Sex differences in systemic metabolites at four life stages: cohort study with repeated metabolomics

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.

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.

Past or Present; Which Exposures Predict Metabolomic Aging Better? The Doetinchem Cohort Study

People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36-75 of Round 4 (2003-2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987-1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R2 6.8 and 5.8, respectively) and women (R2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men 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.

COVID-19: A complex disease with a unique metabolic signature

Plasma of COVID-19 patients contains a strong metabolomic/lipoproteomic signature, revealed by the NMR analysis of a cohort of >500 patients sampled during various waves of COVID-19 infection, corresponding to the spread of different variants, and having different vaccination status. This composite signature highlights common traits of the SARS-CoV-2 infection. The most dysregulated molecules display concentration trends that scale with disease severity and might serve as prognostic markers for fatal events. Metabolomics evidence is then used as input data for a sex-specific multi-organ metabolic model. This reconstruction provides a comprehensive view of the impact of COVID-19 on the entire human metabolism. The human (male and female) metabolic network is strongly impacted by the disease to an extent dictated by its severity. A marked metabolic reprogramming at the level of many organs indicates an increase in the generic energetic demand of the organism following infection. Sex-specific modulation of immune response is also suggested.

Sex differences in lipids: A life course approach

Differences between men and women in lipids and lipoproteins are observed in distribution and trajectory from infancy to adulthood in the general population. However, these differences are more pronounced in hereditary lipid disorders such as familial hypercholesterolemia (FH) when absolute cholesterol levels are higher from birth onwards. In the early life course, girls compared to boys have higher low-density lipoprotein cholesterol (LDL-C) levels and total cholesterol, while high-density lipoprotein cholesterol (HDL-C) levels are similar. In early adulthood to middle-age, women have lower LDL-C and higher HDL-C levels, as LDL-C levels increase and HDLC levels decrease in men. In the elderly, all lipids - total cholesterol, LDL-C, HDL-C and triglyceride levels decrease but are more pronounced in men. Lipid levels are also affected by specific transitions in girls/women such as the menstrual cycle, pregnancy, breastfeeding and menopause. Lipid levels fluctuate during the menstrual cycle. During pregnancy a physiological increase of LDL-C and even a larger increase in triglyceride levels are observed. Pregnancy has a double impact on LDL-C accumulation in women with FH as they have to stop statins, and the absolute increase in LDL-C is higher than in women without FH. In the menopausal transition, women develop a more adverse lipid profile. Therefore, it is important to take into account both sex and the life course when assessing a lipid profile.

Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study

BACKGROUND AND AIMS

Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV).

METHODS

From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition.

RESULTS

In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate.

CONCLUSIONS

Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.

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.

Plasma lipoprotein subclass variation in middle-aged and older adults: Sex-stratified distributions and associations with health status and cardiometabolic risk factors

BACKGROUND

Circulating lipids and lipoproteins mediate cardiovascular risk, however routine plasma lipid biochemistry provides limited information on pro-atherogenic remnant particles.

OBJECTIVE

We analysed plasma lipoprotein subclasses including very low-density and intermediate-density lipoprotein (VLDL and IDL); and assessed their associations with health and cardiometabolic risk.

METHODS

From 1,976 community-dwelling adults aged 45-67 years, 114/1071 women (10.6%) and 153/905 men (16.9%) were categorised as very healthy. Fasting plasma lipoprotein profiles comprising 112 parameters were measured using 1H nuclear magnetic resonance (NMR) spectroscopy, and associations with health status and cardiometabolic risk factors examined.

RESULTS

HDL cholesterol was higher, and IDL and VLDL cholesterol and triglycerides lower, in very healthy women compared to other women, and women compared to men. IDL and VLDL cholesterol and triglyceride were lower in very healthy men compared to other men. HDL cholesterol and apolipoprotein (apo) A-I were inversely, and IDL and VLDL cholesterol, apoB-100, and apoB-100/apoA-I ratio directly associated with body mass index (BMI) in women and men. In women, LDL, IDL and VLDL cholesterol increased with age. Women with diabetes and cardiovascular disease had higher cholesterol, triglycerides, phospholipids and free cholesterol across IDL and VLDL fractions, with similar trends for men with diabetes.

