Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites

Whole-exome sequencing identifies rare genetic variants associated with human plasma metabolites

Metabolite levels measured in the human population are endophenotypes for biological processes. We combined sequencing data for 3,924 (whole-exome sequencing, WES, discovery) and 2,805 (whole-genome sequencing, WGS, replication) donors from a prospective cohort of blood donors in England. We used multiple approaches to select and aggregate rare genetic variants (minor allele frequency [MAF] < 0.1%) in protein-coding regions and tested their associations with 995 metabolites measured in plasma by using ultra-high-performance liquid chromatography-tandem mass spectrometry. We identified 40 novel associations implicating rare coding variants (27 genes and 38 metabolites), of which 28 (15 genes and 28 metabolites) were replicated. We developed algorithms to prioritize putative driver variants at each locus and used mediation and Mendelian randomization analyses to test directionality at associations of metabolite and protein levels at the ACY1 locus. Overall, 66% of reported associations implicate gene targets of approved drugs or bioactive drug-like compounds, contributing to drug targets' validating efforts.

Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies

OBJECTIVE

Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.

METHOD

We analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites.

RESULTS

Tryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with T2D risk. We identified multiple host genetic variants, dietary factors, gut bacteria and their potential interplay associated with these T2D-relaetd metabolites. Intakes of fibre-rich foods, but not protein/tryptophan-rich foods, were the dietary factors most strongly associated with tryptophan metabolites. The fibre-indolepropionate association was partially explained by indolepropionate-associated gut bacteria, mostly fibre-using Firmicutes. We identified a novel association between a host functional LCT variant (determining lactase persistence) and serum indolepropionate, which might be related to a host gene-diet interaction on gut Bifidobacterium, a probiotic bacterium significantly associated with indolepropionate independent of other fibre-related bacteria. Higher milk intake was associated with higher levels of gut Bifidobacterium and serum indolepropionate only among genetically lactase non-persistent individuals.

CONCLUSION

Higher milk intake among lactase non-persistent individuals, and higher fibre intake were associated with a favourable profile of circulating tryptophan metabolites for T2D, potentially through the host-microbial cross-talk shifting tryptophan metabolism toward gut microbial indolepropionate production.

Ratios of Acetaminophen Metabolites Identify New Loci of Pharmacogenetic Relevance in a Genome-Wide Association Study

Genome-wide association studies (GWAS) with non-targeted metabolomics have identified many genetic loci of biomedical interest. However, metabolites with a high degree of missingness, such as drug metabolites and xenobiotics, are often excluded from such studies due to a lack of statistical power and higher uncertainty in their quantification. Here we propose ratios between related drug metabolites as GWAS phenotypes that can drastically increase power to detect genetic associations between pairs of biochemically related molecules. As a proof-of-concept we conducted a GWAS with 520 individuals from the Qatar Biobank for who at least five of the nine available acetaminophen metabolites have been detected. We identified compelling evidence for genetic variance in acetaminophen glucuronidation and methylation by UGT2A15 and COMT, respectively. Based on the metabolite ratio association profiles of these two loci we hypothesized the chemical structure of one of their products or substrates as being 3-methoxyacetaminophen, which we then confirmed experimentally. Taken together, our study suggests a novel approach to analyze metabolites with a high degree of missingness in a GWAS setting with ratios, and it also demonstrates how pharmacological pathways can be mapped out using non-targeted metabolomics measurements in large population-based studies.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

Effects of Acute and Chronic Resistance Exercise on the Skeletal Muscle Metabolome

Resistance training promotes metabolic health and stimulates muscle hypertrophy, but the precise routes by which resistance exercise (RE) conveys these health benefits are largely unknown.

AIM

To investigate how acute RE affects human skeletal muscle metabolism.

METHODS

We collected vastus lateralis biopsies from six healthy male untrained volunteers at rest, before the first of 13 RE training sessions, and 45 min after the first and last bouts of RE. Biopsies were analysed using untargeted mass spectrometry-based metabolomics.

RESULTS

We measured 617 metabolites covering a broad range of metabolic pathways. In the untrained state RE altered 33 metabolites, including increased 3-methylhistidine and N-lactoylvaline, suggesting increased protein breakdown, as well as metabolites linked to ATP (xanthosine) and NAD (N1-methyl-2-pyridone-5-carboxamide) metabolism; the bile acid chenodeoxycholate also increased in response to RE in muscle opposing previous findings in blood. Resistance training led to muscle hypertrophy, with slow type I and fast/intermediate type II muscle fibre diameter increasing by 10.7% and 10.4%, respectively. Comparison of post-exercise metabolite levels between trained and untrained state revealed alterations of 46 metabolites, including decreased N-acetylated ketogenic amino acids and increased beta-citrylglutamate which might support growth. Only five of the metabolites that changed after acute exercise in the untrained state were altered after chronic training, indicating that training induces multiple metabolic changes not directly related to the acute exercise response.

CONCLUSION

The human skeletal muscle metabolome is sensitive towards acute RE in the trained and untrained states and reflects a broad range of adaptive processes in response to repeated stimulation.

Bacille Calmette-Guérin vaccine reprograms human neonatal lipid metabolism in vivo and in vitro

Vaccines have generally been developed with limited insight into their molecular impact. While systems vaccinology enables characterization of mechanisms of action, these tools have yet to be applied to infants, who are at high risk of infection and receive the most vaccines. Bacille Calmette-Guérin (BCG) protects infants against disseminated tuberculosis (TB) and TB-unrelated infections via incompletely understood mechanisms. We employ mass-spectrometry-based metabolomics of blood plasma to profile BCG-induced infant responses in Guinea-Bissau in vivo and the US in vitro. BCG-induced lysophosphatidylcholines (LPCs) correlate with both TLR-agonist- and purified protein derivative (PPD, mycobacterial antigen)-induced blood cytokine production in vitro, raising the possibility that LPCs contribute to BCG immunogenicity. Analysis of an independent newborn cohort from The Gambia demonstrates shared vaccine-induced metabolites, such as phospholipids and sphingolipids. BCG-induced changes to the plasma lipidome and LPCs may contribute to its immunogenicity and inform the development of early life vaccines.

Bibliometric and Visual Analysis on Metabolomics in Coronary Artery Disease Research

Background

Metabolomics has immense research value in coronary artery disease and has drawn increasing attention over the past decades. Many articles have been published in this field, which may challenge researchers aiming to investigate all the available information. However, bibliometrics can provide deep insights into this research field.

Objective

We aimed to qualitatively and quantitatively study metabolomics and coronary artery disease research, visually analyse the development status, trends, research hotspots, and frontiers of this field, and provide a reference for research on coronary artery disease.

Methods

Articles were acquired from the Web of Science Core Collection. VOSviewer and CiteSpace software were used to analyse publication growth, country/region, institution, journal distribution, author, reference, and keywords, and detected the keywords with strong citation burstness to identify emerging topics.

