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- Acute venous thromboembolism plasma and red blood cell metabolomic profiling reveals potential new early diagnostic biomarkers: observational clinical studyPublication . Febra, Claúdia; Saraiva, Joana; Vaz, Fátima; Soares, Nelson; Penque, PenqueBackground: Venous thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is based on complex imaging exams due to the lack of biomarkers. Recent multi-omics based research has contributed to the development of novel biomarkers in cardiovascular diseases. Our aim was to determine whether patients with acute VTE have differences in the metabolomic profile compared to non-acute VTE. Methods: This observational trial included 62 patients with clinical suspicion of acute deep vein thrombosis or pulmonary embolism, admitted to the emergency room. There were 50 patients diagnosed with acute VTE and 12 with non-acute VTE conditions and no significant differences were found between the two groups for clinical and demographic characteristics. Metabolomics assays identified and quantified a final number of 91 metabolites in plasma and 55 metabolites in red blood cells (RBCs). Plasma from acute VTE patients expressed tendency to a specific metabolomic signature, with univariate analyses revealing 23 significantly different molecules between acute VTE patients and controls (p < 0.05). The most relevant metabolic pathway with the strongest impact on the acute VTE phenotype was D-glutamine and D-glutamate (p = 0.001, false discovery rate = 0.06). RBCs revealed a specific metabolomic signature in patients with a confirmed diagnosis of DVT or PE that distinguished them from other acutely diseased patients, represented by 20 significantly higher metabolites and four lower metabolites. Three of those metabolites revealed high performant ROC curves, including adenosine 3',5'-diphosphate (AUC 0.983), glutathione (AUC 0.923), and adenine (AUC 0.91). Overall, the metabolic pathway most impacting to the differences observed in the RBCs was the purine metabolism (p = 0.000354, false discovery rate = 0.68). Conclusions: Our findings show that metabolite differences exist between acute VTE and nonacute VTE patients admitted to the ER in the early phases. Three potential biomarkers obtained from RBCs showed high performance for acute VTE diagnosis. Further studies should investigate accessible laboratory methods for the future daily practice usefulness of these metabolites for the early diagnosis of acute VTE in the ER.
- Artificial Intelligence and multiomics beyond PSA screening in African and Middle Eastern prostate cancer patientsPublication . Al-Shahrabi, Rula; Alkhnbashi, Omer S.; Almarri, Rauda S.B.; Ahmad, Sarfraz; Soares, Nelson C.; Al Shareef, ZainabProstate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specific heterogeneity of PCa underscores the urgent need for advanced strategies to improve detection and risk stratification. This review highlights how multiomics integration, including transcriptomics, DNA methylation, proteomics, and metabolomics, combined with artificial intelligence (AI), can validate biological mechanisms across molecular layers, thereby enhancing diagnostic reliability and biological relevance. While prostate-specific antigen (PSA) testing has significantly shaped PCa epidemiology, its limited specificity and sensitivity have led to widespread overdiagnosis and overtreatment, particularly of indolent tumors. These limitations are especially pronounced in underrepresented populations, notably men of African descent and those in the Middle East and North Africa (MENA) region, where PSA-based screening demonstrates reduced effectiveness. Despite advances in biomarker discovery, current datasets lack sufficient ethnic and regional diversity, raising concerns about the clinical validity and equity of AI-driven models. We argue that equitable precision oncology requires not only technological innovation but also the development of inclusive, demographically representative datasets. This review offers a forward-looking perspective on advancing PCa screening and stratification beyond PSA, with a particular emphasis on addressing the unmet clinical needs of African and Middle Eastern patients.
- Assessing the role of children in the COVID-19 pandemic in Belgium using perturbation analysisPublication . Angeli, Leonardo; Caetano, Constantino Pereira; Franco, Nicolas; Coletti, Pietro; Faes, Christel; Molenberghs, Geert; Beutels, Philippe; Abrams, Steven; Willem, Lander; Hens, NielUnderstanding the evolving role of different age groups in virus transmission is essential for effective pandemic management. We investigated SARS-CoV-2 transmission in Belgium from November 2020 to February 2022, focusing on age-specific patterns. Using a next generation matrix approach integrating social contact data and simulating population susceptibility evolution, we performed a longitudinal perturbation analysis of the effective reproduction number to unravel age-specific transmission dynamics. From November to December 2020, adults in the [18, 60) age group were the main transmission drivers, while children contributed marginally. This pattern shifted between January and March 2021, when in-person education resumed, and the Alpha variant emerged: children aged under 12 years old were crucial in transmission. Stringent social distancing measures in March 2021 helped diminish the noticeable contribution of the [18, 30) age group. By June 2021, as the Delta variant became the predominant strain, adults aged [18, 40) years emerged as main contributors to transmission, with a resurgence in children’s contribution during September-October 2021. This study highlights the effectiveness of our methodology in identifying age-specific transmission patterns.