CONCLUSION

Lipoprotein subclasses and density fractions, and their lipid and apolipoprotein constituents, are differentially distributed by sex, health status and BMI. Very healthy women and men are distinguished by favorable lipoprotein profiles, particularly lower concentrations of VLDL and IDL, providing reference intervals for comparison with general populations and adults with cardiometabolic risk factors.

Urinary Metabolomic Profile of Youth at Risk of Chronic Kidney Disease in Nicaragua

Key Points

Urinary concentrations of glycine, a molecule associated with thermoregulation, were elevated among youth from a high-risk region for chronic kidney disease of non-traditional etiology (CKDnt). Urinary concentrations of pyruvate, citric acid, and inosine were lower among youth at higher risk of CKDnt, suggesting renal stress. Metabolomic analyses may shed light on early disease processes or profiles or risk in the context of CKDnt.

Background

CKD of a nontraditional etiology (CKDnt) is responsible for high mortality in Central America, although its causes remain unclear. Evidence of kidney dysfunction has been observed among youth, suggesting that early kidney damage contributing to CKDnt may initiate in childhood.

Methods

Urine specimens of young Nicaraguan participants 12–23 years without CKDnt (n =136) were analyzed by proton nuclear magnetic resonance spectroscopy for 50 metabolites associated with kidney dysfunction. Urinary metabolite levels were compared by, regional CKDnt prevalence, sex, age, and family history of CKDnt using supervised statistical methods and pathway analysis in MetaboAnalyst. Magnitude of associations and changes over time were assessed through multivariable linear regression.

Results

In adjusted analyses, glycine concentrations were higher among youth from high-risk regions (β =0.82, [95% confidence interval, 0.16 to 1.85]; P = 0.01). Pyruvate concentrations were lower among youth with low eGFR (β = −0.36 [95% confidence interval, −0.57 to −0.04]; P = 0.03), and concentrations of other citric acid cycle metabolites differed by key risk factors. Over four years, participants with low eGFR experienced greater declines in 1-methylnicotinamide and 2-oxoglutarate and greater increases in citrate and guanidinoacetate concentrations.

Conclusion

Urinary concentration of glycine, a molecule associated with thermoregulation and kidney function preservation, was higher among youth in high-risk CKDnt regions, suggestive of greater heat exposure or renal stress. Lower pyruvate concentrations were associated with low eGFR, and citric acid cycle metabolites, such as pyruvate, likely relate to mitochondrial respiration rates in the kidneys. Participants with low eGFR experienced longitudinal declines in concentrations of 1-methylnicotinamide, an anti-inflammatory metabolite associated with anti-fibrosis in tubule cells. These findings merit further consideration in research on the origins of CKDnt.

Human Metabolome Reference Database in a Biracial Cohort across the Adult Lifespan

As one of the OMICS in systems biology, metabolomics defines the metabolome and simultaneously quantifies numerous metabolites that are final or intermediate products and effectors of upstream biological processes. Metabolomics provides accurate information that helps determine the physiological steady state and biochemical changes during the aging process. To date, reference values of metabolites across the adult lifespan, especially among ethnicity groups, are lacking. The "normal" reference values according to age, sex, and race allow the characterization of whether an individual or a group deviates metabolically from normal aging, encompass a fundamental element in any study aimed at understanding mechanisms at the interface between aging and diseases. In this study, we established a metabolomics reference database from 20-100 years of age from a biracial sample of community-dwelling healthy men and women and examined metabolite associations with age, sex, and race. Reference values from well-selected healthy individuals can contribute to clinical decision-making processes of metabolic or related diseases.

