Percorrer por autor "Gomes, Sofia"
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- Common genetic polymorphisms in the ABCB1 gene are associated with risk of major depressive disorder in male Portuguese individualsPublication . Santos, Marlene; Carvalho, Serafim; Lima, Luís; Nogueira, Augusto; Assis, Joana; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiMajor depressive disorder (MDD) is a highly prevalent disorder, which has been associated with an abnormal response of the hypothalamus–pituitary–adrenal (HPA) axis. Reports have argued that an abnormal HPA axis response can be due to an altered P-Glycoprotein (P-GP) function. This argument suggests that genetic polymorphisms in ABCB1 may have an effect on the HPA axis activity; however, it is still not clear if this influences the risk of MDD. Our study aims to evaluate the effect of ABCB1 C1236T, G2677TA and C3435T genetic polymorphisms on MDD risk in a subset of Portuguese patients. DNA samples from 80 MDD patients and 160 control subjects were genotyped using TaqMan SNP Genotyping assays. A significant protection for MDD males carrying the T allele was observed (C1236T: odds ratio (OR) = 0.360, 95% confidence interval [CI]: [0.140– 0.950], p = 0.022; C3435T: OR= 0.306, 95% CI: [0.096–0.980], p = 0.042; and G2677TA: OR= 0.300, 95% CI: [0.100– 0.870], p = 0.013). Male Portuguese individuals carrying the 1236T/2677T/3435T haplotype had nearly 70% less risk of developing MDD (OR = 0.313, 95% CI: [0.118–0.832], p = 0.016, FDR p = 0.032). No significant differences were observed regarding the overall subjects. Our results suggest that genetic variability of the ABCB1 is associated with MDD development in male Portuguese patients. To the best of our knowledge, this is the first report in Caucasian samples to analyze the effect of these ABCB1 genetic polymorphisms on MDD risk.
- Efficiency of the enteral administration of fibbers in the treatment of chronic obstipationPublication . Gomes, Sofia; Moreira, Fernando; Pinho, Cláudia; Ferraz Oliveira, Rita; Oliveira, Ana IsabelIt is estimated that constipation affects 20 % of the population in western countries, leading to a significant impact on people’s quality of life. The administration of some types of fibres has significantly improved the symptoms of constipation over 4-week periods of administration, apparently increasing the frequency of defecation and having a protective effect on the intestinal flora. In addition to their effect on this pathology, fibres have been linked to beneficial outcomes in cardiovascular diseases, diabetes, obesity, colorectal cancer and haemorrhoids. This study focuses on the short-term evaluation of the benefits of fibres on intestinal motility in constipated patients.
- FAS -670A>G genetic polymorphism Is associated with treatment resistant depressionPublication . Santos, Marlene; Carvalho, Serafim; Lima, Luís; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiHippocampal neurogenesis has been suggested as a downstream event of antidepressants (AD) mechanism of action and might explain the lag time between AD administration and the therapeutic effect. Despite the widespread use of AD in the context of Major Depressive Disorder (MDD) there are no reliable biomarkers of treatment response phenotypes, and a significant proportion of patients display Treatment Resistant Depression (TRD). Fas/FasL system is one of the best-known death-receptor mediated cell signaling systems and is recognized to regulate cell proliferation and tumor cell growth. Recently this pathway has been described to be involved in neurogenesis and neuroplasticity. Since FAS -670A>G and FASL -844T>C functional polymorphisms never been evaluated in the context of depression and antidepressant therapy, we genotyped FAS -670A>G and FASL -844T>C in a subset of 80 MDD patients to evaluate their role in antidepressant treatment response phenotypes. We found that the presence of FAS -670G allele was associated with antidepressant bad prognosis (relapse or TRD: OR=6.200; 95% CI: [1.875–20.499]; p=0.001), and we observed that patients carrying this allele have a higher risk to develop TRD (OR=10.895; 95% CI: [1.362–87.135]; p=0.008). Moreover, multivariate analysis adjusted to potentials confounders showed that patients carrying G allele have higher risk of early relapse (HR=3.827; 95% CI: [1.072–13.659]; p=0.039). FAS mRNA levels were down-regulated among G carriers, whose genotypes were more common in TRD patients. No association was found between FASL-844T>C genetic polymorphism and any treatment phenotypes. Small sample size. Patients used antidepressants with different mechanisms of action. To the best of our knowledge this is the first study to evaluate the role of FAS functional polymorphism in the outcome of antidepressant therapy. This preliminary report associates FAS -670A>G genetic polymorphism with Treatment Resistant Depression and with time to relapse. The current results may possibly be given to the recent recognized role of Fas in neurogenesis and/or neuroplasticity.
