The person-to-person transmission landscape of the gut and oral microbiomes.

The human microbiome is an integral component of the human body and a co-determinant of several health conditions1,2. However, the extent to which interpersonal relations shape the individual genetic makeup of the microbiome and its transmission within and across populations remains largely unknown3,4. Here, capitalizing on more than 9,700 human metagenomes and computational strain-level profiling, we detected extensive bacterial strain sharing across individuals (more than 10 million instances) with distinct mother-to-infant, intra-household and intra-population transmission patterns. Mother-to-infant gut microbiome transmission was considerable and stable during infancy (around 50% of the same strains among shared species (strain-sharing rate)) and remained detectable at older ages. By contrast, the transmission of the oral microbiome occurred largely horizontally and was enhanced by the duration of cohabitation. There was substantial strain sharing among cohabiting individuals, with 12% and 32% median strain-sharing rates for the gut and oral microbiomes, and time since cohabitation affected strain sharing more than age or genetics did. Bacterial strain sharing additionally recapitulated host population structures better than species-level profiles did. Finally, distinct taxa appeared as efficient spreaders across transmission modes and were associated with different predicted bacterial phenotypes linked with out-of-host survival capabilities. The extent of microorganism transmission that we describe underscores its relevance in human microbiome studies5, especially those on non-infectious, microbiome-associated diseases.

A reference map of potential determinants for the human serum metabolome.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.

Escape from X-inactivation in twins exhibits intra- and inter-individual variability across tissues and is heritable.

X-chromosome inactivation (XCI) silences one X in female cells to balance sex-differences in X-dosage. A subset of X-linked genes escape XCI, but the extent to which this phenomenon occurs and how it varies across tissues and in a population is as yet unclear. To characterize incidence and variability of escape across individuals and tissues, we conducted a transcriptomic study of escape in adipose, skin, lymphoblastoid cell lines and immune cells in 248 healthy individuals exhibiting skewed XCI. We quantify XCI escape from a linear model of genes' allelic fold-change and XIST-based degree of XCI skewing. We identify 62 genes, including 19 lncRNAs, with previously unknown patterns of escape. We find a range of tissue-specificity, with 11% of genes escaping XCI constitutively across tissues and 23% demonstrating tissue-restricted escape, including cell type-specific escape across immune cells of the same individual. We also detect substantial inter-individual variability in escape. Monozygotic twins share more similar escape than dizygotic twins, indicating that genetic factors may underlie inter-individual differences in escape. However, discordant escape also occurs within monozygotic co-twins, suggesting environmental factors also influence escape. Altogether, these data indicate that XCI escape is an under-appreciated source of transcriptional differences, and an intricate phenotype impacting variable trait expressivity in females.

Vitamin A carotenoids, but not retinoids, mediate the impact of a healthy diet on gut microbial diversity.

BACKGROUND: Vitamin A is essential for physiological processes like vision and immunity. Vitamin A's effect on gut microbiome composition, which affects absorption and metabolism of other vitamins, is still unknown. Here we examined the relationship between gut metagenome composition and six vitamin A-related metabolites (two retinoid: -retinol, 4 oxoretinoic acid (oxoRA) and four carotenoid metabolites, including beta-cryptoxanthin and three carotene diols). METHODS: We included 1053 individuals from the TwinsUK cohort with vitamin A-related metabolites measured in serum and faeces, diet history, and gut microbiome composition assessed by shotgun metagenome sequencing. Results were replicated in 327 women from the ZOE PREDICT-1 study. RESULTS: Five vitamin A-related serum metabolites were positively correlated with microbiome alpha diversity (r = 0.15 to r = 0.20, p < 4 × 10-6). Carotenoid compounds were positively correlated with the short-chain fatty-acid-producing bacteria Faecalibacterium prausnitzii and Coprococcus eutactus. Retinol was not associated with any microbial species. We found that gut microbiome composition could predict circulating levels of carotenoids and oxoretinoic acid with AUCs ranging from 0.66 to 0.74 using random forest models, but not retinol (AUC = 0.52). The healthy eating index (HEI) was strongly associated with gut microbiome diversity and with all carotenoid compounds, but not retinoids. We investigated the mediating role of carotenoid compounds on the effect of a healthy diet (HEI) on gut microbiome diversity, finding that carotenoids significantly mediated between 18 and 25% of the effect of HEI on gut microbiome alpha diversity. CONCLUSIONS: Our results show strong links between circulating carotene compounds and gut microbiome composition and potential links to a healthy diet pattern.

