Simulated Milky Way analogues: implications for dark matter direct searches

We study the implications of galaxy formation on dark matter direct detection using high resolution hydrodynamic simulations of Milky Way-like galaxies simulated within the eagle and apostle projects. We identify MilkyWay analogues that satisfy observational constraints on the Milky Way rotation curve and total stellar mass. We then extract the dark matter density and velocity distribution in the Solar neighbourhood for this set of Milky Way analogues, and use them to analyse the results of current direct detection experiments. For most Milky Way analogues, the event rates in direct detection experiments obtained from the best _t Maxwellian distribution (with peak speed of 223 { 289 km=s) are similar to those obtained directly from the simulations. As a consequence, the allowed regions and exclusion limits set by direct detection experiments in the dark matter mass and spin-independent cross section plane shift by a few GeV compared to the Standard Halo Model, at low dark matter masses. For each dark matter mass, the halo-to-halo variation of the local dark matter density results in an overall shift of the allowed regions and exclusion limits for the cross section. However, the compatibility of the possible hints for a dark matter signal from DAMA and CDMS-Si and null results from LUX and SuperCDMS is not improved

Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Analysis of the theoretical bias in dark matter direct detection

Fitting the model \A" to dark matter direct detection data, when the model that underlies the data is \B", introduces a theoretical bias in the t. We perform a quantitative study of the theoretical bias in dark matter direct detection, with a focus on assumptions regarding the dark matter interactions, and velocity distribution. We address this problem within the e ective theory of isoscalar dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle. We analyze 24 benchmark points in the parameter space of the theory, using frequentist and Bayesian statistical methods. First, we simulate the data of future direct detection experiments assuming a momentum/velocity dependent dark matternucleon interaction, and an anisotropic dark matter velocity distribution. Then, we t a constant scattering cross section, and an isotropic Maxwell-Boltzmann velocity distribution to the simulated data, thereby introducing a bias in the analysis. The best t values of the dark matter particle mass di er from their benchmark values up to 2 standard deviations. The best t values of the dark matter-nucleon coupling constant di er from their benchmark values up to several standard deviations. We conclude that common assumptions in dark matter direct detection are a source of potentially signi cant bias.peerReviewe