The relationship of stalking behaviours to autism spectrum disorders and personality

Stalking perpetration represents a challenge in current forensic research practice in terms of identifying perpetrators and formulating their difficulties, and in developing effective treatment. This thesis explores Autism Spectrum Disorders and Pathological Demand Avoidance (a behavioural profile associated with Autism Spectrum Disorders, characterised by extreme methods of avoiding demands, an anxiety-based need for control over the immediate environment, and turbulent interpersonal relationships) and personality trait models in relation to stalking perpetration. A systematic review identifies the most prevalent clinical factors in stalking perpetration – psychotic disorders and personality disorders. A methodology chapter explores the validity and reliability of online surveys, with emphasis on understanding what makes them suitable for forensic research in the general population, and where the pitfalls may lie. An empirical study investigates the relationship of Pathological Demand Avoidance and Autism Spectrum Disorders with stalking perpetration and personality traits. Pathological Demand Avoidance traits predicted stalking perpetration and Autism Spectrum Disorders traits did not; a mediation analysis exploring the hypothesis that Pathological Demand Avoidance predicted stalking perpetration by way of strategic emotional control was non-significant, suggesting this was not related to stalking perpetration. The relationship of the HEXACO personality traits model to Pathological Demand Avoidance and stalking perpetration was examined, finding that higher levels of Emotionality and lower levels of Honesty predicted stalking perpetration independently of Pathological Demand Avoidance A second post-hoc study found that the gender distribution in the sample overall did not impact the relationships found between Pathological Demand Avoidance, Autism Spectrum Disorders, and stalking perpetration. Females in general scored more highly than males on the Emotionality and Extraversion aspects of the HEXACO model, and a Chi-square analysis indicated no significant differences between genders on specific types of stalking behaviours perpetrated

The relationship of stalking behaviours to autism spectrum disorders and personality

Stalking perpetration represents a challenge in current forensic research practice in terms of identifying perpetrators and formulating their difficulties, and in developing effective treatment. This thesis explores Autism Spectrum Disorders and Pathological Demand Avoidance (a behavioural profile associated with Autism Spectrum Disorders, characterised by extreme methods of avoiding demands, an anxiety-based need for control over the immediate environment, and turbulent interpersonal relationships) and personality trait models in relation to stalking perpetration. A systematic review identifies the most prevalent clinical factors in stalking perpetration – psychotic disorders and personality disorders. A methodology chapter explores the validity and reliability of online surveys, with emphasis on understanding what makes them suitable for forensic research in the general population, and where the pitfalls may lie. An empirical study investigates the relationship of Pathological Demand Avoidance and Autism Spectrum Disorders with stalking perpetration and personality traits. Pathological Demand Avoidance traits predicted stalking perpetration and Autism Spectrum Disorders traits did not; a mediation analysis exploring the hypothesis that Pathological Demand Avoidance predicted stalking perpetration by way of strategic emotional control was non-significant, suggesting this was not related to stalking perpetration. The relationship of the HEXACO personality traits model to Pathological Demand Avoidance and stalking perpetration was examined, finding that higher levels of Emotionality and lower levels of Honesty predicted stalking perpetration independently of Pathological Demand Avoidance A second post-hoc study found that the gender distribution in the sample overall did not impact the relationships found between Pathological Demand Avoidance, Autism Spectrum Disorders, and stalking perpetration. Females in general scored more highly than males on the Emotionality and Extraversion aspects of the HEXACO model, and a Chi-square analysis indicated no significant differences between genders on specific types of stalking behaviours perpetrated

The measurement of adult pathological demand avoidance traits

Pathological (“extreme”) demand avoidance (PDA) involves obsessively avoiding routine demands and extreme emotional variability. It is clinically linked to autism spectrum disorder (ASD). The observer-rated EDA Questionnaire (EDA-Q) for children was adapted as an adult self-report (EDA-QA), and tested in relation to personality and the short-form Autism Screening Questionnaire (ASQ). Study 1 (n = 347) found the EDA-QA reliable, univariate, and correlated with negative affect, antagonism, disinhibition, psychoticism, and ASQ scores. Study 2 (n = 191) found low agreeableness, greater Emotional Instability, and higher scores on the full ASQ predicted EDA-QA. PDA can screened for using this tool, occurs in the general population, and is associated with extremes of personality. Future studies will examine if PDA occurs in other clinical populations

EMPOWERING GLOBAL NUTRITION WITH DIGITAL TECHNOLOGY : PRACTICAL IMPLEMENTATION IN CLINICAL PRACTICE AND RESEARCH

Peer reviewedPublisher PD

Characterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study

Background: Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, their correlations with fasting values and their inter- and intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort. Methods: In the ZOE PREDICT 1 study (n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by a Nightingale NMR panel in fasting and postprandial (4 and 6 h after a 3.7 MJ mixed nutrient meal, with a second 2.2 MJ mixed nutrient meal at 4 h) serum samples. For each metabolite, inter- and intra-individual variability over time was evaluated using linear mixed modelling and intraclass correlation coefficients (ICC) were calculated. Results: Postprandially, 85% (of 250 metabolites) significantly changed from fasting at 6 h (47% increased, 53% decreased; Kruskal–Wallis), with 37 measures increasing by >25% and 14 increasing by >50%. The largest changes were observed in very large lipoprotein particles and ketone bodies. Seventy-one percent of circulating metabolites were strongly correlated (Spearman’s rho >0.80) between fasting and postprandial timepoints, and 5% were weakly correlated (rho <0.50). The median ICC of the 250 metabolites was 0.91 (range 0.08–0.99). The lowest ICCs (ICC <0.40, 4% of measures) were found for glucose, pyruvate, ketone bodies (β-hydroxybutyrate, acetoacetate, acetate) and lactate. Conclusions: In this large-scale postprandial metabolomic study, circulating metabolites were highly variable between individuals following sequential mixed meals. Findings suggest that a meal challenge may yield postprandial responses divergent from fasting measures, specifically for glycolysis, essential amino acid, ketone body and lipoprotein size metabolites

