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Study of genetic variation in Asian Indians -- applications to complex diseases and endogamic exogamy

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STUDY OF GENETIC VARIATION IN ASIAN INDIANS-APPLICATIONS TO
COMPLEX DISEASES AND ENDOGAMIC EXOGAMY

by

Niyati Mehta

___________________________________________

A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOCHEMISTRY AND MOLECULAR BIOLOGY)

August 2007

Copyright 2007 Niyati Mehta

ii
DEDICATION

- to my grand mother who is in heaven and has always blessed me.
- to my parents who have given me constant support and encouragement.
- to my brother who loves me and takes care of me.
- to all my other family members who pray for me.
- to all my friends who have helped me and given me morale support.

iii
ACKNOWLEDGEMENTS

Firstly, I would like to thank Dr. Pragna Patel, whose lab I have worked in
for the past two years. I have greatly appreciated her kindness in accepting me into
her lab and guiding me through the work of three wonderful projects. Secondly, I
would like to thank my committee member and advisor Dr. Zoltan Tokes for taking
time out of his busy schedule both for my defense and whenever I needed his
support. Thirdly, I would like to thank our collaborator and my committee member
Dr. Hooman Allayee for his time, help and knowledge on our cardiovascular disease
subject. Fourthly, I would like to say a big thank you to Dr. Trevor Pemberton and
Gustavo Mendoza under whom I have worked and developed a diverse array of
experimental and data analysis techniques. I would also like to thank my other
former lab members Jason Gee, Fang-Yuan Li, and Steven Wong, as well as Hemani
Wijesuriya and Jaana Hartiala, for their help and advice. Finally, I would like to
thank Dr. Sanjay Mehta for his invaluable help in subject collection in Mumbai,
India.
iv
TABLE OF CONTENTS
DEDICATION .............................................................................................................ii
ACKNOWLEDGEMENTS ........................................................................................iii
LIST OF TABLES ......................................................................................................vi
LIST OF FIGURES ..................................................................................................viii
ABSTRACT................................................................................................................ix

Chapter I: Introduction.................................................................................................1
1.1 Genetic variation in Asian Indians.........................................................................1
1.2 Coronary Artery Disease in Asian Indians.............................................................3
1.2.1 Pathogenesis of CAD:.....................................................................................4
1.2.2 Epidemiology of CAD: ...................................................................................8
1.2.2.1 Worldwide:...............................................................................................8
1.2.2.2 India: ........................................................................................................9
1.2.3 Striking features of CAD in Asian Indians: ..................................................10
1.2.4 Women are no exception:..............................................................................11
1.2.5 Biochemistry involved in the ALOX5 Pathway: ...........................................12
1.3. Endogamy - Work in progress: ...........................................................................18

Chapter II: Materials and Methods ............................................................................24
2.1 Genetic variation in Asian Indians.......................................................................24
2.1.1 Study population: ..........................................................................................24
2.1.2 Marker genotyping:.......................................................................................24
2.1.2.1 Allelic Discrimination:...........................................................................24
2.1.2.2 Fragment Analysis: ................................................................................25
2.1.2.3 Haplotype Analysis:...............................................................................27
2.1.2.4 Statistical Analysis:................................................................................27
2.2 Coronary Artery Disease......................................................................................29
2.2.1 Subject Collection:........................................................................................29
2.2.1.1 USA........................................................................................................30
2.2.1.2 Mumbai, India........................................................................................31
2.2.2 Blood Collection: ..........................................................................................31
2.2.3 Nucleic Acids Extraction: .............................................................................32
2.2.4 Marker genotyping........................................................................................32
2.2.5 Statistical Analysis........................................................................................32
2.3 Endogamy: ...........................................................................................................33
2.3.1 Subject Collection:........................................................................................33
2.3.2 The Fragment Analysis: ................................................................................33
2.3.3 Snapshot Assay: ............................................................................................35

v
Chapter III: Prevalence of Common Disease-associated Polymorphisms in
Asian Indians..............................................................................................................37
3.1 Analysis of polymorphisms at the ALOX5 locus in Indian language groups.......38
3.2 Analysis of polymorphisms at the DG8S737 and rs1447295 loci in Indian
language groups .........................................................................................................43
3.3 Discussion: ...........................................................................................................48

Chapter IV: Association studies on Coronary Artery Disease in Asian Indians........53
4.1 Statistical analysis of genotypes at the ALOX5 locus in CAD cases
and controls ................................................................................................................53
4.2 Discussion ............................................................................................................57

Chapter V: Endogamic exogamy in Gujarati Patels of India: Work in progress.......59

Chapter VI: Conclusions and future direction ...........................................................65

Chapter VII: References.............................................................................................68

Appendices.................................................................................................................82
Appendix A:...........................................................................................................82
Appendix B: ...........................................................................................................85
Appendix C: ...........................................................................................................87
Appendix D:...........................................................................................................89
Appendix E: ...........................................................................................................90

vi

LIST OF TABLES

Table 1: List of genes investigated, associated polymorphisms
and their phenotypes. ...................................................................................................2

Table 2: A partial list of genes implicated in heart disease..........................................7

Table 3: List of DYS markers used for fragment analysis.........................................34

Table 4: PCR conditions for DYS 437 and DYS 439................................................35

Table 5: SNaPshot PCR Reaction protocol................................................................35

Table 6: A list of the SNPs with their corresponding PCR and
Snapshot primers........................................................................................................36

Table 7: Allele frequencies of the polymorphisms at the ALOX5 locus in
Indians belonging to different language groups.........................................................39

Table 8: Squared correlation (r²) values between alleles of ALOX5P and
the three coding ALOX5 SNPs ...................................................................................41

Table 9: Haplotypes and Diplotypes of identified ALOX5 polymorphisms
with its corresponding frequencies.............................................................................42

Table 10: Allele frequencies of the polymorphisms at loci previously
associated with prostate cancer, in Indian language groups. .....................................44

Table 11: Linkage disequilibrium (D') and the squared correlation (r²) values
between alleles of DG8S737 and rs1447295. ............................................................46

Table 12: Haplotype and diplotype frequencies for the -4 allele of the
DG8S737 microsatellite and the rs1447295 alleles ...................................................47

Table 13: Squared correlation (r²) values between alleles of ALOX5P
and the three coding ALOX5 SNPs in cases, controls and all subjects. .....................54

Table 14: Haplotypes of identified ALOX5 polymorphisms with their
corresponding frequency............................................................................................55

Table 15: Diplotypes of identified ALOX5 polymorphism with its
corresponding frequency............................................................................................56

vii
Table 16: Calibration of fragment sizes using Hazara samples .................................61

Table 17: Calibration of fragment sizes using HapMap samples. .............................62

Table 18: List of the SNPs and their corresponding alleles.......................................64

viii

LIST OF FIGURES

Figure 1: Pathogenesis of CAD ...................................................................................5

Figure 2: Biochemistry involved in the ALOX5 pathway:.........................................13

Figure 3: The leukotriene biosynthetic pathway........................................................14

Figure 4: Structure of the ALOX5 gene.....................................................................16

ix

ABSTRACT

There are over a billion Asian Indians in the world and they comprise one-
sixth of the world’s population. One of the major health concerns facing Indians,
both those in India and in the diaspora, is the rapid increase in the incidence of
common diseases such as heart disease and type 2 diabetes. Until recently, no large-
scale population genetics study had included the Asian Indian population.
Here I describe investigation of the prevalence of common polymorphisms
that have been associated with two common diseases: atherosclerosis (ALOX5) and
prostate cancer (DG8S737, rs1447295). Haplotype analysis of the data revealed that
allele frequency differences between the different Asian Indian groups were small,
and many polymorphisms were found at a frequency similar to those of European
and African populations but not other Asian populations. Haplotype analysis
between DG8S737 and the rs1447295 in this Asian Indian cohort found that the rarer
-4 allele of DG8S737 exhibited the greatest correlation with the A-allele of
rs1447295, along with being in strong LD, while the -1 allele was in complete LD
with the A-allele of rs1447295, but was weakly correlated.
Coronary Artery Disease (CAD) occurs when the coronary arteries that
supply blood to the heart muscle become hard and narrow due to the build up of lipid
filled lesions called “plaques” in the inner walls. This condition is known as
atherosclerosis. We examined ALOX5 in 243 Asian Indian case-control individuals,
since this gene participates in atherosclerosis and inflammation as reported earlier.
x
No statistically significant association was found between CAD and the ALOX5
locus.
Endogamy has been a strong influence on the Indian society over the

centuries and most of the 75,000 sub-castes or subgroups of India's

complex social
stratification system practice endogamy. We have studied one such group: the Chh
Gaam Patels which comprises Patels from six villages, to determine the number of
founders and occurrence of any genetic isolation due to the endogamic exogamy
practiced. Genotypes were obtained, for 168 India-born Gujarati male individuals
sampled in the United States. These genotypes corresponded to repeat numbers and
will be used to obtain haplogroups and carry out haplogroup analysis. The
haplogroups thus obtained will help to form a phylogenetic tree which will enable us
to know the paternal lineage of individuals from each of the villages. These data as
well as the microsatellite and mitochondrial genotype data are being analyzed.

