While the heritability of cigarette smoking and nicotine dependence (ND) is well-documented, the contribution of specific genetic variants to specific phenotypes has not been closely examined. The ...objectives of this study were to test the associations between 321 tagging single-nucleotide polymorphisms (SNPs) that capture common genetic variation in 24 genes, and early smoking and ND phenotypes in novice adolescent smokers, and to assess if genetic predictors differ across these phenotypes.
In a prospective study of 1294 adolescents aged 12-13 years recruited from ten Montreal-area secondary schools, 544 participants who had smoked at least once during the 7-8 year follow-up provided DNA. 321 single-nucleotide polymorphisms (SNPs) in 24 candidate genes were tested for an association with number of cigarettes smoked in the past 3 months, and with five ND phenotypes (a modified version of the Fagerstrom Tolerance Questionnaire, the ICD-10 and three clusters of ND symptoms representing withdrawal symptoms, use of nicotine for self-medication, and a general ND/craving symptom indicator).
The pattern of SNP-gene associations differed across phenotypes. Sixteen SNPs in seven genes (ANKK1, CHRNA7, DDC, DRD2, COMT, OPRM1, SLC6A3 (also known as DAT1)) were associated with at least one phenotype with a p-value <0.01 using linear mixed models. After permutation and FDR adjustment, none of the associations remained statistically significant, although the p-values for the association between rs557748 in OPRM1 and the ND/craving and self-medication phenotypes were both 0.076.
Because the genetic predictors differ, specific cigarette smoking and ND phenotypes should be distinguished in genetic studies in adolescents. Fifteen of the 16 top-ranked SNPs identified in this study were from loci involved in dopaminergic pathways (ANKK1/DRD2, DDC, COMT, OPRM1, and SLC6A3).
Dopaminergic pathways may be salient during early smoking and the development of ND.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Neurofilament light chain (NfL) is a promising blood biomarker to detect neurodegeneration in Alzheimer's disease (AD) and other brain disorders. However, there are limited reports of how ...longitudinal NfL relates to imaging biomarkers. We herein investigated the relationship between blood NfL and brain metabolism in AD.
Voxelwise regression models tested the cross-sectional association between 18Ffluorodeoxyglucose (18FFDG) and both plasma and cerebrospinal fluid NfL in cognitively impaired and unimpaired subjects. Linear mixed models were also used to test the longitudinal association between NfL and 18FFDG in amyloid positive (Aβ+) and negative (Aβ−) subjects.
Higher concentrations of plasma and cerebrospinal fluid NfL were associated with reduced 18FFDG uptake in correspondent brain regions. In Aβ+ participants, NfL associates with hypometabolism in AD-vulnerable regions. Longitudinal changes in the association 18FFDG-NfL were confined to cognitively impaired Aβ+ individuals.
These findings indicate that plasma NfL is a proxy for neurodegeneration in AD-related regions in Aβ+ subjects.
•Plasma and CSF neurofilament light show similar pattern of association with 18FFDG.•In Aβ+ group, brain hypometabolism associates with NfL in Alzheimer's disease signature regions.•The association 18Ffluorodeoxyglucose-plasma NfL increases over 24 months in Aβ+ patients.
Identifying disease‐associated changes in DNA methylation can help us gain a better understanding of disease etiology. Bisulfite sequencing allows the generation of high‐throughput methylation ...profiles at single‐base resolution of DNA. However, optimally modeling and analyzing these sparse and discrete sequencing data is still very challenging due to variable read depth, missing data patterns, long‐range correlations, data errors, and confounding from cell type mixtures. We propose a regression‐based hierarchical model that allows covariate effects to vary smoothly along genomic positions and we have built a specialized EM algorithm, which explicitly allows for experimental errors and cell type mixtures, to make inference about smooth covariate effects in the model. Simulations show that the proposed method provides accurate estimates of covariate effects and captures the major underlying methylation patterns with excellent power. We also apply our method to analyze data from rheumatoid arthritis patients and controls. The method has been implemented in R package SOMNiBUS.
Incidents pose challenges to the reliable operation of urban rail transit systems. Given the high frequency of subway services, even minor incidents can cause cascading delays across multiple trains. ...Understanding incident effects is crucial for improving response time and enabling efficient recovery strategies. This study uses operational records from the Montreal subway system to quantify the overall impact of incidents including the number of affected trains and total delay time. The proposed approach involves integrating operational records with incident data to identify the source of delays and subsequent knock-on effects. To recognize distinct propagation patterns among various incident types, K-means clustering is applied to categorize incidents into three clusters. Cluster 1 represents incidents with the lowest impacts, affecting only one direction of a subway line and imposing an average total delay time of 16 min. Cluster 2, which comprises most incidents, causing moderate operational impacts with an average total delay time of 52 min. Cluster 3 includes severe incidents, affecting an average of 26 trains and causing a total delay time of 273 min. Peak hour analysis indicates that morning and evening peak hours have the highest average number of affected trains, emphasizing the impact of peak hours on incident severity. Investigation into the causes of incidents highlights that the most frequent incidents fall into Cluster 2, implying moderate impacts on subway operations. This research provides valuable insights into subway incident management, laying the groundwork for further studies aimed at enhancing the performance of urban rail transit systems during service disruptions.
