Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts.

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = - 0.98 standard deviations; 95% CI: - 1.11, - 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies.

BACKGROUND: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. METHODS: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. FINDINGS: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. CONCLUSIONS: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. FUNDING: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

The metabolic potential of inflammatory and insulinaemic dietary patterns and risk of type 2 diabetes.

AIMS/HYPOTHESIS: Diets with higher inflammatory and insulinaemic potential have been associated with an increased risk of type 2 diabetes. However, it remains unknown whether plasma metabolomic profiles related to proinflammatory/hyperinsulinaemic diets and to inflammatory/insulin biomarkers are associated with type 2 diabetes risk. METHODS: We analysed 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study to identify the plasma metabolome related to empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), four circulating inflammatory biomarkers and C-peptide. Dietary intakes were assessed using validated food frequency questionnaires. Plasma metabolomic profiling was conducted by LC-MS/MS. Metabolomic signatures were derived using elastic net regression. Multivariable Cox regression was used to examine associations of the metabolomic profiles with type 2 diabetes risk. RESULTS: We identified 27 metabolites commonly associated with both EDIP and inflammatory biomarker z score and 21 commonly associated with both EDIH and C-peptide. Higher metabolomic dietary inflammatory potential (MDIP), reflecting higher metabolic potential of both an inflammatory dietary pattern and circulating inflammatory biomarkers, was associated with higher type 2 diabetes risk. The HR comparing highest vs lowest quartiles of MDIP was 3.26 (95% CI 2.39, 4.44). We observed a strong positive association with type 2 diabetes risk for the metabolomic signature associated with EDIP-only (HR 3.75; 95% CI 2.71, 5.17) or inflammatory biomarkers-only (HR 4.07; 95% CI 2.91, 5.69). In addition, higher metabolomic dietary index for hyperinsulinaemia (MDIH), reflecting higher metabolic potential of both an insulinaemic dietary pattern and circulating C-peptide, was associated with greater type 2 diabetes risk (HR 3.00; 95% CI 2.22, 4.06); further associations with type 2 diabetes were HR 2.79 (95% CI 2.07, 3.76) for EDIH-only signature and HR 3.89 (95% CI 2.82, 5.35) for C-peptide-only signature. The diet scores were significantly associated with risk, although adjustment for the corresponding metabolomic signature scores attenuated the associations with type 2 diabetes, these remained significant. CONCLUSIONS/INTERPRETATION: The metabolomic signatures reflecting proinflammatory or hyperinsulinaemic diets and related biomarkers were positively associated with type 2 diabetes risk, supporting that these dietary patterns may influence type 2 diabetes risk via the regulation of metabolism.

A Plasma Metabolite Score Related to Psychological Distress and Diabetes Risk: A Nested Case-control Study in US Women.

CONTEXT: Psychological distress has been linked to diabetes risk. Few population-based, epidemiologic studies have investigated the potential molecular mechanisms (e.g., metabolic dysregulation) underlying this association. OBJECTIVE: To evaluate the association between a metabolomic signature for psychological distress and diabetes risk. METHODS: We conducted a nested case-control study of plasma metabolomics and diabetes risk in the Nurses' Health Study, including 728 women (mean age: 55.2 years) with incident diabetes and 728 matched controls. Blood samples were collected between 1989-1990 and incident diabetes was diagnosed between 1992-2008. Based on our prior work, we calculated a weighted plasma metabolite-based distress score (MDS) comprised of 19 metabolites. We used conditional logistic regression accounting for matching factors and other diabetes risk factors to estimate odds ratios (OR) and 95% CI for diabetes risk according to MDS. RESULTS: After adjusting for sociodemographic factors, family history of diabetes, and health behaviors, the OR (95% CI) for diabetes risk across quintiles of the MDS was 1.00 (reference) for Q1, 1.16 (0.77, 1.73) for Q2, 1.30 (0.88, 1.91) for Q3, 1.99 (1.36, 2.92) for Q4, and 2.47 (1.66, 3.67) for Q5. Each SD increase in MDS was associated with 36% higher diabetes risk (95% CI: 1.21, 1.54; p-trend<0.0001). This association was moderately attenuated after additional adjustment for BMI (comparable OR: 1.17; 95% CI: 1.02, 1.35; p-trend=0.02). The MDS explained 17.6% of the association between self-reported psychological distress (defined as presence of depression or anxiety symptoms) and diabetes risk (p=0.04). CONCLUSIONS: MDS was significantly associated with diabetes risk in women. These results suggest that differences in multiple lipid and amino acid metabolites may underlie the observed association between psychological distress and diabetes risk.

