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IntroductionGenomic conditions can be associated with developmental delay, intellectual disability and physical and mental health symptoms, but are individually rare and variable, which limits the use of standard clinical guidelines. A simple screening tool to identify young people with genetic conditions associated with neurodevelopmental disorders (ND-GC) who could benefit from further support would be of considerable value. We used machine learn approaches to address this question.MethodsA total of 489 individuals were included: 376 with a ND-GC, mean age=9.33, 63% male) and 113 unaffected siblings; mean age=10.35, 50% male). Primary carers completed detailed assessments of behavioural, neurodevelopmental and psychiatric symptoms and physical health conditions. Machine learning techniques (elastic net regression, random forests, support vector machines and artificial neural networks) were used to develop classifiers of ND-GC status using a limited set of variables. Exploratory Graph Analysis was used to understand associations within the final variable set.ResultsWe identified a set of 30 variables best discriminating between ND-GC carriers and control individuals, which formed 4 dimensions: Anxiety, Motor Development, Insomnia and Depression. All methods showed high discrimination accuracy with Linear Support Vector machines outperforming other methods (AUROC between 0.959 and 0.971).ConclusionsIn this study we developed models that identified a compact set of psychiatric and physical health measures that differentiate individuals with a ND-GC from controls and highlight the structure within these measures. This work is a step toward developing of a screening instrument to select young people with ND-GCs who might benefit from further specialist assessment.

Aims Growing evidence suggests that poor sleep health is associated with cardiovascular risk. However, research in this area often relies upon recollection dependent questionnaires or diaries. Accelerometers provide an alternative tool for measuring sleep parameters objectively. This study examines the association between wrist-worn accelerometer-derived sleep onset timing and cardiovascular disease (CVD). Methods and results We derived sleep onset and waking up time from accelerometer data collected from 103 712 UK Biobank participants over a period of 7 days. From this, we examined the association between sleep onset timing and CVD incidence using a series of Cox proportional hazards models. A total of 3172 cases of CVD were reported during a mean follow-up period of 5.7 (±0.49) years. An age- and sex-controlled base analysis found that sleep onset time of 10:00 p.m.–10:59 p.m. was associated with the lowest CVD incidence. An additional model, controlling for sleep duration, sleep irregularity, and established CVD risk factors, did not attenuate this association, producing hazard ratios of 1.24 (95% confidence interval, 1.10–1.39; P Conclusions Our findings suggest the possibility of a relationship between sleep onset timing and risk of developing CVD, particularly for women. We also demonstrate the potential utility of collecting information about sleep parameters via accelerometry-capable wearable devices, which may serve as novel cardiovascular risk indicators.

Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an unmet need to move away from the current approach of group-wise comparisons to methods with the sensitivity to detect altered tissue states at the individual level. This would ultimately enable the early detection and interpretation of microstructural abnormalities in individual patients, an important step towards personalized medicine in translational imaging. To this end, Detect was developed to advance diffusion magnetic resonance imaging tractometry towards single-patient analysis. By operating on the manifold of white-matter pathways and learning normative microstructural features, our framework captures idiosyncrasies in patterns along white-matter pathways. Our approach paves the way from traditional group-based comparisons to true personalized radiology, taking microstructural imaging from the bench to the bedside. The authors propose Detect, a browser-based anomaly detection framework for diffusion magnetic resonance imaging tractometry data. The tool leverages normative microstructural brain features derived from healthy participants using deep autoencoders to detect anomalies at the individual level.

