Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders, bioRxiv, 2019-01-27

SummaryGenetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficithyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

biorxiv genomics 100-200-users 2019

Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Supplemental Tables 1 - 18, bioRxiv, 2019-01-27

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficithyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

biorxiv genomics 100-200-users 2019

High-pass filtering artifacts in multivariate classification of neural time series data, bioRxiv, 2019-01-27

The application of time-resolved multivariate pattern classification analyses (MVPA) to EEG and MEG data has become increasingly popular. Traditionally, such time series data are high-pass filtered before analyses, in order to remove slow drifts. Here we show that high-pass filtering should be applied with extreme caution in MVPA, as it may easily create artifacts that result in displacement of decoding accuracy, leading to statistically significant above-chance classification during time periods in which the source is clearly not in brain activity. In both real and simulated EEG data, we show that spurious decoding may emerge with filter cut-off settings from as modest as 0.1 Hz. We provide an alternative method of removing slow drift noise, referred to as robust detrending (de Cheveigne & Arzounian, 2018), which, when applied in concert with masking of cortical events does not result in the temporal displacement of information. We show that temporal generalization may benefit from robust detrending, without any of the unwanted side effects introduced by filtering. However, we conclude that for sufficiently clean data sets, no filtering or detrending at all may work sufficiently well. Implications for other types of data are discussed, followed by a number of recommendations.

biorxiv neuroscience 100-200-users 2019

Short-range interactions govern cellular dynamics in microbial multi-genotype systems, bioRxiv, 2019-01-27

Ecosystem processes result from interaction between organisms. When interactions are local, the spatial organization of organisms defines their network of interactions, and thus influences the system's functioning. This can be especially relevant for microbial systems, which often consist of spatially structured communities of cells connected by a dense interaction network. Here we measured the spatial interaction network between cells in microbial systems and identify the factors that determine it. Combining quantitative single-cell analysis of synthetic bacterial communities with mathematical modeling, we find that cells only interact with other cells in their immediate neighbourhood. This short interaction range impacts the functioning of the whole system by reducing its ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of cell-to-cell interaction plays a fundamental role in understanding and controlling natural communities, and in engineering microbial systems for specific purposes.

biorxiv systems-biology 100-200-users 2019

Conduit integrity is compromised during acute lymph node expansion, bioRxiv, 2019-01-24

Lymph nodes (LNs) work as filtering organs, constantly sampling peripheral cues. This is facilitated by the conduit network, a parenchymal tubular-like structure formed of bundles of aligned extracellular matrix (ECM) fibrils ensheathed by fibroblastic reticular cells (FRCs). LNs undergo 5-fold expansion with every adaptive immune response and yet these ECM-rich structures are not permanently damaged. Whether conduit integrity and filtering functions are affected during cycles of LN expansion and resolution is not known. Here we show that the conduit structure is disrupted during acute LN expansion but FRC-FRC contacts remain intact. In homeostasis, polarised FRCs adhere to the underlying substrate to deposit ECM ba-solaterally. ECM production by FRCs is regulated by the C-type lectin CLEC-2, expressed by dendritic cells (DCs), at transcriptional and secretory levels. Inflamed LNs maintain conduit size-exclusion, but flow becomes leaky, which allows soluble antigens to reach more antigen-presenting cells. We show how dynamic communication between peripheral tissues and LNs changes during immune responses, and describe a mechanism that enables LNs to prevent inflammation-induced fibrosis.Highlights<jatslist list-type=bullet><jatslist-item>FRCs use polarized microtubule networks to guide matrix deposition<jatslist-item><jatslist-item>CLEC-2PDPN controls matrix production at transcriptional and post-transcriptional levels<jatslist-item><jatslist-item>FRCs halt matrix production and decouple from conduits during acute LN expansion<jatslist-item><jatslist-item>Conduits leak soluble antigen during acute LN expansion<jatslist-item>

biorxiv immunology 100-200-users 2019

Genetic Identification of Cell Types Underlying Brain Complex Traits Yields Novel Insights Into the Etiology of Parkinson’s Disease, bioRxiv, 2019-01-24

AbstractGenome-wide association studies (GWAS) have discovered hundreds of loci associated with complex brain disorders, and provide the best current insights into the etiology of these idiopathic traits. However, it remains unclear in which cell types these variants are active, which is essential for understanding etiology and subsequent experimental modeling. Here we integrate GWAS results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying psychiatric disorders, neurological diseases, and brain complex traits. We show that psychiatric disorders are predominantly associated with cortical and hippocampal excitatory neurons, and medium spiny neurons from the striatum. Cognitive traits were generally associated with similar cell types but their associations were driven by different genes. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, we found that Parkinson’s disease is not only genetically associated with dopaminergic neurons but also with serotonergic neurons and cells of the oligodendrocyte lineage. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson’s disease.

biorxiv genomics 100-200-users 2019