This short presentation describes molecular epidemiology, differentiate it from genetic epidemiology, and also deals with ascertaining the cause of disease.

1. Molecular Epidemiology and
Molecular basis of Disease
Bhoj R Singh
Division of Epidemiology, ICAR-IVRI, Izatnagar-
243122, India

2. Molecular Epidemiology
• The term “molecular epidemiology" was first coined by Edwin D.
Kilbourne in a 1973 article entitled "The molecular epidemiology of
influenza”.
• Epidemiology using molecular biology tools: the use of the techniques of
molecular biology, and the epidemiology in understanding the disease
causation, distribution and impact of different determinants.
• Molecular epidemiology is a branch of epidemiology that focuses on the
contribution of potential genetic and environmental risk factors, identified
at the molecular level, to the aetiology, distribution and prevention of
disease within herds, breeds, lines and across populations.
– Molecular epidemiology describes a process of identifying the genetic basis of
disease, including variants within hosts and pathogens that influence
infection, transmission, and prevention. (Biomarkers, genetic markers, specific
genes, virulence genes, susceptibility markers, meta-genome bases
knowledge).
• Molecular and genetic epidemiology represent two separate branches of
epidemiology whose boundaries are overlapping. While molecular
epidemiology evaluates the association of variations in known genes with
risk of cancer, genetic epidemiology aims to identify the unknown genes
that influence risk of malignancies.

3. • The unique disease principle: Conceptually, each individual has a
unique disease process different from any other
individual, considering uniqueness of the exposome and its unique
influence on molecular pathologic process in each individual.
Studies to examine the relationship between an exposure and
molecular pathologic signature of disease.
• Tools of Molecular Epidemiology: PCR, metagenomics, Proteomics,
RAPD, RFLP, AFLP, ERIC PCR, MLEE, MLST, plasmid profiling, protein
and genetic profiling using gel electrophoresis techniques like two
or three dimensional SDS-PAGE, pulsed-field gel electrophoresis,
Western blotting, Southern Blotting etc.
• Uses of Molecular epidemiology:
– Molecular surveillance of disease risk factors
– Measuring the geographical and temporal distribution of disease risk
factors
– Characterizing the evolution of pathogens and classifying new
pathogen species

4. Receptors in hosts for common virus
Source: https://viralzone.expasy.org/5356 & https://thenativeantigencompany.com/virus-receptors/
Virus group Receptors in hosts
Avian hepatitis B virus Carboxypeptidase D
Avian influenza A virus DC-SIGN; CLEC4M(L-SIGN); Neu5Gc α 2,3 sialic acid
Blue tongue virus Sialic acid, Heparan sulphate, Intigrin
Bovine Corona virus Sialic acid
Bovine Herpes virus Heparan sulphate; Poliovirus receptor (PVR); Nectin 1 (PVRL-1)
Bovine influenza D virus Neu 5; 9Ac2 Sialic acid
Bovine leukemia virus AP3D1 (BLVR)
Bovine Parvovirus Α2,3 N-linked and O-linked sialic acid
Bovine Viral Diarrhoea virus CD46
Canine distemper virus Nectin 4 (PVRL4); SLAMF1
Canine parvovirus Transferin receptors (TFRC)
Classical swine fever virus Heparan sulphate; CD46
Dengue virus Mannoise receptor (MRC1); Heparan sulphate; CLEC5A; DC-SIGN; HAVCR-1(T1M1), CLDN1; Tyro3 &
AXL (TAM family); Laminin receptors (RPSA)
Ebola virus DC-SIGN; CLEN4G (LSECtin); HAVCR1 (TIM1); Tyro3 & AXL (TAM family); CLEN4M(l-SIGN);
NPC1
Equine Herpesvirus MHC class 1(HLA)
Feline calcivirus JAM-A/F11R
Feline immunodeficiency virus TNFRSF4; CXCr4
Feline leukemiavirus A; B, C; T SLC19A2(Pit2); SLC20A1(Pit1) & Pit2; FLVCR1; FeLIX & Pit1
Equine Herpesvirus MHC class1 (HLA)
FMD Virus and Hantavirus Integrins αV & β 1,3,8,6
SARS COV and SARS COV2 ACE2
Rabies virus nAchR
Human immunodeficiency virus CD4
Vesicular stomatitis virus PS receptors
MERS Coronavirus DPP4
Nipahvirus Ephrin B2, Ephrin B3
Lassavirus DAG1
Junin arenavirus, Machupvirus TRFC
Sendaivirus ASGR2

5. Understanding Disease causation
Association of causes: An association exists if two variables appear to be
related by a mathematical relationship; that is, a change of one appears to
be related to the change in the other. Association is necessary for a causal
relationship to exist but association alone does not prove that a causal
relationship exists. A correlation coefficient or the risk measures often
quantify associations.
– Negative Association (Inverse Relationship): The magnitude of one
variable appears to move in the opposite direction of the other associated
variable. The correlation coefficient is negative and, if the relationship is
causal, higher levels of the risk factor are protective against the outcome.
– Positive Association (Direct Relationship): The magnitudes of both
variables appear to move together up or down. The correlation coefficient
is positive and, if the relationship is causal, higher levels of the risk factor
cause more of the outcome.
Cause: The combination of necessary and sufficient factors (e.g., attributes
and exposures) the presence of which, alone or in combination, at some
time during an individual’s life, inevitably result in disease in that
individual.

