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.

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).

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.

Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts.

Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of "metabolically healthy obese". We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify "at risk" individuals for targeted intervention and monitoring.

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.

Serum 21-Deoxycortisol for Diagnosis of Nonclassic Congenital Adrenal Hyperplasia in Women With Androgen Excess.

CONTEXT: Nonclassic congenital adrenal hyperplasia (NCCAH) requires exclusion before diagnosing polycystic ovary syndrome (PCOS). Increasing use of liquid chromatography and tandem mass spectrometry (LC-MS/MS) necessitates revision of immunoassay-based criteria for NCCAH. Measurement of 21-deoxycortisol (21DF) may simplify the diagnosis of heterozygosity (HTZ), the presence of 1 affected CYP21A2 allele, which currently relies on complex molecular studies. OBJECTIVE: We aimed to determine LC-MS/MS-specific criteria for NCCAH and HTZ and compare the diagnostic accuracy of 21DF and 17-hydroxyprogesterone (17OHP). METHODS: A cross-sectional study involving 99 hyperandrogenic females was performed. We identified females who had undergone both a synacthen stimulation test (SST) and CYP21A2 genotyping from 2010 to 2017, and prospectively recruited females referred for an SST to investigate hyperandrogenic symptoms from 2017 to 2021. Steroids were compared between genetically confirmed NCCAH, HTZ, and PCOS. Optimal 17OHP and 21DF thresholds for HTZ and NCCAH were determined by receiver operating characteristic analysis. RESULTS: Basal 17OHP, stimulated 17OHP, and 21DF were measured in 99, 85, and 42 participants, respectively. Optimal thresholds for NCCAH were 3.0 nmol/L and 20.7 nmol/L for basal and stimulated 17OHP, respectively. Basal and stimulated 21DF thresholds of 0.31 nmol/L and 13.3 nmol/L provided 100% sensitivity with specificities of 96.8% and 100% for NCCAH, respectively. Diagnostic thresholds for HTZ of 8.0 nmol/L, 1.0 nmol/L, and 13.6 for stimulated 17OHP, 21DF, and the ratio (21DF + 17OHP)/cortisol each provided 100% sensitivity with specificities of 80.4%, 90.5%, and 85.0%, respectively. CONCLUSION: LC-MS/MS-specific 17OHP thresholds for NCCAH are lower than those based on immunoassay. LC-MS/MS-quantified 17OHP and 21DF accurately discriminate HTZ and NCCAH from PCOS.

Serum testosterone and sex hormone-binding globulin are inversely associated with leucocyte telomere length in men: a cross-sectional analysis of the UK Biobank study.

OBJECTIVE: Older men on an average have lower testosterone concentrations, compared with younger men, and more age-related comorbidities. Whether lower testosterone concentrations contribute to biological ageing remains unclear. Shorter telomeres are a marker for biological age. We tested the hypothesis that testosterone concentrations are associated with leucocyte telomere length (LTL), in middle- to older-aged men. DESIGN: Cross-sectional analysis of the UK Biobank study, involving community-dwelling men aged 40-69 years. METHODS: Serum testosterone and sex hormone-binding globulin (SHBG) were assayed. Free testosterone was calculated (cFT). Leucocyte telomere length was measured using polymerase chain reaction. Multivariable models were used to assess associations of hormones with standardised LTL. RESULTS: In 167 706 men, median age 58 years, adjusting for sociodemographic, lifestyle, and medical factors, total testosterone was inversely associated with standardised LTL, which was 0.09 longer (95% confidence interval [CI], 0.08-0.10, P < .001) in men with total testosterone at median of lowest quintile [Q1] vs highest [Q5]. This relationship was attenuated after additional adjustment for SHBG (0.03 longer, CI = 0.02-0.05, P = .003). The association between cFT and LTL was similar in direction but lower in magnitude. In multivariable analysis, SHBG was inversely associated with standardised LTL, which was 0.12 longer (CI = 0.10-0.13, P < .001) for SHBG at median Q1 vs Q5. Results were similar with testosterone included in the model (0.10 longer, CI = 0.08-0.12, P < .001). CONCLUSIONS: Total testosterone and SHBG were independently and inversely associated with LTL. Men with higher testosterone or SHBG had shorter telomeres, arguing against a role for testosterone to slow biological ageing in men.

Shariant platform: Enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation.

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease.

We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.

Validation of ICD-10-AM Coding for Myocardial Infarction Subtype in Hospitalisation Data.

BACKGROUND: International Classification of Disease (ICD) codes are central for identifying myocardial infarction (MI) in administrative hospitalisation data, however validation of MI subtype codes is limited. We measured the sensitivity and specificity of ICD-10-AM (Australian Modification) codes for ST-elevation MI (STEMI) and non-STEMI (NSTEMI). METHODS: A sample of MI admissions was obtained from a dataset containing all MI hospitalisations in Western Australia (WA) for 2003, 2008 and 2013. Clinical data were collected from hospital medical records (n=799 patients). Cases were classified by ICD-10-AM codes for STEMI, NSTEMI and unspecified MI, and compared to clinical classification from review of available electrocardiographs (ECGs) and cardiac biomarkers (n=660). Sensitivity and specificity for ICD-10-AM coding versus clinical classification was measured, stratified by calendar year of discharge. RESULTS: The majority of classifiable cases had MI recorded in the principal diagnosis field (STEMI n=293, 84.2%; NSTEMI n=202, 74.3%; unspecified MI n=20, 50.0%). Overall sensitivity of the ICD-10-AM STEMI code was 86.3% (95% CI 81.7-90.0%) and was higher when restricted to MI as a principal versus secondary diagnosis (88.8% vs 66.7%). Comparable values for NSTEMI were 66.7% (95% CI 61.5-71.6%), and 68.8% vs 61.4% respectively. Between 2003 and 2013, sensitivity for both MI subtypes increased: 80.2-89.5% for STEMI, and 51.2-73.8% for NSTEMI. Specificity was high for NSTEMI throughout (88.2% 95% CI 84.1-91.6%), although improving over time for STEMI (68.1-76.4%). CONCLUSIONS: The sensitivity and specificity of ICD-10-AM codes for MI subtypes in hospitalisation data are generally high, particularly for principal diagnosis cases. However, the temporal improvement in sensitivity in coding of MI subtypes, particularly NSTEMI, may necessitate modification to trend studies using administrative hospitalisation data.

APOE ε2 resilience for Alzheimer's disease is mediated by plasma lipid species: Analysis of three independent cohort studies.

INTRODUCTION: The apolipoprotein E (APOE) genotype is the strongest genetic risk factor for late-onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood. METHODS: We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087; the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819; and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species. RESULTS: A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. Individual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively. DISCUSSION: Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.

Prevalence and patterns of multimorbidity in Australian baby boomers: the Busselton healthy ageing study.

