Prevalence of genotypic HIV-1 drug resistance in Thailand, 2002

BACKGROUND: The prices of reverse transcriptase (RT) inhibitors in Thailand have been reduced since December 1, 2001. It is expected that reduction in the price of these inhibitors may influence the drug resistance mutation pattern of HIV-1 among infected people. This study reports the frequency of HIV-1 genetic mutation associated with drug resistance in antiretroviral-treated patients from Thailand. METHODS: Genotypic resistance testing was performed on samples collected in 2002 from 88 HIV-1 infected individuals. Automated DNA sequencing was used to genotype the HIV-1 polymerase gene isolated from patients' plasma. RESULTS: Resistance to protease inhibitors, nucleoside and non-nucleoside reverse transcriptase inhibitors were found in 10 (12%), 42 (48%) and 19 (21%) patients, respectively. The most common drug resistance mutations in the protease gene were at codon 82 (8%), 90 (7%) and 54 (6%), whereas resistant mutations at codon 215 (45%), 67 (40%), 41 (38%) and 184 (27%) were commonly found in the RT gene. This finding indicates that genotypic resistance to nucleoside reverse transcriptase inhibitors was prevalent in 2002. The frequency of resistant mutations corresponding to non-nucleoside reverse transcriptase inhibitors was three times higher-, while resistant mutation corresponding to protease inhibitors was two times lower than those frequencies determined in 2001. CONCLUSION: This study shows that the frequencies of RT inhibitor resistance mutations have been increased after the reduction in the price of RT inhibitors since December 2001. We believe that this was an important factor that influenced the mutation patterns of HIV-1 protease and RT genes in Thailand

Parallelization of logic regression analysis on SNP-SNP interactions of a Crohn’s disease dataset model

SNP-SNP interactions have been recognized to be basically important for understanding genetic causes of complex disease traits. Logic regression is an effective methods for identifying SNP-SNP interactions associated with risk of complex disease. However, identifying SNP-SNP interactions are computationally challenging and may take hours, weeks and months to complete. Although parallel computing is a powerful method to accelerate computing time, it is arduous for users to apply this method to logic regression analyses of SNP-SNP interactions because it requires advanced programming skills to correctly partition and distribute data, control and monitor tasks across multi-core CPUs or several computers, and merge output files. In this paper, we present a novel R-library called SNPInt to automatically speed up analyses of SNP-SNP interactions of genome-wide association (GWA) studies using parallel computing without the advanced programming skills. The Crohn’s disease GWA studies dataset from the Wellcome Trust Case Control Consortium (WTCCC) that includes 4,680 individuals with 500,000 SNPs’ genotypes was analyzed using logic regression on a computer cluster to evaluate SNPInt performance. The results from SNPInt with any number of CPUs are the same as the results from non-parallel approach, and SNPInt library quite accelerated the logic regression analysis. For instance, with two hundred genes and twenty permutation rounds, the computing time was continuously decreased from 7.3 days to only 0.9 day when SNPInt applied eight CPUs. Executing analyses of SNP-SNP interactions using the SNPInt library is an effective way to boost performance, and simplify the parallelization of analyses of SNP-SNP interactions

Genetic diversity, determinants, and dissemination of Burkholderia pseudomallei lineages implicated in melioidosis in Northeast Thailand

Melioidosis is an often-fatal neglected tropical disease caused by an environmental bacterium Burkholderia pseudomallei. However, our understanding of the disease-causing bacterial lineages, their dissemination, and adaptive mechanisms remains limited. To address this, we conduct a comprehensive genomic analysis of 1,391 B. pseudomallei isolates collected from nine hospitals in northeast Thailand between 2015 and 2018, and contemporaneous isolates from neighbouring countries, representing the most densely sampled collection to date. Our study identifies three dominant lineages, each with unique gene sets potentially enhancing bacterial fitness in the environment. We find that recombination drives lineage-specific gene flow. Transcriptome analyses of representative clinical isolates from each dominant lineage reveal increased expression of lineage-specific genes under environmental conditions in two out of three lineages. This underscores the potential importance of environmental persistence for these dominant lineages. The study also highlights the influence of environmental factors such as terrain slope, altitude, and river direction on the geographical dispersal of B. pseudomallei. Collectively, our findings suggest that environmental persistence may play a role in facilitating the spread of B. pseudomallei, and as a prerequisite for exposure and infection, thereby providing useful insights for informing melioidosis prevention and control strategies

Exome Sequencing Identifies Compound Heterozygous Mutations in SCN5A Associated with Congenital Complete Heart Block in the Thai Population

