Sex differences in the human metabolome

Sex-Dependent Effects of Cardiometabolic Health and APOE4 on Brain Age: A Longitudinal Cohort Study

BACKGROUND AND OBJECTIVES

The aging population is growing faster than all other demographic strata. With older age comes a greater risk of health conditions such as obesity and high blood pressure (BP). These cardiometabolic risk factors (CMRs) exhibit prominent sex differences in midlife and aging, yet their influence on brain health in females vs males is largely unexplored. In this study, we investigated sex differences in relationships between BP, body mass index (BMI), and brain age over time and tested for interactions with APOE ε4 genotype (APOE4), a known genetic risk factor of Alzheimer disease.

METHODS

The sample included participants from 2 United Kingdom-based longitudinal birth cohorts, the Lothian Birth Cohort (1936) and Insight 46 (1946). Participants with MRI data from at least 1 time point were included to evaluate sex differences in associations between CMRs and brain age. The open-access software package brainageR 2.1 was used to estimate brain age for each participant. Linear mixed-effects models were used to assess the relationships between brain age, BMI, BP, and APOE4 status (i.e., carrier vs noncarrier) in males and females over time.

RESULTS

The combined sample comprised 1,120 participants (48% female) with a mean age (SD) of 73 (0.72) years in the Lothian Birth Cohort and 71 (0.68) years in Insight 46 at the time point 1 assessment. Approximately 30% of participants were APOE4 carriers. Higher systolic and diastolic BP was significantly associated with older brain age in females only (β = 0.43-0.56, p < 0.05). Among males, higher BMI was associated with older brain age across time points and APOE4 groups (β = 0.72-0.77, p < 0.05). In females, higher BMI was linked to older brain age among APOE4 noncarriers (β = 0.68-0.99, p < 0.05), whereas higher BMI was linked to younger brain age among carriers, particularly at the last time point (β = -1.75, p < 0.05).

DISCUSSION

This study indicates sex-dependent and time-dependent relationships between CMRs, APOE4 status, and brain age. Our findings highlight the necessity of sex-stratified analyses to elucidate the role of CMRs in individual aging trajectories, providing a basis for developing personalized preventive interventions.

Unraveling sex-specific risks of knee osteoarthritis before menopause: Do sex differences start early in life?

OBJECTIVE

Sufficient evidence within the past two decades have shown that osteoarthritis (OA) has a sex-specific component. However, efforts to reveal the biological causes of this disparity have emerged more gradually. In this narrative review, we discuss anatomical differences within the knee, incidence of injuries in youth sports, and metabolic factors that present early in life (childhood and early adulthood) that can contribute to a higher risk of OA in females.

DESIGN

We compiled clinical data from multiple tissues within the knee joint-since OA is a whole joint disorder-aiming to reveal relevant factors behind the sex differences from different perspectives.

RESULTS

The data gathered in this review indicate that sex differences in articular cartilage, meniscus, and anterior cruciate ligament are detected as early as childhood and are not only explained by sex hormones. Aiming to unveil the biological causes of the uneven sex-specific risks for knee OA, we review the current knowledge of sex differences mostly in young, but also including old populations, from the perspective of (i) human anatomy in both healthy and pathological conditions, (ii) physical activity and response to injury, and (iii) metabolic signatures.

CONCLUSIONS

We propose that to close the gap in health disparities, and specifically regarding OA, we should address sex-specific anatomic, biologic, and metabolic factors at early stages in life, as a way to prevent the higher severity and incidence of OA in women later in life.

Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis

Objective

Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.

Design

We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.

Results

Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.

Conclusions

A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.

Acute toxicity profiling of medicinal herb Ardisia elliptica leaf extract by conventional evaluations and proton nuclear magnetic resonance (NMR) metabolomics

Background and aim

Interest in the safety of herbal medicine is growing rapidly regarding knowledge and challenges in natural products. Hence, this study aimed to reveal the toxicological profile of Ardisia elliptica, a traditional medicinal plant used in the treatment of various illnesses.

Experimental procedure

Acute toxicity study was performed on female and male Sprague Dawley rats with a single oral administration of 2000 mg/kg BW of 70% ethanolic A. elliptica leaf extract, using a combination of conventional investigations and 1H-NMR-based metabolomics approaches.

Results

Physical, hematological, biochemical, and histopathological assessments demonstrated the usual rat profile, with no mortality and delayed toxicity 14 days after administration. 1H NMR serum metabolomics depicted similar metabolites between normal and treated groups. Nevertheless, 1H NMR of urinary metabolomics revealed perturbation in carbohydrate, amino acid, and energy metabolism within 24h after extract administration, while no accumulation of toxic biomarkers in the collected biological fluids on Day 14. A minor gender-based difference revealed the influence of sex hormones and different energy expenditure on response to extract treatment.

Conclusion

This study suggested that 2000 mg/kg BW of 70% ethanolic A. elliptica leaf extract is considered as safe for consumption and offered a comprehensive overview of the response of physiological and metabolic aspects applicable to food and herbal product development.

Plasma acylcarnitines and amino acids in dyslipidemia: An integrated metabolomics and machine learning approach

Purpose

The Discovery of underlying intermediates associated with the development of dyslipidemia results in a better understanding of pathophysiology of dyslipidemia and their modification will be a promising preventive and therapeutic strategy for the management of dyslipidemia.

Methods

The entire dataset was selected from the Surveillance of Risk Factors of Noncommunicable Diseases (NCDs) in 30 provinces of Iran (STEPs 2016 Country report in Iran) that included 1200 subjects and was stratified into four binary classes with normal and abnormal cases based on their levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C.Plasma concentrations of 20 amino acids and 30 acylcarnitines in each class of dyslipidemia were evaluated using Tandem mass spectrometry. Then, these attributes, along with baseline characteristics data, were used to check whether machine learning (ML) algorithms could classify cases and controls.

Results

Our ML framework accurately predicts TG binary classes. Among the models tested, the SVM model stood out, performing slightly better with an AUC of 0.81 and a standard deviation of test accuracy at 0.04. Consequently, it was chosen as the optimal model for TG classification. Moreover, the findings showed that alanine, phenylalanine, methionine, C3, C14:2, and C16 had great power in differentiating patients with high TG from normal TG controls. Conclusions: The comprehensive output of this work, along with sex-specific attributes, will improve our understanding of the underlying intermediates involved in dyslipidemia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01384-9.

Intermittent fasting as a dietary intervention with potential sexually dimorphic health benefits

Intermittent fasting (IF) has proven to be a feasible dietary intervention for the wider population. The recent increase in IF clinical trials highlights its potential effects on health, including changes in body composition, cardiometabolic status, and aging. Although IF may have clinical applications in different populations, studies suggest there may be sex-specific responses in parameters such as body composition or glucose and lipid metabolism. Here, the existing literature on IF clinical trials is summarized, the application of IF in both disease prevention and management is discussed, and potential disparities in response to this type of diet between men and women are assessed. Moreover, the potential mechanisms that may be contributing to the sexually dimorphic response, such as age, body composition, tissue distribution, or sex hormones are investigated. This review underscores the need to further study these sex-specific responses to IF to define the most effective time frames and length of fasting periods for men and women. Tailoring IF to specific populations with a personalized approach may help achieve its full potential as a lifestyle intervention with clinical benefits.

