Insights on Personalized Medicine from Ayurveda

Abstract

The “omics” era of research has provided vital information on the genetic and biochemical diversity of individuals. This has lead to the emergence of “personalized medicine,” wherein one aims to design specific drugs for individual patients or subtypes of patients. Indeed, the ongoing patent wars on this matter, suggest that personalized medicine represents a major goal for today's pharmaceutical industries. Although the concept of personalized medicine is new to modern medicine, it is a well-established concept in Ayurveda, the traditional system of Indian medicine that is still being practiced. Therefore, this article discusses topics that are crucial for the advancement of modern personalized medicine. These topics include disease susceptibility, disease subtypes, and Ayurvedic therapeutics. First, we explain how Ayurveda, Traditional Chinese Medicine, and Traditional Korean medicine or Sasang Constitutional medicine; conceptualize disease susceptibility and disease subtypes. Next, we focus on conceptual similarities between molecular medicine and Ayurvedic concepts of disease susceptibility and disease subtypes. For each topic, we explain the relevant experimental evidence reported in the literature. We also propose new hypotheses and suggest experimental approaches for their testing and validation.

Introduction

S ignificant breakthroughs in personalized medicine require innovative research on the fundamental bases of individual variation. Interestingly, Ayurveda recognizes distinct patterns of individual variation and accordingly classifies individuals into groups. Notably, Ayurveda uses nongenetic concepts and tested empirical approaches to broadly predict disease susceptibility, disease severity, and drug response within each group. Scientific analysis of this remarkable predictive power of Ayurveda has already begun. In this article, we focus on topics wherein new insights would make a significant impact on the rapidly advancing field of personalized medicine. We begin with an explanation of basic concepts in Ayurveda, Traditional Chinese Medicine (TCM), and Traditional Korean medicine or Sasang Constitutional medicine (SCM).

Traditional Systems of Medicine

Ayurveda

Ayurveda defines three dynamic patho-physiological entities (doshas) as the basis for all body functions. The physiological functions and cellular correlates likely to be associated with each of the three doshas (vata, pitta, and kapha), are shown in Table 1.¹ Briefly, the vata dosha is associated with all movements and includes functions of the nervous and musculo-skeletal systems. Pitta dosha is associated with transformative activities such as digestion, metabolism, actions of hormones and growth factors, and immune surveillance. The kapha dosha is associated with homeostasis and maintenance of biological strength and stability.^1

–4 One's basic “body constitution” termed as prakriti, arises due to a unique combination of fixed amounts of these three doshas at conception. Thus, prakriti determines individuality and is akin to one's genotype. Ayurveda recognizes seven constitutional types, or prakritis, based on different combinations of the doshas at conception. Individuals of the three extreme constitutional types express a single dominant dosha and are said to have vata prakriti, pitta prakriti, or kapha prakriti, respectively. The latter individuals exhibit distinct and predictable phenotypes. However, most individuals have prakritis arising from combinations of the three doshas in varying proportions. Accordingly, most individuals have one of seven main types of prakritis (vata, pitta, kapha, vata-pitta, pitta-kapha, vata-kapha, and vata-pitta-kapha), which results in a wide range of phenotypic variation.^2
–4 Notably, Ayurveda encompasses the belief that one's prakriti (genotype) can be influenced by environment, maternal diet, lifestyle, and the age of parents at the time of conception.⁵ Ayurveda also includes the belief that an individual's phenotype can vary, since one's prakriti constantly interacts with diet and environmental factors.^3,6

Table 1.

Physiological Functions and Cellular Correlates for Each Dosha

Dosha ^a	Physiological functions	Cellular correlates
Vata	• Nervous and musculo-skeletal systems, locomotion, respiration, gastro-intestinal function	• Reflexes, muscle-fiber contraction, blood circulation, lung and heart movements, intestinal peristalsis and elimination
	• Regulation of all homeostatic mechanisms	• Neuroendocrine signaling
	• Movement of cells and molecules	• Cell cycle control (cell division, unwinding of DNA during transcription or replication)
		• Cell motility, secretion and excretion of molecules, nutrient uptake, ion transport (e.g., sodium pump)
		• Catabolism
Pitta	• Digestion and metabolism	• Actions of digestive enzymes
	• Maintenance of basal metabolic rate, energy exchange, thermoregulation	• Carbohydrate and energy metabolism (glycolysis, tricarboxylic acid cycle, respiratory chain)
	• Functions of exocrine and endocrine glands	• Transformation
	• Hormones	• Hormone receptors mediate changes in gene expression and cell function in response to hormones
	• Immunity	• Activities of T and B lymphocytes
	• Responses to stimuli and stressors	• Changes in gene expression
		• Cytoprotection and/or cell death
Kapha	• Maintaining biological strength, cohesion, and proper body structure	• Cell structure: synapses, intracellular matrix, membranes, receptor-ligand binding, and organelles
	• Maintaining tissue resistance and stability	• Anabolism: biosynthesis of macromolecules; i.e., proteins, carbohydrates, lipids, nucleotides
	• Maintaining flexibility	• Housekeeping functions: constitutive gene expression, turnover of macromolecules
	• Body fluids (lymph, mucus, synovial fluid)