Dietary Inflammatory and Insulinemic Potentials, Plasma Metabolome and Risk of Colorectal Cancer.

The inflammatory and insulinemic potentials of diets have been associated with colorectal cancer risk. However, it is unknown whether the plasma metabolite profiles related to inflammatory diets, or to insulinemic diets, underlie this association. The aim of this study was to evaluate the association between metabolomic profile scores related to the food-based empirical dietary inflammatory patterns (EDIP), the empirical dietary index for hyperinsulinemia (EDIH), and plasma inflammation (CRP, IL-6, TNFα-R2, adiponectin) and insulin (C-peptide) biomarkers, and colorectal cancer risk. Elastic net regression was used to derive three metabolomic profile scores for each dietary pattern among 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study, and associations with CRC risk were examined using multivariable-adjusted logistic regression, in a case-control study of 524 matched pairs nested in both cohorts. Among 186 known metabolites, 27 were significantly associated with both the EDIP and inflammatory biomarkers, and 21 were significantly associated with both the EDIH and C-peptide. In men, odds ratios (ORs) of colorectal cancer, per 1 standard deviation (SD) increment in metabolomic score, were 1.91 (1.31-2.78) for the common EDIP and inflammatory-biomarker metabolome, 1.12 (0.78-1.60) for EDIP-only metabolome, and 1.65 (1.16-2.36) for the inflammatory-biomarkers-only metabolome. However, no association was found for EDIH-only, C-peptide-only, and the common metabolomic signatures in men. Moreover, the metabolomic signatures were not associated with colorectal cancer risk among women. Metabolomic profiles reflecting pro-inflammatory diets and inflammation biomarkers were associated with colorectal cancer risk in men, while no association was found in women. Larger studies are needed to confirm our findings.

Sex differences in the polygenic architecture of hearing problems in adults.

BACKGROUND: Hearing problems (HP) in adults are common and are associated with several comorbid conditions. Its prevalence increases with age, reflecting the cumulative effect of environmental factors and genetic predisposition. Although several risk loci have been already identified, HP biology and epidemiology are still insufficiently investigated by large-scale genetic studies. METHODS: Leveraging the UK Biobank, the Nurses' Health Studies (I and II), the Health Professionals Follow-up Study, and the Million Veteran Program, we conducted a comprehensive genome-wide investigation of HP in 748,668 adult participants (discovery N = 501,825; replication N = 226,043; cross-ancestry replication N = 20,800). We leveraged the GWAS findings to characterize HP polygenic architecture, exploring sex differences, polygenic risk across ancestries, tissue-specific transcriptomic regulation, cause-effect relationships with genetically correlated traits, and gene interactions with HP environmental risk factors. RESULTS: We identified 54 risk loci and demonstrated that HP polygenic risk is shared across ancestry groups. Our transcriptomic regulation analysis highlighted the potential role of the central nervous system in HP pathogenesis. The sex-stratified analyses showed several additional associations related to peripheral hormonally regulated tissues reflecting a potential role of estrogen in hearing function. This evidence was supported by the multivariate interaction analysis that showed how genes involved in brain development interact with sex, noise pollution, and tobacco smoking in relation to their HP associations. Additionally, the genetically informed causal inference analysis showed that HP is linked to many physical and mental health outcomes. CONCLUSIONS: The results provide many novel insights into the biology and epidemiology of HP in adults. Our sex-specific analyses and transcriptomic associations highlighted molecular pathways that may be targeted for drug development or repurposing. Additionally, the potential causal relationships identified may support novel preventive screening programs to identify individuals at risk.

Plasma metabolite profile for primary open-angle glaucoma in three US cohorts and the UK Biobank.

