Quality of relationships in mothers and their partners in the Avon Longitudinal Study of Parents and Children.

Quality of relationship between partners is associated with a wide range of physical and psychological outcomes like anxiety and depression. There are relatively few longitudinal studies with detailed and repeated measures for quality of relationship, particularly in both partners. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a large birth cohort study in the UK with five post-partum repeated measures of quality of relationship between mothers and their partners assessed using the Intimate Bond Measure (IBM). The Measure includes two subscales named "Care" and "Control". These were measured at 2.75, 6, 9, 12, and 18 years post-partum (baseline N for mothers: 8675; baseline N for partners: 5499). The aims of this data note are to provide a comprehensive overview on the existing IBM data in ALSPAC and to describe both its strengths and limitations for future users. The internal consistency of the subscales were high (Cronbach's alpha 0.95 and 0.88 for the Care and Control subscales) in both mothers and their partners at the baseline. In the Care subscale, all 12 items were highly correlated with the overall score (r>0.62) at the baseline, but in the Control subscale there were three items that had relatively low correlations with the total subscale (r<0.46). This should be taken into account in future research. The longitudinal nature of this data on both mothers and partners will enable detailed explorations of the causes and consequences of differences in quality of relationship.

Glycoprotein acetyls and depression: Testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses.

BACKGROUND: Inflammation is associated with depression, but causality remains unclear. We investigated potential causality and direction of effect between inflammation and depression. METHODS: Using data from the ALSPAC birth cohort (n = 4021; 42.18 % male), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression and depression symptoms, assessed at ages 18y and 24y. We used two-sample Mendelian randomization (MR) to investigate potential causality and directionality. Genetic variants for GlycA were obtained from UK Biobank (UKB) (N = 115,078); for depression from the Psychiatric Genomics Consortium and UKB (N = 500,199); and for depressive symptoms (N = 161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted method, we used sensitivity analyses to strengthen causal inference. We conducted multivariable MR adjusting for body mass index (BMI) due to known genetic correlation between inflammation, depression and BMI. RESULTS: In the cohort analysis, after adjusting for potential confounders we found no evidence of associations between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression (OR = 1∙18, 95 % CI: 1∙03-1∙36). MR suggested no causal effect of GlycA on depression, but there was a causal effect of depression on GlycA (mean difference in GlycA = 0∙09; 95 % CI: 0∙03-0∙16), which was maintained in some, but not all, sensitivity analyses. LIMITATIONS: The GWAS sample overlap could incur bias. CONCLUSION: We found no consistent evidence for an effect of GlycA on depression. There was evidence that depression increases GlycA in the MR analysis, but this may be confounded/mediated by BMI.

Cross-Sectional Blood Metabolite Markers of Hypertension: A Multicohort Analysis of 44,306 Individuals from the COnsortium of METabolomics Studies.

Hypertension is the main modifiable risk factor for cardiovascular morbidity and mortality but discovering molecular mechanisms for targeted treatment has been challenging. Here we investigate associations of blood metabolite markers with hypertension by integrating data from nine intercontinental cohorts from the COnsortium of METabolomics Studies. We included 44,306 individuals with circulating metabolites (up to 813). Metabolites were aligned and inverse normalised to allow intra-platform comparison. Logistic models adjusting for covariates were performed in each cohort and results were combined using random-effect inverse-variance meta-analyses adjusting for multiple testing. We further conducted canonical pathway analysis to investigate the pathways underlying the hypertension-associated metabolites. In 12,479 hypertensive cases and 31,827 controls without renal impairment, we identified 38 metabolites, associated with hypertension after adjusting for age, sex, body mass index, ethnicity, and multiple testing. Of these, 32 metabolite associations, predominantly lipid (steroids and fatty acyls) and organic acids (amino-, hydroxy-, and keto-acids) remained after further adjusting for comorbidities and dietary intake. Among the identified metabolites, 5 were novel, including 2 bile acids, 2 glycerophospholipids, and ketoleucine. Pathway analysis further implicates the role of the amino-acids, serine/glycine, and bile acids in hypertension regulation. In the largest cross-sectional hypertension-metabolomics study to date, we identify 32 circulating metabolites (of which 5 novel and 27 confirmed) that are potentially actionable targets for intervention. Further in-vivo studies are needed to identify their specific role in the aetiology or progression of hypertension.

