RAD54L2 counters TOP2-DNA adducts to promote genome stability.

The catalytic cycle of topoisomerase 2 (TOP2) enzymes proceeds via a transient DNA double-strand break (DSB) intermediate termed the TOP2 cleavage complex (TOP2cc), in which the TOP2 protein is covalently bound to DNA. Anticancer agents such as etoposide operate by stabilizing TOP2ccs, ultimately generating genotoxic TOP2-DNA protein cross-links that require processing and repair. Here, we identify RAD54 like 2 (RAD54L2) as a factor promoting TOP2cc resolution. We demonstrate that RAD54L2 acts through a novel mechanism together with zinc finger protein associated with tyrosyl-DNA phosphodiesterase 2 (TDP2) and TOP2 (ZATT/ZNF451) and independent of TDP2. Our work suggests a model wherein RAD54L2 recognizes sumoylated TOP2 and, using its ATPase activity, promotes TOP2cc resolution and prevents DSB exposure. These findings suggest RAD54L2-mediated TOP2cc resolution as a potential mechanism for cancer therapy resistance and highlight RAD54L2 as an attractive candidate for drug discovery.

Placental Metabolomics of Fetal Growth Restriction.

Fetal growth restriction is an obstetrical pathological condition that causes high neonatal mortality and morbidity. The mechanisms of its onset are not completely understood. Metabolites were extracted from 493 placentas from non-complicated pregnancies in Hamilton Country, TN (USA), and analyzed by gas chromatography-mass spectrometry (GC-MS). Newborns were classified according to raw fetal weight (low birth weight (LBW; <2500 g) and non-low birth weight (Non-LBW; >2500 g)), and according to the calculated birth weight centile as it relates to gestational age (small for gestational age (SGA), large for gestational age (LGA), and adequate for gestational age (AGA)). Mothers of LBW infants had a lower pre-pregnancy weight (66.2 ± 17.9 kg vs. 73.4 ± 21.3 kg, p < 0.0001), a lower body mass index (BMI) (25.27 ± 6.58 vs. 27.73 ± 7.83, p < 0.001), and a shorter gestation age (246.4 ± 24.0 days vs. 267.2 ± 19.4 days p < 0.001) compared with non-LBW. Marital status, tobacco use, and fetus sex affected birth weight centile classification according to gestational age. Multivariate statistical comparisons of the extracted metabolomes revealed that asparagine, aspartic acid, deoxyribose, erythritol, glycerophosphocholine, tyrosine, isoleucine, serine, and lactic acid were higher in both SGA and LBW placentas, while taurine, ethanolamine, ß-hydroxybutyrate, and glycine were lower in both SGA and LBW. Several metabolic pathways are implicated in fetal growth restriction, including those related to the hypoxia response and amino-acid uptake and metabolism. Inflammatory pathways are also involved, suggesting that fetal growth restriction might share some mechanisms with preeclampsia.

A screening test proposal for congenital defects based on maternal serum metabolomics profile.

BACKGROUND: Historically, noninvasive techniques are only able to identify chromosomal anomalies that accounted for <50% of all congenital defects; the other congenital defects are diagnosed via ultrasound evaluations in the later stages of pregnancy. Metabolomic analysis may provide an important improvement, potentially addressing the need for novel noninvasive and multicomprehensive early prenatal screening tools. A growing body of evidence outlines notable metabolic alterations in different biofluids derived from pregnant women carrying fetuses with malformations, suggesting that such an approach may allow the discovery of biomarkers common to most fetal malformations. In addition, metabolomic investigations are inexpensive, fast, and risk-free and often generate high performance screening tests that may allow early detection of a given pathology. OBJECTIVE: This study aimed to evaluate the diagnostic accuracy of an ensemble machine learning model based on maternal serum metabolomic signatures for detecting fetal malformations, including both chromosomal anomalies and structural defects. STUDY DESIGN: This was a multicenter observational retrospective study that included 2 different arms. In the first arm, a total of 654 Italian pregnant women (334 cases with fetuses with malformations and 320 controls with normal developing fetuses) were enrolled and used to train an ensemble machine learning classification model based on serum metabolomics profiles. In the second arm, serum samples obtained from 1935 participants of the New Zealand Screening for Pregnancy Endpoints study were blindly analyzed and used as a validation cohort. Untargeted metabolomics analysis was performed via gas chromatography-mass spectrometry. Of note, 9 individual machine learning classification models were built and optimized via cross-validation (partial least squares-discriminant analysis, linear discriminant analysis, naïve Bayes, decision tree, random forest, k-nearest neighbor, artificial neural network, support vector machine, and logistic regression). An ensemble of the models was developed according to a voting scheme statistically weighted by the cross-validation accuracy and classification confidence of the individual models. This ensemble machine learning system was used to screen the validation cohort. RESULTS: Significant metabolic differences were detected in women carrying fetuses with malformations, who exhibited lower amounts of palmitic, myristic, and stearic acids; N-α-acetyllysine; glucose; L-acetylcarnitine; fructose; para-cresol; and xylose and higher levels of serine, alanine, urea, progesterone, and valine (P<.05), compared with controls. When applied to the validation cohort, the screening test showed a 99.4%±0.6% accuracy (specificity of 99.9%±0.1% [1892 of 1894 controls correctly identified] with a sensitivity of 78%±6% [32 of 41 fetal malformations correctly identified]). CONCLUSION: This study provided clinical validation of a metabolomics-based prenatal screening test to detect the presence of congenital defects. Further investigations are needed to enable the identification of the type of malformation and to confirm these findings on even larger study populations.