Glaucoma is a progressive optic neuropathy and a leading cause of irreversible blindness worldwide. Primary open-angle glaucoma is the most common form, and yet the etiology of this multifactorial disease is poorly understood. We aimed to identify plasma metabolites associated with the risk of developing POAG in a case-control study (599 cases and 599 matched controls) nested within the Nurses' Health Studies, and Health Professionals' Follow-Up Study. Plasma metabolites were measured with LC-MS/MS at the Broad Institute (Cambridge, MA, USA); 369 metabolites from 18 metabolite classes passed quality control analyses. For comparison, in a cross-sectional study in the UK Biobank, 168 metabolites were measured in plasma samples from 2,238 prevalent glaucoma cases and 44,723 controls using NMR spectroscopy (Nightingale, Finland; version 2020). Here we show higher levels of diglycerides and triglycerides are adversely associated with glaucoma in all four cohorts, suggesting that they play an important role in glaucoma pathogenesis.

The Role of Statins in the Prevention of Ovarian and Endometrial Cancers.

Ovarian and endometrial cancers are the most common gynecologic malignancies and emerging evidence suggests that lipid metabolism and subsequent inflammation are important etiologic factors for both tumors. Statins (HMG-CoA reductase inhibitors) are the most widely prescribed lipid-lowering drugs in the United States and are used by 25% of adults aged 40+ years. In addition to their cardio-protective actions, statins have anti-inflammatory effects and have demonstrated antiproliferative and apoptotic properties in cancer cell lines, supporting a potential role in cancer prevention. To appropriately quantify potential public health impact of statin use for cancer prevention, there is a great need to understand the potential risk reduction among individuals at a higher risk of gynecologic cancers, the group that will likely need to be targeted to effectively balance risk/benefit of medications repurposed for cancer prevention. In this commentary, we focus on summarizing emerging evidence suggesting that the anti-inflammatory and lipid-lowering mechanisms of statins may provide important cancer-preventive benefits for gynecologic cancers as well as outline important unanswered questions and future research directions.

Association of Plasma Metabolomic Biomarkers With Persistent Tinnitus: A Population-Based Case-Control Study.

Importance: Persistent tinnitus is common, disabling, and difficult to treat. Objective: To evaluate the association between circulating metabolites and persistent tinnitus. Design, Setting, and Participants: This was a population-based case-control study of 6477 women who were participants in the Nurses' Health Study (NHS) and NHS II with metabolomic profiles and tinnitus data. Information on tinnitus onset and frequency was collected on biennial questionnaires (2009-2017). For cases, metabolomic profiles were measured (2015-2021) in blood samples collected after the date of the participant's first report of persistent tinnitus (NHS, 1989-1999 and 2010-2012; NHS II, 1996-1999). Data analyses were performed from January 24, 2022, to January 14, 2023. Exposures: In total, 466 plasma metabolites from 488 cases of persistent tinnitus and 5989 controls were profiled using 3 complementary liquid chromatography tandem mass spectrometry approaches. Main Outcomes and Measures: Logistic regression was used to estimate odds ratios (ORs) of persistent tinnitus (per 1 SD increase in metabolite values) and 95% CIs for each individual metabolite. Metabolite set enrichment analysis was used to identify metabolite classes enriched for associations with tinnitus. Results: Of the 6477 study participants (mean [SD] age, 52 [9] years; 6477 [100%] female; 6121 [95%] White individuals) who were registered nurses, 488 reported experiencing daily persistent (≥5 minutes) tinnitus. Compared with participants with no tinnitus (5989 controls), those with persistent tinnitus were slightly older (53.0 vs 51.8 years) and more likely to be postmenopausal, using oral postmenopausal hormone therapy, and have type 2 diabetes, hypertension, and/or hearing loss at baseline. Compared with controls, homocitrulline (OR, 1.32; (95% CI, 1.16-1.50); C38:6 phosphatidylethanolamine (PE; OR, 1.24; 95% CIs, 1.12-1.38), C52:6 triglyceride (TAG; OR, 1.22; 95% CIs, 1.10-1.36), C36:4 PE (OR, 1.22; 95% CIs, 1.10-1.35), C40:6 PE (OR, 1.22; 95% CIs, 1.09-1.35), and C56:7 TAG (OR, 1.21; 95% CIs, 1.09-1.34) were positively associated, whereas α-keto-ß-methylvalerate (OR, 0.68; 95% CIs, 0.56-0.82) and levulinate (OR, 0.60; 95% CIs, 0.46-0.79) were inversely associated with persistent tinnitus. Among metabolite classes, TAGs (normalized enrichment score [NES], 2.68), PEs (NES, 2.48), and diglycerides (NES, 1.65) were positively associated, whereas phosphatidylcholine plasmalogens (NES, -1.91), lysophosphatidylcholines (NES, -2.23), and cholesteryl esters (NES,-2.31) were inversely associated with persistent tinnitus. Conclusions and Relevance: This population-based case-control study of metabolomic profiles and tinnitus identified novel plasma metabolites and metabolite classes that were significantly associated with persistent tinnitus, suggesting that metabolomic studies may help improve understanding of tinnitus pathophysiology and identify therapeutic targets for this challenging disorder.

