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Multiple recent studies highlight that genetic variants can have strong impacts on a significant proportion of the human DNA methylome. Methylation quantitative trait loci, or meQTLs, allow for the exploration of biological mechanisms that underlie complex human phenotypes, with potential insights for human disease onset and progression. In this review, we summarize recent milestones in characterizing the human genetic basis of DNA methylation variation over the last decade, including heritability findings and genome-wide identification of meQTLs. We also discuss challenges in this field and future areas of research geared to generate insights into molecular processes underlying human complex traits.

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments. Here, the authors study the interplay between the microbiome and faecal and blood metabolome, and how the microbiome interacts in the dialogue between these metabolic compartments, identifying a key role for microbial functions and underscoring their relevance for microbiome therapeutic strategies.

The human gut microbiome plays a key role in human health 1 , but 16S characterization lacks quantitative functional annotation 2 . The fecal metabolome provides a functional readout of microbial activity and can be used as an intermediate phenotype mediating host–microbiome interactions 3 . In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability ( H 2 ) = 17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits. Comprehensive fecal metabolic profiling in 786 individuals from TwinsUK provides insights into the influence of host genetics and gut microbial composition on metabolites that may mediate microbiome-associated phenotypes.

It has been widely observed that adult men of all ages are at higher risk of developing serious complications from COVID-19 when compared with women. This study aimed to investigate the association of COVID-19 positivity and severity with estrogen exposure in women, in a population based matched cohort study of female users of the COVID Symptom Study application in the UK. Analyses included 152,637 women for menopausal status, 295,689 women for exogenous estrogen intake in the form of the combined oral contraceptive pill (COCP), and 151,193 menopausal women for hormone replacement therapy (HRT). Data were collected using the COVID Symptom Study in May-June 2020. Analyses investigated associations between predicted or tested COVID-19 status and menopausal status, COCP use, and HRT use, adjusting for age, smoking and BMI, with follow-up age sensitivity analysis, and validation in a subset of participants from the TwinsUK cohort. Menopausal women had higher rates of predicted COVID-19 (P = 0.003). COCP-users had lower rates of predicted COVID-19 (P = 8.03E-05), with reduction in hospital attendance (P = 0.023). Menopausal women using HRT or hormonal therapies did not exhibit consistent associations, including increased rates of predicted COVID-19 (P = 2.22E-05) for HRT users alone. The findings support a protective effect of estrogen exposure on COVID-19, based on positive association between predicted COVID-19 with menopausal status, and negative association with COCP use. HRT use was positively associated with COVID-19, but the results should be considered with caution due to lack of data on HRT type, route of administration, duration of treatment, and potential unaccounted for confounders and comorbidities.

Background The composition of bacteria in and on the human body varies widely across human individuals, and has been associated with multiple health conditions. While microbial communities are influenced by environmental factors, some degree of genetic influence of the host on the microbiome is also expected. This study is part of an expanding effort to comprehensively profile the interactions between human genetic variation and the composition of this microbial ecosystem on a genome- and microbiome-wide scale. Results Here, we jointly analyze the composition of the human microbiome and host genetic variation. By mining the shotgun metagenomic data from the Human Microbiome Project for host DNA reads, we gathered information on host genetic variation for 93 individuals for whom bacterial abundance data are also available. Using this dataset, we identify significant associations between host genetic variation and microbiome composition in 10 of the 15 body sites tested. These associations are driven by host genetic variation in immunity-related pathways, and are especially enriched in host genes that have been previously associated with microbiome-related complex diseases, such as inflammatory bowel disease and obesity-related disorders. Lastly, we show that host genomic regions associated with the microbiome have high levels of genetic differentiation among human populations, possibly indicating host genomic adaptation to environment-specific microbiomes. Conclusions Our results highlight the role of host genetic variation in shaping the composition of the human microbiome, and provide a starting point toward understanding the complex interaction between human genetics and the microbiome in the context of human evolution and disease.