A Maternal Serum Metabolite Ratio Predicts Large for Gestational Age Infants at Term: A Prospective Cohort Study.

CONTEXT: Excessive birth weight is associated with maternal and neonatal complications. However, ultrasonically estimated large for gestational age (LGA; >90th percentile) predicts these complications poorly. OBJECTIVE: To determine whether a maternal serum metabolite ratio developed for fetal growth restriction (FGR) is predictive of birth weight across the whole range, including LGA at birth. METHODS: Metabolites were measured using ultrahigh performance liquid chromatography-tandem mass spectroscopy. The 4-metabolite ratio was previously derived from an analysis of FGR cases and a random subcohort from the Pregnancy Outcome Prediction study. Here, we evaluated its relationship at 36 weeks of gestational age (wkGA) with birth weight in the subcohort (n = 281). External validation in the Born in Bradford (BiB) study (n = 2366) used the metabolite ratio at 24 to 28 wkGA. RESULTS: The inverse of the metabolite ratio at 36 wkGA predicted LGA at term [the area under the receiver operating characteristic curve (AUROCC) = 0.82, 95% CI 0.73 to 0.91, P = 6.7 × 10-5]. The ratio was also inversely associated with birth weight z score (linear regression, beta = -0.29 SD, P = 2.1 × 10-8). Analysis in the BiB cohort confirmed that the ratio at 24 to 28 wkGA predicted LGA (AUROCC = 0.60, 95% CI 0.54 to 0.67, P = 8.6 × 10-5) and was inversely associated with birth weight z score (beta = -0.12 SD, P = 1.3 × 10-9). CONCLUSIONS: A metabolite ratio which is strongly predictive of FGR is equally predictive of LGA birth weight and is inversely associated with birth weight across the whole range.

Inflammation proteomics datasets in the ALSPAC cohort.

Proteomics is the identification, detection and quantification of proteins within a biological sample. The complete set of proteins expressed by an organism is known as the proteome. The availability of new high-throughput proteomic technologies, such as Olink Proteomic Proximity Extension Assay (PEA) technology has enabled detailed investigation of the circulating proteome in large-scale epidemiological studies. In particular, the Olink® Target 96 inflammatory panel allows the measurement of 92 circulating inflammatory proteins. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1991-1992 and has followed these women, their partners, and their offspring ever since. In this data note, we describe the newly-released proteomic data available in ALSPAC. Ninety-two proteins were analysed in 9000 blood plasma samples using the Olink® Target 96 inflammatory panel. Samples were derived from 2968 fasted mothers (mean age 47.5; Focus on Mothers 1 (FOM1)), 3005 non-fasted offspring at age 9 (Focus@9) and 3027 fasted offspring at age 24 (Focus@24). Post sample filtering, 1834 offspring have data at both timepoints and 1119 of those have data from their mother available. We performed quality control analyses using a standardised data processing workflow ( metaboprep) to produce a filtered dataset of 8983 samples for researchers to use in future analyses. Initial validation analyses indicate that IL-6 measured using the Olink® Target 96 inflammatory panel is highly correlated with IL-6 previously measured by clinical chemistry (Pearson's correlation = 0.77) and we are able to reproduce the reported positive correlation between body mass index (BMI) and IL-6. The pre-processing and validation analyses indicate a rich proteomic dataset to further characterise the role of inflammation in health and disease.

Demographic and socioeconomic predictors of religious/spiritual beliefs and behaviours in a prospective cohort study (ALSPAC) in Southwest England: Results from the offspring generation.