Sex-specific trajectories of molecular cardiometabolic traits from childhood to young adulthood

BACKGROUND

The changes which typically occur in molecular causal risk factors and predictive biomarkers for cardiometabolic diseases across early life are not well characterised.

METHODS

We quantified sex-specific trajectories of 148 metabolic trait concentrations including various lipoprotein subclasses from age 7 years to 25 years. Data were from 7065 to 7626 offspring (11 702 to14 797 repeated measures) of the Avon Longitudinal Study of Parents and Children birth cohort study. Outcomes were quantified using nuclear magnetic resonance spectroscopy at 7, 15, 18 and 25 years. Sex-specific trajectories of each trait were modelled using linear spline multilevel models.

RESULTS

Females had higher very-low-density lipoprotein (VLDL) particle concentrations at 7 years. VLDL particle concentrations decreased from 7 years to 25 years with larger decreases in females, leading to lower VLDL particle concentrations at 25 years in females. For example, females had a 0.25 SD (95% CI 0.20 to 0.31) higher small VLDL particle concentration at 7 years; mean levels decreased by 0.06 SDs (95% CI -0.01 to 0.13) in males and 0.85 SDs (95% CI 0.79 to 0.90) in females from 7 years to 25 years, leading to 0.42 SDs (95% CI 0.35 to 0.48) lower small VLDL particle concentrations in females at 25 years. Females had lower high-density lipoprotein (HDL) particle concentrations at 7 years. HDL particle concentrations increased from 7 years to 25 years with larger increases among females leading to higher HDL particle concentrations in females at 25 years.

CONCLUSION

Childhood and adolescence are important periods for the emergence of sex differences in atherogenic lipids and predictive biomarkers for cardiometabolic disease, mostly to the detriment of males.

Determinants of Lipid Parameters in Patients without Diagnosed Cardiovascular Disease-Results of the Polish Arm of the EUROASPIRE V Survey

To assess the determinants of lipid parameters in primary care patients without diagnosed cardiovascular disease (CVD), a cross-sectional study was conducted during 2018-2019 with a total of 200 patients. The following lipid parameters were measured: total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), small, dense LDL (sdLDL-C), and lipoprotein (a) (Lp(a)). Predictors of elevated and adequately controlled lipid parameters were assessed with logistic regression analysis. Older age was related to higher risk of TC ≥ 6.2 mmol/L [OR 1.03 (95% CI 1.0-1.05)], sdLDL-C ≥ 1.0 mmol/L [OR 1.05 (95% CI 1.0-1.1)], and decreased risk of Lp(a) ≥ 50 mg/dL [OR 0.97 (95% CI 0.94-0.99)]. Patients with diabetes mellitus (DM) had increased probability of TG ≥ 2.25 mmol/L [OR 3.77 (95% CI 1.34-10.6)] and Lp(a) ≥ 50 mg/dL [OR 2.97 (1.34-6.10)] as well as adequate control of TG and Lp(a). Higher material status was related to lower risk of TC ≥ 6.2 mmol/L [OR 0.19 (95% CI 0.04-0.82)] and LDL-C ≥ 3.6 mmol/L [OR 0.33 (95% CI 0.12-0.92)]. High BMI was related to increased [OR 1.14 (95% CI 1.02-1.29)], and female gender [OR 0.33 (95% CI 0.12-0.96)] and hypertension [OR 0.29 (95% CI 0.1-0.87)] to decreased risk of TG ≥ 2.25 mmol/L [OR 1.14 (95% CI 1.02-1.29)]. Taking lipid-lowering drugs (LLD) was associated with LDL-C < 2.6 mmol/L [OR 2.1 (95% CI 1.05-4.19)] and Lp(a) < 30 mg/dL [OR 0.48 (95% CI 0.25-0.93)]. Physical activity was related to LDL-C < 2.6 mmol/L [OR 2.02 (95% CI 1.02-3.98)]. Higher abdominal circumference was associated with decreased risk of TG < 1.7 mmol/L [OR 0.96 (95% CI 0.93-0.99)]. Elevated lipid parameters were related to age, gender, material status, BMI, history of DM, and hypertension. Adequate control was associated with age, education, physical activity, LLD, history of DM, and abdominal circumference.