ObjectiveProton pump inhibitors (PPIs) are drugs used to suppress gastric acid production and treat GI disorders such as peptic ulcers and gastro-oesophageal reflux. They have been considered low risk, have been widely adopted, and are often over-prescribed. Recent studies have identified an increased risk of enteric and other infections with their use. Small studies have identified possible associations between PPI use and GI microbiota, but this has yet to be carried out on a large population-based cohort.DesignWe investigated the association between PPI usage and the gut microbiome using 16S ribosomal RNA amplification from faecal samples of 1827 healthy twins, replicating results within unpublished data from an interventional study.ResultsWe identified a significantly lower abundance in gut commensals and lower microbial diversity in PPI users, with an associated significant increase in the abundance of oral and upper GI tract commensals. In particular, significant increases were observed in Streptococcaceae. These associations were replicated in an independent interventional study and in a paired analysis between 70 monozygotic twin pairs who were discordant for PPI use. We propose that the observed changes result from the removal of the low pH barrier between upper GI tract bacteria and the lower gut.ConclusionsOur findings describe a significant impact of PPIs on the gut microbiome and should caution over-use of PPIs, and warrant further investigation into the mechanisms and their clinical consequences.

The human gut microbiome has been associated with many health factors but variability between studies limits exploration of effects between them. Gut microbiota profiles are available for >2700 members of the deeply phenotyped TwinsUK cohort, providing a uniform platform for such comparisons. Here, we present gut microbiota association analyses for 38 common diseases and 51 medications within the cohort. We describe several novel associations, highlight associations common across multiple diseases, and determine which diseases and medications have the greatest association with the gut microbiota. These results provide a reference for future studies of the gut microbiome and its role in human health. The human gut microbiome has been associated with many health factors, but variability between studies limits exploration of these effects. Here, Jackson et al. analyse gut microbiota associations for 38 common diseases and 51 medications within >2700 members of the TwinsUK cohort.

Several circulating metabolites derived from bacterial protein fermentation have been found to be inversely associated with renal function but the timing and disease severity is unclear. The aim of this study is to explore the relationship between indoxyl-sulfate, p-cresyl-sulfate, phenylacetylglutamine and gut-microbial profiles in early renal function decline. Indoxyl-sulfate (Beta(SE) = -2.74(0.24); P = 8.8x10-29), p-cresyl-sulfate (-1.99(0.24), P = 4.6x10-16), and phenylacetylglutamine(-2.73 (0.25), P = 1.2x10-25) were inversely associated with eGFR in a large population base cohort (TwinsUK, n = 4439) with minimal renal function decline. In a sub-sample of 855 individuals, we analysed metabolite associations with 16S gut microbiome profiles (909 profiles, QIIME 1.7.0). Three Operational Taxonomic Units (OTUs) were significantly associated with indoxyl-sulfate and 52 with phenylacetylglutamine after multiple testing; while one OTU was nominally associated with p-cresyl sulfate. All 56 microbial members belong to the order Clostridiales and are represented by anaerobic Gram-positive families Christensenellaceae, Ruminococcaceae and Lachnospiraceae. Within these, three microbes were also associated with eGFR. Our data suggest that indoxyl-sulfate, p-cresyl-sulfate and phenylacetylglutamine are early markers of renal function decline. Changes in the intestinal flora associated with these metabolites are detectable in early kidney disease. Future efforts should dissect this relationship to improve early diagnostics and therapeutics strategies.

Significance Because obese people are at an increased risk of many age-related diseases, it is a plausible hypothesis that obesity increases the biological age of some tissues and cell types. However, it has been difficult to detect such an accelerated aging effect because it is unclear how to measure tissue age. Here we use a recently developed biomarker of aging (known as “epigenetic clock”) to study the relationship between epigenetic age and obesity in several human tissues. We report an unexpectedly strong correlation between high body mass index and the epigenetic age of liver tissue. This finding may explain why obese people suffer from the early onset of many age-related pathologies, including liver cancer. Because of the dearth of biomarkers of aging, it has been difficult to test the hypothesis that obesity increases tissue age. Here we use a novel epigenetic biomarker of aging (referred to as an “epigenetic clock”) to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle, and adipose tissue. A significant correlation between BMI and epigenetic age acceleration could only be observed for liver ( r = 0.42, P = 6.8 × 10 ⁻⁴ in dataset 1 and r = 0.42, P = 1.2 × 10 ⁻⁴ in dataset 2). On average, epigenetic age increased by 3.3 y for each 10 BMI units. The detected age acceleration in liver is not associated with the Nonalcoholic Fatty Liver Disease Activity Score or any of its component traits after adjustment for BMI. The 279 genes that are underexpressed in older liver samples are highly enriched (1.2 × 10 ⁻⁹) with nuclear mitochondrial genes that play a role in oxidative phosphorylation and electron transport. The epigenetic age acceleration, which is not reversible in the short term after rapid weight loss induced by bariatric surgery, may play a role in liver-related comorbidities of obesity, such as insulin resistance and liver cancer.

Background Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. Results We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis -acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis -meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans -meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). Conclusions Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .