Heterogeneity amidst healthy individuals at genomic level is being widely acknowledged. This, in turn, is modulated by differential response to environmental cues and treatment regimens, necessitating the need for stratified/personalized therapy. We intend to understand the molecular determinants of Ayurvedic way (ancient Indian system of medicine) of endo-phenotyping individuals into distinct constitution types termed “Prakriti,” which forms the basis of personalized treatment. In this study, we explored and analyzed the healthy human gut microbiome structure within three predominant Prakriti groups from a genetically homogenous cohort to discover differentially abundant taxa, using 16S rRNA gene based microbial community profiling. We found Bacteroidetes and Firmicutes as major gut microbial components in varying composition, albeit with similar trend across Prakriti. Multiple species of the core microbiome showed differential abundance within Prakriti types, with gender specific signature taxons. Our study reveals that despite overall uniform composition of gut microbial community, healthy individuals belonging to different Prakriti groups have enrichment of specific bacteria. It highlights the importance of Prakriti based endo-phenotypes to explain the variability amongst healthy individuals in gut microbial flora that have important consequences for an individual's health, disease and treatment.

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In Ayurveda system of medicine individuals are classified into seven constitution types, “Prakriti”, for assessing disease susceptibility and drug responsiveness. Prakriti evaluation involves clinical examination including questions about physiological and behavioural traits. A need was felt to develop models for accurately predicting Prakriti classes that have been shown to exhibit molecular differences. The present study was carried out on data of phenotypic attributes in 147 healthy individuals of three extreme Prakriti types, from a genetically homogeneous population of Western India. Unsupervised and supervised machine learning approaches were used to infer inherent structure of the data, and for feature selection and building classification models for Prakriti respectively. These models were validated in a North Indian population. Unsupervised clustering led to emergence of three natural clusters corresponding to three extreme Prakriti classes. The supervised modelling approaches could classify individuals, with distinct Prakriti types, in the training and validation sets. This study is the first to demonstrate that Prakriti types are distinct verifiable clusters within a multidimensional space of multiple interrelated phenotypic traits. It also provides a computational framework for predicting Prakriti classes from phenotypic attributes. This approach may be useful in precision medicine for stratification of endophenotypes in healthy and diseased populations.

ObjectiveThe objective of the sub-analysis of data from centers across urban areas in India of the Global Asthma Network (GAN) was to study the 1) prevalence of symptoms of asthma in children and adults, 2) change in prevalence of asthma and its trigger factors since the International Study of Asthma and Allergies in Childhood (ISAAC), and, 3) current asthma treatment practice.MethodsIn this cross–sectional, multicenter, school-based, and self-administered questionnaire, responses from children aged 6–7 years, 13–14 years, and their respective parents were analysed.ResultsThe GAN phase I study included 20084 children in the 6–7-year-age group, 25887 children in the 13–14-year-age group, and 81296 parents. The prevalence of wheeze in the past 12 months was 3.16%, 3.63%, and 3.30% in the three groups respectively. In comparison to the ISAAC studies, there was a significant reduction in the prevalence of current wheeze (p<0.001). Bivariate analysis revealed a significant reduction in the prevalence of trigger factors. Almost 82% of current wheezers and 70% of subjects with symptoms of severe asthma were not clinically diagnosed as having asthma. The daily use of inhaled corticosteroid (ICS) was less than 2.5% in subjects with current wheeze and those with symptoms of severe asthma but less than 1% used daily ICS when asthma remained undiagnosed.ConclusionThe prevalence of current wheeze and its causal factors showed a significant reduction compared to previous ISAAC studies. Among subjects with current wheeze and symptoms of severe asthma, the problem of under-diagnosis and under-treatment was high.

Physical activity (PA), sedentary behaviour (SB) and sleep are important lifestyle behaviours associated with chronic respiratory disease (CRD) morbidity and mortality. These behaviours need to be understood in low- and middle-income countries (LMIC) to develop appropriate interventions. Purpose Where and how have free-living PA, SB and sleep data been collected for adults living with CRD in LMIC? What are the free-living PA, SB and sleep levels of adults living with CRD? Patients and Methods The literature on free-living PA, SB and sleep of people living with CRD in LMIC was systematically reviewed in five relevant scientific databases. The review included empirical studies conducted in LMIC, reported in any language. Reviewers screened the articles and extracted data on prevalence, levels and measurement approach of PA, SB and sleep using a standardised form. Quality of reporting was assessed using bespoke criteria. Results Of 89 articles, most were conducted in Brazil (n=43). PA was the commonest behaviour measured (n=66). Questionnaires (n=52) were more commonly used to measure physical behaviours than device-based (n=37) methods. International Physical Activity Questionnaire was the commonest for measuring PA/SB (n=11). For sleep, most studies used Pittsburgh Sleep Quality Index (n=18). The most common ways of reporting were steps per day (n=21), energy expenditure (n=21), sedentary time (n=16), standing time (n=13), sitting time (n=11), lying time (n=10) and overall sleep quality (n=32). Studies revealed low PA levels [steps per day (range 2669–7490steps/day)], sedentary lifestyles [sitting time (range 283–418min/day); standing time (range 139–270min/day); lying time (range 76–119min/day)] and poor sleep quality (range 33–100%) among adults with CRD in LMIC. Conclusion Data support low PA levels, sedentary lifestyles and poor sleep among people in LMIC living with CRDs. More studies are needed in more diverse populations and would benefit from a harmonised approach to data collection for international comparisons.