Transmission of the two parental alleles to offspring deviating from the Mendelian ratio is termed Transmission Ratio Distortion (TRD), occurs throughout gametic and embryonic development. TRD has ...been well-studied in animals, but remains largely unknown in humans. The Transmission Disequilibrium Test (TDT) was first proposed to test for association and linkage in case-trios (affected offspring and parents); adjusting for TRD using control-trios was recommended. However, the TDT does not provide risk parameter estimates for different genetic models. A loglinear model was later proposed to provide child and maternal relative risk (RR) estimates of disease, assuming Mendelian transmission. Results from our simulation study showed that case-trios RR estimates using this model are biased in the presence of TRD; power and Type 1 error are compromised. We propose an extended loglinear model adjusting for TRD. Under this extended model, RR estimates, power and Type 1 error are correctly restored. We applied this model to an intrauterine growth restriction dataset, and showed consistent results with a previous approach that adjusted for TRD using control-trios. Our findings suggested the need to adjust for TRD in avoiding spurious results. Documenting TRD in the population is therefore essential for the correct interpretation of genetic association studies.
This study aims to quantify placebo response (PR) in children with attention deficit hyperactivity disorder (ADHD) as assessed by parents and teachers and to explore some of its determinants.
Five ...hundred and forty children with ADHD (ages 6–12) were recruited to a randomized, double‐blind, placebo‐controlled crossover trial with methylphenidate. The main outcome variable was Conners' Global Index (CGI), based on assessment of behaviour by parents (CGI‐P) and teacher (CGI‐T). PR was calculated as the difference between CGI‐P/T scores at baseline and placebo week.
There was a highly significant PR as assessed by the parents' and teachers' (p < 0.001). The magnitude of PR as assessed by parents was greater (10.57 points) compared to that assessed by teachers (3.93 points). The determinants of PR were different between parents and teachers. For parents, income, marital status, education, maternal smoking during pregnancy, and prior psychostimulant exposure (PPE) showed a significant effect on PR. For teachers, only ethnicity and PPE had an effect. The pattern of PR revealed two distinct profiles that may shed some light on the mechanisms involved in PR.
PR in children with ADHD varies depending on the setting of the observations and the evaluator. Several psychosocial factors have been identified as modulators of PR. This is relevant for the design and interpretation of clinical trials and for clinical practice.
In recent years, gene expression, genetic association, and metabolic studies have implicated the polyamine system in psychiatric conditions, including suicide. Given the extensive regulation of genes ...involved in polyamine metabolism, as well as their interconnections with the metabolism of other amino acids, we were interested in further investigating the expression of polyamine-related genes across the brain in order to obtain a more comprehensive view of the dysregulation of this system in suicide. To this end, we examined the expression of genes related to polyamine metabolism across 22 brain regions in a sample of 29 mood-disordered suicide completers and 16 controls, and identified 14 genes displaying differential expression. Among these, altered expression of spermidine/spermine N1-acetyltransferase, spermine oxidase, and spermine synthase, has previously been observed in brains of suicide completers, while the remainder of the genes represent novel findings. In addition to genes with direct involvement in polyamine metabolism, including S-adenosylmethionine decarboxylase, ornithine decarboxylase antizymes 1 and 2, and arginase II, we identified altered expression of several more distally related genes, including aldehyde dehydrogenase 3 family, member A2, brain creatine kinase, mitochondrial creatine kinase 1, glycine amidinotransferase, glutamic-oxaloacetic transaminase 1, and arginyl-tRNA synthetase-like. Many of these genes displayed altered expression across several brain regions, strongly implying that dysregulated polyamine metabolism is a widespread phenomenon in the brains of suicide completers. This study provides a broader view of the nature and extent of the dysregulation of the polyamine system in suicide, and highlights the importance of this system in the neurobiology of suicide.
Recently, mapping studies of expression quantitative loci (eQTL) (where gene expression levels are viewed as quantitative traits) have provided insight into the biology of gene regulation. Bayesian ...methods provide natural modeling frameworks for analyzing eQTL studies, where information shared across markers and/or genes can increase the power to detect eQTLs. Bayesian approaches tend to be computationally demanding and require specialized software. As a result, most eQTL studies use univariate methods treating each gene independently, leading to suboptimal results.
We present a powerful, computationally optimized and free open-source R package, iBMQ. Our package implements a joint hierarchical Bayesian model where all genes and SNPs are modeled concurrently. Model parameters are estimated using a Markov chain Monte Carlo algorithm. The free and widely used openMP parallel library speeds up computation. Using a mouse cardiac dataset, we show that iBMQ improves the detection of large trans-eQTL hotspots compared with other state-of-the-art packages for eQTL analysis.
The R-package iBMQ is available from the Bioconductor Web site at http://bioconductor.org and runs on Linux, Windows and MAC OS X. It is distributed under the Artistic Licence-2.0 terms.
christian.deschepper@ircm.qc.ca or rgottard@fhcrc.org.
Supplementary data are available at Bioinformatics online.
This study introduces a novel way to use the lifetime ratings of symptoms of psychosis, mania and depression in genetic linkage analysis of schizophrenia (SZ) and bipolar disorder (BP). It suggests ...using a latent class model developed for family data to define more homogeneous symptom subtypes that are influenced by a smaller number of genes that will thus be more easily detectable. In a two-step approach, we proposed: (i) to form homogeneous clusters of subjects based on the symptom dimensions and (ii) to use the information from these homogeneous clusters in linkage analysis. This framework was applied to a unique SZ and BP sample composed of 1278 subjects from 48 large kindreds from the Eastern Quebec population. The results suggest that our strategy has the power to increase linkage signals previously obtained using the diagnosis as phenotype and allows for a better characterization of the linkage signals. This is the case for a linkage signal, which we formerly obtained in chromosome 13q and enhanced using the dimension mania. The analysis also suggests that the methods may detect new linkage signals not previously uncovered by using diagnosis alone, as in chromosomes 2q (delusion), 15q (bizarre behavior), 7p (anhedonia) and 9q (delusion). In the case of the 15q and 2q region, the results coincide with linkage signals detected in other studies. Our results support the view that dissecting phenotypic heterogeneity by modeling symptom dimensions may provide new insights into the genetics of SZ and BP.
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