Chronotype, Life's Essential 8, and Risk of Cardiovascular Disease: A Prospective Cohort Study in UK Biobank.

Introduction:Individuals with an evening chronotype often experience circadian misalignment, which may disrupt health behaviors and circadian regulation of cardiometabolic functions such as blood pressure. However, the associations of chronotype with modifiable cardiovascular disease (CVD) risk factors and incident CVD are not fully understood.Methods:We conducted a prospective study in 322,777 UK Biobank participants aged 39-74 years who were free of known CVD (2006-2010). Chronotype was self-reported using a single representative question from the Morningness-Eveningness Questionnaire. The Life’s Essential 8 (LE8) score was calculated based on 8 modifiable CVD risk factors, and ranged from 0 to 100 with higher scores indicating better cardiovascular health. Incident CVD was defined as first myocardial infarction (MI) or stroke leading to hospitalization or death, identified via validated algorithms. Cox proportional hazards models estimated the association between chronotype and CVD risk, adjusted for socio-demographics, shift work, and family history of CVD. Under the causal mediation framework, we evaluated the role of LE8 in the association between chronotype and CVD risk by decomposing the total effect into natural direct effect (i.e., independent of LE8) and natural indirect effect (i.e., mediated by LE8; NIE).Results:Participants (mean age: 57) with a “definite evening” chronotype (8% of the total sample) were 79% more likely to have an overall poor LE8 score (<50 points) compared to “intermediate” type (prevalence ratio 95% CI: 1.72 - 1.85). Over a median of 13.2 years of follow-up, there were 17,584 incident CVD events (11,091 MI; 7,214 stroke). The hazard ratio (HR) for total CVD was 1.03 (0.99 - 1.07) for the “definite morning” and 1.16 (1.10 - 1.22) for “definite evening” compared with “intermediate” chronotype (P-trend: 0.10). LE8 explained 74% of the association between evening chronotype and CVD (NIE comparing “definite evening” to “intermediate: 1.11; 95% CI: 1.09, 1.13). Findings were similar when MI and stroke were examined individually.Conclusions:Compared to intermediate chronotype, evening chronotype was associated with modestly higher CVD risk, which was mainly explained by overall poorer cardiovascular health. These results suggest that individuals with evening chronotype may particularly benefit from interventions targeting CVD risk factors.

Introduction: Individuals with evening chronotype often experience circadian misalignment, which may disrupt health behaviors and circadian regulation of cardiometabolic functions such as blood pressure and heart rate. However, the association of chronotype with cardiovascular disease (CVD) and the interplay with other CVD risk factors are not fully understood. Hypothesis: We assessed the hypothesis that individuals with an evening chronotype, compared to those with a morning chronotype, have a poorer cardiovascular health as measured by the Life’s Essential 8 (LE8), and consequently an increased CVD risk. We further explored if the associations differed by sex. Methods: We conducted a prospective study in the UK Biobank among 477,878 adults aged 39-74 years and free of CVD at baseline in 2006-2010. Chronotype was self-reported using a single representative question from the Morningness-Eveningness Questionnaire. The LE8 score was calculated based on 8 modifiable CVD risk factors, and ranged from 0 to 100 with higher scores indicating better cardiovascular health. Incident CVD was defined as first myocardial infarction (MI) or stroke leading to hospitalization or death, identified via validated algorithms that mapped national medical records and death certificates to ICD-10 codes until May 2022. We used Cox proportional hazards models to estimate the association between chronotype and CVD risk. Models were adjusted for demographics, shift work, and family history of CVD. We applied causal mediation framework to decompose the total chronotype-CVD effect into estimated natural direct effect (i.e., independent of LE8) and natural indirect effect (i.e., mediated by LE8; NIE). Results: Participants with a “definite evening” chronotype were 75% more likely to have a low LE8 score (&lt;50) compared to “intermediate” type (prevalence ratio 95% CI: 1.67, 1.84). This association was notably stronger among women ( P -interaction: 0.0001). Over 12.7 years of follow-up, there were 27,346 documented incident CVD events (17,180 MI; 11,329 stroke). The hazard ratio (HR) for total CVD was 1.03 (95% CI: 1.00, 1.06) for the “definite morning” and 1.15 (95% CI: 1.10, 1.20) for “definite evening” compared with “intermediate” chronotype ( P -trend: 0.06). This association was stronger in women ( P -interaction: 0.05), and similar for MI and stroke. The NIE of the chronotype-CVD association comparing “definite evening” to “intermediate” was 1.11 (95% CI: 1.09, 1.13), equivalent to 95% of the association being mediated by LE8. Conclusions: Evening chronotype was associated with a modest increase in CVD risk, compared to intermediate chronotype, which appeared to be mainly explained by overall poor cardiovascular health. Our results suggest potential benefits of targeted interventions in evening chronotype for CVD prevention. Ongoing work is exploring potential effect modification by night shift work.

