Endometriosis: Perspective, lights, and shadows of etiology

Asghari, Samira; Valizadeh, Amir; Aghebati‐Maleki, Leili; Nouri, Mohammad; Yousefi, Mehdi

doi:10.1016/j.biopha.2018.06.109

Cited by 73 publications

(43 citation statements)

References 179 publications

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“…The exact etiology of endometriosis remains unclear 74 . Among studies that examined heritability of the disease, there seems to be both maternal and paternal genes involved in the development of endometriosis, but the majority appear paternally inherited 75 .…”

Section: Discussionmentioning

confidence: 99%

Learning endometriosis phenotypes from patient-generated data

2020

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Endometriosis is a systemic and chronic condition in women of childbearing age, yet a highly enigmatic disease with unresolved questions: there are no known biomarkers, nor established clinical stages. We here investigate the use of patient-generated health data and data-driven phenotyping to characterize endometriosis patient subtypes, based on their reported signs and symptoms. We aim at unsupervised learning of endometriosis phenotypes using self-tracking data from personal smartphones. We leverage data from an observational research study of over 4000 women with endometriosis that track their condition over more than 2 years. We extend a classical mixed-membership model to accommodate the idiosyncrasies of the data at hand, i.e., the multimodality and uncertainty of the self-tracked variables. The proposed method, by jointly modeling a wide range of observations (i.e., participant symptoms, quality of life, treatments), identifies clinically relevant endometriosis subtypes. Experiments show that our method is robust to different hyperparameter choices and the biases of self-tracking data (e.g., the wide variations in tracking frequency among participants). With this work, we show the promise of unsupervised learning of endometriosis subtypes from self-tracked data, as learned phenotypes align well with what is already known about the disease, but also suggest new clinically actionable findings. More generally, we argue that a continued research effort on unsupervised phenotyping methods with patient-generated health data via new mobile and digital technologies will have significant impact on the study of enigmatic diseases in particular, and health in general.

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Section: Discussionmentioning

confidence: 99%

Learning endometriosis phenotypes from patient-generated data

2020

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“…Several nano-sensing strategies have been proposed by investigators for effective detection of endometriosis, enabling timely commencement of therapy. The presence of endometriosis, owing to its inflammatory characteristics, is often characterized by disturbances in the immunological environment, which is strongly reflected by alterations in the expression levels of various cytokines, angiogenic factors, matrix metalloproteases, tumor suppressor genes, and circulating nucleic acids [38,39]. Cathepsins (in particular cathepsins B, D, and G), which belong to the class of proteases, have been quantitatively evaluated in patients with proliferative eutopic endometrium using a surface plasmon resonance (SPR) imaging technique, since cathepsins have been found to have a positive impact on the establishment of endometriotic lesions.…”

Section: Endometriosismentioning

confidence: 99%

Nanotechnology in reproductive medicine: Opportunities for clinical translation

Shandilya

Pathak

Lohiya

et al. 2020

Clin Exp Reprod Med

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In recent years, nanotechnology has revolutionized global healthcare and has been predicted to exert a remarkable effect on clinical medicine. In this context, the clinical use of nanomaterials for cancer diagnosis, fertility preservation, and the management of infertility and other pathologies linked to pubertal development, menopause, sexually transmitted infections, and HIV (human immunodeficiency virus) has substantial promise to fill the existing lacunae in reproductive healthcare. Of late, a number of clinical trials involving the use of nanoparticles for the early detection of reproductive tract infections and cancers, targeted drug delivery, and cellular therapeutics have been conducted. However, most of these trials of nanoengineering are still at a nascent stage, and better synergy between pharmaceutics, chemistry, and cutting-edge molecular sciences is needed for effective translation of these interventions from bench to bedside. To bridge the gap between translational outcome and product development, strategic partnerships with the insight and ability to anticipate challenges, as well as an in-depth understanding of the molecular pathways involved, are highly essential. Such amalgamations would overcome the regulatory gauntlet and technical hurdles, thereby facilitating the effective clinical translation of these nano-based tools and technologies. The present review comprehensively focuses on emerging applications of nanotechnology, which holds enormous promise for improved therapeutics and early diagnosis of various human reproductive tract diseases and conditions.

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“…Several etiologies, such as oxidative stress (3), inflammatory factors, cytokines (4), genetic etiology (5, 6), immunity (7), and hormone role (8), have been reported as catalysts for endometriosis.…”

Section: Introductionmentioning

confidence: 99%

Effect of Maternal Advanced Endometriosis on Risk of Congenital Malformations for Infants Born After in vitro Fertilization and Frozen–Thawed Embryo Transfer: Analysis of 28,600 Newborns

Zhou

Yin

et al. 2019

Front. Endocrinol.

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Background: Endometriosis is one of the most challenging diseases for doctors helping infertile women conceive, which has become a common method to help maternal endometriosis-associated infertility. Women with advanced endometriosis possess a higher risk of several adverse outcomes both during pregnancy and at the time of delivery. Whether endometriosis gives rise to a higher occurrence of congenital abnormalities in infants via in vitro fertilization and frozen–thawed embryo transfer (IVF-ET) remains unknown.Methods: Data collected on 22,865 women undergoing IVF using a freeze-all strategy from 2007 to 2017 were analyzed to estimate the rate of congenital malformations. We used an adjusted OR to compare the fertility outcomes of women with advanced endometriosis to the control group.Results: We studied 1,495 infants born from women with advanced endometriosis and 27,105 infants born from endometriosis-free women. There was a 1.557-fold risk that the infants with advanced maternal endometriosis would develop a congenital malformation (adjusted OR: 1.557, 95% CI: 1.03–2.35). Compared with singletons, twins were 1.957 times more likely to experience an adverse outcome (OR: 1.957, 95% CI: 1.561–2.455). When analyzing specific categories of birth defects, the proportion of circulatory system defects was higher than the other categories of birth defects in total (0.56%), followed by musculoskeletal system defects (0.15%).Conclusions: Maternal advanced endometriosis might increase the risk of congenital malformations for infants born after IVF-ET. The organ system most frequently affected by congenital malformations was the cardiovascular system, followed by the musculoskeletal system.

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Endometriosis: Perspective, lights, and shadows of etiology

Cited by 73 publications

References 179 publications

Learning endometriosis phenotypes from patient-generated data

Learning endometriosis phenotypes from patient-generated data

Nanotechnology in reproductive medicine: Opportunities for clinical translation

Effect of Maternal Advanced Endometriosis on Risk of Congenital Malformations for Infants Born After in vitro Fertilization and Frozen–Thawed Embryo Transfer: Analysis of 28,600 Newborns

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