Disease Informatics:Host factors simplified

Laughter is the best medicine

Rajendra P Deolankaroonnatie@yahoo.com

Prerequisitehttp://www.pitt.edu/~super1/lecture/lec25371/index.htmhttp://www.pitt.edu/~super1/lecture/lec25381/001.htm

Modern man is genetically same as Paleolithic man

But lives in the artifact world

And hence “gene X artifact” is an important subject matter for disease study

http://news.nationalgeographic.com/news/2004/09/images/040910_awastack.jpg

Confounders

Age, Sex, Socioeconomic status, Caste etc are not causes of disease but could be pointers to molecules and mechanisms causing disease

Organization of disease systemMere set of organs is not organismSystem cannot work without organization

To manage a system effectively, you might focus on the interactions of the parts rather than their behavior taken separately. Russell L. Ackoff

Personality of diseaseDisease has a personality and associated factors are its organsAssociated factors are mostly but not necessarily component causes (CCs)

Disease Causal Mechanism (DCM)Summarily,Mere set of CCs DCM

CCs: Component causes

Conceptual scheme of ageing as the accumulation of component causes throughout life Ageing starts with the accumulation of component causes A–E. The presence of these five component causes completes sufficient cause I, resulting in effect I, e.g. unsteadiness. In the following period, the addition of component causes F–H completes sufficient cause II, resulting in effect II, e.g. a gait disorder. The further accumulation of component causes I and J completes sufficient cause III, resulting in effect III, e.g. death (see also the description of the example).

http://www.biomedcentral.com/content/pdf/1471-2318-3-7.pdf

TeamworkP + X PXWhere P and X are CCs andPX is interaction / teamwork amongst CCs

CCs: Component causes

PX DCMDisease is outcome of DCM where factors work in teamTeamwork PX predominate over individual factors P + X

DCM: Disease causal mechanismPX: Interaction / teamwork amongst CCs

Disease and DCMsDCM is regarded as sufficient causeFor a given disease, there could be several sufficient causes

Three sufficient causes of disease.

http://www.ajph.org/cgi/content/full/95/S1/S144/F1

Rothman and GreenlandProposed model

PROF. Kenneth J Rothman Prof. Sander Greenland

A model of causation that describes causes in terms of sufficient causes and their component causes illuminates important principles such as multicausality, the dependence of the strength of component causes on the prevalence of complementary component causes, and interaction between component causes.

Immunity

Innate α (Host X Environment)

Paraspecific α (Innate X immunogen)Specific α (Host X pathogen)

Disease resistance

Host is a common factor

Infectious diseasesPathogen (P) must work together with some CC (X) to compose DCMP is also CC

CC: Component causeDCM: Disease causal mechanism

What is X?We have seen that, in an infectious diseases, Pathogen (P) must work together with some CC (X) to compose DCMX could be described as complex interaction of host/ environmental factors

DCM centric Disease DefinitionsDCM could be P1X OR P2X OR … PmX

Secretory Diarrhoea may be associated with E coli toxin (P1X) OR Vibrio cholerae 01 toxin (P2X) OR

… NSP4 of rotavirus (PmX)

CC centric disease definitionsDCM could also be PX1 OR PX2 OR ... PXn

Dengue virus (P) could be associated with fever (PX1),

hemorrhagic fever (PX2) OR … Shock syndrome (PXn)

http://www.wordinfo.info/words/index/info/view_unit/1/?letter=B&spage=3

Crude classifications and false generalizations are the curse of organized life. George Bernard Shaw

X1 ≠ X2 ≠ Xn

Disease definition for Total disease burden in a localityDCM could be:P1X OR P2X OR … PmX OR

P1X1 OR P1X2 OR … P1Xn OR …

P2X1 OR P2X2 OR … P2Xn OR …

………………………PmXn

Taking the wicket of a key player helps in winning the cricket matchCC in CC centric disease definitions is regarded as a key playerIt is easy to detect CCIt is easy to plan strategy against CCInformation on DCM is complex and difficult to compile

Several captains!!! Almost no playersThis could be a limitation of CC centric disease definitionsTo fight Secretory Diarrhoea, solution based on E coli target may not work against rotavirus. Ultimately several solutions are required to fight the disease.

Team may win even after captains failsBiologicals and chemicals prepared to fight against the disease

May failMay produce complicationsMay emerge into new diseaseIncrease the expenditure on public health

Self = Somatic body (Annamaya kosha) +Vitality (Pranamaya kosha) +Mind (Manomaya kosha) +Intellect (Vidnyanamaya kosha) +Bliss (Anandamaya kosha)

Description of a human in Indian Medicine

Human body computer = Intellect (Central processing unit) + Self / Ego (Software) + Memory (Free space, Floppy/ Hard disk) + Mind/ senses (Program) + Life history (Data)

Principals in DCM in Ancient Indian MedicineErrors in 4 C’s:CatchControlCarry on and Chuck

1st C

Error: In catching from nature: food, water, air, sunlight etc Outcome: Slip in right body compositionSolution: Balancing Dosha

Dosha ≡ Body composition

2nd C

Error: In controlling the body networkOutcome: Slip in right response to the stimulusSolution: Appropriation of Dushya

Dushya ≡ response to stimulus

3rd C

Error: In carrying on the routineOutcome: Deviation from optimum basal metabolic rateSolution: Regularising Agni

