

Methods: A retrospective study of 228 conversion THA procedures in an orthopaedic specialty hospital was performed.

Simulated nonlinear genetic and environmental dynamics of complex traits.

Genetic studies of complex traits often show disparities in estimated heritability depending on the method used, whether by genomic associations or twin and family studies. We present a simulation of individual genomes with dynamic environmental conditions to consider how linear and nonlinear effects, gene-by-environment interactions, and gene-by-environment correlations may work together to govern the long-term development of complex traits and affect estimates of heritability from common methods. Our simulation studies demonstrate that the genetic effects estimated by genome wide association studies in unrelated individuals are inadequate to characterize gene-by-environment interaction, while including related individuals in genome-wide complex trait analysis (GCTA) allows gene-by-environment interactions to be recovered in the heritability.

Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data.

With the advent of new data collection technologies, intensive longitudinal data (ILD) are collected more frequently than ever. Along with the increased prevalence of ILD, more methods are being developed to analyze these data. However, relatively few methods have yet been applied for making long- or even short-term predictions from ILD in behavioral settings.

Periarticular screws: what's in and what's out of the joint?

Periarticular hardware placement can be challenging and a source of angst for orthopaedic surgeons due to fear of penetrating the articular surface and causing undue harm to the joint. In recent years, many surgeons have turned to computed tomography (CT) and other intraoperative or postoperative modalities to determine whether hardware is truly extraarticular in areas of complex anatomy. Yet, these adjuncts are expensive, time consuming, and often unnecessary given the advancement in understanding of intraoperative fluoroscopy.

The Analytic Identification of Variance Component Models Common to Behavior Genetics.

Many behavior genetics models follow the same general structure. We describe this general structure and analytically derive simple criteria for its identification. In particular, we find that variance components can be uniquely estimated whenever the relatedness matrices that define the components are linearly independent (i.

Multilevel Modeling in Classical Twin and Modern Molecular Behavior Genetics.

For more than a decade, it has been known that many common behavior genetics models for a single phenotype can be estimated as multilevel models (e.g., van den Oord 2001; Guo and Wang 2002; McArdle and Prescott 2005; Rabe-Hesketh et al.

Combining Structural-Equation Modeling with Genomic-Relatedness-Matrix Restricted Maximum Likelihood in OpenMx.

There is a long history of fitting biometrical structural-equation models (SEMs) in the pregenomic behavioral-genetics literature of twin, family, and adoption studies. Recently, a method has emerged for estimating biometrical variance-covariance components based not upon the expected degree of genetic resemblance among relatives, but upon the observed degree of genetic resemblance among unrelated individuals for whom genome-wide genotypes are available-genomic-relatedness-matrix restricted maximum-likelihood (GREML). However, most existing GREML software is concerned with quickly and efficiently estimating heritability coefficients, genetic correlations, and so on, rather than with allowing the user to fit SEMs to multitrait samples of genotyped participants.

Emotional and interpersonal mechanisms in community SSRI treatment of social anxiety disorder.

Background: Affective and interpersonal behavioural patterns characteristic of social anxiety disorder show improvement during treatment with serotonin agonists (e.g., selective serotonin reuptake inhibitors), commonly used in the treatment of social anxiety disorder.