Publications by authors named "Anunchai Assawamakin"

34 Publications

An Implementation Framework for Telemedicine to Address Noncommunicable Diseases in Thailand.

Asia Pac J Public Health 2021 Apr 19:10105395211008754. Epub 2021 Apr 19.

Thai Hypertension Society, Bangkok, Thailand.

To maintain the continuity of noncommunicable disease (NCD) services and ascertain the health outcomes of patients with NCDs during the COVID-19 (coronavirus disease 2019) outbreak in Thailand, various telemedicine services have been developed. To achieve this determination, the implementation framework has been constructed based on recommendations from multidisciplinary experts (Thai NCD Collaboration Group). Within the framework, all key elements are illustrated with their priority and expected collaborations. Ultimately, active collaborations from multi-stakeholders are vitally important to ensure that telemedicine services for NCDs will finally become practical, successful, and sustainable.
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http://dx.doi.org/10.1177/10105395211008754DOI Listing
April 2021

Bacterial communities on facial skin of teenage and elderly Thai females.

Arch Microbiol 2017 Sep 8;199(7):1035-1042. Epub 2017 Apr 8.

Genome Technology Research Unit, National Center for Genetic Engineering and Biotechnology, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand.

The Human Microbiome Project was first established to understand the roles of human-associated microbes to human health and disease. This study presents preliminary findings of Thai female facial skin microbiome using three pooled samples from groups of skin microbiome profiles, namely (1) healthy and (2) acne-prone young adults (teenage.hea and teenage.acn) and (3) healthy elderly adults (elderly.hea) based on standard dermatological criteria. These samples were sequenced using 454-pyrosequencing targeting 16S rRNA (V3-V4 regions). Good's coverage index of greater than 92% shows sufficient sampling of our data for each group. Three unique OTUs for each microbiome profile (43, 258 and 59 for teenage.hea, teenage.acn and ederly.hea, respectively) were obtained with 134 shared OTUs among the three datasets. Based on Morisita-Horn similarity coefficient, age is the major factor that brings the community relationship factor closer. The comparison among the three datasets reveal majority of Gemmatimonadetes, Planctomycetes and Nitrospirae in the teenage.hea, whereas Firmicutes are more prevalent in teenage.acn and elderly.hea skin types. In addition, when comparing Thai facial microbial diversity with the 16S data from U.S. forehead female database, significant differences were found among orders of bacteria, pointing to possible differences in human ecto-flora.
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http://dx.doi.org/10.1007/s00203-017-1375-0DOI Listing
September 2017

Genetic analysis of Thai cattle reveals a Southeast Asian indicine ancestry.

PeerJ 2015 27;3:e1318. Epub 2015 Oct 27.

Genome Technology Research Unit, National Center for Genetic Engineering and Biotechnology , Pathum Thani , Thailand.

Cattle commonly raised in Thailand have characteristics of Bos indicus (zebu). We do not know when or how cattle domestication in Thailand occurred, and so questions remain regarding their origins and relationships to other breeds. We obtained genome-wide SNP genotypic data of 28 bovine individuals sampled from four regions: North (Kho-Khaolampoon), Northeast (Kho-Isaan), Central (Kho-Lan) and South (Kho-Chon) Thailand. These regional varieties have distinctive traits suggestive of breed-like genetic variations. From these data, we confirmed that all four Thai varieties are Bos indicus and that they are distinct from other indicine breeds. Among these Thai cattle, a distinctive ancestry pattern is apparent, which is the purest within Kho-Chon individuals. This ancestral component is only present outside of Thailand among other indicine breeds in Southeast Asia. From this pattern, we conclude that a unique Bos indicus ancestor originated in Southeast Asia, and native Kho-Chon Thai cattle retain the signal of this ancestry with limited admixture of other bovine ancestors.
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http://dx.doi.org/10.7717/peerj.1318DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627918PMC
November 2015

iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure.

IEEE/ACM Trans Comput Biol Bioinform 2014 Sep-Oct;11(5):903-14

Understanding genetic differences among populations is one of the most important issues in population genetics. Genetic variations, e.g., single nucleotide polymorphisms, are used to characterize commonality and difference of individuals from various populations. This paper presents an efficient graph-based clustering framework which operates iteratively on the Neighbor-Joining (NJ) tree called the iNJclust algorithm. The framework uses well-known genetic measurements, namely the allele-sharing distance, the neighbor-joining tree, and the fixation index. The behavior of the fixation index is utilized in the algorithm's stopping criterion. The algorithm provides an estimated number of populations, individual assignments, and relationships between populations as outputs. The clustering result is reported in the form of a binary tree, whose terminal nodes represent the final inferred populations and the tree structure preserves the genetic relationships among them. The clustering performance and the robustness of the proposed algorithm are tested extensively using simulated and real data sets from bovine, sheep, and human populations. The result indicates that the number of populations within each data set is reasonably estimated, the individual assignment is robust, and the structure of the inferred population tree corresponds to the intrinsic relationships among populations within the data.
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http://dx.doi.org/10.1109/TCBB.2014.2322372DOI Listing
March 2016

HLA-DRB1 and HLA-DQB1 Are Associated with Adult-Onset Immunodeficiency with Acquired Anti-Interferon-Gamma Autoantibodies.

PLoS One 2015 26;10(5):e0128481. Epub 2015 May 26.

Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

Recently a newly identified clinical syndrome of disseminated non-tuberculous mycobacterial diseases (with or without other opportunistic infections in adult patients who were previously healthy, has been recognized in association with an acquired autoantibody to interferon-gamma. This syndrome is emerging as an important cause of morbidity and mortality, especially among people of Asian descent. Trigger for the production of this autoantibody remains unknown, but genetic factors are strongly suspected to be involved. We compared HLA genotyping between 32 patients with this clinical syndrome, and 38 controls. We found that this clinical syndrome was associated with very limited allele polymorphism, with HLA-DRB1 and DQB1 alleles, especially HLA-DRB1*15:01, DRB1*16:02, DQB1*05:01 and DQB1*05:02. Odds ratio of DRB1*15:01, DRB1*16:02, DQB1*05:01 and DQB1*05:02 were 7.03 (95% CI, 2.18-22.69, P<0.0001, 9.06 (95% CI, 2.79-29.46, P<0.0001), 6.68 (95% CI, 2.29-19.52, P = 0.0004), and 6.64 (95% CI, 2.30-19.20, P = 0.0004), respectively. Further investigation is warranted to provide better understanding on pathogenesis of this association.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128481PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4444022PMC
April 2016

Mycophenolic acid AUC in Thai kidney transplant recipients receiving low dose mycophenolate and its association with UGT2B7 polymorphisms.

Pharmgenomics Pers Med 2014 5;7:379-85. Epub 2014 Dec 5.

Division of Nephrology, Department of Medicine, Mahidol University, Bangkok, Thailand.

Background: Despite use of a lower mycophenolate dose in Thai kidney transplant patients, acceptable graft and patient outcomes can be achieved. We therefore examined the pharmacokinetics of mycophenolic acid (MPA) by area under the curve (AUC) and investigated genetic contribution in mycophenolate metabolism in this population.

Methods: Kidney transplant recipients with stable graft function who were receiving mycophenolate mofetil 1,000 mg/d in combination with either cyclosporine or tacrolimus, and prednisolone were studied. The MPA concentration was measured by fluorescence polarization immunoassay (FPIA), at predose and 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after dosing. Genetic polymorphisms in UGT1A8, UGT1A9, and UGT2B7 were examined by denaturing high-performance liquid chromatography (DHPLC)-based single-base extension (SBE) analysis.

Results: A total 138 patients were included in study. The mean AUC was 39.49 mg-h/L (28.39-89.58 mg-h/L), which was in the therapeutic range. The correlation between the predose MPA concentration and AUC was poor. The mean AUC in the tacrolimus group was higher than that in the cyclosporine group. Polymorphisms in UGT2B7 showed significant association with AUC.

Conclusion: Most of our patients with reduced mycophenolate dose had the AUC within the therapeutic range. Genetic polymorphisms in UGT2B7 may play a role in MPA metabolism in Thai kidney transplant patients.
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http://dx.doi.org/10.2147/PGPM.S72760DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4270037PMC
December 2014

Structural and functional diversity of free-living microorganisms in reef surface, Kra island, Thailand.

BMC Genomics 2014 Jul 18;15:607. Epub 2014 Jul 18.

Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.

Background: Coral reefs worldwide are being harmed through anthropogenic activities. Some coral reefs in Thailand remain well-preserved, including the shallow coral reefs along Kra island, Nakhon Si Thammarat province. Interestingly, the microbial community in this environment remains unknown. The present study identified biodiversity of prokaryotes and eukaryotes of 0.22-30 μm in sizes and their metabolic potentials in this coral reef surface in summer and winter seasons, using 16S and 18S rRNA genes pyrosequencing.

Results: The marine microbial profiles in summer and winter seasons comprised mainly of bacteria, in phylum, particular the Proteobacteria. Yet, different bacterial and eukaryotic structures existed between summer and winter seasons, supported by low Lennon and Yue & Clayton theta similarity indices (8.48-10.43% for 16S rRNA, 0.32-7.81% for 18S rRNA ). The topmost prokaryotic phylum for the summer was Proteobacteria (99.68%), while for the winter Proteobacteria (62.49%) and Bacteroidetes (35.88%) were the most prevalent. Uncultured bacteria in phyla Cyanobacteria, Planctomycetes, SAR406 and SBR1093 were absent in the summer. For eukaryotic profiles, species belonging to animals predominated in the summer, correlating with high animal activities in the summer, whereas dormancy and sporulation predominated in the winter. For the winter, eukaryotic plant species predominated and several diverse species were detected. Moreover, comparison of our prokaryotic databases in summer and winter of Kra reef surface against worldwide marine culture-independent prokaryotic databases indicated our databases to most resemblance those of coastal Sichang island, Chonburi province, Thailand, and the 3 tropical GOS sites close to Galapagos island (GS039, GS040 and GS045), in orderly.

Conclusions: The study investigated and obtained culture-independent databases for marine prokaryotes and eukaryotes in summer and winter seasons of Kra reef surface. The data helped understand seasonal dynamics of microbial structures and metabolic potentials of this tropical ecosystem, supporting the knowledge of the world marine microbial biodiversity.
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http://dx.doi.org/10.1186/1471-2164-15-607DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4223561PMC
July 2014

Microbial ecology of Thailand tsunami and non-tsunami affected terrestrials.

PLoS One 2014 7;9(4):e94236. Epub 2014 Apr 7.

Genome Institute, National Center for Genetic Engineering and Biotechnology, Pathumthani, Thailand.