Results

A total of 1121 references were obtained, and the annual number of publications increased over the past 16 years. Metabolomics research has shown a gradual upward trend in coronary artery disease. The United States of America and China ranked at the top in terms of percentage of articles. The institution with the highest number of research publications in this field was Harvard University, followed by the University of California System and Brigham Women's Hospital. The most frequently cited authors included Hazen SL, Tang WH, and Wang ZN. Ala-Korpela M was the most productive author, followed by Clish CB and Adamski J. The journal with the most publications in this field was Scientific Reports, followed by PLoS One and the Journal of Proteome Research. The keywords used at a high frequency were "risk," "biomarkers," "insulin resistance," and "atherosclerosis." Burst detection analysis of top keywords showed that "microbiota," "tryptophan," and "diabetes" are the current research frontiers in this field.

Conclusion

This study provides useful information for acquiring knowledge on metabolomics and coronary artery diseases. Metabolomics research has shown a gradual upward trend in coronary artery disease studies over the past 16 years. Research on tryptophan metabolism regulated by intestinal flora will become an emerging academic trend in this field, which can offer guidance for more extensive and in-depth studies in the future.

Independent and Interactive Effects of Genetic Background and Sex on Tissue Metabolomes of Adipose, Skeletal Muscle, and Liver in Mice

Genetics play an important role in the development of metabolic diseases. However, the relative influence of genetic variation on metabolism is not well defined, particularly in tissues, where metabolic dysfunction that leads to disease occurs. We used inbred strains of laboratory mice to evaluate the impact of genetic variation on the metabolomes of tissues that play central roles in metabolic diseases. We chose a set of four common inbred strains that have different levels of susceptibility to obesity, insulin resistance, and other common metabolic disorders. At the ages used, and under standard husbandry conditions, these lines are not overtly diseased. Using global metabolomics profiling, we evaluated water-soluble metabolites in liver, skeletal muscle, and adipose from A/J, C57BL/6J, FVB/NJ, and NOD/ShiLtJ mice fed a standard mouse chow diet. We included both males and females to assess the relative influence of strain, sex, and strain-by-sex interactions on metabolomes. The mice were also phenotyped for systems level traits related to metabolism and energy expenditure. Strain explained more variation in the metabolite profile than did sex or its interaction with strain across each of the tissues, especially in liver. Purine and pyrimidine metabolism and pathways related to amino acid metabolism were identified as pathways that discriminated strains across all three tissues. Based on the results from ANOVA, sex and sex-by-strain interaction had modest influence on metabolomes relative to strain, suggesting that the tissue metabolome remains largely stable across sexes consuming the same diet. Our data indicate that genetic variation exerts a fundamental influence on tissue metabolism.

Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.

Effects of glutamate and aspartate on prostate cancer and breast cancer: a Mendelian randomization study

Background

Respectively, prostate cancer (PCa) and breast cancer (BC) are the second most and most commonly diagnosed cancer in men and women, and they account for a majority of cancer-related deaths world-wide. Cancer cells typically exhibit much-facilitated growth that necessitates upregulated glycolysis and augmented amino acid metabolism, that of glutamine and aspartate in particular, which is tightly coupled with an increased flux of the tricarboxylic acid (TCA) cycle. Epidemiological studies have exploited metabolomics to explore the etiology and found potentially effective biomarkers for early detection or progression of prostate and breast cancers. However, large randomized controlled trials (RCTs) to establish causal associations between amino acid metabolism and prostate and breast cancers have not been reported.

Objective

Utilizing two-sample Mendelian randomization (MR), we aimed to estimate how genetically predicted glutamate and aspartate levels could impact upon prostate and breast cancers development.

Methods

Single nucleotide polymorphisms (SNPs) as instrumental variables (IVs), associated with the serum levels of glutamate and aspartate were extracted from the publicly available genome-wide association studies (GWASs), which were conducted to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults; and the glutamate and aspartate we have chosen were two of 644 metabolites. The summary statistics for the largest and latest GWAS datasets for prostate cancer (61,106 controls and 79,148 cases) were from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium, and datasets for breast cancer (113,789 controls and 133,384 cases) were from Breast Cancer Association Consortium (BCAC). The study was performed through two-sample MR method.

Results

Causal estimates were expressed as odds ratios (OR) and 95% confidence interval (CI) per standard deviation increment in serum level of aspartate or glutamate. Aspartate was positively associated with prostate cancer (Effect = 1.043; 95% confidence interval, 1.003 to 1.084; P = 0.034) and breast cancer (Effect = 1.033; 95% confidence interval, 1.004 to 1.063; P = 0.028); however, glutamate was neither associated with prostate cancer nor with breast cancer. The potential causal associations were robust to the sensitivity analysis.

Conclusions

Our study found that the level of serum aspartate could serve as a risk factor that contributed to the development of prostate and breast cancers. Efforts on a detailed description of the underlying biochemical mechanisms would be extremely valuable in early assessment and/or diagnosis, and strategizing clinical intervention, of both cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08442-7.

Gut microbiota drives age-related oxidative stress and mitochondrial damage in microglia via the metabolite N6-carboxymethyllysine

Microglial function declines during aging. The interaction of microglia with the gut microbiota has been well characterized during development and adulthood but not in aging. Here, we compared microglial transcriptomes from young-adult and aged mice housed under germ-free and specific pathogen-free conditions and found that the microbiota influenced aging associated-changes in microglial gene expression. The absence of gut microbiota diminished oxidative stress and ameliorated mitochondrial dysfunction in microglia from the brains of aged mice. Unbiased metabolomic analyses of serum and brain tissue revealed the accumulation of N⁶-carboxymethyllysine (CML) in the microglia of the aging brain. CML mediated a burst of reactive oxygen species and impeded mitochondrial activity and ATP reservoirs in microglia. We validated the age-dependent rise in CML levels in the sera and brains of humans. Finally, a microbiota-dependent increase in intestinal permeability in aged mice mediated the elevated levels of CML. This study adds insight into how specific features of microglia from aged mice are regulated by the gut microbiota.

Integrative Analysis of the Inflammatory Bowel Disease Serum Metabolome Improves Our Understanding of Genetic Etiology and Points to Novel Putative Therapeutic Targets

BACKGROUND & AIMS

Polygenic and environmental factors are underlying causes of inflammatory bowel disease (IBD). We hypothesized that integration of the genetic loci controlling a metabolite's abundance, with known IBD genetic susceptibility loci, may help resolve metabolic drivers of IBD.

METHODS

We measured the levels of 1300 metabolites in the serum of 484 patients with ulcerative colitis (UC) and 464 patients with Crohn's disease (CD) and 365 controls. Differential metabolite abundance was determined for disease status, subtype, clinical and endoscopic disease activity, as well as IBD phenotype including disease behavior, location, and extent. To inform on the genetic basis underlying metabolic diversity, we integrated metabolite and genomic data. Genetic colocalization and Mendelian randomization analyses were performed using known IBD risk loci to explore whether any metabolite was causally associated with IBD.

