Genetic counseling and genetic testing for pathogenic germline mutations among high-risk patients previously diagnosed with breast cancer: a traceback approach.

Genetic counseling and testing are more accessible than ever due to reduced costs, expanding indications and public awareness. Nonetheless, many patients missed the opportunity of genetic counseling and testing due to barriers that existed at that time of their cancer diagnoses. Given the identified implications of pathogenic mutations on patients' treatment and familial outcomes, an opportunity exists to utilize a 'traceback' approach to retrospectively examine their genetic makeup and provide consequent insights to their disease and treatment. In this study, we identified living patients diagnosed with breast cancer (BC) between July 2007 and January 2022 who would have been eligible for testing, but not tested. Overall, 422 patients met the eligibility criteria, 282 were reached and invited to participate, and germline testing was performed for 238, accounting for 84.4% of those invited. The median age (range) was 39.5 (24-64) years at BC diagnosis and 49 (31-75) years at the date of testing. Genetic testing revealed that 25 (10.5%) patients had pathogenic/likely pathogenic (P/LP) variants; mostly in BRCA2 and BRCA1. We concluded that long overdue genetic referral through a traceback approach is feasible and effective to diagnose P/LP variants in patients with history of BC who had missed the opportunity of genetic testing, with potential clinical implications for patients and their relatives.

EMCMDA: predicting miRNA-disease associations via efficient matrix completion.

Abundant researches have consistently illustrated the crucial role of microRNAs (miRNAs) in a wide array of essential biological processes. Furthermore, miRNAs have been validated as promising therapeutic targets for addressing complex diseases. Given the costly and time-consuming nature of traditional biological experimental validation methods, it is imperative to develop computational methods. In the work, we developed a novel approach named efficient matrix completion (EMCMDA) for predicting miRNA-disease associations. First, we calculated the similarities across multiple sources for miRNA/disease pairs and combined this information to create a holistic miRNA/disease similarity measure. Second, we utilized this biological information to create a heterogeneous network and established a target matrix derived from this network. Lastly, we framed the miRNA-disease association prediction issue as a low-rank matrix-complete issue that was addressed via minimizing matrix truncated schatten p-norm. Notably, we improved the conventional singular value contraction algorithm through using a weighted singular value contraction technique. This technique dynamically adjusts the degree of contraction based on the significance of each singular value, ensuring that the physical meaning of these singular values is fully considered. We evaluated the performance of EMCMDA by applying two distinct cross-validation experiments on two diverse databases, and the outcomes were statistically significant. In addition, we executed comprehensive case studies on two prevalent human diseases, namely lung cancer and breast cancer. Following prediction and multiple validations, it was evident that EMCMDA proficiently forecasts previously undisclosed disease-related miRNAs. These results underscore the robustness and efficacy of EMCMDA in miRNA-disease association prediction.

Risk of diabetes mellitus based on the interactive association between G6PD rs72554664 polymorphism and sex in Taiwan Biobank individuals.

The presence of glucose-6-phosphate dehydrogenase (G6PD) deficiency may increase the risk of type 2 diabetes mellitus (T2DM), with differing prevalence between males and females. Although G6PD deficiency is an X-linked genetic condition, its interaction with sex regarding T2DM risk among the Taiwanese population has not been fully explored. This study aimed to investigate the association between G6PD deficiency and T2DM risk in the Taiwanese population, focusing on the potential influence of sex. Data were obtained from the Taiwan Biobank (TWB) database, involving 85,334 participants aged 30 to 70 years. We used multiple logistic regression analysis to assess the interaction between G6PD rs72554664 and sex in relation to T2DM risk. The T2DM cohort comprised 55.35% females and 44.65% males (p < 0.001). The TC + TT genotype of rs72554664 was associated with an increased risk of T2DM, with an odds ratio (OR) of 1.95 (95% CI: 1.39-2.75), and males showed an OR of 1.31 (95% CI: 1.19-1.44). Notably, the G6PD rs72554664-T allelic variant in hemizygous males significantly elevated the T2DM risk (OR), 4.57; p < 0.001) compared to females with the CC genotype. Our findings suggest that the G6PD rs72554664 variant, in conjunction with sex, significantly affects T2DM risk, particularly increasing susceptibility in males. The association of the G6PD rs72554664-T allelic variant with a higher risk of T2DM highlights the importance of sex-specific mechanisms in the interplay between G6PD deficiency and T2DM.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for lung cancer.

BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR). METHODS: Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant. FINDINGS: In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33. INTERPRETATION: We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

Prospective of Mitochondrial DNA Variations in Cancer on Genomic Medicine.

Mitochondrial DNA (mtDNA) has emerged as a pivotal component in understanding the etiology and susceptibility of cancer. A recent study by Chen and colleagues delineated the germline genetic effect of mtDNA single-nucleotide polymorphisms (SNP) and haplogroups across pan-cancer risk. They identified a subset of mtSNPs and the corresponding risk score, as well as haplogroups A and M7 alongside their genetic interactions, conferring a protective effect against various cancers. These findings underscored the value of mtDNA variations as biomarkers for cancer etiology and as tools for cancer risk stratification. Future investigations are encouraged to integrate comprehensive omics data of genomics, transcriptomics, proteomics, and metabolomics, etc., from nuclear DNA with mtDNA variations, alongside single-cell and spatial technologies, to unravel the tumor mechanism and identify the drug targets. Moreover, the incorporation of polygenic risk score, that included mtDNA variations with both rare and common frequencies, and liquid biopsy-based biomarkers would enhance the predictive performance of cancer risk assessment and refine the risk stratification of population-based cancer screening. This commentary advocates for the validation across diverse populations to harness the full potential of mitochondrial genomics, and ultimately paves the prospective way for advancements in personalized cancer therapeutics and prevention strategies. See related article by Chen and colleagues, Cancer Epidemiol Biomarkers Prev 2024;33:381-8.

Circulating interleukin-27 is associated with the risk of chronic periodontitis and allergic rhinitis: A Mendelian randomization analysis.

BACKGROUND: Chronic periodontitis (CP) and allergic rhinitis (AR) have attracted wide attention as global public health problems with high incidence. Recent studies have shown that circulating interleukin-27 (IL-27) is associated with the risk of CP and AR. The aim of this study is to analyze the causal effect between them using Mendelian randomization (MR). METHODS: Bidirectional MR analyses were performed with the use of publicly available genome-wide association study (GWAS) data. Summary data on circulating IL-27, CP, and AR published in genome-wide association studies were collected. Instrumental variables (IV) were extracted using assumptions of correlation, independence and exclusivity as criteria. Inverse variance weighting (IVW) was used as the main method, combined with weighted median method (WM) and MR-Egger and other MR Analysis methods for causal inference of exposure and outcome. Cochran's Q and MR-Egger intercept were used for sensitivity analysis. RESULTS: The IVW study showed a causal effect between increased circulating IL-27 levels and increased risk of CP (OR = 1.14, 95%CI = 1.02-1.26, p = .020). Similarly, the increase of circulating IL-27 level had a causal effect on the decreased risk of AR (OR = 0.88, 95%CI = 0.80-0.97, p = .012). In addition, IVW study found that there was a causal between the increased risk of CP and circulating IL-27 level (OR = 1.05, 95%CI = 1.01-1.10, p = .016). However, there was no significant causal relationship between the risk of AR and circulating IL-27 levels (OR = 0.97, 95%CI = 0.91-1.02, p = .209). no significant heterogeneity or horizontal pleiotropy was found in sensitivity analysis. CONCLUSIONS: There is a causal effect between circulating IL-27 level and CP, AR, which will help to find new ideas and methods for the diagnosis and treatment of CP and AR.

The Genesis of Schizophrenia: An Origin Story.

Schizophrenia is routinely referred to as a neurodevelopmental disorder, but the role of brain development in a disorder typically diagnosed during early adult life is enigmatic. The authors revisit the neurodevelopmental model of schizophrenia with genomic insights from the most recent schizophrenia clinical genetic association studies, transcriptomic and epigenomic analyses from human postmortem brain studies, and analyses from cellular models that recapitulate neurodevelopment. Emerging insights into schizophrenia genetic risk continue to converge on brain development, particularly stages of early brain development, that may be perturbed to deviate from a typical, normative course, resulting in schizophrenia clinical symptomatology. As the authors explicate, schizophrenia genetic risk is likely dynamic and context dependent, with effects of genetic risk varying spatiotemporally, across the neurodevelopmental continuum. Optimizing therapeutic strategies for the heterogeneous collective of individuals with schizophrenia may likely be guided by leveraging markers of genetic risk and derivative functional insights, well before the emergence of psychosis. Ultimately, rather than a focus on therapeutic intervention during adolescence or adulthood, principles of prediction and prophylaxis in the pre- and perinatal and neonatal stages may best comport with the biology of schizophrenia to address the early-stage perturbations that alter the normative neurodevelopmental trajectory.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

Population-Level Identification of Patients With Lynch Syndrome for Clinical Care, Quality Improvement, and Research.