BACKGROUND AND OBJECTIVE: Chronic medical conditions accumulate within individuals with age. However, knowledge concerning the trends, patterns and determinants of multimorbidity remains limited. This study assessed the prevalence and patterns of multimorbidity using extensive individual phenotyping in a general population of Australian middle-aged adults. METHODS: Participants (n = 5029, 55% female), born between 1946 and 1964 and attending the cross-sectional phase of the Busselton Healthy Ageing Study (BHAS) between 2010 and 2015, were studied. Prevalence of 21 chronic conditions was estimated using clinical measurement, validated instrument scores and/or self-reported doctor-diagnosis. Non-random patterns of multimorbidity were explored using observed/expected (O/E) prevalence ratios and latent class analysis (LCA). Variables associated with numbers of conditions and class of multimorbidity were investigated. RESULTS: The individual prevalence of 21 chronic conditions ranged from 2 to 54% and multimorbidity was common with 73% of the cohort having 2 or more chronic conditions. (mean ± SD 2.75 ± 1.84, median = 2.00, range 0-13). The prevalence of multimorbidity increased with age, obesity, physical inactivity, tobacco smoking and family history of asthma, diabetes, myocardial infarct or cancer. There were 13 pairs and 27 triplets of conditions identified with a prevalence > 1.5% and O/E > 1.5. Of the triplets, arthritis (> 50%), bowel disease (> 33%) and depression-anxiety (> 33%) were observed most commonly. LCA modelling identified 4 statistically and clinically distinct classes of multimorbidity labelled as: 1) "Healthy" (70%) with average of 1.95 conditions; 2) "Respiratory and Atopy" (11%, 3.65 conditions); 3) "Non-cardiometabolic" (14%, 4.77 conditions), and 4) "Cardiometabolic" (5%, 6.32 conditions). Predictors of multimorbidity class membership differed between classes and differed from predictors of number of co-occurring conditions. CONCLUSION: Multimorbidity is common among middle-aged adults from a general population. Some conditions associated with ageing such as arthritis, bowel disease and depression-anxiety co-occur in clinically distinct patterns and at higher prevalence than expected by chance. These findings may inform further studies into shared biological and environmental causes of co-occurring conditions of ageing. Recognition of distinct patterns of multimorbidity may aid in a holistic approach to care management in individuals presenting with multiple chronic conditions, while also guiding health resource allocation in ageing populations.

Further heterogeneity in Silver-Russell syndrome: PLAG1 deletion in association with a complex chromosomal rearrangement.

Silver-Russell syndrome (SRS) is a rare genetic condition primarily characterized by growth restriction and facial dysmorphisms. While hypomethylation of H19/IGF2:IG-DMR (imprinting control region 1 [IC1]) located at 11p15.5 and maternal uniparental disomy of chromosome 7 (upd[7]mat) are the most common genetic mechanisms responsible for SRS, the expanding body of literature describing alternative causative variants suggests SRS is a highly heterogeneous condition, also involving variation in the HMGA2-PLAG1-IGF2 pathway. We report a familial PLAG1 deletion in association with a complex chromosomal rearrangement. We describe two siblings with differing unbalanced chromosomal rearrangements inherited from a mother with a 5-breakpoint balanced complex rearrangement involving chromosomes 2, 8, and 21. The overlapping but diverse phenotypes in the siblings were characterized by shared SRS-like features, underlined by a PLAG1 whole gene deletion. Genetic analysis and interpretation was further complicated by a meiotic recombination event occurring in one of the siblings. This family adds to the limited literature available on PLAG1-related SRS. We have reviewed all currently known cases aiming to define the associated phenotype and guide future genetic testing strategies. The heterogeneity of SRS is further expanded by the involvement of complex cytogenomic abnormalities, imposing requirements for a comprehensive approach to testing and genetic counseling.

Paediatric genomic testing: Navigating medicare rebatable genomic testing.

Genomic testing for a genetic diagnosis is becoming standard of care for many children, especially those with a syndromal intellectual disability. While previously this type of specialised testing was performed mainly by clinical genetics teams, it is increasingly being 'mainstreamed' into standard paediatric care. With the introduction of a new Medicare rebate for genomic testing in May 2020, this type of testing is now available for paediatricians to order, in consultation with clinical genetics. Children must be aged less than 10 years with facial dysmorphism and multiple congenital abnormalities or have global developmental delay or moderate to severe intellectual disability. This rebate should increase the likelihood of a genetic diagnosis, with accompanying benefits for patient management, reproductive planning and diagnostic certainty. Similar to the introduction of chromosomal microarray into mainstream paediatrics, this genomic testing will increase the number of genetic diagnoses, however, will also yield more variants of uncertain significance, incidental findings, and negative results. This paper aims to guide paediatricians through the process of genomic testing, and represents the combined expertise of educators, clinical geneticists, paediatricians and genomic pathologists around Australia. Its purpose is to help paediatricians navigate choosing the right genomic test, consenting patients and understanding the possible outcomes of testing.

U-Shaped Relationship of Leukocyte Telomere Length With All-Cause and Cancer-Related Mortality in Older Men.

BACKGROUND: Telomeres are essential DNA-protein complexes whose attrition results in cellular dysfunction and senescence. Leukocyte telomere length (LTL) correlates with tissue telomere length, representing a biomarker for biological age. However, its predictive value for mortality risk, and for cardiovascular versus cancer deaths, in older adults remains uncertain. METHOD: We studied 3608 community-dwelling men aged 77.0 ± 3.6 years. Leukocyte telomere length was measured using multiplex quantitative PCR, expressed as amount of telomeric DNA relative to single-copy control gene (T/S ratio). Deaths from any cause, cardiovascular disease (CVD), and cancer were ascertained using data linkage. Curve fitting used restricted cubic splines and Cox regression analyses adjusted for age, cardiometabolic risk factors, and prevalent disease. RESULTS: There was a U-shaped association of LTL with all-cause mortality. Men with T/S ratio in the middle quartiles had lower mortality (quartiles, Q2 vs Q1, hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.77-0.97, p = .012; Q3 vs Q1 HR = 0.88, CI 0.79-0.99, p = .032). There was no association of LTL with CVD mortality. There was a U-shaped association of LTL with cancer mortality. Men with LTL in the middle quartiles had lower risk of cancer death (Q2 vs Q1, HR = 0.73, CI 0.59-0.90, p = .004; Q3 vs Q1, HR = 0.75, CI 0.61-0.92, p = .007). CONCLUSIONS: In older men, both shorter and longer LTL are associated with all-cause mortality. A similar U-shaped association was seen with cancer deaths, with no association found for cardiovascular deaths. Further research is warranted to explore the prognostic utility of LTL in ageing.

Correction: High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies.

[This corrects the article DOI: 10.1371/journal.pbio.3000870.].

High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies.

Obesity and related metabolic diseases show clear sex-related differences. The growing burden of these diseases calls for better understanding of the age- and sex-related metabolic consequences. High-throughput lipidomic analyses of population-based cohorts offer an opportunity to identify disease-risk-associated biomarkers and to improve our understanding of lipid metabolism and biology at a population level. Here, we comprehensively examined the relationship between lipid classes/subclasses and molecular species with age, sex, and body mass index (BMI). Furthermore, we evaluated sex specificity in the association of the plasma lipidome with age and BMI. Some 747 targeted lipid measures, representing 706 molecular lipid species across 36 classes/subclasses, were measured using a high-performance liquid chromatography coupled mass spectrometer on a total of 10,339 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), with 563 lipid species being validated externally on 4,207 participants of the Busselton Health Study (BHS). Heat maps were constructed to visualise the relative differences in lipidomic profile between men and women. Multivariable linear regression analyses, including sex-interaction terms, were performed to assess the associations of lipid species with cardiometabolic phenotypes. Associations with age and sex were found for 472 (66.9%) and 583 (82.6%) lipid species, respectively. We further demonstrated that age-associated lipidomic fingerprints differed by sex. Specific classes of ether-phospholipids and lysophospholipids (calculated as the sum composition of the species within the class) were inversely associated with age in men only. In analyses with women alone, higher triacylglycerol and lower lysoalkylphosphatidylcholine species were observed among postmenopausal women compared with premenopausal women. We also identified sex-specific associations of lipid species with obesity. Lysophospholipids were negatively associated with BMI in both sexes (with a larger effect size in men), whilst acylcarnitine species showed opposing associations based on sex (positive association in women and negative association in men). Finally, by utilising specific lipid ratios as a proxy for enzymatic activity, we identified stearoyl CoA desaturase (SCD-1), fatty acid desaturase 3 (FADS3), and plasmanylethanolamine Δ1-desaturase activities, as well as the sphingolipid metabolic pathway, as constituent perturbations of cardiometabolic phenotypes. Our analyses elucidate the effect of age and sex on lipid metabolism by offering a comprehensive view of the lipidomic profiles associated with common cardiometabolic risk factors. These findings have implications for age- and sex-dependent lipid metabolism in health and disease and suggest the need for sex stratification during lipid biomarker discovery, establishing biological reference intervals for assessment of disease risk.

Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study.

CVD is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits. Targeted lipidomic profiling was performed on 4,492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes and their genetic correlations with eight CVD traits: BMI, HDL-C, LDL-C, triglycerides, total cholesterol, waist-hip ratio, systolic blood pressure, and diastolic blood pressure. We report heritabilities and genetic correlations of new lipid species/subclasses, including acylcarnitine (AC), ubiquinone, sulfatide, and oxidized cholesteryl esters. Over 99% of lipid species were significantly heritable (h2: 0.06-0.50) and all lipid classes were significantly heritable (h2: 0.14-0.50). The monohexosylceramide and AC classes had the highest median heritabilities (h2 = 0.43). The largest genetic correlation was between clinical triglycerides and total diacylglycerol (rg = 0.88). We observed novel positive genetic correlations between clinical triglycerides and phosphatidylglycerol species (rg: 0.64-0.82), and HDL-C and alkenylphosphatidylcholine species (rg: 0.45-0.74). Overall, 51% of the 4,768 lipid species-CVD trait genetic correlations were statistically significant after correction for multiple comparisons. This is the largest lipidomic study to address the heritability of lipids and their genetic correlation with CVD traits. Future work includes identifying putative causal genetic variants for lipid species and CVD using genome-wide SNP and whole-genome sequencing data.

Associations of plasma IGF1, IGFBP3 and estradiol with leucocyte telomere length, a marker of biological age, in men.

OBJECTIVE: Effects of insulin-like growth factor 1 (IGF1) and its binding proteins (IGFBPs) on ageing, and their interaction with sex hormones, remain uncertain. We examined associations of plasma IGF1, IGFBP1, IGFBP3, estradiol and testosterone, with leucocyte telomere length (LTL), a marker of biological age, in 2999 community-dwelling men aged 70-84 years. METHODS: Plasma IGF1, IGFBP1 and IGFBP3 measured using immunoassay, sex hormones using mass spectrometry. LTL measured by PCR, expressed as ratio of telomeric to single-copy control gene DNA (T/S ratio). Linear regression models adjusted for age and cardio-metabolic risk factors, median splits defined low/high groups. RESULTS: Mean age was 76.7 ± 3.2 years. IGF1 and IGFBP3 showed age-adjusted correlations with LTL (coefficient 0.59, P = 0.001 and 0.45, P = 0.013 respectively), IGFBP1 did not. In multivariable-adjusted models IGF1 and IGFBP3 (but not IGFBP1) were associated with LTL (T/S ratio 0.015 higher per 1 s.d. increase in IGF1, P = 0.007, and 0.011 per 1 s.d. IGFBP3, P = 0.049). IGF1 and estradiol were independently associated with longer telomeres (T/S ratio 0.012 higher per 1 s.d. increase in estradiol, P = 0.027, when included in model with IGF1). Testosterone was not associated with LTL. Men with both high IGF1 (>133 µg/L) and high estradiol (>70 pmol/L) had longer LTL compared to men with lower values (multivariable-adjusted T/S ratio 1.20 vs 1.16, P = 0.018). CONCLUSIONS: Higher IGF1 and IGFBP3 are independently associated with longer telomeres in older men. Additive associations of higher IGF1 and higher estradiol with telomere length are present. Further studies are needed to determine whether these hormonal exposures cooperate to slow biological aging.

Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals.

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 × 10-8) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.