RESULTS

We found 173 genetically controlled metabolites (metabolite quantitative trait loci, 9 novel) within 63 non-overlapping loci (7 novel). Furthermore, several metabolites significantly associated with IBD disease status and activity as defined using clinical and endoscopic indexes. This constitutes a resource for biomarker discovery and IBD biology insights. Using this resource, we show that a novel metabolite quantitative trait locus for serum butyrate levels containing ACADS was not supported as causal for IBD; replicate the association of serum omega-6 containing lipids with the fatty acid desaturase 1/2 locus and identify these metabolites as causal for CD through Mendelian randomization; and validate a novel association of serum plasmalogen and TMEM229B, which was predicted as causal for CD.

CONCLUSIONS

An exploratory analysis combining genetics and unbiased serum metabolome surveys can reveal novel biomarkers of disease activity and potential mediators of pathology in IBD.

Dietary-Derived Essential Nutrients and Amyotrophic Lateral Sclerosis: A Two-Sample Mendelian Randomization Study

Previous studies have suggested a close but inconsistent relationship between essential nutrients and the risk of amyotrophic lateral sclerosis (ALS), and whether this association is causal remains unknown. We aimed to investigate the potential causal relation between essential nutrients (essential amino acids, essential fatty acids, essential minerals, and essential vitamins) and the risk of ALS using Mendelian randomization (MR) analysis. Large-scale European-based genome-wide association studies' (GWASs) summary data related to ALS (assembling 27,205 ALS patients and 110,881 controls) and essential nutrient concentrations were separately obtained. MR analysis was performed using the inverse variance-weighted (IVW) method, and sensitivity analysis was conducted by the weighted median method, simple median method, MR-Egger method and MR-PRESSO method. We found a causal association between genetically predicted linoleic acid (LA) and the risk of ALS (OR: 1.066; 95% CI: 1.011-1.125; p = 0.019). An inverse association with ALS risk was noted for vitamin D (OR: 0.899; 95% CI: 0.819-0.987; p = 0.025) and for vitamin E (OR: 0.461; 95% CI: 0.340-0.626; p = 6.25 × 10^-7). The sensitivity analyses illustrated similar trends. No causal effect was observed between essential amino acids and minerals on ALS. Our study profiled the effects of diet-derived circulating nutrients on the risk of ALS and demonstrated that vitamin D and vitamin E are protective against the risk of ALS, and LA is a suggested risk factor for ALS.

Microbiome and metabolome features of the cardiometabolic disease spectrum

Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

By studying individuals along a spectrum of cardiometabolic disease and adjusting for effects of lifestyle and medication, this investigation identifies alterations of the metabolome and microbiome from dysmetabolic conditions, such as obesity and type 2 diabetes, to ischemic heart disease.

Body mass index mediates the effect of the DASH diet on hypertension: Common metabolites underlying the association

BACKGROUND

The Dietary Approaches to Stop Hypertension (DASH) diet is beneficial in reducing blood pressure; however, this may be a consequence of concurrent weight reduction. In the present study, we investigated whether body mass index (BMI) mediates the association between the DASH diet and hypertension and investigate common metabolic pathways.

METHODS

We included 2424 females from the cross-sectional TwinsUK cohort, with blood pressure, BMI and dietary intake measured within 1.01 (SD = 0.68) years and serum metabolomics profiling (591 metabolites). We constructed a mediation model to test the mediation effects of BMI on the total effect of the DASH diet on hypertension. To identify a metabolite panel associated with the DASH diet and BMI, we built random forest models for each trait, and selected the common metabolic contributors using five-fold cross-validation error.

RESULTS

We found that BMI fully mediates the association between the DASH diet and hypertension, explaining 39.1% of the variance in hypertension. We then identified a panel of six common metabolites predicting both the DASH diet and BMI with opposing effects. Interestingly, at the univariate level, the metabolites were also associated with hypertension in the same direction as BMI. The strongest feature, 1-nonadecanoyl-GPC (19:0), was positively associated with the DASH diet (β [SE] = 0.65 [0.12]) and negatively with BMI (β [SE] = -1.34 [0.12]) and hypertension (odds ratio = 0.71, 95% confidence interval = 0.6-0.84).

CONCLUSIONS

We highlight the role of BMI in the mechanisms by which the DASH diet influences hypertension and also highlight common metabolic pathways. Further studies should investigate the underlying molecular mechanisms to increase our understanding of the beneficial ways of treating hypertension.

Association between Circulating Antioxidants and Longevity: Insight from Mendelian Randomization Study

Background. Antioxidants attracted long-standing attention as promising preventive agents worldwide. Previous observational studies have reported that circulating antioxidants are associated with reduced mortality; however, randomized clinical trials indicate neutral or harmful impacts. The association of long-term circulating antioxidant exposure with longevity is still unclear. Objectives. We aim to determine whether long-term circulating antioxidant exposure is causally associated with longevity in the general population using the two-sample Mendelian randomization (MR) design. Methods. Genetic instruments for circulating antioxidants (ascorbate, lycopene, selenium, beta-carotene, and retinol) and antioxidant metabolites (ascorbate, alpha-tocopherol, gamma-tocopherol, and retinol) were identified from the largest up-to-date genome-wide association studies (GWASs). Summary statistics of these instruments with individual survival to the 90th vs. 60th percentile age (11,262 cases and 25,483 controls) and parental lifespan ( $N=\mathrm{1,012,240}$ individuals) were extracted. The causal effect was estimated using the inverse-variance weighted method in the main analysis and complemented by multiple sensitivity analyses to test the robustness of results. Results. We found that genetically determined higher concentration of circulating retinol (vitamin A) metabolite was casually associated with a higher odds of longevity (OR, 1.07; 95% CI, 1.02–1.13; $P<0.01$ ) and increased parental lifespan (lifespan years per 10-fold increase: 0.17; 95% CI, 0.07–0.27; $P<0.01$ ). Present evidence did not support a causal impact of circulating ascorbate (vitamin C), tocopherol (vitamin E), lycopene, selenium or beta-carotene on life expectancy. No evidence was identified to show the pleiotropic effects had biased the results. Conclusions. Long-term higher exposure to retinol metabolite is causally associated with longevity in the general population. Future MR analyses could assess the current findings further by utilizing additional genetic variants and greater samples from large-scale GWASs.

