Francisco Jose Sanz Lopez
@uv.es
Scopus Publications
- Endometrial cortisol level and its relationship with psychological stress, molecular tissue changes, and clinical outcomes in infertile women
Diana Marti-Garcia, Patricia Sebastian-Leon, Pilar Dolz del Castellar, Almudena Devesa-Peiro, María del Carmen Vidal, Laura Caracena, Francisco José Sanz, Rebeca Esteve-Moreno, Estrella Dura-Ferrandis, Patricia Diaz-Gimeno
Scientific Reports, 2026
Despite fertility treatments are a stressful journey, there remains a lack of studies assessing how stress is affecting endometrial function in infertility. This prospective cohort study, including 84 endometrial biopsies, aims to elucidate the effect of stress, measured by different approaches, in the endometrial function in In Vitro Fertilization treatments. This population was molecularly characterized by measuring endometrial cortisol levels and endometrial transcriptomic profiles, and psychological aspects measured by the State-Trait Anxiety Inventory test. A relationship between endometrial cortisol levels and psychological stress punctuation was found. Psychologically stressed patients had increased endometrial cortisol levels (5.4 ng/g vs. 3.45 ng/g; p = 0.05, in the limit of significance) and cortisol levels correlated with psychological test punctuations (cor = 0.97, p < 0.05). From the clinical point of view, patients with cortisol levels ≥ 13.9 ng/g had a 32% relative higher risk of not becoming pregnant (p = 0.003). Molecular evidences showed, increased cortisol levels were significantly associated with changes in 182 genes in endometrium (p < 0.001) and psychological stress scores were significantly associated with changes in 12 genes involved in key functions for embryo implantation and development (p < 0.001). Psychological evaluation could serve as a less-invasive screening tool to identify at-risk infertility patients and implement preventive psychological interventions in the clinical setting. - Descriptive overview of gene variants potentially affecting female infertility treatments: A systematic review
Asunta Martinez-Martinez, Francisco José Sanz, Pablo Garcia-Acero, Patricia Sebastian-Leon, Patricia Diaz-Gimeno
Biomedicine and Pharmacotherapy, 2026
Pharmacogenetics is an emerging discipline that explores how genetic variants affect drug response, potentially leading to side effects or treatment failure. Although widely applied in other medical specialties, its use in female reproductive medicine remains limited. The objective of this systematic review is to investigate and summarize the current state of knowledge in pharmacogenetics as it applies to female reproductive diseases or conditions, aiming to support clinical application. A comprehensive systematic search was conducted using PubMed up to September 2025, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords related to female infertility and pharmacogenetics/pharmacogenomics were used. The search yielded 603 articles, of which 75 were ultimately included. Evaluation of the studies identified 46 genetic variants affecting drug response in the field of female infertility. Pharmacogenetic research in this field remains limited, with notable gaps for conditions such as endometriosis and uterine fibroids that influence reproductive outcomes. The variants associated with responses during infertility therapies could contribute to preventive medicine aimed at avoiding reduced drug efficacy, excessive responses, or the development of adverse effects. Additionally, greater dissemination of these findings within clinical settings is essential to improve awareness and understanding in this field and to facilitate the study of these variants and their potential translation into clinical practice. This review summarizes the current state of pharmacogenetics in the context of female infertility and aims to serve as a reference and to encourage further research in this area. • Genetic variants influence drug response in female infertility treatments. • FSHR is the most studied gene affecting ovarian stimulation outcomes. • Pharmacogenetics will improve drug efficacy and reduce adverse effects in ART. • There is a lack of studies addressing ADME-related genes in infertility treatments. • Evidence gaps remain for endometriosis and uterine fibroids studies. - Epigenetic clock timing in the endometrium of women undergoing in vitro fertilization
Nataly Del Aguila, Francisco Jose Sanz, Patricia Sebastian-Leon, Mónica Romeu, Asunta Martinez-Martinez, Antonio Parraga-Leo, Ana Monzó, Maria del Carmen Vidal, Immaculada Sanchez-Ribas, Marcos Ferrando, Rebeca Esteve-Moreno, Antonio Pellicer, Patricia Diaz-Gimeno
