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.

Using vulnerability indicators to compare conceptual models of genetic heterogeneity in schizophrenia

Abstract: The search for indicators of vulnerability has been important in schizophrenia research, but, as in many areas, progress has been impeded due to the heterogeneity of schizophrenic disorders. How one conceptualizes the observed heterogeneity is dependent upon the particular genetic model to which one subscribes. In this article, we delineate several models that may account for the distributions of vulnerability indicators in groups of schizophrenic patients and their ill and well relatives. We present these models for heuristic purposes so that they may serve to guide the interpretation of data with respect to the issue of teasing apart familial and nonfamilial environmental components of putative vulnerability indicators. It is suggested that investigators will profit by: a) efforts to combine psychiatric genetic paradigms in order to maximize the yield of family study data, and b) thinking in terms of comparing the ability of different models to account for research findings.

A controlled family study of children with DSM-IV bipolar-I disorder and psychiatric co-morbidity.

Abstract: Background. To estimate the spectrum of familial risk for psychopathology in first-degree relatives of children with unabridged DSM-IV bipolar-I disorder (BP-I). Method. We conducted a blinded, controlled family study using structured diagnostic interviews of 157 children with BP-I probands (n =487 first-degree relatives), 162 attention deficit hyperactivity disorder (ADHD) (without BP-I) probands (n=511 first-degree relatives), and 136 healthy control (without ADHD or BP-I) probands (n=411 first-degree relatives). Results. The morbid risk (MR) of BP-I disorder in relatives of BP-I probands (MR = 0.18) was increased 4-fold [95% confidence interval (CI) 2.3-6.9, p<0.001] over the risk to relatives of control probands (MR=0.05) and 3.5-fold (95% CI 2.1-5.8, p<0.001) over the risk to relatives of ADHD probands (MR=0.06). In addition, relatives of children with BP-I disorder had high rates of psychosis, major depression, multiple anxiety disorders, substance use disorders, ADHD and antisocial disorders compared with relatives of control probands. Only the effect for antisocial disorders lost significance after accounted for by the corresponding diagnosis in the proband. Familial rates of ADHD did not differ between ADHD and BP-I probands. Conclusions. Our results document an increased familial risk for BP-I disorder in relatives of pediatric probands with DSM-IV BP-I. Relatives of probands with BP-I were also at increased risk for other psychiatric disorders frequently associated with pediatric BP-I. These results support the validity of the diagnosis of BP-I in children as defined by DSM-IV. More work is needed to better understand the nature of the association between these disorders in probands and relatives.

Towards defining a meaningful anxiety phenotype for research in ADHD children

Abstract: Objective: To combine anxiety diagnoses empirically into a meaningful definition of a comorbid anxiety syndrome in ADHD children.Methods: The prevalence of all DSM-111-R anxiety disorders was examined in our ADHD sample (N =237) and a Receiver Operating Characteristic (ROC) analysis was conducted to combine the information optimally from these many disorders into a single anxiety phenotype.Results: We found that two or more anxiety disorders correctly identified a large number of ADHD children as anxious (SN=0.75) while maintaining a reasonable false positive rate (Sp=0.67). In contrast, the criterion of three or more anxiety disorders correctly identified only half the sample and the criterion of one or more anxiety disorders had a much higher false positive rate. The necessary data are also presented for those that may wish to use a definition other than 2 or more anxiety disorders.Conclusion: These findings suggest that using 2 or more anxiety disorders may offer a useful approach to defining comorbid ...

ADHD and DAT1: further evidence of paternal over-transmission of risk alleles and haplotype.

Abstract: We [Hawi et al. (2005); Am J Hum Genet 77:958-965] reported paternal over-transmission of risk alleles in some ADHD-associated genes. This was particularly clear in the case of the DAT1 3'-UTR VNTR. In the current investigation, we analyzed three new sample comprising of 1,248 ADHD nuclear families to examine the allelic over-transmission of DAT1 in ADHD. The IMAGE sample, the largest of the three-replication samples, provides strong support for a parent of origin effect for allele 6 and the 10 repeat allele (intron 8 and 3'-UTR VNTR, respectively) of DAT1. In addition, a similar pattern of over-transmission of paternal risk haplotypes (constructed from the above alleles) was also observed. Some support is also derived from the two smaller samples although neither is independently significant. Although the mechanism driving the paternal over-transmission of the DAT risk alleles is not known, these finding provide further support for this phenomenon.

Treatment of ADHD With Stimulant Medications: Response to Nissen Perspective in The New England Journal of Medicine

Abstract: Journal of the American Academy of Child & Adolescent Psychiatry - Vol. 45 - N° 10 - p. 1147-1150

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.