Evening chronotype may promote adherence to an unhealthy lifestyle and increase type 2 diabetes risk. To evaluate the role of modifiable lifestyle behaviors in the association between chronotype and diabetes risk. Prospective cohort study. Nurses' Health Study II. 63 676 nurses aged 45 to 62 years with no history of cancer, cardiovascular disease, or diabetes in 2009 were prospectively followed until 2017. Self-reported chronotype using a validated question from the Morningness-Eveningness Questionnaire. The lifestyle behaviors that were measured were diet quality, physical activity, alcohol intake, body mass index (BMI), smoking, and sleep duration. Incident diabetes cases were self-reported and confirmed using a supplementary questionnaire. Participants reporting a "definite evening" chronotype were 54% (95% CI, 49% to 59%) more likely to have an unhealthy lifestyle than participants reporting a "definite morning" chronotype. A total of 1925 diabetes cases were documented over 469 120 person-years of follow-up. Compared with the "definite morning" chronotype, the adjusted hazard ratio (HR) for diabetes was 1.21 (CI, 1.09 to 1.35) for the "intermediate" chronotype and 1.72 (CI, 1.50 to 1.98) for the "definite evening" chronotype after adjustment for sociodemographic factors, shift work, and family history of diabetes. Further adjustment for BMI, physical activity, and diet quality attenuated the association comparing the "definite evening" and "definite morning" chronotypes to 1.31 (CI, 1.13 to 1.50), 1.54 (CI, 1.34 to 1.77), and 1.59 (CI, 1.38 to 1.83), respectively. Accounting for all measured lifestyle and sociodemographic factors resulted in a reduced but still positive association (HR comparing "definite evening" vs. "definite morning" chronotype, 1.19 [CI, 1.03 to 1.37]). Chronotype assessment using a single question, self-reported data, and homogeneity of the study population. Middle-aged nurses with an evening chronotype were more likely to report unhealthy lifestyle behaviors and had increased diabetes risk compared with those with a morning chronotype. Accounting for BMI, physical activity, diet, and other modifiable lifestyle factors attenuated much but not all of the increased diabetes risk. National Institutes of Health.

Preeclampsia: Exposing Future Cardiovascular Risk in Mothers and Their Children

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The objective of the study was to examine associations between family history of premature cardiovascular disease (CVD), knowledge of CVD risk and protective factors, and health behaviours. The design was via administration of a questionnaire to 307 participants from four general practice centre waiting rooms in the Sydney West area. The most recognised CVD risk factor was smoking (97.7%) and the most recognised CVD protective factor was omega-3 fatty acids (78.5%). After adjustment for age, sex, education attainment and personal history of CVD, a strong family history of premature CVD was associated with being more likely to interpret a blood pressure of 130/85 as a CVD risk factor (OR 2.77, 95% CI 1.07-7.14), but less likely to identify being an ex-smoker (compared with never having smoked before) as a risk factor (OR 0.32, 95% CI 0.12-0.90). Those with a strong family history of premature CVD, on average, had smoked 0.82 pack years more than those with an average family history of premature CVD (s.e. 4.22, P=0.04). In conclusion, there continues to be both strengths and deficits in the community's overall knowledge of CVD risk and protective factors, and a strong family history of premature CVD appears to be an independent risk factor for smoking.

This statement examines the cardiovascular complications of diabetes mellitus and considers opportunities for their prevention. These complications include coronary heart disease (CHD), stroke, peripheral arterial disease, nephropathy, retinopathy, and possibly neuropathy and cardiomyopathy. Because of the aging of the population and an increasing prevalence of obesity and sedentary life habits in the United States, the prevalence of diabetes is increasing. Thus, diabetes must take its place alongside the other major risk factors as important causes of cardiovascular disease (CVD). In fact, from the point of view of cardiovascular medicine, it may be appropriate to say, “diabetes is a cardiovascular disease.” The most prevalent form of diabetes mellitus is type 2 diabetes. This disorder typically makes its appearance later in life. The underlying metabolic causes of type 2 diabetes are the combination of impairment in insulin-mediated glucose disposal (insulin resistance) and defective secretion of insulin by pancreatic β-cells. Insulin resistance develops from obesity and physical inactivity, acting on a substrate of genetic susceptibility.1 2 Insulin secretion declines with advancing age,3 4 and this decline may be accelerated by genetic factors.5 6 Insulin resistance typically precedes the onset of type 2 diabetes and is commonly accompanied by other cardiovascular risk factors: dyslipidemia, hypertension, and prothrombotic factors.7 8 The common clustering of these risk factors in a single individual has been called the metabolic syndrome. Many patients with the metabolic syndrome manifest impaired fasting glucose (IFG)9 even when they do not have overt diabetes mellitus.10 The metabolic syndrome commonly precedes the development of type 2 diabetes by many years11 ; of great importance, the risk factors that constitute this syndrome contribute independently to CVD risk. Recently, new criteria have been accepted for the diagnosis of diabetes.9 The upper threshold of fasting plasma glucose for the …

APOL1 renal risk variants are strongly associated with chronic kidney disease in Black adults, but reported associations with cardiovascular disease (CVD) have been conflicting. We examined associations of APOL1 with incident coronary heart disease (n=323), ischemic stroke (n=331), and the composite CVD outcome (n=500) in 10 605 Black participants of the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Primary analyses compared individuals with APOL1 high-risk genotypes to APOL1 low-risk genotypes in Cox proportional hazards models adjusted for CVD risk factors and African ancestry. APOL1 high-risk participants were younger and more likely to have albuminuria at baseline than APOL1 low-risk participants. The risk of incident stroke, coronary heart disease, or composite CVD end point did not significantly differ by APOL1 genotype status in multivariable models. The association of APOL1 genotype with incident composite CVD differed by diabetes mellitus status (Pinteraction=0.004). In those without diabetes mellitus, APOL1 high-risk genotypes associated with greater risk of incident composite CVD (hazard ratio, 1.67; 95% confidence interval, 1.12-2.47) compared with those with APOL1 low-risk genotypes in multivariable adjusted models. This latter association was driven by ischemic strokes (hazard ratio, 2.32; 95% confidence interval, 1.33-4.07), in particular, those related to small vessel disease (hazard ratio, 5.10; 95% confidence interval, 1.55-16.56). There was no statistically significant association of APOL1 genotypes with incident CVD in subjects with diabetes mellitus. The APOL1 high-risk genotype was associated with higher stroke risk in individuals without but not those with chronic kidney disease in fully adjusted models. APOL1 high-risk status is associated with CVD events in community-dwelling Black adults without diabetes mellitus.