1
CHAPTER I
INTRODUCTION
1.1 Genetic variation in Asian Indians
With a population of 1087 million, India is the second most populated
country in the world surpassed only by China and is predicted to expand to 1628
million by the year 2050 (Bureau 2004). The high prevalence of endogamy and
relatively low admixture present in the population distinguishes Asian Indians (from
the subcontinents of India, Pakistan, Bangladesh and Sri Lanka) from most other
populations presently used in genetic studies (Bittles 2005). As the Asian Indians
accept and adapt the western culture and lifestyle, the incidence of complex diseases
associated with these lifestyle changes is on the rise.

Recent STRUCTURE analysis using 1200 genome-wide polymorphisms in
432 individuals from 15 Asian Indian language groups has shown that Indians
constitute a distinct cluster and that despite the geographic and linguistic diversity of
the groups, they exhibit a low level of genetic differentiation (Rosenberg, Mahajan et
al. 2006).

Many studies have shown that metabolic disorders such as coronary artery
disease (CAD) have an unusually high prevalence in the Asian Indian population
which is likely to be associated with the growing westernization of India. For
example, the incidence of CAD in individuals of Asian Indian origin is currently
2
much higher than in other ethnic groups and is increasing (Wilson, Christiansen et al.
1989; Enas 1991; Enas and Mehta 1995; Gupta, Prakash et al. 1995; Enas, Garg et al.
1996; Enas and Senthilkumar 2001). It is currently estimated that 18% of the Asian
Indian population suffer from hypertension, one of the major risk factors associated
with CAD, and its prevalence is also increasing within this population (Gupta 1997).
However, this prevalence is comparable to that in other worldwide populations
(15.0%-40.0%) (Kearney, Whelton et al. 2004). Other diseases like prostate cancer
are also found at varying frequencies in the Asian Indian population (Hsing, Tsao et
al. 2000; Quinn and Babb 2002). However, despite the disproportionate prevalence
of such common and fatal disorders, most modern genetic studies have not yet
included the Asian Indian population.

In the present study, we have investigated the prevalence of common
polymorphisms that have recently been reported to be risk factors for atherosclerosis
(which is the primary process involved in the etiology of CAD) and prostate cancer
in a cohort of 576 India-born Asian Indians recruited in the United States (Table 1).
Table 1: List of genes investigated, associated polymorphisms and their
phenotypes.

Gene Name/
Gene symbol
NCBI Acc. # Nucleotide change Protein
change
Phenotype Reference
ALOX5 None (5’-GGGGCGG-
3’)3-8
promoter Atherosclerosis (Dwyer, Allayee et
al. 2004)
ALOX5 rs4987105 g.20C>T T7T Atherosclerosis (personal
communication
with HA)
ALOX5 rs2228064 g.8322G>A T90T Atherosclerosis "
ALOX5 rs2228065 g.50778G>A E243K Atherosclerosis "
Intragenic DG8S737 (5’-AC-3’)13-30 none Prostate Cancer (Amundadottir,
Sulem et al. 2006).
Intragenic rs1447295 C>A none Prostate Cancer (Amundadottir,
Sulem et al. 2006).
3
The prevalence of these disease/traits and the frequency of the risk-associated
minor alleles of these polymorphisms have been reported to differ between
ethnicities suggesting that their influence may also differ between populations. The
etiology of most complex diseases such as CAD (Motulsky and Brunzell 2002) and
prostate cancer (Bostwick, Burke et al. 2004) is possibly caused by the combined
effect of genes and environment. However, the role of genes versus environment and
the genetic heterogeneity for the diseases/traits considered here will be very
different. Whilst we have investigated the prevalence of these risk alleles within the
Asian Indian subjects and compared them to those of other populations, we have not
discussed the possible effect of environmental factors that may differ between these
populations.

1.2 Coronary Artery Disease in Asian Indians

Coronary Artery Disease (CAD) occurs when the arteries (coronary arteries)
that supply blood to the heart muscle become hard and narrow due to the build up of
lipid filled lesions called “plaques” in the inner walls. This condition is known as
atherosclerosis. As the plaque size increases, it causes the arteries to stiffen and there
is impaired blood flow which increases the risk of thrombosis. This impairment of
arterial circulation can lead to occurrence of clinical manifestations such as angina or
myocardial infarction (MI). Overtime, CAD can weaken the heart muscle and cause
heart failure or arrhythmias. The etiology of most CAD cases are complex and are
likely caused by the combined effects of genes and the environment (Motulsky AG
and JD 2002).The overall genetic contribution towards the development of CAD is
4
estimated to range from 20-60%, with genetic factors more pivotal in those who
develop CAD at a younger age (Chaer RA, Billeh R et al. 2004). An individual with
a family history of CAD has a two-to seven- fold increased risk of developing the
disease compared to an individual with no family history. The risk further increases,
as the number of affected relatives <55 years of age increase and/or affected female
relatives increase.

1.2.1 Pathogenesis of CAD:
Impaired HDL-C metabolism and inflammation are the primary causes of
CAD. This leads to atherosclerosis, which is the principal process in CAD and is also
responsible for ischemic stroke and peripheral vascular disease. Cholesterol is
naturally made by the liver and is located in cell membranes; hence, dietary
cholesterol is not required for the body. The transport of excess cholesterol from the
periphery into

the liver and bile, followed by excretion in the feces, is defined

as
reverse cholesterol transport (RCT). A combination of lipids and proteins called
lipoproteins are also made in the liver. High Density Lipoprotein – Cholesterol
(HDL-C) is called “good” cholesterol and the lack of its function in RCT is the
primary step in the formation of plaques. HDL-C plays an important role in returning
cholesterol deposited in peripheral cells to the liver, for metabolism or excretion into
the bile. HDL-C concentrations are dependent upon the rate of synthesis and
degradation of these particles. Thus, while HDL-C concentrations are good
indicators of atherosclerosis, they themselves are markers for the activity of a
5
number of other proteins that function in the RCT system. Impairment of any of the
proteins in this pathway, could lead to an imbalance in HDL subclass levels. Low
Density Lipoprotein Cholesterol (LDL-C) is called “bad” cholesterol and its excess
can lead to the formation of plaques in the coronary arteries.
Figure 1: Pathogenesis of CAD:

Low Density Lipoprotein (LDL) cholesterol enters dysfunctional endothelium (which is damaged by
smoking or diabetes, for example, and this is reflected by decreased nitric oxide (NO) production) and
is oxidized by macrophage and smooth muscle cells. Release of growth factors and cytokines, and
upregulation of adhesion molecules, attracts further monocytes. Foam cells (arising from lipid-laden
macrophages) accumulate and smooth muscle cells proliferate, which results in the growth of the
plaque. Inflammatory cell infiltrate, smooth muscle cell death through apoptosis, and matrix
degradation through proteolysis (by matrix metalloproteinases — MMPs) generate a vulnerable
plaque with a thin fibrous cap and a lipid-rich necrotic core. Plaque rupture can cause thrombosis
which might be sufficient to cause vessel occlusion.