Background: We explored associations between possible demographic and socioeconomic causes of religious/spiritual beliefs and behaviours (RSBB) in the offspring generation of the Avon Longitudinal Study of Parents and Children (ALSPAC). Methods: We examined approximately 4,450 offspring aged 28 years with RSBB data from a prospective birth cohort study (ALSPAC) in Southwest England. Three RSBB outcome measures were assessed: religious belief (belief in God/a divine power; yes/not sure/no), religious affiliation (Christian/none/other) and religious attendance (frequency of attendance at a place of worship). We explored age- and sex-adjusted associations between 35 demographic and socioeconomic exposures and each of the three RSBB outcomes using multinomial regression. Exposure-sex interactions were also examined. Results: Some sociodemographic factors were associated with RSBB in this cohort; for instance, being female and from an ethnicity other than White were associated with increased religiosity across all domains. For many other exposures, however, associations were frequently null or inconsistent, often depending on the specific exposure and outcome combination. As an example, higher educational attainment was associated with higher rates of religious attendance, but not with religious belief or affiliation; in contrast, higher income was associated with lower levels of religiosity. No consistent interactions between sex and the exposures on RSBB were found. Effect sizes were also rather weak, with most pseudo- R 2 values below 0.5% and a maximum of 1.2%. Conclusions: The results highlight that several demographic and socioeconomic factors are associated with RSBB in this cohort. However, the number of these associations, and their magnitude, is smaller than comparable results from the parental generation of these offspring, suggesting that patterns of sociodemographic factors associated with RSBB differ between these generations. In addition to describing these associations, this paper will help inform future studies using these data, particularly regarding the choice of potential sociodemographic confounders.

Spousal associations of serum metabolomic profiles by nuclear magnetic resonance spectroscopy.

Phenotype-based assortative mating is well established in humans, with the potential for further convergence through a shared environment. To assess the correlation within infertile couples of physical, social, and behavioural characteristics and 155 circulating metabolic measures. Cross sectional study at a tertiary medical center of 326 couples undertaking IVF. Serum lipids, lipoprotein subclasses, and low-molecular weight metabolites as quantified by NMR spectroscopy (155 metabolic measures). Multivariable and quantile regression correlations within couples of metabolite profiles. Couples exhibited statistical correlations of varying strength for most physical, social, and behavioural characteristics including age, height, alcohol consumption, education, smoking status, physical activity, family history and ethnicity, with correlation coefficients ranging from 0.22 to 0.73. There was no evidence of within couple associations for BMI and weight, where the correlation coefficients were - 0.03 (95% CI - 0.14, 0.08) and 0.01 (95% CI - 0.10, 0.12), respectively. Within spousal associations of the metabolite measurements were all positive but with weak to modest magnitudes, with the median correlation coefficient across all 155 measures being 0.12 (range 0.01-0.37 and interquartile range 0.10-0.18). With just four having associations stronger than 0.3: docosahexaenoic acid (0.37, 95% CI 0.22, 0.52), omega-3 fatty acids (0.32, 95% CI 0.20, 0.43) histidine (0.32, 95% CI 0.23, 0.41) and pyruvate (0.32, 95% CI 0.22, 0.43). Infertile couples exhibit spousal similarities for a range of demographic and serum metabolite measures, supporting initial assortative mating, with diet-derived metabolites suggesting possible subsequent convergence of their individual metabolic profile.

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses.

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Association of the functional ovarian reserve with serum metabolomic profiling by nuclear magnetic resonance spectroscopy: a cross-sectional study of ~ 400 women.