Postmortem metabolomics as a high-throughput cause-of-death screening tool for human death investigations

Autopsy rates are declining globally, impacting cause-of-death (CoD) diagnoses and quality control. Postmortem metabolomics was evaluated for CoD screening using 4,282 human cases, encompassing CoD groups: acidosis, drug intoxication, hanging, ischemic heart disease (IHD), and pneumonia. Cases were split 3:1 into training and test sets. High-resolution mass spectrometry data from femoral blood were analyzed via orthogonal-partial least squares discriminant analysis (OPLS-DA) to discriminate CoD groups. OPLS-DA achieved an R2 = 0.52 and Q2 = 0.30, with true-positive prediction rates of 68% and 65% for training and test sets, respectively, across all groups. Specificity-optimized thresholds predicted 56% of test cases with a unique CoD, average 45% sensitivity, and average 96% specificity. Prediction accuracies varied: 98.7% for acidosis, 80.5% for drug intoxication, 81.6% for hanging, 73.1% for IHD, and 93.6% for pneumonia. This study demonstrates the potential of large-scale postmortem metabolomics for CoD screening, offering high specificity and enhancing throughput and decision-making in human death investigations.

Sex-Associated Metabolites and Incident Stroke, Incident Coronary Heart Disease, Hypertension, and Chronic Kidney Disease in the REGARDS Cohort

BACKGROUND

Sex disparities exist in cardiometabolic diseases. Metabolomic profiling offers insight into disease mechanisms, as the metabolome is influenced by environmental and genetic factors. We identified metabolites associated with sex and determined if sex-associated metabolites are associated with incident stoke, incident coronary heart disease, prevalent hypertension, and prevalent chronic kidney disease.

METHODS AND RESULTS

Targeted metabolomics was conducted for 357 metabolites in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) case-cohort substudy for incident stroke. Weighted logistic regression models were used to identify metabolites associated with sex in REGARDS. Sex-associated metabolites were replicated in the HyperGEN (Hypertension Genetic Epidemiology Network) and using the literature. Weighted Cox proportional hazard models were used to evaluate associations between metabolites and incident stroke. Cox proportional hazard models were used to evaluate associations between metabolites and incident coronary heart disease. Weighted logistic regression models were used to evaluate associations between metabolites and hypertension and chronic kidney disease. Fifty-one replicated metabolites were associated with sex. Higher levels of 6 phosphatidylethanolamines were associated with incident stroke. No metabolites were associated with incident coronary heart disease. Higher levels of uric acid and leucine and lower levels of a lysophosphatidylcholine were associated with hypertension. Higher levels of indole-3-lactic acid, 7 phosphatidylethanolamines, and uric acid, and lower levels of betaine and bilirubin were associated with chronic kidney disease.

CONCLUSIONS

These findings suggest that the sexual dimorphism of the metabolome may contribute to sex differences in stroke, hypertension, and chronic kidney disease.

Pioglitazone-induced alterations of purine metabolism in healthy male subjects

Pioglitazone is class of thiazolidinediones that activates peroxisome proliferator-activated receptors (PPARs) in adipocytes to improve glucose metabolism and insulin sensitivity and has been used as a treatment for type 2 diabetes. However, the underlying mechanisms of associated pioglitazone-induced effects remain unclear. Our study aimed to investigate endogenous metabolite alterations associated with pioglitazone administration in healthy male subjects using an untargeted metabolomics approach. All subjects received 30 mg of pioglitazone once daily in the assigned sequence and period. Urine samples were collected before pioglitazone administration and for 24 h after 7 days of administration. A total of 1465 compounds were detected and filtered using a coefficient of variance below 30% and 108 metabolites were significantly altered upon pioglitazone administration via multivariate statistical analysis. Fourteen significant metabolites were identified using authentic standards and public libraries. Additionally, pathway analysis revealed that metabolites from purine and beta-alanine metabolisms were significantly altered after pioglitazone administration. Further analysis of quantification of metabolites from purine metabolism, revealed that the xanthine/hypoxanthine and uric acid/xanthine ratios were significantly decreased at post-dose. Pioglitazone-dependent endogenous metabolites and metabolic ratio indicated the potential effect of pioglitazone on the activation of PPAR and fatty acid synthesis. Additional studies involving patients are required to validate these findings.

Serum Creatinine as an Independent Predictor of Moderate to Severe Fibrosis in Chinese American Non-obese Metabolic Dysfunction-Associated Steatotic Liver Disease

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely linked to the obesity epidemic. However, non-obese MASLD (body mass index [BMI] < 25 kg/m2 for Asians) is not uncommon, especially among Asian American populations. Preliminary research has demonstrated sarcopenia, a muscle-wasting syndrome, to be a major risk factor for non-obese Chinese MASLD. This study examined serum creatinine (SCr), a sarcopenia biomarker, and other prominent MASLD biomarkers for their ability to predict moderate to severe fibrosis (≥7.5 kPa or ≥F2 fibrosis) in the Chinese American MASLD population.

METHODS

A total of 296 Chinese American MASLD patients were categorized by BMI and fibrosis severity. As per World Health Organization guidelines for Asians, we identified obese MASLD (BMI ≥ 25 kg/m2) in 191 subjects (64.5%) and non-obese MASLD (BMI < 25 kg/m2) in 105 subjects (35.5%). Multivariate logistic regressions were performed to ascertain which biomarkers served as independent predictors of ≥F2 fibrosis. Wilcoxon signed-rank tests were conducted to compare MASLD cohorts (stratified by gender) and the healthy adult population on SCr distribution.

RESULTS

The obese MASLD cohorts had higher rates of ≥F2 fibrosis and type 2 diabetes mellitus compared to their older, non-obese counterparts. For obese MASLD patients, higher age (P < 0.05), increased BMI (P < 0.01), increased AST (P < 0.05), and decreased platelets (P < 0.05) independently predicted ≥F2 fibrosis. For non-obese MASLD patients, lowered SCr (P < 0.05) levels served as the main predictor of ≥F2 fibrosis. Female MASLD patients had markedly lower SCr distributions (P < 0.001) compared to the healthy female population, with 26.8% having SCr levels below the normal range.

CONCLUSIONS

In summary, SCr was the predominant predictor of moderate to severe fibrosis in non-obese Chinese American MASLD patients. The high rate of decreased SCr levels in Chinese American MASLD women suggests that this population may be at higher risk for muscle mass loss, which can lead to liver fat accumulation.