- Autoencoder/RandomForest-TabPFN for cross-cancer metabolomics: prostate and breast cancer diagnosis using paper spray and ion mobility-mass spectrometry techniquesPublication . Hauns, Sven; Pinto, Frederico G.; Khyriem, Costerwell; Singh, Ankita; Al-Sadi, Azzat; Yazeedi, Talal Al; Mohammad, Rasheed; Cisse, Babacar; Garrett, Timothy J.; Uddin, Mohammed; Soares, Nelson C.; Backofen, Rolf; Alkhnbashi, Omer S.Accurate and rapid disease diagnosis, particularly in prostate cancer (PC) and breast cancer (BC), is critical for early intervention and improved patient outcomes. Metabolomic signatures represent a robust molecular framework for elucidating cancer-associated biochemical reprogramming. The use of artificial intelligence (AI) in biology in recent years has become widespread and promising. This study introduces a novel predictive method that integrates an Autoencoder, random forest-based feature selection and Tabular Prior-data Fitted Network (TabPFN) to achieve high diagnostic accuracy from metabolomics data of prostate and BC patients. The datasets were acquired using paper spray ionization mass spectrometry and flow injection-traveling-wave ion mobility-mass spectrometry of individuals diagnosed with PC and BC. When leveraging metabolomic profiling data from two distinct sources, PC urine and serum samples, the proposed model achieved an accuracy up to 98.75% in distinguishing diseased from healthy conditions. Additionally, we employed a BC dataset containing metabolic and lipidomic signatures acquired from core needle biopsies using a miniature MS platform coupled with PSI to assess the fidelity of our implementation across distinct cancer types. Our results on a well-characterized targeted dataset show that we can effectively reduce high-dimensional data into latent feature representations. At the same time, TabPFN captures tumor progression-related changes and feature interaction, thereby enhancing the possibility that the model will be a highly potent and effective tool for stage-specific diagnostic precision. Most existing machine learning approaches for disease diagnosis primarily rely on imaging, genomics, or clinical parameters, often overlooking the critical role of metabolites in identifying disease-specific biochemical signatures. By integrating metabolite-specific data with a robust deep-learning approach, this study demonstrates the transformative potential of AI in metabolomics-based diagnostics. The proposed model offers scalability and versatility, with applications extending beyond oncology to a much broader disease profiling aspect. These findings emphasize the value of combining multi-source metabolomic data with deep learning to advance personalized medicine and enhance diagnostic efficiency in clinical practice.