Objective: 22q11.2 deletion syndrome (22q11DS) is among the strongest known genetic risk factors for schizophrenia. Previous studies have reported variable alterations in subcortical brain structures in 22q11DS. To better characterize subcortical alterations in 22q11DS, including modulating effects of clinical and genetic heterogeneity, the authors studied a large multicenter neuroimaging cohort from the ENIGMA 22q11.2 Deletion Syndrome Working Group. Methods: Subcortical structures were measured using harmonized protocols for gross volume and subcortical shape morphometry in 533 individualswith 22q11DS and 330matched healthy control subjects (age range, 6-56 years; 49% female). Results: Compared with the control group, the 22q11DS group showed lower intracranial volume (ICV) and thalamus, putamen, hippocampus, and amygdala volumes and greater lateral ventricle, caudate, and accumbens volumes (Cohen's d values, 20.90 to 0.93). Shape analysis revealed complex differences in the 22q11DS group across all structures. The larger A-D deletion was associated with more extensive shape alterations compared with the smaller A-B deletion. Participants with 22q11DS with psychosis showed lower ICV and hippocampus, amygdala, and thalamus volumes (Cohen's d values, 20.91 to 0.53) compared with participants with 22q11DS without psychosis. Shape analysis revealed lower thickness and surface area across subregions of these structures. Compared with subcortical findings from other neuropsychiatric disorders studied by the ENIGMA consortium, significant convergence was observed between participants with 22q11DS with psychosis and participants with schizophrenia, bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. Conclusions: In the largest neuroimaging study of 22q11DS to date, the authors found widespread alterations to subcortical brain structures, which were affected by deletion size and psychotic illness. Findings indicate significant overlap between 22q11DS-associated psychosis, idiopathic schizophrenia, and other severe neuropsychiatric illnesses.

BackgroundWhile genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. Despite this, few studies have investigated electrophysiological activity and connectivity in this high-risk group.MethodsMagnetoencephalography (MEG) was used to investigate resting-state cortical oscillatory patterns in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, IQ and neurodevelopmental symptoms.ResultsChildren with 22q11.2DS had atypical oscillatory activity and functional connectivity across multiple frequency bands. In the 22q11.2DS group, low frequency (alpha band) activity was positively associated with cognitive ability, while connectivity was negatively associated with ASD and ADHD symptoms. Frontal high frequency (gamma band) activity and connectivity were positively associated with ASD and ADHD symptoms respectively, while posterior gamma activity was negatively associated with ASD symptoms.ConclusionsThese findings highlight that haploinsufficiency at the 22q11.2 locus alters both local and long-range cortical circuitry, which could be a mechanism underlying neurodevelopmental vulnerability in this high risk group.

BackgroundCaring for children with pathogenic neurodevelopmental Copy Number Variants (CNVs) (ie, deletions and duplications of genetic material) can place a considerable burden on parents and their quality of life. Our study is the first to examine the frequency of psychiatric diagnoses in mothers of children with CNVs compared with the frequency of psychiatric problems in age-matched mothers from a large community study.MethodsCase–control study. 268 mothers of children with a CNV diagnosed in a medical genetics clinic and 2680 age-matched mothers taking part in the Avon Longitudinal Study of Parents and Children study.ResultsMothers of children with CNVs reported higher frequency of depression, anorexia, bulimia, alcohol abuse and drug addiction problems compared with the age-matched mothers from the community sample. Focusing on psychiatric problems arising immediately after the birth of the index child, we found that the levels of depression symptoms were similar between the two groups (48% in mothers of children with CNVs vs 44% in mothers of the community sample, p=0.43), but mothers of children with CNVs had higher frequency of anxiety symptoms (55%) compared with mothers from the community sample (30%, p=0.03).ConclusionOur study highlights the need for healthcare providers to devise treatment plans that not only focus on meeting the child’s needs but also assess and, if needed, address the mental health needs of the parent.