BACKGROUND: Women with diminished ovarian reserve are known to have increased cardiovascular risk, whether there is a continuous association between the ovarian reserve biomarkers; anti-Müllerian hormone (AMH), antral follicle count (AFC) and cardio-metabolic risk factors are unknown. METHODS: A cross-sectional study of 398 women intending to undergo IVF with pre-treatment early follicular AMH and AFC measurements. Serum lipids, lipoprotein subclasses and low-molecular-weight metabolites were quantified by NMR spectroscopy (155 metabolic measures). Associations were analysed using multivariable regression. RESULTS: Participants were mean 35.5 (SD 4.43) years old and had a median AMH of 16 pmol/l (IQR 8.8, 28.0 pmol/l) and a median AFC of 12 (IQR 7.16). AMH showed positive associations with HDL, omega-6 and polyunsaturated fatty acids and the amino acids isoleucine, leucine and tyrosine, with effects ranging from 0.11 (95%CI 0.004 to 0.21) for total lipids in small HDL to 0.16 (0.06 to 0.26) for isoleucine, for a mean difference of one SD of metabolite per one SD increment in AMH, and negatively with acetate: - 0.31(- 0.22, - 0.004) SD per 1 SD AMH. AFC was positively associated with alanine, glutamine and glycine. Results were consistent, though less precisely estimated, when restricted to those women who were preparing for treatment because of their partner's infertility. CONCLUSIONS: In women intending to have IVF, AMH and AFC were not associated with traditional lipid measured but were associated with a number of novel cardiovascular risk factors. Prospective studies will be required for replication, determination of causality and confirmation that ovarian reserve is impacting on metabolism rather than variation in metabolism is influencing ovarian reserve.

A maternal serum metabolite ratio predicts fetal growth restriction at term.

Fetal growth restriction (FGR) is the major single cause of stillbirth1 and is also associated with neonatal morbidity and mortality2,3, impaired health and educational achievement in childhood4,5 and with a range of diseases in later life6. Effective screening and intervention for FGR is an unmet clinical need. Here, we performed ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) metabolomics on maternal serum at 12, 20 and 28 weeks of gestational age (wkGA) using 175 cases of term FGR and 299 controls from the Pregnancy Outcome Prediction (POP) study, conducted in Cambridge, UK, to identify predictive metabolites. Internal validation using 36 wkGA samples demonstrated that a ratio of the products of the relative concentrations of two positively associated metabolites (1-(1-enyl-stearoyl)-2-oleoyl-GPC (P-18:0/18:1) and 1,5-anhydroglucitol) to the product of the relative concentrations of two negatively associated metabolites (5α-androstan-3α,17α-diol disulfate and N1,N12-diacetylspermine) predicted FGR at term. The ratio had approximately double the discrimination as compared to a previously developed angiogenic biomarker7, the soluble fms-like tyrosine kinase 1:placental growth factor (sFLT1:PlGF) ratio (AUC 0.78 versus 0.64, P = 0.0001). We validated the predictive performance of the metabolite ratio in two sub-samples of a demographically dissimilar cohort, Born in Bradford (BiB), conducted in Bradford, UK (P = 0.0002). Screening and intervention using this metabolite ratio in conjunction with ultrasonic imaging at around 36 wkGA could plausibly prevent adverse events through enhanced fetal monitoring and targeted induction of labor.

A comparison of trends in wastewater-based data and traditional epidemiological indicators of stimulant consumption in three locations.

AIMS: To compare long-term trends in wastewater data with other indicators of stimulant use in three locations and to test the reliability of estimates based on 1 week of sampling. DESIGN: Comparison of trends in quantities ('loads') of stimulants or their metabolites in wastewater with trends in other indicators of stimulant use (e.g. treatment, police, population survey data). SETTING AND PARTICIPANTS: Populations in Oslo (Norway), South-East Queensland (Australia) and Eindhoven (the Netherlands). MEASUREMENTS: Wastewater data were modelled for MDMA (3,4-methyl​enedioxy​methamphetamine), benzoylecgonine (a metabolite of cocaine), amphetamine and methamphetamine in Oslo; benzoylecgonine in Eindhoven; and methamphetamine in South-East Queensland. Choice of stimulants modelled in each region was primarily determined by availability of useable data. FINDINGS: In Oslo, wastewater data, driving under the influence of drugs statistics and seizure data all suggested increasing MDMA use between 2009 and 2017. In South-East Queensland, there was an estimated 31.1% [95% confidence interval (CI) = 29.4-32.9%] annual increase in daily loads of methamphetamine in wastewater between 2009 and 2016, compared with a 14.1% (95% CI = 10.9-17.3%) annual increase in seizures. Some of the increase in wastewater can be explained by increased purity. In Eindhoven, there was no evidence of a change in cocaine consumption from wastewater, but a reduction was observed in numbers in treatment for cocaine use from 2012 to 2017. In approximately half the cases examined in Oslo, credible intervals around estimates of annual average loads from a regression model versus estimates based on a single week of sampling did not overlap. CONCLUSIONS: Long-term trends in loads of stimulants in wastewater appear to be broadly consistent with trends in other indicators of stimulant use in three locations. Wastewater data should be interpreted alongside epidemiological indicators and purity data. One week of wastewater sampling may not be sufficient for valid inference about drug consumption.