The effects of tsunamis on microbial ecologies have been ill-defined, especially in Phang Nga province, Thailand. This ecosystem was catastrophically impacted by the 2004 Indian Ocean tsunami as well as the 600 year-old tsunami in Phra Thong island, Phang Nga province. No study has been conducted to elucidate their effects on microbial ecology. This study represents the first to elucidate their effects on microbial ecology. We utilized metagenomics with 16S and 18S rDNA-barcoded pyrosequencing to obtain prokaryotic and eukaryotic profiles for this terrestrial site, tsunami affected (S1), as well as a parallel unaffected terrestrial site, non-tsunami affected (S2). S1 demonstrated unique microbial community patterns than S2. The dendrogram constructed using the prokaryotic profiles supported the unique S1 microbial communities. S1 contained more proportions of archaea and bacteria domains, specifically species belonging to Bacteroidetes became more frequent, in replacing of the other typical floras like Proteobacteria, Acidobacteria and Basidiomycota. Pathogenic microbes, including Acinetobacter haemolyticus, Flavobacterium spp. and Photobacterium spp., were also found frequently in S1. Furthermore, different metabolic potentials highlighted this microbial community change could impact the functional ecology of the site. Moreover, the habitat prediction based on percent of species indicators for marine, brackish, freshwater and terrestrial niches pointed the S1 to largely comprise marine habitat indicating-species.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0094236PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978030PMC
December 2014

Population structure of four Thai indigenous chicken breeds.

BMC Genet 2014 Mar 27;15:40. Epub 2014 Mar 27.

Department of Animal and Aquatic Sciences, Faculty of Agriculture, Chiang Mai University, Chiang Mai 50200, Thailand.

Background: In recent years, Thai indigenous chickens have increasingly been bred as an alternative in Thailand poultry market. Due to their popularity, there is a clear need to improve the underlying quality and productivity of these chickens. Studying chicken genetic variation can improve the chicken meat quality as well as conserving rare chicken species. To begin with, a minimal set of molecular markers that can characterize the Thai indigenous chicken breeds is required.

Results: Using AFLP-PCR, 30 single nucleotide polymorphisms (SNPs) from Thai indigenous chickens were obtained by DNA sequencing. From these SNPs, we genotyped 465 chickens from 7 chicken breeds, comprising four Thai indigenous chicken breeds--Pradhuhangdum (PD), Luenghangkhao (LK), Dang (DA) and Chee (CH), one wild chicken--the red jungle fowls (RJF), and two commercial chicken breeds--the brown egg layer (BL) and commercial broiler (CB). The chicken genotypes reveal unique genetic structures of the four Thai indigenous chicken breeds. The average expected heterozygosities of PD=0.341, LK=0.357, DA=0.349 and CH=0.373, while the references RJF= 0.327, CB=0.324 and BL= 0.285. The F(ST) values among Thai indigenous chicken breeds vary from 0.051 to 0.096. The F(ST) values between the pairs of Thai indigenous chickens and RJF vary from 0.083 to 0.105 and the FST values between the Thai indigenous chickens and the two commercial chicken breeds vary from 0.116 to 0.221. A neighbour-joining tree of all individual chickens showed that the Thai indigenous chickens were clustered into four groups which were closely related to the wild RJF but far from the commercial breeds. Such commercial breeds were split into two closely groups. Using genetic admixture analysis, we observed that the Thai indigenous chicken breeds are likely to share common ancestors with the RJF, while both commercial chicken breeds share the same admixture pattern.

Conclusion: These results indicated that the Thai indigenous chicken breeds may descend from the same ancestors. These indigenous chicken breeds were more closely related to red jungle fowls than those of the commercial breeds. These findings showed that the proposed SNP panel can effectively be used to characterize the four Thai indigenous chickens.
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http://dx.doi.org/10.1186/1471-2156-15-40DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986817PMC
March 2014

MetaSel: a metaphase selection tool using a Gaussian-based classification technique.

BMC Bioinformatics 2013 22;14 Suppl 16:S13. Epub 2013 Oct 22.

Background: Identification of good metaphase spreads is an important step in chromosome analysis for identifying individuals with genetic disorders. The process of finding suitable metaphase chromosomes for accurate clinical analysis is, however, very time consuming since they are selected manually. The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. Although many algorithms have been developed for karyotyping, none have adequately addressed the critical bottleneck of selecting suitable chromosome spreads. In this paper, we present a software tool that uses a simple rule-based system to efficiently identify metaphase spreads suitable for karyotyping.

Results: The chromosome shapes can be classified by the software into four main classes. The first and the second classes refer to individual chromosomes with straight and skewed shapes, respectively. The third class is characterized as those chromosomes with overlapping bodies and the fourth class is for the non-chromosome objects. Good metaphase spreads should largely contain chromosomes of the first and the second classes, while the third class should be kept minimal. Several image parameters were examined and used for creating rule-based classification. The threshold value for each parameter is determined using a statistical model. We observed that the Gaussian model can represent the empirical probability density function of the parameters and, hence, the threshold value can be easily determined. The proposed rules can efficiently and accurately classify the individual chromosome with > 90% accuracy.

Conclusions: The software tool, termed MetaSel, was developed. Using the Gaussian-based rules, the tool can be used to quickly rank hundreds of chromosome spread images so as to assist cytogeneticists to perform karyotyping effectively. Furthermore, MetaSel offers an intuitive, yet comprehensive, workflow to assist karyotyping, including tools for editing chromosome (split, merge and fix) and a karyotyping editor (moving, rotating, and pairing homologous chromosomes). The program can be freely downloaded from "http://www4a.biotec.or.th/GI/tools/metasel".
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http://dx.doi.org/10.1186/1471-2105-14-S16-S13DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015449PMC
April 2014

How bio-questionable are the different recombinant human erythropoietin copy products in Thailand?