Altered Plasma Mitochondrial Metabolites in Persistently Symptomatic Individuals after a GBCA-Assisted MRI

Despite the impressive safety of gadolinium (Gd)-based contrast agents (GBCAs), a small number of patients report the onset of new, severe, ongoing symptoms after even a single exposure-a syndrome termed Gadolinium Deposition Disease (GDD). Mitochondrial dysfunction and oxidative stress have been repeatedly implicated by animal and in vitro studies as mechanisms of Gd/GBCA-related toxicity, and as pathogenic in other diseases with similarities in presentation. Here, we aimed to molecularly characterize and explore potential metabolic associations with GDD symptoms. Detailed clinical phenotypes were systematically obtained for a small cohort of individuals (n = 15) with persistent symptoms attributed to a GBCA-enhanced MRI and consistent with provisional diagnostic criteria for GDD. Global untargeted mass spectroscopy-based metabolomics analyses were performed on plasma samples and examined for relevance with both single marker and pathways approaches. In addition to GDD criteria, frequently reported symptoms resembled those of patients with known mitochondrial-related diseases. Plasma differences compared to a healthy, asymptomatic reference cohort were suggested for 45 of 813 biochemicals. A notable proportion of these are associated with mitochondrial function and related disorders, including nucleotide and energy superpathways, which were over-represented. Although early evidence, coincident clinical and biochemical indications of potential mitochondrial involvement in GDD are remarkable in light of preclinical models showing adverse Gd/GBCA effects on multiple aspects of mitochondrial function. Further research on the potential contributory role of these markers and pathways in persistent symptoms attributed to GBCA exposure is recommended.

A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk

Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to compare fifteen omics ageing clocks, with correlations of 0.21-0.97 with chronAge, even with substantial sub-setting of biomarkers. These clocks track common aspects of ageing with 95% of the variance in chronAge being shared among clocks. The difference between BA and chronAge - omics clock age acceleration (OCAA) - often associates with health measures. One year’s OCAA typically has the same effect on risk factors/10-year disease incidence as 0.09/0.25 years of chronAge. Epigenetic and IgG glycomics clocks appeared to track generalised ageing while others capture specific risks. We conclude BA is measurable and prognostic and that future work should prioritise health outcomes over chronAge.

Relative Deprivation, Income Inequality, and Cardiovascular Health: Observational and Mendelian Randomization Studies in Hong Kong Chinese

The associations between absolute vs. relative income at the household or neighborhood level and cardiovascular disease (CVD) risk remain understudied in the Chinese context. Further, it is unclear whether stress biomarkers, such as cortisol, are on the pathway from income to CVD risk. We examined the associations of absolute and relative income with CVD risk observationally, as well as the mediating role of cortisol, and validated the role of cortisol using Mendelian Randomization (MR) in Hong Kong Chinese. Within Hong Kong's FAMILY Cohort, associations of absolute and relative income at both the individual and neighborhood levels with CVD risk [body mass index (BMI), body fat percentage, systolic blood pressure, diastolic blood pressure, self-reported CVD and self-reported diabetes] were examined using multilevel logistic or linear models (n = 17,607), the mediating role of cortisol using the mediation analysis (n = 1,562), and associations of genetically predicted cortisol with CVD risk using the multiplicative generalized method of moments (MGMMs) or two-stage least squares regression (n = 1,562). In our cross-sectional observational analysis, relative household income deprivation (per 1 SD, equivalent to USD 128 difference in Yitzhaki index) was associated with higher systolic blood pressure (0.47 mmHg, 95% CI 0.30–0.64), but lower BMI (−0.07 kg/m², 95% CI −0.11 to −0.04), independent of absolute income. Neighborhood income inequality was generally unrelated to CVD and its risk factors, nor was absolute income at the household or neighborhood level. Cortisol did not clearly mediate the association of relative household income deprivation with systolic blood pressure. Using MR, cortisol was unrelated to CVD risk. Based on our findings, relative household income deprivation was not consistently associated with cardiovascular health in Hong Kong Chinese, nor were neighborhood income inequality and absolute income, highlighting the context-specific ways in which relative and absolute income are linked to CVD risk.

Metabolome Genome-Wide Association Study Identifies 74 Novel Genomic Regions Influencing Plasma Metabolites Levels

Metabolites are small products of metabolism that provide a snapshot of the wellbeing of an organism and the mechanisms that control key physiological processes involved in health and disease. Here we report the results of a genome-wide association study of 722 circulating metabolite levels in 8809 subjects of European origin, providing both breadth and depth. These analyses identified 202 unique genomic regions whose variations are associated with the circulating levels of 478 different metabolites. Replication with a subset of 208 metabolites that were available in an independent dataset for a cohort of 1768 European subjects confirmed the robust associations, including 74 novel genomic regions not associated with any metabolites in previous works. This study enhances our knowledge of genetic mechanisms controlling human metabolism. Our findings have major potential for identifying novel targets and developing new therapeutic strategies.

Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations

BACKGROUND

Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed.

OBJECTIVE

The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations.

METHODS

We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886).

RESULTS

We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model.

CONCLUSION

PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.

Associations of Blood Caffeine and Genetically Predicted Coffee Consumption with Anthropometric Measures of Obesity: A Two Sample Mendelian Randomization Study

OBJECTIVES

In observational studies, caffeine has been associated with a lower risk of obesity. However, whether the associations are causal and apply to coffee, which is a mixture of chemical compounds is unclear.

DESIGN

Two sample Mendelian randomization study.

SETTING AND PARTICIPANTS

Genetic instruments predicting caffeine were extracted from an existing GWAS of serum metabolites in 1960 individuals of European descent. For coffee consumption up to 91,462 individuals of European ancestry with top SNPs followed-up in ~30,062 coffee consumers and up to 375,833 individuals of European ancestry were taken from two separate studies. Genetic associations with obesity classes (n= 263,407), waist-to-hip ratio (WHR) (n=210,086), waist circumference (WC) (n= 231,355), and hip circumference (HC) (n=211,117) were obtained from summary statistics of individuals of European ancestry from the Genetic Investigation of Anthropocentric Traits (GIANT).

METHODS

The inverse-variance weighted method (IVW) was used as the main analysis. We also employed the weighted median approach (WM) and MR-Egger regression as sensitivity analyses. To gauge evidence of directional pleiotropy, we used Cochrane's Q test, and MR-PRESSO global test, as measures of heterogeneity between ratio estimates of variants.

RESULTS

There was little evidence to support an association between blood caffeine and any anthropometric measure of obesity in the primary and sensitivity analyses. However, genetically predicted coffee consumption was positively associated with higher class I obesity and WHR. Furthermore, this association was maintained after correction for multiple testing (P < 0.05/6 = 0.008). Results from the GWAS of coffee consumption were in tandem with results from the GWMA, but associations with class I obesity and waist to hip ratio (WHR) were not maintained after correction for multiple testing.

CONCLUSION

We found little evidence that caffeine or coffee consumption protects against obesity, adding to growing literature suggesting that previous observational studies may have been confounded. This study demonstrates the dangers of ignoring genetic testing for targeted interventions and basing dietary policy recommendations solely on observational studies restricted to specific populations.

