Claire J. Steves

Proton pump inhibitors alter the composition of the gut microbiota

Objective Proton 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. Design We 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microbiome using 16S ribosomal RNA amplification from faecal samples of 1827 healthy twins, replicating results within unpublished data from an interventional study. Results We 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. Conclusions Our 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.

Signatures of early frailty in the gut microbiota.

BackgroundFrailty is arguably the biggest problem associated with population ageing, and associates with gut microbiome composition in elderly and care-dependent individuals. Here we characterize frailty associations with the gut microbiota in a younger community dwelling population, to identify targets for intervention to encourage healthy ageing.MethodWe analysed 16S rRNA gene sequence data derived from faecal samples obtained from 728 female twins. Frailty was quantified using a frailty index (FI). Mixed effects models were used to identify associations with diversity, operational taxonomic units (OTUs) and taxa. OTU associations were replicated in the Eldermet cohort. Phenotypes were correlated with modules of OTUs collapsed by co-occurrence.ResultsFrailty negatively associated with alpha diversity of the gut microbiota. Models considering a number of covariates identified 637 OTUs associated with FI. Twenty-two OTU associations were significant independent of alpha diversity. Species more abundant with frailty included Eubacterium dolichum and Eggerthella lenta. A Faecalibacterium prausnitzii OTU was less abundant in frailer individuals, and retained significance in discordant twin analysis. Sixty OTU associations were replicated in the Eldermet cohort. OTU co-occurrence modules had mutually exclusive associations between frailty and alpha diversity.ConclusionsThere was a striking negative association between frailty and gut microbiota diversity, underpinned by specific taxonomic associations. Whether these relationships are causal or consequential is unknown. Nevertheless, they represent targets for diagnostic surveillance, or for intervention studies to improve vitality in ageing.

Ageing, genes, environment and epigenetics: what twin studies tell us now, and in the future

Compared with younger people, older people are much more variable in their organ function, and these large individual differences contribute to the complexity of geriatric medicine. What determines this variability? Is it due to the accumulation of different life experiences, or because of the variation in the genes we are born with, or an interaction of both? This paper reviews key findings from ageing twin cohorts probing these questions. Twin studies are the perfect natural experiment to dissect out genes and life experiences. We discuss the paradox that ageing is strongly determined by heritable factors (an influence that often gets stronger with time), yet longevity and lifespan seem not to be so heritable. We then focus on the intriguing question of why DNA sequence-identical twins might age differently. Animal studies are increasingly showing that epigenetic modifications occurring in early development and adulthood, might be key to ageing phenomena but this is difficult to investigate longitudinally in human populations, due to ethical problems of intervention and long lifespan. We propose that identical twin studies using new and existing cohorts may be useful human models in which to investigate the interaction between the environment and genetics, mediated by epigenetic modifications.

Shotgun Metagenomics of 250 Adult Twins Reveals Genetic and Environmental Impacts on the Gut Microbiome

The gut microbiota has been typically viewed as an environmental factor for human health. Twins are well suited for investigating the concordance of their gut microbiomes and decomposing genetic and environmental influences. However, existing twin studies utilizing metagenomic shotgun sequencing have included only a few samples. Here, we sequenced fecal samples from 250 adult twins in the TwinsUK registry and constructed a comprehensive gut microbial reference gene catalog. We demonstrate heritability of many microbial taxa and functional modules in the gut microbiome, including those associated with diseases. Moreover, we identified 8 million SNPs in the gut microbiome and observe a high similarity in microbiome SNPs between twins that slowly decreases after decades of living apart. The results shed new light on the genetic and environmental influences on the composition and function of the gut microbiome that could relate to risk of complex diseases.

Circulating Proteomic Signatures of Chronological Age

To elucidate the proteomic features of aging in plasma, the subproteome targeted by the SOMAscan assay was profiled in blood samples from 202 females from the TwinsUK cohort. Findings were replicated in 677 independent individuals from the AddNeuroMed, Alzheimer’s Research UK, and Dementia Case Registry cohorts. Results were further validated using RNAseq data from whole blood in TwinsUK and the most significant proteins were tested for association with aging-related phenotypes after adjustment for age. Eleven proteins were associated with chronological age and were replicated at protein level in an independent population. These were further investigated at gene expression level in 384 females from the TwinsUK cohort. The two most strongly associated proteins were chordin-like protein 1 (meta-analysis β [SE] = 0.013 [0.001], p = 3.66 × 10−46) and pleiotrophin (0.012 [0.005], p = 3.88 × 10−41). Chordin-like protein 1 was also significantly correlated with birthweight (0.06 [0.02], p = 0.005) and with the individual Framingham 10-years cardiovascular risk scores in TwinsUK (0.71 [0.18], p = 9.9 × 10−5). Pleiotrophin is a secreted growth factor with a plethora of functions in multiple tissues and known to be a marker for cardiovascular risk and osteoporosis. Our study highlights the importance of proteomics to identify some molecular mechanisms involved in human health and aging.

Gut microbiome diversity and high-fibre intake are related to lower long-term weight gain

Background:Cross-sectional studies suggest that the microbes in the human gut have a role in obesity by influencing the human body’s ability to extract and store calories. The aim of this study was to assess if there is a correlation between change in body weight over time and gut microbiome composition.Methods:We analysed 16S ribosomal RNA gene sequence data derived from the faecal samples of 1632 healthy females from TwinsUK to investigate the association between gut microbiome measured cross-sectionally and longitudinal weight gain (adjusted for caloric intake and baseline body mass index). Dietary fibre intake was investigated as a possible modifier.Results:Less than half of the variation in long-term weight change was found to be heritable (h2=0.41 (0.31, 0.47)). Gut microbiota diversity was negatively associated with long-term weight gain, whereas it was positively correlated with fibre intake. Nine bacterial operational taxonomic units (OTUs) were significantly associated with weight gain after adjusting for covariates, family relatedness and multiple testing (false discovery rate <0.05). OTUs associated with lower long-term weight gain included those assigned to Ruminococcaceae (associated in mice with improved energy metabolism) and Lachnospiraceae. A Bacterioides species OTU was associated with increased risk of weight gain but this appears to be driven by its correlation with lower levels of diversity.Conclusions:High gut microbiome diversity, high-fibre intake and OTUs implicated in animal models of improved energy metabolism are all correlated with lower term weight gain in humans independently of calorie intake and other confounders.

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

&NA; Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people. Deviations from healthy brain ageing have been associated with cognitive impairment and disease. Here we sought to further establish the credentials of ‘brain‐predicted age’ as a biomarker of individual differences in the brain ageing process, using a predictive modelling approach based on deep learning, and specifically convolutional neural networks (CNN), and applied to both pre‐processed and raw T1‐weighted MRI data. Firstly, we aimed to demonstrate the accuracy of CNN brain‐predicted age using a large dataset of healthy adults (N = 2001). Next, we sought to establish the heritability of brain‐predicted age using a sample of monozygotic and dizygotic female twins (N = 62). Thirdly, we examined the test‐retest and multi‐centre reliability of brain‐predicted age using two samples (within‐scanner N = 20; between‐scanner N = 11). CNN brain‐predicted ages were generated and compared to a Gaussian Process Regression (GPR) approach, on all datasets. Input data were grey matter (GM) or white matter (WM) volumetric maps generated by Statistical Parametric Mapping (SPM) or raw data. CNN accurately predicted chronological age using GM (correlation between brain‐predicted age and chronological age r = 0.96, mean absolute error [MAE] = 4.16 years) and raw (r = 0.94, MAE = 4.65 years) data. This was comparable to GPR brain‐predicted age using GM data (r = 0.95, MAE = 4.66 years). Brain‐predicted age was a heritable phenotype for all models and input data (h2 ≥ 0.5). Brain‐predicted age showed high test‐retest reliability (intraclass correlation coefficient [ICC] = 0.90–0.99). Multi‐centre reliability was more variable within high ICCs for GM (0.83–0.96) and poor‐moderate levels for WM and raw data (0.51–0.77). Brain‐predicted age represents an accurate, highly reliable and genetically‐influenced phenotype, that has potential to be used as a biomarker of brain ageing. Moreover, age predictions can be accurately generated on raw T1‐MRI data, substantially reducing computation time for novel data, bringing the process closer to giving real‐time information on brain health in clinical settings. HighlightsChronological age can be accurately predicted using convolutional neural networks.Age predicted is accurate even using raw structural neuroimaging data.Brain‐predicted age can be generated in a clinically applicable timeframe.Brain‐predicted age is significantly heritable.Brain‐predicted age is highly reliable, both within and between scanners.