The role of spine length in crustacean and fish associations with echinoids at Los Cabos, Baja California Sur, Mexico / El papel de la longitud de la espina en la asociación de crustáceos y peces con equinoideos en Los Cabos, Baja California Sur, México

Introduction: Echinoids (sea urchins) provide shelter for a variety of facultative or obligatory ectosymbionts. Objective: To evaluate the hypothesis that decapods and fishes prefer to associate with echinoid individuals and species that have longer spines. Methods: We visually studied the frequency of decapod crustaceans and fishes associated with echinoids in shallow water (< 4 m) and deeper water (5-20 m) at Los Cabos, Baja California Sur, Mexico, during 1-6 January 2019. Results: We inspected 1 058 echinoids of six species. Five decapod species associated with three species of echinoids. When compared with other echinoid species, in shallow water, decapods associated 5.1 times more often with the longest-spined echinoid Diadema mexicanum (7.0 times more decapods per individual D. mexicanum); in deeper water, association frequency was similar for all echinoid species. Fourteen fish species associated with four echinoid species. In shallow water, fishes associated 2.6 times more with D. mexicanum (4.5 times more fishes per individual). There was no preferred echinoid species in deeper water. Longer-spined D. mexicanum had more decapods and fishes. Associations were more frequent in shallow water. Multiple individuals and species of decapods and fish often associated together with a single D. mexicanum. The decapod that presumably is Tuleariocaris holthuisi showed a possible obligatory association with one of the equinoids (D. mexicanum); the other decapods and all fish species are facultative associates. Conclusion: Our results support the hypothesis that decapods and fishes associate most frequently with echinoids with the longest spines, presumably to reduce the risk of predation.

Introducción: Los equinoideos (erizos de mar) brindan refugio a una variedad de ectosimbiontes facultativos u obligatorios. Objetivo: Evaluar la hipótesis de que los decápodos y los peces prefieren asociarse con individuos y especies de equinoideos con espinas más largas. Métodos: Estudiamos visualmente la frecuencia de crustáceos decápodos y peces asociados con equinoideos en aguas poco profundas (< 4 m) y aguas más profundas (5-20 m) en Los Cabos, Baja California Sur, México, del 1-6 de enero 2019. Resultados: Examinamos 1 058 equinoideos de seis especies. Cinco especies de decápodos se asociaron con tres especies de equinoideos. Al comparar con otras especies de equinoideos, en aguas poco profundas, los decápodos se asociaron 5.1 veces más frecuentemente con la especie de equinoideo de espinas más largas, Diadema mexicanum (7.0 veces más decápodos por individuo en D. mexicanum); en aguas más profundas, la frecuencia fue similar para todas las especies de equinoideos. Catorce especies de peces se asociaron con 4 especies de equinoideos. En aguas poco profundas, los peces se asociaron 2.6 veces más con D. mexicanum (4.5 veces más peces por individuo). No hubo preferencia por una especie de equinoideo en aguas más profundas. Individuos de D. mexicanum con espinas largas tuvieron más asociación con decápodos y peces. Las asociaciones se dieron con mayor frecuencia en aguas poco profundas. Múltiples individuos y especies de decápodos y peces a menudo se asociaron con un solo D. mexicanum. Un decápodo que presumiblemente es Tuleariocaris holthuisi mostró una posible asociación obligatoria con uno de los equinoideos (D. mexicanum); las otras especies de decápodos y todas las especies de peces presentaron asociaciones facultativas. Conclusión: Nuestros resultados apoyan la hipótesis de que los decápodos y los peces se asociaron con mayor frecuencia con los equinoideos con las espinas más largas, presumiblemente para reducir el riesgo de depredación.

