Traits Contributing to the Autistic Spectrum

It is increasingly recognised that traits associated with autism reflect a spectrum with no clear boundary between typical and atypical behaviour. Dimensional traits are needed to investigate the broader autism phenotype.Ninety-three individual measures reflecting components of social, communication and repetitive behaviours characterising autistic spectrum disorder (ASD) were identified between the ages of 6 months and 9 years from the ALSPAC database. Using missing value imputation, data for 13,138 children were analysed. Factor analysis suggested the existence of 7 factors explaining 85% of the variance. The factors were labelled: verbal ability, language acquisition, social understanding, semantic-pragmatic skills, repetitive-stereotyped behaviour, articulation and social inhibition. Four factors (1, 3, 5 and 7) were specific to ASD being more strongly associated with this phenotype than other co-morbid conditions while other factors were more associated with learning difficulties and specific language impairment. Nevertheless, all 7 factors contributed independently to the explanation of ASD (p<0.001). Exploration of putative genetic causal factors such as variants in the CNTNAP2 gene showed a varying pattern of associations with these traits. An alternative predictive model of ASD was derived using four individual measures: the coherence subscale of the Children's Communication Checklist (9y), the Social and Communication Disorders Checklist (91 m), repetitive behaviour (69 m) and the sociability subscale of the Emotionality Activity and Sociability measure (38 m). Although univarably these traits performed better than some factors, their combined explanations of ASD were similar (R(2) =  0.48).These results support the fractional nature of ASD with different aetiological origins for these components despite pleiotropic genetic effects being observed. These traits are likely to be useful in the exploration of ASD

Differential Item Functioning on Antisocial Behavior Scale Items for Adolescents and Young Adults from Single-Parent and Two-Parent Families

We investigated measurement equivalence in two antisocial behavior scales (i.e., one scale for adolescents and a second scale for young adults) by examining differential item functioning (DIF) for respondents from single-parent (n = 109) and two-parent families (n = 447). Even though one item in the scale for adolescents and two items in the scale for young adults showed significant DIF, the two scales exhibited non-significant differential test functioning (DTF). Both uniform and nonuniform DIF were investigated and examples of each type were identified. Specifically, uniform DIF was exhibited in the adolescent scale whereas nonuniform DIF was shown in the young adult scale. Implications of DIF results for assessment of antisocial behavior, along with strengths and limitations of the study, are discussed

Enhancing volunteer engagement to achieve desirable outcomes: what can non-profit employers do?

Abstract Engagement is a positive psychological state that is linked with a range of beneficial individual and organizational outcomes. However, the factors associated with volunteer engagement have rarely been examined. Data from 1064 volunteers of a wildlife charity in the United Kingdom revealed that both task- and emotion-oriented organizational support were positively related to volunteer engagement, and volunteer engagement was positively related to volunteer happiness and perceived social worth and negatively related to intent to leave the voluntary organization. Consistent with theory, engagement acted as a mediator between these factors. The implications for future research and the relevance of the findings for voluntary organizations are discussed

Genetic variants and functional pathways associated with resilience to Alzheimer\u27s disease.

Approximately 30% of older adults exhibit the neuropathological features of Alzheimer\u27s disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer\u27s disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values \u3c 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values \u3c 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer\u27s disease (P-values \u3e 0.42) nor associated with APOE (P-values \u3e 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer\u27s disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets

Sex differences in the genetic architecture of cognitive resilience to Alzheimer\u27s disease.

Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer\u27s disease neuropathology at autopsy. Studying individuals who are resilient to the cognitive consequences of Alzheimer\u27s disease neuropathology may uncover novel therapeutic targets to treat Alzheimer\u27s disease. It is well established that there are sex differences in response to Alzheimer\u27s disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified [n (males) = 2093, n (females) = 2931] and sex-interaction [n (both sexes) = 5024] genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 [rs827389, β (females) = 0.08, P (females) = 5.76 × 10-09, β (males) = -0.01, P(males) = 0.70, β (interaction) = 0.09, P (interaction) = 1.01 × 10-04] in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer\u27s disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer\u27s disease may be personalized based on their biological sex and genetic context

Risky business: factor analysis of survey data – assessing the probability of incorrect dimensionalisation

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations.We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of overdimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems