Distinct metabolite profiles of adiposity indices and their relationships with habitual diet in young adults

Lipidomic perturbations of normal-weight adiposity phenotypes and their mediations on diet-adiposity associations

BACKGROUND & AIMS

Normal-weight obesity (NWO) and normal-weight central obesity (NWCO) have been linked to higher cardiometabolic risks, but their etiological bases and attributable dietary factors remain unclear. In this study we therefore aimed to identify lipidomic signatures and dietary factors related to NWO and NWCO and to explore the mediation associations of lipids in diet-adiposity associations.

METHODS

Using a high-coverage targeted lipidomic approach, we quantified 1245 serum lipids in participants with NWO (n = 150), NWCO (n = 150), or propensity-score-matched normal-weight controls (n = 150) based on the Regional Ethnic Cohort Study in Northwest China. Consumption frequency of 28 major food items was recorded using a food frequency questionnaire.

RESULTS

Profound lipidomic perturbations of NWCO relative to NWO were observed, and 249 (dominantly glycerolipids) as well as 48 (dominantly glycerophospholipids) lipids were exclusively associated with NWCO or NWO. Based on strong lipidomic signatures identified by a LASSO model, phospholipid biosynthesis was the top enriched pathway of NWCO, and sphingolipid metabolism was the top pathway of NWO. Remarkably, sphingolipids were positively associated with NWO and NWCO, but lyso-phosphatidylcholines were negatively associated with them. Rice, fruit juice, and carbonated drink intakes were positively associated with the risk of NWCO. Both global and individual lipidomic signatures, including SE(28:1_22:6) and HexCer(d18:1/20:1), mediated these diet-NWCO associations (mediation proportion: 15.92%-26.10%).

CONCLUSIONS

Differential lipidomic signatures were identified for overall and abdominal adiposity accumulation in normal-weight individuals, underlining their core mediation roles in dietary contributions to adiposity deposition.

The metabolic profile of waist to hip ratio-A multi-cohort study

BACKGROUND

The genetic background of general obesity and fat distribution is different, pointing to separate underlying physiology. Here, we searched for metabolites and lipoprotein particles associated with fat distribution, measured as waist/hip ratio adjusted for fat mass (WHRadjfatmass), and general adiposity measured as percentage fat mass.

METHOD

The sex-stratified association of 791 metabolites detected by liquid chromatography-mass spectrometry (LC-MS) and 91 lipoprotein particles measured by nuclear magnetic spectroscopy (NMR) with WHRadjfatmass and fat mass were assessed using three population-based cohorts: EpiHealth (n = 2350) as discovery cohort, with PIVUS (n = 603) and POEM (n = 502) as replication cohorts.

RESULTS

Of the 193 LC-MS-metabolites being associated with WHRadjfatmass in EpiHealth (false discovery rate (FDR) <5%), 52 were replicated in a meta-analysis of PIVUS and POEM. Nine metabolites, including ceramides, sphingomyelins or glycerophosphatidylcholines, were inversely associated with WHRadjfatmass in both sexes. Two of the sphingomyelins (d18:2/24:1, d18:1/24:2 and d18:2/24:2) were not associated with fat mass (p>0.50). Out of 91, 82 lipoprotein particles were associated with WHRadjfatmass in EpiHealth and 42 were replicated. Fourteen of those were associated in both sexes and belonged to very-large or large HDL particles, all being inversely associated with both WHRadjfatmass and fat mass.

CONCLUSION

Two sphingomyelins were inversely linked to body fat distribution in both men and women without being associated with fat mass, while very-large and large HDL particles were inversely associated with both fat distribution and fat mass. If these metabolites represent a link between an impaired fat distribution and cardiometabolic diseases remains to be established.

Habitual intakes of sugar-sweetened beverages associated with gut microbiota-related metabolites and metabolic health outcomes in young Chinese adults

BACKGROUND AND AIMS

Reducing consumption of sugar-sweetened beverages (SSBs) is a global public health priority because of their limited nutritional value and associations with increased risk of obesity and metabolic diseases. Gut microbiota-related metabolites emerged as quintessential effectors that may mediate impacts of dietary exposures on the modulation of host commensal microbiome and physiological status.