Family History-Guided Physical Activity for Cardiovascular Disease Prevention.

Understanding Systemic Inflammation, Oral Hygiene, and Cardiovascular Disease

BackgroundThis study aimed to study the association between shift work and incident and fatal cardiovascular disease (CVD), and to explore modifying and mediating factors.MethodsThis is a population-based, prospective cohort study with a median follow-up of 11 years; 238 661 UK Biobank participants who were in paid employment or self-employed at baseline assessment were included.ResultsShift workers had higher risk of incident [hazard ratio (HR) 1.11, 95% confidence interval (CI) 1.06–1.19] and fatal (HR 1.25, 95% CI 1.08–1.44) CVD compared with non-shift workers, after adjusting for socio-economic and work-related factors. The risk was higher with longer duration of shift work, in women and in jobs with little heavy manual labour. Current smoking, short sleep duration, poor sleep quality, adiposity, higher glycated haemoglobin and higher cystatin C were identified as the main potentially modifiable mediators. Mediators collectively explained 52.3% of the associations between shift work and incident CVDs.ConclusionsShift workers have higher risk of incident and fatal CVD, partly mediated through modifiable risk factors such as smoking, sleep duration and quality, adiposity and metabolic status. Workplace interventions targeting these mediators have the potential to alleviate shift workers’ CVD risk.

To the Editor: Recently, an update from the Framingham study could not find uric acid to be an independent risk factor for cardiovascular disease.1 While serum uric acid levels correlated significantly with the risk for cardiovascular events and mortality in women, this relationship became insignificant after factoring for 11 additional variables including hypertension, body mass index, and diuretic use.1 Both the authors1 and an accompanying editorial2 interpreted these findings as showing that uric acid is not a true risk factor for cardiovascular disease and that it should not be routinely measured to assess cardiovascular risk. The careful analysis of the Framingham study is to be commended, but one must be cautious in the interpretation of the findings. While some epidemiologic studies such as the current one have not been able to show uric acid to be an independent risk factor for cardiovascular disease, other studies using multivariate analyses3 4 5 6 came to an opposite conclusion. Another recently completed study, the Worksite,7 also found uric acid to be an independent risk factor for cardiovascular events and mortality, especially in women. One might look for subtle explanations to account for the differences in these various studies, as Culleton et al1 have attempted, but most of the studies examined the very same variables. A more central issue is whether one should interpret the finding that a risk factor is not statistically independent to mean that it should not be considered biologically important. We would argue that this is not true in several situations. First, if the risk factors are causally linked, then one may not be able to show that they are independent of each other. For example, although smoking is a risk factor for mortality, it might no longer be independent if it is …

