Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genomewide association studies (GWAS) were predominantly conducted in individuals of European descent, the limited transferability of PRS reduces its clinical value in non-European populations and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although they remain under-powered. Here we present a novel PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium (LD) diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures and cross-population genetic correlations in simulations, and substantially improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

No abstract

Recently, deep-learning-based approaches have been proposed for the classification of neuroimaging data related to Alzheimer’s disease (AD), and significant progress has been made. However, end-to-end learning that is capable of maximizing the impact of deep learning has yet to receive much attention due to the endemic challenge of neuroimaging caused by the scarcity of data. Thus, this study presents an approach meant to encourage the end-to-end learning of a volumetric convolutional neural network (CNN) model for four binary classification tasks (AD vs. normal control (NC), progressive mild cognitive impairment (pMCI) vs. NC, stable mild cognitive impairment (sMCI) vs. NC and pMCI vs. sMCI) based on magnetic resonance imaging (MRI) and visualizes its outcomes in terms of the decision of the CNNs without any human intervention. In the proposed approach, we use convolutional autoencoder (CAE)-based unsupervised learning for the AD vs. NC classification task, and supervised transfer learning is applied to solve the pMCI vs. sMCI classification task. To detect the most important biomarkers related to AD and pMCI, a gradient-based visualization method that approximates the spatial influence of the CNN model’s decision was applied. To validate the contributions of this study, we conducted experiments on the ADNI database, and the results demonstrated that the proposed approach achieved the accuracies of 86.60% and 73.95% for the AD and pMCI classification tasks respectively, outperforming other network models. In the visualization results, the temporal and parietal lobes were identified as key regions for classification.

No abstract

No abstract

Patients not even minimally improved by week 2 of antipsychotic treatment are unlikely to respond later and may benefit from a treatment change.

The present study investigated the effects of social defeat stress on the behaviours and expressions of 78-kDa glucose-regulated protein (Grp78), CCAAT/enhancer-binding protein (C/EBP) homologous protein (CHOP) and choline acetyltransferase (Chat) in the brains of adolescent mice. Adolescent male C57BL/6J mice were divided into two groups (susceptible and unsusceptible) after 10 d social defeat stress. In expt 1, behavioural tests were conducted and brains were processed for Western blotting on day 21 after stress. In expt 2, social avoidance tests were conducted and brains were subsequently processed for Western blotting on day 12 after stress. Chronic social defeat stress produced more pronounced depression-like behaviours such as decreased locomotion and social interaction, increased anxiety-like behaviours and immobility, and impaired memory performance in susceptible mice. Moreover, susceptible mice showed greater expression of Grp78 and CHOP in the amygdala (Amyg) on days 12 and 21 compared with the other groups. Susceptible and unsusceptible groups showed significant increases in Grp78 and CHOP expression in the prefrontal cortex (PFC) and hippocampus (Hipp) on day 12 compared with the control group; this persisted until day 21. The levels of Chat measured on days 12 and 21 were significantly lower in the PFC, Amyg and Hipp of all defeated mice compared with controls. The findings of the behavioural tests indicate that chronic social defeat in adolescents produces anxiety-like behaviours, social withdrawal, despair-like behaviours and cognitive impairment. The Grp78, CHOP and Chat results suggest that the selective response of endoplasmic reticulum stress proteins in the Amyg plays an important role in the vulnerability-stress model of depression.

No abstract