Advances in Anthropology
2013. Vol.3, No.2, 96-100
Published Online May 2013 in SciRes (http://www.scirp.org/journal/aa) http://dx.doi.org/10.4236/aa.2013.32013
Copyright © 2013 SciRes.
96
A Case Study and Meta-Analysis of Type 2 Diabetes Research
Michael L. Gracia
Department of Anthropology, University of North Carolina, Chapel Hill, USA
Email: mgracia@live.unc.edu
Received March 7th, 2013; revised April 7th, 2013; accepted April 16th, 2013
Copyright © 2013 Michael L. Gracia. This is an open access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited.
In the last decade, a new wave of inspired research surrounding a transcription factor’s role in blood-sugar
homeostasis has emerged. Transcription Factor 7-like 2 (TCF7L2 or TCF4), a member of the Wnt signal-
ing pathway, is intimately involved in suppressing glucagon synthesis. It also may affect β-cell function.
Regiospecific trends concerning the selection of its molecular variants, their dependency on environ-
mental and behavioral changes, and their relative associations with type 2 diabetes (T2D) have become
well documented. This dynamic and nuanced understanding of one T2D risk factor should be desired in
all other phases of study. An open and incorporative mindset such as this can revitalize the research field.
Keywords: Type 2 Diabetes; T2D; Transcription Factor 7-Like 2; TCF7L2; TCF4; West Africa; East Asia;
World Health
Prologue
As a traveling physician, you are summoned to West Africa.
The secular humanitarian-aid NGO Médecins Sans Frontières
has established a proxy in Freetown, Sierra Leone, and Conakry,
Guinea adding 800 beds and rehydration points in response to a
cholera epidemic catalyzed by the rainy season. Somewhere
along the border of Guinea and Sierra Leone, you find a young
man suffering from polyuria, blurred vision, fatigue, and other
discrete symptoms of type 2 diabetes. Although his long and
slender build is revealing enough, you take a crude measure of
his body mass index (BMI) to confirm that he is underweight.
Genetic predisposition, dietary considerations, and Metformin
are all vital components of your prognosis and treatment. Your
diagnosis, measurements, and observations combine to reveal a
very unique incidence of a metabolic disorder thought by the
majority of clinicians to be intimately tied to obesity.
In East Asia, you volunteer to support relief efforts in Indo-
nesia where a 7.6 magnitude earthquake struck the western
coast of Sumatra. While supplementing psychiatric support in
Padang, you treat a slightly obese, elderly man showing cogni-
tive dysfunction after being brought to the hospital for stroke-
like symptoms. In this case, your diagnosis of diabetes is much
more straightforward, and in your follow-up, you emphasize a
dedication to exercise and several lifestyle changes in addition
to the supplementary insulin.
Introduction
All in all, these two hypotheticals reveal the elegance and
pathophysiological diversity of one of humanity’s most com-
mon forms of suffering. Type 2 diabetes affects 285 million
people worldwide, a 900 percent increase from a census taken
in 1985 (WHO). In this article, we dive deeply into and explore
a case example of a specific genetic and micro-regional dimen-
sion of type 2 diabetes, emphasizing the environment’s role in
governing pleiotropic trade-offs in West Africa and East Asia.
Transcription factor 7-like 2, a multi-regulatory transcription
factor, is a perfect candidate for such an analysis by its dual
involvement in blood sugar homeostasis and regiospecificity
within those areas. All the while, we synthesize a new argument
that combines this information with lessons learned from an
analogous, better understood phenomenon that has governed
distributions of malaria and sickle cell anemia across Africa for
thousands of years. These genetic, micro-regional, and parallel
ways of thinking illuminate the necessity of a multiple systems
approach to studying type 2 diabetes and reveal a method of
bringing focus to the ambiguities and voids still remaining
within type 2 diabetes research.
