HENA, heterogeneous network-based data set for Alzheimer's disease.

Alzheimer's disease and other types of dementia are the top cause for disabilities in later life and various types of experiments have been performed to understand the underlying mechanisms of the disease with the aim of coming up with potential drug targets. These experiments have been carried out by scientists working in different domains such as proteomics, molecular biology, clinical diagnostics and genomics. The results of such experiments are stored in the databases designed for collecting data of similar types. However, in order to get a systematic view of the disease from these independent but complementary data sets, it is necessary to combine them. In this study we describe a heterogeneous network-based data set for Alzheimer's disease (HENA). Additionally, we demonstrate the application of state-of-the-art graph convolutional networks, i.e. deep learning methods for the analysis of such large heterogeneous biological data sets. We expect HENA to allow scientists to explore and analyze their own results in the broader context of Alzheimer's disease research

Primate-Accelerated Evolutionary Genes: Novel Routes to Drug Discovery in Psychiatric Disorders

International audienceNovel molecular genetic approaches, at genome-scale in different species allowed characterizing genes that have undergone recent selection. The interest in this research field is not limited to the natural curiosity about our evolutionary past, but it is also to identify novel susceptibility genes for neuropsychiatic disorders by pointing specific human traits, such as behavioral and cognitive abilities. Hypotheses have been proposed to relate specific psychiatric disorders to the origin of modern humans, as evidenced by the theory of Crow about schizophrenia. In the present review, we will focus on genes that underwent positive selection in humans or displayed a human specific evolutionary pattern and which were reported as associated with psychiatric disorders. This will include the (1) DRD4 gene associated with attentiondeficit/ hyperactivity disorder, located in a locus that underwent a positive selection; the (2) GABRB2 gene, a gene associated with schizophrenia and recently reported as the target of a positive selection; (3) MARK1, a candidate gene for autism that was reported as displaying a signature of adaptative evolution in the human lineage, and (4) the ADH and ALDH2 genes which are associated with alcoholism, and for which evidence of positive selection was identified in the human lineage since the divergence between humans and chimpanzees. Identification of novel candidate genes based on recent evolution selection, coupled to genome-wide strategies designed to detect rare structural variants, could lead to a better knowledge of the molecular mechanisms of neurodevelopmental disorders and might therefore help to develop new medical chemistry

Fluorescent nanodiamond tracking reveals intraneuronal transport abnormalities induced by brain-disease-related genetic risk factors

Brain diseases such as autism and Alzheimer's disease (each inflicting >1% of the world population) involve a large network of genes displaying subtle changes in their expression. Abnormalities in intraneuronal transport have been linked to genetic risk factors found in patients, suggesting the relevance of measuring this key biological process. However, current techniques are not sensitive enough to detect minor abnormalities. Here we report a sensitive method to measure the changes in intraneuronal transport induced by brain-disease-related genetic risk factors using fluorescent nanodiamonds (FNDs). We show that the high brightness, photostability and absence of cytotoxicity allow FNDs to be tracked inside the branches of dissociated neurons with a spatial resolution of 12 nm and a temporal resolution of 50 ms. As proof of principle, we applied the FND tracking assay on two transgenic mouse lines that mimic the slight changes in protein concentration ( approximately 30%) found in the brains of patients. In both cases, we show that the FND assay is sufficiently sensitive to detect these changes

Fluorescent nanodiamond tracking reveals intraneuronal transport abnormalities induced by brain-disease-related genetic risk factors

International audienceBrain diseases such as autism and Alzheimer's disease (each inflicting >1% of the world population) involve a large network of genes displaying subtle changes in their expression. Abnormalities in intraneuronal transport have been linked to genetic risk factors found in patients, suggesting the relevance of measuring this key biological process. However, current techniques are not sensitive enough to detect minor abnormalities. Here we report a sensitive method to measure the changes in intraneuronal transport induced by brain-disease-related genetic risk factors using fluorescent nanodiamonds (FNDs). We show that the high brightness, photostability and absence of cytotoxicity allow FNDs to be tracked inside the branches of dissociated neurons with a spatial resolution of 12 nm and a temporal resolution of 50 ms. As proof of principle, we applied the FND tracking assay on two transgenic mouse lines that mimic the slight changes in protein concentration (∼30%) found in the brains of patients. In both cases, we show that the FND assay is sufficiently sensitive to detect these changes