Diet changes due to urbanization in South Africa are linked to microbiome and metabolome signatures of Westernization and colorectal cancer

Transition from traditional high-fiber to Western diets in urbanizing communities of Sub-Saharan Africa is associated with increased risk of non-communicable diseases (NCD), exemplified by colorectal cancer (CRC) risk. To investigate how urbanization gives rise to microbial patterns that may be amenable by dietary intervention, we analyzed diet intake, fecal 16 S bacteriome, virome, and metabolome in a cross-sectional study in healthy rural and urban Xhosa people (South Africa). Urban Xhosa individuals had higher intakes of energy (urban: 3,578 ± 455; rural: 2,185 ± 179 kcal/d), fat and animal protein. This was associated with lower fecal bacteriome diversity and a shift from genera favoring degradation of complex carbohydrates (e.g., Prevotella) to taxa previously shown to be associated with bile acid metabolism and CRC. Urban Xhosa individuals had higher fecal levels of deoxycholic acid, shown to be associated with higher CRC risk, but similar short-chain fatty acid concentrations compared with rural individuals. Fecal virome composition was associated with distinct gut bacterial communities across urbanization, characterized by different dominant host bacteria (urban: Bacteriodota; rural: unassigned taxa) and variable correlation with fecal metabolites and dietary nutrients. Food and skin microbiota samples showed compositional differences along the urbanization gradient. Rural-urban dietary transition in South Africa is linked to major changes in the gut microbiome and metabolome. Further studies are needed to prove cause and identify whether restoration of specific components of the traditional diet will arrest the accelerating rise in NCDs in Sub-Saharan Africa.

A164 IDENTIFYING THE MOST IMPORTANT PREDICTORS TO CORRELATE SERUM METABOLITES WITH MRE CHANGES IN PATIENTS WITH PEDIATRIC CROHN DISEASE

Background

Endoscopy has been the gold standard for assessing activity in Pediatric Crohn disease (pCD); however, it is limited by its invasiveness and partial assessment of small intestine and transmural inflammation. To that end, the Pediatric Inflammatory Crohn's MRE Index (PICMI) is a valid, reliable, non-invasive, and responsive index that includes transmural inflammation when assessing disease activity.

The pathogenesis of pCD remains poorly understood, but evidence suggests that endogenous metabolites produced in the intestinal tract might mediate pathogenesis. Despite the important applicability of metabolomics in increasing the understanding of pCD, there has been limited research on this topic.

Purpose

Serum metabolomic profiles are linked to disease activity in pediatric Crohn disease.

Method

ImageKids is a multicenter, prospective, observational cohort study, designed to develop PICMI for pCD. The study was conducted over 18 months with paired serum specimens collected at study initiation and completion for 56 pCD patients. Due to the long time between the visits and the fact that during the study variables that highly affect serum metabolites were not controlled, we considered each patient visit as an individual measure point. Metabolites were identified using a quantitative metabolomics approach through The Metabolomics Innovation Centre (TMIC; University of Alberta). Disease activity was determined by the cutoff values in the total PICMI score of each patient.

The most relevant serum metabolites were identified by medium-level and high-level variable selection analysis. Pearson correlation and hypothesis testing were used to select important metabolites. Decision trees, regularization techniques, and support vector machines were used to assess explicit importance of metabolites in disease activity.

Result(s)

This work provides a strategy to reduce a dimensional dataset from a metabolomic experiment. By medium-level selection analysis we were able to identify 117 statistical important metabolites for disease activity. The high-level selection analysis allowed to indicate the importance of the top 10 metabolites trough disease activity (defined by PICMI index). Results, also show that the evaluation of importance of metabolites through multivariate statistical models is dependent of the intrinsic variable selection model.

Figure 1 reveals that Tryptophan ranked highest in the feature importance scoring. Histidine, Methylhistidine, Citric acid, Isoleucine, and Decanoylcarnitine also correlated well with disease severity.

Image

Conclusion(s)

This work uses a unique approach of multivariate statistical analyses, to identify metabolites associated with pCD disease activity. Tryptophan has been previously identified as significantly altered in the blood of IBD patients compared to controls. Histidine is known to be involved in the mediation of oxidative stress, potentially influencing intestinal inflammation. These metabolites could serve as biomarkers and help define pCD pathogenesis.

Disclosure of Interest

None Declared

Artificial intelligence and amniotic fluid multiomics: prediction of perinatal outcome in asymptomatic women with short cervix

OBJECTIVE

To evaluate the application of artificial intelligence (AI), i.e. deep learning and other machine-learning techniques, to amniotic fluid (AF) metabolomics and proteomics, alone and in combination with sonographic, clinical and demographic factors, in the prediction of perinatal outcome in asymptomatic pregnant women with short cervical length (CL).