Purpose: Studies on long-term cardiovascular disease (CVD) risk in breast cancer (BC) survivors are limited. We examined CVD risk associated with exposure to specific BC therapies and explored whether body mass index (BMI) or prevalent CVD risk factors at BC diagnosis modified these associations. Methods: The Pathways Heart Study is a prospective cohort study examining incident CVD outcomes and risk factors in women with BC at Kaiser Permanente Northern California (KPNC). Eligible women were diagnosed with stage I-IV invasive BC from 2005-2013, &amp;ge;21 years old, and KPNC members &amp;ge;12 months at diagnosis. KPNC records provided demographic and BC therapy characteristics. Incident CVD outcomes [ischemic heart disease, heart failure/cardiomyopathy (HF/CM), stroke] were assessed from ICD9/10 codes. Multivariable Cox models estimated hazard ratios (HR) and 95% confidence intervals (CI) of each CVD outcome by cancer therapy received compared to not receiving that therapy, excluding those with prevalent CVD. Separate regression models included interaction terms for cancer therapy by overweight, obesity, diabetes, dyslipidemia, and hypertension to test whether the CVD outcome risk varied by presence of these factors at diagnosis. Results: Among 4,181 BC survivors with mean age of 59.6±12.0 years and mean follow-up of 7.9±3.5 years (range: 0.04-13.3), cancer therapies were not associated with incident CVD. However, CVD risks varied by BMI and prevalence of CVD risk factors at BC diagnosis. Normal weight (NW) women who received anthracyclines had higher risk of ischemic heart disease and HF/CM relative to NW women not receiving these therapies; interaction terms indicated HF/CM risk was statistically different than risks for obese women (Table). NW women who received cyclophosphamide or left-sided radiation had higher risk of HF/CM and stroke relative to NW women not receiving these therapies; these risks were statistically different from obese (for cyclophosphamide) or overweight (for radiation) women. Relative to women not receiving these therapies, higher HRs for HF/CM were observed among non-diabetic women who received cyclophosphamide (2.03, CI: 1.22-3.37), non-dyslipidemic women who received anthracyclines (3.65, CI: 1.69-7.87), and non-hypertensive women who received either anthracyclines (4.04, CI: 1.81-9.03) or cyclophosphamide (2.66, CI: 1.23-5.74) (P for interaction range: 0.04 to 0.06). Conclusion: Certain chemotherapy drugs may increase the risk of CVD in NW BC survivors; overweight and obese BC survivors may experience less risk than NW women. While chemotherapy also appears to increase HF/CM risk for women without diabetes, dyslipidemia, and hypertension, these conditions are more prevalent among overweight/obese women. Analysis within these subgroups is needed and forthcoming. Table. Adjusted HRs (95% CI) of CVD outcomes among breast cancer survivors receiving select cancer therapies* stratified by BMI status at diagnosisBMI Ischemic heart diseaseHeart failure/CardiomyopathyStrokeAnthracycline, n=1283Normal4.22 (1.59, 11.2)5.27 (2.54, 10.9)1.89 (0.79, 4.53)Overweight1.66 (0.73, 3.77)2.17 (1.15, 4.11)0.40 (0.16, 0.99)Obese1.26 (0.56, 2.85)1.1 (0.54, 2.27)a0.33 (0.13, 0.83)aCyclophosphamide, n=1705Normal1.63 (0.61, 4.31)3.28 (1.59, 6.75)2.21 (1.01, 4.84)Overweight1.59 (0.75, 3.39)1.63 (0.9, 2.97)0.73 (0.34, 1.58)Obese0.85 (0.39, 1.86)0.75 (0.38, 1.47)a0.31 (0.13, 0.71)aLeft-Side Radiation, n=1331Normal1.44 (0.56, 3.69)2.04 (1.0, 4.18)2.38 (1.28, 4.42)Overweight1.47 (0.68, 3.16)0.68 (0.34, 1.34)b0.72 (0.37, 1.4)bObese1.32 (0.73, 2.38)1.30 (0.79, 2.16)1.05 (0.61, 1.82)*Cancer therapies with non-significant findings (i.e., Trastuzumab, taxanes, aromatase inhibitors, Tamoxifen, and any-side radiation) are not shown.ap≤0.05 normal weight v. obese; bp≤0.05 normal weight v. overweight Citation Format: Heather Greenlee, Eileen Rillamas-Sun, Carlos Iribarren, Richard Cheng, Romain Neugebauer, Jamal S. Rana, Mai Nguyen-Huynh, Zaixing Shi, Cecile A. Laurent, Valerie S. Lee, Janise M. Roh, Hanjie Shen, Dawn L. Hershman, Lawrence H. Kushi, Marilyn L. Kwan. Cardiovascular disease risk of breast cancer therapies: The pathways heart study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD5-01.