Fertility and Sterility, 2026 - Advanced maternal age was associated with an annual decline in reproductive success despite use of donor oocytes: a retrospective study
Patricia Sebastian-Leon, Francisco Jose Sanz, Pietro Molinaro, Antonio Pellicer, Patricia Diaz-Gimeno
Fertility and Sterility, 2025 - Stratifying IVF population endometria using a prognosis gradient independent of endometrial timing
Josefa Maria Sanchez-Reyes, Antonio Parraga-Leo, Patricia Sebastian-Leon, Maria del Carmen Vidal, Diana Marti-Garcia, Katharina Spath, Imma Sanchez-Ribas, Francisco Jose Sanz, Nuria Pellicer, Jose Remohi, Dagan Wells, Antonio Pellicer, Patricia Diaz-Gimeno
Human Reproduction, 2025
STUDY QUESTION Can the disrupted window of implantation (WOI) be stratified according to transcriptomic patterns associated with reproductive success in IVF patients undergoing HRT? SUMMARY ANSWER There are four transcriptomic patterns independent of endometrial timing associated with a gradient of reproductive prognosis underlying different molecular pathomechanisms. WHAT IS KNOWN ALREADY A molecular heterogeneous profile independent of endometrial timing has been discovered as a cause of implantation failure that disrupt the endometrial transcriptome in the mid-secretory phase. However, the molecular heterogeneous patterns underlying the disruption remain poorly identify and understood. Characterizing the molecular heterogeneity of this endometrial disruption is crucial to develop personalized and more accurate diagnostic tools for preventive medicine, particularly for patients with a high risk of endometrial failure. STUDY DESIGN, SIZE, DURATION In this multicenter prospective study, 195 IVF patients undergoing HRT with endometrial biopsy collection, during mid-secretory phase for endometrial progression evaluation, were recruited between January 2019 and August 2022. Out of 195 patients, 131 were finally included in the following analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS Endometrial biopsies were processed for whole endometrial transcriptome analysis using RNA-Sequencing. To identify disruptions in the WOI, the transcriptomic variation due to cyclic endometrial tissue changes was removed. Out of 195 biopsies sequenced, 131 were derived from patients that met the clinical criteria to be classified as implantation failure group (≥3 implantation failures, n = 32) or control group (&lt;3 implantation failures, n = 99). An artificial intelligence (AI) model, based on two supervised learning algorithms: support vector machine (SVM) and k-nearest neighbors (kNN), was performed with 131 patients that were randomly allocated to training (n = 105) and test (n = 26) sets for biomarker signature discovery and assessment of predictive performance, respectively. The reproductive outcomes of the single embryo transfer immediately after biopsy collection were analyzed. Differential expression and functional analyses were performed to characterize molecular profiles. Finally, a quantitative PCR (qPCR) assay was used to corroborate the differential expression of six potential biomarkers. MAIN RESULTS AND THE ROLE OF CHANCE With the dichotomous clinical classification of poor or good reproductive prognosis, there was no transcriptomic distinction between patients with a history of implantation failures during HRT endometrial preparation. Alternatively, using an AI model to stratify IVF patients based on the probability of endometrial disruption revealed molecular and clinical differences between patterns. Patients were stratified into four reproductive prognosis-related profiles: p1 (n = 24), p2 (n = 14), c2 (n = 32) and c1 (n = 61). The highest pregnancy rate (PR) was associated with c1 (91%) and the highest ongoing pregnancy rate (OPR) was associated with c2 (78%), linking these profiles to good reproductive prognoses. On the other hand, p1 had the highest biochemical miscarriage rate (43%) while p2 had the highest clinical miscarriage rate (43%). Notably, both p1 and p2 were related to lower PR and OPR, supporting that these profiles were associated with poor prognoses. Regarding the functional characterization in the poor prognosis profiles that were linked to miscarriages, p1 was associated with an excessive immune response against the embryo during early pregnancy stages, while p2 was initially immune-tolerant but rejected the fetus in later stages due to the lack of metabolic response. LIMITATIONS, REASONS FOR CAUTION Due to the heterogeneous character of the disrupted WOI and the limited sample size of the different stratified groups, the AI model has limited population inference. However, our significant promising findings provide strong leads for further clinical studies with larger sample sizes. WIDER IMPLICATIONS OF THE FINDINGS This new transcriptomic taxonomy associated with distinct reproductive outcomes provides clues to design new and more accurate evaluation tools for endometrial-factor infertility. Furthermore, it enables tailoring therapeutic strategies to apply a personalized medicine to each patient suffering from endometrial-factor infertility, improving their odds of getting pregnant. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by the IVI Foundation (1706-FIVI-048-PD); Instituto de Salud Carlos III (ISCIII) and co-funded by the European Regional Development Fund “A way to make Europe” (PI19/00537 [P.D.-G.]) as well as Instituto Carlos III (ISCIII) through project (PI23/00806 [P.D.-G.]) and co-funded by European Union. Patricia Diaz-Gimeno is supported by Instituto de Salud Carlos III (ISCIII) through the Miguel Servet program (CP20/00118) co-funded by the European Union. Patricia Sebastian-Leon and Francisco Jose Sanz are funded by Instituto de Salud Carlos III (ISCIII) through the Sara Borrell postdoctoral program (CD21/00132 [P.S.-L.] and CD23/00032 [F.J.S.]) co-financed by the European Union. Josefa Maria Sanchez-Reyes was supported by a predoctoral fellowship program of the Generalitat Valenciana (ACIF/2018/072 and BEFPI/2020/028). Antonio Parraga-Leo (FPU18/01777) and Diana Marti-Garcia (FPU19/03247) were supported by predoctoral fellowship programs of the Spanish Ministry of Science, Innovation and Universities. The authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER Not applicable. - Are We Considering All the Potential Drug–Drug Interactions in Women’s Reproductive Health? A Predictive Model Approach
Pablo Garcia-Acero, Ismael Henarejos-Castillo, Francisco Jose Sanz, Patricia Sebastian-Leon, Antonio Parraga-Leo, Juan Antonio Garcia-Velasco, Patricia Diaz-Gimeno
Pharmaceutics, 2025
Background: Drug–drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women’s healthcare. Methods: A DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein–protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. Results: This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25%, respectively). Some were expected to improve current therapies (n = 23), while others would cause harmful effects (n = 11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Conclusions: These results show the importance of DDI studies aimed at identifying those that might compromise or improve their efficacy, which could lead to personalizing female reproductive therapies. - Whole-exome sequencing and Drosophila modelling reveal mutated genes and pathways contributing to human ovarian failure
Ismael Henarejos-Castillo, Francisco José Sanz, Cristina Solana-Manrique, Patricia Sebastian-Leon, Ignacio Medina, José Remohi, Nuria Paricio, Patricia Diaz-Gimeno
Reproductive Biology and Endocrinology, 2024
BACKGROUND: Ovarian failure (OF) is a multifactorial, complex disease presented by up to 1% of women under 40 years of age. Despite 90% of patients being diagnosed with idiopathic OF, the underlying molecular mechanisms remain unknown, making it difficult to personalize treatments for these patients in the clinical setting. Studying the presence and/or accumulation of SNVs at the gene/pathway levels will help describe novel genes and characterize disrupted biological pathways linked with ovarian failure. METHODS: Ad-hoc case-control SNV screening conducted from 2020 to 2023 of 150 VCF files WES data included Spanish IVF patients with (n = 118) and without (n = 32) OF (< 40 years of age; mean BMI 22.78) along with GnomAD (n = 38,947) and IGSR (n = 1,271; 258 European female VCF) data for pseudo-control female populations. SNVs were prioritized according to their predicted deleteriousness, frequency in genomic databases, and proportional differences across populations. A burden test was performed to reveal genes with a higher presence of SNVs in the OF cohort in comparison to control and pseudo-control groups. Systematic in-silico analyses were performed to assess the potential disruptions caused by the mutated genes in relevant biological pathways. Finally, genes with orthologues in Drosophila melanogaster were considered to experimentally validate the potential impediments to ovarian function and reproductive potential. RESULTS: Eighteen genes had a higher presence of SNVs in the OF population (FDR < 0.05). AK2, CDC27, CFTR, CTBP2, KMT2C, and MTCH2 were associated with OF for the first time and their silenced/knockout forms reduced fertility in Drosophila. We also predicted the disruption of 29 sub-pathways across four signalling pathways (FDR < 0.05). These sub-pathways included the metaphase to anaphase transition during oocyte meiosis, inflammatory processes related to necroptosis, DNA repair mismatch systems and the MAPK signalling cascade. CONCLUSIONS: This study sheds light on the underlying molecular mechanisms of OF, providing novel associations for six genes and OF-related infertility, setting a foundation for further biomarker development, and improving precision medicine in infertility. - Age-related uterine changes and its association with poor reproductive outcomes: a systematic review and meta-analysis
