The effect of aspirin and eicosapentaenoic acid on urinary biomarkers of prostaglandin E2 synthesis and platelet activation in participants of the seAFOod polyp prevention trial.

Urinary prostaglandin (PG) E metabolite (PGE-M) and 11-dehydro (d)-thromboxane (TX) B2 are biomarkers of cyclooxygenase-dependent prostanoid synthesis. We investigated (1) the effect of aspirin 300 mg daily and eicosapentaenoic acid (EPA) 2000 mg daily, alone and in combination, on urinary biomarker levels and, (2) whether urinary biomarker levels predicted colorectal polyp risk, during participation in the seAFOod polyp prevention trial. Urinary PGE-M and 11-d-TXB2 were measured by liquid chromatography-tandem mass spectrometry. The relationship between urinary biomarker levels and colorectal polyp outcomes was investigated using negative binomial (polyp number) and logistic (% with one or more polyps) regression models. Despite wide temporal variability in PGE-M and 11-d-TXB2 levels within individuals, both aspirin and, to a lesser extent, EPA decreased levels of both biomarkers (74% [P ≤ .001] and 8% [P ≤ .05] reduction in median 11-d-TXB2 values, respectively). In the placebo group, a high (quartile [Q] 2-4) baseline 11-d-TXB2 level predicted increased polyp number (incidence rate ratio [IRR] [95% CI] 2.26 [1.11,4.58]) and risk (odds ratio [95% CI] 3.56 [1.09,11.63]). A low (Q1) on-treatment 11-d-TXB2 level predicted reduced colorectal polyp number compared to placebo (IRR 0.34 [0.12,0.93] for combination aspirin and EPA treatment) compared to high on-treatment 11-d-TXB2 values (0.61 [0.34,1.11]). Aspirin and EPA both inhibit PGE-M and 11-d-TXB2 synthesis in keeping with shared in vivo cyclooxygenase inhibition. Colorectal polyp risk and treatment response prediction by 11-d-TXB2 is consistent with a role for platelet activation during early colorectal carcinogenesis. The use of urinary 11-d-TXB2 measurement for a precision approach to colorectal cancer risk prediction and chemoprevention requires prospective evaluation.

Metabolomic epidemiology offers insights into disease aetiology.

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

Polymorphisms in Cyclooxygenase, Lipoxygenase, and TP53 Genes Predict Colorectal Polyp Risk Reduction by Aspirin in the seAFOod Polyp Prevention Trial.

Aspirin and eicosapentaenoic acid (EPA) reduce colorectal adenomatous polyp risk and affect synthesis of oxylipins including prostaglandin E2. We investigated whether 35 SNPs in oxylipin metabolism genes such as cyclooxygenase (PTGS) and lipoxygenase (ALOX), as well as 7 SNPs already associated with colorectal cancer risk reduction by aspirin (e.g., TP53; rs104522), modified the effects of aspirin and EPA on colorectal polyp recurrence in the randomized 2 × 2 factorial seAFOod trial. Treatment effects were reported as the incidence rate ratio (IRR) and 95% confidence interval (CI) by stratifying negative binomial and Poisson regression analyses of colorectal polyp risk on SNP genotype. Statistical significance was reported with adjustment for the false discovery rate as the P and q value. 542 (of 707) trial participants had both genotype and colonoscopy outcome data. Reduction in colorectal polyp risk in aspirin users compared with nonaspirin users was restricted to rs4837960 (PTGS1) common homozygotes [IRR, 0.69; 95% confidence interval (CI), 0.53-0.90); q = 0.06], rs2745557 (PTGS2) compound heterozygote-rare homozygotes [IRR, 0.60 (0.41-0.88); q = 0.06], rs7090328 (ALOX5) rare homozygotes [IRR 0.27 (0.11-0.64); q = 0.05], rs2073438 (ALOX12) common homozygotes [IRR, 0.57 (0.41-0.80); q = 0.05], and rs104522 (TP53) rare homozygotes [IRR, 0.37 (0.17-0.79); q = 0.06]. No modification of colorectal polyp risk in EPA users was observed. In conclusion, genetic variants relevant to the proposed mechanism of action on oxylipins are associated with differential colorectal polyp risk reduction by aspirin in individuals who develop multiple colorectal polyps. SNP genotypes should be considered during development of personalized, predictive models of colorectal cancer chemoprevention by aspirin. PREVENTION RELEVANCE: Single-nucleotide polymorphisms in genes controlling lipid mediator signaling may modify the colorectal polyp prevention activity of aspirin. Further investigation is required to determine whether testing for genetic variants can be used to target cancer chemoprevention by aspirin to those who will benefit most.