Benchmarking omics-based prediction of asthma development in children.

BACKGROUND: Asthma is a heterogeneous disease with high morbidity. Advancement in high-throughput multi-omics approaches has enabled the collection of molecular assessments at different layers, providing a complementary perspective of complex diseases. Numerous computational methods have been developed for the omics-based patient classification or disease outcome prediction. Yet, a systematic benchmarking of those methods using various combinations of omics data for the prediction of asthma development is still lacking. OBJECTIVE: We aimed to investigate the computational methods in disease status prediction using multi-omics data. METHOD: We systematically benchmarked 18 computational methods using all the 63 combinations of six omics data (GWAS, miRNA, mRNA, microbiome, metabolome, DNA methylation) collected in The Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohort. We evaluated each method using standard performance metrics for each of the 63 omics combinations. RESULTS: Our results indicate that overall Logistic Regression, Multi-Layer Perceptron, and MOGONET display superior performance, and the combination of transcriptional, genomic and microbiome data achieves the best prediction. Moreover, we find that including the clinical data can further improve the prediction performance for some but not all the omics combinations. CONCLUSIONS: Specific omics combinations can reach the optimal prediction of asthma development in children. And certain computational methods showed superior performance than other methods.

Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women.

Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts.

BACKGROUND: Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS: Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS: Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS: Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses' Health Studies.

BACKGROUND: Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear. METHODS: In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis. RESULTS: Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01). CONCLUSIONS: Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer.

Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms.

Limited data exist on the performance of high-throughput proteomics profiling in epidemiological settings, including the impact of specimen collection and within-person variability over time. Thus, the Olink (972 proteins) and SOMAscan7Kv4.1 (7322 proteoforms of 6596 proteins) assays were utilized to measure protein concentrations in archived plasma samples from the Nurses' Health Studies and Health Professionals Follow-Up Study. Spearman's correlation coefficients (r) and intraclass correlation coefficients (ICCs) were used to assess agreement between (1) 42 triplicate samples processed immediately, 24-h or 48-h after blood collection from 14 participants; and (2) 80 plasma samples from 40 participants collected 1-year apart. When comparing samples processed immediately, 24-h, and 48-h later, 55% of assays had an ICC/r ≥ 0.75 and 87% had an ICC/r ≥ 0.40 in Olink compared to 44% with an ICC/r ≥ 0.75 and 72% with an ICC/r ≥ 0.40 in SOMAscan7K. For both platforms, >90% of the assays were stable (ICC/r ≥ 0.40) in samples collected 1-year apart. Among 817 proteins measured with both platforms, Spearman's correlations were high (r > 0.75) for 14.7% and poor (r < 0.40) for 44.8% of proteins. High-throughput proteomics profiling demonstrated reproducibility in archived plasma samples and stability after delayed processing in epidemiological studies, yet correlations between proteins measured with the Olink and SOMAscan7K platforms were highly variable.

Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women.

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses' Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups.

Presurgical blood metabolites and risk of postsurgical pelvic pain in young patients with endometriosis.

