Stephen V. Faraone

Bio: Stephen V. Faraone is an academic researcher from State University of New York Upstate Medical University. The author has contributed to research in topics: Attention deficit hyperactivity disorder & Bipolar disorder. The author has an hindex of 188, co-authored 1427 publications receiving 140298 citations. Previous affiliations of Stephen V. Faraone include University of Bergen & National Institute for Health Research.

Exploring DRD4 and Its Interaction With SLC6A3 as Possible Risk Factors for Adult ADHD: A Meta-Analysis in Four European Populations

Abstract: Attention-deficit hyperactivity disorder (ADHD) is a common behavioral disorder affecting about 4-8% of children. ADHD persists into adulthood in around 65% of cases, either as the full condition or in partial remission with persistence of symptoms. Pharmacological, animal and molecular genetic studies support a role for genes of the dopaminergic system in ADHD due to its essential role in motor control, cognition, emotion, and reward. Based on these data, we analyzed two functional polymorphisms within the DRD4 gene (120 bp duplication in the promoter and 48 bp VNTR in exon 3) in a clinical sample of 1,608 adult ADHD patients and 2,352 controls of Caucasian origin from four European countries that had been recruited in the context of the International Multicentre persistent ADHD CollaboraTion (IMpACT). Single-marker analysis of the two polymorphisms did not reveal association with ADHD. In contrast, multiple-marker meta-analysis showed a nominal association (P = 0.02) of the L-4R haplotype (dup120bp-48bpVNTR) with adulthood ADHD, especially with the combined clinical subtype. Since we previously described association between adulthood ADHD and the dopamine transporter SLC6A3 9R-6R haplotype (3'UTR VNTR-intron 8 VNTR) in the same dataset, we further tested for gene x gene interaction between DRD4 and SLC6A3. However, we detected no epistatic effects but our results rather suggest additive effects of the DRD4 risk haplotype and the SLC6A3 gene.

Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits

Abstract: Background The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. Methods Using genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rg Results With current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). Conclusions Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.

Lisdexamfetamine dimesylate: the first long-acting prodrug stimulant treatment for attention deficit/hyperactivity disorder

Abstract: Background: Lisdexamfetamine dimesylate is the first long-acting prodrug stimulant and is indicated for the treatment of attention deficit/hyperactivity disorder. Lisdexamfetamine dimesylate is a therapeutically inactive molecule. Methods: Following oral ingestion, it is converted to L-lysine and active d-amphetamine, which is responsible for the therapeutic effect. Lisdexamfetamine dimesylate was developed with the goal of providing a long duration of effect with the potential for less abuse-related liking. Results: In controlled clinical trials lisdexamfetamine dimesylate demonstrated a significant efficacy and extended duration of action as well as a safety profile consistent with other once-daily stimulants (mixed amphetamine salts extended release). In addition, abuse liability studies have shown that lisdexamfetamine dimesylate has lower abuse-related liking scores compared with equipotent doses of immediate-release d-amphetamine.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Using Multivariate Statistics

Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.