- Baseline data and associations between urinary biomarkers of polycyclic aromatic hydrocarbons, blood pressure, hemogram, and lifestyle among wildland firefightersPublication . Barros, Bela; Paiva, Ana Margarida; Oliveira, Marta; Alves, Sara; Esteves, Filipa; Fernandes, Adília; Vaz, Josiana; Slezakova, Klara; Costa, Solange; Teixeira, João Paulo; Morais, SimoneIntroduction: Available literature has found an association between firefighting and pathologic pathways leading to cardiorespiratory diseases, which have been linked with exposure to polycyclic aromatic hydrocarbons (PAHs). PAHs are highlighted as priority pollutants by the European Human Biomonitoring Initiative in occupational and non-occupational contexts. Methods: This cross-sectional study is the first to simultaneously characterize six creatinine-adjusted PAHs metabolites (OHPAHs) in urine, blood pressure, cardiac frequency, and hemogram parameters among wildland firefighters without occupational exposure to fire emissions (> 7 days), while exploring several variables retrieved via questionnaires. Results: Overall, baseline levels for total OHPAHs levels were 2 to 23-times superior to the general population, whereas individual metabolites remained below the general population median range (except for 1-hydroxynaphthalene+1-hydroxyacenaphtene). Exposure to gaseous pollutants and/or particulate matter during work-shift was associated with a 3.5-fold increase in total OHPAHs levels. Firefighters who smoke presented 3-times higher total concentration of OHPAHs than non-smokers (p < 0.001); non-smoker females presented 2-fold lower total OHPAHs (p = 0.049) than males. 1-hydroxypyrene was below the recommended occupational biological exposure value (2.5 μg/L), and the metabolite of carcinogenic PAH (benzo(a)pyrene) was not detected. Blood pressure was above 120/80 mmHg in 71% of subjects. Firefighters from the permanent intervention team presented significantly increased systolic pressure than those who performed other functions (p = 0.034). Tobacco consumption was significantly associated with higher basophils (p = 0.01–0.02) and hematocrit (p = 0.03). No association between OHPAHs and blood pressure was found. OHPAHs concentrations were positively correlated with monocyte, basophils, large immune cells, atypical lymphocytes, and mean corpuscular volume, which were stronger among smokers. Nevertheless, inverse associations were observed between fluorene and pyrene metabolites with neutrophils and eosinophils, respectively, in non-smokers. Hemogram was negatively affected by overworking and lower physical activity. Conclusion: This study suggests possible associations between urinary PAHs metabolites and health parameters in firefighters, that should be further assessed in larger groups.
- Biomonitoring of firefighters’ exposure to priority pollutant metal(loid)s during wildland fire combat missions: Impact on urinary levels and health risksPublication . Paiva, Ana Margarida; Barros, Bela; Azevedo, Rui; Oliveira, Marta; Alves, Sara; Esteves, Filipa; Fernandes, Adília; Vaz, Josiana; Alves, Maria José; Slezakova, Klara; Pereira, Maria do Carmo; Teixeira, João Paulo; Costa, Solange; Almeida, Agostinho; Morais, SimoneWildland firefighters are exposed to metal(loid)s released during wildfires through vegetation combustion, which also promotes remobilization of accumulated anthropogenic metal(loid)s. Studies biomonitoring metal(loid)s exposure promoted exclusively by wildfire suppression activities are lacking. This work aimed to characterize, for the first time, the impact of real-life wildland firefighting operations on urinary levels of priority pollutant metal(loid)s [14 included in ATSDR, 11 in USEPA, and 4 in Human Biomonitoring for Europe Initiative priority lists] in firefighters. Spot urines were sampled pre-exposure (105 non-smokers, 76 smokers) and post-exposure to firefighting activities (20 non-smokers, 25 smokers); among those, paired samples were collected from 14 non-smoking and 24 smoking firefighters. Smokers displayed significantly higher baseline levels of zinc (28 %), lithium (29 %), cadmium (55 %), rubidium (13 %), and copper (20 %) than non-smokers. Following wildfire suppression, the concentration of the WHO potentially toxic metal(loid)s rose from 2 % to 3 % in smokers and 2 % to 5 % in non-smokers (up to 4 % for all firefighters and up to 5 % in paired samples). Levels of nickel (33-53 %), antimony (45-56 %), and cesium (40-47 %) increased significantly post-exposure in non-smokers (in all firefighters and in paired samples), whose urinary concentrations were generally more impacted by wildfire emissions than those of smokers. Arsenic (80 %) displayed the only significant increase post-exposure in smokers, being the best discriminant of exposure to wildfire emissions in these subjects. Significant positive correlations were found for age and/or career length with cadmium, lead, barium, strontium, and mercury, and for body mass index with arsenic. The reference/guidance values were exceeded for arsenic, zinc, cesium, nickel, antimony, cadmium, lead, thallium, mercury, copper, and cobalt in 1-90 % of firefighters suggesting augmented health risks due to wildfire combating and emphasizing the need of mitigation strategies. This study also provides biomonitoring data to help setting reference values for the occupationally exposed part of population.