Harnessing Metabolites as Serum Biomarkers for Liver Graft Pathology Prediction Using Machine Learning

Graft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients with biopsy confirmed metabolic dysfunction-associated steatohepatitis (MASH), T-cell mediated rejection (TCMR) and biliary complications was collected and processed using a combination of LC-MS/MS assay. The metabolomic profiles were integrated with clinical information using a multi-class Machine Learning (ML) classifier. The model's efficacy was assessed through the Out-of-Bag (OOB) error estimate evaluation. Our ML model yielded an overall accuracy of 79.66% with an OOB estimate of the error rate at 19.75%. The model exhibited a maximum ability to distinguish MASH, with an OOB error estimate of 7.4% compared to 22.2% for biliary and 29.6% for TCMR. The metabolites serine and serotonin emerged as the topmost predictors. When predicting binary outcomes using three models: Biliary (biliary vs. rest), MASH (MASH vs. rest) and TCMR (TCMR vs. rest); the AUCs were 0.882, 0.972 and 0.896, respectively. Our ML tool integrating serum metabolites with clinical variables shows promise as a non-invasive, multi-class serum biomarker of graft pathology.

Impact of Distinct Anti-Androgen Exposures on the Plasma Metabolome in Feminizing Gender-Affirming Hormone Therapy

CONTEXT

The plasma metabolome is a functional readout of metabolic activity and is associated with phenotypes exhibiting sexual dimorphism, such as cardiovascular disease. Sex hormones are thought to play a key role in driving sexual dimorphism.

OBJECTIVE

Gender-affirming hormone therapy (GAHT) is a cornerstone of transgender care, but longitudinal changes in the plasma metabolome with feminizing GAHT have not been described.

METHODS

Blood samples were collected at baseline and after three and six months of GAHT from transgender women (n = 53). Participants were randomized to different anti-androgens, cyproterone acetate or spironolactone. NMR-based metabolomics was used to measure 249 metabolic biomarkers in plasma. Additionally, we used metabolic biomarker data from an unrelated cohort of children and their parents (n = 3,748) to identify sex- and age-related metabolite patterns.

RESULTS

We identified 43 metabolic biomarkers altered after six months in both anti-androgen groups, most belonging to the very low- or low-density lipoprotein subclasses, with all but one showing a decrease. We observed a cyproterone acetate-specific decrease in glutamine, glycine, and alanine levels. Notably, of the metabolic biomarkers exhibiting the most abundant 'sex- and age-related' pattern (higher in assigned female children and lower in assigned female adults, relative to assigned males), 80% were significantly lowered after GAHT, reflecting a shift toward the adult female profile.

CONCLUSION

Our results suggest an anti-atherogenic signature in the plasma metabolome after the first six months of feminizing GAHT, with cyproterone acetate also reducing specific plasma amino acids. This study provides novel insight into the metabolic changes occurring across feminizing GAHT.

Physiological phenotypes have optimal values relevant to healthy aging: sweet spots deduced from the Canadian Longitudinal Study on Aging

Previous observations on a group of exceptionally healthy "Super-Seniors" showed a lower variance of multiple physiological measures relevant for health than did a less healthy group of the same age. The finding was interpreted as the healthier individuals having physiological measurement values closer to an optimal level, or "sweet spot." Here, we tested the generalizability of the sweet-spot hypothesis in a larger community sample, comparing differences in the variance between healthier and less healthy groups. We apply this method to the Canadian Longitudinal Study on Aging (CLSA) comprehensive cohort of 30,097 participants aged 45 to 85 years with deep phenotype data. Data from both sexes and four age ranges were analyzed. Five instruments were used to represent different aspects of health, physical, and cognitive functioning. We tested 231 phenotypic measures for lower variance in the most healthy vs. least healthy quartile of each sex and age group, as classified by the five instruments. Segmented regression was used to determine sex-specific optimal values. One hundred forty-two physiological measures (61%) showed lower variance in the healthiest than in the least healthy group, in at least one sex and age group. The difference in variance was most significant for hemoglobin A1c and was also significant for many body composition measurements, but not for bone mineral density. Ninety-four phenotypes showed a nonmonotonic relationship with health, consistent with the idea of a sweet spot; for these, we determined optimal values and 95% confidence intervals that were generally narrower than the ranges of current clinical reference intervals. These findings for sweet spot discovery validate the proposed approach for identifying traits important for healthy aging.

Time-resolved concentrations of serum amino acids, one-carbon metabolites and B-vitamin biomarkers during the postprandial and fasting state: the Postprandial Metabolism in Healthy Young Adults (PoMet) Study

Metabolomics has been utilised in epidemiological studies to investigate biomarkers of nutritional status and metabolism in relation to non-communicable diseases. However, little is known about the effect of prandial status on several biomarker concentrations. Therefore, the aim of this intervention study was to investigate the effect of a standardised breakfast meal followed by food abstinence for 24 h on serum concentrations of amino acids, one-carbon metabolites and B-vitamin biomarkers. Thirty-four healthy subjects (eighteen males and sixteen females) aged 20-30 years were served a breakfast meal (∼500 kcal) after which they consumed only water for 24 h. Blood samples were drawn before and at thirteen standardised timepoints after the meal. Circulating concentrations of most amino acids and metabolites linked to one-carbon metabolism peaked within the first 3 h after the meal. The branched-chain amino acids steadily increased from 6 or 8 hours after the meal, while proline decreased in the same period. Homocysteine and cysteine concentrations immediately decreased after the meal but steadily increased from 3 and 4 hours until 24 h. FMN and riboflavin fluctuated immediately after the meal but increased from 6 h, while folate increased immediately after the meal and remained elevated during the 24 h. Our findings indicate that accurate reporting of time since last meal is crucial when investigating concentrations of certain amino acids and one-carbon metabolites. Our results suggest a need for caution when interpretating studies, which utilise such biomarkers, but do not strictly control for time since the last meal.

New perspectives on 'Breathomics': metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS

Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. "Breathomics" as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath.

Non-Targeted Metabolomics Investigation of a Sub-Chronic Variable Stress Model Unveils Sex-Dependent Metabolic Differences Induced by Stress

Depression is twice as prevalent in women as in men, however, most preclinical studies of depression have used male rodent models. This study aimed to examine how stress affects metabolic profiles depending on sex using a rodent depression model: sub-chronic variable stress (SCVS). The SCVS model of male and female mice was established in discovery and validation sets. The stress-induced behavioral phenotypic changes were similar in both sexes, however, the metabolic profiles of female plasma and brain became substantially different after stress, whereas those of males did not. Four stress-differential plasma metabolites-β-hydroxybutyric acid (BHB), L-serine, glycerol, and myo-inositol-could yield biomarker panels with excellent performance to discern the stressed individuals only for females. Disturbances in BHB, glucose, 1,5-anhydrosorbitol, lactic acid, and several fatty acids in the plasma of stressed females implied a systemic metabolic shift to β-oxidation in females. The plasma levels of BHB and corticosterone only in stressed females were observed not only in SCVS but also in an acute stress model. These results collectively suggest a sex difference in the metabolic responses by stress, possibly involving the energy metabolism shift to β-oxidation and the HPA axis dysregulation in females.