Dietary Magnesium Is Positively Associated With Skeletal Muscle Power and Indices of Muscle Mass and May Attenuate the Association Between Circulating C-Reactive Protein and Muscle Mass in Women

Age-related loss of skeletal muscle mass and strength are risk factors for sarcopenia, osteoporosis, falls, fractures, frailty, and mortality. Dietary magnesium (Mg) could play a role in prevention of age-related loss of skeletal muscle mass, power, and strength directly through physiological mechanisms or indirectly through an impact on chronic low-grade inflammation, itself a risk factor for loss of skeletal muscle mass and strength. In a cross-sectional study of 2570 women aged 18 to 79 years, we examined associations between intakes of Mg, estimated using a food-frequency questionnaire (FFQ), dual-energy X-ray absorptiometry (DXA)-derived measures of muscle mass (fat-free mass as a percentage of body weight [FFM%], fat-free mass index [FFMI, kg/m(2)]), leg explosive power (LEP), and grip strength (n = 949 only). We also examined associations between circulating hs-CRP (C-reactive protein) and muscle mass and LEP, and explored the potential attenuation of these relationships by Mg. We compared our findings with those of age and protein intake. Endpoints were calculated by quintile of Mg and adjusted for relevant confounders. Significant positive associations were found between a higher Mg and indices of skeletal muscle mass and LEP, and also with hs-CRP, after adjustment for covariates. Contrasting extreme quintiles of Mg intake showed differences of 2.6% for FFM% (p trend < 0.001), 0.4 kg/m(2) for FFMI (p trend = 0.005), and 19.6 watts/kg for LEP (p trend < 0.001). Compared with protein, these positive associations were 7 times greater for FFM% and 2.5 times greater for LEP. We also found that higher hs-CRP was negatively associated with skeletal muscle mass and, in statistical modeling, that a higher dietary Mg attenuated this negative relationship by 6.5%, with greater attenuation in women older than 50 years. No association was found between Mg and grip strength. Our results suggest that dietary magnesium may aid conservation of age-related loss of skeletal muscle mass and power in women of all ages.

The Microbiome and Musculoskeletal Conditions of Aging: A Review of Evidence for Impact and Potential Therapeutics

Recently, we have begun to realize that the billions of microorganisms living in symbiosis with us have an influence on disease. Evidence is mounting that the alimentary tract microbiome, in particular, influences both host metabolic potential and its innate and adaptive immune system. Inflammatory states characterize many bone and joint diseases of aging. This prompts the hypothesis that the gut microbiome could alter the inflammatory state of the individual and directly influence the development of these common and burdensome clinical problems. Because the microbiome is easily modifiable, this could have major therapeutic impact. This perspective discusses evidence to date on the role of the microbiome and the highly prevalent age-related disorders of osteoporosis, osteoarthritis, gout, rheumatoid arthritis, sarcopenia, and frailty. It also reviews data on the effects of probiotics and prebiotic interventions in animal and human models. Despite suggestive findings, research to date is not conclusive, and we identify priorities for research to substantiate and translate findings.

Omega-3 fatty acids correlate with gut microbiome diversity and production of N-carbamylglutamate in middle aged and elderly women

Omega-3 fatty acids may influence human physiological parameters in part by affecting the gut microbiome. The aim of this study was to investigate the links between omega-3 fatty acids, gut microbiome diversity and composition and faecal metabolomic profiles in middle aged and elderly women. We analysed data from 876 twins with 16S microbiome data and DHA, total omega-3, and other circulating fatty acids. Estimated food intake of omega-3 fatty acids were obtained from food frequency questionnaires. Both total omega-3and DHA serum levels were significantly correlated with microbiome alpha diversity (Shannon index) after adjusting for confounders (DHA Beta(SE) = 0.13(0.04), P = 0.0006 total omega-3: 0.13(0.04), P = 0.001). These associations remained significant after adjusting for dietary fibre intake. We found even stronger associations between DHA and 38 operational taxonomic units (OTUs), the strongest ones being with OTUs from the Lachnospiraceae family (Beta(SE) = 0.13(0.03), P = 8 × 10−7). Some of the associations with gut bacterial OTUs appear to be mediated by the abundance of the faecal metabolite N-carbamylglutamate. Our data indicate a link between omega-3 circulating levels/intake and microbiome composition independent of dietary fibre intake, particularly with bacteria of the Lachnospiraceae family. These data suggest the potential use of omega-3 supplementation to improve the microbiome composition.