Epidemiological Overview
Type 2 diabetes (T2D) has become a part of the human con-
dition; it is a global phenomenon with a distribution that
reaches across the entire spectrum of human populations. In
1982, P. Zimmet, an Australian-born diabetologist, offered “An
Epidemiological Overview of type 2 (non-insulin-dependent)
diabetes”. Concerning the world distribution, the paper clings to
the idea that the recent rise in diabetes incidence mirrors the
equally prominent rise in “westernized lifestyles” among new
and old populations (Zimmet, 1982). T2D incidence is lowest
in isolated populations such as Inuit, Alaskan Athabascan Indi-
ans, and scattered East Asian populations still living a “tradi-
tional lifestyle” (Zimmet, 1982). Conversely, diabetes preva-
lence is highest in American Indians, specifically the American
Pima Indians; urbanized Pacific Islanders like the Micronesian
population of the Nauru; and among migrant South Asian In-
dian communities within Singapore, Malaysia, and South Af-
rica (Zimmet, 1982). This notion of higher susceptibility among
immigrant South Asian Indians resonates well with a growing
awareness of a varying degree of “genetic predisposition” for
M. L. GRACIA
T2D existing among all people. Spikes in incidence rates that
are aligned with the immigration of certain groups to a new
environment suggest a preexisting set of genetic conditions that
are maladaptive to that new environment. Finally, the overview
concludes with a survey of “universal” environmental and life
history factors that, in all likelihood, do indeed contribute to
type 2 risk among any given population. These factors include
age (specifically the role of diminishing glucose tolerance asso-
ciated with the aging process), obesity (a metric that the World
Health Organization (WHO) expert committee concludes to be
the most powerful predictor of T2D incidence), physical activ-
ity, dietary factors, and parity (Zimmet, 1982). Despite the age
and usage of archaic terminology for describing certain popula-
tions in Zimmet’s article, there are many lessons that can be
learned from it concerning research fallacies therein—many of
which are still employed today.
Two questions immediately come to mind with this sort of
analysis concerning the varying genetic susceptibility of dif-
ferent “ethnic groups”. Firstly, who are these ethnic groups?
Native American Indians throughout the Americas have tended
to lose their genetic isolation and recognizability post-coloni-
zation. Therefore, any claim reliant on these sweeping notions
of genetic lineages and predispositions becomes almost mean-
ingless. We must be sensitive and aware of the persistence of
the mosaic of evolutionary forces and gene flow between hu-
man populations that these “macro ethnic groups” cannot en-
capsulate. Secondly, for what is the term “genetic predisposi-
tion” actually being used in descriptions such as these? The
networks of interactions of the human genome with itself, its
environment, and even the genomes of other organisms is so
complex and daunting that it is unclear whether implementation
of such a loaded term like “genetic predisposition” is being
used to signify a new research avenue or a dead end. This sort
of terminology has been used as a sort of umbrella term—a
catch all—that can be negligent to the phenomena at hand and a
deterrent to deeper research. Despite this fact, many researchers
have been bold enough to enhance our focus and illuminate the
interconnectedness between the microbiological, genetic, and
regional factors of type 2 diabetes in a far less reductive man-
ner. These studies, emphasizing the subtleties of the condition,
paint type 2 diabetes in a brand new light and can help usher in
a new era of productivity within diabetes research.
Subtleties
The mezcla or mixing of risk factors and predispositions sur-
rounding type 2 diabetes (T2D) can be overwhelming. In order
to demystify and partially deconstruct this ever-complex disor-
der, we can view T2D with respect to a single protein. Tran-
scription factor 7-like 2 (TCF7L2) is a pleiotropic gene that,
among its many roles in regulation, serves as a vital member of
the Wnt signaling pathway. By associating with CTNNB1 (pre-
viously β-catenin) within the cell nucleus, TCF7L2 acts on Wnt
target genes that inhibit the production of a glucagon precursor
in enteroendocrine cells of the pancreas (Smith, 2006). Within
the liver, glucagon activates the breakdown of glycogen into
glucose and its release into the bloodstream, therefore serving
to increase blood sugar and directly antagonize insulin. With
this role in blood sugar homeostasis, it is easy to appreciate the
subtle, yet powerful physiological relation existing between
TCF7L2 and type 2 diabetes.
