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In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1–3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.

Objectives: The aim was to identify the most important features of structural knee osteoarthritis (OA) progressors and classification using machine learning methods. Methods: Participants, features and outcomes were from the Osteoarthritis Initiative. Features were from baseline (1107), including articular knee tissues (135) assessed by quantitative magnetic resonance imaging (MRI). OA progressors were ascertained by four outcomes: cartilage volume loss in medial plateau at 48 and 96 months (Prop_CV_48M, 96M), Kellgren–Lawrence (KL) grade ⩾ 2 and medial joint space narrowing (JSN) ⩾ 1 at 48 months. Six feature selection models were used to identify the common features in each outcome. Six classification methods were applied to measure the accuracy of the selected features in classifying the subjects into progressors and non-progressors. Classification of the best features was done using an automatic machine learning interface and the area under the curve (AUC). To prioritize the top five features, sparse partial least square (sPLS) method was used. Results: For the classification of the best common features in each outcome, Multi-Layer Perceptron (MLP) achieved the highest AUC in Prop_CV_96M, KL and JSN (0.80, 0.88, 0.95), and Gradient Boosting Machine for Prop_CV_48M (0.70). sPLS showed the baseline top five features to predict knee OA progressors are the joint space width, mean cartilage thickness of the medial tibial plateau and sub-regions and JSN. Conclusion: In this comprehensive study using a large number of features ( n = 1107) and MRI outcomes in addition to radiological outcomes, we identified the best features and classification methods for knee OA structural progressors. Data revealed baseline X-ray and MRI-based features could predict early OA knee progressors and that MLP is the best classification method.

This is a report of developmental trajectories of cortical surface area and cortical volume in the NIH MRI Study of Normal Brain Development. The quality-controlled sample included 384 individual typically-developing subjects with repeated scanning (1–3 per subject, total scans n=753) from 4.9 to 22.3 years of age. The best-fit model (cubic, quadratic, or first-order linear) was identified at each vertex using mixed-effects models, with statistical correction for multiple comparisons using random field theory. Analyses were performed with and without controlling for total brain volume. These data are provided for reference and comparison with other databases. Further discussion and interpretation on cortical developmental trajectories can be found in the associated Ducharme et al.׳s article “Trajectories of cortical thickness maturation in normal brain development – the importance of quality control procedures” (Ducharme et al., 2015) [1].

BACKGROUND:Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. METHODS:The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects' island membership indices and transmission cluster membership indices with the adjusted Rand index. RESULTS AND CONCLUSION:Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs.

Abstract Background The regulation of the circadian clock genes, which coordinate the activity of the immune system, is disturbed in inflammatory bowel disease (IBD). Emerging evidence suggests that butyrate, a short-chain fatty acid produced by the gut microbiota is involved in the regulation of inflammatory responses as well as circadian-clock genes. This study was conducted to investigate the effects of sodium-butyrate supplementation on the expression of circadian-clock genes, inflammation, sleep and life quality in active ulcerative colitis (UC) patients. Methods In the current randomized placebo-controlled trial, 36 active UC patients were randomly divided to receive sodium-butyrate (600 mg/kg) or placebo for 12-weeks. In this study the expression of circadian clock genes (CRY1, CRY2, PER1, PER2, BMAl1 and CLOCK) were assessed by real time polymerase chain reaction (qPCR) in whole blood. Gene expression changes were presented as fold changes in expression (2^-ΔΔCT) relative to the baseline. The faecal calprotectin and serum level of high-sensitivity C-reactive protein (hs-CRP) were assessed by enzyme-linked immunosorbent assay method (ELIZA). Moreover, the sleep quality and IBD quality of life (QoL) were assessed by Pittsburgh sleep quality index (PSQI) and inflammatory bowel disease questionnaire-9 (IBDQ-9) respectively before and after the intervention. Results The results showed that sodium-butyrate supplementation in comparison with placebo significantly decreased the level of calprotectin (-133.82 ± 155.62 vs. 51.58 ± 95.57, P-value

Abstract Capturing the conditional covariances or correlations among the elements of a multivariate response vector based on covariates is important to various fields including neuroscience, epidemiology and biomedicine. We propose a new method called Covariance Regression with Random Forests (CovRegRF) to estimate the covariance matrix of a multivariate response given a set of covariates, using a random forest framework. Random forest trees are built with a splitting rule specially designed to maximize the difference between the sample covariance matrix estimates of the child nodes. We also propose a significance test for the partial effect of a subset of covariates. We evaluate the performance of the proposed method and significance test through a simulation study which shows that the proposed method provides accurate covariance matrix estimates and that the Type-1 error is well controlled. An application of the proposed method to thyroid disease data is also presented. CovRegRF is implemented in a freely available R package on CRAN.

The impact of neurodevelopmental mutations on functional brain connectivity is poorly understood. Here the authors identify thalamo-sensorimotor dysconnectivity dimensions shared across 16p11.2 and 22q11.2 copy number variants, autism and schizophrenia, but not ADHD.

Abstract Introduction 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. Methods Voxelwise regression models tested the cross‐sectional association between [18F]fluorodeoxyglucose ([18F]FDG) 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 [18F]FDG in amyloid positive (Aβ+) and negative (Aβ−) subjects. Results Higher concentrations of plasma and cerebrospinal fluid NfL were associated with reduced [18F]FDG uptake in correspondent brain regions. In Aβ+ participants, NfL associates with hypometabolism in AD‐vulnerable regions. Longitudinal changes in the association [18F]FDG‐NfL were confined to cognitively impaired Aβ+ individuals. Discussion These findings indicate that plasma NfL is a proxy for neurodegeneration in AD‐related regions in Aβ+ subjects.

Abstract Background Conventional phylogenetic clustering approaches rely on arbitrary cutpoints applied a posteriori to phylogenetic estimates. Although in practice, Bayesian and bootstrap-based clustering tend to lead to similar estimates, they often produce conflicting measures of confidence in clusters. The current study proposes a new Bayesian phylogenetic clustering algorithm, which we refer to as DM-PhyClus (Dirichlet-Multinomial Phylogenetic Clustering), that identifies sets of sequences resulting from quick transmission chains, thus yielding easily-interpretable clusters, without using any ad hoc distance or confidence requirement. Results Simulations reveal that DM-PhyClus can outperform conventional clustering methods, as well as the Gap procedure, a pure distance-based algorithm, in terms of mean cluster recovery. We apply DM-PhyClus to a sample of real HIV-1 sequences, producing a set of clusters whose inference is in line with the conclusions of a previous thorough analysis. Conclusions DM-PhyClus, by eliminating the need for cutpoints and producing sensible inference for cluster configurations, can facilitate transmission cluster detection. Future efforts to reduce incidence of infectious diseases, like HIV-1, will need reliable estimates of transmission clusters. It follows that algorithms like DM-PhyClus could serve to better inform public health strategies.

BACKGROUND:Phylogenetics has been used to investigate HIV transmission among men who have sex with men. This study compares several methodologies to elucidate the role of transmission chains in the dynamics of HIV spread in Quebec, Canada. METHODS:The Quebec Human Immunodeficiency Virus (HIV) genotyping program database now includes viral sequences from close to 4,000 HIV-positive individuals classified as Men who have Sex with Men (MSMs), collected between 1996 and early 2016. Assessment of chain expansion may depend on the partitioning scheme used, and so, we produce estimates from several methods: the conventional Bayesian and maximum likelihood-bootstrap methods, in combination with a variety of schemes for applying a maximum distance criterion, and two other algorithms, DM-PhyClus, a Bayesian algorithm that produces a measure of uncertainty for proposed partitions, and the Gap Procedure, a fast non-phylogenetic approach. Sequences obtained from individuals in the Primary HIV Infection (PHI) stage serve to identify incident cases. We focus on the period ranging from January 1st 2012 to February 1st 2016. RESULTS AND CONCLUSION:The analyses reveal considerable overlap between chain estimates obtained from conventional methods, thus leading to similar estimates of recent temporal expansion. The Gap Procedure and DM-PhyClus suggest however moderately different chains. Nevertheless, all estimates stress that longer older chains are responsible for a sizeable proportion of the sampled incident cases among MSMs. Curbing the HIV epidemic will require strategies aimed specifically at preventing such growth.

Behaviors characterized as restricted and repetitive (RRBs) in autism manifest in diverse ways, from motor mannerisms to intense interests, and are diagnostically defined as interfering with functioning. A variety of early autism interventions target RRBs as preoccupying young autistic children to the detriment of exploration and learning opportunities. In an exploratory study, we developed a novel stimulating play situation including objects of potential interest to autistic children, then investigated repetitive behaviors and object explorations in 49 autistic and 43 age-matched typical young children (20-69 months). Autistic children displayed significantly increased overall frequency and duration of repetitive behaviors, as well as increased specific repetitive behaviors. However, groups did not significantly differ in frequency and duration of overall object explorations, in number of different objects explored, or in explorations of specific objects. Exploratory analyses found similar or greater exploration of literacy-related objects in autistic compared to typical children. Correlations between repetitive behaviors and object explorations (their frequency and duration) revealed positive, not negative, associations in both groups. Our findings, from a novel situation incorporating potential autistic interests, suggest that RRBs do not necessarily displace exploration and its possibilities for learning in autism.

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.

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