OBJECTIVE: To identify metabolites in presurgical blood associated with risk of persistent postsurgical pelvic pain 1 year after endometriosis surgery in adolescent and young adult patients. DESIGN: Prospective observational study within the Women's Health Study: From Adolescence to Adulthood, a US-based longitudinal cohort of adolescents and women enrolled from 2012-2018. SETTING: Two tertiary care hospitals. PATIENT(S): Laparoscopically confirmed endometriosis patients (n = 180) with blood collected before their endometriosis surgery. Of these, 77 patients additionally provided blood samples 5 weeks to 6 months after their surgery. We measured plasma metabolites using liquid chromatography tandem mass spectrometry, and a total of 390 known metabolites were included in our analysis. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Persistent postsurgical pelvic pain, defined as severe, life-impacting pelvic pain 1 year after endometriosis surgery. RESULT(S): Most patients (>95%) were at stage I/II of the revised American Society for Reproductive Medicine classification. Their average age at diagnosis was 18.7 years, with 36% reporting persistent postsurgical pelvic pain. Of the 21 metabolites in presurgical blood that were associated with risk of persistent postsurgical pelvic pain, 19 metabolites, which were mainly lipid metabolites, were associated with increased risk. Only 2 metabolites-pregnenolone sulfate (odds ratio = 0.64, 95% confidence interval = 0.44-0.92) and fucose (odds ratio = 0.69, 95% confidence interval = 0.47-0.97)-were associated with decreased risk. Metabolite set enrichment analysis revealed that higher levels of lysophosphatidylethanolamines (false discovery rate = 0.01) and lysophosphatidylcholines (false discovery rate = 0.01) in presurgical blood were associated with increased risk of persistent postsurgical pelvic pain. CONCLUSION(S): Our results suggest that dysregulation of multiple groups of lipid metabolites may play a role in the persistence of pelvic pain postsurgery among young endometriosis patients.

Plasma Metabolomic Signature of Early Abuse in Middle-Aged Women.

OBJECTIVE: Metabolomic profiling may provide insights into biological mechanisms underlying the strong epidemiologic links observed between early abuse and cardiometabolic disorders in later life. METHODS: We examined the associations between early abuse and midlife plasma metabolites in two nonoverlapping subsamples from the Nurses' Health Study II, comprising 803 (mean age = 40 years) and 211 women (mean age = 61 years). Liquid chromatography-tandem mass spectrometry assays were used to measure metabolomic profiles, with 283 metabolites consistently measured in both subsamples. Physical and sexual abuse before age 18 years was retrospectively assessed by validated questions integrating type/frequency of abuse. Analyses were conducted in each sample and pooled using meta-analysis, with multiple testing adjustment using the q value approach for controlling the positive false discovery rate. RESULTS: After adjusting for age, race, menopausal status, body size at age 5 years, and childhood socioeconomic indicators, more severe early abuse was consistently associated with five metabolites at midlife (q value < 0.20 in both samples), including lower levels of serotonin and C38:3 phosphatidylethanolamine plasmalogen and higher levels of alanine, proline, and C40:6 phosphatidylethanolamine. Other metabolites potentially associated with early abuse (q value < 0.05 in the meta-analysis) included triglycerides, phosphatidylcholine plasmalogens, bile acids, tyrosine, glutamate, and cotinine. The association between early abuse and midlife metabolomic profiles was partly mediated by adulthood body mass index (32% mediated) and psychosocial distress (13%-26% mediated), but not by other life-style factors. CONCLUSIONS: Early abuse was associated with distinct metabolomic profiles of multiple amino acids and lipids in middle-aged women. Body mass index and psychosocial factors in adulthood may be important intermediates for the observed association.

Plasma Metabolite Profiles of Red Meat, Poultry, and Fish Consumption, and Their Associations with Colorectal Cancer Risk.

BACKGROUND: Red and processed meat consumption has been consistently associated with increased risk of colorectal cancer (CRC), but the association for fish intake is unclear. Evidence using objective dietary assessment approaches to evaluate these associations is sparse. OBJECTIVES: We aim to investigate the plasma metabolite profiles related to red meat, poultry, and fish consumption and examine their associations with CRC risk. METHODS: We measured plasma metabolites among 5269 participants from the Nurses' Health Study (NHS), NHSII, and Health Professionals Follow-Up study (HPFS). We calculated partial Spearman correlations between each metabolite and self-reported intake of seven red meat, poultry, and fish groups. Metabolite profile scores correlated to self-reported dietary intakes were developed using elastic net regression. Associations between self-reported intakes, metabolite profile scores, and subsequent CRC risk were further evaluated using conditional logistic regression among 559 matched (1:1) case-control pairs in NHS/HPFS and replicated among 266 pairs in Women's Health Study. RESULTS: Plasma metabolites, especially highly unsaturated lipids, were differentially associated with red meat and fish groups. Metabolite profile scores for each food group were significantly correlated with the corresponding self-reported dietary intake. A higher dietary intake of processed red meat was associated with a higher risk of CRC (pooled OR per 1 SD, 1.15; 95% CI: 1.03, 1.29). In contrast, higher metabolite profile scores for all fish groups, not dietary intakes, were consistently associated with a lower CRC risk: the pooled OR per 1 SD was 0.86 (95% CI: 0.78, 0.96) for total fish, 0.86 (95% CI: 0.77, 0.96) for dark meat fish, and 0.87 (95% CI: 0.78, 0.97) for canned tuna fish. No significant associations were found for other food groups. CONCLUSIONS: Red meat and fish intake exhibited systematically different plasma metabolite profiles. Plasma metabolite profile of fish intake was inversely associated with CRC risk.