The Effects of Dietary Sugars on Cardiovascular Disease and Cardiovascular Disease–Related Mortality: Finding the Sweet Spot

Article Figures and data Abstract Editor's evaluation Introduction Materials and methods Results Discussion Data availability References Decision letter Author response Article and author information Metrics Abstract Background: The risk of adult onset cardiovascular and metabolic (cardiometabolic) disease accrues from early life. Infection is ubiquitous in infancy and induces inflammation, a key cardiometabolic risk factor, but the relationship between infection, inflammation, and metabolic profiles in early childhood remains unexplored. We investigated relationships between infection and plasma metabolomic and lipidomic profiles at age 6 and 12 months, and mediation of these associations by inflammation. Methods: Matched infection, metabolomics, and lipidomics data were generated from 555 infants in a pre-birth longitudinal cohort. Infection data from birth to 12 months were parent-reported (total infections at age 1, 3, 6, 9, and 12 months), inflammation markers (high-sensitivity C-reactive protein [hsCRP]; glycoprotein acetyls [GlycA]) were quantified at 12 months. Metabolic profiles were 12-month plasma nuclear magnetic resonance metabolomics (228 metabolites) and liquid chromatography/mass spectrometry lipidomics (776 lipids). Associations were evaluated with multivariable linear regression models. In secondary analyses, corresponding inflammation and metabolic data from birth (serum) and 6-month (plasma) time points were used. Results: At 12 months, more frequent infant infections were associated with adverse metabolomic (elevated inflammation markers, triglycerides and phenylalanine, and lower high-density lipoprotein [HDL] cholesterol and apolipoprotein A1) and lipidomic profiles (elevated phosphatidylethanolamines and lower trihexosylceramides, dehydrocholesteryl esters, and plasmalogens). Similar, more marked, profiles were observed with higher GlycA, but not hsCRP. GlycA mediated a substantial proportion of the relationship between infection and metabolome/lipidome, with hsCRP generally mediating a lower proportion. Analogous relationships were observed between infection and 6-month inflammation, HDL cholesterol, and apolipoprotein A1. Conclusions: Infants with a greater infection burden in the first year of life had proinflammatory and proatherogenic plasma metabolomic/lipidomic profiles at 12 months of age that in adults are indicative of heightened risk of cardiovascular disease, obesity, and type 2 diabetes. These findings suggest potentially modifiable pathways linking early life infection and inflammation with subsequent cardiometabolic risk. Funding: The establishment work and infrastructure for the BIS was provided by the Murdoch Children's Research Institute (MCRI), Deakin University, and Barwon Health. Subsequent funding was secured from National Health and Medical Research Council of Australia (NHMRC), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women's Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Minderoo Foundation, the Ilhan Food Allergy Foundation, GMHBA, Vanguard Investments Australia Ltd, and the Percy Baxter Charitable Trust, Perpetual Trustees. In-kind support was provided by the Cotton On Foundation and CreativeForce. The study sponsors were not involved in the collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication. Research at MCRI is supported by the Victorian Government's Operational Infrastructure Support Program. This work was also supported by NHMRC Senior Research Fellowships to ALP (1008396); DB (1064629); and RS (1045161) , NHMRC Investigator Grants to ALP (1110200) and DB (1175744), NHMRC-A*STAR project grant (1149047). TM is supported by an MCRI ECR Fellowship. SB is supported by the Dutch Research Council (452173113). Editor's evaluation This paper provides data from a population-based cohort study on early life infection and proinflammatory, atherogenic metabolomic and lipidomic profiles at 12 months of age. The authors generated matched infection, metabolomics and lipidomics data from 555 infants in a pre-birth longitudinal cohort and they showed that frequent infant infections are associated with adverse metabolomic and lipidomic profiles. They also report that similar profiles are noted with higher glycoprotein acetyls (GlycA), but not hsCRP. The paper is interesting and assesses the role of infection and markers of inflammation on lipid and metabolic profile of patients. It provides a comprehensive analysis of lipids and metabolites in infants in response to infection. https://doi.org/10.7554/eLife.75170.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Infectious diseases are ubiquitous in infancy and childhood, with potential long-term impacts on health across the life course. Infection has been recognised as a potential contributor to atherosclerotic cardiovascular disease (CVD), one of the leading causes of adult morbidity and mortality, since the 19th century (Nieto, 1998). More recent adult studies link previous infection with long-term risks of disease (Bergh et al., 2017; Cowan et al., 2018; Wang et al., 2017). The mechanisms are largely unknown, but likely include immune activation and heightened inflammation (Shah, 2019), which are pathways central to CVD pathogenesis (Donath et al., 2019b; Ferrucci and Fabbri, 2018) and therefore offer potentially druggable targets in high-risk individuals (Donath et al., 2019a; Ridker et al., 2017). High-sensitivity C-reactive protein (hsCRP) has been extensively used as a marker of chronic inflammation in adult studies but is an acute phase reactant in children and may not reflect chronic inflammation in early life. Glycoprotein acetyls (GlycA) is a nuclear magnetic resonance (NMR) composite measure that is suggested to better reflect cumulative, chronic inflammation (Connelly et al., 2017). GlycA is an emerging biomarker for cardiometabolic risk (Connelly et al., 2017) that outperforms hsCRP as a predictor of CVD events and mortality (Akinkuolie et al., 2014; Duprez et al., 2016), and of infection-related morbidity and mortality (Ritchie et al., 2015). For example, in the Multi-Ethnic Study of Atherosclerosis (n = 6523), higher GlycA was associated with increased risk of incidence CVD and death, even