The Appropriateness of Medical Devices Is Strongly Influenced by Sex and Gender

Until now, research has been performed mainly in men, with a low recruitment of women; consequentially, biological, physiological, and physio-pathological mechanisms are less understood in women. Obviously, without data obtained on women, it is impossible to apply the results of research appropriately to women. This issue also applies to medical devices (MDs), and numerous problems linked to scarce pre-market research and clinical trials on MDs were evidenced after their introduction to the market. Globally, some MDs are less efficient in women than in men and sometimes MDs are less safe for women than men, although recently there has been a small but significant decrease in the sex and gender gap. As an example, cardiac resynchronization defibrillators seem to produce more beneficial effects in women than in men. It is also important to remember that MDs can impact the health of healthcare providers and this could occur in a sex- and gender-dependent manner. Recently, MDs' complexity is rising, and to ensure their appropriate use they must have a sex-gender-sensitive approach. Unfortunately, the majority of physicians, healthcare providers, and developers of MDs still believe that the human population is only constituted by men. Therefore, to overcome the gender gap, a real collaboration between the inventors of MDs, health researchers, and health providers should be established to test MDs in female and male tissues, animals, and women.

Sex differences in plasma metabolites in a guinea pig model of allergic asthma

Sex seems to be a contributing factor in the pathogenesis of bronchial asthma. This study aimed to find sex-related differences in metabolome measured by hydrogen-1 nuclear magnetic resonance ((1)H NMR) spectroscopy in healthy and ovalbumin (OVA)-sensitized guinea pigs. Adult male and female animals were divided into controls and OVA-sensitized groups. OVA-sensitization was performed by OVA systemic and inhalational administration within 14 days; on day 15, animals were killed by anesthetic overdose followed by exsanguination. Blood was taken and differential white blood cell count was measured. Left lung was saline-lavaged and differential cell count in the bronchoalveolar lavage fluid (BALF) was measured. After blood centrifugation, plasma was processed for (1)H NMR analysis. Metabolomic data was evaluated by principal component analysis (PCA). Eosinophil counts elevated in the BALF confirming eosinophil-mediated inflammation in OVA-sensitized animals of both sexes. Sex differences for lactate, glucose, and citrate were found in controls, where these parameters were lower in males than in females. In OVA-sensitized males higher glucose and lower pyruvate were found compared to controls. OVA-sensitized females showed lower lactate, glucose, alanine, 3-hydroxy-butyrate, creatine, pyruvate, and succinate concentrations compared to controls. In OVA-sensitized animals, lactate concentration was lower in males. Data from females (healthy and OVA-sensitized) were generally more heterogeneous. Significant sex differences in plasma concentrations of metabolites were found in both healthy and OVA-sensitized animals suggesting that sex may influence the metabolism and may thereby contribute to different clinical picture of asthma in males and females.

NMR-based metabolomics in Alzheimer's disease research: a review

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the most common cause of dementia in the elderly population worldwide. Currently, there is no cure for AD, and the continuous increase in the number of susceptible individuals poses one of the most significant emerging threats to public health. However, the molecular pathways involved in the onset and progression of AD are not fully understood. This information is crucial for developing less invasive diagnostic instruments and discovering novel potential therapeutic targets. Metabolomics studies the complete ensemble of endogenous and exogenous metabolites present in biological specimens and may provide an interesting approach to identify alterations in multiple biochemical processes associated with AD onset and evolution. In this mini review, we summarize the results from metabolomic studies conducted using nuclear magnetic resonance (NMR) spectroscopy on human biological samples (blood derivatives, cerebrospinal fluid, urine, saliva, and tissues) from AD patients. We describe the metabolic alterations identified in AD patients compared to controls and to patients diagnosed with mild cognitive impairment (MCI). Moreover, we discuss the challenges and issues associated with the application of NMR-based metabolomics in the context of AD research.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

Disparities in cardio-oncology: Implication of angiogenesis, inflammation, and chemotherapy

Cancers and cardiovascular diseases are the top two causes of death in the United States. Over the past decades, novel therapies have slowed the cancer mortality rate, yet cardiac failures have risen due to the toxicity of cancer treatments. The mechanisms behind this relationship are poorly understood and it is crucial that we properly treat patients at risk of developing cardiac failure in response to cancer treatments. Currently, we rely on early-stage biomarkers of inflammation and angiogenesis to detect cardiotoxicity before it becomes irreversible. Identification of such biomarkers allows healthcare professionals to decrease the adverse effects of cancer therapies. Angiogenesis and inflammation have a systemic influence on the heart and vasculature following cancer therapy. In the field of cardio-oncology, there has been a recent emphasis on gender and racial disparities in cardiotoxicity and the impact of these disparities on disease outcomes, but there is a scarcity of data on how cardiotoxicity varies across diverse populations. Here, we will discuss how current markers of angiogenesis and inflammation induced by cancer therapy are related to disparities in cardiovascular health.

Stratification of Amniotic Fluid Cells and Amniotic Fluid by Sex Opens Up New Perspectives on Fetal Health

Amniotic fluid is essential for fetus wellbeing and is used to monitor pregnancy and predict fetal outcomes. Sex affects health and medicine from the beginning of life, but knowledge of its influence on cell-depleted amniotic fluid (AF) and amniotic fluid cells (AFCs) is still neglected. We evaluated sex-related differences in AF and in AFCs to extend personalized medicine to prenatal life. AFCs and AF were obtained from healthy Caucasian pregnant women who underwent amniocentesis at the 16th-18th week of gestation for advanced maternal age. In the AF, inflammation biomarkers (TNFα, IL6, IL8, and IL4), malondialdehyde, nitrites, amino acids, and acylcarnitines were measured. Estrogen receptors and cell fate (autophagy, apoptosis, senescence) were measured in AFCs. TNFα, IL8, and IL4 were higher in female AF, whereas IL6, nitrites, and MDA were similar. Valine was higher in male AF, whereas several acylcarnitines were sexually different, suggesting a mitochondrial involvement in establishing sex differences. Female AFCs displayed higher expression of ERα protein and a higher ERα/ERβ ratio. The ratio of LC3II/I, an index of autophagy, was higher in female AFCs, while LC3 gene was similar in both sexes. No significant sex differences were found in the expression of the lysosomal protein LAMP1, while p62 was higher in male AFCs. LAMP1 gene was upregulated in male AFCs, while p62 gene was upregulated in female ones. Finally, caspase 9 activity and senescence linked to telomeres were higher in female AFCs, while caspase 3 and β-galactosidase activities were similar. This study supports the idea that sex differences start very early in prenatal life and influence specific parameters, suggesting that it may be relevant to appreciate sex differences to cover knowledge gaps. This might lead to improving the diagnosis of risk prediction for pregnancy complications and achieving a more satisfactory monitoring of fetus health, even preventing future diseases in adulthood.

The impact of chromosomal sex on cardiometabolic health and disease

Many aspects of metabolism are sex-biased, from gene expression in metabolic tissues to the prevalence and presentation of cardiometabolic diseases. The influence of hormones produced by male and female gonads has been widely documented, but recent studies have begun to elucidate the impact of genetic sex (XX or XY chromosomes) on cellular and organismal metabolism. XX and XY cells have differential gene dosage conferred by specific genes that escape X chromosome inactivation or the presence of Y chromosome genes that are absent from XX cells. Studies in mouse models that dissociate chromosomal and gonadal sex have uncovered mechanisms for sex-biased epigenetic, transcriptional, and post-transcriptional regulation of gene expression in conditions such as obesity, atherosclerosis, pulmonary hypertension, autoimmune disease, and Alzheimer's disease.

