The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Unbundling Freedom in the Sharing Economy

Courts and scholars point to the sharing economy as the most recent proof that our labor amp employment infrastructure is obsolete because it rests on a narrow and outmoded idea ”namely that only workers subjected to direct personalized control by their employers need workrelated protections and benefits Since they diagnose the problem as being our system\u27s emphasis on control these critics have long called for reducing or eliminating the primacy of the control test in classifying workers as either protected employees or unprotected independent contractors Despite these persistent criticisms however the concept of control has been remarkably sticky in scholarly and judicial circlesbrbrThis Article argues that critics have misdiagnosed the reason why the control test is an unsatisfying method of classifying workers and dispensing workrelated safeguards Controlbased analysis is faulty because it only captures one of the two conflicting ways in which workers scholars and decisionmakers think about freedom at work One of these ways freedom as noninterference is adequately captured by the control test The other freedom as nondomination is not The tension between these two conceptions of freedom both deeply entrenched in American culture explains why the concept of control has been both faulty and sticky when it comes to worker classification brbrDrawing on a firstofitskind body of ethnographic fieldwork among workers and policymakers across several sharing economy industries this Article begins by showing how workers themselves conceptualize freedom as both noninterference and nondomination It then goes on to show that both these conceptualizations of freedom also exist in case law and statutory law pertaining to work In doing so the Article demonstrates that there is no great divide between work law and work practices and that if anything the problem is that classification doctrine reflects and reinforces an irresolvable tension in the way lay and legal actors think about freedom at wor

Measurement of baryon acoustic oscillations in the Lyman-α forest fluctuations in BOSS data release 9

We use the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 9 (DR9) to detect and measure the position of the Baryonic Acoustic Oscillation (BAO) feature in the three-dimensional correlation function in the Lyman-α flux fluctuations at a redshift zeff = 2.4. The feature is clearly detected at significance between 3 and 5 sigma (depending on the broadband model and method of error covariance matrix estimation) and is consistent with predictions of the standard ΛCDM model. We assess the biases in our method, stability of the error covariance matrix and possible systematic effects. We fit the resulting correlation function with several models that decouple the broadband and acoustic scale information. For an isotropic dilation factor, we measure 100 × (αiso - 1) = -1.6+2.0 +4.3 +7.4-2.0 -4.1 -6.8 (stat.) ±1.0 (syst.) (multiple statistical errors denote 1,2 and 3 sigma confidence limits) with respect to the acoustic scale in the fiducial cosmological model (flat ΛCDM with Ωm = 0.27, h = 0.7). When fitting separately for the radial and transversal dilation factors we find marginalised constraints 100 × (α|| - 1) = -1.3+3.5 +7.6 +12.3-3.3 -6.7 -10.2 (stat.) ±2.0 (syst.) and 100 × (α⊥ - 1) = -2.2+7.4 +17-7.1 -15 (stat.) ±3.0 (syst.). The dilation factor measurements are significantly correlated with cross-correlation coefficient of ~ -0.55. Errors become significantly non-Gaussian for deviations over 3 standard deviations from best fit value. Because of the data cuts and analysis method, these measurements give tighter constraints than a previous BAO analysis of the BOSS DR9 Lyman-α sample, providing an important consistency test of the standard cosmological model in a new redshift regime

Lessons learned from the eMERGE Network: balancing genomics in discovery and practice

The Electronic Medical Records and Genomics (eMERGE) Network, established in 2007, is a consortium of academic and integrated health systems conducting discovery and implementation research in translational genomics. Here, we outline the history of the network, highlight major impacts and lessons learned, and present the tools and resources developed for large-scale genomic analyses and translation into a clinical setting. The network developed methods to extract phenotypes from the electronic medical record to perform genome-wide and phenome-wide association studies. Recruited cohorts were clinically sequenced off a custom panel for targeted sequencing of variants and monogenic disease risks and returned to participants to investigate the impact of return of genomic results. After generating a 105,000 participant-imputed genome-wide association study (GWAS) dataset for discovery, the network enrolled and sequenced 24,998 participants. Integration of these results into the medical record and the effects of results on participants provided key lessons to the field. These learned lessons inform genetic research in diverse populations and provide insights into the clinical impact of return and implementation of genomic medicine using the electronic medical record. The lessons produced by the eMERGE Network can be utilized by other consortia as translational genomic medicine research evolves