after adjustment for hsCRP and other inflammatory markers. Conversely, prediction of these outcomes by hsCRP attenuated to null after mutual adjustment (Duprez et al., 2016). Cardiovascular and metabolic (cardiometabolic) disease pathogenesis begins in early life and accrues across the life course (Nakashima et al., 2008). Infections occur disproportionally in early childhood (Cromer et al., 2014; Grüber et al., 2008; Troeger et al., 2018; Tsagarakis et al., 2018), and there is a dose-response relationship between childhood infections, adverse cardiometabolic phenotypes (Burgner et al., 2015c), and CVD events (Burgner et al., 2015a) in adulthood. Infection is linked to proatherogenic metabolic perturbations in later childhood and adulthood (Feingold and Grunfeld, 2019; Khovidhunkit et al., 2000), including higher triglycerides and oxidised low-density lipoprotein (LDL), and lower high-density lipoprotein (HDL) cholesterol and apolipoprotein A1 (ApoA1) (Liuba et al., 2003; Pesonen et al., 1993), and to acute and chronic inflammation (Burgner et al., 2015b; Ritchie et al., 2015), but little is known about these relationships in early life, when most infections occur. We therefore aimed to characterise metabolomic and lipidomic profiles at 6 and 12 months of age and their relationship to infection burden during the first year of life. We also investigated the extent to which inflammation mediated the relationship between infection burden and metabolomic and lipidomic differences. Materials and methods Study cohort Request a detailed protocol This study used available data from 555 mother-infant dyads in the Barwon Infant Study (BIS), a population-based pre-birth longitudinal cohort (n = 1074 mother-infant dyads). The cohort details and inclusion/exclusion criteria have been detailed elsewhere (Vuillermin et al., 2015); in brief, mothers were eligible if they were residents of the Barwon region in south-east Australia and planned to give birth at the local public or private hospital. Mothers were recruited at approximately 15 weeks' gestation and provided informed consent. They were excluded if they were not a permanent Australian resident, aged <18 years, required an interpreter to complete questionnaires, or had previously participated in BIS. Infants were excluded if they were very preterm (<32 completed weeks gestation) or had a serious illness or major congenital malformation identified during the first few days of life. Ethics approval was granted by the Barwon Health Human Research Ethics Committee (HREC 10/24). Parent-reported infections Request a detailed protocol At the 4-week, 3-month, 6-month, 9-month, and 12-month time points following birth, mothers were asked to report each episode of infant illness or infection since the previous time point using standardised online questionnaires. The number of parent-reported infections from birth to 12 months was defined as the total number of respiratory tract infections, gastroenteritis, conjunctivitis, and acute otitis media episodes. In secondary analyses, numbers of parent-reported infections from birth to 6 months and from 6 to 12 months were considered. It was not possible to identify the proportion of parent-reported infections that lead to health service utilisation (Rowland et al., 2021). Other maternal and infant measures Request a detailed protocol Questionnaires during pregnancy and at birth were used to collect self-reported data on maternal age, household income, maternal education, and prenatal smoking (considered here as a dichotomous any/none exposure). Residential postcode was used to determine neighbourhood disadvantage using the Index of Relative Socio-Economic Disadvantage (IRSD) from the 2011 Socio-Economic Indexes for Areas (SEIFA) (Pink, 2013), with a lower score corresponding to greater socioeconomic disadvantage. Pre-eclampsia (based on International Association of Diabetes and Pregnancy Study Groups criteria; Tranquilli et al., 2014) and gestational diabetes (based on International Society for the Study of Hypertension in Pregnancy criteria; Nankervis et al., 2013) diagnoses were extracted from hospital records. Infant gestational age, birth weight, and mode of delivery (categorised as vaginal, planned caesarean section, or unplanned caesarean section delivery) were collected from birth records, and the age- and sex-standardised birth weight z-score was calculated using the 2009 revised British United Kingdom World Health Organisation (UK-WHO) growth charts (Cole et al., 2011). Postnatal smoking data was collected from questionnaire data, with mothers asked the average number of hours each day someone smoked near or in the same room as the child (Gray et al., 2019). This was dichotomised as any postnatal smoke exposure if >0 hr reported at any time point up to 12 months of age, or no postnatal smoke exposure. Breastfeeding duration up to 12 months of age was collected from maternal questionnaire data. As most evidence for the protective effect of breastfeeding on early life infection is from comparisons between any breastfeeding and no breastfeeding (Victora et al., 2016), and in light of previous evidence in BIS for an association between even a short duration of breastfeeding and lower odds of infection in early infancy (Rowland et al., 2021), we first looked at breastfeeding as a binary (any/none) measure in models (presented in the main text). As most infants (98.2%) were breastfed to some extent, and it is unknown the degree to which breastfeeding, and the timing of breastfeeding, might affect infant metabolomics and lipidomics, we also considered duration of breastfeeding as a continuous variable for sensitivity analyses. Metabolomic and lipidomic profiling Request a detailed protocol Venous peripheral blood was collected from infants at the 6- and 12-month time points in sodium heparin and generally processed within 4 hr, with a minority (197 of 555) of 12-month samples processed after 4 hr (median time for those 197 samples = 19.9 hr, inter-quartile range [IQR] [18.7, 21.4]). The time interval between collection and post-processing storage of samples was included as a covariate in analyses. Due to the bimodal distribution of 12-month sample collection times as samples were either processed same day of collection or the following day, sensitivity analysis excluding