Pharm Res 2014 May 21;31(5):1210-8. Epub 2013 Nov 21.

Department of Pharmaceutics Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.

Purpose: The high prevalence of pure red cell aplasia in Thailand has been associated with the sharp increase in number of recombinant human erythropoietin (rhEPO) copy products, based on a classical generic regulatory pathway, which have entered the market. This study aims to assess the quality of rhEPO copy products being used in Thailand.

Methods: Twelve rhEPO copy products were purchased from pharmacies in Thailand, shipped under controlled cold chain conditions to the Netherlands and characterized using (1) high performance size-exclusion chromatography, (2) asymmetrical flow field-flow fractionation, (3) sodium dodecyl sulfate polyacrylamide gel electrophoresis in combination with (4) Western blotting and additionally tested for (5) host cell protein impurities as well as (6) endotoxin contamination.

Results: Some of the tested rhEPO copy products showed high aggregate levels and contained a substantial amount of protein fragments. Also, one of rhEPO copy products had a high endotoxin level, exceeding the FDA limit.

Conclusions: Our observations show that some of the tested copy products on the Thai market differ significantly from the originator rhEPO product, Epogen®. This comparison study supports a link between the quality attributes of copy rhEPO products and their immunogenicity.
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http://dx.doi.org/10.1007/s11095-013-1243-9DOI Listing
May 2014

Insight into the peopling of Mainland Southeast Asia from Thai population genetic structure.

PLoS One 2013 4;8(11):e79522. Epub 2013 Nov 4.

National Center for Genetic Engineering and Biotechnology (BioTeC), Khlong Luang, Pathum Thani, Thailand ; Inter-Department Program of Biomedical Sciences, Chulalongkorn University, Pathumwan, Bangkok, Thailand.

There is considerable ethno-linguistic and genetic variation among human populations in Asia, although tracing the origins of this diversity is complicated by migration events. Thailand is at the center of Mainland Southeast Asia (MSEA), a region within Asia that has not been extensively studied. Genetic substructure may exist in the Thai population, since waves of migration from southern China throughout its recent history may have contributed to substantial gene flow. Autosomal SNP data were collated for 438,503 markers from 992 Thai individuals. Using the available self-reported regional origin, four Thai subpopulations genetically distinct from each other and from other Asian populations were resolved by Neighbor-Joining analysis using a 41,569 marker subset. Using an independent Principal Components-based unsupervised clustering approach, four major MSEA subpopulations were resolved in which regional bias was apparent. A major ancestry component was common to these MSEA subpopulations and distinguishes them from other Asian subpopulations. On the other hand, these MSEA subpopulations were admixed with other ancestries, in particular one shared with Chinese. Subpopulation clustering using only Thai individuals and the complete marker set resolved four subpopulations, which are distributed differently across Thailand. A Sino-Thai subpopulation was concentrated in the Central region of Thailand, although this constituted a minority in an otherwise diverse region. Among the most highly differentiated markers which distinguish the Thai subpopulations, several map to regions known to affect phenotypic traits such as skin pigmentation and susceptibility to common diseases. The subpopulation patterns elucidated have important implications for evolutionary and medical genetics. The subpopulation structure within Thailand may reflect the contributions of different migrants throughout the history of MSEA. The information will also be important for genetic association studies to account for population-structure confounding effects.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0079522PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3817124PMC
August 2014

Biomarker selection and classification of "-omics" data using a two-step bayes classification framework.

Biomed Res Int 2013 11;2013:148014. Epub 2013 Sep 11.

Department of Pharmacology, Faculty of Pharmacy, Mahidol University, 447 Sri-Ayuthaya Road, Rajathevi, Bangkok 10400, Thailand.

Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray), and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.
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http://dx.doi.org/10.1155/2013/148014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3784073PMC
June 2014

Distal effect of amino acid substitutions in CYP2C9 polymorphic variants causes differences in interatomic interactions against (S)-warfarin.

PLoS One 2013 2;8(9):e74053. Epub 2013 Sep 2.

Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand ; Genomics Institute, National Center for Genetic Engineering and Biotechnology, Pathumtani, Thailand ; Department of Microbiology, University of Washington, Seattle, Washington, United States of America.

Cytochrome P450 2C9 (CYP2C9) is crucial in excretion of commonly prescribed drugs. However, changes in metabolic activity caused by CYP2C9 polymorphisms inevitably result in adverse drug effects. CYP2C9*2 and *3 are prevalent in Caucasian populations whereas CYP2C9*13 is remarkable in Asian populations. Single amino acid substitutions caused by these mutations are located outside catalytic cavity but affect kinetic activities of mutants compared to wild-type enzyme. To relate distal effects of these mutations and defective drug metabolisms, simulations of CYP2C9 binding to anti-coagulant (S)-warfarin were performed as a system model. Representative (S)-warfarin-bound forms of wild-type and mutants were sorted and assessed through knowledge-based scoring function. Interatomic interactions towards (S)-warfarin were predicted to be less favorable in mutant structures in correlation with larger distance between hydroxylation site of (S)-warfarin and reactive oxyferryl heme than wild-type structure. Using computational approach could delineate complication of CYP polymorphism in management of drug therapy.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0074053PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3759441PMC
April 2014

Small Ancestry Informative Marker panels for complete classification between the original four HapMap populations.