Neuronal activity-dependent gene expression is stimulus-specific and changes with neuronal maturation

IntroductionNeuronal activity-dependent gene expression is fundamental to a wide variety of brain functions. The field of neuronal activity-induced gene expression has advanced greatly due to studies performed in early neuronal cultures (7 to 10 DIV) and stimulated with different activation protocols. However, the effect of the developmental stage as well as the influence of specific protocol stimuli like potassium chloride (KCl)-induced depolarization, bicuculline (Bic)-mediated synaptic activation and TTX-withdrawal (TTXw) on activity-induced transcription has not been systematically studied.MethodsTo analyze the influence of neuronal maturation on activity-induced transcription, we used neuronal primary cultures to compare electrophysiological and transcriptional responses at 7 days in vitro (DIV) and 21 DIV upon KCl and Bic stimulation. Also, mature neurons in culture were subjected to treatments with KCl, Bic and TTXw and the transcriptional changes were assessed by RNA-Seq and post-hoc bioinformatic analysis.ResultsOur results demonstrate that the developmental stage of neurons profoundly influences neuronal firing and gene expression. The response to KCl and Bicuculline was dramatically different, even though these compound-based activation protocols have been widely used and considered as methods that produce equivalent effects. Therefore, we next asked how 21DIV neurons, more advanced in their development, react to different stimuli and observed that KCl, Bic and TTXw, which trigger different firing patterns, induce specific transcriptional profiles with unique temporal dynamics and activating a variety of gene groups.ConclusionThese findings hold both technical and conceptual significance. Technically, they underscore the importance of accounting for neuronal maturation and activation protocols when studying gene expression. Conceptually, they demonstrate that neuronal development and drug-induced firing patterns generate distinct expression profiles, which could be crucial for a deeper understanding of transcription-dependent plasticity mechanisms

Postprandial glycaemic dips predict appetite and energy intake in healthy individuals

Understanding how to modulate appetite in humans is key to developing successful weight loss interventions. Here, we showed that postprandial glucose dips 2–3 h after a meal are a better predictor of postprandial self-reported hunger and subsequent energy intake than peak glucose at 0–2 h and glucose incremental area under the blood glucose curve at 0–2 h. We explore the links among postprandial glucose, appetite and subsequent energy intake in 1,070 participants from a UK exploratory and US validation cohort, who consumed 8,624 standardized meals followed by 71,715 ad libitum meals, using continuous glucose monitors to record postprandial glycaemia. For participants eating each of the standardized meals, the average postprandial glucose dip at 2–3 h relative to baseline level predicted an increase in hunger at 2–3 h (r = 0.16, P < 0.001), shorter time until next meal (r = −0.14, P < 0.001), greater energy intake at 3–4 h (r = 0.19, P < 0.001) and greater energy intake at 24 h (r = 0.27, P < 0.001). Results were directionally consistent in the US validation cohort. These data provide a quantitative assessment of the relevance of postprandial glycaemia in appetite and energy intake modulation

Effects of a personalized nutrition program on cardiometabolic health: a randomized controlled trial

Large variability exists in people’s responses to foods. However, the efficacy of personalized dietary advice for health remains understudied. We compared a personalized dietary program (PDP) versus general advice (control) on cardiometabolic health using a randomized clinical trial. The PDP used food characteristics, individual postprandial glucose and triglyceride (TG) responses to foods, microbiomes and health history, to produce personalized food scores in an 18-week app-based program. The control group received standard care dietary advice (US Department of Agriculture Guidelines for Americans, 2020–2025) using online resources, check-ins, video lessons and a leaflet. Primary outcomes were serum low-density lipoprotein cholesterol and TG concentrations at baseline and at 18 weeks. Participants (n = 347), aged 41–70 years and generally representative of the average US population, were randomized to the PDP (n = 177) or control (n = 170). Intention-to-treat analysis (n = 347) between groups showed significant reduction in TGs (mean difference = −0.13 mmol l−1; log-transformed 95% confidence interval = −0.07 to −0.01, P = 0.016). Changes in low-density lipoprotein cholesterol were not significant. There were improvements in secondary outcomes, including body weight, waist circumference, HbA1c, diet quality and microbiome (beta-diversity) (P < 0.05), particularly in highly adherent PDP participants. However, blood pressure, insulin, glucose, C-peptide, apolipoprotein A1 and B, and postprandial TGs did not differ between groups. No serious intervention-related adverse events were reported. Following a personalized diet led to some improvements in cardiometabolic health compared to standard dietary advice

Human postprandial responses to food and potential for precision nutrition

Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866