participants with a plasma storage time greater than 4 hr (197 out of 555 infants, predominantly processed the following day) was performed, as described in the Statistical analysis section below. Plasma was stored at –80°C, and aliquots were shipped on dry ice to Nightingale Health (Helsinki, Finland) for NMR metabolomic quantification and Baker IDI (Melbourne, Australia) for liquid chromatography/mass spectrometry (LC/MS) lipidomic quantification, as described below. For secondary analyses investigating possible 'reverse causality', that is, whether metabolomic or lipidomic profile at birth was associated with number of parent-reported infections from birth to 6 months of age, metabolomics and lipidomics data using the same platforms from venous cord blood collected at birth, as previously described (Burugupalli et al., 2022; Mansell et al., 2021), was used. The NMR-based metabolomics platform has been described in detail (Kettunen et al., 2016; Soininen et al., 2015), and quantified a broad range of metabolic measures including lipoprotein size subclasses, triglycerides, cholesterols, fatty acids, amino acids, ketone bodies, glycolysis metabolites, and GlycA. In brief, plasma samples were mixed with a sodium phosphate buffer prior to NMR measurements with Bruker AVANCE III 500 MHz and Bruker AVANCE III HD 600 MHz spectrometers (Bruker, Billerica, MA). Samples were kept at 6°C using the SampleJet sample changer (Bruker) to prevent degradation. After initial measurements, samples went through a multiple-step lipid extraction procedure using saturated sodium chloride solution, methanol, dichloromethane, and deuterochloroform. The lipid extracts were then analysed using the 600 MHz instrument (Soininen et al., 2015). The utility of this platform in epidemiological research has been detailed elsewhere (Würtz et al., 2017). Using the Nightingale Health 2016 bioinformatics protocol, 228 metabolomic measures were generated for the 12-month samples. From a subset of participants, replicate samples were quantified, and these showed a low percentage coefficient of variation (<10%). Subsequently, the Nightingale Health 2020 bioinformatics protocol was used to generate 250 metabolomic measures for the 6-month samples, with 224 of these measures also present in the 12-month data. As a large proportion of the NMR metabolomic measures are ratios and are strongly correlated with each other in children and adults (Ellul et al., 2019), an informative subset of 51 measures that captured the majority of variation in the metabolomic dataset, primarily absolute metabolite concentrations, were included in analysis presented in the main text. Analyses for excluded metabolomic measures are presented as supplementary data. To complement GlycA as a measure of inflammation, hsCRP was also quantified in 6- and 12-month plasma using enzyme-linked immunosorbent assay (ELISA) (R&D Systems, Minneapolis, MN, cat. no. DY1707), as per the manufacturer's instruction. The details of the high-performance LC/MS lipidomics platform have been described elsewhere (Beyene et al., 2020). In addition, we used medronic acid to passivate the LC/MS system to avoid peak tailing for acidic phospholipids (Hsiao et al., 2018). In brief, this platform quantified 776 lipid features in 36 lipid classes, including sphingolipids, glycerophospholipids, sterols, glycerolipids, and fatty acyls. Analysis was performed on an Agilent 6490 QQQ mass spectrometer with an Agilent 1290 series high-performance liquid chromatography system and two ZORBAX eclipse plus C18 column (2.1 × 100 mm 1.8 mm) (Agilent, Santa Clara, CA) with the thermostat set at 45°C. Mass spectrometry analysis was performed in both positive and negative ion mode with dynamic scheduled multiple reaction monitoring. Quantification of lipid species was determined by comparison to the relevant internal standard. Lipid class total concentrations were calculated as the sum of individual lipid species concentrations, except in the case of triacylglycerols (TGs) and alkyl-diacylglycerols, where we measured both neutral loss and single ion monitoring (SIM) peaks, and subsequently used the SIM species concentrations for summation purposes. Statistical analysis Request a detailed protocol Analyses were performed in R (version 3.6.3) (R Development Core Team, 2018). All metabolomic and lipidomic measures had their lowest observed non-zero value (considered the lower limit of detection) added to their value before they were natural log-transformed and scaled to a standard distribution (standard deviation units). Pearson's correlations were calculated for number of infections from birth to 12 months with 12-month GlycA and hsCRP. The estimated effect of number of parent-reported infections from birth to 12 months as an exposure on 12-month metabolomic and lipidomic profile was investigated using linear regression models for each metabolomic/lipidomic measure. Standard errors were used to calculate 95% confidence intervals for estimated effects. All models were adjusted for infant sex, exact age at 12-month time point, birth weight z-score, gestational age, maternal household income, exposure to maternal smoking during pregnancy, breastfeeding, and time from collection to storage for the plasma sample. Linear regression models adjusted for the same covariates were used to investigate 12-month GlycA and hsCRP as exposures and each metabolomic/lipidomic measure as an outcome. Two-tailed p-values were adjusted for multiple comparisons within each dataset (NMR metabolomics, LC/MS lipidomic species, and LC/MS lipidomic classes) using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995). To investigate the robustness of the estimates, mean model coefficients and bias-corrected accelerated percentile bootstrap confidence intervals were calculated from nonparametric bootstrap resampling (1000 iterations) using the 'boot' package (Davison and Hinkley, 1997) (version 1.3–25) in R, included in Source Data. The assumption of linearity was investigated post hoc using plots of residual values for the top 10 metabolomic and lipidomic differences (ranked by p-value) for each of number of infections, GlycA, and hsCRP. To further investigate the other sources of potential confounding and variation that could affect findings from the primary models, several sensitivity