Publications by authors named "Hong-Kiat Ng"

13 Publications

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Epigenetic disturbances in obesity and diabetes: Epidemiological and functional insights.

Mol Metab 2019 09;27S:S33-S41

Lee Kong Chian School of Medicine, Nanyang Technological University 308232, Singapore; Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall UB1 3HW, UK; Imperial College Healthcare NHS Trust, London W12 0HS, UK. Electronic address:

Background: Obesity and type 2 diabetes (T2D) are major public health issues worldwide, and put a significant burden on the healthcare system. Genetic variants, along with traditional risk factors such as diet and physical activity, could account for up to approximately a quarter of disease risk. Epigenetic factors have demonstrated potential in accounting for additional phenotypic variation, along with providing insights into the causal relationship linking genetic variants to phenotypes.

Scope Of Review: In this review article, we discuss the epidemiological and functional insights into epigenetic disturbances in obesity and diabetes, along with future research directions and approaches, with a focus on DNA methylation.

Major Conclusions: Epigenetic mechanisms have been shown to contribute to obesity and T2D disease development, as well as potential differences in disease risks between ethnic populations. Technology to investigate epigenetic profiles in diseased individuals and tissues has advanced significantly in the last years, and suggests potential in application of epigenetic factors in clinical monitoring and as therapeutic options.
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http://dx.doi.org/10.1016/j.molmet.2019.06.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768506PMC
September 2019

Systematic evaluation of library preparation methods and sequencing platforms for high-throughput whole genome bisulfite sequencing.

Sci Rep 2019 07 17;9(1):10383. Epub 2019 Jul 17.

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.

Whole genome bisulfite sequencing (WGBS), with its ability to interrogate methylation status at single CpG site resolution epigenome-wide, is a powerful technique for use in molecular experiments. Here, we aim to advance strategies for accurate and efficient WGBS for application in future large-scale epidemiological studies. We systematically compared the performance of three WGBS library preparation methods with low DNA input requirement (Swift Biosciences Accel-NGS, Illumina TruSeq and QIAGEN QIAseq) on two state-of-the-art sequencing platforms (Illumina NovaSeq and HiSeq X), and also assessed concordance between data generated by WGBS and methylation arrays. Swift achieved the highest proportion of CpG sites assayed and effective coverage at 26x (P < 0.001). TruSeq suffered from the highest proportion of PCR duplicates, while QIAseq failed to deliver across all quality metrics. There was little difference in performance between NovaSeq and HiSeq X, with the exception of higher read duplication rate on the NovaSeq (P < 0.05), likely attributable to the higher cluster densities on its flow cells. Systematic biases exist between WGBS and methylation arrays, with lower precision observed for WGBS across the range of depths investigated. To achieve a level of precision broadly comparable to the methylation array, a minimum coverage of 100x is recommended.
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http://dx.doi.org/10.1038/s41598-019-46875-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637168PMC
July 2019

miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set.

BMC Bioinformatics 2018 08 10;19(1):299. Epub 2018 Aug 10.

Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore.

Background: The knowledge of miRNAs regulating the expression of sets of mRNAs has led to novel insights into numerous and diverse cellular mechanisms. While a single miRNA may regulate many genes, one gene can be regulated by multiple miRNAs, presenting a complex relationship to model for accurate predictions.

Results: Here, we introduce miREM, a program that couples an expectation-maximization (EM) algorithm to the common approach of hypergeometric probability (HP), which improves the prediction and prioritization of miRNAs from gene-sets of interest. miREM has been made available through a web-server ( https://bioinfo-csi.nus.edu.sg/mirem2/ ) that can be accessed through an intuitive graphical user interface. The program incorporates a large compendium of human/mouse miRNA-target prediction databases to enhance prediction. Users may upload their genes of interest in various formats as an input and select whether to consider non-conserved miRNAs, amongst filtering options. Results are reported in a rich graphical interface that allows users to: (i) prioritize predicted miRNAs through a scatterplot of HP p-values and EM scores; (ii) visualize the predicted miRNAs and corresponding genes through a heatmap; and (iii) identify and filter homologous or duplicated predictions by clustering them according to their seed sequences.

