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Variation in the clinical manifestation of dementia has been associated with differences in cognitive reserve, although less is known about the cumulative effects of exposure to cognitive reserve factors over the life course. We examined the association of cognitive reserve-related factors over the lifespan with the risk of dementia in a community-based cohort of older adults. Information on early-life education, socioeconomic status, work complexity at age 20, midlife occupation attainment, and late-life leisure activities was collected in a cohort of dementia-free community dwellers aged 75+ y residing in the Kungsholmen district of Stockholm, Sweden, in 1987-1989. The cohort was followed up to 9 y (until 1996) to detect incident dementia cases. To exclude preclinical phases of disease, participants who developed dementia at the first follow-up examination 3 y after the baseline were excluded (n = 602 after exclusions). Structural equation modelling was used to generate latent factors of cognitive reserve from three periods over the life course: early (before 20 y), adulthood (around 30-55 y), and late life (75 y and older). The correlation between early- and adult-life latent factors was strong (γ = 0.9), whereas early-late (γ = 0.27) and adult-late (γ = 0.16) latent factor correlations were weak. One hundred forty-eight participants developed dementia during follow-up, and 454 remained dementia-free. The relative risk (RR) of dementia was estimated using Cox models with life-course cognitive reserve-enhancing factors modelled separately and simultaneously to assess direct and indirect effects. The analysis was repeated among carriers and noncarriers of the apolipoprotein E (APOE) ε4 allele. A reduced risk of dementia was associated with early- (RR 0.57; 95% CI 0.36-0.90), adult- (RR 0.60; 95% CI 0.42-0.87), and late-life (RR 0.52; 95% CI 0.37-0.73) reserve-enhancing latent factors in separate multivariable Cox models. In a mutually adjusted model, which may have been imprecisely estimated because of strong correlation between early- and adult-life factors, the late-life factor preserved its association (RR 0.65; 95% CI 0.45-0.94), whereas the effect of midlife (RR 0.73; 95% CI 0.50-1.06) and early-life factors (RR 0.76; 95% CI 0.47-1.23) on the risk of dementia was attenuated. The risk declined progressively with cumulative exposure to reserve-enhancing latent factors, and having high scores on cognitive reserve-enhancing composite factors in all three periods over the life course was associated with the lowest risk of dementia (RR 0.40; 95% CI 0.20-0.81). Similar associations were detected among APOE ε4 allele carriers and noncarriers. Limitations include measurement error and nonresponse, with both biases likely favouring the null. Strong correlation between early- and adult-life latent factors may have led to a loss in precision when estimating mutually adjusted effects of all periods. In this study, cumulative exposure to reserve-enhancing factors over the lifespan was associated with reduced risk of dementia in late life, even among individuals with genetic predisposition.

It has been hypothesized that individually-rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. Here we identified more than 20,000 euchromatic SVs from 14 Drosophila melanogaster genome assemblies, of which ~40% are invisible to high specificity short-read genotyping approaches. SVs are common, with 31.5% of diploid individuals harboring a SV in genes larger than 5kb, and 24% harboring multiple SVs in genes larger than 10kb. SV minor allele frequencies are rarer than amino acid polymorphisms, suggesting that SVs are more deleterious. We show that a number of functionally important genes harbor previously hidden structural variants likely to affect complex phenotypes. Furthermore, SVs are overrepresented in candidate genes associated with quantitative trait loci mapped using the Drosophila Synthetic Population Resource. We conclude that SVs are ubiquitous, frequently constitute a heterogeneous allelic series, and can act as rare alleles of large effect. Rare structural variants may account for a significant fraction of variation in complex traits. Here the authors analyse 14 Drosophila melanogaster genomes and find that structural variants are common, found in functionally important genes, and associated with QTLs.

Although the relationship between education and cognitive status is well-known, evidence regarding whether education moderates the trajectory of cognitive change in late life is conflicting. Early studies suggested that higher levels of education attenuate cognitive decline. More recent studies using improved longitudinal methods have not found that education moderates decline. Fewer studies have explored whether education exerts different effects on longitudinal changes within different cognitive domains. In the present study, we analyzed data from 1014 participants in the Victoria Longitudinal Study to examine the effects of education on composite scores reflecting verbal processing speed, working memory, verbal fluency, and verbal episodic memory. Using linear growth models adjusted for age at enrollment (range, 54–95 years) and gender, we found that years of education (range, 6–20 years) was strongly related to cognitive level in all domains, particularly verbal fluency. However, education was not related to rates of change over time for any cognitive domain. Results were similar in individuals older or younger than 70 at baseline, and when education was dichotomized to reflect high or low attainment. In this large longitudinal cohort, education was related to cognitive performance but unrelated to cognitive decline, supporting the hypothesis of passive cognitive reserve with aging. (JINS, 2011, 17, 1039–1046)

Associations have been found between five-factor model (FFM) personality traits and risk of developing specific predementia syndromes such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI). The aims of this study were to: 1) Compare baseline FFM traits between participants who transitioned from healthy cognition or SCD to amnestic MCI (aMCI) versus non-amnestic MCI (naMCI); and 2) Determine the relationship between FFM traits and risk of transition between predementia cognitive states. Participants were 562 older adults from the Einstein Aging Study, 378 of which had at least one follow-up assessment. Baseline data collected included levels of FFM personality traits, anxiety and depressive symptoms, medical history, performance on a cognitive battery, and demographics. Follow-up cognitive diagnoses were also recorded. Mann-Whitney U tests revealed no differences in baseline levels of FFM personality traits between participants who developed aMCI compared to those who developed naMCI. A four-state multistate Markov model revealed that higher levels of conscientiousness were protective against developing SCD while higher levels of neuroticism resulted in an increased risk of developing SCD. Further, higher levels of extraversion were protective against developing naMCI. FFM personality traits may be useful in improving predictions of who is at greatest risk for developing specific predementia syndromes. Information on these personality traits could enrich clinical trials by permitting trials to target individuals who are at greatest risk for developing specific forms of cognitive impairment. These results should be replicated in future studies with larger sample sizes and younger participants.

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

The interplay between mental health and academic behaviours has been understudied. This study examined the relationship between foundational academic behaviours (e.g., attending class and meeting assignment deadlines), student mental health and well-being, and academic performance. Participants consisted of 229 students (52.6% female) who participated in a first-year introductory learning-to-learn course. Findings from structural equation modelling indicated: (a) higher levels of foundational academic behaviours predicted higher GPA, (b) higher levels of emotional well-being predicted higher levels of foundational academic behaviours and higher GPA, and (c) foundational academic behaviours mediated the relationship between emotional well-being and GPA. Findings affirm the integral role of mental health in academic performance and highlight the mediating role of foundational academic behaviours in this relationship. The association between emotional well-being and foundational academic behaviours underscores the multifaceted nature of academic performance and the importance of considering both mental health and foundational academic behaviours in academic success. Findings from this study suggest that managing behaviours that facilitate engagement in academic tasks, and mental health as a potential internal condition for learning, are both important pieces to the academic success puzzle.

The Drosophila Synthetic Population Resource (DSPR) is a newly developed multifounder advanced intercross panel consisting of >1600 recombinant inbred lines (RILs) designed for the genetic dissection of complex traits. Here, we describe the inference of the underlying mosaic founder structure for the full set of RILs from a dense set of semicodominant restriction-site–associated DNA (RAD) markers and use simulations to explore how variation in marker density and sequencing coverage affects inference. For a given sequencing effort, marker density is more important than sequence coverage per marker in terms of the amount of genetic information we can infer. We also assessed the power of the DSPR by assigning genotypes at a hidden QTL to each RIL on the basis of the inferred founder state and simulating phenotypes for different experimental designs, different genetic architectures, different sample sizes, and QTL of varying effect sizes. We found the DSPR has both high power (e.g., 84% power to detect a 5% QTL) and high mapping resolution (e.g., ∼1.5 cM for a 5% QTL).