Recapitulation of Ayurveda constitution types by machine learning of phenotypic traits

Molecular study of the KCNJ11 gene and its correlation with Prakriti to preventing and managing type 2 diabetes

In Ayurveda, every individual is believed to possess a unique entity known as Prakriti, which distinguishes them from others physically, physiologically, and psychologically. This entity also determines an individual's response to a particular stimulus, and it is believed that such responses are not solely determined by genetics. The present research aims to validate the Ayurvedic concept of Prakriti from a modern molecular perspective to strengthen the personalized and precise treatment approach. A study was conducted to investigate the role of the KCNJ11gene in the susceptibility of individuals to type 2 diabetes mellitus (T2DM) with their metabolic status. The research involved allele mining on three major Prakriti groups - Vata, Pitta, and Kapha - in 112 patients with T2DM and 112 healthy individuals. The KCNJ11 gene, responsible for insulin secretion membrane pore formation, was analyzed to determine the susceptibility of different Prakriti types to T2DM. The MutPred tool predicted the molecular cause of disease-related amino acid substitution. According to the study, only Pitta and Kapha Prakriti were diagnosed with diabetes, while all three Prakriti types were present in the control group of healthy individuals. A protein model was prepared, and the changes resulting from mutations were observed for each group in their protein sequence, both as synonymous and non-synonymous mutations. Ultimately, these changes contributed to the manifestation of T2DM. Based on the findings, it appears that Prakriti groups may experience changes in protein function due to nonsynonymous mutations and differences in amino acids at the protein level.

Ayurgenomics-based frameworks in precision and integrative medicine: Translational opportunities

In today's globalized and flat world, a patient can access and seek multiple health and disease management options. A digitally enabled participatory framework that allows an evidence-based informed choice is likely to assume an immense importance in the future. In India, traditional knowledge systems, like Ayurveda, coexist with modern medicine. However, due to limited crosstalk between the clinicians of both disciplines, a patient attempts integrative medicine by seeking both options independently with limited understanding and evidence. There is a need for an integrative medicine platform with a formalized approach, which allows practitioners from the two diverse systems to crosstalk, coexist, and coevolve for an informed cross-referral that benefits the patients. To be successful, this needs frameworks that enable the bridging of disciplines through a common interface with shared ontologies. Ayurgenomics is an emerging discipline that explores the principles and practices of Ayurveda combined with genomics approaches for mainstream integration. The present review highlights how in conjunction with different disciplines and technologies this has provided frameworks for (1) the discovery of molecular correlates to build ontological links between the two systems, (2) the discovery of biomarkers and targets for early actionable interventions, (3) understanding molecular mechanisms of drug action from its usage perspective in Ayurveda with applications in repurposing, (4) understanding the network and P4 medicine perspective of Ayurveda through a common organizing principle, (5) non-invasive stratification of healthy and diseased individuals using a compendium of system-level phenotypes, and (6) developing evidence-based solutions for practice in integrative medicine settings. The concordance between the two contrasting streams has been built through extensive explorations and iterations of the concepts of Ayurveda and genomic observations using state-of-the-art technologies, computational approaches, and model system studies. These highlight the enormous potential of a trans-disciplinary approach in evolving solutions for personalized interventions in integrative medicine settings.

Ayurgenomics in Anti-Viral Therapy: A Literature Synthesis

This review focuses on Ayurgenomics (AG) used in antiviral therapy. According to Ayurveda, three doshas govern Prakriti, the natural organizational structure of humans. AG is a new field in modern medicine that focuses on establishing individualized self-care. It is a modern therapeutic and preventive method that enhances a person's mental and physical well-being. Due to the threat of emerging lethal viruses and the significant role of Ayurveda in the pandemic, modern genetics studies have emerged. Prakriti, an Ayurvedic notion that AG incorporates, correlated with three doshas (phenotypes) called vata, pitta, and kapha. Each Prakriti individual had a specific balance for each dosha. To date, the most recent field of AG, which aims to characterize Prakriti types in terms of current genetics and physiology, has provided the best definition. Four databases were searched for studies on this topic using the keywords "Ayurgenomics" and "Anti-Viral Therapy." Four articles that demonstrated a favorable approach for the application of AG were gathered for synthesis. According to this study, employing Adhatoda Vasica and Cissampelos pareira L extracts improved the viral structure of the SAR-CoV-2 virus. Further studies involving human participants are required to rule out the positive effects of AG in real-world contexts.