Int J Data Min Bioinform 2012 ;6(6):651-74

Department of Electrical Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, 1518 Piboolsongkram Road, Bangsue, Bangkok 10800, Thailand.

A protocol for the identification of Ancestry Informative Markers (AIMs) from genome-wide Single Nucleotide Polymorphism (SNP) data is proposed. The protocol consists of three main steps: identification of potential positive selection regions via F(ST) extremity measurement, SNP screening via two-stage attribute selection and classification model construction using a Naïve Bayes classifier. The two-stage attribute selection is composed of a newly developed round robin Symmetrical Uncertainty (SU) ranking technique and a wrapper embedded with a Naïve Bayes classifier. The protocol has been applied to the HapMap Phase II data. Two AIM panels, which consist of 10 and 16 SNPs that lead to complete classification between CEU, CHB, JPT and YRI populations, are identified. Moreover, the panels are at least four times smaller than those reported in previous studies. The results suggest that the protocol could be useful in a scenario involving a larger number of populations.
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http://dx.doi.org/10.1504/ijdmb.2012.050249DOI Listing
April 2013

Metagenomic profiles of free-living archaea, bacteria and small eukaryotes in coastal areas of Sichang island, Thailand.

BMC Genomics 2012 13;13 Suppl 7:S29. Epub 2012 Dec 13.

Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.

Background: Tha Wang and Tham Phang coasts, though situated at similar oceanographic positions on Sichang island, Chonburi province, Thailand, are different in bay geography and amount of municipal disturbances. These affect the marine ecosystems. The study used metagenomics combined with 16S and 18S rDNA pyrosequencing to identify types and distributions of archaea, bacteria, fungi and small eukaryotes of sizes ranges 0.45 and ~30 μm.

Results: Following the open bay geography and minimal municipal sewages, Tham Phang coast showed the cleaner water properties, described by color, salinity, pH, conductivity and percent dissolved oxygen. The 16S and 18S rDNA metagenomic profiles for Tha Wang and Tham Phang coasts revealed many differences, highlighting by low Lennon and Yue & Clayton theta similarity indices (66.03-73.03% for 16S rDNA profiles, 2.85-25.38% for 18S rDNA profiles). For 16S rDNA, the percent compositions of species belonging to Proteobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, Verrucomicrobia, Gammatimonadetes, Tenericutes, Acidobacteria, Spirochaetes, Chlamydiae, Euryarchaeota, Nitrospirae, Planctomycetes, Thermotogae and Aquificae were higher or distinctly present in Tha Wang. In Tham Phang, except Actinobacteria, the fewer number of prokaryotic species existed. For 18S rDNA, fungi represented 74.745% of the species in Tha Wang, whereas only 6.728% in Tham Phang. Basidiomycota (71.157%) and Ascomycota (3.060%) were the major phyla in Tha Wang. Indeed, Tha Wang-to-Tham Phang percent composition ratios for fungi Basidiomycota and Chytridiomycota were 1264.701 and 25.422, respectively. In Tham Phang, Brachiopoda (lamp shells) and Mollusca (snails) accounted for 80.380% of the 18S rDNA species detected, and their proportions were approximately tenfold greater than those in Tha Wang. Overall, coastal Tham Phang comprised abundant animal species.

Conclusions: Tha Wang contained numerous archaea, bacteria and fungi, many of which could synthesize useful biotechnology gas and enzymes that could also function in high-saline and high-temperature conditions. Tham Phang contained less abundant archaea, bacteria and fungi, and the majority of the extracted metagenomes belonged to animal kingdom. Many microorganisms in Tham Phang were essential for nutrient-recycling and pharmaceuticals, for instances, Streptomyces, Pennicilium and Saccharomyces. Together, the study provided metagenomic profiles of free-living prokaryotes and eukaryotes in coastal areas of Sichang island.
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http://dx.doi.org/10.1186/1471-2164-13-S7-S29DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521234PMC
June 2013

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies.

BMC Genomics 2012 13;13 Suppl 7:S2. Epub 2012 Dec 13.

National Center for Genetic Engineering and Biotechnology, Pathumthani, 12120, Thailand.

Background: Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD).

Results: In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles.

Conclusion: iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci.
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http://dx.doi.org/10.1186/1471-2164-13-S7-S2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521387PMC
June 2013

Molecular dynamics simulations reveal structural instability of human trypsin inhibitor upon D50E and Y54H mutations.

J Mol Model 2013 Feb 7;19(2):521-8. Epub 2012 Sep 7.

National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand.

Serine protease inhibitor Kazal type 1 (SPINK1) plays an important role in protecting the pancreas against premature trypsinogen activation that causes pancreatitis. Various mutations in the SPINK1 gene were shown to be associated with patients with pancreatitis. Recent transfection studies identified intracellular folding defects, probably caused by mutation induced misfolding of D50E and Y54H mutations, as a common mechanism that reduces SPINK1 secretion and as a possible novel mechanism of SPINK1 deficiency associated with chronic pancreatitis. Using molecular dynamics, we investigated the effects of D50E and Y54H mutations on SPINK1 dynamics and conformation at 300 K. We found that the structures of D50E and Y54H mutants were less stable than and were distorted from those of the wild type, as indicated by the RMSD plots, RMSF plots and DSSP series. Specifically, unwinding of the top of helices (the main secondary structures) and the distortion of the loops above the helices were observed. It may be possible that this distorted protein structure may be recognized as "non-native" by members of the chaperone family; it may be further retained and targeted for degradation, leading to SPINK1 secretion reduction and subsequently pancreatitis in patients as Király et al. (Gut 56:1433, 2007) proposed.
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http://dx.doi.org/10.1007/s00894-012-1565-2DOI Listing
February 2013

An abundance of population-specific monomorphic SNPs may or may not be meaningful: a commentary on differences in allele frequencies of familial hypercholesterolemia SNPs in the Malaysian population.