AimsGrowing evidence suggests that sleep quality is associated with cardiovascular risk. However, research in this area often relies upon recollection dependant questionnaires or diaries. Accelerometers provide an alternative tool for deriving sleep parameters measuring sleep patterns objectively. This study examines the associations between accelerometer derived sleep onset timing and cardiovascular disease (CVD).Methods and ResultsWe derived sleep onset and waking up time from accelerometer data collected from 103,712 UK Biobank participants over a period of seven days. From this, we examined the association between sleep onset timing and CVD incidence using a series of Cox proportional hazards models. 3172 cases of CVD were reported during a mean follow-up period of 5·7 (±0·49) years. An age- and sex-controlled base analysis found that sleep onset time of 10:00pm-10:59pm was associated with the lowest CVD incidence. A fully adjusted model, additionally controlling for sleep duration, sleep irregularity, and established CVD risk factors, was unable to eliminate this association, producing hazard ratios of 1·24 (95% CI, 1·10–1·39;pp=0·04), and 1·25 (1·02–1·52;p=0·03) for sleep onset ConclusionsOur findings suggest an independent relationship between sleep onset timing and risk of developing CVD, particularly for women. We also demonstrate the potential utility of collecting information about sleep parameters via accelerometry-capable wearable devices, which may serve as novel cardiovascular risk indicators.Translational PerspectiveAbnormal sleep timing is a feature of poor-quality sleep and is likely to be associated with cardiovascular diseases. Accelerometer-derived measures of sleep quality, particularly sleep timing, may be associated with greater vulnerability to cardiovascular disease, particularly in women. Onset of sleep timing may constitute a novel cardiovascular risk factor and target for preventative intervention. Wearable devices equipped with accelerometers may be useful in assessing sleep related cardiovascular disease risk factors as they would allow passive measurement of sleep parameters, such as sleep timing.

BackgroundThe prevalence and impact of motor coordination difficulties in children with copy number variants associated with neurodevelopmental disorders (ND-CNVs) remains unknown. This study aims to advance understanding of motor coordination difficulties in children with ND-CNVs and establish relationships between intelligence quotient (IQ) and psychopathology.Methods169 children with an ND-CNV (67% male, median age = 8.88 years, range 6.02–14.81) and 72 closest-in-age unaffected siblings (controls; 55% male, median age = 10.41 years, s.d. = 3.04, range 5.89–14.75) were assessed with the Developmental Coordination Disorder Questionnaire, alongside psychiatric interviews and standardised assessments of IQ.ResultsThe children with ND-CNVs had poorer coordination ability (b = 28.98, p < 0.001) and 91% of children with an ND-CNV screened positive for suspected developmental coordination disorder, compared to 19% of controls (OR = 42.53, p < 0.001). There was no difference in coordination ability between ND-CNV genotypes (F = 1.47, p = 0.184). Poorer coordination in children with ND-CNV was associated with more attention deficit hyperactivity disorder (ADHD) (β = −0.18, p = 0.021) and autism spectrum disorder trait (β = −0.46, p < 0.001) symptoms, along with lower full-scale (ß = 0.21, p = 0.011), performance (β = −0.20, p = 0.015) and verbal IQ (β = 0.17, p = 0.036). Mediation analysis indicated that coordination ability was a full mediator of anxiety symptoms (69% mediated, p = 0.012), and a partial mediator of ADHD (51%, p = 0.001) and autism spectrum disorder trait symptoms (66%, p < 0.001) as well as full scale IQ (40%, p = 0.002), performance IQ (40%, p = 0.005) and verbal IQ (38%, p = 0.006) scores.ConclusionsThe findings indicate that poor motor coordination is highly prevalent and closely linked to risk of mental health disorder and lower intellectual function in children with ND-CNVs. Future research should explore whether early interventions for poor coordination ability could ameliorate neurodevelopmental risk.

22q11.2 deletion syndrome (22q11DS)—a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22—is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6–52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen’s d’s ranging from −0.9 to −1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers. Sin financiación 15.992 JCR (2020) Q1, 10/295 Biochemistry & Molecular Biology 5.071 SJR (2020) Q1, 5/85 Cellular and Molecular Neuroscience No data IDR 2020 UEM

Caring for children with pathogenic neurodevelopmental Copy Number Variants (CNVs) (i.e., deletions and duplications of genetic material) can place a considerable burden on parents, and their quality of life. Our study is the first to examine the frequency of psychiatric diagnoses in mothers of children with CNVs compared to the frequency of psychiatric problems in age-matched mothers from a large community study. 268 mothers of children with CNVs had higher frequency of depression compared to the 2,680 age-matched mothers (p

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen’s d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = −1.01/−1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.

BackgroundA number of genomic conditions caused by copy number variants (CNVs) are associated with a high risk of neurodevelopmental and psychiatric disorders (ND-CNVs). Although these patients also tend to have cognitive impairments, few studies have investigated the range of emotion and behaviour problems in young people with ND-CNVs using measures that are suitable for those with learning difficulties.MethodsA total of 322 young people with 13 ND-CNVs across eight loci (mean age: 9.79 years, range: 6.02–17.91, 66.5% male) took part in the study. Primary carers completed the Developmental Behaviour Checklist (DBC).ResultsOf the total, 69% of individuals with an ND-CNV screened positive for clinically significant difficulties. Young people from families with higher incomes (OR = 0.71, CI = 0.55–0.91, p = .008) were less likely to screen positive. The rate of difficulties differed depending on ND-CNV genotype (χ2 = 39.99, p < 0.001), with the lowest rate in young people with 22q11.2 deletion (45.7%) and the highest in those with 1q21.1 deletion (93.8%). Specific patterns of strengths and weaknesses were found for different ND-CNV genotypes. However, ND-CNV genotype explained no more than 9–16% of the variance, depending on DBC subdomain.ConclusionsEmotion and behaviour problems are common in young people with ND-CNVs. The ND-CNV specific patterns we find can provide a basis for more tailored support. More research is needed to better understand the variation in emotion and behaviour problems not accounted for by genotype.

BackgroundA number of disorders caused by copy number variants (CNVs) are associated with a high risk of neurodevelopmental and psychiatric disorders and cognitive impairments (ND-CNVs). Few studies of ND-CNVs have investigated the emotional and behavioural problems that are important outcomes in young people with developmental and intellectual disabilities using appropriate measures.Methods322 young people with 13 ND-CNVs across eight loci (mean age:9.79 years, range:6.02-17.91, 66.5% male) took part in the study. Primary carers completed the Developmental Behaviour Checklist (DBC).ResultsSixty-seven percent of individuals with an ND-CNV screened positive for clinically significant difficulties. Young people from families with higher incomes (OR=0.71, CI=0.55 – 0.92, p=.009) were less likely to screen positive. Young people born after prolonged labour (OR=2.87, CI=1.18-8.13, p=.030) were more likely to screen positive. The rate of difficulties differed depending on ND-CNV genotype (Deviance=25.83, p=.011), with the lowest rate in 22q11.2 deletion (46%) and the highest in 1q21.1 deletion (87.5%). Individuals with inherited ND-CNVs had greater difficulties (F=6.54, df=1, p=.012, ηp2=.050), including higher self-absorbed (F=5.01, df=1, p=.027, ηp2=.039) and communication disturbance scores (F=9.13, df=1, p=.003, ηp2=.068). Specific patterns of strengths and weaknesses were found for different ND-CNV genotypes. However, ND-CNV genotype explained no more than 7-16% of variance, depending on subdomain.ConclusionsBehavioural and emotional problems are common in young people with ND-CNVs. The ND-CNV specific patterns we find can provide a basis for more tailored support. More research is needed to better understand the variation in behavioural and emotional problems not accounted for by genotype.

Salmonella infection is a globally important cause of gastroenteritis and systemic disease and is a useful tool to study immune responses in the intestine. Although mechanisms leading to immune responses against Salmonella have been extensively studied, questions remain about how bacteria travel from the intestinal mucosa to the mesenteric lymph nodes (MLN), a key site for Ag presentation. In this study, we used a mouse model of infection with Salmonella enterica serovar Typhimurium (STM) to identify changes in intestinal immune cells induced during early infection. We then used fluorescently labeled STM to identify interactions with immune cells from the site of infection through migration in lymph to the MLN. We show that viable STM can be carried in the lymph by any subset of migrating dendritic cells but not by macrophages. Moreover, approximately half of the STM in lymph are not associated with cells at all and travel autonomously. Within the MLN, STM associates with dendritic cells and B cells but predominantly with MLN-resident macrophages. In conclusion, we describe the routes used by STM to spread systemically in the period immediately postinfection. This deeper understanding of the infection process could open new avenues for controlling it.

