Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Sean Chong is active.

Publication


Featured researches published by Sean Chong.


Human Molecular Genetics | 2011

Distinct DNA methylation changes highly correlated with chronological age in the human brain

Dena Hernandez; Michael A. Nalls; J. Raphael Gibbs; Sampath Arepalli; Marcel van der Brug; Sean Chong; Matthew Moore; Dan L. Longo; Mark R. Cookson; Bryan J. Traynor; Andrew Singleton

Methylation at CpG sites is a critical epigenetic modification in mammals. Altered DNA methylation has been suggested to be a central mechanism in development, some disease processes and cellular senescence. Quantifying the extent and identity of epigenetic changes in the aging process is therefore potentially important for understanding longevity and age-related diseases. In the current study, we have examined DNA methylation at >27,000 CpG sites throughout the human genome, in frontal cortex, temporal cortex, pons and cerebellum from 387 human donors between the ages of 1 and 102 years. We identify CpG loci that show a highly significant, consistent correlation between DNA methylation and chronological age. The majority of these loci are within CpG islands and there is a positive correlation between age and DNA methylation level. Lastly, we show that the CpG sites where the DNA methylation level is significantly associated with age are physically close to genes involved in DNA binding and regulation of transcription. This suggests that specific age-related DNA methylation changes may have quite a broad impact on gene expression in the human brain.


PLOS Genetics | 2011

Multiple Loci Are Associated with White Blood Cell Phenotypes

Michael A. Nalls; David Couper; Toshiko Tanaka; Frank J. A. van Rooij; Ming-Huei Chen; Albert V. Smith; Daniela Toniolo; Neil A. Zakai; Qiong Yang; Andreas Greinacher; Andrew R. Wood; Melissa Garcia; Paolo Gasparini; Yongmei Liu; Thomas Lumley; Aaron R. Folsom; Alex P. Reiner; Christian Gieger; Vasiliki Lagou; Janine F. Felix; Henry Völzke; Natalia Gouskova; Alessandro Biffi; Angela Döring; Uwe Völker; Sean Chong; Kerri L. Wiggins; Augusto Rendon; Abbas Dehghan; Matt Moore

White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count—6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count—17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count—6p21, 19p13 at EPS15L1; monocyte count—2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds.


JAMA Neurology | 2011

Large proportion of amyotrophic lateral sclerosis cases in sardinia due to a single founder mutation of the TARDBP gene

Adriano Chiò; Giuseppe Borghero; Maura Pugliatti; Anna Ticca; Andrea Calvo; Cristina Moglia; Roberto Mutani; Maura Brunetti; Irene Ossola; Maria Giovanna Marrosu; Maria Rita Murru; Gianluca Floris; Antonino Cannas; Leslie D. Parish; P Cossu; Yevgeniya Abramzon; Janel O. Johnson; Michael A. Nalls; Sampath Arepalli; Sean Chong; Dena Hernandez; Bryan J. Traynor; Gabriella Restagno

OBJECTIVE To perform an extensive screening for mutations of amyotrophic lateral sclerosis (ALS)-related genes in a consecutive cohort of Sardinian patients, a genetic isolate phylogenically distinct from other European populations. DESIGN Population-based, prospective cohort study. PATIENTS A total of 135 Sardinian patients with ALS and 156 healthy control subjects of Sardinian origin who were age- and sex-matched to patients. INTERVENTION Patients underwent mutational analysis for SOD1, FUS, and TARDBP. RESULTS Mutational screening of the entire cohort found that 39 patients (28.7%) carried the c.1144G>A (p.A382T) missense mutation of the TARDBP gene. Of these, 15 had familial ALS (belonging to 10 distinct pedigrees) and 24 had apparently sporadic ALS. None of the 156 age-, sex-, and ethnicity-matched controls carried the pathogenic variant. Genotype data obtained for 5 ALS cases carrying the p.A382T mutation found that they shared a 94-single-nucleotide polymorphism risk haplotype that spanned 663 Kb across the TARDBP locus on chromosome 1p36.22. Three patients with ALS who carry the p.A382T mutation developed extrapyramidal symptoms several years after their initial presentation with motor weakness. CONCLUSIONS The TARDBP p.A382T missense mutation accounts for approximately one-third of all ALS cases in this island population. These patients share a large risk haplotype across the TARDBP locus, indicating that they have a common ancestor.