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.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The "Omics" field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.

Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative "omics" approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

Lower serum triglyceride levels linked to more severe motor performance in Parkinson’s disease

Introduction

Emerging evidence has suggested that lipid metabolism is correlated with Parkinson’s disease (PD) onset and progression. However, the effect of lipid metabolism on motor performance in PD patients is still unknown. This study estimated the association between lipid profiles and the severity of motor performance in PD.

Methods

This cross-sectional study enrolled 279 idiopathic PD patients from the Department of Neurology of Beijing Tiantan Hospital from May 2016 to August 2018. Serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (Apo-A1), and apolipoprotein B (Apo-B) levels were detected in fast serum samples. Motor performance was assessed by Movement Disorder Society-Unified Parkinson’s Disease Rating Scale part III (MDS-UPDRS III) total scores and subscores in these patients. The associations of lipid profiles with motor performance were analyzed using multivariable linear regression models.

Results

Compared to males, females with PD exhibited significantly higher serum TC, LDL-C, HDL-C, Apo-A1, and Apo-B levels. When accounting for covariates, lower serum TG levels were significantly associated with higher MDS-UPDRS III total scores and gait/postural instability subscores. Additionally, the univariate linear regression model showed that in males with PD, serum HDL-C or Apo-A1 levels were significantly associated with tremor subscores.

Conclusion

Lower serum TG levels were associated with more severe motor performance in patients with PD and TG may be a potential predictive biomarker for motor performance in PD patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10072-022-06113-9.

Menopause modulates the circulating metabolome: evidence from a prospective cohort study

AIMS

We studied the changes in the circulating metabolome and their relation to the menopausal hormonal shift in 17β-oestradiol and follicle-stimulating hormone levels among women transitioning from perimenopause to early postmenopause.

METHODS AND RESULTS

We analysed longitudinal data from 218 Finnish women, 35 of whom started menopausal hormone therapy during the study. The menopausal transition was monitored with menstrual diaries and serum hormone measurements. The median follow-up was 14 months (interquartile range: 8-20). Serum metabolites were quantified with targeted nuclear magnetic resonance metabolomics. The model results were adjusted for age, follow-up duration, education, lifestyle, and multiple comparisons. Menopause was associated with 85 metabolite measures. The concentration of apoB (0.17 standard deviation [SD], 99.5% confidence interval [CI] 0.03-0.31), very-low-density lipoprotein triglycerides (0.25 SD, CI 0.05-0.45) and particles (0.21 SD, CI 0.05-0.36), low-density lipoprotein (LDL) cholesterol (0.17 SD, CI 0.01-0.34) and particles (0.17 SD, CI 0.03-0.31), high-density lipoprotein (HDL) triglycerides (0.24 SD, CI 0.02-0.46), glycerol (0.32 SD, CI 0.07-0.58) and leucine increased (0.25 SD, CI 0.02-0.49). Citrate (-0.36 SD, CI -0.57 to -0.14) and 3-hydroxybutyrate concentrations decreased (-0.46 SD, CI -0.75 to -0.17). Most metabolite changes were associated with the menopausal hormonal shift. This explained 11% and 9% of the LDL cholesterol and particle concentration increase, respectively. Menopausal hormone therapy was associated with increased medium-to-large HDL particle count and decreased small-to-medium LDL particle and glycine concentration.

CONCLUSIONS

Menopause is associated with proatherogenic circulating metabolome alterations. Female sex hormones levels are connected to the alterations, highlighting their impact on women's cardiovascular health.