Metabolomic profiling implicates mitochondrial and immune dysfunction in disease syndromes of the critically endangered black rhinoceros (Diceros bicornis)

The critically endangered black rhinoceros (Diceros bicornis; black rhino) experiences extinction threats from poaching in-situ. The ex-situ population, which serves as a genetic reservoir against impending extinction threats, experiences its own threats to survival related to several disease syndromes not typically observed among their wild counterparts. We performed an untargeted metabolomic analysis of serum from 30 ex-situ housed black rhinos (Eastern black rhino, EBR, n = 14 animals; Southern black rhino, SBR, n = 16 animals) and analyzed differences in metabolite profiles between subspecies, sex, and health status (healthy n = 13 vs. diseased n = 14). Of the 636 metabolites detected, several were differentially (fold change > 1.5; p < 0.05) expressed between EBR vs. SBR (40 metabolites), female vs. male (36 metabolites), and healthy vs. diseased (22 metabolites). Results suggest dysregulation of propanoate, amino acid metabolism, and bile acid biosynthesis in the subspecies and sex comparisons. Assessment of healthy versus diseased rhinos indicates involvement of arachidonic acid metabolism, bile acid biosynthesis, and the pentose phosphate pathway in animals exhibiting inflammatory disease syndromes. This study represents the first systematic characterization of the circulating serum metabolome in the black rhinoceros. Findings further implicate mitochondrial and immune dysfunction as key contributors for the diverse disease syndromes reported in ex-situ managed black rhinos.

Effect of Metformin Treatment on Serum Metabolic Profile Changes in Lean and Obese Zucker Rat Model for Fatty Liver Disease

Excessive weight and obesity are the leading risk factors for the development of chronic diseases, including diabetes. Metformin is capable of significantly improving coexisting complications of diabetes. We used a metabolomics approach to examine the effects of metformin administration on lean and obese (fa/fa) Zucker rats. After 1 week of acclimation, twenty-eight 5-week-old female lean and obese rats were randomly assigned to and maintained in the following four groups (seven rats/group) for 10 weeks: (1) lean control (LC); (2) obese control (OC); (3) lean metformin (LM); and (4) obese metformin (OM). At the end of 10 weeks, serum was collected and analyzed using HPLC with electrochemical detection, HPLC with UV detection, and liquid chromatography mass spectrometry. We selected 50 metabolites' peaks that were shared by all four groups of rats. Peak heights, as a defining factor, generally decreased in metformin-treated lean rats vs. untreated lean controls (3 LM:16 LC). Peak heights generally increased in metformin-treated obese rats vs. untreated obese controls (14 OM:5 OC). Overall, individual peaks were distributed as 11 that represented only lean rats, 11 that represented only obese rats, and 8 that were common among both lean and obese rats. In future studies, we will use a targeted metabolomics approach to identify those metabolites, map them to biochemical pathways and create a list of biomarkers. In summary, the current study contributed to a better understanding of the basic metabolic changes of lean and obese rats and demonstrated that both obesity and metformin make a significant impact on the metabolome of Zucker rats.

Association of Polycyclic Aromatic Hydrocarbons Urine Metabolites with Type 1 Diabetes

Purpose

Polycyclic aromatic hydrocarbons (PAHs) are believed to be a possible factor in the development of cancer, ischemic heart disease, obesity, and cardiovascular disease. The objective of this study was to explore the association between certain metabolites of urinary PAH and type 1 diabetes (T1D).

Methods

In Isfahan City, a case-control study was carried out involving 147 T1D patients and an equal number of healthy individuals. The study measured the levels of urinary metabolites of PAHs, specifically 1-hydroxynaphthalene, 2-hydroxynaphthalene, and 9-hydroxyphenanthrene, in both the case and control groups. The levels of these metabolites were then compared between the two groups to assess any potential association between the biomarkers and T1D.

Results

The mean (SD) age of participants in the case and control groups was 8.4 (3.7) and 8.6 (3.7) years old, respectively, (P > 0.05). In terms of gender distribution, 49.7% and 46% of participants in the case and control groups were girls, respectively (P > 0.05). Geometric mean (95% CI) concentrations were: 36.3 (31.4-42) μg/g creatinine for 1-hydroxynaphthalene, 29.4 (25.6-33.8) μg/g creatinine for 2-hydroxynaphthalene, and 72.26 (63.3-82.5) μg/g creatinine for NAP metabolites. After controlling for variables such as the child's age, gender, maternal and paternal education, duration of breastfeeding, exposure to household passive smoking, formula feeding, cow's milk consumption, body mass index (BMI), and five dietary patterns, it was observed that individuals in the highest quartile of 2-hydroxynaphthalene and NAP metabolites had a significantly greater odd ratio for diabetes compared to those in the lowest quartile (P < 0.05).

Conclusion

Based on the findings of this study, it is suggested that exposure to PAH might be linked to an increased risk of T1D in children and adolescents. To clarify a potential causal relationship related to these findings, further prospective studies are needed.

Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry

Bladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.

Urinary microbiota and metabolic signatures associated with inorganic arsenic-induced early bladder lesions

Inorganic arsenic (iAs) contamination in drinking water is a global public health problem, and exposure to iAs is a known risk factor for bladder cancer. Perturbation of urinary microbiome and metabolome induced by iAs exposure may have a more direct effect on the development of bladder cancer. The aim of this study was to determine the impact of iAs exposure on urinary microbiome and metabolome, and to identify microbiota and metabolic signatures that are associated with iAs-induced bladder lesions. We evaluated and quantified the pathological changes of bladder, and performed 16S rDNA sequencing and mass spectrometry-based metabolomics profiling on urine samples from rats exposed to low (30 mg/L NaAsO₂) or high (100 mg/L NaAsO₂) iAs from early life (in utero and childhood) to puberty. Our results showed that iAs induced pathological bladder lesions, and more severe effects were noticed in the high-iAs group and male rats. Furthermore, six and seven featured urinary bacteria genera were identified in female and male offspring rats, respectively. Several characteristic urinary metabolites, including Menadione, Pilocarpine, N-Acetylornithine, Prostaglandin B1, Deoxyinosine, Biopterin, and 1-Methyluric acid, were identified significantly higher in the high-iAs groups. In addition, the correlation analysis demonstrated that the differential bacteria genera were highly correlated with the featured urinary metabolites. Collectively, these results suggest that exposure to iAs in early life not only causes bladder lesions, but also perturbs urinary microbiome composition and associated metabolic profiles, which shows a strong correlation. Those differential urinary genera and metabolites may contribute to bladder lesions, suggesting a potential for development of urinary biomarkers for iAs-induced bladder cancer.

Machine learning estimation of human body time using metabolomic profiling

Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.

