Parent-child agreement and prevalence estimates of diagnoses in childhood: direct interview versus family history method.

Diagnostic information on children is typically elicited from both children and their parents. The aims of the present paper were to: (1) compare prevalence estimates according to maternal reports, paternal reports and direct interviews of children [major depressive disorder (MDD), anxiety and attention-deficit and disruptive behavioural disorders]; (2) assess mother-child, father-child and inter-parental agreement for these disorders; (3) determine the association between several child, parent and familial characteristics and the degree of diagnostic agreement or the likelihood of parental reporting; (4) determine the predictive validity of diagnostic information provided by parents and children. Analyses were based on 235 mother-offspring, 189 father-offspring and 128 mother-father pairs. Diagnostic assessment included the Kiddie-schedule for Affective Disorders and Schizophrenia (K-SADS) (offspring) and the Diagnostic Interview for Genetic Studies (DIGS) (parents and offspring at follow-up) interviews. Parental reports were collected using the Family History - Research Diagnostic Criteria (FH-RDC). Analyses revealed: (1) prevalence estimates for internalizing disorders were generally lower according to parental information than according to the K-SADS; (2) mother-child and father-child agreement was poor and within similar ranges; (3) parents with a history of MDD or attention deficit hyperactivity disorder (ADHD) reported these disorders in their children more frequently; (4) in a sub-sample followed-up into adulthood, diagnoses of MDD, separation anxiety and conduct disorder at baseline concurred with the corresponding lifetime diagnosis at age 19 according to the child rather than according to the parents. In conclusion, our findings support large discrepancies of diagnostic information provided by parents and children with generally lower reporting of internalizing disorders by parents, and differential reporting of depression and ADHD by parental disease status. Follow-up data also supports the validity of information provided by adolescent offspring.

THE USE OF SIMULATIONS IN EVOLUTIONARY POPULATION GENETICS: APPLICATIONS ON HUMANS, OWLS AND VIRTUAL ORGANISMS

Summary (in English) Computer simulations provide a practical way to address scientific questions that would be otherwise intractable. In evolutionary biology, and in population genetics in particular, the investigation of evolutionary processes frequently involves the implementation of complex models, making simulations a particularly valuable tool in the area. In this thesis work, I explored three questions involving the geographical range expansion of populations, taking advantage of spatially explicit simulations coupled with approximate Bayesian computation. First, the neutral evolutionary history of the human spread around the world was investigated, leading to a surprisingly simple model: A straightforward diffusion process of migrations from east Africa throughout a world map with homogeneous landmasses replicated to very large extent the complex patterns observed in real human populations, suggesting a more continuous (as opposed to structured) view of the distribution of modern human genetic diversity, which may play a better role as a base model for further studies. Second, the postglacial evolution of the European barn owl, with the formation of a remarkable coat-color cline, was inspected with two rounds of simulations: (i) determine the demographic background history and (ii) test the probability of a phenotypic cline, like the one observed in the natural populations, to appear without natural selection. We verified that the modern barn owl population originated from a single Iberian refugium and that they formed their color cline, not due to neutral evolution, but with the necessary participation of selection. The third and last part of this thesis refers to a simulation-only study inspired by the barn owl case above. In this chapter, we showed that selection is, indeed, effective during range expansions and that it leaves a distinguished signature, which can then be used to detect and measure natural selection in range-expanding populations. Résumé (en français) Les simulations fournissent un moyen pratique pour répondre à des questions scientifiques qui seraient inabordable autrement. En génétique des populations, l'étude des processus évolutifs implique souvent la mise en oeuvre de modèles complexes, et les simulations sont un outil particulièrement précieux dans ce domaine. Dans cette thèse, j'ai exploré trois questions en utilisant des simulations spatialement explicites dans un cadre de calculs Bayésiens approximés (approximate Bayesian computation : ABC). Tout d'abord, l'histoire de la colonisation humaine mondiale et de l'évolution de parties neutres du génome a été étudiée grâce à un modèle étonnement simple. Un processus de diffusion des migrants de l'Afrique orientale à travers un monde avec des masses terrestres homogènes a reproduit, dans une très large mesure, les signatures génétiques complexes observées dans les populations humaines réelles. Un tel modèle continu (opposé à un modèle structuré en populations) pourrait être très utile comme modèle de base dans l'étude de génétique humaine à l'avenir. Deuxièmement, l'évolution postglaciaire d'un gradient de couleur chez l'Effraie des clocher (Tyto alba) Européenne, a été examiné avec deux séries de simulations pour : (i) déterminer l'histoire démographique de base et (ii) tester la probabilité qu'un gradient phénotypique, tel qu'observé dans les populations naturelles puisse apparaître sans sélection naturelle. Nous avons montré que la population actuelle des chouettes est sortie d'un unique refuge ibérique et que le gradient de couleur ne peux pas s'être formé de manière neutre (sans l'action de la sélection naturelle). La troisième partie de cette thèse se réfère à une étude par simulations inspirée par l'étude de l'Effraie. Dans ce dernier chapitre, nous avons montré que la sélection est, en effet, aussi efficace dans les cas d'expansion d'aire de distribution et qu'elle laisse une signature unique, qui peut être utilisée pour la détecter et estimer sa force.