Sex differences in the human metabolome

BACKGROUND

The sexual dimorphism represents one of the triggers of the metabolic disparities between the organisms, advising about wild implications in research or diagnostics contexts. Despite the mounting recognition of the importance of sex consideration in the biomedical fields, the identification of male- and female-specific metabolic signatures has not been achieved.

MAIN BODY

This review pointed the focus on the metabolic differences related to the sex, evidenced by metabolomics studies performed on healthy populations, with the leading aim of understanding how the sex influences the baseline metabolome. The main shared signatures and the apparent dissimilarities between males and females were extracted and highlighted from the metabolome of the most commonly analyzed biological fluids, such as serum, plasma, and urine. Furthermore, the influence of age and the significant interactions between sex and age have been taken into account.

CONCLUSIONS

The recognition of sex patterns in human metabolomics has been defined in diverse biofluids. The detection of sex- and age-related differences in the metabolome of healthy individuals are helpful for translational applications from the bench to the bedside to set targeted diagnostic and prevention approaches in the context of personalized medicine.

Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology: disclosure of fundamental structural and metabolic relationships

BACKGROUND

Quantitative lipoprotein analytics using nuclear magnetic resonance (NMR) spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilized also in large biobanks. It allows the comprehensive characterization of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualized here in relation to lipoprotein metabolism with particular attention on the fundamental characteristics of subclass particle numbers, lipid concentrations and compositional measures.

METHODS AND RESULTS

The NMR methodology was applied to fasting serum samples from Northern Finland Birth Cohorts 1966 and 1986 with 5651 and 5605 participants, respectively. All results were highly consistent between the cohorts. Circulating lipid concentrations in a particular lipoprotein subclass arise predominantly as the result of the circulating number of those subclass particles. The spherical lipoprotein particle shape, with a radially oriented surface monolayer, imposes size-dependent biophysical constraints for the lipid composition of individual subclass particles and inherently restricts the accommodation of metabolic changes via compositional modifications. The new finding that the relationship between lipoprotein subclass particle concentrations and the particle size is log-linear reveals that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations.

CONCLUSIONS

The fundamental structural and metabolic relationships between lipoprotein subclasses elucidated in this study empower detailed interpretation of lipoprotein metabolism. Understanding the intricate details of these extensive data is important for the precise interpretation of novel therapeutic opportunities and for fully utilizing the potential of forthcoming analyses of genetic and metabolic data in large biobanks.

The newborn metabolome: associations with gestational diabetes, sex, gestation, birth mode, and birth weight

BACKGROUND

Pathways towards many adult-onset conditions begin early in life, even in utero. Maternal health in pregnancy influences this process, but little is known how it affects neonatal metabolism. We investigated associations between pregnancy and birth factors and cord blood metabolomic profile in a large, population-derived cohort.

METHODS

Metabolites were measured using nuclear magnetic resonance in maternal (28 weeks gestation) and cord serum from 912 mother-child pairs in the Barwon Infant Study pre-birth cohort. Associations between maternal (metabolites, age, BMI, smoking), pregnancy (pre-eclampsia, gestational diabetes (GDM)), and birth characteristics (delivery mode, gestational age, weight, infant sex) with 72 cord blood metabolites were examined by linear regression.

RESULTS

Delivery mode, sex, gestational age, and birth weight were associated with specific metabolite levels in cord blood, including amino acids, fatty acids, and cholesterols. GDM was associated with higher cord blood levels of acetoacetate and 3-hydroxybutyrate.

CONCLUSIONS

Neonatal factors, particularly delivery mode, were associated with many cord blood metabolite differences, including those implicated in later risk of cardiometabolic disease. Associations between GDM and higher offspring ketone levels at birth are consistent with maternal ketosis in diabetic pregnancies. Further work is needed to determine whether these neonatal metabolome differences associate with later health outcomes.

