White matter differences between healthy young ApoE4 carriers and non-carriers identified with tractography and support vector machines.

The apolipoprotein E4 (ApoE4) is an established risk factor for Alzheimer's disease (AD). Previous work has shown that this allele is associated with functional (fMRI) changes as well structural grey matter (GM) changes in healthy young, middle-aged and older subjects. Here, we assess the diffusion characteristics and the white matter (WM) tracts of healthy young (20-38 years) ApoE4 carriers and non-carriers. No significant differences in diffusion indices were found between young carriers (ApoE4+) and non-carriers (ApoE4-). There were also no significant differences between the groups in terms of normalised GM or WM volume. A feature selection algorithm (ReliefF) was used to select the most salient voxels from the diffusion data for subsequent classification with support vector machines (SVMs). SVMs were capable of classifying ApoE4 carrier and non-carrier groups with an extremely high level of accuracy. The top 500 voxels selected by ReliefF were then used as seeds for tractography which identified a WM network that included regions of the parietal lobe, the cingulum bundle and the dorsolateral frontal lobe. There was a non-significant decrease in volume of this WM network in the ApoE4 carrier group. Our results indicate that there are subtle WM differences between healthy young ApoE4 carriers and non-carriers and that the WM network identified may be particularly vulnerable to further degeneration in ApoE4 carriers as they enter middle and old age

Reduced hippocampal volume in healthy young ApoE4 carriers: an MRI study.

The E4 allele of the ApoE gene has consistently been shown to be related to an increased risk of Alzheimer's disease (AD). The E4 allele is also associated with functional and structural grey matter (GM) changes in healthy young, middle-aged and older subjects. Here, we assess volumes of deep grey matter structures of 22 healthy younger ApoE4 carriers and 22 non-carriers (20-38 years). Volumes of the nucleus accumbens, amygdala, caudate nucleus, hippocampus, pallidum, putamen, thalamus and brain stem were calculated by FMRIB's Integrated Registration and Segmentation Tool (FIRST) algorithm. A significant drop in volume was found in the right hippocampus of ApoE4 carriers (ApoE4+) relative to non-carriers (ApoE4-), while there was a borderline significant decrease in the volume of the left hippocampus of ApoE4 carriers. The volumes of no other structures were found to be significantly affected by genotype. Atrophy has been found to be a sensitive marker of neurodegenerative changes, and our results show that within a healthy young population, the presence of the ApoE4+ carrier gene leads to volume reduction in a structure that is vitally important for memory formation. Our results suggest that the hippocampus may be particularly vulnerable to further degeneration in ApoE4 carriers as they enter middle and old age. Although volume reductions were noted bilaterally in the hippocampus, atrophy was more pronounced in the right hippocampus. This finding relates to previous work which has noted a compensatory increase in right hemisphere activity in ApoE4 carriers in response to preclinical declines in memory function. Possession of the ApoE4 allele may lead to greater predilection for right hemisphere atrophy even in healthy young subjects in their twenties

Multiple indices of diffusion identifies white matter damage in mild cognitive impairment and Alzheimer's disease

The study of multiple indices of diffusion, including axial (DA), radial (DR) and mean diffusion (MD), as well as fractional anisotropy (FA), enables WM damage in Alzheimer's disease (AD) to be assessed in detail. Here, tract-based spatial statistics (TBSS) were performed on scans of 40 healthy elders, 19 non-amnestic MCI (MCIna) subjects, 14 amnestic MCI (MCIa) subjects and 9 AD patients. Significantly higher DA was found in MCIna subjects compared to healthy elders in the right posterior cingulum/precuneus. Significantly higher DA was also found in MCIa subjects compared to healthy elders in the left prefrontal cortex, particularly in the forceps minor and uncinate fasciculus. In the MCIa versus MCIna comparison, significantly higher DA was found in large areas of the left prefrontal cortex. For AD patients, the overlap of FA and DR changes and the overlap of FA and MD changes were seen in temporal, parietal and frontal lobes, as well as the corpus callosum and fornix. Analysis of differences between the AD versus MCIna, and AD versus MCIa contrasts, highlighted regions that are increasingly compromised in more severe disease stages. Microstructural damage independent of gross tissue loss was widespread in later disease stages. Our findings suggest a scheme where WM damage begins in the core memory network of the temporal lobe, cingulum and prefrontal regions, and spreads beyond these regions in later stages. DA and MD indices were most sensitive at detecting early changes in MCIa

Using Support Vector Machines with Multiple Indices of Diffusion for Automated Classification of Mild Cognitive Impairment

Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical

Decreased Left Caudate Volume Is Associated with Increased Severity of Autistic-Like Symptoms in a Cohort of ADHD Patients and Their Unaffected Siblings