- IL6-174G > C genetic polymorphism influences antidepressant treatment outcomePublication . Carvalho, Serafim; Santos, Marlene; Lima, Luís; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiMajor depressive disorder is a condition associated with dysregulated cytokine levels; among these, IL6. Furthermore, genetic variations within cytokine genes have been proposed to predict antidepressant treatment outcome. This study aims to evaluate the role of IL6-174G > C and IL6R D358A A > C functional poly-morphisms in antidepressant treatment phenotypes, specifically remission, relapse, and treatment resistant depression (TRD). The referred polymorphisms were genotyped in 80 MDD patients followed at Hospital Magalh~aes Lemos, Portugal, within a period of 27 months. It was found that patients carrying IL6-174 GC genotype present a protection towards the development of TRD (OR ¼ 0.242; 95% CI ¼ 0.068–0.869; p ¼ .038), when compared with GG genotype. Additionally, carriers of IL6-174 CC genotype remit earlier than patients with IL6-174 GG/GC genotypes, with a median time to remission of 6 weeks for CC carriers and 15 weeks for GG or GC carriers (p ¼ .030, Log-rank test). No association was found between IL6R D358A genetic polymorphism and any of the treatment phenotypes evaluated. The IL6-174G > C polymorphism influences antidepressant treatment outcome in this sub-set of MDD patients, providing a putative mechanistic link for the dysregulated IL-6 levels described in the literature in patients with TRD.
- Influence of common ABCB1 genetic polymorphisms in the risk of Major Depressive Desorder and ntidepressant treatment phenotypesPublication . Santos, Marlene; Carvalho, Serafim; Lima, Luís; Nogueira, Augusto; Assis, Joana; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiMajor depressive Disorder (MDD) is a highly prevalent disorder, which has been associated with na abnormal response of hypothalamus-pituitary-adrenal (HPA) axis.
- Influence of il6-174g>c, il6-6331t>c and il6r d358a a>c il-6 genetic polymorphisms in antidepressant treatment phenotypesPublication . Santos, Marlene; Carvalho, Serafim; Lima, Luís; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiSeveral studies associated Major Depressive Disorder (MDD) with an increased production of pro-inflammatory cytokines, such as interleukin 6 (IL-6). Serum IL-6 levels were found to be significantly increased in subjects with MDD and with Treatment Resistant Depression (TRD). Moreover, ketamine, a drug with fast-acting antidepressant properties, has proven to reduce IL-6 levels in rat prefrontal cortex and hippocampus. However, despite the clear influence of IL-6 in the pathophysiology of depression and in antidepressant response, studies evaluating the impact of IL-6 functional genetic polymorphisms on treatment response phenotypes are scarce.
- Life cycle assessment using machine learningPublication . Gomes, Sofia; Faria, Brígida Mónica; Oliveira, Alexandra Alves; Pinto, Edgar; Rodrigues, Matilde; Vieira, Manuela; Faria, Brigida Monica; Oliveira, Alexandra; Pinto, Edgar; Rodrigues, Matilde; Vieira da Silva, ManuelaLife Cycle Assessment (LCA) is a scientific tool that allows calculating the impact of a product or service on the environment, considering the different phases from planting to transportation, commercialization, consumption, and disposal. (1) LCA requires comprehensive data collection of the inputs and outputs such as raw materials, energy, water, used chemicals and pollutants emissions at each stage of the life cycle. Data is usually obtained from different sources like producers or farmers (primary data), literature reviews, government reports and scientific publications (secondary data) or from associations, non-governmental organizations (NGOs) and international organizations. (2) Data processing and analysis are conducted with the aim of uncovering the resultant environmental impacts. This dissertation, integrated into the project REtail using Technology based on Artificial InteLLigence (RETAILL) (3) aims to apply Machine Learning (ML) techniques to develop surrogate LCA models that can be used to estimate LCA results for new products or services. Both public data and data from the Terras de Felgueiras Cooperative (4) will be used to develop the intended model. By preprocessing and modelling this data, the study aims to provide valuable insights for enhancing sustainability in the production of fresh fruits and vegetables. These insights can guide decision-making and drive continuous improvement in the supply chain. The objective of this study is to develop a ML model that estimates LCA results for new products or services and that translates environmental indicators into measurable impacts on both the environment and human health, specifically focusing on the production process. Another objective is to establish clusters that represent similar environmental performance of producers or products. The first step was to review the existing literature on the subject. To accurately determine emissions from agricultural activities, validated equations from the Agri-footprint 6 methodology (5) were employed. Preliminary analyses and descriptive statistics of variables such as fertilizers, pesticides and fungicides applied on agriculture from public data assessments were conducted using tools like SPSS and RapidMiner. This latter was used to carry out the construction of decision trees and clusters. To evaluate clustering models, certain indices were considered namely the Davies-Bouldin Index and the Calinski-Harabasz Index. Meanwhile, for assessing decision trees, measures such as accuracy rate, F- measure, and confusion matrix are well-known evaluation criteria. Subsequently, the ML model was developed using Python programming language and libraries such as Scikit- learn, Pandas, and SciPy. The analysis of public data reveals results from the cultivation of kiwi, watermelon, citrus, tea, and hazelnut across a total of 865 orchards (6). The results include the development of a tailored ML model for LCA phase that allows. the identification and translation of key environmental indicators into environmental and human health impacts. Furthermore, the clustering results of products and producers enables the observation of patterns in the environmental impact of the production process. Overall, this study contributes to the field of sustainability by providing a framework for integrating ML techniques with life cycle assessment, ultimately leading to more efficient and effective practices in agricultural production. The utilization of validated equations from Agri-footprint 6 enhances the reliability of emissions determination from agriculture, contributing to more accurate assessments of environmental impacts. Ultimately, the goal of an LCA is to support informed decision- making and promote more sustainable practices across industries.