However, in order to increase the depth and breadth of our
analysis of the relationship between TCF7L2 and type 2 diabe-
tes, we can also consider the gene that encodes it. By viewing a
discrete gene involved in T2D, we are able to compare demo-
graphic and cross-species data to uncover evolutionary, life his-
tory, and regional trends at the most fundamental level of hu-
man genetics and evolutionary biology. Transcription factor
7-like 2 gene (TCF7L2 gene), also called TCF4 gene, consti-
tutes a 216 kilobase (kb) region on chromosome 10 within the
human genome. PhastCons and PhyloP software techniques
have been used to analyze conservation across a variety of ver-
tebrates, revealing tracks of alignment among 44 species. These
software tools, under the “PHAST” package, are capable of
comparing across cell lines to in order to indicate directional
selection when allelic frequencies are changing at rates that
cannot be accounted for by genetic drift alone. They can also
reveal patterns of conservation and decelerated evolution, if
changes in frequency fall below simulations that assume stable
equilibrium with respect to those alleles. Furthermore, they can
compare the given likelihood of each individual nucleotide
within the sequence belonging to the “conserved element” by
analyzing the individual alignment column relative to its flank-
ing columns. Among the vertebrates found to posses a con-
served sequence in the coding region were placental mammals
such as mice, bats, and, most relevant to human evolution,
chimpanzees (Pan troglodytes) and gorillas (UCSC Encyclope-
dia of DNA Elements). Visualizations of the alignment among
placental mammals and other select vertebrates may be found
in Figure 1. Notice the increasing overlay as the Multiz align-
ment transcends from the Stickleback and other out-groups to
the Rhesus monkey. The high degree of overlap within the
PhyloP analysis, however, suggests that the region is highly
conserved among placental mammals.
Several mutations of TCF7L2 gene have been implicated for
heightened type 2 risk. Among them is an array of single nu-
cleotide polymorphisms (SNPs)—single base pair substitutions
created along the coding sequence. Two SNPs in particular,
markers rs12255372 and rs7903146, have been gaining mo-
mentum among researchers in reference to their connection to
T2D. Munoz et al. have linked presence of the marker rs-
12255372 to a reduction in insulin secretion among non-dia-
betic women of African and European descent—a subtle and
distinct effect not attributable to the Wnt pathway. The pathway
(in which TCF7L2 has been introduced as a vital member) has
a paramount role in glycolysis and therefore in positive in-
creases of blood sugar, but says nothing about insulin, the
blood peptide governing sugar uptake by cells. These research-
ers used multiple clinical and metabolic parameters, such as
BMI, percent body fat, insulin sensitivity (Si), acute insulin
response to glucose (AIRg), and the disposition index (DI) to
confirm an association between homozygosity for the at-risk
allele (TT) and alteration of these metabolic characteristics in
ways that contribute to one’s risk. (Munoz, 2006). Munoz et al.
further propose a mechanism behind this increased risk, posit-
ing that TCF7L2 directly affects β-cell function. More specifi-
cally, they suggest that “TCF7L2 influences insulin secretion
and may affect susceptibility for type 2 diabetes by modulating
the adequacy of insulin secretion to compensate for the pre-
vailing degree of insulin resistance” (Munoz, 2006). This hy-
pothesis introduces a brand new role of the transcription factor
in both senescence and in stimulating insulin secretion within
β-cells in response to increasing insulin resistance and could
Copyright © 2013 SciRes. 97
M. L. GRACIA
Copyright © 2013 SciRes.
98
Figure 1.
Mulitz alignment and PhyloP analysis.
explain the heighted risk of T2D among those expressing
rs12255372 if the mutation is, in fact, deleterious with respect
to that function.
Furthermore, another thread of research has emerged out of
Iceland and Germany in 2006 concerning the association be-
tween rs7903146 and heightened risk of type 2 diabetes and
various forms of colorectal cancer (Grant et al., 2006). These
endeavors question the regiospecificity of T2D by sampling
from various populations worldwide. One particular letter to
Nature: Genetics, “Refining the impact of TCF7L2 gene vari-
ants on type 2 diabetes and adaptive evolution”, further defines
the risk association between TCF7L2 and diabetes among a
selected sample of West Africans by hypothesizing its connec-
tion to a particular variant, HapBT2D—a molecular variant pro-
duced by homozygosity for rs7903146. Researchers introduce
rs7903146 not as a recent polymorphism in the evolutionary
history of the sequence, but as an “ancestral” allele to the cur-
rent wild type (Helgason et al., 2007). Data further supporting
the ancestral allele’s association to T2D were replicated in
roughly 1000 Moroccans in a secondary meta-analysis con-
ducted by Cauchi et al. (2007). Research also suggests that a
second, less understood molecular variant of TCF7L2, HapA,
can also indicate type 2 risk and is, in fact, experiencing posi-
tive selection in some agrarian communities in West Africa,
Europe, and East Asia by its association with body mass index
(BMI) (Helgason et al., 2007).
