Biology subjects

Do, T.-T. T.

Publications and source records attributed to Do, T.-T. T..

3 recordsLinked to original sources

bioRxiv2026

First-Trimester Non-Invasive Prediction of Preterm Birth Using Cell-Free DNA Fragmentomics

ObjectiveTo develop and validate a cell-free DNA (cfDNA) fragmentomic classifier for the early prediction of spontaneous preterm birth (PTB) using routine first-trimester non-invasive prenatal testing (NIPT) data. MethodsA nested case-control study was conducted within a prospective multicenter Vietnamese cohort comprising 286 pregnancies, including 82 spontaneous PTB cases and 204 term controls. Maternal plasma cfDNA collected during routine first-trimester NIPT (median gestational age, 12 weeks) was sequenced to a depth of approximately 20 million reads per sample. Five fragmentomic feature categories including copy number alterations, end-motif composition, nucleosome distance, fragment length, and joint fragment-lengthxend-motif were evaluated for PTB prediction. Machine learning classifiers were developed in a training cohort (n = 228, 65 PTB vs 163TB) and tested in a validation cohort (n = 58, 17 PTB vs 41 TB). ResultsAmong the five fragmentomic feature classes evaluated, 4-mer end-motif (EM) profiles exhibited the most pronounced differences between PTB and term control samples. Consistent with these findings, the EM-based classifier demonstrated the highest discriminative performance in the validation cohort, achieving an AUC of 0.970 (95% CI, 0.912-1.000). At a specificity >90%, the model achieved a sensitivity of 94% (95% CI, 78-100%). ConclusionThese findings demonstrate that cfDNA EM signatures derived from routine first-trimester NIPT can accurately identify pregnancies at risk of spontaneous preterm birth, without additional blood collection or sequencing, thereby extending the clinical utility of existing prenatal screening infrastructure. KEY POINTSO_ST_ABSWhat is already known about this topic?C_ST_ABSO_LICurrent first-trimester prediction strategies based on maternal characteristics, cervical length, and biochemical markers have limited predictive accuracy, particularly in nulliparous women. C_LIO_LIExisting cfDNA-based approaches have shown only modest performance or require additional assays, limiting clinical applicability. C_LI What does this study add?O_LIExisting NIPT sequencing data can be repurposed (without additional blood sampling or sequencing) for accurate prediction of spontaneous preterm birth (AUC=0.970). C_LIO_LIA classifier employing 4-mer end-motif (EM) profiles achieved an AUC of 0.970. At a specificity >90%, the model achieved a sensitivity of 94%. C_LI

genomics↗

bioRxiv2020

Genetic landscape of recessive diseases in the Vietnamese population from large-scale clinical exome sequencing

PurposeAccurate profiling of population-specific recessive diseases is essential for the design of cost-effective carrier screening programs. However, minority populations and ethnic groups, including Vietnamese, are still under-represented in existing genetic studies. Here we reported the first comprehensive study of recessive diseases in the Vietnamese population. MethodsClinical exome sequencing (CES) data of 4,503 disease-associated genes obtained from a cohort of 985 Vietnamese individuals was analyzed to identify pathogenic variants, associated diseases and their carrier frequencies in the population. ResultsEighty-five recessive diseases were identified in the Vietnamese population, among which seventeen diseases had carrier frequencies of at least 1% (1 in 100 individuals). Three diseases were especially prevalent in the Vietnamese population with carrier frequencies of 2-12 times higher than in other East Asia or the world populations, including Beta-thalassemia (1 in 25), citrin deficiency (1 in 33) and phenylketonuria (1 in 40). Seven novel pathogenic and three likely pathogenic variants associated with nine recessive diseases were also discovered. ConclusionsThe comprehensive profile of recessive diseases identified in this study shall enable the design of cost-effective carrier screening programs specific to the Vietnamese population. The newly discovered pathogenic variants may also exist in other populations at extremely low frequencies, thus representing a valuable resource for future research. Our study has demonstrated the advantage of population-specific genetic studies to advance the knowledge and practice of medical genetics.

genetics↗

bioRxiv2019

Genetic profiling of 2,683 Vietnamese genomes from non-invasive prenatal testing data

The under-representation of several ethnic groups in existing genetic databases and studies have undermined our understanding of the genetic variations and associated traits or diseases in many populations. Cost and technology limitations remain the challenges in performing large-scale genome sequencing projects in many developing countries, including Vietnam. As one of the most rapidly adopted genetic tests, non-invasive prenatal testing (NIPT) data offers an alternative untapped resource for genetic studies. Here we performed a large-scale genomic analysis of 2,683 pregnant Vietnamese women using their NIPT data and identified a comprehensive set of 8,054,515 single-nucleotide polymorphisms, among which 8.2% were new to the Vietnamese population. Our study also revealed 24,487 disease-associated genetic variants and their allele frequency distribution, especially 5 pathogenic variants for prevalent genetic disorders in Vietnam. We also observed major discrepancies in the allele frequency distribution of disease-associated genetic variants between the Vietnamese and other populations, thus highlighting a need for genome-wide association studies dedicated to the Vietnamese population. The resulted database of Vietnamese genetic variants, their allele frequency distribution, and their associated diseases presents a valuable resource for future genetic studies.

genomics↗