Deciphering the Relationship between SARS-CoV-2 and Cancer

Some viruses are known to be associated with the onset of specific cancers. These microorganisms, oncogenic viruses or oncoviruses, can convert normal cells into cancer cells by modulating the central metabolic pathways or hampering genomic integrity mechanisms, consequently inhibiting the apoptotic machinery and/or enhancing cell proliferation. Seven oncogenic viruses are known to promote tumorigenesis in humans: human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV), Epstein-Barr virus (EBV), human T-cell leukemia virus 1 (HTLV-1), Kaposi sarcoma-associated herpesvirus (KSHV), and Merkel cell polyomavirus (MCPyV). Recent research indicates that SARS-CoV-2 infection and COVID-19 progression may predispose recovered patients to cancer onset and accelerate cancer development. This hypothesis is based on the growing evidence regarding the ability of SARS-CoV-2 to modulate oncogenic pathways, promoting chronic low-grade inflammation and causing tissue damage. Herein, we summarize the main relationships known to date between virus infection and cancer, providing a summary of the proposed biochemical mechanisms behind the cellular transformation. Mechanistically, DNA viruses (such as HPV, HBV, EBV, and MCPyV) encode their virus oncogenes. In contrast, RNA viruses (like HCV, HTLV-1) may encode oncogenes or trigger host oncogenes through cis-/-trans activation leading to different types of cancer. As for SARS-CoV-2, its role as an oncogenic virus seems to occur through the inhibition of oncosuppressors or controlling the metabolic and autophagy pathways in the infected cells. However, these effects could be significant in particular scenarios like those linked to severe COVID-19 or long COVID. On the other hand, looking at the SARS-CoV-2─cancer relationship from an opposite perspective, oncolytic effects and anti-tumor immune response were triggered by SARS-CoV-2 infection in some cases. In summary, our work aims to recall comprehensive attention from the scientific community to elucidate the effects of SARS-CoV-2 and, more in general, β-coronavirus infection on cancer susceptibility for cancer prevention or supporting therapeutic approaches.

Urinary 1H NMR Metabolomic Analysis of Prenatal Maternal Stress Due to a Natural Disaster Reveals Metabolic Risk Factors for Non-Communicable Diseases: The QF2011 Queensland Flood Study

Prenatal stress alters fetal programming, potentially predisposing the ensuing offspring to long-term adverse health outcomes. To gain insight into environmental influences on fetal development, this QF2011 study evaluated the urinary metabolomes of 4-year-old children (n = 89) who were exposed to the 2011 Queensland flood in utero. Proton nuclear magnetic resonance spectroscopy was used to analyze urinary metabolic fingerprints based on maternal levels of objective hardship and subjective distress resulting from the natural disaster. In both males and females, differences were observed between high and low levels of maternal objective hardship and maternal subjective distress groups. Greater prenatal stress exposure was associated with alterations in metabolites associated with protein synthesis, energy metabolism, and carbohydrate metabolism. These alterations suggest profound changes in oxidative and antioxidative pathways that may indicate a higher risk for chronic non-communicable diseases such obesity, insulin resistance, and diabetes, as well as mental illnesses, including depression and schizophrenia. Thus, prenatal stress-associated metabolic biomarkers may provide early predictors of lifetime health trajectories, and potentially serve as prognostic markers for therapeutic strategies in mitigating adverse health outcomes.

Exploring the association of physical activity with the plasma and urine metabolome in adolescents and young adults

BACKGROUND

Regular physical activity elicits many health benefits. However, the underlying molecular mechanisms through which physical activity influences overall health are less understood. Untargeted metabolomics enables system-wide mapping of molecular perturbations which may lend insights into physiological responses to regular physical activity. In this study, we investigated the associations of habitual physical activity with plasma and urine metabolome in adolescents and young adults.

METHODS

This cross-sectional study included participants from the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study with plasma samples n = 365 (median age: 18.4 (18.1, 25.0) years, 58% females) and 24 h urine samples n = 215 (median age: 18.1 (17.1, 18.2) years, 51% females). Habitual physical activity was assessed using a validated Adolescent Physical Activity Recall Questionnaire. Plasma and urine metabolite concentrations were determined using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) methods. In a sex-stratified analysis, we conducted principal component analysis (PCA) to reduce the dimensionality of metabolite data and to create metabolite patterns. Multivariable linear regression models were then applied to assess the associations between self-reported physical activity (metabolic equivalent of task (MET)-hours per week) with single metabolites and metabolite patterns, adjusted for potential confounders and controlling the false discovery rate (FDR) at 5% for each set of regressions.

RESULTS

Habitual physical activity was positively associated with the "lipid, amino acids and xenometabolite" pattern in the plasma samples of male participants only (β = 1.02; 95% CI: 1.01, 1.04, p = 0.001, adjusted p = 0.042). In both sexes, no association of physical activity with single metabolites in plasma and urine and metabolite patterns in urine was found (all adjusted p > 0.05).

CONCLUSIONS

Our explorative study suggests that habitual physical activity is associated with alterations of a group of metabolites reflected in the plasma metabolite pattern in males. These perturbations may lend insights into some of underlying mechanisms that modulate effects of physical activity.

Phenylalanine metabolism and tetrahydrobiopterin bio-availability in COVID-19 and HIV

Various metabolomics studies have reported increased phenylalanine serum concentrations in SARS-CoV-2 positive cases and have correlated increased phenylalanine with COVID-19 severity. In this study, we report similar results based upon metabolomics analysis of serum collected from a South African cohort of adults with confirmed COVID-19. The novelty of this study is the inclusion of HIV positive cases in the African context. We found that pre-existing HIV co-infection exacerbates the disruption of phenylalanine metabolism in COVID-19. What is lacking in literature is biological context and deeper understanding of perturbed phenylalanine metabolism in COVID-19. We delve deep into the metabolism of phenylalanine in COVID-19 and posit new insights for COVID-19 cases co-infected with HIV; namely, HIV-COVID-19 co-infected individuals do not have sufficient bioavailability of tetrahydrobiopterin (BH₄). Hence, we identify BH₄ as a potential supplement to alleviate/lessen COVID-19 symptoms.

Liquid chromatography-mass spectrometry-based metabolomic profiling reveals sex differences of lipid metabolism among the elderly from Southwest China

BACKGROUND

The sexual dimorphism represents one of the triggers of the metabolic disparities while the identification of sex-specific metabolites in the elderly has not been achieved.

METHODS

A group of aged healthy population from Southwest China were recruited and clinical characteristics were collected. Fasting plasma samples were obtained and untargeted liquid chromatography-mass spectrometry-based metabolomic analyses were performed. Differentially expressed metabolites between males and females were identified from the metabolomic analysis and metabolite sets enrichment analysis was employed.

RESULTS

Sixteen males and fifteen females were finally enrolled. According to clinical characteristics, no significant differences can be found except for smoking history. There were thirty-six differentially expressed metabolites between different sexes, most of which were lipids and lipid-like molecules. Twenty-three metabolites of males were increased while thirteen were decreased compared with females. The top four classes of metabolites were fatty acids and conjugates (30.6%), glycerophosphocholines (22.2%), sphingomyelins (11.1%), and flavonoids (8.3%). Fatty acids and conjugates, glycerophosphocholines, and sphingomyelins were significantly enriched in metabolite sets enrichment analysis.

CONCLUSIONS

Significant lipid metabolic differences were found between males and females among the elderly. Fatty acids and conjugates, glycerophosphocholines, and sphingomyelins may partly account for sex differences and can be potential treatment targets for sex-specific diseases.