An epidemiological introduction to human metabolomic investigations.

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Metabolic drivers of dysglycemia in pregnancy: ethnic-specific GWAS of 146 metabolites and 1-sample Mendelian randomization analyses in a UK multi-ethnic birth cohort.

Introduction: Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required. Methods: To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted. Results: This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia. Discussion: In summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Non-Alcoholic Fatty Liver Disease and Vitamin D in the UK Biobank: A Two-Sample Bidirectional Mendelian Randomisation Study.

Evidence for a role for vitamin D in non-alcoholic fatty liver disease (NAFLD) pathogenesis is conflicting. As Mendelian randomisation (MR) avoids many limitations of conventional observational studies, this two-sample bidirectional MR analysis was conducted to determine the following: (i) whether genetically predicted 25-hydroxyvitamin D [25(OH)D] levels are a risk factor for NAFLD, and (ii) whether genetic risk for NAFLD influences 25(OH)D levels. Single-nucleotide polymorphisms (SNPs) associated with serum 25(OH)D levels were obtained from the European ancestry-derived SUNLIGHT consortium. SNPs associated with NAFLD or NASH (p-value < 1 × 10-5) were extracted from previous studies and supplemented by genome-wide association studies (GWASs) performed in the UK Biobank. These GWASs were done both without (primary analysis) and with (sensitivity analysis) the population-level exclusion of other liver diseases (e.g., alcoholic liver diseases, toxic liver diseases, viral hepatitis, etc.). Subsequently, MR analyses were performed to obtain effect estimates using inverse variance weighted (IVW) random effect models. Cochran's Q statistic, MR-Egger regression intercept, MR pleiotropy residual sum and outlier (MR-PRESSO) analyses were used to assess pleiotropy. No causal association of genetically predicted serum 25(OH)D (per standard deviation increase) with risk of NAFLD was identified in either the primary analysis: n = 2757 cases, n = 460,161 controls, odds ratio (95% confidence interval): 0.95 (0.76, -1.18), p = 0.614; or the sensitivity analysis. Reciprocally, no causal association was identified between the genetic risk of NAFLD and serum 25(OH)D levels, OR = 1.00 (0.99, 1.02, p = 0.665). In conclusion, this MR analysis found no evidence of an association between serum 25(OH)D levels and NAFLD in a large European cohort.

Unique Metabolic Profiles Associate with Gestational Diabetes and Ethnicity in Low- and High-Risk Women Living in the UK.

BACKGROUND: Gestational diabetes mellitus (GDM) is the most common global pregnancy complication; however, prevalence varies substantially between ethnicities, with South Asians (SAs) experiencing up to 3 times the risk of the disease compared with white Europeans (WEs). Factors driving this discrepancy are unclear, although the metabolome is of great interest as GDM is known to be characterized by metabolic dysregulation. OBJECTIVES: The primary aim was to characterize and compare the metabolic profiles of GDM in SA and WE women (at <28 wk of gestation) from the Born in Bradford (BIB) prospective birth cohort in the United Kingdom. METHODS: In total, 146 fasting serum metabolites, from 2,668 pregnant WE and 2,671 pregnant SA women (average BMI 26.2 kg/m2, average age 27.3 y) were analyzed using partial least squares discriminatory analyses to characterize GDM status. Linear associations between metabolite values and post-oral glucose tolerance test measures of dysglycemia (fasting glucose and 2 h postglucose) were also examined. RESULTS: Seven metabolites associated with GDM status in both ethnicities (variable importance in projection ≥1), whereas 6 additional metabolites associated with GDM only in WE women. Unique metabolic profiles were observed in healthy-weight women who later developed GDM, with distinct metabolite patterns identified by ethnicity and BMI status. Of the metabolite values analyzed in relation to dysglycemia, lactate, histidine, apolipoprotein A1, HDL cholesterol, and HDL2 cholesterol associated with decreased glucose concentration, whereas DHA and the diameter of very low-density lipoprotein particles (nm) associated with increased glucose concertation in WE women, and in SAs, albumin alone associated with decreased glucose concentration. CONCLUSIONS: This study shows that the metabolic risk profile for GDM differs between WE and SA women enrolled in BiB in the United Kingdom. This suggests that etiology of the disease differs between ethnic groups and that ethnic-appropriate prevention strategies may be beneficial.