IMPACT

Variations in blood metabolomic profile have been linked to health status in adults and children, but corresponding data in neonates are scarce. We report evidence that pregnancy complications, mode of delivery, and offspring characteristics, including sex, are independently associated with a range of circulating metabolites at birth, including ketone bodies, amino acids, cholesterols, and inflammatory markers. Independent of birth weight, exposure to gestational diabetes is associated with higher cord blood ketone bodies and citrate. These findings suggest that pregnancy complications, mode of delivery, gestational age, and measures of growth influence metabolic pathways prior to birth, potentially impacting later health and development.

Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms

Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer’s, Parkinson’s disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app “MetaboExtract”. Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.

Bibliometric and Visual Analysis on Metabolomics in Coronary Artery Disease Research

Background

Metabolomics has immense research value in coronary artery disease and has drawn increasing attention over the past decades. Many articles have been published in this field, which may challenge researchers aiming to investigate all the available information. However, bibliometrics can provide deep insights into this research field.

Objective

We aimed to qualitatively and quantitatively study metabolomics and coronary artery disease research, visually analyse the development status, trends, research hotspots, and frontiers of this field, and provide a reference for research on coronary artery disease.

Methods

Articles were acquired from the Web of Science Core Collection. VOSviewer and CiteSpace software were used to analyse publication growth, country/region, institution, journal distribution, author, reference, and keywords, and detected the keywords with strong citation burstness to identify emerging topics.

Results

A total of 1121 references were obtained, and the annual number of publications increased over the past 16 years. Metabolomics research has shown a gradual upward trend in coronary artery disease. The United States of America and China ranked at the top in terms of percentage of articles. The institution with the highest number of research publications in this field was Harvard University, followed by the University of California System and Brigham Women's Hospital. The most frequently cited authors included Hazen SL, Tang WH, and Wang ZN. Ala-Korpela M was the most productive author, followed by Clish CB and Adamski J. The journal with the most publications in this field was Scientific Reports, followed by PLoS One and the Journal of Proteome Research. The keywords used at a high frequency were "risk," "biomarkers," "insulin resistance," and "atherosclerosis." Burst detection analysis of top keywords showed that "microbiota," "tryptophan," and "diabetes" are the current research frontiers in this field.

Conclusion

This study provides useful information for acquiring knowledge on metabolomics and coronary artery diseases. Metabolomics research has shown a gradual upward trend in coronary artery disease studies over the past 16 years. Research on tryptophan metabolism regulated by intestinal flora will become an emerging academic trend in this field, which can offer guidance for more extensive and in-depth studies in the future.

Age, Sex, Body Mass Index, Diet and Menopause Related Metabolites in a Large Homogeneous Alpine Cohort

Metabolomics in human serum samples provide a snapshot of the current metabolic state of an individuum. Metabolite concentrations are influenced by both genetic and environmental factors. Concentrations of certain metabolites can further depend on age, sex, menopause, and diet of study participants. A better understanding of these relationships is pivotal for the planning of metabolomics studies involving human subjects and interpretation of their results. We generated one of the largest single-site targeted metabolomics data sets consisting of 175 quantified metabolites in 6872 study participants. We identified metabolites significantly associated with age, sex, body mass index, diet, and menopausal status. While most of our results agree with previous large-scale studies, we also found novel associations including serotonin as a sex and BMI-related metabolite and sarcosine and C2 carnitine showing significantly higher concentrations in post-menopausal women. Finally, we observed strong associations between higher consumption of food items and certain metabolites, mostly phosphatidylcholines and lysophosphatidylcholines. Most, and the strongest, relationships were found for habitual meat intake while no significant relationships were found for most fruits, vegetables, and grain products. Summarizing, our results reconfirm findings from previous population-based studies on an independent cohort. Together, these findings will ultimately enable the consolidation of sets of metabolites which are related to age, sex, BMI, and menopause as well as to participants’ diet.

