Biological age scores capture ageing heterogeneity beyond chronological age but are often dominated by lifestyle and environmental exposures, limiting clinical interpretability. We developed an environmentally adjusted metabolic age score (EAmAge) to isolate intrinsic ageing biology relevant to neurodegeneration and chronic disease. Major environmental influences were statistically removed from plasma lipidomic profiles before constructing an age-prediction model using ridge regression. EAmAge was derived in the AusDiab cohort (n = 10,339) and validated across three independent cohorts (BHS, ADNI and ASPREE; total n = 9,835). Compared with an unadjusted lipidomic age model (mAge_orig), EAmAge showed stronger and more consistent associations with incident Alzheimer’s disease-related dementia, cardiovascular events and all-cause mortality. EAmAge was also associated with Alzheimer’s disease-related biomarkers, including amyloid burden, reduced glucose metabolism and hippocampal atrophy. These findings establish EAmAge as a robust and partially modifiable biomarker that improves risk stratification by disentangling intrinsic metabolic ageing from environmental confounding.

Ratios between two metabolites are sensitive indicators of metabolic changes. Lipidomic profiling studies have revealed that plasma ether lipids, a class of glycero- and glycerophospho-lipids with reported health benefits, are negatively associated with obesity. Here, we utilized lipid ratios as surrogate markers of lipid metabolism to explore the processes underlying the inverse relationship between ether lipid metabolism and obesity. Plasma lipidomics data from two independent human cohorts (n = 10,339 and n = 4,492) were integrated to assess the associations between 82 lipid ratios and obesity-related markers in males and females. Results were externally validated using mouse transcriptomics data from the Hybrid Mouse Diversity Panel (n = 152-227 across 74 strains). Genome-wide association studies using imputed genotypes from a population cohort (n = 4,492) were performed to examine the genetic architecture of the ratios. Findings showed that waist circumference (WC), body mass index, and waist-hip ratio were inversely associated with total plasmalogens relative to total phospholipids in both sexes. Ratios comprising product-substrate pairs positioned either side of enzymes involved in plasmalogen synthesis and degradation showed positive and negative associations with WC, respectively. Branched-chain fatty acids negatively correlated with WC, while omega-6 polyunsaturated fatty acids exhibited differing associations depending on their position within the pathway. Mouse transcriptomics corroborated these results. Genomics data showed strong associations between ratios containing choline-plasmalogens and single-nucleotide polymorphisms in the transmembrane protein 229B (TMEM229B) gene region. This work demonstrates the utility of lipid ratios in understanding lipid metabolism. By applying the ratios to multi-omic datasets, we identified alterations in enzymatic activity and genetic variants likely affecting ether lipid synthesis in obesity that could not have been obtained from lipidomics data alone. Additionally, we characterized a potential role for TMEM229B, offering new perspectives on ether lipid metabolism and regulation.

Understanding the distribution and variation in inflammatory markers is crucial for advancing our knowledge of inflammatory processes and evaluating their clinical utility in diagnosing and monitoring acute and chronic disease. 1H NMR spectroscopy of blood plasma and serum was applied to measure a composite panel of inflammatory markers based on acute phase glycoprotein signals (GlycA and GlycB) and sub-regions of the lipoprotein derived Supramolecular Phospholipid Composite signals (SPC1, SPC2 and SPC3) to establish normal ranges in two healthy, predominantly white cohorts from Australia (n = 398) and Spain (n = 80; ages 20–70 years). GlycA, GlycB, SPC1 and SPC3 were not significantly impacted by age or sex, but SPC2 (an HDL-related biomarker) was significantly higher in women across all age ranges by an average of 33.7%. A free-living Australian population cohort (n = 3945) was used to explore the relationship of BMI with the panel of inflammatory markers. The glycoprotein signals were directly associated with BMI with GlycB levels being significantly higher for women in all BMI classes. Conversely, SPC2 was found to be inversely associated with BMI and differed significantly between the sexes at each BMI category (normal weight p = 3.46x10-43, overweight p = 3.33x10-79, obese p = 2.15x10-64). SPC1 and SPC3 were markedly less affected by BMI changes. Given the significant association between SPC2 and sex, these data suggest that men and women should be modelled independently for NMR-determined inflammatory biomarkers, or that data should be corrected for sex.

( N Engl J Med . 2024;391:1877–1889. doi:10.1056/NEJMoa2314768) The Australian Reproductive Genetic Carrier Screening Project (Mackenzie’s Mission) aimed to assess the feasibility and outcomes of offering reproductive genetic carrier screening (RGCS) to more than 10,000 reproductive couples, focusing on the identification of pathogenic variants in genes associated with severe, childhood-onset conditions. The study tested these couples (free of charge) for pathogenic variants in at least 1281 genes, linked to about 750 autosomal recessive or X-linked conditions. The primary objective was to evaluate the uptake of screening, participant attitudes, and psychosocial outcomes, as well as to explore the impact of genetic information on reproductive decision-making.

