Chapter 14 Evolution and human
health

The germ theory of disease was one of the most
important breakthroughs in medicine.

Louis Pasteur in 1858 proposed that diseases
were caused by microorganisms.

Within a few years the bacteria responsible for
diseases such as anthrax, gonorrhea, typhoid
fever and tuberculosis had been identified.
Anti-bacterial developments
 Infection-fighting
developments followed
soon thereafter.
 Antiseptic
surgery was developed by
Joseph Lister, improved housing and
sanitation reduced infection rates, and the
discovery of antibiotics allowed infections
to be treated.
Anti-bacterial developments

As a result of these developments, death rates
from infection declined rapidly.

By 1997 the TB death rate was < 0.4 per
100,000, less than 0.2% of the 1900 death rate.

By the end of the 1960’s the medical community
considered that infectious disease had been
conquered.
Fig 13.2
Evolving pathogens: antibiotic
resistance
 Unfortunately,
pathogens have evolved in
response to the selection pressures
imposed by medicine.
 Antibiotics
are chemicals that kill bacteria
and the first antibiotic was penicillin
isolated from the mold Penicillum by
Alexander Fleming.
Evolving pathogens: antibiotic
resistance
 Penicillin
saved thousands of lives in
World War II and subsequently.
 Today,
however, penicillin is ineffective
against bacteria that previously were
highly vulnerable and many bacteria have
evolved resistance to multiple antibiotics.
 As a result, infectious diseases have
reemerged as a significant threat.
Evolving pathogens: antibiotic
resistance
 There
is clear evidence that use of
antibiotics selects for resistance in
bacteria.
 Studies
have documented the evolution of
antibiotic resistance in bacterial
populations within individual patients and
also in larger-scale studies of human and
bacterial populations.
Evolving pathogens: antibiotic
resistance
 For
example, researchers have found that
the incidence of antibiotic-resistant
bacteria is higher among patients who
have been previously treated with that
antibiotic.
 For example the incidence of isoniazidresistant bacteria is 21% in relapsed cases
of TB, but only 8% in new cases.
Evolving pathogens: antibiotic
resistance
 On
a larger scale, antibiotic resistance has
been shown to track society-wide antibiotic
use.
 In
the late 1980’s and early 1990’s
penicillin resistance levels among
Pneumococus bacteria in Iceland rose
sharply.
Evolving pathogens: antibiotic
resistance
 When
health authorities campaigned to
reduce use of the antibiotic, rates of use of
penicillin fell 13% and rates of bacterial
resistance declined.
Fig 13.7
Costs of resistance to bacteria
 The
fact that resistance rates fell in
Iceland when Penicillin use dropped
suggests resistance imposes a cost on
bacteria.
 If
the cost is high, non-resistant bacteria
should have an advantage in a penicillinfree environment.
Costs of resistance to bacteria
 Costs
of resistance suggest that
suspending use of an antibiotic might
allow populations to evolve to a nonresistant state again.
Costs of resistance to bacteria
 Unfortunately,
resistant bacteria may also
evolve ways to reduce or eliminate the
costs of resistance and so not be
outcompeted by non-resistant strains.
 A study by Schrag et al. (1997)
documented this.
Schrag et al. (1997)
 They
studied streptomycin-sensitive E. coli
and screened for resistant mutants.
 Streptomycin interferes with protein
synthesis by binding to a ribosomal
protein.
 Point mutations in gene rpsL coding for
that ribosomal protein can confer
resistance.
Schrag et al. (1997)
 Researchers
competed resistant and
sensitive strains against each other. Found
that, initially, resistant strains were at a
disadvantage and sensitive strains grew
better.
Schrag et al. (1997)
 Next,
resistant strains that were allowed to
evolve for many generations in the lab and
then competed against sensitive strains.
 Resistant strains had evolved and
mutations that compensated for costs of
streptomycin resistance had been selected
for.
 As a result, resistant strains outcompeted
sensitive strains.
Schrag et al. (1997)
 Schrag
et al.’s results suggest that there is
no guarantee that bacterial populations
can be restored to vulnerability by
withdrawing an antibiotic from use.
 Thus,
steps to avoid bacteria developing
resistance need to be taken.
Steps to avoid evolution of
resistance