Conclusion: We tested miREM using RNAseq datasets from two single "spiked" knock-in miRNA experiments and two double knock-out miRNA experiments. miREM predicted these manipulated miRNAs as having high EM scores from the gene set signatures (i.e. top predictions for single knock-in and double knock-out miRNA experiments). Finally, we have demonstrated that miREM predictions are either similar or better than results provided by existing programs.
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http://dx.doi.org/10.1186/s12859-018-2292-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086043PMC
August 2018

Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis.

Biol Direct 2018 02 12;13(1). Epub 2018 Feb 12.

Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore, 138671, Singapore.

Background: Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip's law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically under the conditions of infinite observations, real world observations are finite where the finite-size effects will set in to force a power-law distribution into an exponential decay and consequently, manifests as a curvature (i.e., varying exponent values) in a log-log plot. If transcript abundance is truly power-law distributed, the varying exponent signifies changing mathematical moments (e.g., mean, variance) and creates heteroskedasticity which compromises statistical rigor in analysis. The impact of this deviation from the asymptotic power-law on sequencing count data has never truly been examined and quantified.

Results: The anecdotal description of transcript abundance being almost Zipf's law-like distributed can be conceptualized as the imperfect mathematical rendition of the Pareto power-law distribution when subjected to the finite-size effects in the real world; This is regardless of the advancement in sequencing technology since sampling is finite in practice. Our conceptualization agrees well with our empirical analysis of two modern day NGS (Next-generation sequencing) datasets: an in-house generated dilution miRNA study of two gastric cancer cell lines (NUGC3 and AGS) and a publicly available spike-in miRNA data; Firstly, the finite-size effects causes the deviations of sequencing count data from Zipf's law and issues of reproducibility in sequencing experiments. Secondly, it manifests as heteroskedasticity among experimental replicates to bring about statistical woes. Surprisingly, a straightforward power-law correction that restores the distribution distortion to a single exponent value can dramatically reduce data heteroskedasticity to invoke an instant increase in signal-to-noise ratio by 50% and the statistical/detection sensitivity by as high as 30% regardless of the downstream mapping and normalization methods. Most importantly, the power-law correction improves concordance in significant calls among different normalization methods of a data series averagely by 22%. When presented with a higher sequence depth (4 times difference), the improvement in concordance is asymmetrical (32% for the higher sequencing depth instance versus 13% for the lower instance) and demonstrates that the simple power-law correction can increase significant detection with higher sequencing depths. Finally, the correction dramatically enhances the statistical conclusions and eludes the metastasis potential of the NUGC3 cell line against AGS of our dilution analysis.

Conclusions: The finite-size effects due to undersampling generally plagues transcript count data with reproducibility issues but can be minimized through a simple power-law correction of the count distribution. This distribution correction has direct implication on the biological interpretation of the study and the rigor of the scientific findings.

Reviewers: This article was reviewed by Oliviero Carugo, Thomas Dandekar and Sandor Pongor.
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http://dx.doi.org/10.1186/s13062-018-0204-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809866PMC
February 2018

Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity.