Microglia in Alzheimer's Disease: a Key Player in the Transition Between Homeostasis and Pathogenesis

Immune activation accompanies the development of proteinopathy in the brains of Alzheimer's dementia patients. Evolving from the long-held viewpoint that immune activation triggers the pathological trajectory in Alzheimer's disease, there is accumulating evidence now that microglial activation is neither pro-amyloidogenic nor just a simple reactive process to the proteinopathy. Preclinical studies highlight an interesting aspect of immunity, i.e., spurring immune system activity may be beneficial under certain circumstances. Indeed, a dynamic evolving relationship between different activation states of the immune system and its neuronal neighbors is thought to regulate overall brain organ health in both healthy aging and progression of Alzheimer's dementia. A new premise evolving from genome, transcriptome, and proteome data is that there might be at least two major phases of immune activation that accompany the pathological trajectory in Alzheimer's disease. Though activation on a chronic scale will certainly lead to neurodegeneration, this emerging knowledge of a potential beneficial aspect of immune activation allows us to form holistic insights into when, where, and how much immune system activity would need to be tuned to impact the Alzheimer's neurodegenerative cascade. Even with the trove of recently emerging -omics data from patients and preclinical models, how microglial phenotypes are functionally related to the transition of a healthy aging brain towards progressive degenerative state remains unknown. A deeper understanding of the synergism between microglial functional states and brain organ health could help us discover newer interventions and therapies that enable us to address the current paucity of disease-modifying therapies in Alzheimer's disease.

Diet-Derived Antioxidants Do Not Decrease Risk of Ischemic Stroke: A Mendelian Randomization Study in 1 Million People

Background

Dietary intake and blood concentrations of vitamins E and C, lycopene, and carotenoids have been associated with a lower risk of incident (ischemic) stroke. However, causality cannot be inferred from these associations. Here, we investigated causality by analyzing the associations between genetically influenced antioxidant levels in blood and ischemic stroke using Mendelian randomization.

Methods and Results

For each circulating antioxidant (vitamins E and C, lycopene, β‐carotene, and retinol), which were assessed as either absolute blood levels and/or high‐throughput metabolite levels, independent genetic instrumental variables were selected from earlier genome‐wide association studies (P<5×10⁻⁸). We used summary statistics for single‐nucleotide polymorphisms–stroke associations from 3 European‐ancestry cohorts (cases/controls): MEGASTROKE (60 341/454 450), UK Biobank (2404/368 771), and the FinnGen study (8046/164 286). Mendelian randomization analyses were performed on each exposure per outcome cohort using inverse variance–weighted analyses and subsequently meta‐analyzed. In a combined sample of 1 058 298 individuals (70 791 cases), none of the genetically influenced absolute antioxidants or antioxidant metabolite concentrations were causally associated with a lower risk of ischemic stroke. For absolute antioxidants levels, the odds ratios (ORs) ranged between 0.94 (95% CI, 0.85–1.05) for vitamin C and 1.04 (95% CI, 0.99–1.08) for lycopene. For metabolites, ORs ranged between 1.01 (95% CI, 0.98–1.03) for retinol and 1.12 (95% CI, 0.88–1.42) for vitamin E.

Conclusions

This study did not provide evidence for a causal association between dietary‐derived antioxidant levels and ischemic stroke. Therefore, antioxidant supplements to increase circulating levels are unlikely to be of clinical benefit to prevent ischemic stroke.

Microbiota-dependent increase in δ-valerobetaine alters neuronal function and is responsible for age-related cognitive decline

Understanding the physiological origins of age-related cognitive decline is of critical importance given the rising age of the world's population¹. Previous work in animal models has established a strong link between cognitive performance and the microbiota^2-5, and it is known that the microbiome undergoes profound remodeling in older adults⁶. Despite growing evidence for the association between age-related cognitive decline and changes in the gut microbiome, the mechanisms underlying such interactions between the brain and the gut are poorly understood. Here, using fecal microbiota transplantation (FMT), we demonstrate that age-related remodeling of the gut microbiota leads to decline in cognitive function in mice and that this impairment can be rescued by transplantation of microbiota from young animals. Moreover, using a metabolomic approach, we found elevated concentrations of δ-valerobetaine, a gut microbiota-derived metabolite, in the blood and brain of aged mice and older adults. We then demonstrated that δ-valerobetaine is deleterious to learning and memory processes in mice. At the neuronal level, we showed that δ-valerobetaine modulates inhibitory synaptic transmission and neuronal network activity. Finally, we identified specific bacterial taxa that significantly correlate with δ-valerobetaine levels in the brain. Based on our findings, we propose that δ-valerobetaine contributes to microbiota-driven brain aging and that the associated mechanisms represent a promising target for countering age-related cognitive decline.

Metabolomic biomarkers of low BMD: a systematic review

Due to the metabolic nature of osteoporosis, this study was conducted to identify metabolomic studies investigating the metabolic profile of low bone mineral density (BMD) and osteoporosis. A comprehensive systematic literature search was conducted through PubMed, Web of Science, Scopus, and Embase databases up to April 08, 2020, to identify observational studies with cross-sectional or case-control designs investigating the metabolic profile of low BMD in adults using biofluid specimen via metabolomic platform. The quality assessment panel specified for the "omics"-based diagnostic research (QUADOMICS) tool was used to estimate the methodologic quality of the included studies. Ten untargeted and one targeted approach metabolomic studies investigating biomarkers in different biofluids through mass spectrometry or nuclear magnetic resonance platforms were included in the systematic review. Some metabolite panels, rather than individual metabolites, showed promising results in differentiating low BMD from normal. Candidate metabolites were of different categories including amino acids, followed by lipids and carbohydrates. Besides, certain pathways were suggested by some of the studies to be involved. This systematic review suggested that metabolic profiling could improve the diagnosis of low BMD. Despite valuable findings attained from each of these studies, there was great heterogeneity regarding the ethnicity and age of participants, samples, and the metabolomic platform. Further longitudinal studies are needed to validate the results and confirm the predictive role of metabolic profile on low BMD and fracture. It is also mandatory to address and minimize the heterogeneity in future studies by using reliable quantitative methods. Summary: Due to the metabolic nature of osteoporosis, researchers have considered metabolomic studies recently. This systematic review showed that metabolic profiling including different categories of metabolites could improve the diagnosis of low BMD. However, great heterogeneity was observed and it is mandatory to address and minimize the heterogeneity in future studies.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

Background

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

Methods

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

Findings

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

Interpretation

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Metabolomics Study Reveals Systematic Metabolic Dysregulation and Early Detection Markers Associated with Incident Pancreatic Cancer

Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n=192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < 0.05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormone, vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer. This article is protected by copyright. All rights reserved.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Association of BCAT2 and BCKDH polymorphisms with clinical, anthropometric and biochemical parameters in young adults

BACKGROUND AND AIM

Circulating amino acids are modified by sex, body mass index (BMI) and insulin resistance (IR). However, whether the presence of genetic variants in branched-chain amino acid (BCAA) catabolic enzymes modifies circulating amino acids is still unknown. Thus, we determined the frequency of two genetic variants, one in the branched-chain aminotransferase 2 (BCAT2) gene (rs11548193), and one in the branched-chain ketoacid dehydrogenase (BCKDH) gene (rs45500792), and elucidated their impact on circulating amino acid levels together with clinical, anthropometric and biochemical parameters.