The three doshas are interdependent; however, vata dosha exerts significant control over the pitta and kapha doshas, since it is associated with fundamental processes such as signal transduction, inter- and intracellular communication, cell cycle control, and movements of cells, ions, and molecules.

Each type of prakriti is associated with distinct physiological patterns, energy metabolism, and tolerance to external factors.² Thus, individuals with the two extreme types of prakriti (vata versus kapha), show low versus high body mass index values, respectively.⁷ Although one's prakriti is fixed, one's doshas are in dynamic equilibrium, and optimal function of each dosha and interactions between doshas are essential for normal health. Conversely, imbalances or disturbed interactions between the three doshas are the root cause of all disease.² An abnormal dosha can be inhibited, excessive, or aggravated.⁸ Pathogenic factors can also trigger abnormality of the doshas. Notably, the abnormal dosha can disrupt functions of specific tissues and systems in a predictable manner.⁹ While prakriti refers to the body constitution of healthy individuals, the concept of vikriti focuses on deviation from normal health and includes causative factors of disease and modes of pathogenesis. The concept of classifying diseases based on stages and patterns of disease progression is termed rogavastha (stage and subtypes of disease). Examples of rogavastha are discussed later.

Traditional Chinese medicine

In TCM, as in Ayurveda, the constitution of each person is influenced by congenital and acquired factors, which vary from person to person. Yin, yang, and qi are the major biological forces in TCM. Yin and yang are opposite but complementary forces, and their equilibrium is essential for good health. Just as imbalanced Doshas trigger disease, imbalances of yin and yang can cause disease. Qi is an “energy” that circulates and nourishes the entire body and is required for good health.^10,11 Thus, body constitutions are classified on the basis of levels of yin, yang, and qi. Like Ayurveda, TCM includes the belief that body constitution determines disease susceptibility. For example, individuals with a constitution containing high levels of yang tend to develop heat syndrome upon exposure to pathogenic heat, whereas individuals with a constitution containing abundant yin and deficient yang are susceptible to cold and dampness.^11,12 Diagnosis involves assessment of disease symptoms and syndrome differentiation, and TCM practices personalized medicine based on the presentation of disease in each patient and the stages and subtypes of diseases. This aspect of TCM is similar to the Rogavastha concept in Ayurveda. Apart from their diagnostic importance, disease stages and subtypes can also be used as predictors of drug response. For example, in a clinical trial of rheumatoid arthritis, disease pattern differentiation based on symptoms and concepts of TCM was related to response to modern biomedical therapy.¹² Other studies focus on integration of TCM classification of disease patterns with modern biomedical diagnosis.^11,13

Traditional Korean medicine

Traditional Korean medicine or SCM also classifies individuals on the basis of their body constitution. Thus, SCM classifies individuals into four types: taeyangin, taeumin, soyangin, and soeumin. These four types of body constitutions differ in the degree of inborn visceral functions, general figure, character, and temperament. Like Ayurveda and TCM, SCM includes the belief that an individuals' body constitution can predict disease susceptibility.¹⁴ For example, individuals with taeumin constitution have a greater risk for diabetes and hypertension.^15,16 Each type of constitution has specific weaknesses due to congenital hyperactive or hypoactive visceral organs. For example, individuals of soyangin constitution have weakness in elimination of body wastes. Treatment modalities are also based on body constitution. Accordingly, herbs used to treat individuals of one constitution may be contraindicated for individuals with a different type of body constitution.¹⁴

In summary, all three systems of traditional medicine (Ayurveda, TCM, and SCM) draw on the belief that an individual's body constitution plays a major role in determining disease susceptibility. Body constitution is also considered when prescribing drugs or other treatment modalities. In addition, Ayurveda and TCM also focus on disease subtypes and the patterns of disease progression.