Authors:
Simone Wahl Alexander Drong Benjamin Lehne Marie Loh William R Scott Sonja Kunze Pei-Chien Tsai Janina S Ried Weihua Zhang Youwen Yang Sili Tan Giovanni Fiorito Lude Franke Simonetta Guarrera Silva Kasela Jennifer Kriebel Rebecca C Richmond Marco Adamo Uzma Afzal Mika Ala-Korpela Benedetta Albetti Ole Ammerpohl Jane F Apperley Marian Beekman Pier Alberto Bertazzi S Lucas Black Christine Blancher Marc-Jan Bonder Mario Brosch Maren Carstensen-Kirberg Anton J M de Craen Simon de Lusignan Abbas Dehghan Mohamed Elkalaawy Krista Fischer Oscar H Franco Tom R Gaunt Jochen Hampe Majid Hashemi Aaron Isaacs Andrew Jenkinson Sujeet Jha Norihiro Kato Vittorio Krogh Michael Laffan Christa Meisinger Thomas Meitinger Zuan Yu Mok Valeria Motta Hong Kiat Ng Zacharoula Nikolakopoulou Georgios Nteliopoulos Salvatore Panico Natalia Pervjakova Holger Prokisch Wolfgang Rathmann Michael Roden Federica Rota Michelle Ann Rozario Johanna K Sandling Clemens Schafmayer Katharina Schramm Reiner Siebert P Eline Slagboom Pasi Soininen Lisette Stolk Konstantin Strauch E-Shyong Tai Letizia Tarantini Barbara Thorand Ettje F Tigchelaar Rosario Tumino Andre G Uitterlinden Cornelia van Duijn Joyce B J van Meurs Paolo Vineis Ananda Rajitha Wickremasinghe Cisca Wijmenga Tsun-Po Yang Wei Yuan Alexandra Zhernakova Rachel L Batterham George Davey Smith Panos Deloukas Bastiaan T Heijmans Christian Herder Albert Hofman Cecilia M Lindgren Lili Milani Pim van der Harst Annette Peters Thomas Illig Caroline L Relton Melanie Waldenberger Marjo-Riitta Järvelin Valentina Bollati Richie Soong Tim D Spector James Scott Mark I McCarthy Paul Elliott Jordana T Bell Giuseppe Matullo Christian Gieger Jaspal S Kooner Harald Grallert John C Chambers

Nature 2017 01 21;541(7635):81-86. Epub 2016 Dec 21.

Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK.

Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances. Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation, a key regulator of gene expression and molecular phenotype. Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 × 10, range P = 9.2 × 10 to 6.0 × 10; n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 × 10, range P = 5.5 × 10 to 6.1 × 10, n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07-2.56); P = 1.1 × 10). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.
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http://dx.doi.org/10.1038/nature20784DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570525PMC
January 2017

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation.