The Metabolomic Approach for the Screening of Endometrial Cancer: Validation from a Large Cohort of Women Scheduled for Gynecological Surgery.

Endometrial cancer (EC) is the most common gynecological neoplasm in high-income countries. Five-year survival rates are related to stage at diagnosis, but currently, no validated screening tests are available in clinical practice. The metabolome offers an unprecedented overview of the molecules underlying EC. In this study, we aimed to validate a metabolomics signature as a screening test for EC on a large study population of symptomatic women. Serum samples collected from women scheduled for gynecological surgery (n = 691) were separated into training (n = 90), test (n = 38), and validation (n = 563) sets. The training set was used to train seven classification models. The best classification performance during the training phase was the PLS-DA model (96% accuracy). The subsequent screening test was based on an ensemble machine learning algorithm that summed all the voting results of the seven classification models, statistically weighted by each models' classification accuracy and confidence. The efficiency and accuracy of these models were evaluated using serum samples taken from 871 women who underwent endometrial biopsies. The EC serum metabolomes were characterized by lower levels of serine, glutamic acid, phenylalanine, and glyceraldehyde 3-phosphate. Our results illustrate that the serum metabolome can be an inexpensive, non-invasive, and accurate EC screening test.

Analyzing human knockouts to validate GPR151 as a therapeutic target for reduction of body mass index.

Novel drug targets for sustained reduction in body mass index (BMI) are needed to curb the epidemic of obesity, which affects 650 million individuals worldwide and is a causal driver of cardiovascular and metabolic disease and mortality. Previous studies reported that the Arg95Ter nonsense variant of GPR151, an orphan G protein-coupled receptor, is associated with reduced BMI and reduced risk of Type 2 Diabetes (T2D). Here, we further investigate GPR151 with the Pakistan Genome Resource (PGR), which is one of the largest exome biobanks of human homozygous loss-of-function carriers (knockouts) in the world. Among PGR participants, we identify eleven GPR151 putative loss-of-function (plof) variants, three of which are present at homozygosity (Arg95Ter, Tyr99Ter, and Phe175LeufsTer7), with a cumulative allele frequency of 2.2%. We confirm these alleles in vitro as loss-of-function. We test if GPR151 plof is associated with BMI, T2D, or other metabolic traits and find that GPR151 deficiency in complete human knockouts is not associated with clinically significant differences in these traits. Relative to Gpr151+/+ mice, Gpr151-/- animals exhibit no difference in body weight on normal chow and higher body weight on a high-fat diet. Together, our findings indicate that GPR151 antagonism is not a compelling therapeutic approach to treatment of obesity.

A Metabolomics-Based Screening Proposal for Colorectal Cancer.

Colorectal cancer (CRC) is a high incidence disease, characterized by high morbidity and mortality rates. Early diagnosis remains challenging because fecal occult blood screening tests have performed sub-optimally, especially due to hemorrhoidal, inflammatory, and vascular diseases, while colonoscopy is invasive and requires a medical setting to be performed. The objective of the present study was to determine if serum metabolomic profiles could be used to develop a novel screening approach for colorectal cancer. Furthermore, the study evaluated the metabolic alterations associated with the disease. Untargeted serum metabolomic profiles were collected from 100 CRC subjects, 50 healthy controls, and 50 individuals with benign colorectal disease. Different machine learning models, as well as an ensemble model based on a voting scheme, were built to discern CRC patients from CTRLs. The ensemble model correctly classified all CRC and CTRL subjects (accuracy = 100%) using a random subset of the cohort as a test set. Relevant metabolites were examined in a metabolite-set enrichment analysis, revealing differences in patients and controls primarily associated with cell glucose metabolism. These results support a potential use of the metabolomic signature as a non-invasive screening tool for CRC. Moreover, metabolic pathway analysis can provide valuable information to enhance understanding of the pathophysiological mechanisms underlying cancer. Further studies with larger cohorts, including blind trials, could potentially validate the reported results.