Treatment response in rheumatoid arthritis is predicted by the microbiome: a large observational study in UK DMARD-naïve patients.

OBJECTIVES: Disease-modifying antirheumatic drugs (DMARDs) are first line treatment in rheumatoid arthritis (RA). Treatment response to DMARDs is patient-specific, dose efficacy is difficult to predict and long-term results variable. The gut microbiota are known to play a pivotal role in prodromal and early-disease RA, manifested by Prevotella spp. enrichment. The clinical response to therapy may be mediated by microbiota, and large-scale studies assessing the microbiome are few. This study assessed whether microbiome signals were associated with, and predictive of, patient response to DMARD-treatment. Accurate early identification of those who will respond poorly to DMARD therapy would allow selection of alternative treatment (e.g. biologic therapy), and potentially improve patient outcome. METHODS: A multicentre, longitudinal, observational study of stool- and saliva microbiome was performed in DMARD-naïve, newly diagnosed RA patients during introduction of DMARD treatment. Clinical data and samples were collected at baseline (n = 144) in DMARD-naïve patients and at six weeks (n = 117) and 12 weeks (n = 95) into DMARD-therapy. Samples collected (n = 365 stool, n = 365 saliva) underwent shotgun sequencing. Disease activity measures were collected at each timepoint and minimal clinically important improvement determined. RESULTS: In total, 26 stool microbes were found to decrease in those manifesting a minimal clinically important improvement. Prevotella spp. and Streptococcus spp. were the predominant taxa to decline following six weeks and 12 weeks of DMARDs, respectively. Furthermore, baseline microbiota of DMARD-naïve patients were indicative of future response. CONCLUSION: DMARDs appear to restore a perturbed microbiome to a eubiotic state. Moreover, microbiome status can be used to predict likelihood of patient response to DMARD.

Total serum N-glycans associate with response to immune checkpoint inhibition therapy and survival in patients with advanced melanoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of melanoma and other cancers. However, no reliable biomarker of survival or response has entered the clinic to identify those patients with melanoma who are most likely to benefit from ICIs. Glycosylation affects proteins and lipids' structure and functions. Tumours are characterized by aberrant glycosylation which may contribute to their progression and hinder an effective antitumour immune response. METHODS: We aim at identifying novel glyco-markers of response and survival by leveraging the N-glycome of total serum proteins collected in 88 ICI-naive patients with advanced melanoma from two European countries. Samples were collected before and during ICI treatment. RESULTS: We observe that responders to ICIs present with a pre-treatment N-glycome profile significantly shifted towards higher abundancy of low-branched structures containing lower abundances of antennary fucose, and that this profile is positively associated with survival and a better predictor of response than clinical variables alone. CONCLUSION: While changes in serum protein glycosylation have been previously implicated in a pro-metastatic melanoma behaviour, we show here that they are also associated with response to ICI, opening new avenues for the stratification of patients and the design of adjunct therapies aiming at improving immune response.

Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome.

BACKGROUND: Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. RESULTS: According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17 ± 0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18 ± 11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41 ± 0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30 ± 0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed than an increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation. CONCLUSIONS: Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).

Cutaneous manifestations of SARS-CoV-2 infection during the Delta and Omicron waves in 348 691 UK users of the UK ZOE COVID Study app.

