Longitudinal associations of DXA-measured visceral adipose tissue and cardiometabolic risk in middle-to-older aged adults.

BACKGROUND AND AIMS: DXA-measured visceral adipose tissue (VATDXA) is associated with adverse cardiometabolic risk profiles in cross-sectional studies, but longitudinal associations have not been investigated. We examined the longitudinal associations of baseline and change in VATDXA with future cardiometabolic risk in Australian participants of the Busselton Healthy Ageing study. METHODS AND RESULTS: We studied 3569 participants (54.7% female, aged 46-70 years) with data on VATDXA (GE Lunar Prodigy) and cardiometabolic risk factors at baseline and 6 years follow-up. The associations were examined using logistic and linear regression models, adjusting for baseline age and lifestyle factors. Mean baseline VATDXA mass was 1653 ± 880 g and 855 ± 580 g, and mean change in VATDXA +99 ± 500 g and +58 ± 312 g in males and females, respectively. Among all participants, 182 males (11.3%) and 197 females (10.1%) developed incident metabolic syndrome (MetS). Baseline VATDXA was associated with incident MetS with an adjusted odds ratio of 2.53 (95% CI: 2.03, 3.15) in males and 2.78 (2.30, 3.36) in females per SD increment. There was a graded positive association between longitudinal change in VATDXA and MetS severity z score in both sexes adjusted for baseline VAT (P < 0.001). All the above associations remained significant after further adjustment for baseline or change in BMI, waist circumference or waist-to-hip ratio in respective models (all P < 0.001). CONCLUSIONS: Higher baseline and greater longitudinal increase in VATDXA are independently associated with raised cardiometabolic risk over time, and may serve as useful markers for identifying middle-aged individuals at increased cardiometabolic risk.

Development and validation of a plasmalogen score as an independent modifiable marker of metabolic health: population based observational studies and a placebo-controlled cross-over study.

BACKGROUND: Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle. METHODS: We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years). FINDINGS: In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21-0.43), 0.39 (95% CI 0.25-0.61) and 0.42 (95% CI 0.30-0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56-0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score. INTERPRETATION: The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings. FUNDING: National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.

BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

Genomic attributes of airway commensal bacteria and mucosa.

Microbial communities at the airway mucosal barrier are conserved and highly ordered, in likelihood reflecting co-evolution with human host factors. Freed of selection to digest nutrients, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the initial results of systematic culture and whole-genome sequencing of the thoracic airway bacteria, identifying 52 novel species amongst 126 organisms that constitute 75% of commensals typically present in heathy individuals. Clinically relevant genes encode antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. Using whole-genome content we identify dysbiotic features that may influence asthma and chronic obstructive pulmonary disease. We match isolate gene content to transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways to sustain host interactions with microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosa in lung diseases of global significance.

Lipidomic Risk Score to Enhance Cardiovascular Risk Stratification for Primary Prevention.

BACKGROUND: Accurate risk stratification is vital for primary prevention of cardiovascular disease (CVD). However, traditional tools such as the Framingham Risk Score (FRS) may underperform within the diverse intermediate-risk group, which includes individuals requiring distinct management strategies. OBJECTIVES: This study aimed to develop a lipidomic-enhanced risk score (LRS), specifically targeting risk prediction and reclassification within the intermediate group, benchmarked against the FRS. METHODS: The LRS was developed via a machine learning workflow using ridge regression on the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab; n = 10,339). It was externally validated with the Busselton Health Study (n = 4,492), and its predictive utility for coronary artery calcium scoring (CACS)-based outcomes was independently validated in the BioHEART cohort (n = 994). RESULTS: LRS significantly improved discrimination metrics for the intermediate-risk group in both AusDiab and Busselton Health Study cohorts (all P < 0.001), increasing the area under the curve for CVD events by 0.114 (95% CI: 0.1123-0.1157) and 0.077 (95% CI: 0.0755-0.0785), with a net reclassification improvement of 0.36 (95% CI: 0.21-0.51) and 0.33 (95% CI: 0.15-0.49), respectively. For CACS-based outcomes in BioHEART, LRS achieved a significant area under the curve improvement of 0.02 over the FRS (0.76 vs 0.74; P < 1.0 × 10-5). A simplified, clinically applicable version of LRS was also created that had comparable performance to the original LRS. CONCLUSIONS: LRS, augmenting the FRS, presents potential to improve intermediate-risk stratification and to predict atherosclerotic markers using a simple blood test, suitable for clinical application. This could facilitate the triage of individuals for noninvasive imaging such as CACS, fostering precision medicine in CVD prevention and management.

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.