Reduce infection rate (avoid e.g. undercooked
eggs and meat; wash hands to slow disease
spread).
Limit use of antibacterial soaps and cleaners.
Doctors should avoid prescribing antibiotics for
viral infections.
Drugs that target as few bacteria as possible
should be used.
Antibiotic use in animal feed should be
eliminated.
Evolving pathogens: Evading
host immune response
 The
human immune system mounts a
formidable defense against microbes.
 Pathogens
 Large
naturally evolve responses.
population sizes, short generation
times and high rates of mutation make
pathogens a formidable opponent.
Evolution of influenza virus
 Influenza A causes
annual flu epidemics
and occasional global pandemics including
the infamous 1918 Spanish flu.
 In
a normal flu season flu kills about
20,000 Americans. The 1918 flu infected
about 20% of the world’s population and
killed 50-100 million people.
Evolution of influenza virus
 Influenza A has
a genome of 8 RNA
strands that code for a total of 10 proteins.
 These
include polymerases, structural
proteins and coat proteins.
13.3
Evolution of influenza virus
 Main
viral coat protein is hemagglutinin.
This binds to sialic acid on host cell’s
surface to gain entry.
 Hemagglutinin
is also the primary protein
recognized and attacked by the immune
system.
Evolution of influenza virus
 Survival
for a viral strain means it must
constantly find new hosts that do not
recognize its hemagglutinin protein.
 The
immune system recognizes certain
stretches of the hemagglutinin protein,
which are called antigenic sites.
 Viruses that have novel antigenic sites
should have a selective advantage.
Evolution of influenza virus
 Fitch
et al. (1991) tested this hypothesis
by examining frozen flu virus strains dating
from 1968 to 1987.
 Flu
virus evolves about 1 million time
faster than humans so 20 years is
equivalent to 20 million years of human
evolution.
Evolution of influenza virus
 Flu
strains evolved at a steady rate (about
6.7 X 10–3 mutations per nucleotide per
year.
13.4
Evolution of influenza virus
 Most
flu samples examined represented
side branches of one main evolutionary
tree of multiple closely related strains.
 Instead
of a wide variety of lineages
derived from different 1968 era flu viruses
there was one main lineage, the other
viruses from 1968 having gone extinct.
Evolution of influenza virus

Fitch et al. suspected that the successful strain
would have had more mutations in its antigenic
sites than the extinct strains.

In surviving lineage they identified 33 amino acid
replacements in antigenic sites and 10 in non
antigenic sites. In extinct lineages found 31
replacements in antigenic sites and 35 in non
antigenic sites.
Evolution of influenza virus
 Surviving
strain had more than 75% of
replacements in antigenic sites versus less
than 50% for extinct strains.
 Statistically
significant difference, which
suggests increased variability in antigenic
sites gave the surviving strain an
advantage.
Evolution of influenza virus
 Further
evidence that flu is under strong
selection from human immune systems
comes from examining the rate of silent
versus replacement nucleotide
substitutions in strains of flu virus.
 Silent
mutations don’t result in a change in
the amino acid coded for.
Evolution of influenza virus
 Rates
of replacement substitutions are
statistically much higher than rates of
silent mutations, which infers selection is
strongly favoring replacements.
Origins of pandemic flu strains
 Flu
strains with novel hemagglutinin genes
have a selective advantage.
 Hence,
any strain with a hemagglutinin
sufficiently different from any that human
immune systems had previously been
exposed to, could spread uncontrollably.
Origins of pandemic flu strains

The influenza virus contains 8 different RNA
strands and different strains of flu can infect a
host.

If a host becomes infected with two different flu
strains these strains could swap RNA strands

As a result of this gene exchange a novel, very
different, flu strain might result.
Origins of pandemic flu strains
 There
is strong evidence that flu strains do
swap genes.
 Phylogenetic
analysis of flu strains by
Gorman et al. (1991) shows this.
Origins of pandemic flu strains


Gorman et al. (1991) determined the nucleotide
sequences of influenza nucleoprotein genes.
Nucleoprotein gene apparently most important
gene for determining host specificity (enables
strain to infect a certain host) and tends to limit it
to that species.
 Thus, phylogeny of this gene should give good
strain history.
Origins of pandemic flu strains
 There
are distinct clades of strains that
infect mainly humans, mainly pigs, mainly
birds, etc.
Origins of pandemic flu strains
 Branch
tips give date of strain and a viral
subtype (e.g. H3N2).
 Viral
subtype specifies hemagglutinin-3
and neuraminidase-2). Neuraminidase,
like hemagglutinin, is a coat protein.
 The
number specifies a group of proteins
that provoke the same antibody response.
Origins of pandemic flu strains
 Each
hemagglutinin group constitutes a
clade. H1s are more closely related to
each other than H2s, etc.
 Same
logic applies to the neuraminidases.
Origins of pandemic flu strains
 Examining
two strains of flu from Australia
in 1968 Victoria (H2N2) and Northern
Territory (H3N2) shown in bold on next
slide we see that they have nucleoproteins
and neuraminidases that are closely
related, but hemagglutinins that are
distantly related.
Origins of pandemic flu strains
 How
is this possible?
 Simplest
explanation is that flu strains
swap genes.
 Before
1968 pandemic human flu strains
had never carried H3. Where did H3
come from?
Origins of pandemic flu strains
 A phylogeny
of H3 strains by Bean et al.
(1992) shows that human H3 branches
from within the bird H3 tree.
Origins of pandemic flu strains
 Apparently,
1968 pandemic flu strain
acquired its genes from birds.
 How
did it get into humans?
Origins of pandemic flu strains
 Bird
flu strains are known to infect pigs
and pig strains can infect humans,
especially, where humans and pigs live in
close contact.
 Human
1968 pandemic H3N2 flu is most
similar to a 1976 strain isolated from pigs
in Hong Kong.
Origins of pandemic flu strains
 Popular
hypothesis among flu researchers
is that human pandemics begin when bird
and human flu strains simultaneously
infect a pig, swap genes and move from
pigs to people.
Origins of pandemic flu strains
 It
is feared that the current avian flu
(H5N1) that has killed millions of birds
worldwide and several hundred people will
mutate into a form readily transmissible
from person to person, thus triggering a
new pandemic.
Evolution of virulence in
pathogens
 Virulence
is the harm done to a host by a
pathogen.
 Virulence
differs widely from pathogen to
pathogen. The cold virus is not harmful,
but smallpox, cholera, and Ebola virus are
often or usually lethal.
Evolution of virulence in
pathogens
 There
are three general models to explain
the evolution of virulence.
 (1) The coincidental evolution hypothesis.
Virulence of some pathogens in humans
may not be a target of selection at all.
Instead, it may be an accidental result of
selection on other traits.
Evolution of virulence in
pathogens
 Tetanus
is caused by a soil bacterium
Claustridium tetanae that can live in
human wounds, but usually lives in soil.
 It
secretes a potent neurotoxin, but that
toxin is probably a result of selection for
living in soil.
Evolution of virulence in
pathogens
 (2)
The short-sighted evolution hypothesis.
Many generations of a pathogen may live
in a host before finding a new host
becomes necessary.
 Under these conditions traits that favor
within-host fitness may spread even if they
hinder transmission to new hosts.
Evolution of virulence in
pathogens

Polio virus normally lives in cells that line the
gut, causes no symptoms, and is transmitted via
feces.
 Occasionally, the virus invades nerve cells,
which may be selected for because lack of
competition enhances within-host fitness.

However, virus cannot be transmitted to a new
host from nervous tissue.
Evolution of virulence in
pathogens
 In
patients with HIV infections shortsighted evolution also occurs.
 Patients
whose immune systems are
destroyed eventually die, but selection
favors those virus particles that reproduce
most quickly even though doing so
ultimately dooms the virus particles along
with the host.
Evolution of virulence in
pathogens

Late in an HIV infection HIV particles that use a
cell receptor called CXCR4 as a coreceptor to
enter T-cells become more common.

The use of the type of T-cell with this coreceptor
is short-sighted because (i) viruses that use
them do not get transmitted to other hosts and
(ii) attacking these cells is the final blow to the
host’s immune system and death soon follows.
Evolution of virulence in
pathogens


(3) The trade-off hypothesis.
Traditionally, biologists believed that evolution
would favor lower virulence because killing the
host would kill pathogens too.
 However, if increasing the risk to the host
enhances the pathogens’ prospects of
transmission to other hosts increased virulence
could be favored by selection.
Evolution of virulence in
pathogens
 Hence,
selection should favor strains that
strike a balance between costs and
benefits of harming their host.
 HIV-1
is more damaging to its hosts than
HIV-2, but it is more likely to be
transmitted because of its higher viral
load. Thus, HIV-1 has become much
more common than HIV-2.
Evolution of virulence in
pathogens
 A key
assumption of the trade-off
hypothesis is that the pathogen cannot
reproduce inside the host without doing it
some harm (because energy and nutrients
are taken from the host and pathogen
waste products must be removed by the
host).
Evolution of virulence in
pathogens

Host mounts an immune response to eliminate
the costs of hosting the pathogen.

All else being equal, pathogens with higher
within-host reproductive rates should be
transmitted to hosts more effectively.