Prakriti, Genetics, and Disease

In addition to defining one's body constitution, the three doshas are also associated with different types of temperaments. Indeed, an individual's constitution and temperament are considered during Ayurvedic diagnoses and treatment.¹⁷ Patwardhan¹⁸ first hypothesized a genetic basis for prakriti and its role in personalized management of diseases. Patwardhan et al. ^19
–21 then provided experimental support for this concept by showing correlations between certain human leukocyte antigen (HLA) alleles and the individual Prakriti types. Chen et al. ²² also found an association between frequencies of specific HLA class II polymorphic alleles and the body types of TCM. The proteins encoded by the HLA class I and class II genes in the major histocompatibility complex (MHC) are essential in immune recognition, transplant rejection, and susceptibility to several infectious and autoimmune diseases. Correlations between specific HLA alleles and different body types in both Ayurveda and TCM are significant since immunity is one major link in the mind–body connection, and HLA molecules have long been associated with onset of autoimmune diseases. Indeed, genes in the HLA complex are among the strongest predisposing genetic factors for autoimmune diseases.^23,24

Although HLA alleles are highly polymorphic, identification of HLA variants with causal links to specific disease is problematic since linkage disequilibrium extends across multiple HLA and non-HLA genes in the MHC locus.²⁴ However, there are a few cases of HLA variants with pathogenic relevance. For example, in spondyloarthropathies, a single nucleotide polymorphism (SNP) results in a variant HLAb27 allele, which encodes a single altered amino acid in an immunogenic peptide with “arthritogenic” properties.²⁵ In the autoimmune digestive disorder termed celiac disease, HLA typing is used for clinical purposes.^26,27 HLA proteins associated with type 1 diabetes have been extensively studied since the HLA complex contributes 50% of the inherited risk for the disorder.²⁸ Analysis of complexes of particular HLA molecules with epitopes of disease-specific antigens has provided insights on the molecular pathology underlying type 1 diabetes.^27,28

Disease Susceptibility, Gene Networks, and Prakriti

Microarray profiling has been used to analyze gene signatures in individuals with the three extreme prakriti types (vata, pitta, or kapha). Thus, Prasher et al. ⁵ observed that the functional categories of genes that significantly varied among these prakriti types were correlated with many of their functions. For example, genes regulating cell division and nucleo-cytoplasmic transport were differentially expressed in individuals of vata prakriti. Genes regulating immune surveillance were differentially expressed in individuals with pitta prakriti, whereas individuals of kapha prakriti showed strong expression of genes regulating anabolism (Table 1). Interestingly, 30% of these differentially expressed genes were associated with complex and monogenic diseases.⁵

A major focus of modern research on disease susceptibility involves genome-wide association studies (GWAS), which have identified more than 2000 SNPs associated with disease susceptibility.²⁹ Although these data are useful, they have disadvantages. First, SNPs explain a small portion of the total inheritable genetic contributions to complex diseases.³⁰ Second, it is difficult to determine functional effects of individual SNPs, since most SNPs are found in the noncoding regions of genes. Third, identifying disease-related SNPs can be problematic since common diseases may be associated with different combinations of hundreds of rare SNP variants.³¹ Therefore, new methods are being used for analysis and validation of GWAS and SNP data.³² Thus, studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a novel approach. Another method examines “genetic interactomes,” wherein biochemical pathways and signaling networks of genes identified by GWAS are analyzed. Indeed, such studies have already provided new insights into genetic susceptibility to three inflammatory diseases (Crohn's disease, rheumatoid arthritis, and type 1 diabetes).³³ Genetic interactome studies also identified unexpected interrelationships between very different diseases such as type 1 diabetes and Alzheimer's disease. Notably, the interrelatedness between these two diseases was undetectable at the (GWAS) gene level.³⁴