Tissue-Specific Sex Difference in Mouse Eye and Brain Metabolome Under Fed and Fasted States

Purpose

Visual physiology and various ocular diseases demonstrate sexual dimorphisms; however, how sex influences metabolism in different eye tissues remains undetermined. This study aims to address common and tissue-specific sex differences in metabolism in the retina, RPE, lens, and brain under fed and fasted conditions.

Methods

After ad libitum fed or being deprived of food for 18 hours, mouse eye tissues (retina, RPE/choroid, and lens), brain, and plasma were harvested for targeted metabolomics. The data were analyzed with both partial least squares-discriminant analysis and volcano plot analysis.

Results

Among 133 metabolites that cover major metabolic pathways, we found 9 to 45 metabolites that are sex different in different tissues under the fed state and 6 to 18 metabolites under the fasted state. Among these sex-different metabolites, 33 were changed in 2 or more tissues, and 64 were tissue specific. Pantothenic acid, hypotaurine, and 4-hydroxyproline were the top commonly changed metabolites. The lens and the retina had the most tissue-specific, sex-different metabolites enriched in the metabolism of amino acid, nucleotide, lipids, and tricarboxylic acid cycle. The lens and the brain had more similar sex-different metabolites than other ocular tissues. The female RPE and female brain were more sensitive to fasting with more decreased metabolites in amino acid metabolism, tricarboxylic acid cycles, and glycolysis. The plasma had the fewest sex-different metabolites, with very few overlapping changes with tissues.

Conclusions

Sex has a strong influence on eye and brain metabolism in tissue-specific and metabolic state-specific manners. Our findings may implicate the sexual dimorphisms in eye physiology and susceptibility to ocular diseases.

Causal Inference of Central Nervous System-Regulated Hormones in COVID-19: A Bidirectional Two-Sample Mendelian Randomization Study

We assessed the causal association of three COVID-19 phenotypes with insulin-like growth factor 1, estrogen, testosterone, dehydroepiandrosterone (DHEA), thyroid-stimulating hormone, thyrotropin-releasing hormone, luteinizing hormone (LH), and follicle-stimulating hormone. We used bidirectional two-sample univariate and multivariable Mendelian randomization (MR) analyses to evaluate the direction, specificity, and causality of the association between CNS-regulated hormones and COVID-19 phenotypes. Genetic instruments for CNS-regulated hormones were selected from the largest publicly available genome-wide association studies of the European population. Summary-level data on COVID-19 severity, hospitalization, and susceptibility were obtained from the COVID-19 host genetic initiative. DHEA was associated with increased risks of very severe respiratory syndrome (odds ratio [OR] = 4.21, 95% confidence interval [CI]: 1.41-12.59), consistent with multivariate MR results (OR = 3.72, 95% CI: 1.20-11.51), and hospitalization (OR = 2.31, 95% CI: 1.13-4.72) in univariate MR. LH was associated with very severe respiratory syndrome (OR = 0.83; 95% CI: 0.71-0.96) in univariate MR. Estrogen was negatively associated with very severe respiratory syndrome (OR = 0.09, 95% CI: 0.02-0.51), hospitalization (OR = 0.25, 95% CI: 0.08-0.78), and susceptibility (OR = 0.50, 95% CI: 0.28-0.89) in multivariate MR. We found strong evidence for the causal relationship of DHEA, LH, and estrogen with COVID-19 phenotypes.

Time- and Sex-Dependent Effects of Fingolimod Treatment in a Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD) is the most common cause of dementia. Fingolimod has previously shown beneficial effects in different animal models of AD. However, it has shown contradictory effects when it has been applied at early disease stages. Our objective was to evaluate fingolimod in two different treatment paradigms. To address this aim, we treated male and female APP-transgenic mice for 50 days, starting either before plaque deposition at 50 days of age (early) or at 125 days of age (late). To evaluate the effects, we investigated the neuroinflammatory and glial markers, the Aβ load, and the concentration of the brain-derived neurotrophic factor (BDNF). We found a reduced Aβ load only in male animals in the late treatment paradigm. These animals also showed reduced microglia activation and reduced IL-1β. No other treatment group showed any difference in comparison to the controls. On the other hand, we detected a linear correlation between BDNF and the brain Aβ concentrations. The fingolimod treatment has shown beneficial effects in AD models, but the outcome depends on the neuroinflammatory state at the start of the treatment. Thus, according to our data, a fingolimod treatment would be effective after the onset of the first AD symptoms, mainly affecting the neuroinflammatory reaction to the ongoing Aβ deposition.

Exposomics as a tool to investigate differences in health and disease by sex and gender

The health and disease of an individual is mediated by their genetics, a lifetime of environmental exposures, and interactions between the two. Genetic or biological sex, including chromosome composition and hormone expression, may influence both the types and frequency of environmental exposures an individual experiences, as well as the biological responses an individual has to those exposures. Gender identity, which can be associated with social behaviors such as expressions of self, may also mediate the types and frequency of exposures an individual experiences. Recent advances in exposome-level analysis have progressed our understanding of how environmental factors affect health outcomes; however, the relationship between environmental exposures and sex- and gender-specific health remains underexplored. The comprehensive, non-targeted, and unbiased nature of exposomic research provides a unique opportunity to systematically evaluate how environmental exposures interact with biological sex and gender identity to influence health. In this forward-looking narrative review, we provide examples of how biological sex and gender identity influence environmental exposures, discuss how environmental factors may interact with biological processes, and highlight how an intersectional approach to exposomics can provide critical insights for sex- and gender-specific health sciences.

Linking Air Pollution Exposure to Blood-Based Metabolic Features in a Community-Based Aging Cohort with and without Dementia

BACKGROUND

Long-term exposure to air pollution has been associated with changes in levels of metabolites measured in the peripheral blood. However, most research has been conducted in ethnically homogenous, young or middle-aged populations.

OBJECTIVE

To study the relationship between the plasma metabolome and long-term exposure to three air pollutants: particulate matter (PM) less than 2.5μm in aerodynamic diameter (PM2.5), PM less than 10μm in aerodynamic diameter (PM10), and nitrogen dioxide (NO2) in an ethnically diverse, older population.

METHODS

Plasma metabolomic profiles of 107 participants of the Washington Heights and Inwood Community Aging Project in New York City, collected from 1995-2015, including non-Hispanic white, Caribbean Hispanic, and non-Hispanic Black older adults were used. We estimated the association between each metabolic feature and predicted annual mean exposure to the air pollutants using three approaches: 1) A metabolome wide association study framework; 2) Feature selection using elastic net regression; and 3) A multivariate approach using partial-least squares discriminant analysis.

RESULTS

79 features associated with exposure to PM2.5 but none associated with PM10 or NO2. PM2.5 exposure was associated with altered amino acid metabolism, energy production, and oxidative stress response, pathways also associated with Alzheimer's disease. Three metabolites were associated with PM2.5 exposure through all three approaches: cysteinylglycine disulfide, a diglyceride, and a dicarboxylic acid. The relationship between several features and PM2.5 exposure was modified by diet and metabolic diseases.