METHODS AND RESULTS

We performed a cross-sectional comparative study in which we recruited 1612 young adults (749 women and 863 men) aged 19.7 ± 2.1 years and with a BMI of 24.9 ± 4.7 kg/m². Participants underwent clinical evaluation and provided blood samples for DNA extraction and biochemical analysis. The single nucleotide polymorphisms (SNPs) were determined by allelic discrimination using real-time polymerase chain reaction (PCR). The frequencies of the less common alleles were 15.2 % for BCAT2 and 9.83 % for BCKDH. The subjects with either the BCAT2 or BCKDH SNPs displayed no differences in the evaluated parameters compared with subjects homozygotes for the most common allele at each SNP. However, subjects with both SNPs had higher body weight, BMI, blood pressure, glucose, and circulating levels of aspartate, isoleucine, methionine, and proline than the subjects homozygotes for the most common allele (P < 0.05, One-way ANOVA).

CONCLUSION

Our findings suggest that the joint presence of both the BCAT2 rs11548193 and BCKDH rs45500792 SNPs induces metabolic alterations that are not observed in subjects without either SNP.

Sequencing-based genome-wide association studies reporting standards

Genome sequencing has recently become a viable genotyping technology for use in genome-wide association studies (GWASs), offering the potential to analyze a broader range of genome-wide variation, including rare variants. To survey current standards, we assessed the content and quality of reporting of statistical methods, analyses, results, and datasets in 167 exome- or genome-wide-sequencing-based GWAS publications published from 2014 to 2020; 81% of publications included tests of aggregate association across multiple variants, with multiple test models frequently used. We observed a lack of standardized terms and incomplete reporting of datasets, particularly for variants analyzed in aggregate tests. We also find a lower frequency of sharing of summary statistics compared with array-based GWASs. Reporting standards and increased data sharing are required to ensure sequencing-based association study data are findable, interoperable, accessible, and reusable (FAIR). To support that, we recommend adopting the standard terminology of sequencing-based GWAS (seqGWAS). Further, we recommend that single-variant analyses be reported following the same standards and conventions as standard array-based GWASs and be shared in the GWAS Catalog. We also provide initial recommended standards for aggregate analyses metadata and summary statistics.

mGWAS identification of six novel single nucleotide polymorphism loci with strong correlation to gastric cancer

BACKGROUND

Metabolite genome-wide association studies (mGWAS) are key for understanding the genetic regulation of metabolites in complex diseases including cancers. Although mGWAS has revealed hundreds of metabolomics quantitative trait loci (mQTLs) in the general population, data relating to gastric cancer (GC) are still incomplete.

METHODS

We identified mQTLs associated with GC by analyzing genome-wide and metabolome-wide datasets generated from 233 GC patients and 233 healthy controls.

RESULTS

Twenty-two metabolites were statistically different between GC cases and healthy controls, and all of them were associated with the risk of gastric cancer. mGWAS analyses further revealed that 9 single nucleotide polymorphisms (SNPs) were significantly associated with 3 metabolites. Of these 9 SNPs, 6 loci were never reported in the previous mGWAS studies. Surprisingly, 4 of 9 SNPs were significantly enriched in genes involved in the T cell receptor signaling pathway.

CONCLUSIONS

Our study unveiled several novel GC metabolite and genetic biomarkers, which may be implicated in the prevention and diagnosis of gastric cancer.

Metabolomic architecture of obesity implicates metabolonic lactone sulfate in cardiometabolic disease

OBJECTIVE

Identify and characterize circulating metabolite profiles associated with adiposity to inform precision medicine.

METHODS

Untargeted plasma metabolomic profiles in the Insulin Resistance Atherosclerosis Family Study (IRASFS) Mexican American cohort (n = 1108) were analyzed for association with anthropometric (body mass index, BMI; waist circumference, WC; waist-to-hip ratio, WHR) and computed tomography measures (visceral adipose tissue, VAT; subcutaneous adipose tissue, SAT; visceral-to-subcutaneous ratio, VSR) of adiposity. Genetic data, inclusive of genome-wide array-based genotyping, whole exome sequencing (WES) and whole genome sequencing (WGS), were evaluated to identify the genetic contributors. Phenotypic and genetic association signals were replicated across ancestries. Transcriptomic data were analyzed to explore the relationship between genetic and metabolomic data.

RESULTS

A partially characterized metabolite, tentatively named metabolonic lactone sulfate (X-12063), was consistently associated with BMI, WC, WHR, VAT, and SAT in IRASFS Mexican Americans (P_MA <2.02 × 10^-27). Trait associations were replicated in IRASFS African Americans (P_AA < 1.12 × 10^-07). Expanded analyses revealed associations with multiple phenotypic measures of cardiometabolic health, e.g. insulin sensitivity (S_I), triglycerides (TG), diastolic blood pressure (DBP) and plasminogen activator inhibitor-1 (PAI-1) in both ancestries. Metabolonic lactone sulfate levels were heritable (h² > 0.47), and a significant genetic signal at the ZSCAN25/CYP3A5 locus (P_MA = 9.00 × 10^-41, P_AA = 2.31 × 10^-10) was observed, highlighting a putative functional variant (rs776746, CYP3A5∗3). Transcriptomic analysis in the African American Genetics of Metabolism and Expression (AAGMEx) cohort supported the association of CYP3A5 with metabolonic lactone sulfate levels (P_FDR = 6.64 × 10^-07).

CONCLUSIONS

Variant rs776746 is associated with a decrease in the transcript levels of CYP3A5, which in turn is associated with increased metabolonic lactone sulfate levels and poor cardiometabolic health.

Proteins Associated with Risk of Kidney Function Decline in the General Population

BACKGROUND

Proteomic profiling may allow identification of plasma proteins that associate with subsequent changesin kidney function, elucidating biologic processes underlying the development and progression of CKD.

METHODS

We quantified the association between 4877 plasma proteins and a composite outcome of ESKD or decline in eGFR by ≥50% among 9406 participants in the Atherosclerosis Risk in Communities (ARIC) Study (visit 3; mean age, 60 years) who were followed for a median of 14.4 years. We performed separate analyses for these proteins in a subset of 4378 participants (visit 5), who were followed at a later time point, for a median of 4.4 years. For validation, we evaluated proteins with significant associations (false discovery rate <5%) in both time periods in 3249 participants in the Chronic Renal Insufficiency Cohort (CRIC) and 703 participants in the African American Study of Kidney Disease and Hypertension (AASK). We also compared the genetic determinants of protein levels with those from a meta-analysis genome-wide association study of eGFR.

RESULTS

In models adjusted for multiple covariates, including baseline eGFR and albuminuria, we identified 13 distinct proteins that were significantly associated with the composite end point in both time periods, including TNF receptor superfamily members 1A and 1B, trefoil factor 3, and β-trace protein. Of these proteins, 12 were also significantly associated in CRIC, and nine were significantly associated in AASK. Higher levels of each protein associated with higher risk of 50% eGFR decline or ESKD. We found genetic evidence for a causal role for one protein, lectin mannose-binding 2 protein (LMAN2).

CONCLUSIONS

Large-scale proteomic analysis identified both known and novel proteomic risk factors for eGFR decline.