6
Native LDL is not taken up by macrophages rapidly enough to generate foam
cells, and so it was proposed that LDL is somehow “modified” in the vessel wall
(Goldstein JL, Ho YK et al. 1979). It was later shown that trapped LDL does indeed
undergo modification like oxidation, lipolysis, aggregation etc. and that these kinds
of modifications contribute to the formation of foam cells and subsequent
inflammation (Fig. 1). Oxidation is one of the significant modifications for lesion
formation, since it can inhibit the production of nitric oxide (NO), a chemical
intermediate with several anti-atherogenic properties, including vasorelaxation. It
was shown that mice lacking endothelial NO synthase showed enhanced
atherosclerosis, due in part to raised blood pressure (Knowles, Reddick et al. 2000).
In addition to LDL, a number of other factors are likely to modulate inflammation,
including hemodynamic forces, homocysteine levels, sex hormones, and infection.
Inflammatory processes characterize all stages of atherogenesis, from the early
endothelial activation by modified lipids to the eventual rupture of the atherosclerotic
plaque. Atherosclerosis is characterized by the recruitment of monocytes and
lymphocytes, but not neutrophils, to the arterial wall. A sequence of molecular and
cellular steps is involved to cause inflammation in the arterial wall. Diabetes may
promote inflammation in part, by the formation of advanced end products of
glycation that interact with endothelial receptors (Hofmann MA, Drury S et al.
1999). Studies of mice deficient in P- and E- selectins or the cell-adhesion molecule
ICAM, revealed the role of these adhesion molecules in atherosclerosis too. (Dong,
Chapman et al. 1998; Collins, Velji et al. 2000).
7
Table 2: A partial list of genes implicated in heart disease

Gene Nomencl
ature of
gene
Type of gene Single Nucleotide
Polymorphism
Causing disorder Reference
Arachidonate
5-
lipoxygenase
ALOX5 Clinical marker
for
atherosclerosis
Involved in inflammation
and immediate
hypersensitivity; associated
with Atherosclerosis.

5-
Lipoxygenase
activating
protein
FLAP Clinical marker
for
atherosclerosis
Luekotriene synthesis;
associated with myocardial
infarction.

Platelet
endothelial
cell adhesion
molecule-1
PECAM-
1
Thrombosis and
atherosclerosis
Leu125Val Associated with CAD (Fang L,
Wei H et
al. 2005)
Endothelial
Nitric Oxide
synthase
Enos
Lipoprotein
Lipase
LPL Dyslipidemia Regulation of plasma lipids;
associated with HDL-C and
total plasma cholesterol and
plasma triglycerides.

Complement
factor H
CFH Arterial
inflammation
Y402H of the CFH
gene.
AMD and possibly
associated with MI
(Kardys,
Klaver et
al. 2006)
Lecithin-
cholesterol
acyltransferase
LCAT Structural protein for HDL;
lipoprotein metabolism
especially in reverse
cholesterol transport.

Leukotriene
A4 hydrolase
LTA4H Biosynthesis of eicosanoids;
associated with myocardial
infarction.

Lymphotoxin
alpha
LTA Pro-
inflammatory
and pro-
atherogenic
Modulator in the immune
response; associated with
myocardial infarction.

Ligand
galactin-2
LGALS2 MI The C3279T SNP in
intron 1 was associated
with low levels of
LGALS2 transcripts.
Binds to LTA; associated
with myocardial infarction.
(Ozaki,
Inoue et al.
2004)

Apolipoprotei
n A-I
APOA1 Structural protein for HDL;
activator for LCAT; ligand
for HDL receptor

Apolipoprotei
n C3
APOC3 Rare S2 SstI allele of
ApoC3
Associated with
hypertriglyceridemia.
(Chhabra,
Narang et
al. 2002)
Hs-C Reactive
protein
Hs-CRP
Toll like
receptor 4
TLR4
MHC Class II
activator
MHC2TA Arterial
Inflammation
MHC2TA Promoter
A168G SNP of
Increased susceptibility to
MI
(Swanberg
M, Lidman
O et al.
2005)
8
In an attempt to identify genes underlying atherosclerosis , whole genome
scans for loci associated with diabetes, hyperlipidemia, low HDL levels and
hypertension have been performed (Krushkal, Ferrell et al. 1999). However, few loci
with significant evidence of linkage have been found, emphasizing the complexity of
the traits.

We decided to examine ALOX5 in the Asian Indian Gujarati population since
this gene participates in atherosclerosis and inflammation as reported earlier.

1.2.2 Epidemiology of CAD:
1.2.2.1 Worldwide:
Cardiovascular Disease (CVD) was responsible for 16.7 million deaths in
2003 globally (April 10, 2005). Of these, 7.2 million deaths were the result of
ischemic heart disease. Approximately 80% of these deaths occurred in the
developing world (April 10, 2005). Nearly one fourth of these developing countries
are in South Asia ( India, Pakistan, Bangladesh, Nepal and Sri Lanka) and have been
strongly affected by this epidemic of CAD (Nishtar). Since 1990, more people have
died worldwide from CAD than any other disease (Mackay 2004). Twenty million
people survive heart attacks and strokes annually and a majority of them require
expensive clinical care (Bedi US, Singh S et al. 2006)

9
1.2.2.2 India:
Multiple studies have shown that Asian Indians have an increased
predisposition to CAD (Reddy and Yusuf 1998; Mohan V, Deepa R et al. 2001;
Mohan V, Shanthirani CS et al. 2003). Prevalence studies done in India have also
shown that the incidence of CAD is increasing in the Indian population living in the
Indian subcontinent and is approaching that of the immigrant Indian population in
other nations (Bedi US, Singh S et al. 2006). The WHO predicts that by 2010, Asian-
Indian patients will represent 60% of the world’s cardiac patients i.e. approximately
100 million people (Mishra N and L. 2001). The prevalence of CAD in men in New
Delhi, India is four times (9.7% vs. 2.5%) that of men in the Framingham Offspring
study group (Wilson PW, Christiansen JC et al. 1989; Enas EA and J. 1995). The
prevalence of CAD among the ~35,000 immigrant male U.S physicians born in India
is three times that of men in the Framingham Offspring study (EA 1991; Enas EA,
Garg A et al. 1996). The hospitalization rate for CAD in the United States among
non-physician Asian Indians is four times that of Caucasians, Japanese and Filipinos,
and five times higher that that of Chinese and other Asians (Klatsky AL, Tekawa I et
al. 1993). In the UK, the overall CAD mortality in Asian Indian men is 50% higher
than the country wide average but it is 313% higher in Asian Indian men who are
<30 years of age (Balarajan R 1991).

10
1.2.3 Striking features of CAD in Asian Indians:
Asian Indians show two unique characteristics about CAD: either severe or
premature (or both). The course of the disease is often severe and extensive, often
leaving patients not enough time to take any action, resulting in premature morbidity
and mortality. Standard blood lipid measurements including total cholesterol and
LDL-C are not elevated in Asian Indians when compared with Caucasians (Hughes,
Wojciechowski et al. 1990). Superko et al. reported in a study done on the LDL and
HDL subclass distribution in 173 Asian Indian males and 239 non-Asian Indian
males that the men of Asian Indian origin had significantly lower HDL2b levels
when compared with age-matched non-Indian males (Superko HR 2005). This
finding persisted when examining males with >40mg/dl (considered not at increased
CAD risk) with a p value of 0.0001. The peak particle diameter for LDL was also
found to be smaller in the group with HDL >40mg/dl. Bhadolkar and colleagues
have compared HDL and LDL cholesterol subclasses and particle sizes in Asian
Indian men (Bhalodkar, Blum et al. 2004) and women (Bhalodkar NC, Blum S et al.
2005) with Caucasian men and women, respectively from the Framingham Offspring
study and found that Asian Indians had a significantly smaller overall HDL particle
size but showed no differences in HDL-C or LDL-C levels, or in LDL particle
concentration and size. These findings likely reflect impaired reverse cholesterol
transport in the Asian Indian population.

11
CAD in the young is in its most severe form and occurs before the age of 40 years.
Of all the cases of CAD in the West, less than 5% occur in the young, and in the
largest study in Texas, the prevalence of CAD in the young is only 2% (Negus,
Willard et al. 1994). CAD in the young is being recognized frequently in Indians and
has been reported to be as high as 12% in India (Krishnaswami S, Prasad NK et al.
1989). Asian-Indian men under the age of 40 had a 15-fold higher rate of CAD
compared to Chinese men, and 10-fold higher rate compared to Malays when studied
angiographically (Rajadurai J, Arokiasamy J et al. 1992). The incidence of a first MI
at <40y was found to be 10 times that of Caucasians in the U.K (Hughes LO, Raval
U et al. 1989). Of 1066 male patients studied by angiography in Vellore, India,
significant CAD was observed in 877. Of these, 55% were <50 y, 34% were<45 y
and 12% were <20 y (Krishnaswami S, Prasad NK et al. 1989).

1.2.4 Women are no exception:
Asian Indian women have unusually high rates of CAD as well. A study in
New Delhi showed the prevalence of CAD is about 10% in Asian Indian women
(Chadha SL, Radhakrishnan S et al. 1990). In South Africa, Asian Indian women
have the highest relative risk of CAD mortality amongst 4 other ethnic groups: 4
times higher than that of US women, 14 times higher than that of French women and
21 times higher than that of Japanese women (Steinberg WJ, Balfe DL et al. 1988).
Among Asian-Indian women suffering from CAD in the U.K., the standardized
mortality ratio (SMR) is 1.5 times higher than that of native British women, and 2.6
12
times higher than that of immigrant American women (Balarajan R 1991). A study in
South Africa suggested that natural protection from CAD seen in Caucasian
premenopausal women is not present in Asian Indian women. This was supported by
CAD mortality in Indian women aged 30-69 which was 49% above that for the same
age group women of European descent (AM. 1963). Additional support comes from
the study in Singapore on 9,568 autopsies which showed three vessel disease in half
of all Asian Indian women, one third of whom were premenopausal (Danaraj TJ,
Acker MS et al. 1959).

In the present study, we have examined the Indian population from USA and
from India, since Indians are found to be highly affected and predisposed to CAD in
spite of some common symptoms of CAD not being prevalent in the Asian Indians.
Also, variant alleles shown to be atherogenic in some populations are not disease-
causing in the Indians as proved by a study conducting in lab (Appendix A). Hence,
a case-control study was carried out to determine the frequency of allelic variants of
the ALOX5 gene and to determine if they were associated with CAD or not.

1.2.5 Biochemistry involved in the ALOX5 Pathway:
Eicosanoids are lipid mediators of inflammation and hypersensitivity
reactions (Funk 2001), and arachidonate 5-lipoxygenase is the key enzyme in the
oxidative biosynthesis of a class of paracrine and autocrine eicosanoids known as
leukotrienes (LTs)(Fig. 2) (B.Samuelsson 1983).
13
Figure 2: Biochemistry involved in the ALOX5 pathway:

The 5-LO atherosclerosis hypothesis of arterial wall inflammation. Macrophages/foam cells/dendritic
cells express cytosolic phospholipase A
2
(cPLA
2
) and the 5-LO cascade. cPLA
2
activation hydrolyzes
arachidonic acid (AA) from the sn2 position of membrane glycerophospholipids. The released
unesterified AA binds to FLAP which transfers it to 5-LO facilitating AA conversion to 5-H(P)ETE
(5-hydro(pero)xyeicosatetraenoic acid) and LTA
4
. LTA
4
serves as substrate for LTC
4
synthase to
generate LTC
4
/LTD
4
(black arrows) or for LTA
4
hydrolase to generate LTB
4
(red arrows). LT
formation may occur in lamina intima lesions or in the lamina adventitia. Macrophages, T cells, mast
cells, SMCs, and endothelial cells express LT-Rs. CysLTs act on cysLT
1
-Rs on macrophages in an
autocrine (bent black arrows) or on cysLT
1
-R on other neighboring cells including lymphocytes
and/or SMCs in a paracrine fashion (straight black arrows). CysLTs may also activate endothelial
cells in a paracrine manner (straight black arrows). Moreover, LTB
4
may act on neighboring cells
including , SMCs, and T lymphocytes in a paracrine fashion (red straight arrows) and on macrophages
in an autocrine fashion (red bent arrows). Inset shows an endothelial cell and genes that have been
identified by microarray analyses 60 min after stimulation of cultured human umbilical vein
endothelial cells with 100 nM LTD
4
: CAMs (cell adhesion molecules), MIP-2 (macrophage
inflammatory protein 2), IL-8 (interleukin 8). Note that the precise LT-R pattern on cells forming
inflammatory circuits in the arterial wall has not yet been determined.
K.Lotzer et al. / Biochimica et Biophysica Acta 1736 (2005) 30-37 Review.

14
LT formation is initiated by the activation of cytosolic phospholipaseA2
(cPLA2) resulting in arachidonic acid (AA) release from membrane
glycerophospholipids (B.Samuelsson 1983). Metabolism of unesterified arachidonic
acid to LTs is achieved by 5-LO along with an associated protein called 5-LO-
activating protein (FLAP) which appears to serve as an arachidonic acid binding and
transfer protein, thereby facilitating 5-LO enzyme activity. The intermediate
metabolite, i.e. LTA4 , is converted either to LTB4 or to cysLTs by the downstream
enzymes LTA4 hydrolase and LTC4 synthase, respectively (B.Samuelsson 1983).
The dihydroxy leukotriene B4 (LTB4) is a potent leukocyte chemo attractant,
whereas the cysteinyl leukotrienes (cysLTs) increase vascular permeability and
promote contraction of vascular smooth muscle (Fig. 3) (B., SE Dahlen et al. 1987).
Figure 3: The leukotriene biosynthetic pathway (Mehrabian M et al 2003)

15
Atherosclerosis is a chronic inflammatory process involving the recruitment
and accumulation of monocytes, macrophages, and dendritic cells in artery walls,
where they become loaded with modified and aggregated low-density lipoproteins
(LDLs) (Ross. 1993; Lusis. 2000). Of the leukocytes that are present, macrophages,
foam cells, dendritic cells, and mast cells express 5-LO, whereas T cells do not. In
diseased human arteries, the number of 5-LO+ macrophages expands during lesion
formation which makes up a significant portion of the atherosclerotic plaques.
Evidence suggesting a role of the 5-LO pathway in atherogenesis has only recently
emerged from the past invitro (McIntyre, Zimmerman et al. 1986; Palmberg,
Claesson et al. 1987; Huang, Manning et al. 1993; Datta, Romano et al. 1995;
Heimburger M and JE. 1996; Porreca E, Di Febbo C et al. 1996; Pedersen, Bochner
et al. 1997; Friedrich, Tager et al. 2003), morphological (Spanbroek, Grabner et al.
2003), and pharmacological studies and data from genetically engineered mice
(Dahlen SE, Bjork J et al. 1981; Michelassi F, Landa L et al. 1982; Smedegard G,
Hedqvist P et al. 1982; Secrest RJ and BM. 1988; Allen SP, Chester AH et al. 1992;
Allen, Dashwood et al. 1998). The use of animal models is a potentially powerful
way of identifying genes that contribute to common forms of atherosclerosis in
humans. Mice and rats- the most commonly used mammals for genetic studies- have
common variations in many traits relevant to atherosclerosis, and orthologous genes
frequently contribute to a trait in rodents, and humans (Stoll, Kwitek-Black et al.
2000). The 5-lipoxygenase pathway has been linked to atherosclerosis in mouse
models (Aiello, Bourassa et al. 2002; Mehrabian, Allayee et al. 2002) and in a
16
histologic study in humans (Spanbroek, Grabner et al. 2003). These findings
suggested the hypothesis that a change in the 5-lipoxygenase promoter region allele
could vary eicosanoid-mediated inflammatory circuits in the artery wall and promote
atherogenesis.
The ALOX5 gene is located on chromosome 10q11.2. It is comprised of 14
exons and is 71.88 kb in length. The common (wild-type) 5-lipoxygenase allele has
five tandem Sp1 motifs which are G/C rich (Fig. 4). The variant allele has either less
than five or more than five tandem Sp1 motifs. A large increase in carotid intima-
media thickness was reported among carriers of two variant 5-lipoxygenase promoter
alleles as compared with carriers of the common allele (Dwyer, Allayee et al. 2004).
Dwyer et al also observed that the diet-gene interactions suggest an effect of
genotype on atherosclerosis mediated by the 5-lipoxygenase pathway.
Figure 4: Structure of the ALOX5 gene Fig. courtesy H.Allayee.
Human 5 Human 5- -LO Gene Structure LO Gene Structure
Human 5 Human 5- -LO Gene Structure LO Gene Structure

17
The dietary intake of arachidonic acid increases (Ferretti A, Nelson GJ et al.
1997; Kelley DS, Taylor PC et al. 1998) the production of leukotriene B4 in human
monocytes since it is the primary substrate for 5-lipoxygenase , and increased intake
of linoleic acid and arachidonic acid enhances the production of leukotrienes
(Ferretti A, Nelson GJ et al. 1997; Kelley DS, Taylor PC et al. 1998) and this
increase could induce an atherogenic chronicity of inflammatory circuits in the
arterial wall (Lotzer, Spanbroek et al. 2003; Spanbroek, Grabner et al. 2003). The
increased dietary intake of marine n-3 fatty acids reduces (Lee TH, Hoover RL et al.
1985) the atherogenic effect of the variant alleles of 5-lipoxygenase. This interaction
was due to a leukotriene-mediated pathway, since eicosapentaenoic acid is a
competing substrate for 5-lipoxygenase and increased intake of the same will reduce
the production of LTB4 by activated monocytes (Lee TH, Hoover RL et al. 1985;
Sperling RI, Benincaso AI et al. 1993; Kelley DS, Taylor PC et al. 1999). The intake
of marine n-3 fatty acids shifts the production of more active B4 form to less active
B5 form (Lee TH, Sethi T et al. 1988; Koller, Senkal et al. 2003) and may also
induce the production of other anti-inflammatory mediators (Hong, Gronert et al.
2003).

