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Featured researches published by Jing Hua Zhao.


Nature Genetics | 2009

Genetic variation in LIN28B is associated with the timing of puberty

Ken K. Ong; Cathy E. Elks; Shengxu Li; Jing Hua Zhao; J. Luan; Lars Bo Andersen; Sheila Bingham; Soren Brage; George Davey Smith; Ulf Ekelund; Christopher J Gillson; Beate Glaser; Jean Golding; Rebecca Hardy; Kay-Tee Khaw; Diana Kuh; Robert Luben; Michele Marcus; Michael A. McGeehin; Andy R Ness; Kate Northstone; Susan M. Ring; Carol Rubin; Matthew Sims; Kijoung Song; David P. Strachan; Peter Vollenweider; Gérard Waeber; Dawn M. Waterworth; Andrew Wong

The timing of puberty is highly variable. We carried out a genome-wide association study for age at menarche in 4,714 women and report an association in LIN28B on chromosome 6 (rs314276, minor allele frequency (MAF) = 0.33, P = 1.5 × 10−8). In independent replication studies in 16,373 women, each major allele was associated with 0.12 years earlier menarche (95% CI = 0.08–0.16; P = 2.8 × 10−10; combined P = 3.6 × 10−16). This allele was also associated with earlier breast development in girls (P = 0.001; N = 4,271); earlier voice breaking (P = 0.006, N = 1,026) and more advanced pubic hair development in boys (P = 0.01; N = 4,588); a faster tempo of height growth in girls (P = 0.00008; N = 4,271) and boys (P = 0.03; N = 4,588); and shorter adult height in women (P = 3.6 × 10−7; N = 17,274) and men (P = 0.006; N = 9,840) in keeping with earlier growth cessation. These studies identify variation in LIN28B, a potent and specific regulator of microRNA processing, as the first genetic determinant regulating the timing of human pubertal growth and development.


Frontiers in Endocrinology | 2012

Variability in the Heritability of Body Mass Index: A Systematic Review and Meta-Regression

Cathy E. Elks; Marcel den Hoed; Jing Hua Zhao; Stephen J. Sharp; Nicholas J. Wareham; Ruth J.F. Loos; Ken K. Ong

Evidence for a major role of genetic factors in the determination of body mass index (BMI) comes from studies of related individuals. Despite consistent evidence for a heritable component of BMI, estimates of BMI heritability vary widely between studies and the reasons for this remain unclear. While some variation is natural due to differences between populations and settings, study design factors may also explain some of the heterogeneity. We performed a systematic review that identified 88 independent estimates of BMI heritability from twin studies (total 140,525 twins) and 27 estimates from family studies (42,968 family members). BMI heritability estimates from twin studies ranged from 0.47 to 0.90 (5th/50th/95th centiles: 0.58/0.75/0.87) and were generally higher than those from family studies (range: 0.24–0.81; 5th/50th/95th centiles: 0.25/0.46/0.68). Meta-regression of the results from twin studies showed that BMI heritability estimates were 0.07 (Pu2009=u20090.001) higher in children than in adults; estimates increased with mean age among childhood studies (+0.012/year, Pu2009=u20090.002), but decreased with mean age in adult studies (−0.002/year, Pu2009=u20090.002). Heritability estimates derived from AE twin models (which assume no contribution of shared environment) were 0.12 higher than those from ACE models (Pu2009<u20090.001), whilst lower estimates were associated with self reported versus DNA-based determination of zygosity (−0.04, Pu2009=u20090.02), and with self reported versus measured BMI (−0.05, Pu2009=u20090.03). Although the observed differences in heritability according to aspects of study design are relatively small, together, the above factors explained 47% of the heterogeneity in estimates of BMI heritability from twin studies. In summary, while some variation in BMI heritability is expected due to population-level differences, study design factors explained nearly half the heterogeneity reported in twin studies. The genetic contribution to BMI appears to vary with age and may have a greater influence during childhood than adult life.


