Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model

Large-scale collaborative analysis of brain imaging data, in psychiatry and neurology, offers a new source of statistical power to discover features that boost accuracy in disease classification, differential diagnosis, and outcome prediction. However, due to data privacy regulations or limited accessibility to large datasets across the world, it is challenging to efficiently integrate distributed information. Here we propose a novel classification framework through multi-site weighted LASSO: each site performs an iterative weighted LASSO for feature selection separately. Within each iteration, the classification result and the selected features are collected to update the weighting parameters for each feature. This new weight is used to guide the LASSO process at the next iteration. Only the features that help to improve the classification accuracy are preserved. In tests on data from five sites (299 patients with major depressive disorder (MDD) and 258 normal controls), our method boosted classification accuracy for MDD by 4.9% on average. This result shows the potential of the proposed new strategy as an effective and practical collaborative platform for machine learning on large scale distributed imaging and biobank data

Human Immunodeficiency Virus-1 Latency Reversal via the Induction of Early Growth Response Protein 1 to Bypass Protein Kinase C Agonist-Associated Immune Activation

Human Immunodeficiency Virus-1 (HIV) remains a global health challenge due to the latent HIV reservoirs in people living with HIV (PLWH). Dormant yet replication competent HIV harbored in the resting CD4+ T cells cannot be purged by antiretroviral therapy (ART) alone. One approach of HIV cure is the “Kick and Kill” strategy where latency reversal agents (LRAs) have been implemented to disrupt latent HIV, expecting to eradicate HIV reservoirs by viral cytopathic effect or immune-mediated clearance. Protein Kinase C agonists (PKCa), a family of LRAs, have demonstrated the ability to disrupt latent HIV to an extent. However, the toxicity of PKCa remains a concern in vivo. Early growth response protein 1 (EGR1) is a downstream target of PKCa during latency reversal. Here, we show that PKCa induces EGR1 which directly drives Tat-dependent HIV transcription. Resveratrol, a natural phytoalexin found in grapes and various plants, induces Egr1 expression and disrupts latent HIV in several HIV latency models in vitro and in CD4+ T cells isolated from ART-suppressed PLWH ex vivo. In the primary CD4+ T cells, resveratrol does not induce immune activation at the dosage that it reverses latency, indicating that targeting EGR1 may be able to reverse latency and bypass PKCa-induced immune activation

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Are sex differences in human brain structure associated with sex differences in behavior?

On average, men and women differ in brain structure and behaviour, raising the possibility of a link between sex differences in brain and behaviour. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (N=1,040) and Human Connectome Project (N=1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behaviour based on average sex differences in brain structure and behaviour, respectively. We found a weak association between these brain and behavioural differences, driven by brain size. These brain and behavioural differences were moderately heritable. Our findings suggest that behavioural sex differences are to some extent related to sex differences in brain structure, but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously

Generation of integration-free neural progenitor cells from cells in human urine

Human neural stem cells hold great promise for research and therapy in neural disease. We describe the generation of integration-free and expandable human neural progenitor cells (NPCs). We combined an episomal system to deliver reprogramming factors with a chemically defined culture medium to reprogram epithelial-like cells from human urine into NPCs (hUiNPCs). These transgene-free hUiNPCs can self-renew and can differentiate into multiple functional neuronal subtypes and glial cells in vitro. Although functional in vivo analysis is still needed, we report that the cells survive and differentiate upon transplant into newborn rat brain.postprin

Meta-Analysis of Gene Level Tests for Rare Variant Association

The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large sample sizes while protecting against common artifacts due to population structure, repeated small sample analyses, and/or limitations with sharing individual level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the unit of analysis. Here, we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features of single variant meta-analytic approaches and demonstrate its utility in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays

Genetic Variants in CETP Increase Risk of Intracerebral Hemorrhage

OBJECTIVE: In observational epidemiologic studies, higher plasma high-density lipoprotein cholesterol (HDL-C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL-C; as such, medicines that inhibit CETP and raise HDL-C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL-C also increase risk for ICH.METHODS: We performed 2 candidate-gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL-C as well as ICH risk.RESULTS: Twelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10(-4) ) with no heterogeneity across studies (I(2) = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL-C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10(-6) ).INTERPRETATION: Genetic variants in CETP associated with increased HDL-C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL-raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730-740

Are sex differences in human brain structure associated with sex differences in behaviour?

On average, men and women differ in brain structure and behaviour, raising the possibility of a link between sex differences in brain and behaviour. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (N=1,040) and Human Connectome Project (N=1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behaviour based on average sex differences in brain structure and behaviour, respectively. We found a weak association between these brain and behavioural differences, driven by brain size. These brain and behavioural differences were moderately heritable. Our findings suggest that behavioural sex differences are to some extent related to sex differences in brain structure, but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously

Identification of a Rare Coding Variant in Complement 3 Associated with Age-related Macular Degeneration

Macular degeneration is a common cause of blindness in the elderly. To identify rare coding variants associated with a large increase in risk of age-related macular degeneration (AMD), we sequenced 2,335 cases and 789 controls in 10 candidate loci (57 genes). To increase power, we augmented our control set with ancestry-matched exome sequenced controls. An analysis of coding variation in 2,268 AMD cases and 2,268 ancestry matched controls revealed two large-effect rare variants; previously described R1210C in the CFH gene (fcase = 0.51%, fcontrol = 0.02%, OR = 23.11), and newly identified K155Q in the C3 gene (fcase = 1.06%, fcontrol = 0.39%, OR = 2.68). The variants suggest decreased inhibition of C3 by Factor H, resulting in increased activation of the alternative complement pathway, as a key component of disease biology