J Hum Genet 2012 Jul 31;57(7):403-4. Epub 2012 May 31.

The Department of Research and Development, Division of Molecular Genetics, Mahidol University, Bangkok, Thailand.

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http://dx.doi.org/10.1038/jhg.2012.52DOI Listing
July 2012

A novel maternally-derived insertional translocation resulting in partial trisomy 4q13.2-q22.1 with complex translocation t(8;20) in a family with intellectual disability.

Am J Med Genet A 2012 Apr 14;158A(4):901-8. Epub 2012 Mar 14.

Department of Immunology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand.

We characterized the chromosomal aberration in family with intellectual disability, including two affected children and their affected mother. Initial standard karyotypes of the three individuals showed an apparently balanced translocation of chromosomes 8 and 20. Using molecular cytogenetic techniques, we observed complex structural chromosomal aberration comprising of reciprocal translocation between chromosomes 8 and 20 with pericentric inversion (8p11.12q22.3) and insertion of chromosome 4 segments into both der(8) and der(20). In particular, the insertion of chromosome 4 was complex. Two segments (4q13.2-q13.3 and 4q21.21-q22.1) were inserted into the der(8)t(8;20) breakpoint and one segment (4q13.3-q21.21) into the der(20)t(8;20) breakpoint. Both children inherited two normal chromosomes 4 from their parents and the der(8) and der(20) from the mother, resulting in partial trisomy of 4q13.2-q22.1. Interestingly, the mother, in addition to the same complex insertions and inversion, was founded to have a deletion of 4q13.2-q22.1 in one of her chromosomes 4, yielding no genetic imbalance but with potential disruption of intellectual dysfunction-related gene(s) at the breakpoints as the cause of her intellectual impairment. This family is the third case report of an insertional translocation mechanism causing partial trisomy 4q syndrome. Our study demonstrates that an insertion of an extra chromosomal segment, not primarily involving in translocation breakpoints, which results in partial trisomy, can be an unapparent cause of the abnormal phenotypes.
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http://dx.doi.org/10.1002/ajmg.a.35259DOI Listing
April 2012

Comparative view of in silico DNA sequencing analysis tools.

Methods Mol Biol 2011 ;760:207-21

National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Pahonyothin Road, Klong 1, Klong Luang, 12120, Pathum Thani, Thailand.

DNA sequencing is an important tool for discovery of genetic variants. The task of detecting single-nucleotide variants is complicated by noise and sequencing artifacts in sequencing data. Several in silico tools have been developed to assist this process. These tools interpret the raw chromatogram data and perform a specialized base-calling and quality-control assessment procedure to identify variants. The approach used to identify variants differs between the tools, with some specific to SNPs and other for Indels. The choice of a tool is guided by the design of the sequencing project and the nature of the variant to be discovered. In this chapter, these tools are compared to facilitate the choice of a tool used for variant discovery.
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http://dx.doi.org/10.1007/978-1-61779-176-5_13DOI Listing
November 2011

Combination of multiplex PCR and DHPLC-based strategy for CYP2D6 genotyping scheme in Thais.

Clin Biochem 2011 Sep 6;44(13):1144-1152. Epub 2011 Jul 6.

Division of Molecular Genetics, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok 10700, Thailand. Electronic address:

Objective: To develop CYP2D6 genotyping scheme for accurate allele calling and reliable estimation of functional allele dosage in Thais.

Design And Methods: We analyzed CYP2D6 copy numbers by pentaplex PCR coupled with semi-quantitative denaturing high performance liquid chromatography (DHPLC)-based technique. Ten common SNPs were genotyped from CYP2D6 gene product using single base extension (SBE) followed by DHPLC analysis. This detection scheme was compared with real-time PCR and conventional PCR-RFLP for cost-effectiveness.

Results: The distribution of CYP2D6 gene copy numbers in our population ranged from zero (0.69%), one (7.99%), two (60.07%), three (28.13%) and four (3.13%). The most commonly detected SNPs were related to CYP2D6*10 haplotype. CYP2D6*36 in tandem with CYP2D6*10B is the major rearrangement type in Thais (18.75%).

Conclusions: Multiplex PCR coupled with DHPLC-based strategy is convenient and reliable method for CYP2D6 genotyping offering sufficient allele coverage for Asians. Both cost and analytical time saving were shown and the method could potentially be modified to accommodate CYP2D6 genotyping in other ethnics.
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http://dx.doi.org/10.1016/j.clinbiochem.2011.06.985DOI Listing
September 2011

PanSNPdb: the Pan-Asian SNP genotyping database.

PLoS One 2011 23;6(6):e21451. Epub 2011 Jun 23.

National Center for Genetic Engineering and Biotechnology (BIOTEC), Klong Luang, Pathumthani, Thailand.

