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The genetic component of Alzheimer’s disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals —16,036 AD cases and 16,522 controls— in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, Aβ-aggregation, lipid metabolism and microglial function in AD.

Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method—Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)—that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer's Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (< 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF.

The harms of youth homelessness are well described in the academic literature, but less is known about transitions into homelessness among at risk youth. Given the importance of preventing youth homelessness, and in particular, the first incidence of homelessness, quantitative and qualitative data from street involved youth in Vancouver were analyzed in order to determine significant factors associated with this transition and generate policy options for addressing this issue. Ultimately, this study recommends placing youth workers in secondary schools to support the academic and social development of at risk youth, as well as provide connections to appropriate community supports such as housing. This is the first known study to directly ask youth for their thoughts on how to prevent the first incidence of homelessness, and the results from this Capstone provides policy makers with opportunities for targeted interventions to address youth homelessness in Vancouver.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10^−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Children and youth exposed to the child welfare system represent one of society’s most vulnerable populations. Compared to their peer group, too many youth exposed to the child welfare system in British Columbia experience elevated rates of homelessness, substance use, incarceration, unplanned pregnancies, poverty and underemployment, and both mental and physical health issues in early adulthood. Given these disparities, child welfare policy reform is needed to better assist youth in care, rectify lagging outcomes and facilitate successful transitions to independence throughout the province. This study employed a mixed methodology using quantitative data from a prospective cohort of illicit substance-using street youth, semi-structured qualitative interviews and a literature review. Findings from the quantitative analysis found that youth with a history of being in care were more likely to: be of Aboriginal ancestry; have been physically abused; have a parent that drank heavily or used illicit substances; not have completed high school; and have initiated hard drug-use at an earlier age. A range of policy options were developed and informed by various stakeholder groups and evaluated against a set of criteria. The outcome of these evaluations indicate that a portfolio of policies, including the provision of greater resources to kinship caregivers and extending foster care to 21 years old will have the greatest impact on improving outcomes for former government care youth. Moving towards expanding and extending independent living programs was also identified as a promising policy approach to improve outcomes for youth transitioning out of care.

Design Systematic Review. Objective To determine which intervention approaches to manage depression in the workplace have been successful and yielded value for employers in developed economies. Data Sources We searched MEDLINE, EMBASE, CINAHL, Central, PsycINFO, and Business Source Premier up to June 2010 using search terms in four broad areas: work setting, depression, intervention, and work outcomes. Study Selection Two independent reviewers selected potential articles that met the following criteria: working age individuals with mild or moderate depression; interventions or programs that were workplace-based or could be implemented and/or facilitated by the employer; inclusion of a comparator group in the analysis; outcomes of prevention, management, and recurrences of work disability or sickness absence, and work functioning. Methods Two reviewers independently reviewed each article for quality and extracted data using standardised forms. Following guidelines from the GRADE Working Group, the quality of evidence addressing each outcome was graded as high, moderate, low, or very low on the basis of six criteria: study design, risk of bias, consistency, generalisability, data precision, and economic benefit. Using this information and following Cochrane Collaboration guidelines, the findings for each intervention were summarised and key messages were developed. Results We identified ten randomised trials and two non-randomised studies from various countries and jurisdictions that evaluated a wide range of intervention practices. The evidence was graded as "very low" for all outcomes identified. Therefore, no intervention could be recommended. Conclusions To date, there is insufficient quality of evidence to determine which interventions are effective and yield value to manage depression in the workplace.