However, too rapid a reproduction rate may
debilitate the host so much that transmission is
reduced.
Evolution of virulence in
pathogens
 Messenger
et al. (1999) examined this
trade-off in E. coli and a virus (a
bacteriophage called f1.)
 Phage
invades bacterium and lives inside
as a plasmid. Induces cell to make copies
of it, which are released from the cell.
Evolution of virulence in
pathogens
 Production
of new phage copies slows
cells growth rate by about a third, but
when cell does divide both daughter cells
carry the phage.
 Thus,
phage has two modes of
transmission: vertically from one
generation of host cells to the next and
horizontally from one host to another.
Evolution of virulence in
pathogens
 Messenger
et al. (1999) maintained two
sets of cultures for 24 days and controlled
the virions ability to transmit itself vertically
and horizontally
 In
first culture they alternated 1 day-long
vertical transmission phases with brief
horizontal transmission phases.
Evolution of virulence in pathogens
 In
second culture alternated 8-day long
vertical transmission with brief horizontal
transmission phases.
 After
24 days compared virulence as
growth rate of infected hosts in the two
populations.
Evolution of virulence in
pathogens
 Messenger
et al. predicted that phages
that induced more phage reproduction
would slow host growth more.
 Also predicted that in 8-day cultures
phages would evolve lower reproductive
rates and be less virulent.
 Longer vertical transmission phase should
select for less virulence.
Evolution of virulence in
pathogens
 Results
were consistent with predictions.
 Host
growth was slowed most by phage
strains that reproduced faster.
 Eight-day
cultures had lower reproductive
rates and lower virulence than one-day
cultures.
Virulence in human pathogens
 Paul
Ewald has applied trade-off
hypothesis to show that the mechanism by
which a pathogen is transmitted is likely to
have a strong influence on the pathogens
virulence.
Virulence in human pathogens
 Cold
and flu viruses depend for
transmission on direct contact between
infected and uninfected people.
 In
contrast, diseases such as malaria are
transmitted by insect vectors
Virulence in human pathogens
 These
differences in mode of transmission
should select for different levels of
virulence.
 A cold
cannot afford to incapacitate its
host because it needs the host to
encounter new potential hosts. Malaria,
however, can be transmitted from a
debilitated host.
Virulence in human pathogens
 Ewald
predicted that vector-borne
diseases should have higher mortality
rates than those that depend on direct
transmission.
 Surveyed
wide variety of diseases. Data
fit prediction.
Virulence in human pathogens
 Vast
majority of directly transmitted
diseases have mortality rates below 0.1%.
 More
than 60% of vector-borne diseases
have mortality rates >0.1%.
13.10
Virulence in human pathogens
 Ewald
also applied same logic to bacteria
that infect the digestive tract.
 These can be transmitted directly from
person to person or via contaminated
water.
 Water plays same role as a vector
because sewage from severely infected
people enters the water supply as easily
as sewage from uninfected people.
Virulence in human pathogens
 Ewald
studied data on about 1,000
outbreaks of disease caused by 9 types of
bacteria and contrasted mortality rates
with the fraction of outbreaks that were
waterborne. He predicted that waterborne
bacteria would be more virulent.
 Data
are consistent with Ewald’s
hypothesis, with cholera the most virulent.
Virulence in human pathogens
13.11
Virulence in human pathogens
 Ewald’s
work suggests that human
behavior can affect disease severity.
 Dumping
untreated sewage in rivers and
poor hygiene facilitate the transmission of
pathogens. This, in turn, favors increased
virulence.
Applying adaptationist thinking to
humans.
 To
what environment are humans
adapted?
 Before
the development of agriculture
approximately 10,000 years ago humans
lived as hunter-gatherers in an
environment very different from a modern
urban environment.
Applying adaptationist thinking to
humans.
 Modern
humans live in an environment
radically different from the stone-age one
their bodies and brains evolved in.
 Comparisons
of modern hunter-gatherer
societies and modern urban societies
show major differences in diet and activity
level.
Applying adaptationist thinking to
humans.
13.16
Applying adaptationist thinking to
humans.
 More
subtle environmental differences,
however, also exist and may increase the
rates of a variety of medical conditions.
Applying adaptationist thinking to
humans: Myopia
 The
frequency of myopia (or
nearsightedness) in many populations is
25% or more.
 Studies of twins show that myopia is
partially heritable.
 Given the disadvantage of poor vision to
hunter-gatherers why haven’t alleles for
myopia been eliminated by selection?
Applying adaptationist thinking to
humans: Myopia
 Solution
is likely that alleles that
predispose us to myopia do so only under
modern conditions (e.g. reading under
artificial light).
Applying adaptationist thinking to
humans: Myopia
 Evidence
consistent with this explanation
is provided by populations that have only
recently adopted a modern lifestyle.
 A study
of an Inuit group in Barrow, Alaska
showed that there was a clear age
difference between people with and
without myopia.
Applying adaptationist thinking to
humans: Myopia
 People
aged 6-35 who had attended
modern schools and read a lot had a 42%
rate of myopia.
 Among
older individuals (36-88) who had
less schooling and read little, only 5%
were myopic.
Applying adaptationist thinking to
humans: Myopia
 Thus,
it appears that alleles that
predispose humans to myopia do not do
so in a hunter gatherer environment.
Applying adaptationist thinking to
humans: Breast Cancer

About 1 in 8 North American women develops
breast cancer, some of whom die while in their
child-bearing years.