Background. Congenital heart block is characterized by blockage of electrical impulses from the atrioventricular node (AV node) to the ventricles. This blockage can be caused by ion channel impairment that is the result of genetic variation. This study aimed to investigate the possible causative variants in a Thai family with complete heart block by using whole exome sequencing. Methods. Genomic DNA was collected from a family consisting of five family members in three generations in which one of three children in generation III had complete heart block. Whole exome sequencing was performed on one complete heart block affected child and one unaffected sibling. Bioinformatics was used to identify annotated and filtered variants. Candidate variants were validated and the segregation analysis of other family members was performed. Results. This study identified compound heterozygous variants, c.101G>A and c.3832G>A, in the SCN5A gene and c.28730C>T in the TTN gene. Conclusions. Compound heterozygous variants in the SCN5A gene were found in the complete heart block affected child but these two variants were found only in the this affected sibling and were not found in other unaffected family members. Hence, these variants in the SCN5A gene were the most possible disease-causing variants in this family

Phenotypic and genetic alterations of Burkholderia pseudomallei in patients during relapse and persistent infections

The bacterium Burkholderia pseudomallei is the causative agent of melioidosis, a severe tropical disease associated with high mortality and relapse and persistent infections. Treatment of melioidosis requires prolonged antibiotic therapy; however, little is known about relapse and persistent infections, particularly the phenotypic and genetic alterations of B. pseudomallei in patients. In this study, we performed pulsed-field gel electrophoresis (PFGE) to compare the bacterial genotype between the initial isolate and the subsequent isolate from each of 23 suspected recurrent and persistent melioidosis patients in Northeast Thailand. We used whole-genome sequencing (WGS) to investigate multilocus sequence types and genetic alterations of within-host strain pairs. We also investigated the bacterial phenotypes associated with relapse and persistent infections, including multinucleated giant cell (MNGC) formation efficiency and intracellular multiplication. We first identified 13 (1.2%) relapse, 7 (0.7%) persistent, and 3 (0.3%) reinfection patients from 1,046 survivors. Each of the 20 within-host strain pairs from patients with relapse and persistent infections shared the same genotype, suggesting that the subsequent isolates arise from the infecting isolate. Logistic regression analysis of clinical data revealed regimen and duration of oral antibiotic therapies as risk factors associated with relapse and persistent infections. WGS analysis demonstrated 17 within-host genetic alteration events in 6 of 20 paired isolates, including a relatively large deletion and 16 single-nucleotide polymorphism (stocktickerSNP) mutations distributed across 12 genes. In 1 of 20 paired isolates, we observed significantly increased cell-to-cell fusion and intracellular replication in the second isolate compared with the initial isolate from a patient with persistent infection. WGS analysis suggested that a non-synonymous mutation in the tssB-5 gene, which encoded an essential component of the type VI secretion system, may be associated with the increased intracellular replication and MNGC formation efficiency of the second isolate of the patient. This information provides insights into genetic and phenotypic alterations in B. pseudomallei in human melioidosis, which may represent a bacterial strategy for persistent and relapse infections

Success stories in genomic medicine from resource-limited countries

In recent years, the translation of genomic discoveries into mainstream medical practice and public health has gained momentum, facilitated by the advent of new technologies. However, there are often major discrepancies in the pace of implementation of genomic medicine between developed and developing/resource-limited countries. The main reason does not only lie in the limitation of resources but also in the slow pace of adoption of the new findings and the poor understanding of the potential that this new discipline offers to rationalize medical diagnosis and treatment. Here, we present and critically discuss examples from the successful implementation of genomic medicine in resource-limited countries, focusing on pharmacogenomics, genome informatics, and public health genomics, emphasizing in the latter case genomic education, stakeholder analysis, and economics in pharmacogenomics. These examples can be considered as model cases and be readily replicated for the wide implementation of pharmacogenomics and genomic medicine in other resource-limited environments. © 2015 Mitropoulos et al

Genomic medicine without borders: which strategies should developing countries employ to invest in precision medicine? A new "fast-second winner" strategy