CONCLUSIONS

These relationships uncover the mechanisms through which PM2.5 exposure can lead to altered metabolic outcomes in an older population.

Biomarkers of post-match recovery in semi-professional and professional football (soccer)

High-level football (soccer) players face intense physical demands that result in acute and residual fatigue, impairing their physical performance in subsequent matches. Further, top-class players are frequently exposed to match-congested periods where sufficient recovery times are not achievable. To evaluate training and recovery strategies, the monitoring of players' recovery profiles is crucial. Along with performance and neuro-mechanical impairments, match-induced fatigue causes metabolic disturbances denoted by changes in chemical analytes that can be quantified in different body fluids such as blood, saliva, and urine, thus acting as biomarkers. The monitoring of these molecules might supplement performance, neuromuscular and cognitive measurements to guide coaches and trainers during the recovery period. The present narrative review aims to comprehensively review the scientific literature on biomarkers of post-match recovery in semi-professional and professional football players as well as provide an outlook on the role that metabolomic studies might play in this field of research. Overall, no single gold-standard biomarker of match-induced fatigue exists, and a range of metabolites are available to assess different aspects of post-match recovery. The use of biomarker panels might be suitable to simultaneously monitoring these broad physiological processes, yet further research on fluctuations of different analytes throughout post-match recovery is warranted. Although important efforts have been made to address the high interindividual heterogeneity of available markers, limitations inherent to these markers might compromise the information they provide to guide recovery protocols. Further research on metabolomics might benefit from evaluating the long-term recovery period from a high-level football match to shed light upon new biomarkers of post-match recovery.

Sex-Gender-Based Differences in Metabolic Diseases

Sexual dimorphism creates different biological and cellular activities and selective regulation mechanisms in males and females, thus generating differential responses in health and disease. In this scenario, the sex itself is a source of physiologic metabolic disparities that depend on constitutive genetic and epigenetic features that characterize in a specific manner one sex or the other. This has as a direct consequence a huge impact on the metabolic routes that drive the phenotype of an individual. The impact of sex is being clearly recognized also in disease, whereas male and females are more prone to the development of some disorders, or have selective responses to drugs and therapeutic treatments. Actually, very less is known regarding the probable differences guided by sex in the context of inherited metabolic disorders, owing to the scarce consideration of sex in such restricted field, accompanied by an intrinsic bias connected with the rarity of such diseases. Metabolomics technologies have been ultimately developed and adopted for being excellent tools for the investigation of metabolic mechanisms, for marker discovery or monitoring, and for supporting diagnostic procedures of metabolic disorders. Hence, metabolomic approaches can excellently embrace the discovery of sex differences, especially when associated to the outcome or the management of certain inborn errors of the metabolism.

Sex Differences in Arteriovenous Fistula Failure: Insights from Bioinformatics Analysis

(1) Background: Arteriovenous fistulas (AVFs) are the preferred access for hemodialysis. Unfortunately, about 60% of patients, especially female patients, fail to receive normal dialysis within one year after surgery because of AVF failure. However, the underlying mechanisms caused by sex differences in AVF failure remain unclear. (2) Methods: We performed analysis of DEGs and functional analysis with the dataset GSE119296 to reveal the biology underlying AVF failure. Immune responses were calculated using CIBERSORT. A protein-protein interaction network and hub gene were constructed using STRING and stepwise identification of potential drugs was performed online. (3) Results: Functional analysis showed that extracellular matrix reprogramming and PI3K-AKT pathway enrichment were significant in both male and female patients. COL1A1 was the hub gene in male patients, whereas CDK1 was the hub gene in female patients. Immune responses including γδ-T cells and mast cells are activated in female patients while no significant differences were noted in the male group. (4) Conclusions: In this study, we used a series of mature and recognized bioinformatic strategies to determine the following items: (1) Reveal the pathogenesis of AVF failure through HUB genes and signaling pathways between the different sexes. (2) Determine the relationship between sex differences in AVF failure and immune abnormalities. (3) Search for relevant sex-specific drugs targeting AVF failure.

The Aging Process: A Metabolomics Perspective

Aging process is characterized by a progressive decline of several organic, physiological, and metabolic functions whose precise mechanism remains unclear. Metabolomics allows the identification of several metabolites and may contribute to clarifying the aging-regulated metabolic pathways. We aimed to investigate aging-related serum metabolic changes using a metabolomics approach. Fasting blood serum samples from 138 apparently healthy individuals (20−70 years old, 56% men) were analyzed by Proton Nuclear Magnetic Resonance spectroscopy (1H NMR) and Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS), and for clinical markers. Associations of the metabolic profile with age were explored via Correlations (r); Metabolite Set Enrichment Analysis; Multiple Linear Regression; and Aging Metabolism Breakpoint. The age increase was positively correlated (0.212 ≤ r ≤ 0.370, p < 0.05) with the clinical markers (total cholesterol, HDL, LDL, VLDL, triacylglyceride, and glucose levels); negatively correlated (−0.285 ≤ r ≤ −0.214, p < 0.05) with tryptophan, 3-hydroxyisobutyrate, asparagine, isoleucine, leucine, and valine levels, but positively (0.237 ≤ r ≤ 0.269, p < 0.05) with aspartate and ornithine levels. These metabolites resulted in three enriched pathways: valine, leucine, and isoleucine degradation, urea cycle, and ammonia recycling. Additionally, serum metabolic levels of 3-hydroxyisobutyrate, isoleucine, aspartate, and ornithine explained 27.3% of the age variation, with the aging metabolism breakpoint occurring after the third decade of life. These results indicate that the aging process is potentially associated with reduced serum branched-chain amino acid levels (especially after the third decade of life) and progressively increased levels of serum metabolites indicative of the urea cycle.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

Sex modifies the association between urinary albumin-to-creatinine ratio and diabetes among adults in the United States (NHANES 2011-2018)

BACKGROUND

Studies on the association between urinary albumin-to-creatinine ratio (uACR) and diabetes are limited. We aimed to examine the association between uACR and diabetes among adults in the United States, with particular interest in sex differences.

METHODS

Overall, 5307 participants were included in this study. The exposure variable was uACR, where uACR = urine albumin/urine creatinine. The primary outcome of this study was diabetes, defined as self-reported physician diagnosis of diabetes, fasting plasma glucose concentration ≥ 7.0 mmol/L, or use of glucose-lowering drugs.

RESULTS

The average age of the participants in this study was 46.37 ± 17.38 years, 818 (15.41%) had diabetes and the median uACR was 7 mg/g (interquartile range, 4-12 mg/g). There was a significant positive association between uACR and diabetes (per natural log [uACR] increment: OR, 1.81; 95% CI 1.39-2.34). A multivariate logistic regression model demonstrated that per unit increment in LguACR, the diabetes prevalence increased 2.26-fold among male participants (OR 2.26, 95% CI 1.59-3.21). However, in female participants, we observed that uACR was not related to the prevalence of diabetes (odds ratio [OR], 1.28; 95% CI 0.82-2.01). Our findings showed that there was an interaction between sex and uACR (P for interaction = 0.049).

CONCLUSIONS

A higher uACR is significantly associated with an increased prevalence of diabetes, and sex can modify the relationship between them.