Bhoom Suktitipat’s research while affiliated with Mahidol University and other places

10572 Background: Effective breast cancer prevention and management require accurate risk prediction tools. Polygenic risk scores (PRS) have shown promise but are often less effective in non-European populations due to differences in genetic architecture. This study evaluates PRS performance and adaptation for breast cancer in the Thai population, addressing disparities in underrepresented groups. Methods: We retrospectively analyzed breast cancer cases from the Genomics Thailand project at Siriraj Hospital and general population controls from the National Health Examination Survey (NHES) in Thailand. Whole-genome sequencing was performed for cases, and genotyping with imputation was done for controls using the TOPMed r2 reference panel. Clinical data were extracted from electronic medical records. PRS were constructed using SBayesRC, incorporating variants from publicly available genome-wide association study (GWAS) summary statistics and variant functional annotations. Logistic regression and area under the receiver operating characteristic curve (AUC) analyses were conducted using R. Results: The discovery cohort included 975 cases and 1,502 controls, with 230 cases and 265 controls in the validation cohort. Of the 330 previously reported GWAS loci, only 231 lead variants were identified in our dataset. We further analyzed variants near these lead variants within the 330 loci, identifying nominal associations with breast cancer for 329 loci (p<0.05). Four PRS models were tested: (1) 231 variants, (2) ~7 million functional variants based on European (EUR) data, (3) East Asian (EAS) models, and (4) combined EUR and EAS models. The EUR-based model (AUC 0.66) outperformed the 231-variant model (AUC 0.59) and the population-specific EAS model (AUC 0.58) at p<0.05. The combined EUR and EAS models showed no significant improvement over the EUR model alone (AUC 0.66 for both, p=0.69). Individuals in the highest PRS risk group (above the 90 th percentile) had an odds ratio (OR) of 3.34 for breast cancer compared to the rest of the population (95% confidence interval: 2.54–4.42, p<0.05). Among 249 patients with pathology data, PRS was not associated with tumor size, estrogen receptor status, or nodal metastasis. Conclusions: In the Thai population, PRS derived from large-scale European GWAS provided the highest prediction accuracy for breast cancer risk. The limited transferability of a top-variant PRS (e.g., 330-variant model) underscores the challenge posed by variant availability in this population. Validation in prospective studies is essential to optimize PRS utility and address disparities in genetic risk prediction.

Breast cancer genomic landscapes differ across ethnic groups, yet the somatic profile of Thai breast tumours has remained uncharacterised. This study analysed 1676 high-hereditary-risk Thai breast cancer patients, identified according to National Comprehensive Cancer Network (NCCN) guideline. Germline alterations were assessed in 1370 cases using a custom 36-core cancer panel. Somatic mutations were characterised in formalin-fixed, paraffin-embedded tumour tissues from 180 of the 1676 patients using the 501-gene Oncomine Comprehensive Assay Plus panel. Pathogenic or likely pathogenic (P/LP) variants were detected in 13% of the 1370 germline analyses, with BRCA1 and BRCA2 being the most frequently altered genes. The prevalence of P/LP variants in BRCA1, BRCA2, and PALB2 differed from that observed in other ethnic cohorts. In somatic profiling, TP53 emerged as the most frequently mutated gene, especially in HER2 and TNBC tumours, whereas MAP3K1 and GATA3 were the most frequently mutated genes in the HR+/HER2- tumours. Moreover, hormone-receptor-positive (HR+) tumours showed distinct mutation patterns compared with other ethnicities. Notably, germline carriers exhibited lower PIK3CA mutation rates than non-carriers. These findings advance our understanding of Thai breast cancer genomics and underscore the importance of ethnic diversity in cancer research, offering insights into tailored screening and therapeutic approaches.

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally. The relationships of human diversity with biological and biomedical phenotypes are pervasive, yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We detected single-cell signatures of human diversity not apparent at the level of cell types, as well as modulation of the effects of age and sex by self-reported ethnicity. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond.