- Role of pharmacogenomics in predicting antidepressant response and individualizing therapyPublication . Santos, Marlene; Carvalho, Serafim; Lima, Luís; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiMajor Depressive Disorder (MDD) is a highly prevalent chronic psychiatric condition with significant morbidity. Despite several antidepressants drugs (AD) available, a wide fraction of patients fail to respond, present relapse or display treatment resistant depression (TRD). Pharmacogenomics could help identify patients at risk of relapse or TRD and possibly have a direct impact on personalizing therapy. Additionally, recent studies suggested that immune activation and cytokines may be involved in depression, and its normalization occurs after antidepressant treatment. The proinflammatory cytokines interleukin-18 (IL-18) and IL-6 are less reported in depression, but considered to be relevant since they have been found to be increased in patients with depression.
- Sono e dor musculoesquelética cervical em atletas de voleibolPublication . Figueiras, Benedita; Gomes, Sofia; Faria, Brígida Mónica; Bohn, Lucimere; Miranda, LeonorA dor cervical é frequente em jogadores de voleibol e pode comprometer o desempenho ocupacional e a participação no sono. A terapia ocupacional, numa compreensão holística da problemática da dor cervical e do sono nestes atletas (Leive et al., 2020), enquanto seres ocupacionais (Gomes et al., 2021), poderá desempenhar um relevante papel na avaliação e intervenção terapêutica, e consequentemente na promoção da saúde (Bisht et al., 2021).
- The impact of BDNF, NTRK2, NGFR, CREB1, GSK3B, AKT, MAPK1, MTOR, PTEN, ARC, and SYN1 genetic polymorphisms in antidepressant treatment response phenotypesPublication . Santos, Marlene; Lima, Luis; Carvalho, Serafim; Mota-Pereira, Jorge; Pimentel, Paulo; Maia, Dulce; Correia, Diana; Barroso, M. Fátima; Gomes, Sofia; Cruz, Agostinho; Medeiros, RuiThis study aimed to investigate the influence of genetic variants in neuroplasticity-related genes on antidepressant treatment phenotypes. The BDNF-TrkB signaling pathway, as well as the downstream kinases Akt and ERK and the mTOR pathway, have been implicated in depression and neuroplasticity. However, clinicians still struggle with the unpredictability of antidepressant responses in depressed patients. We genotyped 26 polymorphisms in BDNF, NTRK2, NGFR, CREB1, GSK3B, AKT, MAPK1, MTOR, PTEN, ARC, and SYN1 in 80 patients with major depressive disorder treated according to the Texas Medical Algorithm for 27 months at Hospital Magalhães Lemos, Porto, Portugal. Our results showed that BDNF rs6265, PTEN rs12569998, and SYN1 rs1142636 SNP were associated with treatment-resistant depression (TRD). Additionally, MAPK1 rs6928 and GSK3B rs6438552 gene polymorphisms were associated with relapse. Moreover, we found a link between the rs6928 MAPK1 polymorphism and time to relapse. These findings suggest that the BDNF, PTEN, and SYN1 genes may play a role in the development of TRD, while MAPK1 and GSK3B may be associated with relapse. GO analysis revealed enrichment in synaptic and trans-synaptic transmission pathways and glutamate receptor activity with TRD-associated genes. Genetic variants in these genes could potentially be incorporated into predictive models of antidepressant response.