Background The 22q11.2 deletion is associated with psychiatric and behavioural disorders, intellectual disability and multiple physical abnormalities. Recent research also indicates impaired coordination skills may be part of the clinical phenotype. This study aimed to characterise sensorimotor control abilities in children with 22q11.2 deletion syndrome (22q11.2DS) and investigate their relationships with co-occurring IQ impairments and psychopathology. Methods Fifty-four children with 22q11.2DS and 24 unaffected sibling controls, comparable in age and gender, underwent kinematic analysis of their hand movements, whilst performing a battery of three visuo-manual coordination tasks that measured their tracking, aiming and steering abilities. Additionally, standardised assessments of full-scale IQ (FSIQ), attention deficit hyperactivity disorder, indicative autism spectrum disorder (ASD) and anxiety disorder symptomatology were conducted. Results Children with 22q11.2DS showed deficits on seven of eight kinematic descriptors of movement quality across the three coordination tasks, compared to controls. Within 22q11.2DS cases, the extent of impairment on only three kinematic descriptors was significantly related to FSIQ after correction for multiple testing. Moreover, only error whilst visuo-manually tracking was nominally associated with ADHD symptom counts. Conclusions Impairments in sensorimotor control are seen on a range of visuo-manual tasks in children with 22q11.2DS but the extent of these impairments are largely unrelated to the severity of other psychopathological and intellectual impairments commonly found in children with 22q11.2DS. Electronic supplementary material The online version of this article (10.1186/s11689-019-9271-3) contains supplementary material, which is available to authorized users.

Diffusion MRI (dMRI) is widely used to study the brain’s white matter (WM) microstructure in a range of psychiatric and neurological diseases. As the diffusion tensor model has limitations in brain regions with crossing fibers, novel diffusion MRI reconstruction models may offer more accurate measures of tissue properties, and a better understanding of the brain abnormalities in specific diseases. Here we studied a large sample of 249 participants with 22q11.2 deletion syndrome (22q11DS), a neurogenetic condition associated with high rates of developmental neuropsychiatric disorders, and 224 age-matched healthy controls (HC) (age range: 8-35 years). Participants were scanned with dMRI at eight centers worldwide. Using a meta-analytic approach, we assessed the profile of group differences in four diffusion anisotropy measures to better understand the patterns of WM microstructural abnormalities and evaluate their consistency across alternative measures. When assessed in atlas-defined regions of interest, we found statistically significant differences for all anisotropy measures, all showing a widespread but not always coinciding pattern of effects. The tensor distribution function fractional anisotropy (TDF-FA) showed largest effect sizes all in the same direction (greater anisotropy in 22q11DS than HC). Fractional anisotropy based on the tensor model (FA) showed the second largest effect sizes after TDF-FA; some regions showed higher mean values in 22q11DS, but others lower. Generalized fractional anisotropy (GFA) showed the opposite pattern to TDF-FA with most regions showing lower anisotropy in 22q11DS versus HC. Anisotropic power maps (AP) showed the lowest effect sizes also with a mixed pattern of effects across regions. These results were also consistent across skeleton projection methods, with few differences when projecting anisotropy values from voxels sampled on the FA map or projecting values from voxels sampled from each anisotropy map. This study highlights that different mathematical definitions of anisotropy may lead to different profiles of group differences, even in large, well-powered population studies. Further studies of biophysical models derived from multi-shell dMRI and histological validations may help to understand the sources of these differences. 22q11DS is a promising model to study differences among novel anisotropy/dMRI measures, as group differences are relatively large and there exist animal models suitable for histological validation.