BACKGROUND: Symptoms of SARS-CoV-2 infection have differed during the different waves of the pandemic but little is known about how cutaneous manifestations have changed. OBJECTIVES: To investigate the diagnostic value, frequency and duration of cutaneous manifestations of SARS-CoV-2 infection and to explore their variations between the Delta and Omicron waves of the pandemic. METHODS: In this retrospective study, we used self-reported data from 348 691 UK users of the ZOE COVID Study app, matched 1 : 1 for age, sex, vaccination status and self-reported eczema diagnosis between the Delta and Omicron waves, to assess the diagnostic value, frequency and duration of five cutaneous manifestations of SARS-CoV-2 infection (acral, burning, erythematopapular and urticarial rash, and unusual hair loss), and how these changed between waves. We also investigated whether vaccination had any effect on symptom frequency. RESULTS: We show a significant association between any cutaneous manifestations and a positive SARS-CoV-2 test result, with a diagnostic value higher in the Delta compared with the Omicron wave (odds ratio 2·29, 95% confidence interval 2·22-2·36, P < 0·001; and odds ratio 1·29, 95% confidence interval 1·26-1·33, P < 0·001, respectively). Cutaneous manifestations were also more common with Delta vs. Omicron (17·6% vs. 11·4%, respectively) and had a longer duration. During both waves, cutaneous symptoms clustered with other frequent symptoms and rarely (in < 2% of the users) as first or only clinical sign of SARS-CoV-2 infection. Finally, we observed that vaccinated and unvaccinated users showed similar odds of presenting with a cutaneous manifestation, apart from burning rash, where the odds were lower in vaccinated users. CONCLUSIONS: Cutaneous manifestations are predictive of SARS-CoV-2 infection, and their frequency and duration have changed with different variants. Therefore, we advocate for their inclusion in the list of clinically relevant COVID-19 symptoms and suggest that their monitoring could help identify new variants. What is already known about this topic? Several studies during the wildtype COVID-19 wave reported that patients presented with common skin-related symptoms. It has been observed that COVID-19 symptoms differ among variants. No study has focused on how skin-related symptoms have changed across different variants. What does this study add? We showed, in a community-based retrospective study including over 348 000 individuals, that the presence of cutaneous symptoms is predictive of SARS-CoV-2 infection during the Delta and Omicron waves and that this diagnostic value, along with symptom frequency and duration, differs between variants. We showed that infected vaccinated and unvaccinated individuals reported similar skin-related symptoms during the Delta and Omicron waves, with only burning rashes being less common after vaccination.

O- and N-Glycosylation of Serum Immunoglobulin A is Associated with IgA Nephropathy and Glomerular Function.

BACKGROUND: IgA nephropathy (IgAN) is the most common primary glomerular disease worldwide and is a leading cause of renal failure. The disease mechanisms are not completely understood, but a higher abundance of galactose-deficient IgA is recognized to play a crucial role in IgAN pathogenesis. Although both types of human IgA (IgA1 and IgA2) have several N-glycans as post-translational modification, only IgA1 features extensive hinge-region O-glycosylation. IgA1 galactose deficiency on the O-glycans is commonly detected by a lectin-based method. To date, limited detail is known about IgA O- and N-glycosylation in IgAN. METHODS: To gain insights into the complex O- and N-glycosylation of serum IgA1 and IgA2 in IgAN, we used liquid chromatography-mass spectrometry (LC-MS) for the analysis of tryptic glycopeptides of serum IgA from 83 patients with IgAN and 244 age- and sex-matched healthy controls. RESULTS: Multiple structural features of N-glycosylation of IgA1 and IgA2 were associated with IgAN and glomerular function in our cross-sectional study. These features included differences in galactosylation, sialylation, bisection, fucosylation, and N-glycan complexity. Moreover, IgA1 O-glycan sialylation was associated with both the disease and glomerular function. Finally, glycopeptides were a better predictor of IgAN and glomerular function than galactose-deficient IgA1 levels measured by lectin-based ELISA. CONCLUSIONS: Our high-resolution data suggest that IgA O- and N-glycopeptides are promising targets for future investigations on the pathophysiology of IgAN and as potential noninvasive biomarkers for disease prediction and deteriorating kidney function.

Cancer and Risk of COVID-19 Through a General Community Survey.

Individuals with cancer may be at high risk for coronavirus disease 2019 (COVID-19) and adverse outcomes. However, evidence from large population-based studies examining whether cancer and cancer-related therapy exacerbates the risk of COVID-19 infection is still limited. Data were collected from the COVID Symptom Study smartphone application since March 29 through May 8, 2020. Among 23,266 participants with cancer and 1,784,293 without cancer, we documented 10,404 reports of a positive COVID-19 test. Compared with participants without cancer, those living with cancer had a 60% increased risk of a positive COVID-19 test. Among patients with cancer, current treatment with chemotherapy or immunotherapy was associated with a 2.2-fold increased risk of a positive test. The association between cancer and COVID-19 infection was stronger among participants >65 years and males. Future studies are needed to identify subgroups by tumor types and treatment regimens who are particularly at risk for COVID-19 infection and adverse outcomes.