analyses were performed. These were: (i) additional adjustment of the primary model for postnatal smoking exposure, gestational diabetes, and pre-eclampsia; (ii) analyses excluding twins (five infants); (iii) analyses excluding infants with hsCRP >5 mg/L (24 infants) as a marker of acute infection (Lemiengre et al., 2018; et al., analyses excluding plasma samples with hr from collection to storage (197 and analyses for breastfeeding duration of any Analyses of the primary models adjusted for measures of socioeconomic or maternal of household were also considered. These models are presented as supplementary plots analyses to investigate 6-month of infections were performed. The birth to 6-month models investigated the relationship between infections up to 6 months of age, 6-month inflammation, and 6-month metabolomic/lipidomic The 6- to 12-month models investigated the relationship of infections between 6 and 12 months of age, 12-month inflammation, and 12-month metabolomic/lipidomic with adjustment for the corresponding 6-month For secondary analyses to investigate regression models et al., were either for (i) each metabolomic/lipidomic measure from cord blood at birth as exposure and total number of infections from birth to 6 months of age as or (ii) each 6-month metabolomic/lipidomic measures as exposure and total number of infections from 6 to 12 months of age as the with adjustment for number of infections from birth to 6 months of age. All secondary models were adjusted for the same covariates as the primary models described that is, infant sex, gestational age, exact age 6- or 12-month time birth weight z-score, maternal household income, exposure to maternal smoking during pregnancy, and sample time between collection and post-processing with birth metabolomic/lipidomic measures as the exposure were adjusted for mode of which is associated with differences across NMR metabolomic measures in cord in this cohort et al., 2021). To investigate the potential role of inflammation in mediating associations between infection and metabolic the package et al., 2017) (version in R was then used in a to the natural effect mediated by and natural effect by of infection. 12-month GlycA or hsCRP were considered as for the effect of number of infections from birth to 12 months of age on metabolomic and lipidomic differences at 12 months, for metabolomic and lipidomic measures associated with number of infections with an adjusted from the linear regression models described mediation was calculated as the estimated natural effect by the total effect effect plus natural of the mediation model is in for model investigated in this The natural effect by glycoprotein acetyls or C-reactive protein and natural effect mediated by of parent-reported infections on metabolomic and lipidomic measures were with adjustment for were considered to for associations to exposure to and to As models investigating described suggested that 6-month GlycA or lipidomic measures may number of infections from 6 to 12 months of age, we performed mediation analyses to the percentage mediation of 12-month GlycA and hsCRP for the effect of number of infections from 6 to 12 months of age on 12-month metabolomic and lipidomic with additional adjustment for the corresponding 6-month measures of infections from birth to 6 months of age, 6-month GlycA or and the 6-month metabolomic/lipidomic Results The for the 555 infants included in this study is in and the cohort for these infants are in The number of total parent-reported infections from birth to 12 months of age was = infections from birth to 6 months of age was 2 and infections from 6 to 12 months of age was 12-month hsCRP and GlycA were mg/L and number of parent-reported infections between birth and 12 months of age was more strongly correlated with 12-month GlycA = than hsCRP = The of metabolomic and lipidomic measures at each time point for the cohort are in and (n = age at delivery smoking during pregnancy diabetes (n = (n = household to to to to (n = than year 10 of 10 of or 12 of or of birth caesarean caesarean postnatal smoke exposure to 12 months (n = of duration to weeks age weight weight at 6-month time point at 6 months z-score at 6 at 12-month time point at 12 months z-score at 12 of parent-reported infections from birth to 12 Infections from birth to 6 Infection from 6 to 12 GlycA at 6 months at 6 months at 12 months at 12 months All = 555 infants had complete covariate data for primary models, data of secondary exposures is to the relevant measure. lower value greater socioeconomic disadvantage on 2 of Barwon Infant Study participants included this study participants had complete infection data from time points between birth and 12 months of age, and 12-month plasma nuclear magnetic resonance (NMR) metabolomics data. included participants (n = out of 555) had 12-month plasma liquid chromatography/mass spectrometry (LC/MS) lipidomics data. Infection and inflammation burden and plasma NMR metabolomic profile at 12 months was evidence for higher number of infections with higher inflammatory markers per infection, 95% and hsCRP lower HDL to to and to cholesterols, lower to lower to higher and to a extent with higher triglycerides and lower to In models with GlycA as the marker of inflammation metabolomic differences observed for higher GlycA were largely similar but more those for parent-reported including HDL per in GlycA to higher and lipoprotein to higher apolipoprotein higher total fatty higher total triglycerides and amino and lower to metabolites lower to and lower to were generally similar to standard regression for models. effect were generally similar across most sensitivity analyses excluding samples with time greater than 4 hr the of estimated of parent-reported infections on HDL and hsCRP was associated with lower HDL cholesterol per in to to and to and higher to as observed for GlycA, and with lower of most other amino and to and higher triglycerides with 2 in 12-month plasma nuclear magnetic resonance (NMR) metabolomic measures for each in parent-reported infection to 12 and for each in 12-month glycoprotein acetyls (GlycA) (n = plots of the estimated 12-month metabolomic differences for each additional parent-reported infection from birth to 12 months or 12-month GlycA from adjusted linear regression models, and the