American Journal of Respiratory and Critical Care Medicine | 2012

Genome-Wide Association Studies Identify CHRNA5/3 and HTR4 in the Development of Airflow Obstruction

Jemma B. Wilk; Nick Shrine; Laura R. Loehr; Jing Hua Zhao; Ani Manichaikul; Lorna M. Lopez; Albert V. Smith; Susan R. Heckbert; Joanna Smolonska; Wenbo Tang; Daan W. Loth; Ivan Curjuric; Jennie Hui; Michael H. Cho; Jeanne C. Latourelle; Amanda P. Henry; Melinda C. Aldrich; Per Bakke; Terri H. Beaty; Amy R. Bentley; Ingrid B. Borecki; Guy Brusselle; Kristin M. Burkart; Ting Hsu Chen; David Couper; James D. Crapo; Gail Davies; Josée Dupuis; Nora Franceschini; Amund Gulsvik

RATIONALEnGenome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known.nnnOBJECTIVESnPerform meta-analyses of GWAS for airflow obstruction, a key pathophysiologic characteristic of COPD assessed by spirometry, in population-based cohorts examining all participants, ever smokers, never smokers, asthma-free participants, and more severe cases.nnnMETHODSnFifteen cohorts were studied for discovery (3,368 affected; 29,507 unaffected), and a population-based family study and a meta-analysis of case-control studies were used for replication and regional follow-up (3,837 cases; 4,479 control subjects). Airflow obstruction was defined as FEV(1) and its ratio to FVC (FEV(1)/FVC) both less than their respective lower limits of normal as determined by published reference equations.nnnMEASUREMENTS AND MAIN RESULTSnThe discovery meta-analyses identified one region on chromosome 15q25.1 meeting genome-wide significance in ever smokers that includes AGPHD1, IREB2, and CHRNA5/CHRNA3 genes. The region was also modestly associated among never smokers. Gene expression studies confirmed the presence of CHRNA5/3 in lung, airway smooth muscle, and bronchial epithelial cells. A single-nucleotide polymorphism in HTR4, a gene previously related to FEV(1)/FVC, achieved genome-wide statistical significance in combined meta-analysis. Top single-nucleotide polymorphisms in ADAM19, RARB, PPAP2B, and ADAMTS19 were nominally replicated in the COPD meta-analysis.nnnCONCLUSIONSnThese results suggest an important role for the CHRNA5/3 region as a genetic risk factor for airflow obstruction that may be independent of smoking and implicate the HTR4 gene in the etiology of airflow obstruction.


The Lancet Respiratory Medicine | 2015

Molecular mechanisms underlying variations in lung function: a systems genetics analysis

Ma'en Obeidat; Ke Hao; Yohan Bossé; David C. Nickle; Yunlong Nie; Dirkje S. Postma; Michel Laviolette; Andrew J. Sandford; Denise Daley; James C. Hogg; W. Mark Elliott; Nick Fishbane; Wim Timens; Pirro G. Hysi; Jaakko Kaprio; James F. Wilson; Jennie Hui; Rajesh Rawal; Holger Schulz; Beate Stubbe; Caroline Hayward; Ozren Polasek; Marjo-Riitta Järvelin; Jing Hua Zhao; Deborah Jarvis; Mika Kähönen; Nora Franceschini; Kari E. North; Daan W. Loth; Guy Brusselle

BACKGROUNDnLung function measures reflect the physiological state of the lung, and are essential to the diagnosis of chronic obstructive pulmonary disease (COPD). The SpiroMeta-CHARGE consortium undertook the largest genome-wide association study (GWAS) so far (n=48,201) for forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC) in the general population. The lung expression quantitative trait loci (eQTLs) study mapped the genetic architecture of gene expression in lung tissue from 1111 individuals. We used a systems genetics approach to identify single nucleotide polymorphisms (SNPs) associated with lung function that act as eQTLs and change the level of expression of their target genes in lung tissue; termed eSNPs.nnnMETHODSnThe SpiroMeta-CHARGE GWAS results were integrated with lung eQTLs to map eSNPs and the genes and pathways underlying the associations in lung tissue. For comparison, a similar analysis was done in peripheral blood. The lung mRNA expression levels of the eSNP-regulated genes were tested for associations with lung function measures in 727 individuals. Additional analyses identified the pleiotropic effects of eSNPs from the published GWAS catalogue, and mapped enrichment in regulatory regions from the ENCODE project. Finally, the Connectivity Map database was used to identify potential therapeutics in silico that could reverse the COPD lung tissue gene signature.nnnFINDINGSnSNPs associated with lung function measures were more likely to be eQTLs and vice versa. The integration mapped the specific genes underlying the GWAS signals in lung tissue. The eSNP-regulated genes were enriched for developmental and inflammatory pathways; by comparison, SNPs associated with lung function that were eQTLs in blood, but not in lung, were only involved in inflammatory pathways. Lung function eSNPs were enriched for regulatory elements and were over-represented among genes showing differential expression during fetal lung development. An mRNA gene expression signature for COPD was identified in lung tissue and compared with the Connectivity Map. This in-silico drug repurposing approach suggested several compounds that reverse the COPD gene expression signature, including a nicotine receptor antagonist. These findings represent novel therapeutic pathways for COPD.nnnINTERPRETATIONnThe system genetics approach identified lung tissue genes driving the variation in lung function and susceptibility to COPD. The identification of these genes and the pathways in which they are enriched is essential to understand the pathophysiology of airway obstruction and to identify novel therapeutic targets and biomarkers for COPD, including drugs that reverse the COPD gene signature in silico.nnnFUNDINGnThe research reported in this article was not specifically funded by any agency. See Acknowledgments for a full list of funders of the lung eQTL study and the Spiro-Meta CHARGE GWAS.