Molecular genetics of "PRPF31" dominant mutations linked to retinitis pigmentosa

ABSTRACT : The retina is one of the most important human sensory tissues since it detects and transmits all visual information from the outside world to the brain. Retinitis pigmentosa (RP) is the name given to a group of inherited diseases that affect specifically the photoreceptors present in the retina and in many instances lead to blindness. Dominant mutations in PRPF31, a gene that encodes for a pre-mRNA splicing factor, cause retinitis pigmentosa with reduced penetrance. We functionally investigated a novel mutation, identified in a large family with autosomal dominant RP, and 7 other mutations, substitutions and microdeletions, in 12 patients from 7 families with PRPF31-linked RP. Seven mutations lead to PRPF31 mRNA with premature stop codons and one to mRNA lacking the exon containing the initiation codon. Quantification of PRPF31 mRNA and protein levels revealed a significant reduction in cell lines derived from patients, compared to non carriers of mutations in PRPF31. Allelic quantification of PRPF31 mRNA indicated that the level of mutated mRNA is very low compared to wild-type mRNA. No mutant protein was detected and the subnuclear localization of wild-type PRPF31 remains the same in cell lines from patients and controls. Blocking nonsense-mediated mRNA decay in cell lines derived from patients partially restored PRPF31 mutated mRNA but derived proteins were still undetectable, even when protein degradation pathways were inhibited. Our results demonstrated that the vast majority of PRPF31 mutations result in null alleles, since they are subject to surveillance mechanisms that degrade mutated mRNA and possibly block its translation. Altogether, these data indicate that the likely cause of PRPF31-linked RP is haploinsufficiency, rather than a dominant negative effect. Penetrance of PRPF31 mutations has been previously demonstrated to be inversely correlated with the level of PRPF31 mRNA, since high expression of wild-type PRPF31 mRNA protects from the disease. Consequently, we have investigated the genetic modifiers that control the expression of PRPF31 by quantifying PRPF31 mRNA levels in cell lines derived from 200 individuals from 15 families representative of the general population. By linkage analyses we identified a 8.2Mb-region on chromosome 14q21-23 that contains a gene involved in the modulation of PRPF31 expression. We also assessed apreviously-mapped penetrance factor invariably located on the wild-type allele and linked to the PRPF31 locus in asymptomatic patients from different families with RP. We demonstrated that this modifier increases the expression of both PRPF31 alleles already at the pre-mRNA level. Finally, our data suggest that PRPF31 mRNA expression and consequently the penetrance of PRPF31 mutations is modulated by at least 2 diffusible compounds, which act on both PRPF31 alleles during their transcription.