Authors:
Norihiro Kato Marie Loh Fumihiko Takeuchi Niek Verweij Xu Wang Weihua Zhang Tanika N Kelly Danish Saleheen Benjamin Lehne Irene Mateo Leach Alexander W Drong James Abbott Simone Wahl Sian-Tsung Tan William R Scott Gianluca Campanella Marc Chadeau-Hyam Uzma Afzal Tarunveer S Ahluwalia Marc Jan Bonder Peng Chen Abbas Dehghan Todd L Edwards Tõnu Esko Min Jin Go Sarah E Harris Jaana Hartiala Silva Kasela Anuradhani Kasturiratne Chiea-Chuen Khor Marcus E Kleber Huaixing Li Zuan Yu Mok Masahiro Nakatochi Nur Sabrina Sapari Richa Saxena Alexandre F R Stewart Lisette Stolk Yasuharu Tabara Ai Ling Teh Ying Wu Jer-Yuarn Wu Yi Zhang Imke Aits Alexessander Da Silva Couto Alves Shikta Das Rajkumar Dorajoo Jemma C Hopewell Yun Kyoung Kim Robert W Koivula Jian'an Luan Leo-Pekka Lyytikäinen Quang N Nguyen Mark A Pereira Iris Postmus Olli T Raitakari Molly Scannell Bryan Robert A Scott Rossella Sorice Vinicius Tragante Michela Traglia Jon White Ken Yamamoto Yonghong Zhang Linda S Adair Alauddin Ahmed Koichi Akiyama Rasheed Asif Tin Aung Inês Barroso Andrew Bjonnes Timothy R Braun Hui Cai Li-Ching Chang Chien-Hsiun Chen Ching-Yu Cheng Yap-Seng Chong Rory Collins Regina Courtney Gail Davies Graciela Delgado Loi D Do Pieter A Doevendans Ron T Gansevoort Yu-Tang Gao Tanja B Grammer Niels Grarup Jagvir Grewal Dongfeng Gu Gurpreet S Wander Anna-Liisa Hartikainen Stanley L Hazen Jing He Chew-Kiat Heng James E Hixson Albert Hofman Chris Hsu Wei Huang Lise L N Husemoen Joo-Yeon Hwang Sahoko Ichihara Michiya Igase Masato Isono Johanne M Justesen Tomohiro Katsuya Muhammad G Kibriya Young Jin Kim Miyako Kishimoto Woon-Puay Koh Katsuhiko Kohara Meena Kumari Kenneth Kwek Nanette R Lee Jeannette Lee Jiemin Liao Wolfgang Lieb David C M Liewald Tatsuaki Matsubara Yumi Matsushita Thomas Meitinger Evelin Mihailov Lili Milani Rebecca Mills Nina Mononen Martina Müller-Nurasyid Toru Nabika Eitaro Nakashima Hong Kiat Ng Kjell Nikus Teresa Nutile Takayoshi Ohkubo Keizo Ohnaka Sarah Parish Lavinia Paternoster Hao Peng Annette Peters Son T Pham Mohitha J Pinidiyapathirage Mahfuzar Rahman Hiromi Rakugi Olov Rolandsson Michelle Ann Rozario Daniela Ruggiero Cinzia F Sala Ralhan Sarju Kazuro Shimokawa Harold Snieder Thomas Sparsø Wilko Spiering John M Starr David J Stott Daniel O Stram Takao Sugiyama Silke Szymczak W H Wilson Tang Lin Tong Stella Trompet Väinö Turjanmaa Hirotsugu Ueshima André G Uitterlinden Satoshi Umemura Marja Vaarasmaki Rob M van Dam Wiek H van Gilst Dirk J van Veldhuisen Jorma S Viikari Melanie Waldenberger Yiqin Wang Aili Wang Rory Wilson Tien-Yin Wong Yong-Bing Xiang Shuhei Yamaguchi Xingwang Ye Robin D Young Terri L Young Jian-Min Yuan Xueya Zhou Folkert W Asselbergs Marina Ciullo Robert Clarke Panos Deloukas Andre Franke Paul W Franks Steve Franks Yechiel Friedlander Myron D Gross Zhirong Guo Torben Hansen Marjo-Riitta Jarvelin Torben Jørgensen J Wouter Jukema Mika Kähönen Hiroshi Kajio Mika Kivimaki Jong-Young Lee Terho Lehtimäki Allan Linneberg Tetsuro Miki Oluf Pedersen Nilesh J Samani Thorkild I A Sørensen Ryoichi Takayanagi Daniela Toniolo Habibul Ahsan Hooman Allayee Yuan-Tsong Chen John Danesh Ian J Deary Oscar H Franco Lude Franke Bastiaan T Heijman Joanna D Holbrook Aaron Isaacs Bong-Jo Kim Xu Lin Jianjun Liu Winfried März Andres Metspalu Karen L Mohlke Dharambir K Sanghera Xiao-Ou Shu Joyce B J van Meurs Eranga Vithana Ananda R Wickremasinghe Cisca Wijmenga Bruce H W Wolffenbuttel Mitsuhiro Yokota Wei Zheng Dingliang Zhu Paolo Vineis Soterios A Kyrtopoulos Jos C S Kleinjans Mark I McCarthy Richie Soong Christian Gieger James Scott Yik-Ying Teo Jiang He Paul Elliott E Shyong Tai Pim van der Harst Jaspal S Kooner John C Chambers

Nat Genet 2015 11 21;47(11):1282-1293. Epub 2015 Sep 21.