Human Molecular Genetics | 2015

Integrative Pathway Genomics of Lung Function and Airflow Obstruction

Sina A. Gharib; Daan W. Loth; María Soler Artigas; Timothy P. Birkland; Jemma B. Wilk; Louise V. Wain; Jennifer A. Brody; Ma'en Obeidat; Dana B. Hancock; Wenbo Tang; Rajesh Rawal; H. Marike Boezen; Medea Imboden; Jennifer E. Huffman; Lies Lahousse; Alexessander Couto Alves; Ani Manichaikul; Jennie Hui; Alanna C. Morrison; Adaikalavan Ramasamy; Albert V. Smith; Vilmundur Gudnason; Ida Surakka; Veronique Vitart; David Evans; David P. Strachan; Ian J. Deary; Albert Hofman; Sven Gläser; James F. Wilson

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10s role in influencing lungs susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.


International Journal of Epidemiology | 2017

Evidence for large-scale gene-by-smoking interaction effects on pulmonary function

Hugues Aschard; Martin D. Tobin; Dana B. Hancock; David Skurnik; Akshay Sood; Alan James; Albert V. Smith; Ani Manichaikul; Archie Campbell; Bram P. Prins; Caroline Hayward; Daan W. Loth; David J. Porteous; David P. Strachan; Eleftheria Zeggini; George T. O'Connor; Guy Brusselle; H. Marike Boezen; Holger Schulz; Ian J. Deary; Ian P. Hall; Igor Rudan; Jaakko Kaprio; James F. Wilson; Jemma B. Wilk; Jennifer E. Huffman; Jing Hua Zhao; Kim de Jong; Leo-Pekka Lyytikäinen; Louise V. Wain

Abstract Background: Smoking is the strongest environmental risk factor for reduced pulmonary function. The genetic component of various pulmonary traits has also been demonstrated, and at least 26 loci have been reproducibly associated with either FEV1 (forced expiratory volume in 1 second) or FEV1/FVC (FEV1/forced vital capacity). Although the main effects of smoking and genetic loci are well established, the question of potential gene-by-smoking interaction effect remains unanswered. The aim of the present study was to assess, using a genetic risk score approach, whether the effect of these 26 loci on pulmonary function is influenced by smoking. Methods: We evaluated the interaction between smoking exposure, considered as either ever vs never or pack-years, and a 26-single nucleotide polymorphisms (SNPs) genetic risk score in relation to FEV1 or FEV1/FVC in 50u2009047 participants of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and SpiroMeta consortia. Results: We identified an interaction (βintu2009=u2009–0.036, 95% confidence interval, –0.040 to –0.032, Pu2009=u20090.00057) between an unweighted 26 SNP genetic risk score and smoking status (ever/never) on the FEV1/FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV1/FVC threshold used to diagnose chronic obstructive pulmonary disease is higher among ever smokers than among never smokers. A replication analysis in two independent datasets, although not statistically significant, showed a similar trend in the interaction effect. Conclusions: This study highlights the benefit of using genetic risk scores for identifying interactions missed when studying individual SNPs and shows, for the first time, that persons with the highest genetic risk for low FEV1/FVC may be more susceptible to the deleterious effects of smoking.


Archive | 2014

Random-effects models incorporating genomic relationships among individuals

Jing Hua Zhao; Stephen Sharp

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Daan W. Loth

Erasmus University Rotterdam

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Guy Brusselle

Ghent University Hospital

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Jennie Hui

University of Western Australia

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Nora Franceschini

University of North Carolina at Chapel Hill

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