Changes in gut microbiota and lactose intolerance symptoms before and after daily lactose supplementation in individuals with the lactase nonpersistent genotype.

BACKGROUND: Approximately 70%-100% of the Asian adult population is lactase nonpersistent (LNP). The literature shows that many individuals with the LNP-genotype can consume ≤12 g of lactose without experiencing gastrointestinal discomfort. Repetitive consumption of lactose may reduce intolerance symptoms via adaptation of the gut microbiota. OBJECTIVE: This study aimed to assess the effects of daily consumption of incremental lactose doses on microbiota composition and function, and intolerance symptoms. METHODS: Twenty-five healthy adults of Asian origin, carrying the LNP-genotype were included in this 12-wk before and after intervention trial. Participants consumed gradually increasing lactose doses from 3 to 6 g to 12 g twice daily, each daily dose of 6 g, 12 g, or 24 g being provided for 4 consecutive weeks. Participants handed-in repeated stool samples and underwent a 25 g lactose challenge hydrogen breath test (HBT) before and after the 12-wk intervention. Daily gastrointestinal symptoms and total symptom scores (TSSs) during the lactose challenge were recorded. RESULTS: A significant increase from 5.5% ± 7.6% to 10.4% ± 9.6% was observed in Bifidobacterium relative abundance after the intervention (P = 0.009), accompanied by a 2-fold increase (570 ± 269 U/g; P < 0.001) in fecal ß-galactosidase activity compared with baseline (272 ± 158 U/g). A 1.5-fold decrease (incremental area under the curve; P = 0.01) in expired hydrogen was observed during the second HBT (38 ± 35 ppm·min), compared with the baseline HBT (57 ± 38 ppm·min). There was a nonsignificant decrease in TSS (10.6 ± 8.3 before compared with 8.1 ± 7.2 after intervention; P = 0.09). Daily consumption of lactose was well tolerated, with mild to no gastrointestinal complaints reported during the intervention. CONCLUSIONS: Increased levels of Bifidobacterium indicate an adaptation of the gut microbiota upon repetitive consumption of incremental doses of lactose, which was well tolerated as demonstrated by reduced expired hydrogen concentrations during the second 25-g lactose HBT. Bifidobacteria metabolize lactose without gas production thereby potentially reducing intestinal gas formation in the gut of individuals with the LNP-genotype. This increased lactose tolerance possibly lifts the necessity to remove nutrient-rich dairy foods completely from the diet. The trial is registered at the International Clinical Trials Registry Platform: NL9516. The effect of dietary lactose in lactase nonpersistent individuals on gut microbiota.

Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography.

OBJECTIVE: Machine learning (ML) approaches have the potential to uncover regular patterns in multi-layered data. Here we applied self-organizing maps (SOMs) to detect such patterns with the aim to better predict in-stent restenosis (ISR) at surveillance angiography 6 to 8 months after percutaneous coronary intervention with stenting. METHODS: In prospectively collected data from 10,004 patients receiving percutaneous coronary intervention (PCI) for 15,004 lesions, we applied SOMs to predict ISR angiographically 6-8 months after index procedure. SOM findings were compared with results of conventional uni- and multivariate analyses. The predictive value of both approaches was assessed after random splitting of patients into training and test sets (50:50). RESULTS: Conventional multivariate analyses revealed 10, mostly known, predictors for restenosis after coronary stenting: balloon-to-vessel ratio, complex lesion morphology, diabetes mellitus, left main stenting, stent type (bare metal vs. first vs. second generation drug eluting stent), stent length, stenosis severity, vessel size reduction, and prior bypass surgery. The SOM approach identified all these and nine further predictors, including chronic vessel occlusion, lesion length, and prior PCI. Moreover, the SOM-based model performed well in predicting ISR (AUC under ROC: 0.728); however, there was no meaningful advantage in predicting ISR at surveillance angiography in comparison with the conventional multivariable model (0.726, p = 0.3). CONCLUSIONS: The agnostic SOM-based approach identified-without clinical knowledge-even more contributors to restenosis risk. In fact, SOMs applied to a large prospectively sampled cohort identified several novel predictors of restenosis after PCI. However, as compared with established covariates, ML technologies did not improve identification of patients at high risk for restenosis after PCI in a clinically relevant fashion.

Integrating Clinical and Epidemiologic Data on Allergic Diseases Across Birth Cohorts: A Harmonization Study in the Mechanisms of the Development of Allergy Project.

The numbers of international collaborations among birth cohort studies designed to better understand asthma and allergies have increased in the last several years. However, differences in definitions and methods preclude direct pooling of original data on individual participants. As part of the Mechanisms of the Development of Allergy (MeDALL) Project, we harmonized data from 14 birth cohort studies (each with 3-20 follow-up periods) carried out in 9 European countries during 1990-1998 or 2003-2009. The harmonization process followed 6 steps: 1) organization of the harmonization panel; 2) identification of variables relevant to MeDALL objectives (candidate variables); 3) proposal of a definition for each candidate variable (reference definition); 4) assessment of the compatibility of each cohort variable with its reference definition (inferential equivalence) and classification of this inferential equivalence as complete, partial, or impossible; 5) convocation of a workshop to agree on the reference definitions and classifications of inferential equivalence; and 6) preparation and delivery of data through a knowledge management portal. We agreed on 137 reference definitions. The inferential equivalence of 3,551 cohort variables to their corresponding reference definitions was classified as complete, partial, and impossible for 70%, 15%, and 15% of the variables, respectively. A harmonized database was delivered to MeDALL investigators. In asthma and allergy birth cohorts, the harmonization of data for pooled analyses is feasible, and high inferential comparability may be achieved. The MeDALL harmonization approach can be used in other collaborative projects.

Does early onset asthma increase childhood obesity risk? A pooled analysis of 16 European cohorts.

The parallel epidemics of childhood asthma and obesity over the past few decades have spurred research into obesity as a risk factor for asthma. However, little is known regarding the role of asthma in obesity incidence. We examined whether early-onset asthma and related phenotypes are associated with the risk of developing obesity in childhood.This study includes 21 130 children born from 1990 to 2008 in Denmark, France, Germany, Greece, Italy, The Netherlands, Spain, Sweden and the UK. We followed non-obese children at 3-4 years of age for incident obesity up to 8 years of age. Physician-diagnosed asthma, wheezing and allergic rhinitis were assessed up to 3-4 years of age.Children with physician-diagnosed asthma had a higher risk for incident obesity than those without asthma (adjusted hazard ratio (aHR) 1.66, 95% CI 1.18-2.33). Children with active asthma (wheeze in the last 12 months and physician-diagnosed asthma) exhibited a higher risk for obesity (aHR 1.98, 95% CI 1.31-3.00) than those without wheeze and asthma. Persistent wheezing was associated with increased risk for incident obesity compared to never wheezers (aHR 1.51, 95% CI 1.08-2.09).Early-onset asthma and wheezing may contribute to an increased risk of developing obesity in later childhood.