METHODS AND RESULTS

This study assessed the associations among SSBs, circulating microbial metabolites, and gut microbiota-host co-metabolites, as well as metabolic health outcomes in young Chinese adults (n = 86), from the Carbohydrate Alternatives and Metabolic Phenotypes study in Shaanxi Province. Five principal component analysis-derived beverage drinking patterns were determined on self-reported SSB intakes, which were to a varying degree associated with 143 plasma levels of gut microbiota-related metabolites profiled by untargeted metabolomics. Moreover, carbonated beverages, fruit juice, energy drinks, and bubble tea exhibited positive associations with obesity-related markers and blood lipids, which were further validated in an independent cohort of 16,851 participants from the Regional Ethnic Cohort Study in Northwest China in Shaanxi Province. In contrast, presweetened coffee was negatively associated with the obesity-related traits. A total of 79 metabolites were associated with both SSBs and metabolic markers, particularly obesity markers. Pathway enrichment analysis identified the branched-chain amino acid catabolism and aminoacyl-tRNA biosynthesis as linking SSB intake with metabolic health outcomes.

CONCLUSION

Our findings demonstrate the associations between habitual intakes of SSBs and several metabolic markers relevant to noncommunicable diseases, and highlight the critical involvement of gut microbiota-related metabolites in mediating such associations.

Staple Food Preference and Obesity Phenotypes: The Regional Ethnic Cohort Study in Northwest China

Staple food preference vary in populations, but evidence of its associations with obesity phenotypes are limited. Using baseline data (n = 105,840) of the Regional Ethnic Cohort Study in Northwest China, staple food preference was defined according to the intake frequency of rice and wheat. Overall and specifically abdominal fat accumulation were determined by excessive body fat percentage and waist circumference. Logistic regression and equal frequency substitution methods were used to evaluate the associations. We observed rice preference (consuming rice more frequently than wheat; 7.84% for men and 8.28% for women) was associated with a lower risk of excessive body fat (OR, 0.743; 95%CI, 0.669-0.826) and central obesity (OR, 0.886; 95%CI, 0.807-0.971) in men; and with lower risk of central obesity (OR, 0.898; 95%CI, 0.836-0.964) in women, compared with their wheat preference counterparties. Furthermore, similar but stronger inverse associations were observed in participants with normal body mass index. Wheat-to-rice (5 times/week) reallocations were associated with a 36.5% lower risk of normal-weight obesity in men and a 20.5% lower risk of normal-weight central obesity in women. Our data suggest that, compared with wheat, rice preference could be associated with lower odds ratios of certain obesity phenotypes in the Northwest Chinese population.

BMI and lipidomic biomarkers with risk of gestational diabetes in pregnant women

OBJECTIVE

The study aimed to identify BMI-related lipids and to explore the role of lipids linking BMI and gestational diabetes mellitus (GDM).

METHODS

Plasma lipidome, height, and weight were measured in early pregnancy among 1008 women. Pearson correlation analyses and least absolute shrinkage and selection operator regression (LASSO) were performed to identify BMI-associated lipids. Based on these lipids, a lipid score was created using LASSO, and its association with GDM risk was evaluated by conditional logistic regression. The causal relationships between BMI and lipids were tested by Mendelian randomization analysis with genotyping data. Mediation analysis was conducted to evaluate the mediating effect of lipids on the association of BMI with GDM.

RESULTS

Of 366 measured lipids, BMI was correlated with 28 lipids, which mainly belong to glycerophospholipids and glycerolipids. A total of 10 lipid species were associated with BMI, and a lipid score was established. A causal relationship between BMI and lysophosphatidylcholine 14:0 was observed. The lipid score was associated with a 1.69-fold increased risk of GDM per 1-point increment (95% CI: 1.33-2.15). Furthermore, BMI-associated lipids might explain 66.4% of the relationship between BMI and GDM.

CONCLUSIONS

Higher BMI in early pregnancy was associated with altered lipid metabolism that may contribute to the increased risk of GDM.

A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses' Health Studies

BACKGROUND

Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear.

METHODS

In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis.

RESULTS

Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01).

CONCLUSIONS

Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer.

Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.