To prove these hypotheses, Helgason et al. (2007) genotyped
a group of 1149 affected Danish individuals among 2400 con-
trols and 621 affected West Africans among 448 controls. These
demographic groups were chosen because of the high incidence
rates among them. After the second wave of genotyping, it was
discovered that one of the markers, with respect to relative risk,
stood out among the rest. The SNP rs7903146 yielded a relative
risk (RR) = 1.49 with a 95% confidence interval among the
Danish group, and a RR = 1.45 in West Africa, values much
higher than those produced by the other haplotype (rs12255372).
Helgason et al. (2007) also inquire about the possible positive
selection for HapA, another variant of TCF7L2 occurring
within certain West African, European, and East Asian popula-
tions, on the grounds that this variant is associated with high
BMI and alters concentration of hunger-satiety hormones that
positively affect energy metabolism in more energy-plentiful
environments. Indeed, molecular-clock dating analyses align
the emergence of HapA with the transition to agriculture within
each HapMap group (Helgason et al., 2007). In a second assay,
they performed both a Fixation Index (FST) test and long-range
haplotype (LRH) test within these populations in the hopes of
finding evidence supporting positive selection. Realized fixa-
tion index values (FST = .306) suggested that this sort of ge-
netic differentiation is unlikely via neutral evolution. Addition-
ally, high LRH results, a statistic that gauges the relative hap-
lotype homozygosity within a population, further support the
presence of positive selection. High FST values and high ho-
mozygosity suggest a rapid rate of divergence where neutral,
background mutation is insignificant. SNP rs7903146 and
variant HapA are both relevant risk factors to type 2 diabetes
within their respective populations, though their physiological
connections to the disease may differ significantly (Helgason et
al., 2007).
This article illuminates some of the subtle complexities of
natural selection. It is important to remember that natural selec-
tion does not work to create a super organism or to rid an or-
ganism of all impurities. In fact, evolution and natural selection
walk a very fine line. These processes work to strike a perfect
note in resource allocation due to the pleiotropic reality of life
on earth, a constant re-equilibration, at the genetic level, be-
tween relative benefit and disadvantage. There is no free lunch
in evolution. This is a fact highlighted in the positive selection
for HapA. Although it has been illustrated as a risk factor for
diabetes, authors speculate that HapA’s reproductive success
despite this fact is due to its advantageous effects on BMI rela-
tive to energy metabolism in agricultural environments (Hel-
gason et al., 2007). With regards to human disease in general,
we can take some additional time to ponder and appreciate the
ways in which different physiological pathways can arrive at a
single disorder. HapA has been strongly correlated with high
BMI increases among certain groups of West Africans, Euro-
peans, and East Asians in more energy-plentiful environments,
while the haplotypes rs12255372 and rs7903146 (HapB) have
been found unassociated, and at times negatively associated,
with BMI among other sampled populations of North and West
Africa. Instead, the latter variant contributes to T2D risk by af-
fecting insulin secretion in the ways previously described (Hel-
gason et al., 2007). These researchers were respectful and thor-
oughly sensitive to the genetic nature and variability of their
subject matter. Their attention to regiospecificity brings a new,
important perspective to understanding these risk factors, be-
cause any discussion of selective pressures or human evolution
cannot exist without intense consideration for the environments
in which populations exist. Both the methodology executed and
conclusions posited in Helgason et al. (2007) put forth creative
techniques and viewpoints in studying T2D, in turn adding
another wrinkle of understanding to the disorder’s complex
epidemiology.
M. L. GRACIA
An Analogy
A metaphor exists comparing the relationship between body
mass index and type 2 diabetes in Africa and East Asia to the
rise and distribution of malaria and sickle cell trait across the
African continent. Both series of evolutionary phenomena re-
volve around the implementation of agriculture and the subse-
quent rise in human population size and societal complexity.