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10(-11) to 5.0 × 10(-21)). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10(-6)). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.
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http://dx.doi.org/10.1038/ng.3405DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719169PMC
November 2015

Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study.

Lancet Diabetes Endocrinol 2015 Jul 18;3(7):526-534. Epub 2015 Jun 18.

​ (J C Chambers PhD, M Loh PhD, B Lehne PhD, W R Scott MRCP, W Zhang PhD, G Campanella MSc, M Chadeau-Hyam PhD, U Afzal MRCP, Prof P Froguel PhD, Prof P Vineis MD, Prof M-R Jarvelin PhD, Prof P Elliott PhD) (J C Chambers, Prof M-R Jarvelin, Prof P Elliott, Prof J S Kooner FRCP) (W R Scott, S-T Tan MRCP, Prof J Scott PhD, Prof J S Kooner) (J Abbott PhD) (J C Chambers, W Zhang, S-T Tan, U Afzal, Prof J S Kooner) (J C Chambers, P Punjabi FRCS, Prof J S Kooner) (M Loh) (C Blancher PhD) (A Drong PhD, Prof M I McCarthy MD) (Prof M I McCarthy) (J Kriebel PhD, S Wahl MSc, C Gieger PhD, H Grallert PhD) (C Gieger) (J Kriebel, S Wahl, C Gieger, B Thorand PhD, H Grallert) (H Prokisch PhD) (J Kriebel, S Wahl, B Thorand, H Grallert) (V Motta PhD, F Rota PhD, L Tarantini PhD, B Albetti PhD, Prof P A Bertazzi MD, V Bollati PhD) (Prof M Ala-Korpela PhD) (H R Elliott Dip Biol, R C Richmond BA, R Caiazzo PhD, T R Gaunt FRCP, Prof C L Relton PhD) (L Yengo PhD, Prof F Pattou PhD, R Caiazzo, S Cauchi PhD, Prof P Froguel) (L Yengo, S Cauchi, Prof P Froguel) (L Yengo, Prof F Pattou, S Cauchi, Prof P Froguel) (M Adamowicz-Brice PhD, Prof T J Aitman PhD) (K Bozaoglu PhD, R Caiazzo, J Jowett PhD) (Z Y Mok BSc, H K Ng BSc, M A Rozario BSc, R Soong PhD) (E-S Tai PhD) (E-S Tai) (Prof F Pattou) (H Prokisch) (Prof M Ala-Korpela, A J Kangas MSc, P Soininen PhD) (M Loh, Prof M-R Jarvelin) (Prof M-R Jarvelin) (Prof M Ala-Korpela, P Soininen) (Prof M-R Jarvelin) (Prof M Ala-Korpela) (Prof O Ammerpohl PhD) (Prof C Schafmayer MD) (Prof J Danesh FRCP) (Prof S de Lusignan PhD, Prof S Jones PhD) (Prof T Illig PhD) (S Jha MRCP) (A Kasturiratne MD, Prof A R Wickremasinghe PhD) (N Kato PhD) (N Kotea PhD) (S Kowlessur Dip Pub Health Admin) (J Pitkäniemi PhD) (Prof J Tuomilehto PhD) (J Pitkäniemi) (D Saleheen PhD) (D Saleheen) (D Saleheen) (E-S Tai) (Prof S A Kyrtopoulos PhD) (C Herder PhD) (C Herder) (Prof J Hampe MD) (R Soong) (Prof P Vineis) (Prof M I McCarthy).

Background: Indian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes.

Methods: We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10(-7). We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians.

Findings: 1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8-3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1-2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0·5% (SD 0·1) to 1·1% (0·2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1·09 (95% CI 1·07-1·11; p=1·3 × 10(-17)) for ABCG1, 0·94 (0·92-0·95; p=4·2 × 10(-11)) for PHOSPHO1, 0·94 (0·92-0·96; p=1·4 × 10(-9)) for SOCS3, 1·07 (1·04-1·09; p=2·1 × 10(-10)) for SREBF1, and 0·92 (0·90-0·94; p=1·2 × 10(-17)) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3·51, 95% CI 2·79-4·42; p=1·3 × 10(-26)), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 × 10(-34)).