Ethnic-specific associations between dietary consumption and gestational diabetes mellitus incidence: A meta-analysis.

Globally, one in seven pregnant women are diagnosed with gestational diabetes mellitus (GDM), conferring short- and long-term health risks to both mother and child. While dietary prevention strategies are common in clinical practice, their effectiveness in different ethnicities is uncertain. To better inform prevention strategies, here the effects of unhealthy and healthy diets on GDM risk within distinct ethnic or cultural populations and geographic regions were evaluated and summarised. Pubmed, Scopus, Cochrane and OVID were systematically searched to identify randomised controlled trials (RCTs) and observational studies that investigated diet and GDM. A grouped analysis of common 'healthy' and 'unhealthy' diets was performed first, before analysing individual dietary patterns (e.g., prudent, Mediterranean). Random effect models and dose response analyses were performed where possible. PROSPERO (CRD42019140873). Thirty-eight publications provided information on 5 population groups: white European (WE), Asian, Iranian, Mediterranean and Australian. No associations were identified between healthy diets and GDM incidence in RCTs in any population. However, when synthesizing observational studies, healthy diets reduced odds of GDM by 23% (95% CI: 0.70-0.89, p<0.001, I2 = 75%), while unhealthy diets increased odds of GDM by 61% (95% CI: 1.41-1.81, p<0.0001, I2 = 0%) in WE women. No evidence of consistent effects in other populations were observed, even when adequately powered. Diet consistently associated with GDM risk in WEs but not in other populations. Heterogenous use and reporting of ethnically and culturally appropriate diets and dietary assessment tools, particularly in RCTs, raises uncertainty regarding the lack of association found in non-WE populations. Future studies require the use of culturally appropriate tools to confidently evaluate dietary and metabolic mediators of GDM and inform culturally-specific dietary prevention strategies.

Investigation of the Causal Association between Long-Chain n-6 Polyunsaturated Fatty Acid Synthesis and the Risk of Type 2 Diabetes: A Mendelian Randomization Analysis.

BACKGROUND: Globally, 1 in 11 adults has diabetes mellitus, and most of these cases are type 2 diabetes (T2D). The risk of T2D is influenced by many factors, including diet. The synthesis of long-chain n-6 polyunsaturated fatty acids (LC n-6 PUFA) has been posited as a risk factor for T2D; however, its causal role is uncertain. AIM: To test the causal effect of LC n-6 PUFA synthesis on insulin resistance and transgenerational T2D risk in a large cohort of men and women. METHODS: Two-sample mendelian randomization (MR) was conducted to evaluate the effect of low or high levels of LC n-6 PUFA synthesis on glycemia and development of T2D in the UK Biobank (n = 463,010) and Meta-Analysis of Glucose- and Insulin-Related Traits Consortium (MAGIC; n = 5,130) cohorts. The increased likelihood of a predisposition to low or high LC n-6 PUFA synthesis and the risk of T2D was also investigated using the participants' siblings and parents. In MR-Base, 4 genetic variants associated with LC n-6 PUFA synthesis were found (p < 10-8). After pruning, 1 variant (rs174547) on the FADS1 gene was retained. RESULTS: Lower LC n-6 PUFA synthesis and abundance (per % unit decrease) are associated with small reductions in the insulin disposition index (-0.038 ± 0.012 mM-1; p = 0.002) within MAGIC. In the UK Biobank, we report negligible effects of low n-6 PUFA synthesis on the odds of T2D (OR <1%; p < 0.05). Additionally, reduced LC n-6 PUFA synthesis does not appear to be a contributor to familial T2D risk. No significant association was observed between LC n-6 PUFA synthesis and BMI. CONCLUSION: In a primarily white European population, LC n-6 PUFA synthesis is not a major contributor to T2D risk.