Statin therapy is a highly successful and cost-effective strategy for the prevention and treatment of cardiovascular diseases (CVD). Adjusting for statin usage is crucial when exploring the association of the lipidome with CVD to avoid erroneous conclusions. However, practical challenges arise in real-world scenarios due to the frequent absence of statin usage information. To address this limitation, we demonstrate that statin usage can be accurately predicted using lipidomic data. Using three large population datasets and a longitudinal clinical study, we show that lipidomic-based statin prediction models exhibit high prediction accuracy in external validation. Furthermore, we introduce a re-weighted model, designed to overcome a ubiquitous limitation of prediction models, namely the need for predictor alignment between training and target data. We demonstrated that the re-weighted models achieved comparable prediction accuracy to ad hoc models which use the aligned predictor between training and target data. This innovation holds promise for significantly enhancing the transferability of statin prediction and other 'omics prediction models, especially in situations where predictor alignment is incomplete. Our statin prediction model now allows for the inclusion of statin usage in lipidomic analyses of cohorts even where statin use is not available, improving the interpretability of the resulting analyses.

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.

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). Signi fi cant 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.

Background Genomic sequencing technology allows for identification of reproductive couples with an increased chance, as compared with that in the general population, of having a child with an autosomal recessive or X-linked genetic condition. Methods We investigated the feasibility, acceptability, and outcomes of a nationwide, couple-based genetic carrier screening program in Australia as part of the Mackenzie's Mission project. Health care providers offered screening to persons before pregnancy or early in pregnancy. The results obtained from testing at least 1281 genes were provided to the reproductive couples. We aimed to ascertain the psychosocial effects on participants, the acceptability of screening to all participants, and the reproductive choices of persons identified as having an increased chance of having a child with a condition for which we screened. Results Among 10,038 reproductive couples enrolled in the study, 9107 (90.7%) completed screening, and 175 (1.9%) were newly identified as having an increased chance of having a child with a genetic condition for which we screened. These conditions involved pathogenic variants in 90 different genes; 74.3% of the conditions were autosomal recessive. Three months after receiving the results, 76.6% of the couples with a newly identified increased chance had used or planned to use reproductive interventions to avoid having an affected child. Those newly identified as having an increased chance had greater anxiety than those with a low chance. The median level of decisional regret was low in all result groups, and 98.9% of participants perceived screening to be acceptable. Conclusions Couple-based reproductive genetic carrier screening was largely acceptable to participants and was used to inform reproductive decision making. The delivery of screening to a diverse and geographically dispersed population was feasible. (Funded by the Medical Research Future Fund of the Australian government; ClinicalTrials.gov number, NCT04157595.) A Nationwide Couple-Based Genetic Screen In this study, 77% of couples identified as having an increased risk of having a child with an autosomal recessive or X-linked condition used or planned to use reproductive interventions.

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.

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: 0.11230.1157) 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 x 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.

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.

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.

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 1 H 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 apolipopro-tein (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 con-stituents, 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, pro-viding reference intervals for comparison with general populations and adults with cardiometabolic risk factors.(c) 2023 National Lipid Association. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 588,452 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

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.

The apolipoprotein E gene (APOE) genotype is the first and strongest genetic risk factor for late-onset Alzheimer’s disease and has emerged as a novel therapeutic target for AD. The encoded protein (Apolipoprotein E, APOE) is well-known to be involved in lipoprotein transport and metabolism, but its effect on lipid metabolic pathways and the potential mediating effect of these on disease risk have not been fully defined. We performed lipidomic analysis on three independent cohorts (AIBL, n = 693; ADNI, n=207; BHS, n=4,384) and defined the association between APOE polymorphisms (ε4 and ε2) and plasma lipid species. To identify associations independent of lipoprotein metabolism, the analyses was performed with adjustment for clinical lipids (total cholesterol, HDL-C and triglycerides). Causal mediation analysis was performed to estimate the proportion of risk in the outcome model explained by a direct effect of APOE genotype on prevalent AD — the average direct effect (ADE) — and the proportion that was mediated by lipid species or lipidomic risk models — the average causal mediation effect (ACME). We identified multiple associations of species from lipid classes such as ceramide, hexosylceramide, sphingomyelin, plasmalogens, alkyldiacylglycerol and cholesteryl esters with APOE polymorphisms (ε4 and ε2) that were independent of clinical lipoprotein measurements. There were 104 and 237 lipid species associated with APOE ε4 and ε2 respectively which were largely discordant. Of these 116 were also associated with Alzheimer’s disease. Individual lipid species (notably the alkyldiacylglycerol subspecies) or lipidomic risk models of APOE genotypes mediated up to 10% and 30% of APOE ε4 and ε2 treatment effect on AD risks respectively. We demonstrate a strong relationship between APOE polymorphisms and peripheral lipid species. Lipids species mediate a proportion of the effects of APOE genotypes in risk of AD, particularly resilience with e2. Our results highlight the involvement of lipids in how APOE e2 mediates its resilience to AD and solidify their involvement with the disease pathway.

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

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.

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.

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.