Neurobiology of Disease | 2012

Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain.

Dena Hernandez; Michael A. Nalls; Matthew Moore; Sean Chong; Allissa Dillman; Daniah Trabzuni; J. Raphael Gibbs; Mina Ryten; Sampath Arepalli; Michael E. Weale; Alan B. Zonderman; Juan C. Troncoso; Richard O'Brien; Robert P. Walker; Colin Smith; Stefania Bandinelli; Bryan J. Traynor; John Hardy; Andrew Singleton; Mark R. Cookson

Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied.


JAMA Neurology | 2015

A genome-wide association study of myasthenia gravis

Alan E. Renton; Hannah Pliner; Carlo Provenzano; Amelia Evoli; Roberta Ricciardi; Michael A. Nalls; Giuseppe Marangi; Yevgeniya Abramzon; Sampath Arepalli; Sean Chong; Dena Hernandez; Janel O. Johnson; Emanuela Bartoccioni; Flavia Scuderi; Michelangelo Maestri; J. Raphael Gibbs; Edoardo Errichiello; Adriano Chiò; Gabriella Restagno; Mario Sabatelli; Mark Macek; Sonja W. Scholz; Andrea M. Corse; Vinay Chaudhry; Michael Benatar; Richard J. Barohn; April L. McVey; Mamatha Pasnoor; Mazen M. Dimachkie; Julie Rowin

IMPORTANCE Myasthenia gravis is a chronic, autoimmune, neuromuscular disease characterized by fluctuating weakness of voluntary muscle groups. Although genetic factors are known to play a role in this neuroimmunological condition, the genetic etiology underlying myasthenia gravis is not well understood. OBJECTIVE To identify genetic variants that alter susceptibility to myasthenia gravis, we performed a genome-wide association study. DESIGN, SETTING, AND PARTICIPANTS DNA was obtained from 1032 white individuals from North America diagnosed as having acetylcholine receptor antibody-positive myasthenia gravis and 1998 race/ethnicity-matched control individuals from January 2010 to January 2011. These samples were genotyped on Illumina OmniExpress single-nucleotide polymorphism arrays. An independent cohort of 423 Italian cases and 467 Italian control individuals were used for replication. MAIN OUTCOMES AND MEASURES We calculated P values for association between 8,114,394 genotyped and imputed variants across the genome and risk for developing myasthenia gravis using logistic regression modeling. A threshold P value of 5.0×10(-8) was set for genome-wide significance after Bonferroni correction for multiple testing. RESULTS In the overall case-control cohort, we identified association signals at CTLA4 (rs231770; P=3.98×10(-8); odds ratio, 1.37; 95% CI, 1.25-1.49), HLA-DQA1 (rs9271871; P=1.08×10(-8); odds ratio, 2.31; 95% CI, 2.02-2.60), and TNFRSF11A (rs4263037; P=1.60×10(-9); odds ratio, 1.41; 95% CI, 1.29-1.53). These findings replicated for CTLA4 and HLA-DQA1 in an independent cohort of Italian cases and control individuals. Further analysis revealed distinct, but overlapping, disease-associated loci for early- and late-onset forms of myasthenia gravis. In the late-onset cases, we identified 2 association peaks: one was located in TNFRSF11A (rs4263037; P=1.32×10(-12); odds ratio, 1.56; 95% CI, 1.44-1.68) and the other was detected in the major histocompatibility complex on chromosome 6p21 (HLA-DQA1; rs9271871; P=7.02×10(-18); odds ratio, 4.27; 95% CI, 3.92-4.62). Association within the major histocompatibility complex region was also observed in early-onset cases (HLA-DQA1; rs601006; P=2.52×10(-11); odds ratio, 4.0; 95% CI, 3.57-4.43), although the set of single-nucleotide polymorphisms was different from that implicated among late-onset cases. CONCLUSIONS AND RELEVANCE Our genetic data provide insights into aberrant cellular mechanisms responsible for this prototypical autoimmune disorder. They also suggest that clinical trials of immunomodulatory drugs related to CTLA4 and that are already Food and Drug Administration approved as therapies for other autoimmune diseases could be considered for patients with refractory disease.


