Lajmi Lakhal-Chaieb

Outdoor temperature, age, sex, body mass index, and diabetic status determine the prevalence, mass, and glucose-uptake activity of 18F-FDG-detected BAT in humans.

CONTEXT In humans, the prevalence, mass, and glucose-uptake activity of (18)F-fluorodeoxyglucose ((18)F-FDG)-detected brown adipose tissue (BAT), which are expectedly enhanced by a cold stimulus, also appear modulated by other factors that still have to be disentangled. OBJECTIVE The objective of the study was to investigate the factors determining the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT in humans. RESEARCH DESIGN AND METHODS We retrospectively analyzed all (18)F-FDG positron emission tomography/computed tomography examinations performed between January 2007 and December 2008 at our institution for (18)F-FDG uptake within the cervical/supraclavicular, mediastinal, paravertebral, and perirenal fat areas. The influence of outdoor temperature, sex, age, body mass index (BMI), plasma glucose level, diabetes diagnosis, day length, and cancer status on the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT depots was investigated. RESULTS Three hundred twenty-eight of the 4842 patients (6.8%) had (18)F-FDG-detected BAT. The prevalence of (18)F-FDG BAT was negatively associated with outdoor temperature (P < 0.0001), age (P < 0.0001), BMI (P < 0.0001), and diabetes status (P = 0.0003). Moreover, there was a significant age × sex interaction for the prevalence of (18)F-FDG BAT (the younger the subjects, the greater the sex difference). The mass and glucose-uptake activity of (18)F-FDG-detected BAT also decreased with increasing outdoor temperature (P < 0.0001), age (P < 0.0001), and BMI (P < 0.0001). They were lower in men than in women (P < 0.001) and lower in diabetic than in nondiabetic patients (P = 0.0002). CONCLUSIONS The present study identifies outdoor temperature, age, sex, BMI, and diabetes status as determinants of the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT.

Robust Estimation of Mean Functions and Treatment Effects for Recurrent Events Under Event-Dependent Censoring and Termination: Application to Skeletal Complications in Cancer Metastatic to Bone

In clinical trials featuring recurrent clinical events, the definition and estimation of treatment effects involves a number of interesting issues, especially when loss to follow-up may be event-related and when terminal events such as death preclude the occurrence of further events. This paper discusses a clinical trial of breast cancer patients with bone metastases where the recurrent events are skeletal complications, and where patients may die during the trial. We argue that treatment effects should be based on marginal rate and mean functions. When recurrent event data are subject to event-dependent censoring, however, ordinary marginal methods may yield inconsistent estimates. Incorporating correctly specified inverse probability of censoring weights into analyses can protect against dependent censoring and yield consistent estimates of marginal features. An alternative approach is to obtain estimates of rate and mean functions from models that involve some conditioning to render censoring conditionally independent. We consider three methods of estimating mean functions of recurrent event processes and examine the bias and efficiency of unweighted and inverse probability weighted versions of the methods with and without a terminating event. We compare the methods via simulation and use them to analyse the data from the breast cancer trial.

A human ALDH1A2 gene variant is associated with increased newborn kidney size and serum retinoic acid

Nephron number varies widely between 0.3 and 1.3 million per kidney in humans. During fetal life, the rate of nephrogenesis is influenced by local retinoic acid (RA) level such that even moderate maternal vitamin A deficiency limits the final nephron number in rodents. Inactivation of genes in the RA pathway causes renal agenesis in mice; however, the impact of retinoids on human kidney development is unknown. To resolve this, we tested for associations between variants of genes involved in RA metabolism (ALDH1A2, CYP26A1, and CYP26B1) and kidney size among normal newborns. Homozygosity for a common (1 in 5) variant, rs7169289(G), within an Sp1 transcription factor motif of the ALDH1A2 gene, showed a significant 22% increase in newborn kidney volume when adjusted for body surface area. Infants bearing this allele had higher umbilical cord blood RA levels compared to those with homozygous wild-type ALDH1A2 rs7169289(A) alleles. Furthermore, the effect of the rs7169289(G) variant was evident in subgroups with or without a previously reported hypomorphic RET 1476(A) proto-oncogene allele that is critical in determining final nephron number. As maternal vitamin A deficiency is widespread in developing countries and may compromise availability of retinol for fetal RA synthesis, our study suggests that the ALDH1A2 rs7169289(G) variant might be protective for such individuals.

Newborn serum retinoic acid level is associated with variants of genes in the retinol metabolism pathway.