Plasma Metabolomics and Breast Cancer Risk over 20 Years of Follow-up among Postmenopausal Women in the Nurses' Health Study.

BACKGROUND: Metabolite profiles provide insight into biologic mechanisms contributing to breast cancer development. We explored the association between prediagnostic plasma metabolites (N = 307) and invasive breast cancer among postmenopausal women in a nested case-control study within the Nurses' Health Study (N = 1,531 matched pairs). METHODS: Plasma metabolites were profiled via LC/MS-MS using samples taken ≥10 years (distant, N = 939 cases) and <10 years (proximate, N = 592 cases) before diagnosis. Multivariable conditional logistic regression was used to estimate ORs and 95% confidence intervals (CI) comparing the 90th to 10th percentile of individual metabolite level, using the number of effective tests (NEF) to account for testing multiple correlated hypotheses. Associations of metabolite groups with breast cancer were evaluated using metabolite set enrichment analysis (MSEA) and weighted gene coexpression network analysis (WGCNA), with adjustment for the FDR. RESULTS: No individual metabolites were significantly associated with breast cancer risk. MSEA showed negative enrichment of cholesteryl esters at the distant timepoint [normalized enrichment score (NES) = -2.26; Padj = 0.02]. Positive enrichment of triacylglycerols (TAG) with <3 double bonds was observed at both timepoints. TAGs with ≥3 double bonds were inversely associated with breast cancer at the proximate timepoint (NES = -2.91, Padj = 0.03). CONCLUSIONS: Cholesteryl esters measured earlier in disease etiology were inversely associated with breast cancer. TAGs with many double bonds measured closer to diagnosis were inversely associated with breast cancer risk. IMPACT: The discovered associations between metabolite subclasses and breast cancer risk can expand our understanding of biochemical processes involved in cancer etiology.

Plasma metabolomic profiles for colorectal cancer precursors in women.

How metabolome changes influence the early process of colorectal cancer (CRC) development remains unknown. We conducted a 1:2 matched nested case-control study to examine the associations of pre-diagnostic plasma metabolome (profiled using LC-MS) with risk of CRC precursors, including conventional adenomas (n = 586 vs. 1141) and serrated polyps (n = 509 vs. 993), in the Nurses' Health Study (NHS) and NHSII. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). We used the permutation-based Westfall and Young approach to account for multiple testing. Subgroup analyses were performed for advanced conventional adenomas (defined as at least one adenoma of ≥ 10 mm or with high-grade dysplasia, or tubulovillous or villous histology) and high-risk serrated polyps that were located in the proximal colon or with size of ≥ 10 mm. After multiple testing correction, among 207 metabolites, higher levels of C36:3 phosphatidylcholine (PC) plasmalogen were associated with lower risk of conventional adenomas, with the OR (95% CI) comparing the 90th to the 10th percentile of 0.62 (0.48-0.81); C54:8 triglyceride (TAG) was associated with higher risk of serrated polyps (OR = 1.79, 95% CI: 1.31-2.43), and phenylacetylglutamine (PAG) was associated with lower risk (OR = 0.57, 95% CI:0.43-0.77). PAG was also inversely associated with advanced adenomas (OR = 0.57, 95% CI: 0.36-0.89) and high-risk serrated polyps (OR = 0.54, 95% CI: 0.32-0.89), although the multiple testing-corrected p value was > 0.05. Our findings suggest potential roles of lipid metabolism and phenylacetylglutamine, a microbial metabolite, in the early stage of colorectal carcinogenesis, particularly for the serrated pathway.