The HUGO Pan-Asian SNP consortium conducted the largest survey to date of human genetic diversity among Asians by sampling 1,719 unrelated individuals among 71 populations from China, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand. We have constructed a database (PanSNPdb), which contains these data and various new analyses of them. PanSNPdb is a research resource in the analysis of the population structure of Asian peoples, including linkage disequilibrium patterns, haplotype distributions, and copy number variations. Furthermore, PanSNPdb provides an interactive comparison with other SNP and CNV databases, including HapMap3, JSNP, dbSNP and DGV and thus provides a comprehensive resource of human genetic diversity. The information is accessible via a widely accepted graphical interface used in many genetic variation databases. Unrestricted access to PanSNPdb and any associated files is available at: http://www4a.biotec.or.th/PASNP.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0021451PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3121791PMC
November 2011

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

BMC Bioinformatics 2011 Jun 23;12:255. Epub 2011 Jun 23.

Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.

Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis.

Results: A new heuristic called EigenDev for detecting population structure is presented. When tested on simulated data, this heuristic is robust to sample size. In contrast, the TW statistic was found to be susceptible to type I error, especially for large population samples. EigenDev is thus better-suited for analysis of large datasets containing many individuals, in which spurious patterns are likely to exist and could be incorrectly interpreted as population stratification. EigenDev was applied to the iterative pruning PCA (ipPCA) method, which resolves the underlying subpopulations. This subpopulation information was used to supervise STRUCTURE analysis to infer patterns of ancestry at an unprecedented level of resolution. To validate the new approach, a bovine and a large human genetic dataset (3945 individuals) were analyzed. We found new ancestry patterns consistent with the subpopulations resolved by ipPCA.

Conclusions: The EigenDev heuristic is robust to sampling and is thus superior for detecting structure in large datasets. The application of EigenDev to the ipPCA algorithm improves the estimation of the number of subpopulations and the individual assignment accuracy, especially for very large and complex datasets. Furthermore, we have demonstrated that the structure resolved by this approach complements parametric analysis, allowing a much more comprehensive account of population structure. The new version of the ipPCA software with EigenDev incorporated can be downloaded from http://www4a.biotec.or.th/GI/tools/ippca.
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http://dx.doi.org/10.1186/1471-2105-12-255DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3148578PMC
June 2011

RExPrimer: an integrated primer designing tool increases PCR effectiveness by avoiding 3' SNP-in-primer and mis-priming from structural variation.

BMC Genomics 2009 Dec 3;10 Suppl 3:S4. Epub 2009 Dec 3.

Genome Institute, National Center for Genetic Engineering and Biotechnology, Pathumthani, Thailand.

Background: Polymerase chain reaction (PCR) is very useful in many areas of molecular biology research. It is commonly observed that PCR success is critically dependent on design of an effective primer pair. Current tools for primer design do not adequately address the problem of PCR failure due to mis-priming on target-related sequences and structural variations in the genome.

Methods: We have developed an integrated graphical web-based application for primer design, called RExPrimer, which was written in Python language. The software uses Primer3 as the primer designing core algorithm. Locally stored sequence information and genomic variant information were hosted on MySQLv5.0 and were incorporated into RExPrimer.

Results: RExPrimer provides many functionalities for improved PCR primer design. Several databases, namely annotated human SNP databases, insertion/deletion (indel) polymorphisms database, pseudogene database, and structural genomic variation databases were integrated into RExPrimer, enabling an effective without-leaving-the-website validation of the resulting primers. By incorporating these databases, the primers reported by RExPrimer avoid mis-priming to related sequences (e.g. pseudogene, segmental duplication) as well as possible PCR failure because of structural polymorphisms (SNP, indel, and copy number variation (CNV)). To prevent mismatching caused by unexpected SNPs in the designed primers, in particular the 3' end (SNP-in-Primer), several SNP databases covering the broad range of population-specific SNP information are utilized to report SNPs present in the primer sequences. Population-specific SNP information also helps customize primer design for a specific population. Furthermore, RExPrimer offers a graphical user-friendly interface through the use of scalable vector graphic image that intuitively presents resulting primers along with the corresponding gene structure. In this study, we demonstrated the program effectiveness in successfully generating primers for strong homologous sequences.

Conclusion: The improvements for primer design incorporated into RExPrimer were demonstrated to be effective in designing primers for challenging PCR experiments. Integration of SNP and structural variation databases allows for robust primer design for a variety of PCR applications, irrespective of the sequence complexity in the region of interest. This software is freely available at http://www4a.biotec.or.th/rexprimer.
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http://dx.doi.org/10.1186/1471-2164-10-S3-S4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788391PMC
December 2009

Mapping human genetic diversity in Asia.

Science 2009 Dec;326(5959):1541-5

Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.
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http://dx.doi.org/10.1126/science.1177074DOI Listing
December 2009

Iterative pruning PCA improves resolution of highly structured populations.

BMC Bioinformatics 2009 Nov 23;10:382. Epub 2009 Nov 23.

BIOTEC 113 Thailand Science Park, Paholyothin Road, Klong 1, Klong Luang, Pathumtani 12120, Thailand.

Background: Non-random patterns of genetic variation exist among individuals in a population owing to a variety of evolutionary factors. Therefore, populations are structured into genetically distinct subpopulations. As genotypic datasets become ever larger, it is increasingly difficult to correctly estimate the number of subpopulations and assign individuals to them. The computationally efficient non-parametric, chiefly Principal Components Analysis (PCA)-based methods are thus becoming increasingly relied upon for population structure analysis. Current PCA-based methods can accurately detect structure; however, the accuracy in resolving subpopulations and assigning individuals to them is wanting. When subpopulations are closely related to one another, they overlap in PCA space and appear as a conglomerate. This problem is exacerbated when some subpopulations in the dataset are genetically far removed from others. We propose a novel PCA-based framework which addresses this shortcoming.