Retro-analysis and comparison of the co-evolution between P.
falciparum and humans to the genetic changes that positively
affect BMI despite T2D risk in some African populations can
further reframe diabetes in our minds as a dynamic and subtle
consequence of human behavioral history. This analogy is
meant to remind us of the environment’s powerful effect on the
genome, to add context and understanding to the trends we
have studied thus far, and to affirm a novel perspective for
studying T2D and other emergent disorders in the future.
To learn from this analogy, one needs to retrace the concur-
rent adaptation of a protozoan with macro-scale behavioral
changes of the human species. The “burden” of malaria, as de-
scribed in Richard Carter and Kamini Mendis’ survey of the
mosquito-borne infectious disease, has been felt by inverte-
brates, vertebrates, mammals, and primates throughout evolu-
tionary history. Plasmodium falciparum, the most virulent hu-
man malaria agent, may have diverged from Plasmodium rei-
chenowi in concert with the split between the precursors of
humans and chimpanzees around 4 to 10 million years ago
(Carter & Mendis, 2002). P. falciparum and other extant Plas-
modium agents of human malaria—P. malariae, P. ovale, and
P. vivax—are also equally tied to the evolution of their vector,
the female Anopheles mosquito. These realities, perhaps better
than any other, truly embody the intimate coevolutionary rela-
tionship existing between the extant Plasmodium agents of
human malaria and their hosts.
Eight to ten thousand years ago in the “Fertile Crescent” of
modern day southern Turkey and northeastern Iraq, modern
humans began changing their behavior, and their surroundings,
in a momentous way. The innovation of agriculture—a meth-
odological practice involving the clearing, irrigating, cultivating
and harvesting of fertile land—would allow humans an un-
precedented level of sustainability and control over their envi-
ronment. This newfound control would direct the species’ glo-
bal distribution and evolution, as well as those of the species
dependent on them. Four to five thousand years ago, the agrar-
ian revolution reached western and central Africa. Human
populations across Africa began gathering in larger settlements
and reproducing at much higher rates, now supported by this
new form of energy production (Carter & Mendis, 2002).
The behavioral adaptations of humans caused the African
Anopheles to follow in suit. The anthropophilic index, the pro-
bability that a mosquito in a given region will acquire a blood
meal from a human source, is a good proxy for gauging this
coevolution. Carter and Mendis cite anthropophilic indices
taken from various regions of the world in the range of 10% -
50%. In sub-Saharan Africa, however, the range of indices is
80% - 100% (Carter & Mendis, 2002). Frank Livingstone was
the first to attribute this stark shift in preference to the signifi-
cant changes in human density and population size created by
the implementation of agriculture. It has been hypothesized that
the subtropical, cultivated regions of Asia and the Middle East
were shielded from this trend by presenting mosquitos with a
larger buffer of domesticated animals, thereby dampening their
dependency on human activity and distribution. Furthermore, in
Africa, the practice of agriculture also created large collections
of still water that facilitated mosquito breeding. The increases
in human density and local population size along with the addi-
tion of mosquito habitats near these population centers com-
bined to create a situation of endemic malaria in certain regions
of Africa (Carter & Mendis, 2002). From an ecological per-
spective, the invention of agriculture can and should be viewed
as a major disturbance within the community. Furthermore, hu-
man beings can be viewed as ecological engineers within their
ecosystem. By manipulating their environment, they also fa-
cilitated the re-colonization and proliferation of another de-
pendent species within the successional process.
We must now track a final aspect to this story—the frequen-
cies and selection for human HgbS, the allele causing the auto-
somal recessive genetic blood disorder sickle-cell anemia.
While homozygosity for this allele produces the commonly
mortal phenotype we call sickle-cell anemia, a heterozygous
phenotype produces a co-dominant effect we call “sickle-cell
trait”. Those bearing the heterozygous phenotype produce a
blend of normal red blood cells and “sickled” cells—abnormal
red blood cells that acquire their distinct shape from a deform-
ity in the β-globin chains of hemoglobin. It is the presence of
these sickled cells among functional red blood cells that offers
carriers both adequate perfusion of body tissue and an intraery-
throcytic environment that inhibits P. falciparum’s lifecycle
and proliferation. Increases in post-infection survivability among
carriers, estimated to be as high as 90% in some regions, have
created intense selective pressure for this heterozygous advan-
tage in regions of endemic malaria (Carter & Mendis, 2002).