Interpretation: DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians.

Funding: The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health.
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http://dx.doi.org/10.1016/S2213-8587(15)00127-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724884PMC
July 2015

Feasibility of low-throughput next generation sequencing for germline DNA screening.

Clin Chem 2014 Dec 22;60(12):1549-57. Epub 2014 Oct 22.

Cancer Science Institute of Singapore, National University of Singapore, Singapore; Department of Pathology, National University Health System, Singapore;

Background: Next generation sequencing (NGS) promises many benefits for clinical diagnostics. However, current barriers to its adoption include suboptimal amenability for low clinical throughputs and uncertainty over data accuracy and analytical procedures. We assessed the feasibility and performance of low-throughput NGS for detecting germline mutations for Lynch syndrome (LS).

Methods: Sequencing depth, time, and cost of 6 formats on the MiSeq and Personal Genome Machine platforms at 1-12 samples/run were calculated. Analytical performance was assessed from 3 runs of 3 DNA samples annotated for 7500 nucleotides by BeadChip arrays. The clinical performance of low-throughput NGS and 9 analytical processes were assessed through blinded analysis of DNA samples from 12 LS cases confirmed by Sanger sequencing, and 3 control cases.

Results: The feasibility analysis revealed different formats were optimal at different throughputs. Detection was reproducible for 2619/2635 (99.39%) replicate variants, and sensitivity and specificity to array annotation were 99.42% and 99.99% respectively. Eleven of 16 inconsistently detected variants could be specifically identified by having allele frequencies ≤ 0.15, strand biases >-35, or genotype quality scores ≤ 80. Positive selection for variants in the Human Genome Mutation Database (colorectal cancer, nonpolyposis) and variants with ≤ 5% frequency in the Asian population gave the best clinical performance (92% sensitivity, 67% specificity).

Conclusions: Low-throughput NGS can be a cost-efficient and reliable approach for screening germline variants; however, its clinical utility is subject to the quality of annotation of clinically relevant variants.
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http://dx.doi.org/10.1373/clinchem.2014.227728DOI Listing
December 2014

Association of maternal and nutrient supply line factors with DNA methylation at the imprinted IGF2/H19 locus in multiple tissues of newborn twins.

Epigenetics 2013 Oct 5;8(10):1069-79. Epub 2013 Aug 5.

Department of Paediatrics; University of Melbourne; Parkville, VIC Australia; Early Life Epigenetics Group; Murdoch Childrens Research Institute (MCRI); Royal Children's Hospital; Parkville, VIC Australia.

Epigenetic events are crucial for early development, but can be influenced by environmental factors, potentially programming the genome for later adverse health outcomes. The insulin-like growth factor 2 (IGF2)/H19 locus is crucial for prenatal growth and the epigenetic state at this locus is environmentally labile. Recent studies have implicated maternal factors, including folate intake and smoking, in the regulation of DNA methylation at this locus, although data are often conflicting in the direction and magnitude of effect. Most studies have focused on single tissues and on one or two differentially-methylated regions (DMRs) regulating IGF2/H19 expression. In this study, we investigated the relationship between multiple shared and non-shared gestational/maternal factors and DNA methylation at four IGF2/H19 DMRs in five newborn cell types from 67 pairs of monozygotic and 49 pairs of dizygotic twins. Data on maternal and non-shared supply line factors were collected during the second and third trimesters of pregnancy and DNA methylation was measured via mass spectrometry using Sequenom MassArray EpiTyper analysis. Our exploratory approach showed that the site of umbilical cord insertion into the placenta in monochorionic twins has the strongest positive association with methylation in all IGF2/H19 DMRs (p<0.05). Further, evidence for tissue- and locus-specific effects were observed, emphasizing that responsiveness to environmental exposures in utero cannot be generalized across genes and tissues, potentially accounting for the lack of consistency in previous findings. Such complexity in responsiveness to environmental exposures in utero has implications for all epigenetic studies investigating the developmental origins of health and disease.
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http://dx.doi.org/10.4161/epi.25908DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3891688PMC
October 2013

A distinct DNA methylation signature defines pediatric pre-B cell acute lymphoblastic leukemia.