- Biomonitoring of polycyclic aromatic hydrocarbons exposure and short-time health effects in wildland firefighters during real-life fire eventsPublication . Paiva, Ana Margarida; Barros, Bela; Oliveira, Marta; Alves, Sara; Esteves, Filipa; Fernandes, Adília; Vaz, Josiana; Slezáková; Teixeira, João Paulo; Costa, Solange; Morais, SimoneHuman biomonitoring data retrieved from real-life wildland firefighting in Europe and, also, worldwide are scarce. Thus, in this study, 176 Portuguese firefighters were biomonitored pre- and post- unsimulated wildfire combating (average:12-13 h; maximum: 55 h) to evaluate the impact on the levels of urinary polycyclic aromatic hydrocarbons hydroxylated metabolites (OHPAH; quantified by high-performance liquid chromatography with fluorescence detection) and the associated short-term health effects (symptoms, and total and differentiated white blood cells). Correlations between these variables and data retrieved from the self-reported questionnaires were also investigated. Firefighters were organized into four groups according to their exposure to wildfire emissions and their smoking habits: non-smoking non-exposed (NSNExp), non-smoking exposed (NSExp), smoking non-exposed (SNExp), and smoking and exposed (SExp). The most abundant metabolites were 1-hydroxynaphthalene and 1-hydroxyacenaphthene (1OHNaph + 1OHAce) (98-99 %), followed by 2-hydroxyfluorene (2OHFlu) (0.2-1.1 %), 1-hydroxyphenanthrene (1OHPhen) (0.2-0.4 %), and 1-hydroxypyrene (1OHPy) (0.1-0.2 %); urinary 3-hydroxybenzo(a)pyrene was not detected. The exposure to wildfire emissions significantly elevated the median concentrations of each individual and total OHPAH compounds in all groups, but this effect was more pronounced in non-smoking (1.7-4.2 times; p ≤ 0.006) than in smoking firefighters (1.3-1.6 times; p ≤ 0.03). The greatest discriminant of exposure to wildfire emissions was 1OHNaph + 1OHAce (increase of 4.2 times), while for tobacco smoke it was 2OHFlu (increase of 10 times). Post-exposure, white blood cells count significantly increased ranging from 1.4 (smokers, p = 0.025) to 3.7-fold (non-smokers, p < 0.001), which was accompanied by stronger significant correlations (0.480 < r < 0.882; p < 0.04) between individual and total OHPAH and total white blood cells (and lymphocytes > monocytes > neutrophils in non-smokers), evidencing the impact of PAH released from wildfire on immune cells. This study identifies Portuguese firefighters with high levels of biomarkers of exposure to PAH and points out the importance of adopting biomonitoring schemes, that include multiple biomarkers of exposure and biomarkers of effect, and implementing mitigations strategies.
- Comparative analysis of hybrid‑SNP microarray and nanopore sequencing for detection of large‑sized copy number variants in the human genomePublication . Silva, Catarina; Ferrão, José; Marques, Bárbara; Pedro, Sónia; Correia, Hildeberto; Valente, Ana; Rodrigues, António Sebastião; Vieira, LuísBackground: Nanopore sequencing is a technology that holds great promise for identifying all types of human genome variations, particularly structural variations. In this work, we used nanopore sequencing technology to sequence 2 human cell lines at low depth of coverage to call copy number variations (CNV), and compared the results variant by variant with chromosomal microarray (CMA) results. Results: We analysed sequencing data using CuteSV and Sniffles2 variant callers, compared breakpoints based on hybrid-SNP microarray, nanopore sequencing and Sanger sequencing, and analysed CNV coverage. From a total of 48 high confidence variants (truth set), variant calling detected 79% of the truth set variants, increasing to 86% for interstitial CNV. Simultaneous use of the 2 callers slightly increased variant calling. Both callers performed better when calling CNV losses than gains. Variant sizes from CMA and nanopore sequencing showed an excellent correlation, with breakpoints determined by nanopore sequencing differing by only 20 base pairs on average from Sanger sequencing. Nanopore sequencing also revealed that four variants concealed genomic inversions undetectable by CMA. In the 10 CNV not called in nanopore sequencing, 8 showed coverage evidence of genomic loss or gain, highlighting the need to improve SV calling algorithms performance. Conclusions: Nanopore sequencing offers advantages over CMA for structural variant detection, including the identification of multiple variant types and their breakpoints with increased precision. However, further improvements in variant calling algorithms are still needed for nanopore sequencing to become a highly robust and standardized approach for a comprehensive analysis of genomic structural variation.