Diana Marti-Garcia, Asunta Martinez-Martinez, Francisco Jose Sanz, Almudena Devesa-Peiro, Patricia Sebastian-Leon, Nataly del Aguila, Antonio Pellicer, Patricia Diaz-Gimeno
Reproductive Biology and Endocrinology, 2024
BACKGROUND: The decline in women's fertility becomes clinically relevant between 35-40 years old, when there is insufficient ovarian activity, and it becomes more difficult to achieve pregnancy naturally and through artificial reproductive technologies. A competent endometrium is required for establishing and maintaining a pregnancy to term, however, experts in the field underestimate the contribution of endometrial age and its impact on reproductive outcomes remains unclear. STUDY DESIGN: A systematic search of full-text articles available in PubMed was conducted to retrieve relevant studies published until March 2023. Search terms included: endometrium, uterus, age, aging, pregnancy, and oocyte donation. Terms related to reproductive pathologies were excluded. Eligibility criteria included original, rigorous, and accessible peer-reviewed work, published in English on the effect of age on the uterus and endometrium. RESULTS: From 11,354 records identified, 142 studies were included for systematic review, and 59 were eligible for meta-analysis of endometrial thickness (n = 7), pregnancy rate (n = 22), implantation rate (n = 10), live birth rate (n = 10) and pregnancy loss rate (n = 11). Studies for the meta-analysis of reproductive outcomes only included transfers of embryos from ovum donation (ovum donors < 36 years old). Age shrinks the uterus; depletes endometrial blood supply through narrow uterine veins and a progressive loss of uterine spiral arteries; disrupts endometrial architecture and cellular composition; alters hormone production, shortening menstrual cycle length and impeding endometrial progression to the secretory stage; and dysregulates key endometrial functions such as adhesion, proliferation, apoptosis, and receptivity, among others. Women over 35-40 years old had significantly thinner endometrium (MD 0.52 mm). Advanced maternal age is associated with lower odds of achieving implantation (27%) and clinical pregnancy (20%), or higher odds of experiencing pregnancy loss (44%). CONCLUSION: Due to the effect of age on endometrium reported in this review, managing patients with advanced maternal age may require considering the endometrial factor as a potential tissue to treat with anti-aging strategies. This review provides researchers and clinicians with an updated and in-depth summary of this topic, encouraging the development of new tailored anti-aging and preventive strategies for precision medicine in endometrial factor in infertility. TRIAL REGISTRATION: PROSPERO 2023 (CRD42023416947). - Evaluation of type 1 diabetes mellitus as a risk factor of Parkinson's disease in a Drosophila model
Francisco José Sanz, Guillermo Martínez‐Carrión, Cristina Solana‐Manrique, Nuria Paricio
Journal of Experimental Zoology Part A Ecological and Integrative Physiology, 2023
Diabetes mellitus (DM) is a chronic metabolic disease characterized by high blood glucose levels, resulting from insulin dysregulation. Parkinson's disease (PD) is the most common neurodegenerative motor disorder caused by the selective loss of dopaminergic (DA) neurons in the substantia nigra pars compacta. DM and PD are both age-associated diseases that are turning into epidemics worldwide. Previous studies have indicated that type 2 DM might be a risk factor of developing PD. However, scarce information about the link between type 1 DM (T1DM) and PD does exist. In this work, we have generated a Drosophila model of T1DM based on insulin deficiency to evaluate if T1DM could be a risk factor to trigger PD onset. As expected, model flies exhibited T1DM-related phenotypes such as insulin deficiency, increased content of carbohydrates and glycogen, and reduced activity of insulin signaling. Interestingly, our results also demonstrated that T1DM model flies presented locomotor defects as well as reduced levels of tyrosine hydroxylase (a marker of DA neurons) in brains, which are typical PD-related phenotypes. In addition, T1DM model flies showed elevated oxidative stress levels, which could be causative of DA neurodegeneration. Therefore, our results indicate that T1DM might be a risk factor of developing PD, and encourage further studies to shed light into the exact link between both diseases. - Disease-Modifying Effects of Vincamine Supplementation in Drosophila and Human Cell Models of Parkinson’s Disease Based on DJ-1 Deficiency