Background The study of non-communicable diseases (NCDs) in a developing country like Thailand has rarely been conducted in long-term cohorts, especially among the working-age population. We aim to assess the prevalence and incidence of risk factors and their associations underlying NCDs, especially type-2 diabetes mellitus (T2DM) among healthcare workers enrolled in the Siriraj Health (SIH) study cohort. Methods The SIH study was designed as a longitudinal cohort and conducted at Siriraj hospital, Thailand. A total of 5,011 participants (77% women) were recruited and follow-up. Physical examinations, blood biochemical analyses, family history assessments, behavior evaluations, and genetics factors were assessed. Results The average age was 35.44±8.24 years and 51% of participants were overweight and obese. We observed that men were more likely to have a prevalence of T2DM and dyslipidemia (DLP) compared to women. Aging was significantly associated with pre-diabetes and T2DM (P<0.001). Additionally, aging, metabolic syndrome, and elevated triglycerides were associated with the development of pre-diabetes and T2DM. The minor T allele of the rs7903146(C/T) and rs4506565 (A/T) were associated with a high risk of developing pre-diabetes with odds ratios of 2.74 (95% confidence interval [CI]: 0.32–23.3) and 2.71 (95% CI: 0.32–23.07), respectively; however, these associations were statistically insignificant (P>0.05). Conclusion The findings of the SIH study provide a comprehensive understanding of the health status, risk factors, and genetic factors related to T2DM in a specific working population and highlight areas for further research and intervention to address the growing burden of T2DM and NCDs.

The revised WHO guidelines for classifying and grading brain tumors include several copy number variation (CNV) markers. The turnaround time for detecting CNVs and alterations throughout the entire genome is drastically reduced with the customized read incremental approach on the nanopore platform. However, this approach is challenging for non-bioinformaticians due to the need to use multiple software tools, extract CNV markers and interpret results, which creates barriers due to the time and specialized resources that are necessary. To address this problem and help clinicians classify and grade brain tumors, we developed GLIMMERS: glioma molecular markers exploration using long-read sequencing, an open-access tool that automatically analyzes nanopore-based CNV data and generates simplified reports. Availability and implementation GLIMMERS is available at https://gitlab.com/silol_public/glimmers under the terms of the MIT license.

Background The study of non-communicable diseases (NCDs) in a developing country like Thailand has rarely conducted in long-term cohort, especially in working-age population. We aim to assess the prevalence and incidence of risk factors and their associations underlying NCDs, especially type-2 diabetes mellitus (T2DM) among healthcare workers enrolled in the Siriraj Health (SIH) study cohort. Methods SIH study was designed as a longitudinal cohort and conducted at Siriraj hospital, Thailand. A total 5,011 participants (77% Female) were recruited and follow-up. Physical examinations, blood biochemical, family history, behavior and genetics factors were assessed. Results The average age was 35.44 ± 8.24 years and 51% of participants were overweight and obese. We observed men were more likely to have prevalence to T2DM and dyslipidemia (DLP) more than woman. Obese were significantly increased with prediabetes and T2DM (P < 0.001). Additionally, aging, obesity, metabolic syndrome, and DLP were associated with the development of prediabetes and T2DM. The minor T allele of the rs7903146(C/T) and rs4506565 (A/T) was associated with high risk of development of T2DM with an odds ratio of 2.74 (95% confidence interval [CI]: 0.32–23.3) and 2.71 (95% CI: 0.32–23.07), respectively; however, they were statistically insignificant (P > 0.05). Conclusion The SIH study's findings provide a comprehensive understanding of the health status, risk factors, and genetic factors related to T2DM in a specific working population and highlight areas for further research and intervention to address the growing burden of T2DM and NCDs.

The 2021 WHO Classification of Central Nervous System Tumors recommended evaluation of cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletion in addition to codeletion of 1p/19q to characterize IDH-mutant glio-mas. Here, we demonstrated the use of a nanopore-based copy-number variation sequencing (nCNV-seq) approach to simultaneously identify deletions of CDKN2A/B and 1p/19q. The nCNV-seq approach was initially evaluated on three distinct glioma cell lines and then applied to 19 IDH-mutant gliomas (8 astrocytomas and 11 oligodendrogliomas) from patients. The whole-arm 1p/19q codeletion was detected in all oligodendrogliomas with high concordance among nCNV-seq, FISH, DNA methylation profiling, and whole-genome sequencing. For the CDKN2A/B deletion, nCNV-seq detected the loss in both astrocytoma and oligodendroglioma, with strong correlation with the CNV profiles derived from whole-genome sequencing (Pearson correlation (r) = 0.95, P < 2.2 Â 10 À16 to r = 0.99, P < 2.2 Â 10 À16) and methylome profiling. Furthermore, nCNV-seq can differentiate between homozygous and hemizygous deletions of CDKN2A/B. Taken together, nCNV-seq holds promise as a new, alternative approach for a rapid and simultaneous detection of the molecular signatures of IDH-mutant gliomas without capital expenditure for a sequencer.