Hence we decided to examine for the SNPs and variant allele in exons 1, 2
and 6 and the promoter of ALOX5, respectively in the Indian Gujarati study
population that we had sampled.

18
1.3. Endogamy - Work in progress:
During the migratory dispersion of early humans out of Africa, India served
as a major corridor between West and East Asia (Cann 2001). The date of entry of
modern humans into India remains uncertain, but by the middle Paleolithic period
(50,000-20,000 years before present), humans appear to have spread into many parts
of India (Misra 1992). Whilst it is known that modern humans migrated from West
Asia into India, whether there were also returns to Africa from India/Asia, and from
East Asia back to India, remains unclear (Maca-Meyer, Gonzalez et al. 2001;
Susanta, Sangita et al. 2001; Cruciani F, Santolamazza P et al. 2002). Contemporary
ethnic India is a land of enormous cultural and linguistic diversity (Karve 1961;
Beteille 1998; Majumder 1998). From a genetic perspective, the population of India
is exceptional in its size and degree of subdivision, with endogamous marriage as a
custom. However, a previous study from our lab concluded that whilst genetic
variation in India is distinctive with respect to the rest of the world, the level of
genetic divergence is smaller within Asian Indians than might be expected for such a
geographically and linguistically diverse country (Rosenberg, Mahajan et al. 2006).

The people of India are culturally stratified as tribals, who constitute 8.08%
of the total population (1991 Census of India), and nontribals. There are ~450 tribal
communities in India (Singh 1992), who speak ~750 dialects (Kosambi 1991) that
can be classified into one of the following three language families: Austro-Asiatic
(AA), Dravidian (DR) and Tibeto-Burman (TB). Most contemporary nontribal
19
populations of India belong to the Hindu religious sect and are hierarchically
arranged in four main caste classes; Brahmin (priestly class), Kshatriya (warrior
class), Vysya (business class), and Sudra (menial labour class). The nontribals
predominantly speak languages that belong to Indo-European (IE) or DR.

The IE and DR groups have been the major contributors to the development
of Indian culture and society (Meenakshi 1995), which are also known to have been
affected by multiple waves of migration and gene flow that took place in historic and
prehistoric times (Ratnagar 1995; Thapar 1995). In a recent study conducted on
ranked caste populations sampled from one Southern Indian state (Andhra Pradesh),
it was found that the genomic affinity to Europeans is proportionate to caste rank; the
upper castes being most similar to Europeans, particularly East Europeans, and the
lower castes more similar to East Asians (Bamshad, Kivisild et al. 2001). Therefore,
on the basis of linguistic evidence, it appears that European and Asian populations
were the major “donors” in the peopling of India. These findings are consistent with
the migration of IE groups into India, the establishment of the caste system, and
subsequent recruitment of indigenous people into the caste system. The tribals are
possibly the original inhabitants of India (Ray 1973), although their evolutionary
histories and biological contributions to the nontribals populations have been debated
(Risley 1915; Guha 1935; Sarkar 1958). Therefore, it is crucial to carry out genetic
investigations in such a geographically and culturally disparate, but ethnically well-
defined, population, to better understand their history.
20
A model for the origins of human diversity deduced from paleaontological
evolutionary geography maintains that while the modern human species originates
from a single evolutionary event, diversity is a result of subsequent multiple
evolutionary events associated with various geographic range expansions,
migrations, colonizations and differential survival of populations (Lahr and Foley
1994). DNA sequences offer an evidentiary alternative to fossil-based pre-historical
reconstructions (Lynn B. Jorde 1998). The uniparentally inherited non-recombining
haploid mtDNA and the Y chromosome loci are particularly sensitive to the
influences of drift, especially founder effect. Consequently, these loci are ideal for
assessing the origins of contemporary population diversity, and provide a context for
paleaontological hypothesis testing (Foley 1998; Shen, Wang et al. 2000)

Unique Event Polymorphisms (UEP) are neutral mutations that are believed
to have arisen just once during human, or population, evolution, and they are
commonly single nucleotide (SNPs) or insertion/deletion (indel) polymorphisms.
When investigating the origins of a population, UEP haplogroups, or discrete
combinations of UEPs, on the non-recombining portion of the Y chromosome
(NRY) and in the mitochondrial genome allow for the deconvolution of the maternal
and paternal origins. Autosomal microsatellite variation at unlinked loci can be used
to date events in prehistory, albeit with wide confidence intervals, as they are
unaffected by sex and are present in large numbers in the human genome (Kittles
RA, Perola M et al. 1998; Thomas, Skoreckiad et al. 1998).
21
In a recent study in our laboratory 1200 genome-wide polymorphisms were
analyzed n 15 Indian sub-populations, 14 of which were defined by language,
consisting of 432 distinct Indian-born Asian Indians. This study concluded that
populations from India and South Asia generally, constitute one of the major human
subgroups with increased similarity of genetic ancestry, although, a relatively small
amount of genetic differentiation exists among the Indian populations (Rosenberg,
Mahajan et al. 2006). The results suggest that the frequencies of many genetic
variants are distinctive in India compared to other parts of the world and that the
effects of population heterogeneity on the production of false positives in association
studies may be smaller in the Indian American population sampled, than might be
expected for such a geographically and linguistically diverse subset of the human
population (Rosenberg, Mahajan et al. 2006).

Social stratification in India is evident as social classes that are defined by a
number of endogamous groups often termed as j ātis or castes. The j ātis themselves
exist among one of the four varnas or classes namely, Brahmin, Kshatriya, Vaishya
and Shudra. Within a j āti, there exist exogamous groups known as gotras, or gols,
and refer to the lineage or clan of a person. Societal rules governing marriage are
similar in diverse regions of India. There is typically a strict definition of the clan,
gol or gotra from within which an individual’s mate may be selected and a sanction
against marriage to any individual from within his or her own gotra. This typically
translates into a surname or gotra endogamy. Thus, while consanguinity is strictly
22
avoided and there is randomness in mate selection, there is likely degree of gene
flow restriction. Patels who originate from the state of Gujarat practice this form
“endogamic exogamy” i.e. members of a village do not marry anybody from their
own village but may only marry an individual from one of the other villages within a
specified group of villages. We have studied one such group: the Chh Gaam Patels
which comprises Patels from 6 villages namely, Dharmaj, Karamsad, Nadiad,
Sojitra, Bhadran and Vaso, and this group constitutes the largest gol amongst Patels.
In order to determine the genetic structure of this group, we have obtained genotypes
at six microsatellite loci and five SNPs on the Y- chromosome and haplogroup
analysis will also been conducted. These data will be analyzed to determine if the
restricted marital practice within the same geographic region has resulted in limited
genetic differentiation and effective “genetic isolation”. The number of founders and
the extent of admixture will also be determined.

Although caution is warranted due to the fact that US-sampled Gujarati Asian
Indians do not represent a random sample from Gujarat, India, these results will
hopefully shed light on the migratory history of this endogamic population of India.
In addition to its use in understanding human evolutionary history, investigation of
human genetic variation and population structure is important for the design and
analysis of studies that map disease-susceptibility loci (Rosenberg, Mahajan et al.
2006). As human genetic disease is predicted to largely be a consequence of
common alleles and haplotypes, identifying common variants in a given population
23
provides a database of predictors that can be tested in that population for association
with disease status (Zondervan and Cardon 2004; Hinds, Stuve et al. 2005; The
International HapMap 2005). In examining genetic variants for disease association,
knowledge of the underlying population structure is important for evading the
spurious associations that can be produced by heterogeneity in the ancestry of
sampled individuals (Devlin, Roeder et al. 2001; Pritchard and Donnelly 2001;
Thomas and Witte 2002; Ziv and Burchard 2003).

During the last few decades the prevalence in India of complex genetic
diseases associated with increased life span and with an urban and western lifestyle
– including coronary artery disease, non-insulin-dependant diabetes, and metabolic
syndrome -has arisen considerably and is now greater than in most other populations
(Enas EA and J. 1995; Ramachandran, Snehalatha et al. 1997; Uppaluri 2002; Gupta,
Deedwania et al. 2004; Venkataraman, Nanda et al. 2004).