6. Causes
Etiology: The study of disease causes and their modes of operation.
Causal Pathway (Causal Web, Cause and Effect Relationships): The
actions of risk factors acting individually, in sequence, or together
that result in disease in an individual. These pathways are often
different with different sets of risk factors for individuals in
different situations. Understanding these pathways and their
differences is necessary to devise effective preventive or corrective
measures (interventions) for a specific situation. What is effective
in one pathway may not be in another because of the differences
in the component risk factors. (e.g., bronchopneumonia in a
housed calf vs. in a feedlot calf).
Necessary Cause: A risk factor that must be, or have been, present
for the disease to occur (e.g., a specific infectious agent for a
particular infectious disease). Although necessary, few infectious
agents cause disease by themselves alone.
Sufficient Cause: The minimal combination of risk factors acting on
the individual, on the etiologic agent if one is involved, or in the
environment whose occurrence in an individual’s life inevitably
results in disease. A disease can often be caused by more than one
set of sufficient causes and thus different causal pathways for
individuals contracting the disease in different situations.

7. Inductive Inference for discovering
causal relationships
• Mill's Eliminative Methods of Induction (System of
Logic, 1843):
– Method of Agreement: "If two or more instances of the phenomenon have only one
circumstance in common, the circumstance in which alone all instances agree is the
cause or effect of the given phenomenon."
– Method of Difference: "If an instance in which the phenomenon under investigation
occurs, and an instance in which it does not occur, have every circumstance in
common save one, that one occurring in the former, the circumstance in which alone
the two instances differ, is the effect, or the cause, or an indispensable part of the
cause, of the phenomenon."
– Method of Residues: "Subduct from any phenomenon such part as is known by
previous inductions to be the effect of certain antecedents, and the residue of the
phenomenon is the effect of the remaining antecedents."
– Method of Concomitant Variations: "Whatever phenomenon varies in any manner
whenever another phenomenon varies in some particular manner, is either a cause or
an effect of that phenomenon, or is connected with it through some fact of
causation.“
– Method of Analogy: If it happens like that the similar other event should also take the
same route. Through comparison of patterns of the diseases.

8. Koch's postulates are
The postulates were formulated by Robert Koch and Friedrich Loeffler
in 1884 and refined and published by Koch in 1890.
• The microorganism must be found in abundance in all organisms
suffering from the disease, but should not be found in healthy
organisms.
• The microorganism must be isolated from a diseased organism and
grown in pure culture.
• The cultured microorganism should cause disease when introduced
into a healthy organism.
• The microorganism must be re-isolated from the inoculated,
diseased experimental host and identified as being identical to the
original specific causative agent.
• However, Koch abandoned the universalist requirement of the first
postulate altogether when he discovered asymptomatic carriers of
cholera and, later, of typhoid fever.

9. Koch's postulates for 21st Century:
The use of new methods in disease diagnosis has led to revised versions of Koch’s
postulates: Fredricks and Relman (1996) have suggested the following set of
Koch’s postulates for the 21st century:
• A nucleic acid sequence belonging to a putative pathogen should be present in
most cases of an infectious disease. Microbial nucleic acids should be found
preferentially in those organs or gross anatomic sites known to be diseased, and
not in those organs that lack pathology.
• Fewer, or no, copies of pathogen-associated nucleic acid sequences should occur
in hosts or tissues without disease.
• With resolution of disease, the copy number of pathogen-associated nucleic acid
sequences should decrease or become undetectable. With clinical relapse, the
opposite should occur.
• When sequence detection predates disease, or sequence copy number correlates
with severity of disease or pathology, the sequence-disease association is more
likely to be a causal relationship.
• The nature of the microorganism inferred from the available sequence should be
consistent with the known biological characteristics of that group of organisms.
• Tissue-sequence correlates should be sought at the cellular level: efforts should be
made to demonstrate specific in situ hybridization of microbial sequence to areas
of tissue pathology and to visible microorganisms or to areas where
microorganisms are presumed to be located.
• These sequence-based forms of evidence for microbial causation should be
reproducible.

10. Hill's Criteria of Causation (1965)
In 1965 Austin Bradford Hill detailed criteria for assessing evidence of causation. These guidelines are
sometimes referred to as the Bradford-Hill criteria, but this makes it seem like it is some sort of
checklist. For example, Phillips and Goodman (2004) note that they are often taught or referenced
as a checklist for assessing causality, despite this not being Hill's intention. Hill himself said "None
of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect
hypothesis and none can be required sine qua non".
• Strength: A small association does not mean that there is not a causal effect, though the larger the
association, the more likely that it is causal
• Consistency: Consistent findings observed by different persons in different places with different
samples strengthens the likelihood of an effect.
• Specificity: Causation is likely if a very specific population at a specific site and disease with no other
likely explanation. The more specific an association between a factor and an effect is, the bigger the
probability of a causal relationship.
• Temporality: The effect has to occur after the cause (and if there is an expected delay between the
cause and expected effect, then the effect must occur after that delay).
• Biological gradient: Greater exposure should generally lead to greater incidence of the effect.
However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an
inverse proportion is observed: greater exposure leads to lower incidence.
• Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that
knowledge of the mechanism is limited by current knowledge).
• Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of
an effect. However, Hill noted that "... lack of such [laboratory] evidence cannot nullify the
epidemiological effect on associations".
• Experiment: "Occasionally it is possible to appeal to experimental evidence".
• Analogy: The effect of similar factors may be considered.

11. Quiz
1. Define molecular epidemiology in your words with
example.
2. The Koch’s postulates are applicable for what types of
diseases and which are the most volatile postulates?
3. Molecular techniques you have used in past and the
techniques you want to use in future for epidemiology
and why?
4. What are different types of causes of disease define with
example of a disease causation?
5. Enlist differential and non differential diagnostic
biomarker molecules of bacterial, viral and fungal
infections.
6. Enlist the receptors for 5 disease causing viruses.