Prenatal metabolomic profiles mediate the effect of maternal obesity on early childhood growth trajectories and obesity risk: the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study

Metabolic abnormalities in the bone marrow cells of young offspring born to mothers with obesity

BACKGROUND/OBJECTIVES

Intrauterine metabolic reprogramming occurs in mothers with obesity during gestation, putting the offspring at high risk of developing obesity and associated metabolic disorders even before birth. We have generated a mouse model of maternal high-fat diet-induced obesity that recapitulates the metabolic changes seen in humans born to women with obesity.

METHODS

Here, we profiled and compared the metabolic characteristics of bone marrow cells of newly weaned 3-week-old offspring of dams fed either a high-fat (Off-HFD) or a regular diet (Off-RD). We utilized a state-of-the-art flow cytometry, and targeted metabolomics approach coupled with a Seahorse metabolic analyzer.

RESULTS

We revealed significant metabolic perturbation in the offspring of HFD-fed vs. RD-fed dams, including utilization of glucose primarily via oxidative phosphorylation. We also show a reduction in levels of amino acids, a phenomenon previously linked to bone marrow aging. Using flow cytometry, we found changes in the immune complexity of bone marrow cells and identified a unique B cell population expressing CD19 and CD11b in the bone marrow of three-week-old offspring of high-fat diet-fed mothers. Our data also revealed increased expression of Cyclooxygenase-2 (COX-2) on myeloid CD11b, and on CD11bhi B cells.

CONCLUSIONS

Altogether, we demonstrate that the offspring of mothers with obesity show metabolic and immune changes in the bone marrow at a very young age and prior to any symptomatic metabolic disease.

Investigating the relationship between blood metabolites and diabetic retinopathy using two-sample mendelian randomization and in vivo validation

We addressed fundamental questions about the influence of metabolites on the development of Diabetic retinopathy (DR), and explored the related pathological mechanism. Genome-wide association study (GWAS) database data for metabolites and DR were used to perform Mendelian randomization (MR) studies. The inverse variance weighting (IVW) was chosen as the primary analysis method. Sensitivity analysis was conducted using MR-PRESSO, leave-one-out and Cochran's Q test. Confounding factors were eliminated to ensure robustness. We also conducted metabolic pathway analysis. In vivo experimental validation was conducted using Sprague Dawley rats. The serum metabolites of the DR group rats and normal group rats were examined to evaluate the MR results. The screen identified eighteen metabolites associated with DR risk, twelve of which were known components. Seven metabolites were positively correlated with DR risk, while five could reduce it. Eight metabolites associated with proliferative DR (PDR) risk were identified, four of which are known components. Three of these were positively associated with PDR risk and one metabolite reduced PDR risk. Additionally, two possible metabolic pathways involved in the biological mechanism of DR were identified. The ELISA results showed that the serum levels of isoleucine and 4-HPA were significantly increased in DR rats, while the level of inosine was decreased. This study offers novel insights into the biological mechanisms underlying DR. Metabolites that are causally linked to DR may serve as promising biomarkers and therapeutic targets.

Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium

INTRODUCTION

Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility.

OBJECTIVE

The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework.

METHODS

We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure.

RESULTS

Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction.

CONCLUSIONS

Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Metabolic abnormalities in the bone marrow cells of young offspring born to obese mothers

Intrauterine metabolic reprogramming occurs in obese mothers during gestation, putting the offspring at high risk of developing obesity and associated metabolic disorders even before birth. We have generated a mouse model of maternal high-fat diet-induced obesity that recapitulates the metabolic changes seen in humans. Here, we profiled and compared the metabolic characteristics of bone marrow cells of newly weaned 3-week-old offspring of dams fed either a high-fat (Off-HFD) or a regular diet (Off-RD). We utilized a state-of-the-art targeted metabolomics approach coupled with a Seahorse metabolic analyzer. We revealed significant metabolic perturbation in the offspring of HFD-fed vs. RD-fed dams, including utilization of glucose primarily via oxidative phosphorylation, and reduction in levels of amino acids, a phenomenon previously linked to aging. Furthermore, in the bone marrow of three-week-old offspring of high-fat diet-fed mothers, we identified a unique B cell population expressing CD19 and CD11b, and found increased expression of Cyclooxygenase-2 (COX-2) on myeloid CD11b, and on CD11b hi B cells, with all the populations being significantly more abundant in offspring of dams fed HFD but not a regular diet. Altogether, we demonstrate that the offspring of obese mothers show metabolic and immune changes in the bone marrow at a very young age and prior to any symptomatic metabolic disease.