From menarche to menopause: the impact of reproductive factors on the metabolic profile of over 65,000 women

Clayton, Gemma; Borges, Maria Carolina; Lawlor, Deborah A

doi:10.1101/2022.04.17.22273947

Cited by 7 publications

(6 citation statements)

References 70 publications

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“…SNP-outcome (metabolite) estimates were obtained from a GWAS of metabolites in UK Biobank. 56, 57 Prior to GWAS, all metabolite measures were standardised and normalised using rank-based inverse normal transformation. Genetic association data for metabolites were retrieved using the MRC IEU UK Biobank GWAS pipeline.…”

Section: Methodsmentioning

confidence: 99%

Identifying metabolic features of colorectal cancer liability using Mendelian randomization

Bull

Hazelwood

Bell

et al. 2023

Preprint

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Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. To investigate whether changes in circulating metabolites characterise the early stages of colorectal cancer (CRC) development, we examined associations between a genetic risk score (GRS) associated with CRC liability (72 single nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N=6,221). Linear regression models were applied to examine associations between genetic liability to colorectal cancer and circulating metabolites measured in the same individuals at age 8, 16, 18 and 25 years. The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P<0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N=118,466, median age 58y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism, and suggest that fatty acids may play an important role in CRC development.

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Section: Methodsmentioning

confidence: 99%

Identifying metabolic features of colorectal cancer liability using Mendelian randomization

Bull

Hazelwood

Bell

et al. 2023

Preprint

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“…For the first GWAS, genetic association data were generated for up to 115,078 UK Biobank participants of European ancestry (54% females; age (years): mean = 56, SD: 8) for which metabolic traits were available using linear mixed model (LMM) association method as implemented in BOLT-LMM (v2.3) adjusting for genotype array, fasting time, and sex (hereafter 'UKBB GWAS'), as previously described [51][52][53][54]. For the second GWAS, genetic association data were generated for up to 24,925 individuals of European ancestry from the Kettunen et al meta-analysis including 10 studies adjusting for age, sex, time from last meal, and, where applicable, 10 first principal components [55] (hereafter 'Kettunen GWAS').…”

Section: Genetic Association Data For Metabolic Traitsmentioning

confidence: 99%

“…Genetic association data on birthweight were contributed by the EGG Consortium using the UK Biobank Resource and were downloaded from www.egg-consortium.org, accessed date 21 January 2021. Genetic association data on NMR metabolic traits from UK Biobank participants were generated as previously described under UK Biobank Project 30418 [52,53]. Genetic association data on NMR metabolic traits from Kettunen et al were extracted from the IEU Open GWAS platform [63]…”

Section: Supplementary Materialsmentioning

confidence: 99%

Using Mendelian Randomisation to Prioritise Candidate Maternal Metabolic Traits Influencing Offspring Birthweight

et al. 2022

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Marked physiological changes in pregnancy are essential to support foetal growth; however, evidence on the role of specific maternal metabolic traits from human studies is limited. We integrated Mendelian randomisation (MR) and metabolomics data to probe the effect of 46 maternal metabolic traits on offspring birthweight (N = 210,267). We implemented univariable two-sample MR (UVMR) to identify candidate metabolic traits affecting offspring birthweight. We then applied two-sample multivariable MR (MVMR) to jointly estimate the potential direct causal effect for each candidate maternal metabolic trait. In the main analyses, UVMR indicated that higher maternal glucose was related to higher offspring birthweight (0.328 SD difference in mean birthweight per 1 SD difference in glucose (95% CI: 0.104, 0.414)), as were maternal glutamine (0.089 (95% CI: 0.033, 0.144)) and alanine (0.137 (95% CI: 0.036, 0.239)). In additional analyses, UVMR estimates were broadly consistent when selecting instruments from an independent data source, albeit imprecise for glutamine and alanine, and were attenuated for alanine when using other UVMR methods. MVMR results supported independent effects of these metabolites, with effect estimates consistent with those seen with the UVMR results. Among the remaining 43 metabolic traits, UVMR estimates indicated a null effect for most lipid-related traits and a high degree of uncertainty for other amino acids and ketone bodies. Our findings suggest that maternal gestational glucose and glutamine are causally related to offspring birthweight.

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“…We used summary data from European population GWAS of GlycA, (55) MDD (56) and depressive symptom. (57) The GlycA GWAS was undertaken in UK Biobank data (UKBB), the MDD GWAS was from the Psychiatric Genomics Consortium (PGC) and the depressive symptoms GWAS from the Social Science Genetic Association Consortium (SSGAC).…”

Section: Univariable Bidirectional Two-sample Mendelian Randomisationmentioning

confidence: 99%

Glycoprotein Acetyls and Depression: testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses

Crick

Sanderson

Jones

et al. 2022

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Background: Inflammation is implicated in depression, but the issue of causality remains unclear. Objectives: To investigate potential causality and direction of effect between inflammation and depression. Methods: Using data from the ALSPAC birth cohort (n=4021), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression symptoms score and diagnosis, 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 (UKBB) (N=115,078); for depression from the Psychiatric Genomics Consortium and UKBB (N=500,199); and for depressive symptoms (N=161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted (IVW) 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: After adjusting for potential confounders we found no association between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression diagnosis (OR=1.18, 95% CI: 1.03-1.36). MR suggested no causal effect of GlycA on depression, but there was evidence of 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. Conclusion: We found no consistent evidence for an effect of the inflammatory marker GlycA on depression. There was some evidence that depression may increase GlycA, but this may be confounded/mediated by BMI.

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From menarche to menopause: the impact of reproductive factors on the metabolic profile of over 65,000 women

Cited by 7 publications

References 70 publications

Identifying metabolic features of colorectal cancer liability using Mendelian randomization

Identifying metabolic features of colorectal cancer liability using Mendelian randomization

Using Mendelian Randomisation to Prioritise Candidate Maternal Metabolic Traits Influencing Offspring Birthweight

Glycoprotein Acetyls and Depression: testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses

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