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.

An fMRI study of working memory in persons with bipolar disorder or at genetic risk for bipolar disorder.

Abstract: First-degree relatives of persons with bipolar disorders (BDs) carry elevated risk for the illness, and manifest deficits in attention and memory (possible "endophenotypes"). However, there is only one published functional magnetic resonance imaging (fMRI) study of candidate endophenotypes in BD. We used fMRI to examine brain function in BD and in first-degree relatives performing a 2-back working memory (WM) task, and correlated brain activity with mood measures taken at the scanning session. Subjects (age 32-46) were 19 persons with BD, 18 unmedicated, non-psychotic first-degree relatives (RELs) of persons with BD, and 19 matched controls, ascertained from a long-term follow-up of a prenatal cohort study in New England. fMRI signal during 2-back and 0-back WM tasks was measured on a Siemens 1.5T MR scanner. fMRI data were analyzed using SPM-2. Persons with BD and RELs failed to suppress activation in the left anterior insula (BA 13) during WM, whereas controls suppressed activation. Compared to controls, RELs also failed to suppress activation in the orbitofrontal cortex (OFC) and superior parietal cortex. Controls and RELs exhibited greater activation than BD individuals in the left frontopolar cortex (BA 10) during WM. Results remained significant after controlling for confounders except for mild attenuation of OFC findings. Significant correlations between brain activity, mood, and WM suggest that activity in WM circuits is affected by activity in emotion-regulatory circuits. Persons with BD and RELs exhibit altered activity in the frontopolar cortex and insula, which may represent biomarkers of genetic risk for BD.

Collaborative Analysis of DRD4 and DAT Genotypes in Population-Defined ADHD Subtypes.

Abstract: Background: It has been proposed that some of the variability in reporting of associations between attention deficit hyperactivity disorder (ADHD) and candidate genes may result from mixing of genetically heterogeneous forms of ADHD using DSM-IV criteria. The goal of the current study is to test whether population-based ADHD subtypes defined by latent class analysis help resolve issues of variable findings across individual gene association studies. Methods: Three studies which had previously reported no associations between polymorphisms of the DRD4 and DAT genes and DSM-IV defined ADHD were reanalyzed using population-based and DSM-IV defined ADHD subtypes. Results: Across studies no significant associations were found for either DRD4 or DAT polymorphisms using DSM-IV ADHD subtypes. In contrast, a significant association was found between the combined data set for the 440 base pair 3¢ DAT VNTR polymorphism and population-defined severe combined ADHD (OR ¼ 1.25, p ¼ .01). A marginally significant association was also found between the 7 repeat DRD4 allele and population-defined severe combined ADHD. Conclusion: Use of alternative population-based defined ADHD subtypes may help resolve some of the variable results presented for candidate gene association studies in ADHD. Keywords: Attention deficit/hyperactivity disorder, DRD4, DAT, latent class analysis. Abbreviations: ADHD: attention deficit/hyperactivity disorder; VNTR: variable number of tandem repeats; DRD4: dopamine D4 receptor gene; DAT: dopamine transporter gene; TDT: transmission disequilibrium test.

The impact of study design and diagnostic approach in a large multi-centre ADHD study. Part 1: ADHD symptom patterns

Abstract: The International Multi-centre ADHD Genetics (IMAGE) project with 11 participating centres from 7 European countries and Israel has collected a large behavioural and genetic database for present and future research. Behavioural data were collected from 1068 probands with the combined type of attention deficit/hyperactivity disorder (ADHD-CT) and 1446 'unselected' siblings. The aim was to analyse the IMAGE sample with respect to demographic features (gender, age, family status, and recruiting centres) and psychopathological characteristics (diagnostic subtype, symptom frequencies, age at symptom detection, and comorbidities). A particular focus was on the effects of the study design and the diagnostic procedure on the homogeneity of the sample in terms of symptom-based behavioural data, and potential consequences for further analyses based on these data. Diagnosis was based on the Parental Account of Childhood Symptoms (PACS) interview and the DSM-IV items of the Conners' teacher questionnaire. Demographics of the full sample and the homogeneity of a subsample (all probands) were analysed by using robust statistical procedures which were adjusted for unequal sample sizes and skewed distributions. These procedures included multi-way analyses based on trimmed means and winsorised variances as well as bootstrapping. Age and proband/sibling ratios differed between participating centres. There was no significant difference in the distribution of gender between centres. There was a significant interaction between age and centre for number of inattentive, but not number of hyperactive symptoms. Higher ADHD symptom frequencies were reported by parents than teachers. The diagnostic symptoms differed from each other in their frequencies. The face-to-face interview was more sensitive than the questionnaire. The differentiation between ADHD-CT probands and unaffected siblings was mainly due to differences in hyperactive/impulsive symptoms. Despite a symptom-based standardized inclusion procedure according to DSM-IV criteria with defined symptom thresholds, centres may differ markedly in probands' ADHD symptom frequencies. Both the diagnostic procedure and the multi-centre design influence the behavioural characteristics of a sample and, thus, may bias statistical analyses, particularly in genetic or neurobehavioral studies.

Attention-deficit/hyperactivity disorder in children and adolescents with obsessive-compulsive disorder: fact or artifact?

Abstract: Objective To clarify whether the symptoms of inattention and distractibility commonly seen in children and adolescents with obsessive-compulsive disorder (OCD) represent true comorbidity with attention-deficit/hyperactivity disorder (ADHD) or a manifestation of obsessional anxiety Method Phenotypic features and functional correlates of ADHD-like symptoms were examined in youths with and without OCD from a large sample of pediatric psychiatry patients consecutively referred since 1997 Results The number, frequency, and types of core ADHD symptoms as well as ADHD-associated functional indices were identical in all youths with DSM-IV –diagnosed ADHD irrespective of the presence or absence of comorbid OCD Conclusions These findings suggest that when ADHD-like symptoms are seen in youths with OCD, they reflect a true comorbid state of OCD plus ADHD and that the ADHD syndrome may be independent of OCD in comorbid youths

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.