To learn and apply the lessons concerning agriculture, ma-
laria, and sicke-cell trait to selective forces in agrarian societies
that affect the distribution of type 2 diabetes, we must think
laterally. While agriculture as a common denominator makes
this an easy comparison, direct similarities in this meta-analysis
are not as important as the underlying principles they imply.
Agriculture and its effects on Plasmodium, Anopheles, and
humans serve as an example of behavioral and environmental
catalysis of adaptive evolutionary change. In the same way that
the practice of agriculture has created significant selective
pressures that have increased the frequency of the HgbS allele
despite the devastating effects of the recessive homozygous
genotype, agriculture has created an energy abundant environ-
ment where a molecular variant of TCF7L2 (HapA), despite its
positive association with BMI and type 2 diabetes, can thrive
because of its advantages in energy metabolism. Additionally,
while we have learned a substantial amount from the similari-
ties of these examples, we can also learn from the subtle ways
in which they differ. It is important to distinguish that while
causality of these evolutionary relationships are similar, selec-
tion for HapA is not being driven by the environmental side
effects of agriculture, but rather by the production of agriculture
itself. The various new forms and quantities of food possible in
agricultural societies have forever changed the dietary patterns
within them. This different form of behavioral change has
shown equally capable of influencing genetic change, and the
persistence of type 2 diabetes. One must remember that diet,
along with subsistence, infectious disease, and other sociocul-
tural and environmental filters must be given the attention they
deserve in the study of any worldly distributed disorder
(Jackson, 2004). Both these filters—by their ability to fill the
gap and complicate the pathway between a coded genotype and
Copyright © 2013 SciRes. 99
M. L. GRACIA
Copyright © 2013 SciRes.
100
an expressed phenotype—and the regional subtleties already
described have a lot to tell us if we are willing to listen.
Conclusion
A meta-analysis superimposed on this case study has been
meant to promote the consideration of subtle, often pleiotropic
genetic relationships, micro-regional analysis, population sub-
structure, and the role of the environment over notions of
macro-ethnic groups and uninspired dogmas revolving around
“westernization” as a universal cause. Often within the litera-
ture, type 2 diabetes is treated as a static and isolated condition,
and studies on its behalf have been plagued by these ambiguous
claims along with narrow-focused, absolutist parameters that
obsess with obesity and insulin secretion. Together, these two
foci in research have combined to create a mindset that ignores
many of the subtitles within the condition and its ties to other
facets of life and history.
To bring a new mindset to life, we were introduced to
TCF7L2, a transcription factor coded in a highly conserved
sequence of the genome and intimately involved in glycolysis
and β-cell function. Several single nucleotide polymorphisms
(SNPs) of TCF7L2 gene have been positively associated with
type 2 diabetes. The molecular variant that arises from these
polymorphisms (HapBT2D) and another molecular variant that is
less understood (HapA) each increase risk for T2D by either
directly affecting β-cell function within the pancreas or by
positively associating with BMI. The persistent, and in some
cases, growing frequencies of these variants in studied popula-
tions is often the result of balancing selection dictated by the
pleiotropic reality of TCF7L2 gene and changes in human en-
vironments and behavior. One such example of this pleiotropic
tradeoff is the selection of HapA in some African populations.
As an adaptive mechanism, HapA is still being selected for in
certain agricultural environments despite its positive association
with type 2 risk because of the advantages in energy storage
and metabolism of higher BMI. This causal relationship is
similar in principle to the ways in which agriculture has gov-
erned the frequencies and distribution of malaria and sickle cell
trait across the African continent.
Just as humans continue to adapt and evolve, so too must the
body of literature surrounding type 2 diabetes. The literature is
a reflection of our mindset, and our mindset needs to change.
These realizations allow us to reframe diabetes as a highly
delicate and variable human condition, and to place it within a
matrix of adaptive evolution, the environment, human behavior,
and human history.
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