PURPOSE: Identification of those at risk of hereditary cancer syndromes using electronic health record (EHR) data sources is important for clinical care, quality improvement, and research. We describe diagnostic processes, previously seldom reported, for a common hereditary cancer syndrome, Lynch syndrome (LS), using EHR data within a community-based, multicenter, demographically diverse health system. METHODS: Within a retrospective cohort enrolled between 2015 and 2020 at Kaiser Permanente Northern California, we assessed electronic diagnostic domains for LS including (1) family history of LS-associated cancer; (2) personal history of LS-associated cancer; (3) LS screening via mismatch repair deficiency (MMRD) testing of newly diagnosed malignancy; (4) germline genetic test results; and (5) clinician-entered diagnostic codes for LS. We calculated proportions and overlap for each diagnostic domain descriptively. RESULTS: Among 5.8 million individuals, (1) 28,492 (0.49%) had a family history of LS-associated cancer of whom 3,635 (13%) underwent genetic testing; (2) 100,046 (1.7%) had a personal history of a LS-associated cancer; and (3) 8,711 (0.1%) were diagnosed with colorectal cancer of whom 7,533 (86%) underwent MMRD screening and of the positive screens (486), 130 (27%) underwent germline testing. One thousand seven hundred and fifty-seven (0.03%) were diagnosed with endometrial cancer of whom 1,613 (92%) underwent MMRD screening and of the 195 who screened positive, 55 (28%) underwent genetic testing. (4) 30,790 (0.05%) had LS germline genetic testing with 707 (0.01%) testing positive; and (5) 1,273 (0.02%) had a clinician-entered diagnosis of LS. CONCLUSION: It is feasible to electronically characterize the diagnostic processes of LS. No single data source comprehensively identifies all LS carriers. There is underutilization of LS genetic testing for those eligible and underdiagnosis of LS. Our work informs similar efforts in other settings for hereditary cancer syndromes.

Understanding the Impact of the Sirtuin 1 (SIRT1) Gene on Age-related Macular Degeneration: A Comprehensive Study.

Age-related macular degeneration (AMD) is a prevalent and incurable condition affecting the central retina and posing a significant risk to vision, particularly in individuals over the age of 60. As the global population ages, the prevalence of AMD is expected to rise, leading to substantial socioeconomic impacts and increased healthcare costs. The disease manifests primarily in two forms, neovascular and non-neovascular, with genetic, environmental and lifestyle factors playing a pivotal role in disease susceptibility and progression. This review article involved conducting an extensive search across various databases, including Google Scholar, PubMed, Web of Science, ScienceDirect, Scopus and EMBASE, to compile relevant case-control studies and literature reviews from online published articles extracted using search terms related to the work. SIRT1, a key member of the sirtuin family, influences cellular processes such as ageing, metabolism, DNA repair and stress response. Its dysregulation is linked to retinal ageing and ocular conditions like AMD. This review discusses the role of SIRT1 in AMD pathology, its association with genetic variants and its potential as a biomarker, paving the way for targeted interventions and personalised treatment strategies. In addition, it highlights the findings of case-control studies investigating the relationship between SIRT1 gene polymorphisms and AMD risk. These studies collectively revealed a significant association between certain SIRT1 gene variants and AMD risk. Further studies with larger sample sizes are required to validate these findings. As the prevalence of AMD grows, understanding the role of SIRT1 and other biomarkers becomes increasingly vital for improving diagnosis, treatment and, ultimately, patient outcomes.

Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis.

OBJECTIVE: This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms. METHODS: This genome-wide pleiotropic association study uses multiple statistical methods to systematically analyse the shared genetic basis between five respiratory diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, lung cancer and snoring) using the largest publicly available genome wide association studies summary statistics. The missions of this study are to evaluate global and local genetic correlations, to identify pleiotropic loci, to elucidate biological pathways at the multiomics level and to explore causal relationships between respiratory diseases. Data were collected from 27 November 2022 to 30 March 2023 and analysed from 14 April 2023 to 13 July 2023. MAIN OUTCOMES AND MEASURES: The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects. RESULTS: Significant genetic correlations were found for 10 paired traits in 5 respiratory diseases. Cross-Phenotype Association identified 12 400 significant potential pleiotropic single-nucleotide polymorphism at 156 independent pleiotropic loci. In addition, multitrait colocalisation analysis identified 15 colocalised loci and a subset of colocalised traits. Gene-based analyses identified 432 potential pleiotropic genes and were further validated at the transcriptome and protein levels. Both pathway enrichment and single-cell enrichment analyses supported the role of the immune system in respiratory diseases. Additionally, five pairs of respiratory diseases have a causal relationship. CONCLUSIONS AND RELEVANCE: This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. It provides strong evidence for further therapeutic strategies and risk prediction for the phenomenon of respiratory disease comorbidity.