Epigenetics 2012 Jun 1;7(6):535-41. Epub 2012 Jun 1.

Murdoch Childrens Research Institute, Department of Paediatrics, The University of Melbourne, Royal Children's Hospital, Melbourne, Victoria, Australia.

Pre-B cell acute lymphoblastic leukemia (ALL) is the most prevalent childhood malignancy and remains one of the highest causes of childhood mortality. Despite this, the mechanisms leading to disease remain poorly understood. We asked if recurrent aberrant DNA methylation plays a role in childhood ALL and have defined a genome-scale DNA methylation profile associated with the ETV6-RUNX1 subtype of pediatric ALL. Archival bone marrow smears from 19 children collected at diagnosis and remission were used to derive a disease specific DNA methylation profile. The gene signature was confirmed in an independent cohort of 86 patients. A further 163 patients were analyzed for DNA methylation of a three gene signature. We found that the DNA methylation signature at diagnosis was unique from remission. Fifteen loci were sufficient to discriminate leukemia from disease-free samples and purified CD34+ cells. DNA methylation of these loci was recurrent irrespective of cytogenetic subtype of pre-B cell ALL. We show that recurrent aberrant genomic methylation is a common feature of pre-B ALL, suggesting a shared pathway for disease development. By revealing new DNA methylation markers associated with disease, this study has identified putative targets for development of novel epigenetic-based therapies.
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http://dx.doi.org/10.4161/epi.20193DOI Listing
June 2012

DNA methylation analysis of multiple tissues from newborn twins reveals both genetic and intrauterine components to variation in the human neonatal epigenome.

Hum Mol Genet 2010 Nov 10;19(21):4176-88. Epub 2010 Aug 10.

Developmental Epigenetics, Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia.

Mounting evidence from both animal and human studies suggests that the epigenome is in constant drift over the life course in response to stochastic and environmental factors. In humans, this has been highlighted by a small number of studies that have demonstrated discordant DNA methylation patterns in adolescent or adult monozygotic (MZ) twin pairs. However, to date, it remains unclear when such differences emerge, and how prevalent they are across different tissues. To address this, we examined the methylation of four differentially methylated regions associated with the IGF2/H19 locus in multiple birth tissues derived from 91 twin pairs: 56 MZ and 35 dizygotic (DZ). Tissues included cord blood-derived mononuclear cells and granulocytes, human umbilical vein endothelial cells, buccal epithelial cells and placental tissue. Considerable variation in DNA methylation was observed between tissues and between unrelated individuals. Most interestingly, methylation discordance was also present within twin pairs, with DZ pairs showing greater discordance than MZ pairs. These data highlight the variable contribution of both intrauterine environmental exposures and underlying genetic factors to the establishment of the neonatal epigenome of different tissues and confirm the intrauterine period as a sensitive time for the establishment of epigenetic variability in humans. This has implications for the effects of maternal environment on the development of the newborn epigenome and supports an epigenetic mechanism for the previously described phenomenon of 'fetal programming' of disease risk.
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http://dx.doi.org/10.1093/hmg/ddq336DOI Listing
November 2010

DNA methylation-mediated down-regulation of DNA methyltransferase-1 (DNMT1) is coincident with, but not essential for, global hypomethylation in human placenta.

J Biol Chem 2010 Mar 13;285(13):9583-9593. Epub 2010 Jan 13.