Heart rate variability during head-up tilt shows inter-individual differences among healthy individuals of extreme Prakriti types

Autonomic modulation is critical during various physiological activities, including orthostatic stimuli and primarily evaluated by heart rate variability (HRV). Orthostatic stress affects people differently suggesting the possibility of identification of predisposed groups to autonomic dysfunction-related disorders in a healthy state. One way to understand this kind of variability is by using Ayurvedic approach that classifies healthy individuals into Prakriti types based on clinical phenotypes. To this end, we explored the differential response to orthostatic stress in different Prakriti types using HRV. HRV was measured in 379 subjects(Vata = 97, Pitta = 68, Kapha = 68, and Mixed Prakriti = 146) from two geographical regions(Vadu and Delhi NCR) for 5 min supine (baseline), 3 min head-up-tilt (HUT) at 60°, and 5 min resupine. We observed that Kapha group had lower baseline HRV than other two groups, although not statistically significant. The relative change (%Δ1&2 ) in various HRV parameters in response to HUT was although minimal in Kapha group. Kapha also had significantly lower change in HR, LF (nu), HF (nu), and LF/HF than Pitta in response to HUT. The relative change (%Δ1 ) in HR and parasympathetic parameters (RMSSD, HF, SD1) was significantly greater in the Vata than in the Kapha. Thus, the low baseline and lower response to HUT in Kapha and the maximum drop in parasympathetic activity of Vata may indicate a predisposition to early autonomic dysfunction and associated conditions. It emphasizes the critical role of Prakriti-based phenotyping in stratifying the differential responses of cardiac autonomic modulation in various postures among healthy individuals across different populations.

Stratification of rheumatoid arthritis cohort using Ayurveda based deep phenotyping approach identifies novel genes in a GWAS

Background and aim

Genome wide association studies have scaled up both in terms of sample size and range of complex disorders investigated, but these have explained relatively little phenotypic variance. Of the several reasons, phenotypic heterogeneity seems to be a likely contributor for missing out genetic associations of large effects. Ayurveda, the traditional Indian system of medicine is one such tool which adopts a holistic deep phenotyping approach and classifies individuals based on their body constitution/prakriti. We hypothesized that Ayurveda based phenotypic stratification of healthy and diseased individuals will allow us to achieve much desired homogeneous cohorts which would facilitate detection of genetic association of large effects. In this proof of concept study, we performed a genome wide association testing of clinically diagnosed rheumatoid arthritis patients and healthy controls, who were re-phenotyped into Vata, Pitta and Kapha predominant prakriti sub-groups.

Experimental procedure

Genotypes of rheumatoid arthritis cases (Vata = 49; Pitta = 117; Kapha = 78) and controls (Vata = 33; Pitta = 175; Kapha = 85) were retrieved from the total genotype data, used in a recent genome-wide association study performed in our laboratory. A total of 528461 SNPs were included after quality control. Prakriti-wise genome-wide association analysis was employed.

Results and conclusion

This study identified (i) prakriti-specific novel disease risk genes of high effect sizes; (ii) putative candidates of novel therapeutic potential; and (iii) a good correlation between genetic findings and clinical knowledge in Ayurveda. Adopting Ayurveda based deep phenotyping may facilitate explaining hitherto undiscovered heritability in complex traits and may propel much needed progress in personalized medicine.

