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Cytochrome P450 2C19 (CYP2C19) is a major enzyme involved in the biotransformation and metabolism of various substances. Loss-of-function of the CYP2C19 gene represents downregulation of CYP2C19 enzyme indication limited or no enzymatic function, which may be, in turn, associated with some disease susceptibility. The relationship between CYP2C19 polymorphisms and susceptibility to premature coronary artery disease (PCAD) is not fully understood. This study aimed to assess this relationship. Methods: This study included 635 PCAD patients, and 548 age-matched non-CAD individuals as controls, from November 2019 to August 2023. The CYP2C19 rs4244285 (681G > A, *2) and rs4986893 (636G > A, *3) were genotyped, and the distribution of CYP2C19 polymorphisms between patients and controls and the relationship between CYP2C19 polymorphisms and PCAD risk were analyzed. Results: A total of 442 (37.4%), 543 (45.9%), and 198 (16.7%) individuals had CYP2C19 extensive metabolizer (EM) (*1/*1), intermediate metabolizer (IM) (*1/*2 and *1/*3), and poor metabolizer (PM) (*2/*2, *2/*3, and *3/*3) phenotypes, respectively. CYP2C19 *2/*2 genotype frequency was higher, *1/*1 genotype was lower in PCAD patients than controls. Individuals with CYP2C19 PM phenotype had higher triglyceride (TG) levels than those with CYP2C19 EM or IM phenotypes. Logistic regression analysis showed that body mass index (BMI) ≥ 24.0 kg/m2 (≥ 24.0 kg/m2 vs 18.5– 23.9 kg/m2, odds ratio (OR): 1.326, 95% confidence interval (CI): 1.041– 1.688, p = 0.022), smoking (OR: 1.974, 95% CI: 1.283– 3.306, p = 0.002), hypertension (OR: 1.327, 95% CI: 1.044– 1.687, p = 0.021), diabetes mellitus (OR: 1.390, 95% CI: 1.054– 1.834, p = 0.020), CYP2C19 PM phenotype (PM phenotype vs EM phenotype, OR: 1.701, 95% CI: 1.200– 2.411, p = 0.003), and CYP2C19 IM+PM phenotypes (IM+PM vs EM phenotype, OR: 1.369, 95% CI: 1.077– 1.740, p = 0.010) were associated with PCAD. Conclusion: CYP2C19 PM or IM+PM phenotypes, overweight, smoking, hypertension, and diabetes mellitus were associated with PCAD. [ABSTRACT FROM AUTHOR]

The aim of this paper is to conduct a systematic and theoretical analysis of estimation and inference for a class of functional mixed effects models (FMEM). Such FMEMs consist of fixed effects that characterize the association between longitudinal functional responses and covariates of interest and random effects that capture the spatial-temporal correlations of longitudinal functional responses. We propose local linear estimates of refined fixed effect functions and establish their weak convergence along with a simultaneous confidence band for each fixed-effect function. We propose a global test for the linear hypotheses of varying coefficient functions and derive the associated asymptotic distribution under the null hypothesis and the asymptotic power under the alternative hypothesis are derived. We also establish the convergence rates of the estimated spatial-temporal covariance operators and their associated eigenvalues and eigenfunctions. We conduct extensive simulations and apply our method to a white-matter fiber data set from a national database for autism research to examine the finite-sample performance of the proposed estimation and inference procedures.

Hypotheses exploring the influence of dietary conditions on the life history trade-off between survival and reproductive success are extensively tested in female insects, but are rarely explored in males. Here, the impact of dietary quality and female access on age-specific reproduction and survival of male Mexican fruit flies, Anastrepha ludens Loew (Diptera: Tephritidae), are examined. There is a clear cost of female access for males with access to dietary protein, measurable as a decrease in life expectancy, which is further influenced by the age when females are introduced. A protein deficient diet reduces the lifespan benefit of virginity and masks the detrimental effect of female access on male life expectancy. Dietary protein is not necessary for reproductive success, but access to protein at eclosion improves the lifetime reproductive success of males compared to when it is delayed. Overall, reproductive success diminishes as the male flies age, regardless of the dietary conditions, providing evidence for reproductive senescence in males. Delaying the males' access to a protein source fails to influence the negative effect of age on reproductive ability. Because age specific reproductive rates decline with age, regardless of diet, male fitness does not benefit from lifespan extension. Therefore, males can be expected to allocate available resources towards reproductive effort in favour of extended lifespan, regardless of mate and protein availability.

Many longitudinal imaging studies have collected repeated diffusion tensor magnetic resonance imaging data to understand white matter maturation and structural connectivity pattern in normal controls and diseased subjects. There is an urgent demand for the development of statistical methods for the analysis of diffusion properties along fiber tracts and clinical data obtained from longitudinal studies. Jointly analyzing repeated fiber-tract diffusion properties and covariates (e.g., age or gender) raises several major challenges including (i) infinite-dimensional functional response data, (ii) complex spatial-temporal correlation structure, and (iii) complex spatial smoothness. To address these challenges, this article is to develop a functional mixed effects modeling (FMEM) framework to delineate the dynamic changes of diffusion properties along major fiber tracts and their association with a set of covariates of interest and the structure of the variability of these white matter tract properties in various longitudinal studies. Our FMEM consists of a functional mixed effects model for addressing all three challenges, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial-temporal correlation structure, a test procedure with local and global test statistics for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FMEM and to demonstrate that FMEM significantly outperforms the standard pointwise mixed effects modeling approach. We apply FMEM to study the spatial-temporal dynamics of white-matter fiber tracts in a clinical study of neurodevelopment.

We generalize the sign covariance introduced by Bergsma & Dassios (2014) to multivariate random variables and beyond. The new interpoint-ranking sign covariance is applicable to general types of random objects as long as a meaningful similarity measure can be defined, and it is shown to be zero if and only if the two random variables are independent. The test statistic is a |$U$| -statistic, whose large-sample behaviour guarantees that the proposed test is consistent against general types of alternatives. Numerical experiments and data analyses demonstrate the superior empirical performance of the proposed method. [ABSTRACT FROM AUTHOR]