Results: A novel population structure analysis algorithm called iterative pruning PCA (ipPCA) was developed which assigns individuals to subpopulations and infers the total number of subpopulations present. Genotypic data from simulated and real population datasets with different degrees of structure were analyzed. For datasets with simple structures, the subpopulation assignments of individuals made by ipPCA were largely consistent with the STRUCTURE, BAPS and AWclust algorithms. On the other hand, highly structured populations containing many closely related subpopulations could be accurately resolved only by ipPCA, and not by other methods.

Conclusion: The algorithm is computationally efficient and not constrained by the dataset complexity. This systematic subpopulation assignment approach removes the need for prior population labels, which could be advantageous when cryptic stratification is encountered in datasets containing individuals otherwise assumed to belong to a homogenous population.
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http://dx.doi.org/10.1186/1471-2105-10-382DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2790469PMC
November 2009

pHCR: a parallel haplotype configuration reduction algorithm for haplotype interaction analysis.

J Hum Genet 2009 Nov 20;54(11):634-41. Epub 2009 Nov 20.

Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

Finding gene interaction models is one of the most important issues in genotype-phenotype association studies. This paper presents a model-free nonparametric statistical interaction analysis known as Parallel Haplotype Configuration Reduction (pHCR). This technique extends the original Multifactor Dimensionality Reduction (MDR) algorithm by using haplotype contribution values (c-values) and a haplotype interaction scheme instead of analyzing interactions among single-nucleotide polymorphisms. The proposed algorithm uses the statistical power of haplotypes to obtain a gene-gene interaction model. pHCR computes a statistical value for each haplotype, which contributes to the phenotype, and then performs haplotype interaction analysis on the basis of the cumulative c-value of each individual haplotype. To address the high computational complexity of pHCR, this paper also presents a scalable parallel computing solution. Nine common two-locus disease models were used to evaluate the algorithm performance under different scenarios. The results from all cases showed that pHCR shows higher power to detect gene-gene interaction in comparison with the results obtained from running MDR on the same data set. We also compared pHCR with FAMHAP, which mainly considers haplotype in the association analysis. For every experiment on the simulated data set, pHCR correctly produced haplotype interactions with much fewer false positives. We also challenged pHCR with a real data set input of beta-thalassemia/Hemoglobin E (HbE) disease. The result suggested the interaction between two previously reported quantitative trait loci of the fetal hemoglobin level, which is a major modifying factor, and disease severity of beta-thalassemia/HbE disease.
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http://dx.doi.org/10.1038/jhg.2009.85DOI Listing
November 2009

Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.

BMC Bioinformatics 2009 Sep 17;10:294. Epub 2009 Sep 17.

Department of Electrical Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand.

Background: Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Furthermore, there is no explicit proof that a combination of multiple two-locus analyses can lead to the correct identification of multi-locus interactions.

Results: The proposed 2LOmb algorithm performs an omnibus permutation test on ensembles of two-locus analyses. The algorithm consists of four main steps: two-locus analysis, a permutation test, global p-value determination and a progressive search for the best ensemble. 2LOmb is benchmarked against an exhaustive two-locus analysis technique, a set association approach, a correlation-based feature selection (CFS) technique and a tuned ReliefF (TuRF) technique. The simulation results indicate that 2LOmb produces a low false-positive error. Moreover, 2LOmb has the best performance in terms of an ability to identify all causative single nucleotide polymorphisms (SNPs) and a low number of output SNPs in purely epistatic two-, three- and four-locus interaction problems. The interaction models constructed from the 2LOmb outputs via a multifactor dimensionality reduction (MDR) method are also included for the confirmation of epistasis detection. 2LOmb is subsequently applied to a type 2 diabetes mellitus (T2D) data set, which is obtained as a part of the UK genome-wide genetic epidemiology study by the Wellcome Trust Case Control Consortium (WTCCC). After primarily screening for SNPs that locate within or near 372 candidate genes and exhibit no marginal single-locus effects, the T2D data set is reduced to 7,065 SNPs from 370 genes. The 2LOmb search in the reduced T2D data reveals that four intronic SNPs in PGM1 (phosphoglucomutase 1), two intronic SNPs in LMX1A (LIM homeobox transcription factor 1, alpha), two intronic SNPs in PARK2 (Parkinson disease (autosomal recessive, juvenile) 2, parkin) and three intronic SNPs in GYS2 (glycogen synthase 2 (liver)) are associated with the disease. The 2LOmb result suggests that there is no interaction between each pair of the identified genes that can be described by purely epistatic two-locus interaction models. Moreover, there are no interactions between these four genes that can be described by purely epistatic multi-locus interaction models with marginal two-locus effects. The findings provide an alternative explanation for the aetiology of T2D in a UK population.

Conclusion: An omnibus permutation test on ensembles of two-locus analyses can detect purely epistatic multi-locus interactions with marginal two-locus effects. The study also reveals that SNPs from large-scale or genome-wide case-control data which are discarded after single-locus analysis detects no association can still be useful for genetic epidemiology studies.
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http://dx.doi.org/10.1186/1471-2105-10-294DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759961PMC
September 2009