Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease

Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. 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

S-COL: A Copernican turn for the development of flexibly reusable collaboration scripts

Collaboration scripts are usually implemented as parts of a particular collaborative-learning platform. Therefore, scripts of demonstrated effectiveness are hardly used with learning platforms at other sites, and replication studies are rare. The approach of a platform-independent description language for scripts that allows for easy implementation of the same script on different platforms has not succeeded yet in making the transfer of scripts feasible. We present an alternative solution that treats the problem as a special case of providing support on top of diverse Web pages: In this case, the challenge is to trigger support based on the recognition of a Web page as belonging to a specific type of functionally equivalent pages such as the search query form or the results page of a search engine. The solution suggested has been implemented by means of a tool called S-COL (Scripting for Collaborative Online Learning) and allows for the sustainable development of scripts and scaffolds that can be used with a broad variety of content and platforms. The tool’s functions are described. In order to demonstrate the feasibility and ease of script reuse with S-COL, we describe the flexible re-implementation of a collaboration script for argumentation in S-COL and its adaptation to different learning platforms. To demonstrate that a collaboration script implemented in S-COL can actually foster learning, an empirical study about the effects of a specific script for collaborative online search on learning activities is presented. The further potentials and the limitations of the S-COL approach are discussed

Sex Differences in Sum Scores May Be Hard to Interpret: The Importance of Measurement Invariance

In most assessment instruments, distinct items are designed to measure a trait, and the sum score of these items serves as an approximation of an individual’s trait score. In interpreting group differences with respect to sum scores, the instrument should measure the same underlying trait across groups (e.g., male/female, young/old). Differences with respect to the sum score should accurately reflect differences in the latent trait of interest. A necessary condition for this is that the instrument is measurement invariant. In the current study, the authors illustrate a stepwise approach for testing measurement invariance with respect to sex in a four-item instrument designed to assess disordered eating behavior in a large epidemiological sample (1,195 men and 1,507 women). This approach can be applied to other phenotypes for which group differences are expected. Any analysis of such variables may be subject to measurement bias if a lack of measurement invariance between grouping variables goes undetected

Eating disorders: from twin studies to candidate genes and beyond

Substantial effort has been put into the exploration of the biological background of eating disorders, through family, twin and molecular genetic studies. Family studies have shown that anorexia (AN) and bulimia nervosa (BN) are strongly familial, and that familial etiologic factors appear to be shared by both disorders. Twin studies often focus on broader phenotypes or subthreshold eating disorders. These studies consistently yielded moderate to substantial heritabilities. In addition, there has been a proliferation of molecular genetic studies that focused on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) AN and BN. Seven linkage regions have been identified in genome-wide screens. Many genetic association studies have been performed, but no consistent association between a candidate gene and AN or BN has been reported. Larger genetic association studies and collaborations are needed to examine the involvement of several candidate genes and biological pathways in eating disorders. In addition, twin studies should be designed to assist the molecular work by further exploring genetic determinants of endophenotypes, evaluating the magnitude of contribution to liability of measured genotypes as well as environmental risk factors related to eating disorders. In this manner twin and molecular studies can move the field forward in a mutually informative way

Stable Genetic Effects on Symptoms of Alcohol Abuse and Dependence from Adolescence into Early Adulthood

Relatively little is known about how genetic influences on alcohol abuse and dependence (AAD) change with age. We examined the change in influence of genetic and environmental factors which explain symptoms of AAD from adolescence into early adulthood. Symptoms of AAD were assessed using the four AAD screening questions of the CAGE inventory. Data were obtained up to six times by self-report questionnaires for 8,398 twins from the Netherlands Twin Register aged between 15 and 32 years. Longitudinal genetic simplex modeling was performed with Mx. Results showed that shared environmental influences were present for age 15–17 (57%) and age 18–20 (18%). Unique environmental influences gained importance over time, contributing 15% of the variance at age 15–17 and 48% at age 30–32. At younger ages, unique environmental influences were largely age-specific, while at later ages, age-specific influences became less important. Genetic influences on AAD symptoms over age could be accounted for by one factor, with the relative influence of this factor differing across ages. Genetic influences increased from 28% at age 15–17 to 58% at age 21–23 and remained high in magnitude thereafter. These results are in line with a developmentally stable hypothesis that predicts that a single set of genetic risk factors acts on symptoms of AAD from adolescence into young adulthood