Nestlé Institute of Health Science/ Nestlé Research
Department of Gastro-Intestinal Health
Shaillay Kumar Dogra is a computational biologist with expertise in Microbiome. He has extensively studied Early Life Microbiome (ELM) in Infants in different Cohorts and interventional Clinical Trials across geographies. He has published methods and designed a cohort to further study ELM. His current focus in on understanding Microbiome Maturation in infants and it’s link with nutrition and health. In Adults, he has built on concept of Microbiome Resilience and designed a nutritional intervention to improve Resilience, which was successfully tested in an interventional Clinical Trial. Further in Adults, he has worked on Machine Learning based applications to assess gut Microbiome Markers and to improve these by nutritional means. Shaillay has ~20 years Industry experience and has co-authored over 22 peer-reviewed papers, filed over 15 patents as a co-inventor and peer reviewed more than 200 manuscripts.

Presenter of 4 Presentations

Questions & answers

Session Type
Industry Symposium
Date
03/31/2023
Session Time
08:30 AM - 10:00 AM
Room
Platinum Suite Room 3
Lecture Time
09:10 AM - 09:30 AM

HMOs influencing the infant gut microbiome maturation in early life

Session Type
Industry Symposium
Date
03/31/2023
Session Time
08:30 AM - 10:00 AM
Room
Platinum Suite Room 3
Lecture Time
08:50 AM - 09:10 AM

EARLY LIFE GUT MICROBIOME DEVELOPMENT IN BANGLADESHI INFANTS, ITS ASSOCIATION WITH FOOD INTAKE AND HEALTH OUTCOMES

Session Type
Oral Presentation
Date
04/01/2023
Session Time
12:45 PM - 01:45 PM
Room
Platinum Suite Room 4
Lecture Time
12:51 PM - 12:57 PM

Abstract

Background and Aims

We characterized infants’ gut microbiome maturation as a trajectory in the Microbiota and Health Study (MH), Bangladesh (NCT02361164). For bacteria in trajectory, we examined their associations with diet, metabolites, and health.

Methods

Reference set was MH infants with vaginal delivery, absence of diarrhea episodes until 24 months, weight-for-length Z-scores > -2 at all visits (n=37/222). Using metagenomics data from fecal samples (birth, 2, 6, 10, 15, 18 and 24 months), modeling of microbiome-age was performed to capture age-appropriate maturation. Fecal metabolites were measured using a mass spectrometry platform. Consumption of 13 food items was recorded every month qualitatively. A market basket algorithm was applied at different age-groups to identify feeding-patterns associated with microbiome maturation.

Results

In gut microbiome maturation reference trajectory, bacteria known to produce Short-Chain Fatty-Acids (SCFAs) were Bifidobacterium longum (acetate), Blautia obeum and Veillonella parvula (propionate), Eubacterium rectale, Faecalibacterium prausnitzii and Anaerostipes hadrus (butyrate). Fecal propionate significantly increased with age (p-value = 2.4x10-41). Suji intake was associated with higher butyrate, and milk consumption with lower butyrate (both p-values < 0.05) at multiple timepoints. Blautia obeum abundance was significantly higher in 0 vs. 3+ diarrhea episodes (cumulative incidence from 10 to 24 months) by a longitudinal, permutation-based test (p-value < 0.05). Blautia obeum was positively associated with egg consumption at 15 months (p-value = 0.04).

Conclusions

SCFAs-producing bacteria, amongst others, constituted the reference microbiome trajectory characterizing the infants’ age-appropriate gut microbiome maturation and its link to diet and health.

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INFANT AND TODDLER FORMULAS SUPPLEMENTED WITH 5 HMOS AND FED FROM BIRTH TO 15 MONTHS MODULATE THE GUT MICROBIOME TRAJECTORY TOWARDS THAT OF BREASTFED INFANTS

Session Type
Oral Presentation
Date
04/01/2023
Session Time
12:45 PM - 01:45 PM
Room
Platinum Suite Room 4
Lecture Time
01:15 PM - 01:21 PM

Abstract

Background and Aims

Human milk oligosaccharides (HMOs) are known to drive gut microbiome development during early life. We assessed microbiome related secondary-endpoints in a randomized controlled trial of infants fed formulas containing a blend of five HMOs.

Methods

Formula-fed infants (7-21d at enrollment) were randomized to control (CG, n=154), standard cow’s milk-based infant formula [IF] until age 6 months (m), follow-up formula [FUF] until 12m, growing-up milk [GUM] until 15m or the same formula regimen supplemented with either lower (TG1, 1.5g/L, n=155) or higher (TG2, 2.5g/L, n=153) HMO concentration in IF, followed by identical FUF (0.5g/L) and GUM (0.4g/L) for both TG1 and TG2. Fecal samples (baseline, 3, 6, 12, 15m) were used for microbiome profiling. Microbiome-age predictor training using Genus, Species, or CAZyme composition was conducted with reference data from non-randomized vaginally delivered breastfed infants that were enrolled in parallel (HMG-VD, n=31). Models were applied to CG, TG1, and TG2 to predict microbiome-age and identify outliers (microbiome-for-age z-score: |MAZ|>3). Microbiome-age trajectories were compared for each group against the HMG-VD reference trajectory.

Results

Using Genus-based model (10 features, R2=0.862), TG trajectories converged on reference trajectory earlier than CG, i.e., significantly distinct until ~11.4 months (CG), ~9.4 months (TG1), ~9.6 months (TG2). Following intervention, outliers were significantly reduced in TGs compared to CG (overall trend test p=0.0002) and at visits (3-6m p=0.0002; 12-15m: p=0.0377). Trends on other data models were similar.

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Conclusions

IF, FUF, and GUM supplemented with specific blend of five HMOs modifies the infant gut microbiome maturation trajectory towards that of breastfed, vaginally-delivered reference infants.

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