Tryptophan metabolites suppress the Wnt pathway and promote adverse limb events in chronic kidney disease.

Chronic kidney disease (CKD) imposes a strong and independent risk for peripheral artery disease (PAD). While solutes retained in CKD patients (uremic solutes) inflict vascular damage, their role in PAD remains elusive. Here, we show that the dietary tryptophan-derived uremic solutes including indoxyl sulfate (IS) and kynurenine (Kyn) at concentrations corresponding to those in CKD patients suppress ß-catenin in several cell types, including microvascular endothelial cells (ECs), inhibiting Wnt activity and proangiogenic Wnt targets in ECs. Mechanistic probing revealed that these uremic solutes downregulated ß-catenin in a manner dependent on serine 33 in its degron motif and through the aryl hydrocarbon receptor (AHR). Hindlimb ischemia in adenine-induced CKD and IS solute-specific mouse models showed diminished ß-catenin and VEGF-A in the capillaries and reduced capillary density, which correlated inversely with blood levels of IS and Kyn and AHR activity in ECs. An AHR inhibitor treatment normalized postischemic angiogenic response in CKD mice to a non-CKD level. In a prospective cohort of PAD patients, plasma levels of tryptophan metabolites and plasma's AHR-inducing activity in ECs significantly increased the risk of future adverse limb events. This work uncovers the tryptophan metabolite/AHR/ß-catenin axis as a mediator of microvascular rarefaction in CKD patients and demonstrates its targetability for PAD in CKD models.

Indoleamine 2,3-dioxygenase-1, a Novel Therapeutic Target for Post-Vascular Injury Thrombosis in CKD.

BACKGROUND: CKD, characterized by retained uremic solutes, is a strong and independent risk factor for thrombosis after vascular procedures . Urem ic solutes such as indoxyl sulfate (IS) and kynurenine (Kyn) mediate prothrombotic effect through tissue factor (TF). IS and Kyn biogenesis depends on multiple enzymes, with therapeutic implications unexplored. We examined the role of indoleamine 2,3-dioxygenase-1 (IDO-1), a rate-limiting enzyme of kynurenine biogenesis, in CKD-associated thrombosis after vascular injury. METHODS: IDO-1 expression in mice and human vessels was examined. IDO-1-/- mice, IDO-1 inhibitors, an adenine-induced CKD, and carotid artery injury models were used. RESULTS: Both global IDO-1-/- CKD mice and IDO-1 inhibitor in wild-type CKD mice showed reduced blood Kyn levels, TF expression in their arteries, and thrombogenicity compared with respective controls. Several advanced IDO-1 inhibitors downregulated TF expression in primary human aortic vascular smooth muscle cells specifically in response to uremic serum. Further mechanistic probing of arteries from an IS-specific mouse model, and CKD mice, showed upregulation of IDO-1 protein, which was due to inhibition of its polyubiquitination and degradation by IS in vascular smooth muscle cells. In two cohorts of patients with advanced CKD, blood IDO-1 activity was significantly higher in sera of study participants who subsequently developed thrombosis after endovascular interventions or vascular surgery. CONCLUSION: Leveraging genetic and pharmacologic manipulation in experimental models and data from human studies implicate IS as an inducer of IDO-1 and a perpetuator of the thrombotic milieu and supports IDO-1 as an antithrombotic target in CKD.

Advancements within Modern Machine Learning Methodology: Impacts and Prospects in Biomarker Discovery.