24
CHAPTER II
Materials and Methods:
2.1 Genetic variation in Asian Indians
2.1.1 Study population:
The Asian Indian cohort used in the study was previously described
(Rosenberg, Mahajan et al. 2006). Our sample consisted of an expanded population
of 576 individuals of Indian-born Asian Indians living in the United States who have
largely emigrated from Indian cities. This population was designed so that when
subdividing study participants by their primary spoken Indian language, 15
languages (Assamese, Bengali, Gujarati, Hindi, Kannada, Kashmiri, Konkani,
Malayalam, Marathi, Marwari, Oriya, Parsi, Punjabi, Tamil, Telugu), each having a
relatively localized distribution within India, would be well-represented. The number
of Gujarati individuals sampled (181) was larger that the other language groups to
examine rare minor allele frequencies. The other language groups (Dogri, Sindhi,
and Tulu) were present in the population but not at a significant number to be
analyzed independently, but these were retained for whole cohort analysis.
Informed consent was obtained from all subjects enrolled.

2.1.2 Marker genotyping:
2.1.2.1 Allelic Discrimination:
Single Nucleotide Polymorphisms (SNPs) in Exon 1, Exon 2 and Exon 6 of
the ALOX5 gene were analyzed using TaqMan allelic discrimination assays
25
(Applied Biosystems, Foster City, CA) following the manufacturer’s recommended
protocol for a 5 µl reaction volume and 2 ng of dried DNA using Applied
Biosystems (Foster City, CA) 7900HT fast real-time PCR system. ABgene
(Rochester, New York) ABsolute™ QPCR ROX (500nM) mix was used for all
assays. Custom assays were designed using the Applied Biosystems (Foster City,
CA) assay-by-design service for ALOX5 g.20C>T (Probe: 5’-
TGGCCAC[G/A]GTGACC-3’; Forward primer: 5’CGCCATGCCCTCCTACAC-3’;
Reverse primer: 5’-AGTGCCGGCGAACCA-3’), ALOX5 g.8322G>A (Probe:
5’CTGAAGAC[G/A]CCCCACG-3’; Forward primer: 5’-
TGAATGACGACTGGTACCTGAAGTA-3’; Reverse primer: 5’-
GGTGATCCAGCGGTAGCA-3’), and ALOX5 g.50778G>A (Probe: 5’-
CTGCCC[G/A]AGAAGC-3’; Forward primer: 5’-
AGACCTGATGTTTGGCTACCAGTT-3’; Reverse primer: 5’-
CGCTCCAGGCTGCACTCTA-3’).

2.1.2.2 Fragment Analysis:

The microsatellite marker was genotyped using the fluorescent primers on an
ABI3100 genetic analyzer (Applied Biosystems, Foster City, CA) and analyzed
using Genotyper version 3.7 (Applied Biosystems, Foster City, CA).

Primers for the ALOX5 promoter microsatellite (ALOX5P) were previously
described (In, Asano et al. 1997) but with the inclusion of the GTGTCTT pig-tail
(Brownstein, Carpten et al. 1996). The fluorescent marker used was FAM (blue).
26
The PCR was performed in an Applied Biosystems (Foster City, CA) GeneAmp
9700 thermal cycler using the following cycle parameter conditions: 95ºC 12 mins
followed by 10 cycles of 94ºC for 1 min, 68ºC for 2 mins, followed by 25 cycles of
94ºC for 30 sec, 60ºC for 30 sec, 72ºC for 45 sec, and a final hold at 72ºC 5 mins,
before holding at 4ºC. AmpliTaq Gold DNA Polymerase (1.2U) Applied Biosystems
(Foster City, CA) and manufacturer supplied 10x buffer was used together with
1.5mM MgCl2, 2% DMSO, 400nmol of each primer (Dwyer, Allayee et al. 2004) 30
µmol of dATP, dUTP and dCTP (Invitrogen, Carlsbad, CA), 62.5µmol 7-deaza-
dGTP (New England Biolabs, Ipswich, MA), and 30ng of DNA in a 25 µl reaction
volume. Alleles of ALOX5P were assigned labels based upon the number of
hexanucleotide Sp1-binding sites that were present. The PCR product is tested on the
1% Agarose gel to check for the expected fragment size. Depending on the strength
of the fragment, dilution of the PCR product is decided. A mixture of 9.6 ul of HiDi
Formamide + 0.4 ul Gene Scan ROX 400HD size standard (Applied Biosystems,
Foster City, CA) is added to 3 µl of the PCR product. The mixture is then set to
denature at 96’C for 10 mins and put in ice immediately, after which the plate is
loaded on the ABI 3100 genetic analyzer.

The primers for DG8S737 microsatellite were previously described
(Amundadottir, Sulem et al. 2006) and the PCR was performed using a Biometra
(Goettingen, Germany) T-Gradient thermal cycler and the following cycle
parameters were used: 95C 5mins followed by 35 cycles of 95C for 45 sec, 60C for
27
45 sec, 72C for 45 sec, and a final hold at 72C 10 mins before holding at 4C. New
England Biolabs (Ipswich, MA) Taq DNA polymerase (1U) and manufacturer
supplied 10x buffer (including MgCl2) was used along with 4 pmol of each primer,
30µmol off each dNTP (Invitrogen, Carlsbad, CA), and 30 ng of DNA in a 15µl
reaction volume. Alleles of DG8S737 were assigned based upon the change in the
number of repeats away from that of the reference sequence in the NCBI database
(23 AC dinucleotide repeats; Acc. # NT_008046.15: 148848-149016).

2.1.2.3 Haplotype Analysis:
Haplotype phase was estimated using PHASE version 2.1 (Stephens, Smith et
al. 2001; Stephens and Scheet 2005) for the ALOX5P and the three coding SNPs
(g.20C>T, g.8322G>A, g.50778G>A) for atherosclerosis, and also for the DG8S737
and rs1447295 for prostate cancer.

2.1.2.4 Statistical Analysis:
All statistics were calculated in R version 2.3.1 (Team 2006) unless otherwise
stated. A Hardy-Weinberg equilibrium (HWE) constant was calculated for each
polymorphism within the Asian Indian cohort, using the HWE.test function in the
genetics R-package (Warnes and Leisch 2005) to test whether all SNPs are in
equilibrium. An exact-test was calculated for all SNP data but a Pearson’s χ² test
with simulated p-value (based on 10000 replicates) was calculated for the
microsatellite data. An HWE score of 0 equates to the polymorphism being in
28
complete Hardy-Weinberg equilibrium, and a score of 1 equates to the
polymorphism being in complete Hardy-Weinberg disequilibrium.

Weir and Cockerham F
ST
test statistics (Weir and Cockerham 1984) was used
to calculate all the SNP data as previously described (Akey, Zhang et al. 2002) by
using R to measure the effect of population subdivision and the overall genetic
divergence among these subpopulations, where as F
ST
of 0 means no genetic
divergence, and 1 means extreme genetic divergence, between the subpopulations,
and an F
ST
of up to 0.05 represents negligible genetic differentiation. Weir and
Cockerham F test statistics for the microsatellite data were calculated using FSTAT
(Goudet 2001). A probability value (p) was calculated for each F
ST
value from a χ²
distribution using the pchisq function in the Stats R-package, to estimate the
significance of these F
ST
values.

Since it was impractical to assume that the variance within the Asian Indian
cohort is equal to that of other populations, a Welch modified two-sample t-test with
unequal variances was calculated between the minor allele frequencies in the Asian
Indian cohort and those previously reported. Hence, to test whether or not the minor
allele frequencies of the Asian Indian cohort were significantly different from those
of other populations a test was performed using the t.test function of the Stats R-
package. To give an accurate representation of the MAF in the Asian Indian cohort,
the MAF of each subpopulation was included in the analysis. Data on other
29
populations was obtained from prior publications and the National Center for
Biotechnology Information’s (NCBI) dbSNP database (Sherry, Ward et al. 2001;
dbSNP 2006). These populations were grouped into the following geographical
regions for comparison: Africa (including the Middle East), Asia (including Central,
Southern, Eastern and South-Eastern Asian countries), Americas (populations of
South and Central America, and native populations of North America), Europe
(including non-native North American populations and Russia), Oceania (Australia,
New Zealand, and the Pacific islands).