Genomic medicine has greatly matured in terms of its technical capabilities, but the diffusion of genomic innovations worldwide faces significant barriers beyond mere access to technology. New global development strategies are sorely needed for biotechnologies such as genomics and their applications toward precision medicine without borders. Moreover, diffusion of genomic medicine globally cannot adhere to a “one-size-fits-all-countries” development strategy, in the same way that drug treatments should be customized. This begs a timely, difficult but crucial question: How should developing countries, and the resource-limited regions of developed countries, invest in genomic medicine? Although a full-scale investment in infrastructure from discovery to the translational implementation of genomic science is ideal, this may not always be feasible in all countries at all times. A simple “transplantation of genomics” from developed to developing countries is unlikely to be feasible. Nor should developing countries be seen as simple recipients and beneficiaries of genomic medicine developed elsewhere because important advances in genomic medicine have materialized in developing countries as well. There are several noteworthy examples of genomic medicine success stories involving resource-limited settings that are contextualized and described in this global genomic medicine innovation analysis. In addition, we outline here a new long-term development strategy for global genomic medicine in a way that recognizes the individual country's pressing public health priorities and disease burdens. We term this approach the “Fast-Second Winner” model of innovation that supports innovation commencing not only “upstream” of discovery science but also “mid-stream,” building on emerging highly promising biomarker and diagnostic candidates from the global science discovery pipeline, based on the unique needs of each country. A mid-stream entry into innovation can enhance collective learning from other innovators' mistakes upstream in discovery science and boost the probability of success for translation and implementation when resources are limited. This à la carte model of global innovation and development strategy offers multiple entry points into the global genomics innovation ecosystem for developing countries, whether or not extensive and expensive discovery infrastructures are already in place. Ultimately, broadening our thinking beyond the linear model of innovation will help us to enable the vision and practice of genomics without borders in both developed and resource-limited settings

ParallABEL: an R library for generalized parallelization of genome-wide association studies

Background: Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files.Results: Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors.Conclusions: Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL

Emergence of HIV-1 drug resistance mutations among antiretroviral-naïve HIV-1-infected patients after rapid scaling up of antiretroviral therapy in Thailand

<p>Abstract</p> <p>Background</p> <p>After rapid scaling up of antiretroviral therapy in HIV-1-infected patients, the data of primary HIV-1 drug resistance in Thailand is still limited. This study aims to determine the prevalence and associated factors of primary HIV-1 drug resistance in Thailand.</p> <p>Methods</p> <p>A prospective observational study was conducted among antiretroviral-naïve HIV-1-infected Thai patients from 2007 to 2010. HIV-1 subtypes and mutations were assayed by sequencing a region of HIV-1 pol gene. Surveillance drug resistance mutations recommended by the World Health Organization for surveillance of transmitted HIV-1 drug resistance in 2009 were used in all analyses. Primary HIV-1 drug resistance was defined as the presence of one or more surveillance drug resistance mutations.</p> <p>Results</p> <p>Of 466 patients with a mean age of 38.8 years, 58.6% were males. Risks of HIV-1 infection included heterosexual (77.7%), homosexual (16.7%), and intravenous drug use (5.6%). Median (IQR) CD4 cell count and HIV-1 RNA were 176 (42-317) cells/mm³and 68,600 (19,515-220,330) copies/mL, respectively. HIV-1 subtypes were CRF01_AE (86.9%), B (8.6) and other recombinants (4.5%). The prevalence of primary HIV-1 drug resistance was 4.9%; most of these (73.9%) had surveillance drug resistance mutations to only one class of antiretroviral drugs. The prevalence of patients with NRTI, NNRTI, and PI surveillance drug resistance mutations was 1.9%, 2.8% and 1.7%, respectively. From logistic regression analysis, there was no factor significantly associated with primary HIV-1 drug resistance. There was a trend toward higher prevalence in females [odds ratio 2.18; 95% confidence interval 0.896-5.304; p = 0.086].</p> <p>Conclusions</p> <p>There is a significant emergence of primary HIV-1 drug resistance in Thailand after rapid scaling up of antiretroviral therapy. Although HIV-1 genotyping prior to antiretroviral therapy initiation is not routinely recommended in Thailand, our results raise concerns about the risk of early treatment failure in patients with primary HIV-1 drug resistance. Interventions to prevent the transmission of HIV-1 drug resistance and continuation of surveillance for primary HIV-1 drug resistance in Thailand are indicated.</p

Success stories in genomic medicine from resource-limited countries

In recent years, the translation of genomic discoveries into mainstream medical practice and public health has gained momentum, facilitated by the advent of new technologies. However, there are often major discrepancies in the pace of implementation of genomic medicine between developed and developing/resource-limited countries. The main reason does not only lie in the limitation of resources but also in the slow pace of adoption of the new findings and the poor understanding of the potential that this new discipline offers to rationalize medical diagnosis and treatment. Here, we present and critically discuss examples from the successful implementation of genomic medicine in resource-limited countries, focusing on pharmacogenomics, genome informatics, and public health genomics, emphasizing in the latter case genomic education, stakeholder analysis, and economics in pharmacogenomics. These examples can be considered as model cases and be readily replicated for the wide implementation of pharmacogenomics and genomic medicine in other resource-limited environments