Although the role of HLA genes in determining susceptibility to autoimmune diseases is becoming clear, the genetic basis for susceptibility to other groups of diseases remains unclear. Like TCM and SCM, Ayurveda believes that an individuals' body constitution (prakriti) can broadly predict susceptibility to groups of diseases. For example, individuals of vata prakriti are prone to disorders of the nervous and musculo-skeletal systems, whereas individuals of pitta prakriti are susceptible to disorders of the blood, skin, and digestive tract.^35,36 Thus, one experimental approach for understanding susceptibility to groups of specific diseases is to search for correlations between the Ayurvedic and modern parameters for disease susceptibility and prevalence. Ideally, these correlative studies would analyze data from GWAS, SNP, and genetic interactome data of patients with different sets of related diseases. Indeed, Petsko³¹ suggests that GWAS should focus on “the association between diseases and the causes of a class of common diseases.” Since Ayurveda and modern medicine have different concepts of disease origin and pathogenesis, they may also differ on the interrelationships between diseases. Therefore, such studies should be done with groups of related diseases as specified by both systems of medicine. If results from the above experiments show that specific gene networks or hub genes are strongly correlated with one's prakriti and susceptibility to groups of diseases (as predicted by Ayurveda), then further studies could be done. For example, clinical trials could determine whether classifying individuals on the basis of their active, shared gene networks or alleles of hub genes can actually lead to correct predictions of their prakritis and their patterns of disease susceptibility. Positive findings from such studies will have significant applications for modern personalized medicine.

Metabolic Syndrome and Kapha Prakriti

Based on the above discussion, we hypothesize that there are strong correlations between Ayurvedic parameters for disease susceptibility and gene networks associated with certain groups of diseases. Metabolic syndrome is a good test of this hypothesis because modern medicine has identified a common gene signature linking dyslipidemia with inflammatory and metabolic diseases.^37,38 The central role of dyslipidemia in the shared pathology between these major diseases strongly resonates with the Ayurvedic view that individuals of kapha prakriti are most susceptible to metabolic syndrome and cardiovascular diseases.^5,39 Interestingly, Susruta, one of the founding fathers of Ayurveda, advocated moderate exercise to maintain the equilibrium of kapha dosha and to minimize the consequences of obesity and diabetes.⁴⁰ Together, these ideas strongly suggest that individuals of kapha prakriti share active gene networks that predispose them to metabolic syndrome. To test this hypothesis, one can analyze expression of isoforms of specific hub genes in individuals of the three extreme types of prakritis. For example, the peroxisome proliferator-activated receptor γ transcriptional coactivator-1 (PGC-1) is a good candidate gene, since PGC-1 proteins regulate lipoprotein homeostasis and energy balance and are major hubs for linking nutritional and hormonal signals with energy metabolism.⁴¹ Furthermore, this gene has a polymorphism that is associated with increased risk for type 2 diabetes. In contrast, the related gene, peroxisome proliferator activated receptor γ2 (PPARγ2); has a specific allele which is consistently associated with a reduced risk of type 2 diabetes.⁴² Therefore, studies on allele-specific expression of the PGC-1 and PPARγ2 genes, may determine whether the presence of certain polymorphisms of these critical hub genes show positive correlation with kapha prakriti, high body mass index value, and increased risk for metabolic syndrome and cardiovascular diseases. One must also analyze epigenetic and post-transcriptional mechanisms regulating expression of PGC-1 and PPARγ2 genes, since such mechanisms may play a critical role in the expression of these hub genes.^41,42

Disease Subtypes

Identifying disease subtypes is the immediate goal of personalized medicine. Indeed, the identification of certain subtypes of cancers has already resulted in some degree of personalized treatment for some patients with cancer. However, virtually nothing is known about subtypes of other diseases. Ayurveda has a comprehensive diagnostic system that detects all manifestations of the primary disease and allows determination of disease subtype and severity. Clinical examination focuses on the entire pathogenesis by analyzing links between causation and disease manifestation. Diseases subtypes are based on the dominant status of a dosha, the involvement of specific tissues (dhatus), the disease stage (rogavastha), or various combinations of these factors. For example, the rogavastha concept classifies rheumatoid arthritis on the basis of presence or absence of ama (a pro-inflammatory substance produced by impaired metabolism). Medicines and therapeutic procedures are specific to both these stages of rheumatoid arthritis. Another example of rogavastha relates to prameha (metabolic syndrome and diabetes mellitus), which has 20 subtypes resulting from disturbed interactions between the doshas and different tissues.³⁹

In summary, a matrix of patient-specific and disease-related variables results in a highly personalized approach to diagnosis and therapeutic management for each patient. Notably, this approach can also be applied for diagnosis and management of “new” diseases that are not exactly mentioned in the classical texts of Ayurveda.