To test whether or not alleles of the ALOX5P and the three ALOX5 coding-
SNPs (g.20C>T, g.8322G>A, g.50778G>A) and the DG8S737 microsatellite and the
rs1447295 SNP are in linkage disequilibrium, the linkage disequilibrium measure
(D') and the squared correlation measure of linkage disequilibrium (r²) were
calculated between the respective polymorphisms using the java based linkage
disequilibrium plotter JLIN (Carter, McCaskie et al. 2006). For the ALOX5P and
DG8S737 microsatellite markers, each allele was tested individually with all other
alleles collapsed into a single “super-allele”.

2.2 Coronary Artery Disease
2.2.1 Subject Collection:
We advertised the study by putting up flyers (See Appendix D) and talking to
people in places like temples and health fairs, etc. A detailed questionnaire was
30
specifically designed (See Appendix E) in order to collect all the necessary
information that would be required from the subjects. The inclusion criteria for
controls were: male/female above the age of 60 years, and no history of
angiographically proven coronary artery disease to ensure they are disease-free given
the complexity of the disease .Individuals with systemic diseases that could affect the
plasma lipid profile, such as acute or chronic inflammation, collagenosis, metabolic
disease, neoplasm, hepatic or renal disease will be excluded from the study (except
for Type-2 diabetes). The inclusion criteria for cases were: male/female of any age
with a history of severe angiostenosis (>50%) in at least one major coronary artery.
In addition subjects identified with angina pectoris or MI and have had an
angioplasty, stenting or coronary artery bypass surgery will also be included.

2.2.1.1 USA
A brief lecture on the genetics of Coronary Artery Disease and the study was
given at the Jain Temple (8072 Commonwealth Avenue, Buena Park CA 90621.)
after which people volunteered to participate in the study. Contact information was
collected from these volunteers for future reference, and recruitment was conducted
in June 2006 at a Health Fair in Artesia (Albert O.Little Community Center; Artesia
Park ; 18750 Clarkdale Avenue; Artesia CA 90701) hosted by Dr. Nitin Shah. In
December 2006 a further collection was performed by Dr. Pragna Patel at a relative’s
house and at the Shri Mangal Mandir temple in Silverspring, Maryland. In each
31
recruitment location, blood was collected in different tubes as per the subject’s
case/control status.

2.2.1.2 Mumbai, India
Recruitment was done in August 2005. People were informed about the study
by word of mouth and telephonic conversations. Volunteers were enrolled into the
study depending on the inclusion criteria for cases and controls. Blood samples were
collected only in purple top tubes, at the subjects’ residences. Dr. Sanjay Mehta
helped with the phlebotomy and storage of samples at 4ºC overnight. Samples were
processed at the Jaslok Hospital (15 - Dr. Deshmukh Marg, Pedder Road,Mumbai-
400 026 India)and shipped to the Institute for Genetic Medicine, University of
Southern California.
Informed consent was obtained from all subjects, enrolled either in USA or India.

2.2.2 Blood Collection:
The following tubes were used during blood collection: 10ml Purple top tubes
containing K2EDTA (B.D.Biosciences, Franklin Lakes, NJ) for DNA extraction, 10ml Tiger
top tubes containing serum separation gel with pro-clotting agent (B.D.Biosciences, Franklin
Lakes, NJ) for serum to obtain a lipid profile, and 10ml PAX gene tubes containing
proprietary additive (B.D.Biosciences, Franklin Lakes, NJ) for RNA extraction. We
collected purple tops and tiger tops for all subjects, but for select cases and controls
we collected PAX gene tubes to use RNA for gene expression analysis. These tubes
32
were stored at 4ºC overnight and shipped to Institute for Genetic Medicine,
University of Southern California until DNA/RNA extraction.

2.2.3 Nucleic Acids Extraction:
Purple tops were stored at 4’C until processed for DNA extraction using
Puregene® DNA Purification kit following manufacturer’s recommended protocol
(Gentra Systems, Indianapolis, IN).
PAX gene tubes were processed immediately for RNA extraction using
manufacturer’s recommended protocol (Qiagen, Valencia, CA)
Tiger top tubes were immediately spun in the centrifuge machine to obtain serum for
a lipid profile.

2.2.4 Marker genotyping

Done as described for ALOX5 in section 2.1.2.

2.2.5 Statistical Analysis
A one-sample z-test for a Binomial Proportion for two sided/tailed alternative
for a large sample size with a significance level at 0.01 was calculated. A Pearson’s
Chi square test with Yate’s continuity correction for two-sample was calculated to
confirm the above z-test statistic. This was also confirmed by carrying out the test
statistic on this website. http://www.unc.edu/~preacher/chisq/chisq.htm

33
2.3 Endogamy:
2.3.1 Subject Collection:

Indian Gujarati samples were collected by Dr.Patel from different places in
USA. Primarily adult Gujarati male individuals were enrolled since males are known
to strictly maintain endogamic marriage practices and importantly, Y chromosome
analysis requires males. They should be from specific endogamic or exogamic
groups. For the study group, the individuals should originate from one of the groups
of Chha Gaam in Gujarat, and for control subjects; they should be male and have an
ethnic origin from Gujarat but not originate from the Chh Gaams. No specific
inclusion criterion for health status was observed. Subjects should be in general good
health, but if with chronic diseases, were accepted. Informed consent was obtained
from all the subjects enrolled.

2.3.2 The Fragment Analysis:
In 1997, the European forensic community settled on a core set of Y-STR
markers or “minimal haplotypes” that includes DYS19, DYS389I/II, DYS390,
DYS391, DYS392, DYS393, and DYS385a/b with YCAIIa/b as an optional marker
to create an “extended haplotypes” (Kayser, Caglià et al. 1997; Knijff, Kayser et al.
1997; L. Roewer, M. Krawczak et al. 2001). We used all the above markers except
DYS389I/II, DYS393, DYS385a/b and YCAIIa/b for our population analysis, along
with a few other Y-STRs and SNPs suggested by Chris-Tyler Smith, as per our
population parameters.
34

Fragment analysis was carried out for the following list of markers and the
corresponding fluorescent labels. The primer sequence and the PCR product size is
described in Table 3.
Table 3: List of DYS markers used for fragment analysis

Marker
Primer Expected PCR product size
DYS19-L-NED
CTACTGAGTTTCTGTTATAGT 195
DYS19-R
GTGTCTTATGGCATGTAGTGAGGACA
DYS390-L
GTGTCTTTATATTTTACACATTTTTGGGCC 215
DYS390-R-FAM
TGACAGTAAAATGAACACATTGC
DYS391-L-FAM
CTATTCATTCAATCATACACCCATAT 287
DYS391-R
GTGTCTTACATAGCCAAATATCTCCTGGG
DYS392-L
GTGTCTTAAAAGCCAAGAAGGAAAACAAA 254
DYS392-R-HEX
CAGTCAAAGTGGAAAGTAGTCTGG
DYS437-F-FAM
GACTATGGGCGTGAGTGCAT 192
DYS437-R
GTGTCTTAGACCCTGTCATTCACAGATGA
DYS439-F-FAM
TCCTGAATGGTACTTCCTAGGTTT 252
DYS439-R
GTGTCTTGCCTGGCTTGGAATTCTTTT

The PCR reagents used were: 0.2 µl of Taq DNA Polymerase (5U/µl) New
England Biolabs Inc. (Ipswich, MA) and 1.5 µl manufacturer supplied 10x buffer
was used together with 1.5mM MgCl2, 0.4 µl of 10 µM dNTPs along with 0.3 µl of
10 µM forward and reverse primer as mentioned in Table 3.The PCR was performed
in an Applied Biosystems (Foster City, CA) GeneAmp 9700 thermal cycler. The
PCR product is tested on the 1% Agarose gel to check for the expected fragment
size. Depending on the strength of the fragment, dilution of the PCR product is
35
decided. A mixture of 10 ul of HiDi Formamide + Rox size standard (Applied
Biosystems, Foster City, CA) is added to 3 µl of the PCR product. 40ul of Rox is
required in 1 ml. The mixture is then set to denature at 96’C for 10 mins and put in
ice immediately, after which the plate is loaded on the 3100 genetic analyzer.
Table 4: PCR conditions for DYS 437 and DYS 439

Marker
Pre-
incubation
Denaturing Annealing
Extension Cycles
Denaturing Annealing
Extension Cycles
Final
Extension
DYS437
94 C, 5
mins
94C,1 min 65C-->55C(-1C/cycle)
72C,1 min 30 sec 10
94C, 1min 56C, 1min
72C, 1min 25
72C, 7
mins
DYS439
94 C, 5
mins
94C,1 min 65C-->55C(-1C/cycle)
72C,1 min 30 sec 10
94C, 1min 56C, 1min
72C, 1min 25
72C, 7
mins

DYS 19, DYS 390, DYS 391 and DYS 392 were genotyped at the Marshfield
genotyping facility (markerd in red in Table 3).

