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.

Effect of candidate gene polymorphisms on the course of attention deficit hyperactivity disorder.

Abstract: article i nfo The main aim of this study was to examine the association between attention-deficit hyperactivity disorder (ADHD)-associated genes and the course of ADHD. Subjects were derived from identically designed case- control family studies of boys and girls with ADHD and a genetic linkage study of families with children with ADHD. Caucasian probands and family members with ADHD and with available genetic data were included in this analysis (N=563). The course of ADHD was compared in subjects with and without putative risk alleles (DRD4 7-repeat allele, DAT1 10-repeat allele, and 5HTTLPR long allele). The persistence of ADHD (full or subthreshold diagnosis in the last month) was plotted using Kaplan-Meier survival functions and tested with Cox proportional hazard models. Survival analyses revealed that by 25 years of age 76% of subjects with a DRD4 7-repeat allele were estimated to have significantly more persistent ADHD compared with 66% of subjects without the risk allele. In contrast, there were no significant associations between the course of ADHD and the DAT1 10-repeat allele (P=0.94) and 5HTTLPR long allele. Our findings suggest that the DRD4 7-repeat allele is associated with a more persistent course of ADHD.

Early onset bipolar disorder: possible linkage to chromosome 9q34.

Abstract: Objectives: Bipolar disorder (BD) is characterized by manic and depressive states that onset at various times in life. Research shows that early onset forms of BD are associated with a stronger genetic loading for the illness. We hypothesized that using age at onset to look at subsets of BD families in a genetic linkage analysis would prove useful in separating etiologically homogeneous BD sub-groups and subsequently identifying genetic susceptibility regions. Methods: We used the wave-I National Institute of Mental Health (NIMH) Genetics Initiative BD sample, which includes 540 individuals from 97 families with BD, in an ordered-subsets linkage analysis with age at onset of mania as the subset-identifying covariate. This analysis was performed using GENEHUNTER-PLUS followed by the ordered-subsets analysis program. This program generates empirical p-values for the subset with the largest LOD score to determine whether this value was significantly higher than the baseline LOD score using all families. Results: Three chromosomal regions resulted in LOD scores above 2.0: 2.21 (6q25), 3.21 (9q34), and 2.16 (20q11). The largest increase in LOD score was observed on chromosome 9q34 between markers D9S290 and D9S915 in the subset of 58 families that had mania onset before age 20. Families with a minimal mania onset less than 20 years had a significantly greater number of psychiatric comorbidities (p = 0.02) and a marginal increase in depressive symptoms (p = 0.10). Conclusions: Further investigation into chromosomal region 9q34 is necessary to determine whether this region may harbor a gene specific to families with a minimal age at onset of less than 20.

Clustering by neurocognition for fine mapping of the schizophrenia susceptibility loci on chromosome 6p.

Abstract: Chromosome 6p is one of the most commonly implicated regions in the genome-wide linkage scans of schizophrenia, whereas further association studies for markers in this region were inconsistent likely due to heterogeneity. This study aimed to identify more homogeneous subgroups of families for fine mapping on regions around markers D6S296 and D6S309 (both in 6p24.3) as well as D6S274 (in 6p22.3) by means of similarity in neurocognitive functioning. A total of 160 families of patients with schizophrenia comprising at least two affected siblings who had data for eight neurocognitive test variables of the continuous performance test (CPT) and the Wisconsin card sorting test (WCST) were subjected to cluster analysis with data visualization using the test scores of both affected siblings. Family clusters derived were then used separately in family-based association tests for 64 single nucleotide polymorphisms (SNPs) covering the region of 6p24.3 and 6p22.3. Three clusters were derived from the family-based clustering, with deficit cluster 1 representing deficit on the CPT, deficit cluster 2 representing deficit on both the CPT and the WCST, and a third cluster of nondeficit. After adjustment using false discovery rate for multiple testing, SNP rs13873 and haplotype rs1225934-rs13873 on BMP6-TXNDC5 genes were significantly associated with schizophrenia for the deficit cluster 1 but not for the deficit cluster 2 or nondeficit cluster. Our results provide further evidence that the BMP6-TXNDC5 locus on 6p24.3 may play a role in the selective impairments on sustained attention of schizophrenia.

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.