BACKGROUND: The adoption of biomarkers as part of high-throughput, complex microarray or sequencing data has necessitated the discovery and validation of these data through machine learning. Machine learning has remained a fundamental and indispensable tool due to its efficacy and efficiency in both feature extraction of relevant biomarkers as well as the classification of samples as validation of the discovered biomarkers. OBJECTIVES: This review aims to present the impact and ability of various machine learning methodologies and models to process high-throughput, high-dimensionality data found within mass spectrometry, microarray, and DNA/RNA-sequence data; data that precluded biomarker discovery prior to the use of machine learning. METHODS: A vast array of literature highlighting machine learning for biomarker discovery was reviewed, resulting in the eligibility of 21 machine learning algorithms/networks and 3 combinatory architectures, spanning 17 fields of study. This literature was screened to investigate the usage and development of machine learning within the framework of biomarker discovery. RESULTS: Out of the 93 papers collected, a total of 62 biomarker studies were further reviewed across different subfields-49 of which employed machine learning algorithms, and 13 of which employed neural network-based models. Through the application, innovation, and creation of tools in biomarker-related machine learning methodologies, its use allowed for the discovery, accumulation, validation, and interpretation of biomarkers within varied data formats, sources, as well as fields of study. CONCLUSION: The use of machine learning methodologies for biomarker discovery is critical to the analysis of various types of data used for biomarker discovery, such as mass spectrometry, nucleotide and protein sequencing, and image (e.g. CT-scan) data. Further studies containing more standardized techniques for evaluation, and the use of cutting- edge machine learning architectures may lead to more accurate and specific results.

Noninvasive screening for congenital heart defects using a serum metabolomics approach.

OBJECTIVE: Heart anomalies represent nearly one-third of all congenital anomalies. They are currently diagnosed using ultrasound. However, there is a strong need for a more accurate and less operator-dependent screening method. Here we report a metabolomics characterization of maternal serum in order to describe a metabolomic fingerprint representative of heart congenital anomalies. METHODS: Metabolomic profiles were obtained from serum of 350 mothers (280 controls and 70 cases). Nine classification models were built and optimized. An ensemble model was built based on the results from the individual models. RESULTS: The ensemble machine learning model correctly classified all cases and controls. Malonic, 3-hydroxybutyric and methyl glutaric acid, urea, androstenedione, fructose, tocopherol, leucine, and putrescine were determined as the most relevant metabolites in class separation. CONCLUSION: The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal heart anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the revelation of the associated metabolites and their respective biochemical pathways allows a better understanding of the overall pathophysiology of affected pregnancies.

A Review of Per- and Polyfluorinated Alkyl Substance Impairment of Reproduction.

In this review article, we compiled peer-reviewed literature describing PFAS exposure and reproductive effects in animals and humans. The aim was to compare environmental occurrence and effects of the most prominent long-chain PFAS compounds and their short-chain replacements. Long-chain PFAS compounds are known to persist in the environment due to their chemical stability, and also known to bioaccumulate; hence, these compounds are being replaced globally. Indeed, PFOA and PFOS are considered long-chain "forever pollutants," and thus the potential reproductive risk may continue for decades. Much less is known about their short-chain replacements despite the fact that they becoming more widespread in the environment. Short-chain PFAS are generally less bioaccumulative than long-chain, but they are more mobile and persistent in aquatic ecosystems. The three most prominent of these are commonly referred to as GenX, ADONA and F53B. The short-chain PFAS have similar physical and chemical properties as their predecessors; however, because they are relatively new, much less is known about the potential to disrupt reproduction. Indeed, high-quality epidemiological studies are needed to determine associations between short-chain PFAS exposure and effects on reproductive health. However, epidemiological evidence is mounting that long-chain PFAS exposure is associated with reproductive effects (i.e., decrease in fertility, reduced fetal growth and birth weight, pregnancy-induced hypertension and preeclampsia, thyroid hormone disruption during pregnancy, and preterm birth). Evidence from animal models and human cell lines indicates that short-chain PFAS similarly affect reproductive endpoints; however, epidemiological studies are scarce and inconsistent. Although short-chain PFAS have been quantified in drinking water and sediment worldwide, most of these studies did not focus on quantitation of GenX, ADONA, and F53B. There are also many other short-chain PFAS byproducts of manufacturing that have yet to be identified and studied. When sum total concentration of long- and short-chain PFAS are considered, the concentration rises by an order or magnitude or greater, as will the risk of exposure and subsequent reproductive effects.

Transmembrane and Immunoglobulin Domain Containing 1, a Putative Tumor Suppressor, Induces G2/M Cell Cycle Checkpoint Arrest in Colon Cancer Cells.