Illicit drug profiling, reflection on statistical comparisons

This paper presents reflexions about statistical considerations on illicit drug profiling and more specifically about the calculation of threshold for determining of the seizure are linked or not. The specific case of heroin and cocaine profiling is presented with the necessary details on the target profiling variables (major alkaloids) selected and the analytical method used. Statistical approach to compare illicit drug seizures is also presented with the introduction of different scenarios dealing with different data pre-treatment or transformation of variables.The main aim consists to demonstrate the influence of data pre-treatment on the statistical outputs. A thorough study of the evolution of the true positive rate (TP) and the false positive rate (FP) in heroin and cocaine comparison is then proposed to investigate this specific topic and to demonstrate that there is no universal approach available and that the calculations have to be revaluate for each new specific application.

Narcolepsy and familial advanced sleep-phase syndrome: molecular genetics of sleep disorders.

Sleep disorders are very prevalent and represent an emerging worldwide epidemic. However, research into the molecular genetics of sleep disorders remains surprisingly one of the least active fields. Nevertheless, rapid progress is being made in several prototypical disorders, leading recently to the identification of the molecular pathways underlying narcolepsy and familial advanced sleep-phase syndrome. Since the first reports of spontaneous and induced loss-of-function mutations leading to hypocretin deficiency in human and animal models of narcolepsy, the role of this novel neurotransmission pathway in sleep and several other behaviors has gained extensive interest. Also, very recent studies using an animal model of familial advanced sleep-phase syndrome shed new light on the regulation of circadian rhythms.

Random mating with a finite number of matings.

Random mating is the null model central to population genetics. One assumption behind random mating is that individuals mate an infinite number of times. This is obviously unrealistic. Here we show that when each female mates a finite number of times, the effective size of the population is substantially decreased.

Statistical evaluation of the influence of writing postures on on-line signatures. Study of the impact of time.

The aim of this study is to investigate the influence of unusual writing positions on a person's signature, in comparison to a standard writing position. Ten writers were asked to sign their signature six times, in each of four different writing positions, including the standard one. In order to take into consideration the effect of the day-to-day variation, this same process was repeated over 12 sessions, giving a total of 288 signatures per subject. The signatures were collected simultaneously in an off-line and on-line acquisition mode, using an interactive tablet and a ballpoint pen. Unidimensional variables (height to width ratio; time with or without in air displacement) and time-dependent variables (pressure; X and Y coordinates; altitude and azimuth angles) were extracted from each signature. For the unidimensional variables, the position effect was assessed through ANOVA and Dunnett contrast tests. Concerning the time-dependent variables, the signatures were compared by using dynamic time warping, and the position effect was evaluated through classification by linear discriminant analysis. Both of these variables provided similar results: no general tendency regarding the position factor could be highlighted. The influence of the position factor varies according to the subject as well as the variable studied. The impact of the session factor was shown to cover the impact that could be ascribed to the writing position factor. Indeed, the day-to-day variation has a greater effect than the position factor on the studied signature variables. The results of this study suggest guidelines for best practice in the area of signature comparisons and demonstrate the importance of a signature collection procedure covering an adequate number of sampling sessions, with a sufficient number of samples per session.

Genetics of sleep.

Molecular and genetic approaches in several species have provided new insights into the mechanisms of rest-activity and sleep-wake regulation. Many of these discoveries are believed to support hypotheses about sleep functions, which nevertheless remain elusive. In this review we discuss the specific contribution of both mammalian and invertebrate models to our understanding of the molecular basis of sleep.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

Current genetic data do not improve the prediction of type 2 diabetes mellitus: the CoLaus study.

CONTEXT: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data. OBJECTIVE: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM. DESIGN: This was a prospective study, with a mean follow-up time of 5 yr. SETTING AND SUBJECTS: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr). MAIN OUTCOME MEASURE: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference. RESULTS: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement. CONCLUSIONS: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.