Designing Clinical AAC Tablet Applications with Adults who have Mild Intellectual Disabilities

Patients with mild intellectual disabilities (ID) face significant communication barriers within primary care services. This has a detrimental effect on the quality of treatment being provided, meaning the consultation process could benefit from augmentative and alternative communication (AAC) technologies. However, little research has been conducted in this area beyond that of paper-based aids. We address this by extracting design requirements for a clinical AAC tablet application from n=10 adults with mild ID. Our results show that such technologies can promote communication between general practitioners (GPs) and patients with mild ID by extracting symptoms in advance of the consultation via an accessible questionnaire. These symptoms act as a referent and assist in raising the awareness of conditions commonly overlooked by GPs. Furthermore, the application can support people with ID in identifying and accessing healthcare services. Finally, the participants identified 6 key factors that affect the clarity of medical images

Investigating olfactory gene variation and odour identification in older adults

Ageing is associated with a decrease in odour identification. Additionally, deficits in olfaction have been linked to age-related disease and mortality. Heritability studies suggest genetic variation contributes to olfactory identification. The olfactory receptor (OR) gene family is the largest in the human genome and responsible for overall odour identification. In this study, we sought to find olfactory gene family variants associated with individual and overall odour identification and to examine the relationships between polygenic risk scores (PRS) for olfactory-related phenotypes and olfaction. Participants were Caucasian older adults from the Sydney Memory and Ageing Study and the Older Australian Twins Study with genome-wide genotyping data (n = 1395, mean age = 75.52 ± 6.45). The Brief-Smell Identification Test (BSIT) was administered in both cohorts. PRS were calculated from independent GWAS summary statistics for Alzheimer’s disease (AD), white matter hyperintensities (WMH), Parkinson’s disease (PD), hippocampal volume and smoking. Associations with olfactory receptor genes (n = 967), previously identified candidate olfaction-related SNPs (n = 36) and different PRS with BSIT scores (total and individual smells) were examined. All of the relationships were analysed using generalised linear mixed models (GLMM), adjusted for age and sex. Genes with suggestive evidence for odour identification were found for 8 of the 12 BSIT items. Thirteen out of 36 candidate SNPs previously identified from the literature were suggestively associated with several individual BSIT items but not total score. PRS for smoking, WMH and PD were negatively associated with chocolate identification. This is the first study to conduct genetic analyses with individual odorant identification, which found suggestive olfactory-related genes and genetic variants for multiple individual BSIT odours. Replication in independent and larger cohorts is needed

A meta-analysis of genome-wide association studies of growth differentiation Factor-15 concentration in blood

Blood levels of growth differentiation factor-15 (GDF-15), also known as macrophage inhibitory cytokine-1 (MIC-1), have been associated with various pathological processes and diseases, including cardiovascular disease and cancer. Prior studies suggest genetic factors play a role in regulating blood MIC-1/GDF-15 concentration. In the current study, we conducted the largest genome-wide association study (GWAS) to date using a sample of ∼5,400 community-based Caucasian participants, to determine the genetic variants associated with MIC-1/GDF-15 blood concentration. Conditional and joint (COJO), gene-based association, and gene-set enrichment analyses were also carried out to identify novel loci, genes, and pathways. Consistent with prior results, a locus on chromosome 19, which includes nine single nucleotide polymorphisms (SNPs) (top SNP, rs888663, p = 1.690 × 10-35), was significantly associated with blood MIC-1/GDF-15 concentration, and explained 21.47% of its variance. COJO analysis showed evidence for two independent signals within this locus. Gene-based analysis confirmed the chromosome 19 locus association and in addition, a putative locus on chromosome 1. Gene-set enrichment analyses showed that the“COPI-mediated anterograde transport” gene-set was associated with MIC-1/GDF15 blood concentration with marginal significance after FDR correction (p = 0.067). In conclusion, a locus on chromosome 19 was associated with MIC-1/GDF-15 blood concentration with genome-wide significance, with evidence for a new locus (chromosome 1). Future studies using independent cohorts are needed to confirm the observed associations especially for the chromosomes 1 locus, and to further investigate and identify the causal SNPs that contribute to MIC-1/GDF-15 levels

Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study

Background: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. Methods and findings: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54–105 (mean = 72.7) years and without dementia at baseline. Studies had 2–15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = −0.1, SE = 0.01), APOE*4 carriage (B = −0.31, SE = 0.11), depression (B = −0.11, SE = 0.06), diabetes (B = −0.23, SE = 0.10), current smoking (B = −0.20, SE = 0.08), and history of stroke (B = −0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = −0.07, SE = 0.01), APOE*4 carriage (B = −0.41, SE = 0.18), and diabetes (B = −0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = −0.24, SE = 0.12), and between diabetes and cognitive decline (B = −0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. Conclusions: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

Investigating the influence of KIBRA and CLSTN2 genetic polymorphisms on cross-sectional and longitudinal measures of memory performance and hippocampal volume in older individuals

The variability of episodic memory decline and hippocampal atrophy observed with increasing age may partly be explained by genetic factors. KIBRA (kidney and brain expressed protein) and CLSTN2 (calsyntenin 2) are two candidate genes previously linked to episodic memory performance and volume of the hippocampus, a key memory structure. However, whether polymorphisms in these two genes also influence age-related longitudinal memory decline and hippocampal atrophy is still unknown. Using data from two independent cohorts, the Sydney Memory and Ageing Study and the Older Australian Twins Study, we investigated whether the KIBRA and CLSTN2 genetic polymorphisms (rs17070145 and rs6439886) are associated with episodic memory performance and hippocampal volume in older adults (65-90 years at baseline). We were able to examine these polymorphisms in relation to memory and hippocampal volume using cross-sectional data and, more importantly, also using longitudinal data (2 years between testing occasions). Overall we did not find support for an association of KIBRA either alone or in combination with CLSTN2 with memory performance or hippocampal volume, nor did variation in these genes influence longitudinal memory decline or hippocampal atrophy in two cohorts of older adults

Aging, exceptional longevity and comparisons of the Hannum and Horvath epigenetic clocks

Aim: To examine the relationships between two epigenetic clocks, aging and exceptional longevity. Materials & methods: Participants were from three adult cohorts with blood DNA methylation data (Illumina 450 K, n = 275, 34-103 years). Epigenetic age (DNAmage) and age acceleration measures were calculated using the Hannum and Horvath epigenetic clocks. Results: Across all cohorts, DNAmage was correlated with chronological age. In the long-lived cohort (Sydney Centenarian Study; 95+, n = 23), DNAmage was lower than chronological age for both clocks. Mean Sydney Centenarian Study Hannum age acceleration was negative, while the converse was observed for the Horvath model. Conclusion: Long-lived individuals have a young epigenetic age compared with their chronological age

Downregulated transferrin receptor in the blood predicts recurrent MDD in the elderly cohort: a fuzzy forests approach

Background: At present, no predictive markers for Major Depressive Disorder (MDD) exist. The search for such markers has been challenging due to clinical and molecular heterogeneity of MDD, the lack of statistical power in studies and suboptimal statistical tools applied to multidimensional data. Machine learning is a powerful approach to mitigate some of these limitations. Methods: We aimed to identify the predictive markers of recurrent MDD in the elderly using peripheral whole blood from the Sydney Memory and Aging Study (SMAS) (N = 521, aged over 65) and adopting machine learning methodology on transcriptome data. Fuzzy Forests is a Random Forests-based classification algorithm that takes advantage of the co-expression network structure between genes; it allows to alleviate the problem of p >> n via reducing the dimensionality of transcriptomic feature space. Results: By adopting Fuzzy Forests on transcriptome data, we found that the downregulated TFRC (transferrin receptor) can predict recurrent MDD with an accuracy of 63%. Limitations: Although we corrected our data for several important confounders, we were not able to account for the comorbidities and medication taken, which may be numerous in the elderly and might have affected the levels of gene transcription. Conclusions: We found that downregulated TFRC is predictive of recurrent MDD, which is consistent with the previous literature, indicating the role of the innate immune system in depression. This study is the first to successfully apply Fuzzy Forests methodology on psychiatric condition, opening, therefore, a methodological avenue that can lead to clinically useful predictive markers of complex traits.Liliana G.Ciobanu, Perminder S.Sachdev ... Bernhard Baune ... Sarah Cohen-Woods ... Klaus Schubert .... Catherine Toben ... et al

Un modello retorico di memoria storica in Velleio Patercolo: L. Munazio Planco e C. Asinio Pollione

The historiographical memories of Lucius Munatius Plancus and Gaius Asinius Pollio according to Velleius Paterculus is taken into account, with special attention to their rhetorical (especially epideictic) and political background