METHODS

AF samples, which had been obtained in the second trimester from asymptomatic women with short CL (< 15 mm) identified on transvaginal ultrasound, were analyzed. CL, funneling and the presence of AF 'sludge' were assessed in all cases close to the time of amniocentesis. A combination of liquid chromatography coupled with mass spectrometry and proton nuclear magnetic resonance spectroscopy-based metabolomics, as well as targeted proteomics analysis, including chemokines, cytokines and growth factors, was performed on the AF samples. To determine the robustness of the markers, we used six different machine-learning techniques, including deep learning, to predict preterm delivery < 34 weeks, latency period prior to delivery < 28 days after amniocentesis and requirement for admission to a neonatal intensive care unit (NICU). Omics biomarkers were evaluated alone and in combination with standard sonographic, clinical and demographic factors to predict outcome. Predictive accuracy was assessed using the area under the receiver-operating characteristics curve (AUC) with 95% CI, sensitivity and specificity.

RESULTS

Of the 32 patients included in the study, complete omics, demographic and clinical data and outcome information were available for 26. Of these, 11 (42.3%) patients delivered ≥ 34 weeks, while 15 (57.7%) delivered < 34 weeks. There was no statistically significant difference in CL between these two groups (mean ± SD, 11.2 ± 4.4 mm vs 8.9 ± 5.3 mm, P = 0.31). Using combined omics, demographic and clinical data, deep learning displayed good to excellent performance, with an AUC (95% CI) of 0.890 (0.810-0.970) for delivery < 34 weeks' gestation, 0.890 (0.790-0.990) for delivery < 28 days post-amniocentesis and 0.792 (0.689-0.894) for NICU admission. These values were higher overall than for the other five machine-learning methods, although each individual machine-learning technique yielded statistically significant prediction of the different perinatal outcomes.

CONCLUSIONS

This is the first study to report use of AI with AF proteomics and metabolomics and ultrasound assessment in pregnancy. Machine learning, particularly deep learning, achieved good to excellent prediction of perinatal outcome in asymptomatic pregnant women with short CL in the second trimester. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Metabolomic identification of diagnostic serum-based biomarkers for advanced stage melanoma

INTRODUCTION

Melanoma is a highly aggressive malignancy and is currently one of the fastest growing cancers worldwide. While early stage (I and II) disease is highly curable with excellent prognosis, mortality rates rise dramatically after distant spread. We sought to identify differences in the metabolome of melanoma patients to further elucidate the pathophysiology of melanoma and identify potential biomarkers to aid in earlier detection of recurrence.

METHODS

Using ¹H NMR and DI-LC-MS/MS, we profiled serum samples from 26 patients with stage III (nodal metastasis) or stage IV (distant metastasis) melanoma and compared their biochemical profiles with 46 age- and gender-matched controls.

RESULTS

We accurately quantified 181 metabolites in serum using a combination of ¹H NMR and DI-LC-MS/MS. We observed significant separation between cases and controls in the PLS-DA scores plot (permutation test p-value = 0.002). Using the concentrations of PC-aa-C40:3, DL-carnitine, octanoyl-L-carnitine, ethanol, and methylmalonyl-L-carnitine we developed a diagnostic algorithm with an AUC (95% CI) = 0.822 (0.665-0.979) with sensitivity and specificity of 100 and 56%, respectively. Furthermore, we identified arginine, proline, tryptophan, glutamine, glutamate, glutathione and ornithine metabolism to be significantly perturbed due to disease (p < 0.05).

CONCLUSION

Targeted metabolomic analysis demonstrated significant differences in metabolic profiles of advanced stage (III and IV) melanoma patients as compared to controls. These differences may represent a potential avenue for the development of multi-marker serum-based assays for earlier detection of recurrences, allow for newer, more effective targeted therapy when tumor burden is less, and further elucidate the pathophysiologic changes that occur in melanoma.