Autism spectrum disorder (ASD) symptoms frequently occur in individuals with attention-deficit/ hyperactivity disorder (ADHD). While there is evidence that both ADHD and ASD have differential structural brain correlates, knowledge of the structural brain profile of individuals with ADHD with raised ASD symptoms is limited. The presence of ASD-like symptoms was measured by the Children's Social Behavior Questionnaire (CSBQ) in a sample of typically developing controls (n = 154), participants with ADHD (n = 239), and their unaffected siblings (n = 144) between the ages of 8 and 29. Structural magnetic resonance imaging (MRI) correlates of ASD ratings were analysed by studying the relationship between ASD ratings and grey matter volumes using mixed effects models which controlled for ADHD symptom count and total brain volume. ASD ratings were significantly elevated in participants with ADHD relative to controls and unaffected siblings. For the entire group (participants with ADHD, unaffected siblings and TD controls), mixed effect models revealed that the left caudate nucleus volume was negatively correlated with ASD ratings (t = 2.83; P = 0.005). The current findings are consistent with the role of the caudate nucleus in executive function, including the selection of goals based on the evaluation of action outcomes and the use of social reward to update reward representations. There is a specific volumetric profile associated with subclinical ASD-like symptoms in participants with ADHD, unaffected siblings and controls with the caudate nucleus and globus pallidus being of critical importance in predicting the level of ASD-like symptoms in all three groups.</p

Voxel-based morphometry analysis reveals frontal brain differences in participants with ADHD and their unaffected siblings

Contains fulltext : 168270.pdf (publisher's version ) (Closed access)BACKGROUND: Data on structural brain alterations in patients with attention-deficit/hyperactivity disorder (ADHD) have been inconsistent. Both ADHD and brain volumes have a strong genetic loading, but whether brain alterations in patients with ADHD are familial has been underexplored. We aimed to detect structural brain alterations in adolescents and young adults with ADHD compared with healthy controls. We examined whether these alterations were also found in their unaffected siblings, using a uniquely large sample. METHODS: We performed voxel-based morphometry analyses on MRI scans of patients with ADHD, their unaffected siblings and typically developing controls. We identified brain areas that differed between participants with ADHD and controls and investigated whether these areas were different in unaffected siblings. Influences of medication use, age, sex and IQ were considered. RESULTS: Our sample included 307 patients with ADHD, 169 unaffected siblings and 196 typically developing controls (mean age 17.2 [range 8-30] yr). Compared with controls, participants with ADHD had significantly smaller grey matter volume in 5 clusters located in the precentral gyrus, medial and orbitofrontal cortex, and (para)cingulate cortices. Unaffected siblings showed intermediate volumes significantly different from controls in 4 of these clusters (all except the precentral gyrus). Medication use, age, sex and IQ did not have an undue influence on the results. LIMITATIONS: Our sample was heterogeneous, most participants with ADHD were taking medication, and the comparison was cross-sectional. CONCLUSION: Brain areas involved in decision making, motivation, cognitive control and motor functioning were smaller in participants with ADHD than in controls. Investigation of unaffected siblings indicated familiality of 4 of the structural brain differences, supporting their potential in molecular genetic analyses in ADHD research

Teagasc submission made in response to the Consultation Paper on Interim Review of Ireland’s Nitrates Derogation 2019

Teagasc SubmissionSubmission to governmentThis submission was made in response to the consultation process run jointly by the Department of Housing, Planning, Community and Local Government (DHPCLG) and the Department of Agriculture, Food and the Marine (DAFM) inviting views and comments on proposals for the Interim Review of Ireland’s Nitrates Derogation Programme in 2019. It has been prepared by Teagasc’s Water Quality Working Group in consultation with the Gaseous Emissions Working Group. These working groups have members drawn from both the Knowledge Transfer and Research Directorates of Teagasc. It was prepared following consultation with colleagues across Teagasc using their collective knowledge and expertise in agri-environmental science and practice and the implementation of the Good Agricultural Practice (GAP) and Nitrates Derogation Regulations.https://www.teagasc.ie/publications/2019/teagasc-submission-made-in-response-to-the-consultation-paper-on-interim-review-of-irelands-nitrates-derogation-2019.ph