Colorectal cancer (CRC) is a leading nonfamilial cause of cancer mortality among men and women. Although various genetic and epigenetic mechanisms have been identified, the full molecular mechanisms deriving CRC tumorigenesis are not fully understood. This study demonstrates that cell adhesion molecule transmembrane and immunoglobulin domain containing 1 (TMIGD1) are highly expressed in mouse and human normal intestinal epithelial cells. TMIGD1 knockout mice were developed, and the loss of TMIGD1 in mice was shown to result in the development of adenomas in small intestine and colon. In addition, the loss of TMIGD1 significantly impaired intestinal epithelium brush border membrane, junctional polarity, and maturation. Mechanistically, TMIGD1 inhibits tumor cell proliferation and cell migration, arrests cell cycle at the G2/M phase, and induces expression of p21CIP1 (cyclin-dependent kinase inhibitor 1), and p27KIP1 (cyclin-dependent kinase inhibitor 1B) expression, key cell cycle inhibitor proteins involved in the regulation of the cell cycle. Moreover, TMIGD1 is shown to be progressively down-regulated in sporadic human CRC, and its downregulation correlates with poor overall survival. The findings herein identify TMIGD1 as a novel tumor suppressor gene and provide new insights into the pathogenesis of colorectal cancer and a novel potential therapeutic target.

Endocrine-Disrupting Air Pollutants and Their Effects on the Hypothalamus-Pituitary-Gonadal Axis.

Anthropogenic endocrine-disrupting chemicals (EDCs) can contaminate air, soil, and water. Human exposures to EDCs occur through inhalation, absorption, and ingestion. EDCs act by disrupting various pathways in the endocrine system. When the hypothalamic-pituitary-gonadal (HPG) axis is disrupted by EDCs, there can be effects on fertility in both men and women. Not only can fertility be indirectly affected by EDC disruptions of the HPG axis, but EDCs can also directly affect the menstrual cycle and sperm morphology. In this review, we will discuss the current findings on EDCs that can be inhaled. This review examines effects of exposure to prominent EDCs: brominated and organophosphate flame retardants, diesel exhaust, polycyclic aromatic hydrocarbons, cadmium and lead, TCDD, and polychlorinated biphenyls on fertility through alterations that disrupt the HPG axis and fertility through inhalation. Although the studies included herein include multiple exposure routes, all the studies indicate receptor interactions that can occur from inhalation and the associated effects of all compounds on the HPG axis and subsequent fertility.

Development and Validation of a Serum Metabolomic Signature for Endometrial Cancer Screening in Postmenopausal Women.

Importance: Endometrial carcinoma (EC) is the most commonly diagnosed gynecologic cancer. Its early detection is advisable because 20% of women have advanced disease at the time of diagnosis. Objective: To clinically validate a metabolomics-based classification algorithm as a screening test for EC. Design, Setting, and Participants: This diagnostic study enrolled 2 cohorts. A multicenter prospective cohort, with 50 cases (postmenopausal women with EC; International Federation of Gynecology and Obstetrics stage I-III and grade G1-G3) and 70 controls (no EC but matched on age, years from menopause, tobacco use, and comorbidities), was used to train multiple classification models. The accuracy of each trained model was then used as a statistical weight to produce an ensemble machine learning algorithm for testing, which was validated with a subsequent prospective cohort of 1430 postmenopausal women. The study was conducted at the San Giovanni di Dio e Ruggi d'Aragona University Hospital of Salerno (Italy) and Lega Italiana per la Lotta contro i Tumori clinic in Avellino (Italy). Data collection was conducted from January 2018 to February 2019, and analysis was conducted from January to March 2019. Main Outcomes and Measures: The presence or absence of EC based on evaluation of the blood metabolome. Metabolites were extracted from dried blood samples from all participants and analyzed by gas chromatography-mass spectrometry. A confusion matrix was used to summarize test results. Performance indices included sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy. Confirmation or exclusion of EC in women with a positive test result was by means of hysteroscopy. Participants with negative results were followed up 1 year after enrollment to investigate the appearance of EC signs. Results: The study population consisted of 1550 postmenopausal women. The mean (SD) age was 68.2 (11.7) years for participants with no EC in the training cohort, 69.4 (13.8) years for women with EC in the training cohort, and 59.7 (7.7) years for women in the validation cohort. Application of the ensemble machine learning to the validation cohort resulted in 16 true-positives, 2 false-positives, and 0 false-negatives, and it correctly classified more than 99% of samples. Disease prevalence was 1.12% (16 of 1430). Conclusions and Relevance: In this study, dried blood metabolomic profile was used to assess the presence or absence of EC in postmenopausal women not receiving hormonal therapy with greater than 99% accuracy.