Metabolomic Predictors of Non-alcoholic Steatohepatitis and Advanced Fibrosis in Children

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in western countries both in children and adults. Metabolic dysregulation associated with gut microbial dysbiosis may influence disease progression from hepatic steatosis to inflammation and subsequent fibrosis. Using a multi-omics approach, we profiled the oral and fecal microbiome and plasma metabolites from 241 predominantly Latino children with non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver (NAFL), and controls. Children with more severe liver pathology were dysbiotic and had increased gene content associated with lipopolysaccharide biosynthesis and lipid, amino acid and carbohydrate metabolism. These changes were driven by increases in Bacteroides and concomitant decreases of Akkermansia, Anaerococcus, Corynebacterium, and Finegoldia. Non-targeted mass spectrometry revealed perturbations in one-carbon metabolism, mitochondrial dysfunction, and increased oxidative stress in children with steatohepatitis and fibrosis. Random forests modeling of plasma metabolites was highly predictive of non-alcoholic steatohepatitis (NASH) (97% accuracy) and hepatic fibrosis, steatosis and lobular inflammation (93.8% accuracy), and can differentiate steatohepatitis from simple steatosis (90.0% accuracy). Multi-omics predictive models for disease and histology findings revealed perturbations in one-carbon metabolism, mitochondrial dysfunction, and increased oxidative stress in children with steatohepatitis and fibrosis. These results highlight the promise of non-invasive biomarkers for the growing epidemic of fatty liver disease.

The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene

Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk. We used genetic approaches to identify inflammatory mechanisms associated with kynurenine variability and their relationship to cardiometabolic disease. We identified single-nucleotide polymorphisms (SNPs) previously associated with plasma kynurenine, including a missense-variant (rs3184504) in the inflammatory gene SH2B3/LNK. We examined the association between rs3184504 and plasma kynurenine in independent human samples, and measured kynurenine levels in SH2B3-knock-out mice and during human LPS-evoked endotoxemia. We conducted phenome scanning to identify clinical phenotypes associated with each kynurenine-related SNP and with a kynurenine polygenic score using the UK-Biobank (n = 456,422), BioVU (n = 62,303), and Electronic Medical Records and Genetics (n = 32,324) databases. The SH2B3 missense variant associated with plasma kynurenine levels and SH2B3-/- mice had significant tissue-specific differences in kynurenine levels.LPS, an acute inflammatory stimulus, increased plasma kynurenine in humans. Mendelian randomization showed increased waist-circumference, a marker of central obesity, associated with increased kynurenine, and increased kynurenine associated with C-reactive protein (CRP). We found 30 diagnoses associated (FDR q < 0.05) with the SH2B3 variant, but not with SNPs mapping to genes known to regulate tryptophan-kynurenine metabolism. Plasma kynurenine may be a biomarker of acute and chronic inflammation involving the SH2B3 pathways. Its regulation lies upstream of CRP, suggesting that kynurenine may be a biomarker of one inflammatory mechanism contributing to increased cardiometabolic disease risk.

Genome-wide association study of serum metabolites in the African American Study of Kidney Disease and Hypertension

The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. To date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m2) in the African American Study of Kidney Disease and Hypertension, a clinical trial of blood pressure lowering and antihypertensive medication in African Americans with chronic kidney disease. We identified 42 significant variant metabolite associations. Twenty associations had been previously identified in published GWAS, and eleven novel associations were replicated in a separate cohort of 818 African Americans with genetic and metabolomic data from the Atherosclerosis Risk in Communities Study. The replicated novel variant-metabolite associations comprised eight metabolites and eleven distinct genomic loci. Nine of the replicated associations represented clear enzyme-metabolite interactions, with high expression in the kidneys as well as the liver. Three loci (ACY1, ACY3, and NAT8) were associated with a common pool of metabolites, acetylated amino acids, but with different individual affinities. Thus, extensive metabolite profiling in an African American population with chronic kidney disease aided identification of novel genome-wide metabolite associations, providing clues about substrate specificity and the key roles of enzymes in modulating systemic levels of metabolites.

Associations of metabolomic profiles with circulating vitamin E and urinary vitamin E metabolites in middle-aged individuals

Vitamin E (α-tocopherol [α-TOH]) is transported in lipoprotein particles in blood, but little is known about the transportation of its oxidized metabolites. In the Netherlands Epidemiology of Obesity Study, we aimed to investigate the associations of 147 circulating metabolomic measures obtained through targeted nuclear magnetic resonance with serum α-TOH and its urinary enzymatic (α-CEHC) and oxidized (α-TLHQ) metabolites from 24-h urine quantified by liquid chromatography with tandem mass spectrometry. Multivariable linear regression analyses, in which multiple testing was taken into account, were performed to assess associations between metabolomic measures (determinants; standardized to mean = 0, SD = 1) and vitamin E metabolites (outcomes), adjusted for demographic factors. We analyzed 474 individuals (55% women, 45% men) with a mean (SD) age of 55.7 (6.0) y. Out of 147 metabolomic measures, 106 were associated (P < 1.34 × 10^-3) with serum α-TOH (median β [interquartile range] = 0.416 [0.383-0.466]), predominantly lipoproteins associated with higher α-TOH. The associations of metabolomic measures with urinary α-CEHC have directions similar to those with α-TOH, but effect sizes were smaller and non-significant (median β [interquartile range] = 0.065 [0.047-0.084]). However, associations of metabolomic measures with urinary α-TLHQ were markedly different from those with both serum α-TOH and urinary α-CEHC, with negative and small-to-null relations to most very-low-density lipoproteins and amino acids. Therefore, our results highlight the differences in the lipoproteins involved in the transportation of circulating α-TOH and oxidized vitamin E metabolites. This indicates that circulating α-TOH may be representative of the enzymatic but not the antioxidative function of vitamin E.

Genetic and Environmental Contributions to Variation in the Stable Urinary NMR Metabolome over Time: A Classic Twin Study

Genes, sex, age, diet, lifestyle, gut microbiome, and multiple other factors affect human metabolomic profiles. Understanding metabolomic variation is critical in human nutrition research as metabolites that are sensitive to change versus those that are more stable might be more informative for a particular study design. This study aims to identify stable metabolomic regions and determine the genetic and environmental contributions to stability. Using a classic twin design, ¹H nuclear magnetic resonance (NMR) urinary metabolomic profiles were measured in 128 twins at baseline, 1 month, and 2 months. Multivariate mixed models identified stable urinary metabolites with intraclass correlation coefficients ≥0.51. Longitudinal twin modeling measured the contribution of genetic and environmental influences to variation in the stable urinary NMR metabolome, comprising stable metabolites. The conservation of an individual’s stable urinary NMR metabolome over time was assessed by calculating conservation indices. In this study, 20% of the urinary NMR metabolome is stable over 2 months (intraclass correlation (ICC) 0.51–0.65). Common genetic and shared environmental factors contributed to variance in the stable urinary NMR metabolome over time. Using the stable metabolome, 91% of individuals had good metabolomic conservation indices ≥0.70. To conclude, this research identifies 20% of the urinary NMR metabolome as stable, improves our knowledge of the sources of metabolomic variation over time, and demonstrates the conservation of an individual’s urinary NMR metabolome.