Developmental Epigenetics, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria 3052, Australia. Electronic address:

The genome of extraembryonic tissue, such as the placenta, is hypomethylated relative to that in somatic tissues. However, the origin and role of this hypomethylation remains unclear. The DNA methyltransferases DNMT1, -3A, and -3B are the primary mediators of the establishment and maintenance of DNA methylation in mammals. In this study, we investigated promoter methylation-mediated epigenetic down-regulation of DNMT genes as a potential regulator of global methylation levels in placental tissue. Although DNMT3A and -3B promoters lack methylation in all somatic and extraembryonic tissues tested, we found specific hypermethylation of the maintenance DNA methyltransferase (DNMT1) gene and found hypomethylation of the DNMT3L gene in full term and first trimester placental tissues. Bisulfite DNA sequencing revealed monoallelic methylation of DNMT1, with no evidence of imprinting (parent of origin effect). In vitro reporter experiments confirmed that DNMT1 promoter methylation attenuates transcriptional activity in trophoblast cells. However, global hypomethylation in the absence of DNMT1 down-regulation is apparent in non-primate placentas and in vitro derived human cytotrophoblast stem cells, suggesting that DNMT1 down-regulation is not an absolute requirement for genomic hypomethylation in all instances. These data represent the first demonstration of methylation-mediated regulation of the DNMT1 gene in any system and demonstrate that the unique epigenome of the human placenta includes down-regulation of DNMT1 with concomitant hypomethylation of the DNMT3L gene. This strongly implicates epigenetic regulation of the DNMT gene family in the establishment of the unique epigenetic profile of extraembryonic tissue in humans.
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http://dx.doi.org/10.1074/jbc.M109.064956DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2843208PMC
March 2010

Placenta-specific methylation of the vitamin D 24-hydroxylase gene: implications for feedback autoregulation of active vitamin D levels at the fetomaternal interface.

J Biol Chem 2009 May 23;284(22):14838-48. Epub 2009 Feb 23.

Developmental Epigenetics, Murdoch Childrens Research Institute, Royal Children's Hospital, and Department of Paediatrics, University of Melbourne, Parkville, Victoria 3052, Australia.

Plasma concentrations of biologically active vitamin D (1,25-(OH)(2)D) are tightly controlled via feedback regulation of renal 1alpha-hydroxylase (CYP27B1; positive) and 24-hydroxylase (CYP24A1; catabolic) enzymes. In pregnancy, this regulation is uncoupled, and 1,25-(OH)(2)D levels are significantly elevated, suggesting a role in pregnancy progression. Epigenetic regulation of CYP27B1 and CYP24A1 has previously been described in cell and animal models, and despite emerging evidence for a critical role of epigenetics in placentation generally, little is known about the regulation of enzymes modulating vitamin D homeostasis at the fetomaternal interface. In this study, we investigated the methylation status of genes regulating vitamin D bioavailability and activity in the placenta. No methylation of the VDR (vitamin D receptor) and CYP27B1 genes was found in any placental tissues. In contrast, the CYP24A1 gene is methylated in human placenta, purified cytotrophoblasts, and primary and cultured chorionic villus sampling tissue. No methylation was detected in any somatic human tissue tested. Methylation was also evident in marmoset and mouse placental tissue. All three genes were hypermethylated in choriocarcinoma cell lines, highlighting the role of vitamin D deregulation in this cancer. Gene expression analysis confirmed a reduced capacity for CYP24A1 induction with promoter methylation in primary cells and in vitro reporter analysis demonstrated that promoter methylation directly down-regulates basal promoter activity and abolishes vitamin D-mediated feedback activation. This study strongly suggests that epigenetic decoupling of vitamin D feedback catabolism plays an important role in maximizing active vitamin D bioavailability at the fetomaternal interface.
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http://dx.doi.org/10.1074/jbc.M809542200DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2685665PMC
May 2009