Agni ≡ Basal Metabolic Rate

4th C

Error: In chucking the wasteOutcome: A body that is not free from dysbiotics and morbid substancesSolution: Elimination of Ama

Human microbial organsGut associated microbiota organVagina associated microbiota organ Skin associated microbiota organ

Prof. Stig Bengmark

Ama ≡ products of dysbiosis

Disease triad described in ancient Indian medicineDisease triad is working together of Host factors (Adhyatmic),Environmental factors (Adhidaivik) and Agents: physical, chemical or biological (Adhibhautik)To give outcome as disease (Vyadhi)

Associations with disease outcomeCCs work together to give disease outcomes that can be observed at a particular time, at a particular place or in a particular personTime (Season: Kala-bala),Place (Daiva- bala) and Person (Prakruti, described separately)

Details observed in Person1. Genetically predisposed / metabolically imprinted (Aadi- bala pravritta)2. Congenital (Janma-bala)3. Imbalance of body composition (Dosha-bala)4. Metabolic activity (Vata, Pitta and Kapha)5. Trauma (Sanghata-bala) and 6. Age, sex, socioeconomic status etc (Svabhava-bala)

Thrifty geneshttp://www.bmj.com/cgi/content/full/328/7447/1070

Prenatal adaptationshttp://www.bmj.com/cgi/content/full/328/7447/1070

Host body phenotypic characterizationDensitySomatotypeState of matterCompositionMotilityShape etc

Density of bodyVariation in dosha resemble density of the body(Vata-light, Kapha-heavy; Pitta-neither heavy nor light)

Somatotype of the bodyEctomorph (Vata),Endomorph (Kapha) andMesomorph (Pitta)

http://www.innerexplorations.com/catpsy/t1c4.htm

Endomorph Ectomorph

Mesomorph

State of body matterGas (Vata)Solid (Kapha) andLiquid (Pitta)

Body compositionLow muscle (Vata)Fatty and muscular (Kapha) andIn between i.e. lean mass dominated (Pitta)

Body motilityHigh (Vata)Low (Kapha) andMedium (Pitta)

Body shapeLinear (Vata)Hour glass (Pitta) andApple, pear or rectangular (Kapha)

Tridosha in ancient medicineVata, Pitta and Kapha of a person are called as Tridosha in the ancient Indian medicineNone of the body characterization criteria described in the earlier slides singly can describe the tridoshaTridosha is complex

Quantifying tridosha; Rajni Joshi methodhttp://www.liebertonline.com/doi/abs/10.1089/acm.2004.10.879?cookieSet=1&journalCode=acm

Dosha assessmentDosha assessment may vary depending upon the skill level of the vaidya (Doctor)

What we can learn from ancient scienceParameters for measurement of characteristics of a person could be many and hence data could be quite hugeDimensionality of data can be reduced if similar parameters are grouped together

How to reduce dimensionality of data?Techniques in multivariate statisticsComputer databases and software

Example of database preparationPrepare a multi-dimension data set using all possible criteria on a representative population (Density, somatotype, body shape (digitalize), composition, IQ, EQ etc)

Example of application of multivariate statisticsCluster the individuals by applying some algorithm of multivariate statisticsThe individuals having similar characteristic will fall in one groupThus the population will be divided in a few groups(G1, G2…Gk)

Example of application of multivariate statisticsPerform Principal Component Analysis (Statistical analysis)on each group (G1, G2…Gk)The number of variables now would be 2 to 3. The three components expected could be similar to Vata, Pitta and Kapha in order of their importanceThis order will vary in each group (cluster)

http://content.digitalwell.washington.edu/msr/external_release_talks_12_05_2005/13651/lecture.htm

Example of prediction modelList which variables are closely associated with Principal ComponentsSee how Principal Components look like in real lifeHow the Principal Components can be predicted?(e.g. least square technique)

Prepare a model for component balanceUnderstand host with fewer parameters (Principal components)Estimate the Prakruti (constitution of a person)Estimate the Vikruti (Loss of harmony in constitution)

Stress and disturbed sleep are such factors which could contribute spontaneously to the DCM

The procedure described is based on phenotypic characterizationThe preventive strategies could be described as:NutriphenomicsPharmacophenomics etc

Now, human genomic data is also availableThe preventive strategies are:NutrigenomicsPharmacogenomics etc

Preventive strategies

Ancient Indian methods to tackle total disease burden in a localitySeasonal lifestyle goals (Rutucharya)Diurnal lifestyle goals (Dinacharya)

How to implement goalsControl by risk groups (Vrata) Transformation of patients (Vaikalya)Festivals for everybody (Sana)

Message of Rishi Panchami Vrata Reduce artifacts from your lifestyle

Make up of Vrata, Vaikalya and SanaFunctional foodsNutraceuticalsExercises and Spiritual practices

Dr V Prakash

Importance of Indian Medicine for Disease Informatics

Genetic and lifestyle variables of a host could be described in fewer words (e.g. Vata, Pitta and Kapha) to understand events in Disease Causal Chains (DiCC)A great help in drawing DiCC

Disease informatics for setting up Disease definition, drawing Disease Causal Chain / Web, marking Risk Events, Backend and Frontend Events, and Health Problem Solutions

http://bmj.bmjjournals.com/cgi/eletters/331/7516/566#134452

Thanks

Points in Indian Medicine is outcome of discussion with Dr. Mandar AkkalkotkarStatistics guru is Dr. Sham J Amdekar