Association of measures of body fat with serum alpha-tocopherol and its metabolites in middle-aged individuals

BACKGROUND AND AIMS

The accumulation of fat increases the formation of lipid peroxides, which are partly scavenged by alpha-tocopherol (α-TOH). Here, we aimed to investigate the associations between different measures of (abdominal) fat and levels of urinary α-TOH metabolites in middle-aged individuals.

METHODS AND RESULTS

In this cross-sectional analysis in the Netherlands Epidemiology of Obesity study (N = 511, 53% women; mean [SD] age of 55 [6.1] years), serum α-TOH and α-TOH metabolites from 24-h urine were measured as alpha-tocopheronolactone hydroquinone (α-TLHQ, oxidized) and alpha-carboxymethyl-hydroxychroman (α-CEHC, enzymatically converted) using liquid-chromatography-tandem mass spectrometry. Body mass index and total body fat were measured, and abdominal subcutaneous and visceral adipose tissue (aSAT and VAT) were assessed using magnetic resonance imaging. Using multivariable-adjusted linear regression analyses, we analysed the associations of BMI, TBF, aSAT and VAT with levels of urinary α-TOH metabolites, adjusted for confounders. We observed no evidence for associations between body fat measures and serum α-TOH. Higher BMI and TBF were associated with lower urinary levels of TLHQ (0.95 [95%CI: 0.90, 1.00] and 0.94 [0.88, 1.01] times per SD, respectively) and with lower TLHQ relative to CEHC (0.93 [0.90, 0.98] and 0.93 [0.87, 0.98] times per SD, respectively). We observed similar associations for VAT (TLHQ: 0.94 [0.89, 0.99] times per SD), but not for aSAT.

CONCLUSIONS

Opposite to our research hypothesis, higher abdominal adiposity was moderately associated with lower levels of oxidized α-TOH metabolites, which might reflect lower vitamin E antioxidative activity in individuals with higher abdominal fat instead.

Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease

BACKGROUND

Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors.

RESULT

We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target.

CONCLUSION

This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.

Linking the FTO obesity rs1421085 variant circuitry to cellular, metabolic, and organismal phenotypes in vivo

Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates Irx3 and Irx5 gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot-dependent manner and affects organismal phenotypes that are relevant for obesity, including decreased high-fat diet-induced weight gain, decreased whole-body fat mass, and decreased skin fat thickness. Last, we connected the CRM to a genetically determined effect on steroid patterns in males that was dependent on nutritional challenge and conserved across mice and humans. Together, our data establish cross-species conservation of the rs1421085 regulatory circuitry at the molecular, cellular, metabolic, and organismal level, revealing previously unknown contextual dependence of the variant's action.

A Metabolomic Signature of Glucagon Action in Healthy Individuals With Overweight/Obesity

Context

Glucagon is produced and released from the pancreatic alpha-cell to regulate glucose levels during periods of fasting. The main target for glucagon action is the liver, where it activates gluconeogenesis and glycogen breakdown; however, glucagon is postulated to have other roles within the body.

Objective

We sought to identify the circulating metabolites that would serve as markers of glucagon action in humans.

Methods

In this study (NCT03139305), we performed a continuous 72-hour glucagon infusion in healthy individuals with overweight/obesity. Participants were randomized to receive glucagon 12.5 ng/kg/min (GCG 12.5), glucagon 25 ng/kg/min (GCG 25), or a placebo control. A comprehensive metabolomics analysis was then performed from plasma isolated at several time points during the infusion to identify markers of glucagon activity.

Results

Glucagon (GCG 12.5 and GCG 25) resulted in significant changes in the plasma metabolome as soon as 4 hours following infusion. Pathways involved in amino acid metabolism were among the most affected. Rapid and sustained reduction of a broad panel of amino acids was observed. Additionally, time-dependent changes in free fatty acids and diacylglycerol and triglyceride species were observed.

Conclusion

These results define a distinct signature of glucagon action that is broader than the known changes in glucose levels. In particular, the robust changes in amino acid levels may prove useful to monitor changes induced by glucagon in the context of additional glucagon-like peptide-1 or gastric inhibitory polypeptide treatment, as these agents also elicit changes in glucose levels.

Molecular Portrait of an Athlete

Sequencing of the human genome and further developments in "omics" technologies have opened up new possibilities in the study of molecular mechanisms underlying athletic performance. It is expected that molecular markers associated with the development and manifestation of physical qualities (speed, strength, endurance, agility, and flexibility) can be successfully used in the selection systems in sports. This includes the choice of sports specialization, optimization of the training process, and assessment of the current functional state of an athlete (such as overtraining). This review summarizes and analyzes the genomic, proteomic, and metabolomic studies conducted in the field of sports medicine.

Diet-Derived Circulating Antioxidants and Risk of Coronary Heart Disease: A Mendelian Randomization Study

BACKGROUND

Previously, observational studies have identified associations between higher levels of dietary-derived antioxidants and lower risk of coronary heart disease (CHD), whereas randomized clinical trials showed no reduction in CHD risk following antioxidant supplementation.

OBJECTIVES

The purpose of this study was to investigate possible causal associations between dietary-derived circulating antioxidants and primary CHD risk using 2-sample Mendelian randomization (MR).

METHODS

Single-nucleotide polymorphisms for circulating antioxidants (vitamins E and C, retinol, β-carotene, and lycopene), assessed as absolute levels and metabolites, were retrieved from the published data and were used as genetic instrumental variables. Summary statistics for gene-CHD associations were obtained from 3 databases: the CARDIoGRAMplusC4D consortium (60,801 cases; 123,504 control subjects), UK Biobank (25,306 cases; 462,011 control subjects), and FinnGen study (7,123 cases; 89,376 control subjects). For each exposure, MR analyses were performed per outcome database and were subsequently meta-analyzed.

RESULTS

Among an analytic sample of 768,121 individuals (93,230 cases), genetically predicted circulating antioxidants were not causally associated with CHD risk. For absolute antioxidants, the odds ratio for CHD ranged between 0.94 (95% confidence interval [CI]: 0.63 to 1.41) for retinol and 1.03 (95% CI: 0.97 to 1.10) for β-carotene per unit increase in ln-transformed antioxidant values. For metabolites, the odds ratio ranged between 0.93 (95% CI: 0.82 to 1.06) for γ-tocopherol and 1.01 (95% CI: 0.95 to 1.08) for ascorbate per 10-fold increase in metabolite levels.

CONCLUSIONS

Evidence from our study did not support a protective effect of genetic predisposition to high dietary-derived antioxidant levels on CHD risk. Therefore, it is unlikely that taking antioxidants to increase blood antioxidants levels will have a clinical benefit for the prevention of primary CHD.

Multi-Omics Approaches in Immunological Research

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.