Designing experiments to bridge the Ayurvedic concepts of diseases subtypes with parallel concepts in modern medicine is difficult since Ayurvedic physiology and pathology have not been explained in terms of modern biochemistry and cell biology. One could analyze isoforms and mutants of proteins associated with the disease pathology. If such data are positively correlated with the Ayurvedic diagnostic parameters for the disease in question, it may lead to a molecular understanding of Ayurvedic subtypes for at least one disease. However, our incomplete understanding of genotype–phenotype relationships in normal versus diseased individuals, poses a fundamental barrier to progress in this field. Fortunately, major breakthroughs are expected with newer molecular methods. For example, next generation sequence technology has revealed the presence of hundreds of potentially harmful, rare genetic variants in some normal individuals.⁴³ Understanding how a given phenotype or related phenotypes correlate with the common versus rare variants of a given gene could potentially provide important information on subtypes of diseases. For example, a next-generation sequencing study of 56 genes associated with Crohn's disease has already identified new independent risk factors and protective variants in different genes.⁴⁴ One approach for improved understanding of genotype–phenotype relationships is “targeted phenotyping,” which analyzes and compares the over- and underrepresented phenotypes in individuals with or without a given SNP with random controls.⁴⁵ A second approach is termed as “deep phenotyping,” wherein patients with rare genetic disorders undergo comprehensive analysis of their phenotypes. Alternately, deep phenotyping can involve analysis of patients with rare mutations of a specific gene.⁴⁶ Together, these new genetic approaches may elucidate subtle variations in gene networks. These subtle variations may enable one to distinguish between individuals expressing rare variants of normal genes from those who express gene variants that truly cause a particular phenotypic subtype of a disease.

In summary, the experimental approaches discussed may identify important links between the molecular and Ayurvedic concepts of disease subtypes.

Ayurvedic Therapeutics

Just as CYP gene polymorphisms regulate drug tolerance and metabolism,⁴⁷ Ayurveda believes that drug tolerance and drug response depend on specific interactions between the patient (host) and drug. Ghodke et al. ⁴⁸ investigated this concept and reported that individuals with pitta prakriti expressed the SNP of CYP2C19, which is associated with the “extensive metabolizer” phenotype. In contrast, individuals with kapha prakriti expressed the SNP of CYP2C19, which is associated with the “slow metabolizer” phenotype.⁴⁹ Notably, in addition to ones' prakriti, there are 12 other host factors and 12 drug-related parameters to be considered.^50,51 Ayurvedic physicians account for all permutations and combinations of these host and drug factors and accordingly select appropriate drugs for the patient. The final choice of drugs is highly personalized because additional parameters such as the patient's overall health, diet, digestive status, immunity, and response to environmental factors are also considered. Interestingly, these same parameters are the focus of intense modern research. Thus, metabonomics⁵² and interactions between genetic, epigenetic, and nongenetic factors are now known to influence pathogenesis⁴⁴ and drug action.⁵³ Indeed, Nebert et al. ⁵⁴ state that “individualized drug therapy will never be achieved by DNA testing alone.”

We discussed the sophisticated nature of Ayurvedic personalized medicine with two examples. First, we explained how individuals with different subtypes of osteoarthritis can be treated with different drugs. Next, we illustrated the dynamic nature of Ayurvedic medicine by explaining how a sequence of personalized drugs can be used to treat different stages of asthma in a single patient.⁵⁵

Conclusions

Ayurveda is a working system of safe and effective personalized medicine that has withstood the test of time. Therefore, establishing links between Ayurveda and modern medicine can provide novel insights for modern personalized medicine. Accordingly, we identify areas of possible convergence between the two systems of medicine and propose testable hypotheses on topics relevant to personalized medicine. We outline experiments that may link the Ayurvedic concept of prakriti with genes associated with susceptibility to groups of diseases and disease subtypes. We also suggest experiments to determine whether specific gene networks/hub genes are associated with kapha prakriti and a predisposition to metabolic syndrome. We also point out that our understanding of disease subtypes hinges on deeper analysis of genotype–phenotype relationships using new genetic technologies such as next-generation sequencing, targeted phenotyping, and deep phenotyping. All these experiments require serious collaborations between biochemists, molecular biologists, geneticists, epidemiologists, physiologists, and physicians (Ayurvedic and modern). Such a multidisciplinary approach is worthwhile since it can potentially lead to novel paradigms for modern personalized medicine.

Footnotes

Acknowledgments

We acknowledge the helpful suggestions of Dr. Sandip Ubale, Dr. Pramod Dhumal, and Dr. Neelima Tillu. Dr. G. Tillu acknowledges the Vaidya Scientist Fellow Program by Institute of Ayurveda and Integrative Medicine, Bangalore and Department of AYUSH, Government of India for fellowship support.

Author Disclosure Statement

No financial conflicts exist.

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