Association of the serum metabolomic profile by nuclear magnetic resonance spectroscopy with sperm parameters: a cross-sectional study of 325 men.

OBJECTIVE: To determine whether 155 circulating metabolic measures relevant to lifestyle and metabolic health are associated with sperm parameters, as measured by concentration, motility, and total motile sperm count (TMSC). STUDY DESIGN: Cross sectional. SETTING: University hospital. PATIENT(S): Three hundred twenty-five men prospectively recruited between April 1, 2017 and March 31, 2019. INTERVENTION(S): Detailed demographic, lifestyle, fertility, medical history, and semen analysis with quantification of nonfasting serum lipids, lipoprotein subclasses, and low-molecular weight metabolites (including amino acids, glycolysis, and inflammatory markers) by nuclear magnetic resonance (NMR) spectroscopy. MAIN OUTCOME MEASURE(S): Association of serum metabolic profiles with sperm parameters. RESULT(S): The age of the participants was mean 37.2 years, with a median sperm concentration of 35 million/mL and median motility of 53%. Of these men, 76% had a TMSC >15 million, 10% had 5-15 million, and 14% had <5 million. In both univariate and confounder adjusted analyses, an extensive range of lipids and lipoproteins, glycolysis-related metabolites, amino acids, ketone bodies, creatinine, or albumin showed no strong statistically significant association with sperm concentration, motility, or the odds of having a reduced or low TMSC. Higher levels of glycolysis metabolites and ketone bodies were associated with an increased odds of TMSC <15 million compared with ≥15 million (odds ratios of ∼1.2-1.3), and several lipids/lipoprotein concentrations appeared to protect against very low TMSC (<5 million compared with ≥5 million) with odds ratios of ∼0.8 or greater. CONCLUSION(S): Several metabolites exhibited potentially clinically relevant strength of association with the odds of a low TMSC and warrant replication.

Metabolomics datasets in the Born in Bradford cohort.

Metabolomics is the quantification of small molecules, commonly known as metabolites. Collectively, these metabolites and their interactions within a biological system are known as the metabolome. The metabolome is a unique area of study, capturing influences from both genotype and environment. The availability of high-throughput technologies for quantifying large numbers of metabolites, as well as lipids and lipoprotein particles, has enabled detailed investigation of human metabolism in large-scale epidemiological studies. The Born in Bradford (BiB) cohort includes 12,453 women who experienced 13,776 pregnancies recruited between 2007-2011, their partners and their offspring. In this data note, we describe the metabolomic data available in BiB, profiled during pregnancy, in cord blood and during early life in the offspring. These include two platforms of metabolomic profiling: nuclear magnetic resonance and mass spectrometry. The maternal measures, taken at 26-28 weeks' gestation, can provide insight into the metabolome during pregnancy and how it relates to maternal and offspring health. The offspring cord blood measurements provide information on the fetal metabolome. These measures, alongside maternal pregnancy measures, can be used to explore how they may influence outcomes. The infant measures (taken around ages 12 and 24 months) provide a snapshot of the early life metabolome during a key phase of nutrition, environmental exposures, growth, and development. These metabolomic data can be examined alongside the BiB cohorts' extensive phenotype data from questionnaires, medical, educational and social record linkage, and other 'omics data.