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.

Further evidence for robust familiality of pediatric bipolar I disorder: results from a very large controlled family study of pediatric bipolar I disorder and a meta-analysis.

Abstract: Objective To determine the risk for BP-I disorder in first-degree relatives of children with DSM-IV bipolar-I disorder (BP-I) via meta-analysis and expanded controlled study.

Evaluation of potential gene-gene interactions for attention deficit hyperactivity disorder in the Han Chinese population.

Abstract: Several lines of evidence suggest that attention-deficit/hyperactivity disorder (ADHD) is a polygenic disorder produced by the interaction of several genes with minor effects. To explore potential gene-gene interactions among candidate genes for ADHD, we studied the dopamine D2 receptor (DRD2), dopamine D4 receptor (DRD4), dopamine transporter (DAT1), and catechol-O-methyltransferase (COMT) genes in the Han Chinese population. A sample of 340 children with ADHD was diagnosed according to the DSM-IV criteria. We also recruited 226 unrelated controls. Identified polymorphisms included a 48-base-pair-repeat in Exon 3 of DRD4, a 40-base-pair-repeat in the 3' untranslated region of DAT1, a restriction-fragment-length polymorphism at codon 158 of COMT, and a -241A > G transition in the promoter of DRD2. Associations of polymorphisms with ADHD and its subtypes were examined by comparing allele frequencies between probands and controls. Binary logistic regression analysis was used to examine the potential gene-gene interactions. Binary logistic regression analysis with the sample of refined phenotypes showed that male gender and long-repeat genotypes of DRD4 and DAT1 were independent risk factors for ADHD. We found no evidence for gene-gene interactions among the candidate genes studied. The present study suggests that dopamine candidate genes are associated with increased vulnerability to ADHD in the Han Chinese population.

Understanding the Effect Size of Lisdexamfetamine Dimesylate for Treating ADHD in Children and Adults

Abstract: Objective: An earlier meta-analysis of pediatric clinical trials indicated that lisdexamfetamine dimesylate (LDX) had a greater effect size than other stimulant medications. This work tested the hypothesis that the apparent increased efficacy was artifactual. Method: The authors assessed two potential artifacts: an unusually high precision of measurement and an unusually low placebo effect. The authors evaluated generalizability from children of adults. Results: The LDX effect sizes for children were significantly larger than the pooled stimulant effect sizes from studies using the same outcome measures. However, although no other individual stimulant study had an effect size greater than LDX, there was overlap between the 95% confidence intervals for some of these studies and the LDX study. The high LDX effect sizes were not due measurement or placebo effect artifacts. LDX effect sizes for adults were not larger than the stimulant effect sizes from other studies. Conclusion: The high LDX effect size for ...

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

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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.