Genetic, Molecular, and Cellular Determinants of Sex-Specific Cardiovascular Traits

Despite the well-known sex dimorphism in cardiovascular disease traits, the exact genetic, molecular, and cellular underpinnings of these differences are not well understood. A growing body of evidence currently points at the links between cardiovascular disease traits and the genome, epigenome, transcriptome, and metabolome. However, the sex-specific differences in these links remain largely unstudied due to challenges in bioinformatic methods, inadequate statistical power, analytic costs, and paucity of valid experimental models. This review article provides an overview of the literature on sex differences in genetic architecture, heritability, epigenetic changes, transcriptomic signatures, and metabolomic profiles in relation to cardiovascular disease traits. We also review the literature on the associations between sex hormones and cardiovascular disease traits and discuss the potential mechanisms underlying these associations, focusing on human studies.

Asparagine Metabolism in Tumors Is Linked to Poor Survival in Females with Colorectal Cancer: A Cohort Study

The interplay between the sex-specific differences in tumor metabolome and colorectal cancer (CRC) prognosis has never been studied and represents an opportunity to improve patient outcomes. This study examines the link between tumor metabolome and prognosis by sex for CRC patients. Using untargeted metabolomics analysis, abundances of 91 metabolites were obtained from primary tumor tissues from 197 patients (N = 95 females, N = 102 males) after surgical colectomy for stage I-III CRC. Cox Proportional hazard (PH) regression models estimated the associations between tumor metabolome and 5-year overall survival (OS) and recurrence-free survival (RFS), and their interactions with sex. Eleven metabolites had significant sex differences in their associations with 5-year OS, and five metabolites for 5-year RFS. The metabolites asparagine and serine had sex interactions for both OS and RFS. Furthermore, in the asparagine synthetase (ASNS)-catalyzed asparagine synthesis pathway, asparagine was associated with substantially poorer OS (HR (95% CI): 6.39 (1.78–22.91)) and RFS (HR (95% CI): 4.36 (1.39–13.68)) for female patients only. Similar prognostic disadvantages in females were seen in lysophospholipid and polyamine synthesis. Unique metabolite profiles indicated that increased asparagine synthesis was associated with poorer prognosis for females only, providing insight into precision medicine for CRC treatment stratified by sex.

Sex-specific associations of adiposity with cardiometabolic traits in the UK: A multi-life stage cohort study with repeat metabolomics

BACKGROUND

Sex differences in cardiometabolic disease risk are commonly observed across the life course but are poorly understood and may be due to different associations of adiposity with cardiometabolic risk in females and males. We examined whether adiposity is differently associated with cardiometabolic trait levels in females and males at 3 different life stages.

METHODS AND FINDINGS

Data were from 2 generations (offspring, Generation 1 [G1] born in 1991/1992 and their parents, Generation 0 [G0]) of a United Kingdom population-based birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). Follow-up continues on the cohort; data up to 25 y after recruitment to the study are included in this analysis. Body mass index (BMI) and total fat mass from dual-energy X-ray absorptiometry (DXA) were measured at mean age 9 y, 15 y, and 18 y in G1. Waist circumference was measured at 9 y and 15 y in G1. Concentrations of 148 cardiometabolic traits quantified using nuclear magnetic resonance spectroscopy were measured at 15 y, 18 y, and 25 y in G1. In G0, all 3 adiposity measures and the same 148 traits were available at 50 y. Using linear regression models, sex-specific associations of adiposity measures at each time point (9 y, 15 y, and 18 y) with cardiometabolic traits 3 to 6 y later were examined in G1. In G0, sex-specific associations of adiposity measures and cardiometabolic traits were examined cross-sectionally at 50 y. A total of 3,081 G1 and 4,887 G0 participants contributed to analyses. BMI was more strongly associated with key atherogenic traits in males compared with females at younger ages (15 y to 25 y), and associations were more similar between the sexes or stronger in females at 50 y, particularly for apolipoprotein B-containing lipoprotein particles and lipid concentrations. For example, a 1 standard deviation (SD) (3.8 kg/m2) higher BMI at 18 y was associated with 0.36 SD (95% confidence interval [CI] = 0.20, 0.52) higher concentrations of extremely large very-low-density lipoprotein (VLDL) particles at 25 y in males compared with 0.15 SD (95% CI = 0.09, 0.21) in females, P value for sex difference = 0.02. By contrast, at 50 y, a 1 SD (4.8 kg/m2) higher BMI was associated with 0.33 SD (95% CI = 0.25, 0.42) and 0.30 SD (95% CI = 0.26, 0.33) higher concentrations of extremely large VLDL particles in males and females, respectively, P value for sex difference = 0.42. Sex-specific associations of DXA-measured fat mass and waist circumference with cardiometabolic traits were similar to findings for BMI and cardiometabolic traits at each age. The main limitation of this work is its observational nature, and replication in independent cohorts using methods that can infer causality is required.