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism.

BACKGROUND: MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn't been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training. RESULTS: The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227. CONCLUSIONS: The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.

Serum 25-hydroxyvitamin D levels and dermatomyositis: A 2-sample mendelian randomization study.

BACKGROUND: Previous studies have reported low serum 25-hydroxyvitamin D [25(OH)D] levels in dermatomyositis (DM) patients, but the exact causal relationship between them remains elusive. Our aim is to confirm the causal relationship between 25(OH)D and DM risk through a Mendelian randomization study. METHODS: Retrieve genome-wide association study (GWAS) data on 25(OH)D (n = 441 291) and DM (n cases = 201, n controls = 172 834) from the GWAS database (https://gwas.mrcieu.ac.uk/). Select single-nucleotide polymorphisms (SNPs) strongly correlated with 25(OH)D as instrumental variables (IVs). The primary analytical approach involves the use of the inverse-variance weighted method (IVW), supplemented by MR-Egger regression and weighted median methods to enhance the reliability of the results. Heterogeneity and sensitivity analyses were conducted using Cochran's Q and leave-one-out approaches, respectively. RESULTS: The IVW analysis confirmed a positive causal relationship between genetic variation in 25(OH)D levels and DM (OR = 2.36, 95% CI = 1.01-5.52, p = .048). Although not statistically significant (all p > .05), the other methods also suggested a protective effect of 25(OH)D on DM. Based on MR-Egger intercepts and Cochran's Q analysis, the selected SNPs showed no horizontal pleiotropy and heterogeneity. Sensitivity analysis demonstrated the robustness of the results against individual SNPs. CONCLUSION: We provide the first evidence of a causal relationship between 25(OH)D levels and DM. Our findings support the importance of measuring serum 25(OH)D levels and considering vitamin D supplementation in clinical practice for patients with DM.

The causal associations of inflammatory cytokines with obesity and systemic lupus erythematosus: A Mendelian randomization study.

OBJECTIVE: Previous studies have partly discussed the roles of inflammatory cytokines in obesity and systemic lupus erythematosus (SLE), but the causal relationship among inflammatory cytokines, obesity, and SLE is unclear. It is challenging to comprehensively evaluate the causal relationship between these variables. This study aimed to investigate the role of cytokines as intermediates between obesity and SLE. METHODS: The inverse-variance weighted method (IVW) of mendelian randomization (MR) is mainly used to explore the causal relationship between exposure and outcome by using the genetic variation of the open large genome-wide association studies (GWAS), namely single-nucleotide polymorphisms (SNPs) related to obesity (more than 600 000 participants), inflammatory cytokines (8293 healthy participants) and SLE (7219 cases). Methods such as weighted median, MR-Egger are used to evaluate the reliability of causality. Reverse analysis is performed for each MR analysis to avoid reverse causality. Cochran's Q statistic and funnel chart are used to detect heterogeneity, MR-Egger intercept test and leave-one-out sensitivity analyses evaluated pleiotropy. RESULTS: Obesity was associated with 25 cytokines, and 3 cytokines were associated with SLE, including CTACK (OR = 1.19, 95% CI: 1.06, 1.33, p = .002), IL-18 (OR = 1.13, 95% CI: 1.01, 1.26, p = .027), SCGFb (OR = 0.89, 95% CI: 0.79, 0.99, p = .044). In the opposite direction, SLE was associated with 18 cytokines, and 2 cytokines were associated with obesity, including IP-10 (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .002), MIP-1B (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .004). CONCLUSION: Our MR study suggested that CTACK, IL-18 and SCGFb may play an intermediary role in obesity to SLE, while IP-10 and MIP-1B may play an intermediary role in SLE to obesity.

Addressing causal relationship between drinking behavior and metabolic syndrome: one-sample Mendelian randomization analysis.