Retinoic acid (RA) is a critical regulator of gene expression during embryonic development. In rodents, moderate maternal vitamin A deficiency leads to subtle morphogenetic defects and inactivation of RA pathway genes causes major disturbances of embryogenesis. In this study, we quantified RA in umbilical cord blood of 145 healthy full-term Caucasian infants from Montreal. Sixty seven percent of values were <10 nmol/L (84 were <0.07 nmol/L) and 33% had moderate or high levels. Variation in RA could not be explained by parallel variation in its precursor, retinol (ROL). However, we found that the (A) allele of the rs12591551 single nucleotide polymorphism (SNP) in the ALDH1A2 gene (ALDH1A2rs12591551(A)), occurring in 19% of newborns, was associated with 2.5-fold higher serum RA levels. ALDH1A2 encodes retinaldehyde dehydrogenase (RALDH) 2, which synthesizes RA in fetal tissues. We also found that homozygosity for the (A) allele of the rs12724719 SNP in the CRABP2 gene (CRABP2rs12724719(A/A)) was associated with 4.4-fold increase in umbilical cord serum RA. CRABP2 facilitates RA binding to its cognate receptor complex and transfer to the nucleus. We hypothesize that individual variation in RA pathway genes may account for subtle variations in RA-dependent human embryogenesis.

Archimedean copula model selection under dependent truncation

One-sided truncated survival data arise when a pair of time-to-event variables (X, Y) is observed only when X<Y. Existing methods of analysis rely on the assumption of quasi-independence between X and Y. Recently, Lakhal-Chaieb et al. (Biometrika 2006; 93:655-669) modeled potential dependency between these random variables via a semi-survival Archimedean copula. In this paper, we present a model selection procedure to rank a set of semi-survival Archimedean copula families according to their ability to fit a given data set subject to dependent truncation. The proposed procedure is based on a truncated version of Kendalls tau (J. Multivariate Anal. 1996; 56:60-74). The performance of the proposal is illustrated through simulations and three real data sets.

Inverse Probability of Censoring Weighted Estimates of Kendall's τ for Gap Time Analyses

In life history studies, interest often lies in the analysis of the interevent, or gap times and the association between event times. Gap time analyses are challenging however, even when the length of follow-up is determined independently of the event process, because associations between gap times induce dependent censoring for second and subsequent gap times. This article discusses nonparametric estimation of the association between consecutive gap times based on Kendalls τ in the presence of this type of dependent censoring. A nonparametric estimator that uses inverse probability of censoring weights is provided. Estimates of conditional gap time distributions can be obtained following specification of a particular copula function. Simulation studies show the estimator performs well and compares favorably with an alternative estimator. Generalizations to a piecewise constant Clayton copula are given. Several simulation studies and illustrations with real data sets are also provided.

Kendall’s tau for hierarchical data

This paper is concerned with hierarchical data having three levels. The level 1 units are nested in the level 2 units or subclusters which are themselves nested in the level 3 clusters. The model for this data is assumed to fulfill some symmetry assumptions. The level 1 units within each subcluster are exchangeable and a permutation of the subclusters belonging to the same cluster leaves the model unchanged. We are interested in measuring the dependence associated to clusters and subclusters respectively. Two exchangeable Kendall’s tau are proposed as non parametric measures of these two associations and estimators for these measures are proposed. Their asymptotic properties are then investigated under the proposed hierarchical model for the data. These statistics are then used to estimate the intra-class correlation coefficients for data drawn from elliptical hierarchical distributions. Hypothesis tests for the cluster and subcluster effects based on the proposed estimators are developed and their performances are assessed using Pitman efficiencies and a Monte Carlo study.

Association measures for bivariate failure times in the presence of a cure fraction

This paper proposes a new joint model for pairs of failure times in the presence of a cure fraction. The proposed model relaxes some of the assumptions required by the existing approaches. This allows us to add some flexibility to the dependence structure and to widen the range of association measures that can be defined. A numerically stable iterative algorithm based on estimating equations is proposed to estimate the parameters. The estimators are shown to be consistent and asymptotically normal. Simulations show that they have good finite-sample properties. The added flexibility of the proposal is illustrated with an application to data from a diabetes retinopathy study.

A rare variant association test in family‐based designs and non‐normal quantitative traits

Rare variant studies are now being used to characterize the genetic diversity between individuals and may help to identify substantial amounts of the genetic variation of complex diseases and quantitative phenotypes. Family data have been shown to be powerful to interrogate rare variants. Consequently, several rare variants association tests have been recently developed for family-based designs, but typically, these assume the normality of the quantitative phenotypes. In this paper, we present a family-based test for rare-variants association in the presence of non-normal quantitative phenotypes. The proposed model relaxes the normality assumption and does not specify any parametric distribution for the marginal distribution of the phenotype. The dependence between relatives is modeled via a Gaussian copula. A score-type test is derived, and several strategies to approximate its distribution under the null hypothesis are derived and investigated. The performance of the proposed test is assessed and compared with existing methods by simulations. The methodology is illustrated with an association study involving the adiponectin trait from the UK10K project.

SNP Set Association Testing for Survival Outcomes in the Presence of Intrafamilial Correlation.

In this work, we propose a single nucleotide polymorphism (SNP) set association test for censored phenotypes in the presence of a family‐based design. The proposed test is valid for both common and rare variants. A proportional hazards Cox model is specified for the marginal distribution of the trait and the familial dependence is modeled via a Gaussian copula. Censored values are treated as partially missing data and a multiple imputation procedure is proposed in order to compute the test statistics. The P‐value is then deduced analytically. The finite‐sample empirical properties of the proposed method are evaluated and compared to existing competitors by simulations and its use is illustrated using a breast cancer data set from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2.