Epidemiology and costs associated with norovirus outbreaks in NHS Lothian, Scotland 2007-2009

Healthcare-associated gastroenteritis outbreaks are becoming more common and are recognized challenges in hospital and community settings. In Edinburgh [NHS (National Health Service) Lothian], all the hospitals and the community were actively monitored for outbreaks of gastroenteritis from September 2007 to June 2009. In total, 1732 patients and 599 healthcare staff were affected in 192 unit outbreaks. In the acute sector, 1368 patients (0.99 cases/1000 inpatient bed-days) and 406 healthcare staff (0.29 cases/1000 inpatient bed-days) were affected in 155 unit outbreaks (0.23 unit outbreaks/day). Noroviruses were detected in 142 outbreaks (74%); 50 were not laboratory confirmed but were presumed to be noroviruses on epidemiological grounds. The closure of affected units to new admissions resulted in the loss of 3678 bed-days. By extrapolation, lost bed-days and staff absence due to gastroenteritis outbreaks cost NHS Lothian £1.2 million for the two norovirus seasons. Outbreaks in which the affected unit was closed within the first three days of recognizing the index case were contained in a mean of six days, and outbreaks in units that were closed later persisted for a mean of seven days; this difference was not statistically significant. Rapid implementation of control measures was effective in the control of outbreaks.

Phenol-Explorer: an online comprehensive database on polyphenol contents in foods

A number of databases on the plant metabolome describe the chemistry and biosynthesis of plant chemicals. However, no such database is specifically focused on foods and more precisely on polyphenols, one of the major classes of phytochemicals. As antoxidants, polyphenols influence human health and may play a role in the prevention of a number of chronic diseases such as cardiovascular diseases, some cancers or type 2 diabetes. To determine polyphenol intake in populations and study their association with health, it is essential to have detailed information on their content in foods. However this information is not easily collected due to the variety of their chemical structures and the variability of their content in a given food. Phenol-Explorer is the first comprehensive web-based database on polyphenol content in foods. It contains more than 37 000 original data points collected from 638 scientific articles published in peer-reviewed journals. The quality of these data has been evaluated before they were aggregated to produce final representative mean content values for 502 polyphenols in 452 foods. The web interface allows making various queries on the aggregated data to identify foods containing a given polyphenol or polyphenols present in a given food. For each mean content value, it is possible to trace all original content values and their literature sources. Phenol-Explorer is a major step forward in the development of databases on food constituents and the food metabolome. It should help researchers to better understand the role of phytochemicals in the technical and nutritional quality of food, and food manufacturers to develop tailor-made healthy foods. Database URL: http://www.phenol-explorer.eu

The transcriptome of the implant biopsy identifies donor kidneys at increased risk of delayed graft function

Improved assessment of donor organ quality at time of transplantation would help in management of potentially usable organs. The transcriptome might correlate with risk of delayed graft function (DGF) better than conventional risk factors. Microarray results of 87 consecutive implantation biopsies taken postreperfusion in 42 deceased (DD) and 45 living (LD) donor kidneys were compared to clinical and histopathology-based scores. Unsupervised analysis separated the 87 kidneys into three groups: LD, DD1 and DD2. Kidneys in DD2 had a greater incidence of DGF (38.1 vs. 9.5%, p < 0.05) than those in DD1. Clinical and histopathological risk scores did not discriminate DD1 from DD2. A total of 1051 transcripts were differentially expressed between DD1 and DD2, but no transcripts separated DGF from immediate graft function (adjusted p < 0.01). Principal components analysis revealed a continuum from LD to DD1 to DD2, i.e. from best to poorest functioning kidneys. Within DD kidneys, the odds ratio for DGF was significantly increased with a transcriptome-based score and recipient age (p < 0.03) but not with clinical or histopathologic scores. The transcriptome reflects kidney quality and susceptibility to DGF better than available clinical and histopathological scoring systems.

Microarray analysis of rejection in human kidney transplants using pathogenesis-based transcript sets

Microarrays offer potential for objective diagnosis and insights into pathogenesis of allograft rejection. We used mouse transplants to annotate pathogenesis-based transcript sets (PBTs) that reflect major biologic events in allograft rejection-cytotoxic T-cell infiltration, interferon-gamma effects and parenchymal deterioration. We examined the relationship between PBT expression, histopathologic lesions and clinical diagnoses in 143 consecutive human kidney transplant biopsies for cause. PBTs correlated strongly with one another, indicating that transcriptome disturbances in renal transplants have a stereotyped internal structure. This disturbance was continuous, not dichotomous, across rejection and nonrejection. PBTs correlated with histopathologic lesions and were the highest in biopsies with clinically apparent rejection episodes. Surprisingly, antibody-mediated rejection had changes similar to T-cell mediated rejection. Biopsies lacking PBT disturbances did not have rejection. PBTs suggested that some current Banff histopathology criteria are unreliable, particularly at the cut-off between borderline and rejection. Results were validated in 51 additional biopsies. Thus many transcriptome changes previously described in rejection are features of a large-scale disturbance characteristic of rejection but occurring at lower levels in many forms of injury. PBTs represent a quantitative measure of the inflammatory disturbances in organ transplants, and a new window on the mechanisms of these changes.

Transplant glomerulopathy, late antibody-mediated rejection and the ABCD tetrad in kidney allograft biopsies for cause

To define the relative frequency of phenotypes of transplant glomerulopathy, we retrospectively reviewed the findings in 1036 biopsies for clinical indications from 1320 renal transplant patients followed in our clinics between 1997 and 2005. Transplant glomerulopathy, defined by double contours of glomerular basement membranes (D), was diagnosed in 53 biopsies (5.1%) from 41 patients (3.1%) at a median of 5.5 years post-transplant (range 3.8-381 months). In cases with D, we studied the frequency of circulating anti-HLA alloantibody (A), peritubular capillary basement membrane multilayering (B) and peritubular capillary C4d deposition (C). B was present in 48 (91%) of D biopsies. C4d staining by indirect immunofluorescence was detected in 18 of 50 D biopsies studied (36%). By Flow PRA Screening or ELISA, A was detected in 33 (70%) in 47 D cases with available sera, of which 28/33 or 85% were donor-specific. Class II (13/33) or class I and II (17/33) were more common than class I (3/33) antibodies. Thus 73% of transplant glomerulopathy has evidence of alloantibody-mediated injury (A and/or C), with ABCD and ABD being the common phenotypes in biopsies for cause. The remaining 27%, mostly BD, may be a different disease or a stage in which A and C are undetectable.

Molecular mimicry of human tumor antigen by heavy chain CDR3 sequence of the anti-idiotypic antibody

We isolated and characterized an anti-idiotype monoclonal antibody (AR42.1) which is capable of mimicking a distinct and specific epitope of MUC-1 antigen. The cDNA sequences coding for the AR42.1 variable regions were determined. We found significant amino acid homology between complementary determining regions 3 (CDR3) in the heavy chain of AR42.1 and the determinant epitope sequence of MUC-1. This 10 amino acid sequence may represent an "internal image" of the anti-idiotype antibody to the MUC-1 antigen, and could be used for development of a MUC-1 surrogate for immunotherapy.

Construction and expression of bi-functional proteins of single-chain Fv with effector domains

We fused various polypeptide extensions to the C-termini of single chain Fv (scFv) and disulfide-stabilized Fv (dsFv) fragments to facilitate detection of bi-functional proteins or to add biological effector domains, which included the human metallothionein (HMT) motif and biotin mimetic sequence. These bi-functional proteins were expressed and secreted in a recombinant Pichia pastoris system and showed specific anti-idiotype binding activity, as determined by competitive radioimmunoassaying. However, the fusion protein constructed with dsFv- HMT, but not scFv-HMT, had lost this binding activity. The interruption of the structural conformation as a result in dsFv-HMT may be explained by the interactions between the cysteines engineered in dsFv domains and the cysteines in the HMT region.

Vl-linker-Vh orientation-dependent expression of single chain Fv-containing an engineered disulfide-stabilized bond in the framework regions

Single chain Fv fragments (scFv) derived from an antibody, MAb 174H.64 (Tru-ScintRSQ kit, Biomira), were constructed in both orientations, i.e. Vh-linker-Vl and Vl-linker-Vh, but only the latter form could be expressed and secreted in the recombinant Pichia pastoris system. The secreted scFv protein showed specific anti-idiotype binding activity. Additionally, the molecular graphic modeling has been used to identify a possible site for the introduction of an interchain disulfide bond in the framework region of Fv. These Cys-modifications of the sites were done using a method of PCR-mediated mutagenesis. The engineered protein (disulfide-stabilized Fv: dsFv) was expressed and tested for its binding activity. It was found that dsFv was as active as the corresponding scFv and more stable as determined by competitive radioimmunoassay.

Convention cities: San Juan

Images

Convention cities in Scotland

Images

Convention cities: Heidelberg

Images

Convention cities: Buenos Aires

Images

Tahiti: land of Gauguin

Images

Convention cities: Sydney

Images

Convention cities: Las Vegas

Images

Convention cities: Seattle

Images

Convention cities: Paris

Images

Convention cities: Acapulco

Images

Convention cities: Rio de Janeiro

Images

Convention cities: San Diego

Images

Scotland: sailing the Western Isles

Images

The vacation forecast for 1984

Images

Convention cities: Honolulu

Images

Convention cities: Helsinki

Images

Convention cities: Lisbon

Images

Convention cities: Singapore

Images

Convention cities: San Francisco

Images

Convention cities: Monte Carlo

Images

Cruising the Greek islands

Images

Sports medicine: specialized care for the athlete in everyone

Images