- A Comparative Overview of the Role of Human Ribonucleases in Nonsense-Mediated mRNA DecayPublication . da Costa, Paulo J.; Menezes, Juliane; Guedes, Raquel; Reis, Filipa P.; Teixeira, Alexandre; Saramago, Margarida; Viegas, Sandra C.; Arraiano, Cecília M.; Romão, LuísaEukaryotic cells possess surveillance mechanisms that detect and degrade defective transcripts. Aberrant transcripts include mRNAs with a premature termination codon (PTC), targeted by the nonsense-mediated decay (NMD) pathway, and mRNAs lacking a termination codon, targeted by the nonstop decay (NSD) pathway. The eukaryotic exosome, a ribonucleolytic complex, plays a crucial role in mRNA processing and turnover through its catalytic subunits PM/Scl100 (Rrp6 in yeast), DIS3 (Rrp44 in yeast), and DIS3L1. Additionally, eukaryotic cells have other ribonucleases, such as SMG6 and XRN1, that participate in RNA surveillance. However, the specific pathways through which ribonucleases recognize and degrade mRNAs remain elusive. In this study, we characterized the involvement of human ribonucleases, both nuclear and cytoplasmic, in the mRNA surveillance mechanisms of NMD and NSD. We performed knockdowns of SMG6, PM/Scl100, XRN1, DIS3, and DIS3L1, analyzing the resulting changes in mRNA levels of selected natural NMD targets by RT-qPCR. Additionally, we examined the levels of different human β-globin variants under the same conditions: wild-type, NMD-resistant, NMD-sensitive, and NSD-sensitive. Our results demonstrate that all the studied ribonucleases are involved in the decay of certain endogenous NMD targets. Furthermore, we observed that the ribonucleases SMG6 and DIS3 contribute to the degradation of all β-globin variants, with an exception for βNS in the former case. This is also the case for PM/Scl100, which affects all β-globin variants except the NMD-sensitive variants. In contrast, DIS3L1 and XRN1 show specificity for β-globin WT and NMD-resistant variants. These findings suggest that eukaryotic ribonucleases are target-specific rather than pathway-specific. In addition, our data suggest that ribonucleases play broader roles in mRNA surveillance and degradation mechanisms beyond just NMD and NSD.
- Cumulus cell DNA damage linked to fertilization success in females with an ovulatory dysfunction phenotypePublication . Rodrigues, Bárbara; Sousa, Vanessa; Esteves, Filipa; Vale-Fernandes, Emídio; Costa, Solange; Sousa, Daniela; Brandão, Raquel; Leal, Carla; Pires, Joana; Gaivão, Isabel; Teixeira, João Paulo; Nogueira, António J.A.; Jorge, PaulaIntracytoplasmic sperm injection (ICSI) is a widely used technique in fertility centers. ICSI success depends on both nuclear and cytoplasmic oocyte maturation. Cumulus cells, which surround the oocytes, play a pivotal role in oocyte competence. However, the significance of DNA damage in cumulus cells as a marker of fertilization success remains largely unexplored. This study aims to investigate the relationship between DNA damage in cumulus cells of females undergoing ICSI, and oocyte competence, with a focus on in vitro fertilization (IVF) outcomes. We employed the alkaline comet assay to assess DNA damage levels (%TDNA) in cumulus cells and whole blood from 22 potentially fertile females and 35 infertile females, including 20 with an ovulatory disfunction phenotype. Our results revealed significant differences between the levels of %TDNA in cumulus cells and blood. Females with an ovulatory dysfunction phenotype exhibited higher levels of %TDNA in cumulus cells compared to potentially fertile females. Additionally, within the group of females with ovulatory dysfunction, a significant correlation was observed between %TDNA levels and the number of oocytes with two pronuclei. Our findings suggest that blood does not accurately reflect DNA damage in cumulus cells, which was correlated with the fertilization success in females with ovulatory dysfunction. High levels of %TDNA in cumulus cells were associated with a higher likelihood of successful fertilization. Moreover, our results imply that low levels of %TDNA may be linked to oocytes that fail to complete maturation and, consequently, do not fertilize (oocytes with zero pronuclei). Further research with larger cohorts is necessary to validate these findings and to explore potential applications in female fertility. However, our study provides evidence that DNA damage in cumulus cells may serve as a valuable biomarker for predicting fertilization success and oocyte competence.
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