Like myopia, breast cancer has both genetic and
environmental components.

Given the high rate of breast cancer why hasn’t
selection eliminated genes that cause the
disease or selected for individuals resistant to
environmental effects that induce cancer?
Applying adaptationist thinking to
humans: Breast Cancer
 Possible


solutions include:
(i) Breast cancer may be caused by a
pathogen (e.g. a virus or bacterium that has
evolved with us).
(ii) Breast cancer, like myopia, may be a
disease of civilization
Applying adaptationist thinking to
humans: Breast Cancer
 Mice
carry a virus called Mouse Mammary
Tumor Virus (MMTV) that causes the
mouse equivalent of breast cancer.
 There
are suspicions that MMTV or a
similar virus may cause breast cancer in
humans.
Applying adaptationist thinking to
humans: Breast Cancer
 Two
suggestive pieces of evidence
support the hypothesis.
 (i) In an analysis of 314 breast tissue
samples (Wang et al. 1995) 38.5% of
cancer tissue samples contained DNA
sequences similar to MMTV, but only 1.9%
of normal breast tissue samples did.
Applying adaptationist thinking to
humans: Breast Cancer
 Second
piece of evidence comes from
geographical level analysis looking at
incidence of breast cancer in relation to
distribution of the mouse species Mus
domesticus and Mus musculus (Stewart
et al. (2000)).
Applying adaptationist thinking to
humans: Breast Cancer
 Mus
domesticus occurs in Western
Europe Mus musculus occurs in Eastern
Europe.
 Mus
domesticus also tends to be more
heavily infected with MMTV.
Mus musculus (dark green)
Fig 13.17a
Mus domesticus (light blue)
Applying adaptationist thinking to
humans: Breast Cancer
 If
MMTV causes breast cancer, then rates
of breast cancer should be higher in
Western Europe than in Eastern Europe.
 Data fit that pattern.
13.17b
Applying adaptationist thinking
to humans: Breast Cancer
 Data
on MMTV are suggestive, but not
definitive. MMTV has not been isolated
from breast tumors and possible route of
infection is unknown.
 Also,
MMTV cannot account for more than
40% of breast cancer cases. Thus, need
to consider the alternative hypothesis.
Applying adaptationist thinking
to humans: Breast Cancer
 Breast
cancer as a disease of civilization.
 Monthly
menstrual cycle of most
modern/western women is considered
normal.
 However,
epidemiological evidence
suggests monthly menstrual cycles may
increase the risk of breast cancer.
Applying adaptationist thinking to
humans: Breast Cancer

Breast cancer risk increases with:




Early onset of menstruation.
Later in life woman first gives birth.
Less time woman spends nursing.
Menstrual cycling appears to elevate risk of
cancer because the combination of estrogen
and progesterone stimulates cell division in cells
lining milk ducts. More cell division increases
chance of mutations.
Applying adaptationist thinking to
humans: Breast Cancer

Is monthly menstrual cycling normal?

Strassmann (1999) studied menstruation among
the Dogon of Mali. Dogon use no contraception.

Women 20-35 spend little time menstruating.
They are either pregnant or experiencing
lactational amenorrhea (no cycling because of
breastfeeding).
Applying adaptationist thinking to
humans: Breast Cancer
 At
any given time less than 30% of Dogon
women are undergoing menstrual cycling.
 Over
the course of her reproductive
lifetime a Dogon woman experiences
about 100 cycles as compared to the
approximately 300 cycles of a North
American woman.
Number of menstrual cycles in two years among Dogon
women of reproductive age
.
Fig 13.18a
(of Dogon women).
13.18b
Applying adaptationist thinking to
humans: Breast Cancer

There are no data on breast cancer rates in
Dogon women, but rates in comparable
populations are only about 1/12th the North
American rate.

Alternative contraceptive regimens that more
closely mimic the ancestral menstrual cycling
pattern might reduce the risk of breast cancer
among North American women.