AIMS: Alcohol drinking is associated with central obesity, hypertension, and hyperlipidemia, which further causes metabolic syndrome (MetS). However, prior epidemiological studies on such associations lack experimental evidence for a causal relationship. This study aims to explore the causal relationship between drinking behavior and MetS in Taiwan population by using Mendelian randomization (MR) analysis. METHODS: A cross-sectional study was conducted using the Taiwan Biobank database, which comprised 50 640 Han Chinese who were 30-70 years old without cancer from 2008 to 2020. In MR analysis, we constructed weighted and unweighted genetic risk scores by calculating SNP alleles significantly associated with alcohol drinking. We calculated odds ratios and 95% confidence interval (CI) by using a two-stage regression model. RESULTS: A total of 50 640 participants were included with a mean age of 49.5 years (SD: 1.67 years), 36.6% were men. The adjusted odds ratio (aOR) of MetS per 5% increase in the likelihood of genetic predisposition to drink based on weighted genetic risk score with adjustment was 1.11 (95% CI: 1.10, 1.12, P < .001). Analysis was also conducted by grouping the likelihood of genetic predisposition to drink based on quartiles with multivariate adjustment. Using Q1 as the reference group, the aORs of MetS for Q2, Q3, and Q4 were 1.19 (1.12, 1.27, p < .001), 1.31 (1.23, 1.40, p < .001), and 1.87 (1.75, 2.00, p < .001), respectively, for the weighted genetic risk score. CONCLUSIONS: This study shows a modest relationship between drinking behavior and MetS by using MR analysis.

Gastroesophageal reflux disease and non-alcoholic fatty liver disease: a two-sample Mendelian randomization combined with meta-analysis.

Accumulating evidence from observational studies have suggested an association between gastroesophageal reflux disease (GERD) and non-alcoholic fatty liver disease (NAFLD). However, due to that such studies are prone to biases, we imported Mendelian randomization (MR) to explore whether the causal association between two diseases exsit. Hence, we aimed to analysis the potential association with MR. The single nucleotide polymorphisms (SNPs) of GERD were retrieved from the genome-wide association study dataset as the exposure. The SNPs of NAFLD were taken from the FinnGen dataset as the outcome. The relationship was analyzed with the assistance of inverse variance weighted, MR-Egger, and weighted median. We also uitilized the MR-Egger intercept, Cochran's Q test, leave-one-out analysis, MR-PRESSO, and Steiger directionality test to evaluate the robustness of the causal association. The meta-analysis were also implemented to give an overall evaluation. Finally, our analysis showed a causal relationship between GERD and NAFLD with aid of MR and meta-analysis (OR 1.71 95% CI 1.40-2.09; P < 0.0001).

Prevalence of Potentially Pathogenic Germline Variants Among Adult Patients in the Philippines With Solid Malignancies Who Underwent Tumor Genomic Profiling.

PURPOSE: In high-income countries, 2%-10% of tumor genomic profiling (TGP) reports reveal incidental pathogenic germline variants. A third of these patients would not qualify for genetic testing on the basis of current guidelines. Our study determined the prevalence of potentially pathogenic germline variants (PPGVs) in TGP results of adult patients with solid malignancies in the Philippines. METHODS: Annotated reports of patients with solid cancers who underwent TGP using FoundationOne or FoundationOne Heme between January 2021 and July 2023 were reviewed. PPGV criteria include having a variant allele frequency of >30% and were categorized as (1) high penetrance gene (HP), founder variant (FV), or variant associated with clinical presentation (VA). Pathogenicity was crosschecked through the ClinVar database. RESULTS: Of 446 patients, 13 PPGV variants were found in 50 (11.2%) patients at a median age of 60.5 years. Of them, 28 (56%) had HP (BRCA1, BRCA2, MSH2, MSH6, MLH1, RAD51C, RAD51D), 25 (50%) patients had VA (APC, SMAD4, CDH1, CDKN2A, PTEN), and two patients with lung cancer had a FV (EGFR p.Thr790Met). Six patients had more than one PPGV. PPGVs were primarily found in patients with colorectal (42% of 50 patients with PPGVs), breast (16%), ovarian (6%), and lung (6%) cancer (P < .001). HP genes were mostly found in female patients (71.4%; P = .03). CONCLUSION: With a PPGV prevalence of 11% in this study, it is important to recognize PPGVs as it can prompt genetic counseling and confirmatory germline testing.