The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review

Background: The development of artificial intelligence (AI) in the medical field has been growing rapidly. As AI models have been introduced in complementary and alternative medicine (CAM), a systematized review must be performed to understand its current status. Objective: To categorize and seek the current usage of AI in CAM. Method: A systematic scoping review was conducted based on the method proposed by the Joanna Briggs Institute. The three databases, PubMed, Embase, and Cochrane Library, were used to find studies regarding AI and CAM. Only English studies from 2000 were included. Studies without mentioning either AI techniques or CAM modalities were excluded along with the non-peer-reviewed studies. A broad-range search strategy was applied to locate all relevant studies. Results: A total of 32 studies were identified, and three main categories were revealed: 1) acupuncture treatment, 2) tongue and lip diagnoses, and 3) herbal medicine. Other CAM modalities were music therapy, meditation, pulse diagnosis, and TCM syndromes. The majority of the studies utilized AI models to predict certain patterns and find reliable computerized models to assist physicians. Conclusion: Although the results from this review have shown the potential use of AI models in CAM, future research ought to focus on verifying and validating the models by performing a large-scale clinical trial to better promote AI in CAM in the era of digital health.

Whole Exome Sequencing in Healthy Individuals of Extreme Constitution Types Reveals Differential Disease Risk: A Novel Approach towards Predictive Medicine

Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed “Prakriti”. It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.

Exploring AyuGenomics approach for understanding COVID-19 predisposition and progression

Recent reports on COVID-19 suggest that, the susceptibility to COVID-19 infection and its progression have a genetic predisposition. Majorly associated genetic variants are found in human leukocyte antigen (HLA), angiotensin convertase enzyme (ACE; rs1799752: ACE2; rs73635825), and transmembrane protease serine 2 (TMPRSS-2; rs12329760) genes. Identifying highly prone population having these variants is imperative for determining COVID-19 therapeutic strategies. Ayurveda (Indian traditional system of medicine) concept of Prakriti holds potential to predict genomic and phenotypic variations. Reported work on Prakriti correlates HLA-DR alleles with three broad phenotypes (Tridosha) described in Ayurveda (AyuGenomics). This is suggestive of differences in immune responses in individuals with specific constitutions. Therefore, the reported studies provide clues for clinically relevant hypotheses to be tested in systematic studies. The proposed approach of Ayurveda-based phenotype screening may offer a way ahead to design customized strategies for management of COVID-19 based on differences in Prakriti, immune response, and drug response. However, this needs clinical evaluation of the relation between Prakriti and genetic or phenotypic variants in COVID-19 prone and resistant populations.

Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types

Differences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate molecular players for individualized and early interventions. Functional studies of lymphoblastoid cell line (LCL) model of phenotypically well-characterized healthy individuals can help deconvolute and validate these molecular mechanisms. In this study, LCLs are developed from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV were studied in these LCLs. Significant differences in cell proliferation rates were observed between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one of the fast growing groups (Vata) shows higher cell death but recovers its numbers due to an inherent higher rates of proliferation. This study reveals that baseline differences in cell proliferation could be a key to understanding the survivability of cells under UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitution types but can also help set priors during the design of an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes among healthy individuals with potential implications in precision medicine.

Ayurgenomics and Modern Medicine

Within the disciplines of modern medicine, P4 medicine is emerging as a new field which focuses on the whole patient. The development of Ayurgenomics could greatly enrich P4 medicine by providing a clear theoretical understanding of the whole patient and a practical application of ancient and modern preventative and therapeutic practices to improve mental and physical health. One of the most difficult challenges today is understanding the ancient concepts of Ayurveda in terms of modern science. To date, a number of researchers have attempted this task, of which one of the most successful outcomes is the creation of the new field of Ayurgenomics. Ayurgenomics integrates concepts in Ayurveda, such as Prakriti, with modern genetics research. It correlates the combination of three doshas, Vata, Pitta and Kapha, with the expression of specific genes and physiological characteristics. It also helps to interpret Ayurveda as an ancient science of epigenetics which assesses the current state of the doshas, and uses specific personalized diet and lifestyle recommendations to improve a patient’s health. This review provides a current update of this emerging field.

Western Indian Rural Gut Microbial Diversity in Extreme Prakriti Endo-Phenotypes Reveals Signature Microbes

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.