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.

Shared familial risk factors between attention‐deficit/hyperactivity disorder and overweight/obesity – a population‐based familial coaggregation study in Sweden

Abstract: Background Despite meta-analytic evidence for the association between attention-deficit/hyperactivity disorder (ADHD) and overweight/obesity, the mechanisms underlying the association are yet to be fully understood. Methods By linking multiple Swedish national and regional registers, we identified 472,735 index males born during 1973–1992, with information on body weight and height directly measured before they were conscripted for military service. We further identified 523,237 full siblings born during 1973–2002 for the index males. All individuals were followed up from their third birthday to December 31, 2009 for ADHD diagnosis. Logistic regression models were used to estimate the association between overweight/obesity in index males and ADHD in their full siblings. Results Siblings of index males with overweight/obesity had increased risk for ADHD (overweight: OR = 1.14, 95% CI = 1.05–1.24; obesity: OR = 1.42, 95% CI = 1.24–1.63), compared with siblings of index males with normal weight. The results were adjusted for birth year of the index male and sex of the sibling. After further adjustment for ADHD status of the index male, the familial coaggregation remained significant (overweight: OR = 1.13, 95% CI = 1.04–1.22; obesity: OR = 1.38, 95% CI = 1.21–1.57). The results were similar across sex of the siblings. Conclusions Attention-deficit/hyperactivity disorder and overweight/obesity share familial risk factors, which are not limited to those causing overweight/obesity through the mediation of ADHD. Future research aiming at identifying family-wide environmental risk factors as well as common pleiotropic genetic variants contributing to both traits is warranted.

Family-based association study of the BDNF, COMT and serotonin transporter genes and DSM-IV bipolar-I disorder in children

Abstract: Background Over the past decade pediatric bipolar disorder has gained recognition as a potentially more severe and heritable form of the disorder. In this report we test for association with genes coding brain-derived neurotrophic factor (BDNF), the serotonin transporter (SLC6A4), and catechol-O-methyltransferase (COMT).

Structural Brain Imaging Studies Offer Clues about the Effects of the Shared Genetic Etiology among Neuropsychiatric Disorders

Abstract: Background Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. Methods From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD) and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. Results The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were significantly correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494; p = 0.025). Conclusions Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Lifetime prevalence of mood and anxiety disorders in twin pairs discordant for schizophrenia.

Abstract: There have been long questions about the relationship of schizophrenia to other mental disorders Lifetime DSM-III-R diagnoses of mood and anxiety disorders in twins with clinically diagnosed schizophrenia (n = 24) and their non-affected co-twins (n = 24) were compared with twins from pairs without schizophrenia (n = 3327) using a sample from the Vietnam Era Twin Registry Schizophrenic probands had significantly elevated rates of all included disorders (bipolar disorder, major depression, dysthymia, generalized anxiety disorder, panic disorder, and PTSD) compared with controls (P<001) The odd ratios comparing co-twins of schizophrenic probands with controls was greater than three for every disorder, but did not attain statistical significance A similar pattern was observed when analyses were restricted to only monozygotic twins (n = 12) Consistent with other studies, schizophrenics appeared to have higher rates of a range of mental disorders Our results suggest that schizophrenia per se represents a risk factor for other psychiatric disorders, but the absence of significantly elevated risk among non-schizophrenic co-twins suggested that family environmental and/or genetic factors that contribute to risk of schizophrenia do not increase the risk of mood and anxiety disorders to the same extent that the risk of these other disorders is increased by the presence 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.