Human Molecular Genetics | 2011

Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

Andrew R. Wood; Dena Hernandez; Michael A. Nalls; Hanieh Yaghootkar; J. Raphael Gibbs; Lorna W. Harries; Sean Chong; Matthew Moore; Michael N. Weedon; Jack M. Guralnik; Stefania Bandinelli; Anna Murray; Luigi Ferrucci; Andrew Singleton; David Melzer; Timothy M. Frayling

The identification of multiple signals at individual loci could explain additional phenotypic variance (‘missing heritability’) of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.


Neuron | 2010

Exome Sequencing Reveals VCP Mutations as a Cause of Familial ALS

Janel O. Johnson; Jessica Mandrioli; Michael Benatar; Yevgeniya Abramzon; Vivianna M. Van Deerlin; John Q. Trojanowski; J. Raphael Gibbs; Maura Brunetti; Susan Gronka; Joanne Wuu; Jinhui Ding; Leo McCluskey; Maria Martinez-Lage; Dana Falcone; Dena Hernandez; Sampath Arepalli; Sean Chong; Jennifer C. Schymick; Jeffrey D. Rothstein; Francesco Landi; Yong Dong Wang; Andrea Calvo; Gabriele Mora; Mario Sabatelli; Maria Rosaria Monsurrò; Stefania Battistini; Fabrizio Salvi; Rossella Spataro; Patrizia Sola; Giuseppe Borghero


Human Molecular Genetics | 1997

Contribution of DNA Sequence and CAG Size to Mutation Frequencies of Intermediate Alleles for Huntington Disease: Evidence from Single Sperm Analyses

Sean Chong; Elisabeth W. Almqvist; H. Telenius; Leah LaTray; K. Nichol; Brooke N. Bourdélat-Parks; Y.P. Goldberg; B. R. Haddad; F. Richards; David Sillence; C. R. Greenberg; Elizabeth Ives; G. van den Engh; M. R. Hughes; Michael R. Hayden


Neuron | 2011

Erratum exome sequencing reveals VCP mutations as a cause of familial ALS

Janel O. Johnson; Jessica Mandrioli; Michael Benatar; Yevgeniya Abramzon; Vivianna M. Van Deerlin; John Q. Trojanowski; J. Raphael Gibbs; Maura Brunetti; Susan Gronka; Joanne Wuu; Jinhui Ding; Leo McCluskey; Maria Martinez-Lage; Dana Falcone; Dena Hernandez; Sampath Arepalli; Sean Chong; Jennifer C. Schymick; Jeffrey D. Rothstein; Francesco Landi; Yong Dong Wang; Andrea Calvo; Gabriele Mora; Mario Sabatelli; Maria Rosaria Monsurrò; Stefania Battistini; Fabrizio Salvi; Rossella Spataro; Patrizia Sola; Giuseppe Borghero


Clinical Biochemistry | 2011

Identifying likely causal connections between gene expression levels using a Mendelian randomization approach

Hanieh Yaghootkar; Dena Hernandez; Michael A. Nalls; Andrew R. Wood; Raphael Gibbs; Lorna W. Harries; Sean Chong; Matthew Moore; Jack M. Guralnik; Stefaniai Bandinell; Anna Murray; Luigi Ferrucci; Andrew Singleton; David Melzer; Timothy M. Frayling

Collaboration


Dive into the Sean Chong's collaboration.

Top Co-Authors

Avatar

Dena Hernandez

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Michael A. Nalls

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

J. Raphael Gibbs

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Sampath Arepalli

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Andrew Singleton

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Janel O. Johnson

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Matthew Moore

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Yevgeniya Abramzon

National Institutes of Health

View shared research outputs
Top Co-Authors

Avatar

Mario Sabatelli

The Catholic University of America

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge