Evidence of assortative mating in autism spectrum disorder

Background Assortative mating is a non-random mating system in which individuals with similar genotypes and/or phenotypes mate with one another more frequently than would be expected in a random mating system. Assortative mating has been hypothesized to play a role in Autism Spectrum Disorder (ASD) in an attempt to explain some of the increase in the prevalence of ASD that has recently been observed. ASD is considered to be a heritable neurodevelopmental disorder but there is limited understanding of its causes. Assortative mating can be explored through both phenotypic and genotypic data, but up until now, has never been investigated through genotypic measures in ASD. Methods We investigated genotypically similar mating pairs using genome-wide Single Nucleotide Polymorphism (SNP) data on trio families (Autism Genome Project (AGP) data (1,590 parents) and Simons Simplex Collection (SSC) data (1962 parents)). To determine whether or not an excess in genetic similarity was present we employed kinship coefficients and examined spousal correlation between the principal components in both the AGP and SSC datasets. We also examined assortative mating using phenotype data on the parents to detect any correlation between ASD traits. Results We found significant evidence of genetic similarity between the parents of ASD offspring using both methods in the AGP dataset. In the SSC, there was also significant evidence of genetic similarity between the parents when explored through spousal correlation. Conclusions This gives further support to the hypothesis that positive assortative mating plays a role in ASD

Creating successful valuing nature initiatives: A guide to analysing local context and developing strong theories of change

The guide aims to help practitioners understand local context and external pressures – the formal and informal institutional, political, legal, economic and social setting of conservation – to guide action for better ecosystem management

Bridging the translational gap: what can synaptopathies tell us about autism?

Multiple molecular pathways and cellular processes have been implicated in the neurobiology of autism and other neurodevelopmental conditions. There is a current focus on synaptic gene conditions, or synaptopathies, which refer to clinical conditions associated with rare genetic variants disrupting genes involved in synaptic biology. Synaptopathies are commonly associated with autism and developmental delay and may be associated with a range of other neuropsychiatric outcomes. Altered synaptic biology is suggested by both preclinical and clinical studies in autism based on evidence of differences in early brain structural development and altered glutamatergic and GABAergic neurotransmission potentially perturbing excitatory and inhibitory balance. This review focusses on the NRXN-NLGN-SHANK pathway, which is implicated in the synaptic assembly, trans-synaptic signalling, and synaptic functioning. We provide an overview of the insights from preclinical molecular studies of the pathway. Concentrating on NRXN1 deletion and SHANK3 mutations, we discuss emerging understanding of cellular processes and electrophysiology from induced pluripotent stem cells (iPSC) models derived from individuals with synaptopathies, neuroimaging and behavioural findings in animal models of Nrxn1 and Shank3 synaptic gene conditions, and key findings regarding autism features, brain and behavioural phenotypes from human clinical studies of synaptopathies. The identification of molecular-based biomarkers from preclinical models aims to advance the development of targeted therapeutic treatments. However, it remains challenging to translate preclinical animal models and iPSC studies to interpret human brain development and autism features. We discuss the existing challenges in preclinical and clinical synaptopathy research, and potential solutions to align methodologies across preclinical and clinical research. Bridging the translational gap between preclinical and clinical studies will be necessary to understand biological mechanisms, to identify targeted therapies, and ultimately to progress towards personalised approaches for complex neurodevelopmental conditions such as autism

Participatory modeling updates expectations for individuals and groups, catalyzing behavior change and collective action in water-energy-food nexus governance

Participatory modeling is a potentially high-impact approach for catalyzing fundamental sustainability transformations. We test if participation in a group system dynamics modeling exercise increases participants' agency through a novel method to evaluate potential behavioral change using expectations measures. A water-energy-food nexus a functionally interdependent but under-conceptualised system with low consensus and high scientific uncertainty -- was mapped and its evolution simulated by 46 participants in three interventions in a region undergoing hydropower infrastructure development in North-eastern Cambodia. Participants' system-related expectations were measured before and after the interventions. Our results suggest that participants became significantly more optimistic about their individual agency to increase agricultural and fishing income, and interestingly, less likely to participate in local government development planning procedures. Findings also reveal how some uncertainties for multiple variables were reduced within and across the groups. Such converging expectations suggest that participatory modelling could contribute to making collective solutions and institutionalised agreements more likely. This research contributes to innovation in sustainability because it unpacks some underlying mechanics of how participatory processes can lead to new adaptive capacities, shared perspectives and collective actions

Weight status of children aged 2-5 years old, attending a paediatric outpatient clinic and its association with parental feeding style and parental perceptions of weight status

Background: A child’s weight status can allow health care professionals to assess their developmental growth. A child having a low or high weight for height could be due to an imbalance in nutrient intake occurring. It is important to balance dietary intake and physical activity to maintain a healthy weight status. Excessive consumption of food can lead to an overweight/obese weight status which is linked to non-communicable diseases. Parental feeding style can directly impact a child’s set of eating behaviours. Therefore, parents have a strong influence over a child’s growth pattern. In addition, parental awareness of childhood obesity is reported to be poor which could be a barrier to interventions. Aim: To determine; (1) the weight status of children aged 2-5 years attending Sligo University Hospital (SUH); (2) current parental feeding styles being utilised; (3) whether parents were able to correctly classify their own weight status and that of their child and if this was associated with parental misclassification of their own weight status and (4) whether parents are interested in further information in this area, and what form this information/guidance should take. Method: A cross-sectional study was conducted in a paediatric outpatient department between September 2018 and May 2019. Data collected included anthropometric measurements and demographic information as well as a validated parental feeding style questionnaire. Data analysis was conducted using SPSS version 24. Statistical significance was set at p \u3c.05. Results: Fifty parents and children were recruited. 72% of children were classified as having a normal weight status, 22% an overweight status and 6% an obese weight status. No parent correctly classified a child as having an overweight status. No association was found between parental misclassification of a child’s weight status and their own weight status. The majority of parents used an encouragement feeding style. 84% of parents reported to be interested in obtaining healthy lifestyle information. The preferred method of receiving this information is in the form of a leaflet. Discussion/Conclusion: The childhood overweight and obesity rates within this cohort are slightly above the national rates for childhood obesity. Parental awareness of childhood overweight/obesity was found to be poor as illustrated in previous studies. Interventions need to be implemented to improve parental classification of a child’s weight status. Parents expressed an interest in receiving health education material in this setting

Functionality of promoter microsatellites of arginine vasopressin receptor 1A (AVPR1A): implications for autism

<p>Abstract</p> <p>Background</p> <p>Arginine vasopressin (AVP) has been hypothesized to play a role in aetiology of autism based on a demonstrated involvement in the regulation of social behaviours. The arginine vasopressin receptor 1A gene (<it>AVPR1A</it>) is widely expressed in the brain and is considered to be a key receptor for regulation of social behaviour. Moreover, genetic variation at <it>AVPR1A </it>has been reported to be associated with autism. Evidence from non-human mammals implicates variation in the 5'-flanking region of <it>AVPR1A </it>in variable gene expression and social behaviour.</p> <p>Methods</p> <p>We examined four tagging single nucleotide polymorphisms (SNPs) (rs3803107, rs1042615, rs3741865, rs11174815) and three microsatellites (RS3, RS1 and AVR) at the <it>AVPR1A </it>gene for association in an autism cohort from Ireland. Two 5'-flanking region polymorphisms in the human <it>AVPR1A</it>, RS3 and RS1, were also tested for their effect on relative promoter activity.</p> <p>Results</p> <p>The short alleles of RS1 and the SNP rs11174815 show weak association with autism in the Irish population (<it>P </it>= 0.036 and <it>P </it>= 0.008, respectively). Both RS1 and RS3 showed differences in relative promoter activity by length. Shorter repeat alleles of RS1 and RS3 decreased relative promoter activity in the human neuroblastoma cell line SH-SY5Y.</p> <p>Conclusions</p> <p>These aligning results can be interpreted as a functional route for this association, namely that shorter alleles of RS1 lead to decreased <it>AVPR1A </it>transcription, which may proffer increased susceptibility to the autism phenotype.</p

Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning

Monitoring wildland fire burn severity is important for assessing ecological outcomes of fire and their spatial patterning as well as guiding efforts to mitigate or restore areas where ecological outcomes are negative. Burn severity mapping products are typically created using satellite reflectance data but must be calibrated to field data to derive meaning. The composite burn index (CBI) is the most widely used field-based method used to calibrate satellite-based burn severity data but important limitations of this approach have yet to be resolved. The objective of this study was focused on predicting CBI from point cloud and visible-spectrum camera (RGB) metrics derived from single-scan terrestrial laser scanning (TLS) datasets to determine the viability of TLS data as an alternative approach to estimating burn severity in the field. In our approach, we considered the predictive potential of post-scan-only metrics, differenced pre- and post-scan metrics, RGB metrics, and all three together to predict CBI and evaluated these with candidate algorithms (i.e., linear model, random forest (RF), and support vector machines (SVM) and two evaluation criteria (R-squared and root mean square error (RMSE)). In congruence with the strata-based observations used to calculate CBI, we evaluated the potential approaches at the strata level and at the plot level using 70 TLS and 10 RGB independent variables that we generated from the field data. Machine learning algorithms successfully predicted total plot CBI and strata-specific CBI; however, the accuracy of predictions varied among strata by algorithm. RGB variables improved predictions when used in conjunction with TLS variables, but alone proved a poor predictor of burn severity below the canopy. Although our study was to predict CBI, our results highlight that TLS-based methods for quantifying burn severity can be an improvement over CBI in many ways because TLS is repeatable, quantitative, faster, requires less field-expertise, and is more flexible to phenological variation and biomass change in the understory where prescribed fire effects are most pronounced. We also point out that TLS data can also be leveraged to inform other monitoring needs beyond those specific to wildland fire, representing additional efficiency in using this approach