CONCLUSIONS

The results of this study suggest that associations of adiposity with adverse cardiometabolic risk begin earlier in the life course among males compared with females and are stronger until midlife, particularly for key atherogenic lipids. Adolescent and young adult males may therefore be high priority targets for obesity prevention efforts.

Gender-Specific Metabolomics Approach to Kidney Cancer

Renal cell carcinoma (RCC) is the most common form of kidney malignancy. RCC is more common among men with a 2/1 male/female incidence ratio worldwide. Given the underlying epidemiological differences in the RCC incidence between males and females, we explored the gender specific ¹H NMR serum metabolic profiles of RCC patients and their matched controls. A number of differential metabolites were shared by male and female RCC patients. These RCC specific changes included lower lactate, threonine, histidine, and choline levels together with increased levels of pyruvate, N-acetylated glycoproteins, beta-hydroxybutyrate, acetoacetate, and lysine. Additionally, serum lactate/pyruvate ratio was a strong predictor of RCC status regardless of gender. Although only moderate changes in metabolic profiles were observed between control males and females there were substantial gender related differences among RCC patients. Gender specific metabolic features associated with RCC status were identified suggesting that different metabolic panels could be leveraged for a more precise diagnostic.

The Relation Between Adult Weight Gain, Adipocyte Volume, and the Metabolic Profile at Middle Age

CONTEXT

Weight gain during adulthood increases cardiometabolic disease risk, possibly through adipocyte hypertrophy.

OBJECTIVE

We aimed to study the specific metabolomic profile of adult weight gain, and to examine its association with adipocyte volume.

METHODS

Nuclear magnetic resonance-based metabolomics were measured in the Netherlands Epidemiology of Obesity (NEO) study (n = 6347, discovery) and Oxford Biobank (n = 6317, replication). Adult weight gain was calculated as the absolute difference between body mass index (BMI) at middle age and recalled BMI at age 20 years. We performed linear regression analyses with both exposures BMI at age 20 years and weight gain, and separately with BMI at middle age in relation to 149 serum metabolomic measures, adjusted for age, sex, and multiple testing. Additionally, subcutaneous abdominal adipocyte biopsies were collected in a subset of the Oxford Biobank (n = 114) to estimate adipocyte volume.

RESULTS

Mean (SD) weight gain was 4.5 (3.7) kg/m2 in the NEO study and 3.6 (3.7) kg/m2 in the Oxford Biobank. Weight gain, and not BMI at age 20 nor middle age, was associated with concentrations of 7 metabolomic measures after successful replication, which included polyunsaturated fatty acids, small to medium low-density lipoproteins, and total intermediate-density lipoprotein. One SD weight gain was associated with 386 μm3 (95% CI, 143-629) higher median adipocyte volume. Adipocyte volume was associated with lipoprotein particles specific for adult weight gain.

CONCLUSION

Adult weight gain is associated with specific metabolomic alterations of which the higher lipoprotein concentrations were likely contributed by larger adipocyte volumes, presumably linking weight gain to cardiometabolic disease.