Francisco José Sanz, Cristina Solana-Manrique, Nuria Paricio
ACS Chemical Neuroscience, 2023
Parkinson’s disease (PD) is an incurable neurodegenerative disorder caused by the selective loss of dopaminergic neurons in the substantia nigra pars compacta. Current therapies are only symptomatic, and are not able to stop or delay its progression. In order to search new and more effective therapies, our group carried out a high-throughput screening assay, identifying several candidate compounds able to suppress motor defects in DJ-1β mutant flies (a Drosophila model of familial PD) and to reduce oxidative stress (OS)-induced lethality in DJ-1-deficient SH-SY5Y human cells. One of them was vincamine (VIN), a natural alkaloid obtained from the leaves of Vinca minor. Our results showed that VIN is able to suppress PD-related phenotypes in both Drosophila and human cell PD models. Specifically, VIN reduced OS levels in PD model flies. Besides, VIN diminished OS-induced lethality by decreasing apoptosis, increased mitochondrial viability and reduced OS levels in DJ-1-deficient human cells. In addition, we have demonstrated that VIN is able to exert its beneficial role, at least partially, by the inhibition of voltage-gated Na+ channels. Therefore, we propose that these channels might be a promising target in the search for new compounds to treat PD, and that VIN constitutes a potential therapeutic treatment for the disease. - Exploring the link between Parkinson's disease and type 2 diabetes mellitus in Drosophila
Francisco José Sanz, Cristina Solana‐Manrique, Joaquín Lilao‐Garzón, Yeray Brito‐Casillas, Silvia Muñoz‐Descalzo, Nuria Paricio
FASEB Journal, 2022 - Antioxidant and Neuroprotective Effects of Carnosine: Therapeutic Implications in Neurodegenerative Diseases
Cristina Solana-Manrique, Francisco José Sanz, Guillermo Martínez-Carrión, Nuria Paricio
Antioxidants, 2022 - Metabolic Alterations in a Drosophila Model of Parkinson’s Disease Based on DJ-1 Deficiency
Cristina Solana-Manrique, Francisco José Sanz, Isabel Torregrosa, Martina Palomino-Schätzlein, Carolina Hernández-Oliver, Antonio Pineda-Lucena, Nuria Paricio
Cells, 2022 - Modeling of Parkinson’s disease in Drosophila based on DJ-1 deficiency
Francisco José Sanz, Cristina Solana-Manrique, Nuria Paricio
Handbook of Animal Models in Neurological Disorders, 2022 - A High-Throughput Chemical Screen in DJ-1β Mutant Flies Identifies Zaprinast as a Potential Parkinson’s Disease Treatment
Francisco José Sanz, Cristina Solana-Manrique, Josema Torres, Esther Masiá, María J. Vicent, Nuria Paricio
Neurotherapeutics, 2021 - Oxidative modification impairs SERCA activity in Drosophila and human cell models of Parkinson's disease
Cristina Solana-Manrique, Verónica Muñoz-Soriano, Francisco José Sanz, Nuria Paricio
Biochimica Et Biophysica Acta Molecular Basis of Disease, 2021 - Enhanced activity of glycolytic enzymes in Drosophila and human cell models of Parkinson's disease based on DJ-1 deficiency
Cristina Solana-Manrique, Francisco José Sanz, Edna Ripollés, M. Carmen Bañó, Josema Torres, Verónica Muñoz-Soriano, Nuria Paricio
Free Radical Biology and Medicine, 2020 - Drosophila as a model system for the identification of pharmacological therapies in neurodegenerative diseases
Cristina Solana-Manrique, María Dolores Moltó, Pablo Calap-Quintana, Francisco José Sanz, José Vicente Llorens, Nuria Paricio
Insights into Human Neurodegeneration Lessons Learnt from Drosophila, 2019 - Cbt modulates Foxo activation by positively regulating insulin signaling in Drosophila embryos
Verónica Muñoz-Soriano, Yaiza Belacortu, Francisco José Sanz, Cristina Solana-Manrique, Luke Dillon, Carmen Suay-Corredera, Marina Ruiz-Romero, Montserrat Corominas, Nuria Paricio
Biochimica Et Biophysica Acta Gene Regulatory Mechanisms, 2018 - Identification of potential therapeutic compounds for Parkinson's disease using Drosophila and human cell models
Francisco José Sanz, Cristina Solana-Manrique, Verónica Muñoz-Soriano, Pablo Calap-Quintana, María Dolores Moltó, Nuria Paricio
Free Radical Biology and Medicine, 2017