An Analysis of the Cost of the Abatement of Ammonia Emissions in Irish Agriculture to 2030

peer-reviewedThis analysis quantifies the potential to abate national ammonia (NH3) emissions up to 2030. This report is an updated marginal abatement cost curve (MACC) analysis where Teagasc has quantified the abatement potential of a range of ammonia mitigation measures, as well as their associated costs/benefits (see Lanigan et al. 2015 for previous analysis). The objective of this analysis is to quantify the extent and costs associated with meeting future ammonia emission targets that were negotiated as part of the amended Clean Air Policy Package. The requirement to reduce ammonia emissions is urgent, both in terms of compliance with the National Emissions Ceilings Directive (NECD), and as a principal loss pathway for agricultural nitrogen (N). Improvement of N efficiency is a key focus for improving farm efficiency and sustainability as well as reducing the ammonia, nitrate and greenhouse gas (GHG) footprint of agriculture. This is particularly relevant in the context of the national strategies on the development of the agri-food sector: Food Wise 2025, Ag-food strategy 2030 and Ag-Climatise (currently under development) and the newly unveiled EU Farm to Fork Strategy, which is a part of the European Green Deal. Under the baseline scenario (S1), agricultural ammonia emissions are projected to increase by 9% (without any mitigation) by 2030 relative to 2005 levels. While these increases are small in comparison to the targeted increase in agricultural output, they will provide a major challenge to meeting emissions targets, particularly as agriculture comprises over 99% of national emissions. The analysis presented in this report seeks to quantify the ammonia mitigation potential under likely uptake pathways. This is not an exhaustive analysis of all mitigation measures, but represents an assessment of best available techniques, based on scientific, peer-reviewed research carried out by Teagasc and associated national and international research partners. Indeed, any future changes in the sector or in the national emission inventory calculations will require further analysis of the applicability of ammonia mitigation techniques, particularly in terms of housing and storage but also in the context of other reactive N1 emissions. It should also be noted that some mitigation measures, particularly those related to nitrogen application to soils, could result in either higher greenhouse gas emissions or higher nitrate leaching. Compared to a future where no mitigation measures are deployed to address emissions, by 2030 the average technical abatement2 potential was estimated to be approximately 15.26 kt NH3 at a net cost of €10.86 million per annum. However, it should be noted that the net cost (€10.86 million) is comprised of 6 measures that are cost negative (-€22.21 million) and 7 measures that are cost positive (€33.07) and that some of the cost negative measures are predicated on efficiency gains driven by best management practice adoption (e.g. liming and clover measures with associate chemical N reductions). Amongst the thirteen mitigation measures selected for this analysis, 80% of the mitigation potential can be achieved by the full implementation of the mitigation pathways for protected urea and low emission slurry spreading (LESS) techniques for bovines. It should be stressed that this is an assessment of the maximum abatement potential and realising this level of abatement in practice will be extremely challenging. Any increase in agricultural activity beyond the baseline scenario will increase absolute emissions. The level of mitigation achievable is based on the draft AgClimatise measures any delay or reduction in the uptake of these measures will reduce the mitigation achieved. It must also be ensured that all mitigation measures should, where possible, be synergistic with reductions in greenhouse gas emissions and N loss to water

The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders.

BACKGROUND: The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD. METHODS: LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability. RESULTS: Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some 'lessons learnt'. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted). CONCLUSION: We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies

The EU-AIMS Longitudinal European Autism Project (LEAP): clinical characterisation.

BACKGROUND: The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study on biomarkers for autism spectrum disorder (ASD). The current paper describes the clinical characteristics of the LEAP cohort and examines age, sex and IQ differences in ASD core symptoms and common co-occurring psychiatric symptoms. A companion paper describes the overall design and experimental protocol and outlines the strategy to identify stratification biomarkers. METHODS: From six research centres in four European countries, we recruited 437 children and adults with ASD and 300 controls between the ages of 6 and 30 years with IQs varying between 50 and 148. We conducted in-depth clinical characterisation including a wide range of observational, interview and questionnaire measures of the ASD phenotype, as well as co-occurring psychiatric symptoms. RESULTS: The cohort showed heterogeneity in ASD symptom presentation, with only minimal to moderate site differences on core clinical and cognitive measures. On both parent-report interview and questionnaire measures, ASD symptom severity was lower in adults compared to children and adolescents. The precise pattern of differences varied across measures, but there was some evidence of both lower social symptoms and lower repetitive behaviour severity in adults. Males had higher ASD symptom scores than females on clinician-rated and parent interview diagnostic measures but not on parent-reported dimensional measures of ASD symptoms. In contrast, self-reported ASD symptom severity was higher in adults compared to adolescents, and in adult females compared to males. Higher scores on ASD symptom measures were moderately associated with lower IQ. Both inattentive and hyperactive/impulsive ADHD symptoms were lower in adults than in children and adolescents, and males with ASD had higher levels of inattentive and hyperactive/impulsive ADHD symptoms than females. CONCLUSIONS: The established phenotypic heterogeneity in ASD is well captured in the LEAP cohort. Variation both in core ASD symptom severity and in commonly co-occurring psychiatric symptoms were systematically associated with sex, age and IQ. The pattern of ASD symptom differences with age and sex also varied by whether these were clinician ratings or parent- or self-reported which has important implications for establishing stratification biomarkers and for their potential use as outcome measures in clinical trials