2.3.3 Snapshot Assay:
The PCR reaction for SNP analysis was carried out using the ABI PRISM
SNaPshot Multiplex Kit following the manufacturer’s recommended protocol, but
reducing the volume to half as shown below:
Table 5: SNaPshot PCR Reaction protocol

Item
One Sample (ul)
manufacturer's
recommendation
One sample (ul)
Used protocol
Snapshot Multiplex Ready Reaction Mix 5 2.5
Pooled PCR products 3 1.5
Pooled Snapshot primers 1 0.5
Deionized water 1 0.5
Total 10 5

We firstly used 2ul of SAP and 0.1ul of ExoI for each reaction during the
template preparation. Then 1.5 ul of the pooled cleaned template is used along with
36
the above mentioned reagents for a 5 ul reaction for 25 cycles at 96C for 10 sec,
followed by 50C for 5 sec, 60C for 30 sec and 4C at infinity performed on the ABI
PRISM 9700 Thermal Cycler. After which, 0.5ul of SAP was used to remove the
unincorporated ddNTPs. 10ul of HiDi was added and denatured at 96C for 10 mins
and left on ice immediately for 10 mins. The product was then run on the ABI
PRISM 3100 Genetic Analyser and the results were analysed using GeneScan
Analysis Software version 3.1.

Table 6: A list of the SNPs with their corresponding PCR and Snapshot primers

SNPs PCR primer Snapshot primer
Expected
PCR
product
size (bp)
YAP-c-NED AGGACTAGCAATAGCAGGGGAAGA absent/present 99/413
YAP-d CAGGGCCAACTCCAACCAAG
M95-F Ggtctgtgaaccccactttc AGGCTAAGCCATCCA 300
M95-R Tgaggtccttcccagagatg
M134-F cccacaaccagacaatcAGA TTGATCCCCACCAAT 247
M134-R TTTGGCTTCTCTTTGAACAGg
M82-F GGGTAGCCTGTtcaaatcca CCTACCTGGAAACAT 273
M82-R Gaaccagaggcaagggacta
M69-F Gtccagccctcagatcacat gctgtttacactcctgaaa 273
M69-R Tggaaacatatgaaaatgcagaa

37

CHAPTER III
Prevalence of Common Disease-associated Polymorphisms in Asian
Indians

The work described here is part of a larger study conducted in the laboratory
that examined variation of nineteen common polymorphisms associated with
diseases/traits in a collection of 576 individuals born in India who were sampled in
the United States and who self-reported that their mother-tongue was one of 14 of
the 23 official or scheduled Indian languages as well as individuals who belong to
one additional ethnic group (Parsis). The purpose of these studies was to compare the
allele frequency distribution in Indians when compared to that in other populations
for which frequencies had been previously reported. My contribution to this study
was the examination of variation at the ALOX5 locus and two loci on chromosome 8
that have been recently associated with prostate cancer in Icelandic, African
American, and HapMap Caucasian American and African in this cohort. This cohort
that had been sampled for population genetics studies was genotyped at 1200 loci
and structure analysis of these data showed that: (1) Indians constitute a distinct
cluster, and (2) despite the geographic and linguistic diversity of the groups they
exhibit a low level of genetic heterogeneity (Rosenberg, Mahajan et al. 2006).
Because the study participants were born in India, we refer to the individuals and
population as being “Asian Indian” or just “Indian”; however, it is important to note
that because the Asian Indian individuals were sampled in the United States, some
38
biases may be introduced when extrapolating the results to India as a whole
(Rosenberg, Mahajan et al. 2006).
3.1 Analysis of polymorphisms at the ALOX5 locus in Indian
language groups.

The ALOX5 locus has been previously associated with atherosclerosis, and
was the first gene involved in inflammation that was implicated in this disease. Four
polymorphisms have been widely studied at the ALOX5 locus. The common (wild-
type) 5-lipoxygenase allele has five tandem Sp1 motifs which are G/C rich. The
variant allele has either less than five or more than five tandem Sp1 motifs. The
microsatellite under study is located in the promoter region of the gene and three
SNPs: g.20C>T, g.8322G>A and g.50778G>A located in exon 1, exon 2 and exon 6,
respectively were also examined. Genotypes were determined at these polymorphic
sites in 576 Indian individuals as described in Methods (Chapter II). All of the
polymorphisms were found to be in Hardy-Weinberg equilibrium (HWE) as shown
in Table 7, except for the ALOX5 g.20C>T polymorphism which yielded an HWE
constant of 0.016.

39
Table 7: Allele frequencies of the polymorphisms at the ALOX5 locus in Indians belonging to different language groups

Atherosclerosis
Gene Name: ALOX5 ALOX5 ALOX5 ALOX5
Nucleotide change: MS (5'-GGGCGG-3' starting at -145) g.20C>T g.8322G>A g.50778G>A

n 3 4 5 6 7 8 T A A

Mother Tongue

Assamese 26 0 0.16 0.8 0.04 0 0 0.14 0 0.02
Bengali 27 0 0.276 0.655 0.069 0 0 0.276 0.017 0
Gujarati 181 0 0.167 0.792 0.042 0 0 0.188 0 0
Hindi 29 0 0.186 0.767 0.047 0 0 0.186 0.012 0
Kannada 24 0 0.179 0.732 0.089 0 0 0.179 0.036 0
Kashmiri 24 0 0.18 0.8 0.02 0 0 0.16 0.02 0
Konkani 43 0 0.08 0.86 0.06 0 0 0.096 0.058 0
Malayalam 25 0 0.148 0.759 0.093 0 0 0.148 0 0
Marathi 26 0 0.111 0.778 0.111 0 0 0.111 0 0
Marwari 25 0.008 0.186 0.758 0.044 0 0.003 0.193 0.019 0.003
Oriya 27 0 0.231 0.692 0.077 0 0 0.231 0 0
Parsi 25 0 0.24 0.66 0.1 0 0 0.24 0.02 0
Punjabi 28 0.034 0.259 0.69 0.017 0 0 0.241 0 0.017
Tamil 29 0.018 0.232 0.714 0.036 0 0 0.232 0.054 0.018
Telugu 28 0 0.229 0.688 0.063 0.021 0 0.229 0 0

F
ST
0.006 0.013 0.009 0.013
p-value 1 1 1 1

40
Table 7, Continued
Gender

Female 237 0.008 0.191 0.733 0.066 0.002 0 0.192 0.017 0.006
Male 339 0.004 0.192 0.753 0.049 0 0.001 0.193 0.016 0.003

F
ST
0 0.052 0.052 0.037
p-value 1 0.819 0.82 0.847

Population

Cohort 576 0.006 0.192 0.745 0.056 0.001 0.001 0.193 0.016 0.004
Standard Error 0.003 0.014 0.015 0.007 0.001 1.85 x 10
-4
0.013 0.005 0.002

HWE Constant 0.009 0.016 2.50 x 10
-4
1.94 x 10
-5

p-value 0.213 0.014 1 1

Welch modified t-test:
Africa 0.151 0.172
Europe 0.724 0.067
Middle
East
Central/South Asia
East Asia 0.007
Americas
Oceania

P-values significant at <0.05 are shown in bold.

41
Whilst a variant of the common 5-allele of ALOX5P has been previously
associated with an increased risk of atherosclerosis (Dwyer, Allayee et al. 2004), the
association of the three coding SNPs (g.20C>T, g.8322G>A, g.50778G>A) has not been
previously reported. Haplotype analysis of the alleles of the ALOX5P and the three
ALOX5 coding SNPs in this Asian Indian cohort showed that they were in strong LD
with a D’ close to 1 (data not shown). However, their squared correlation (r²) was found
to vary (Table 8). The 4-repeat allele of ALOX5P was found to be very strongly
correlated with the minor T-allele of the g.20C>T SNP (r² = 0.949), and the common 5-
repeat allele was less strongly correlated with the major allele C-allele of the g.20C>T
SNP (r² = 0.674). The 3-repeat allele of the promoter repeat polymorphism was also
found to be in moderate correlation with the major G-allele of the g.50778G>A SNP (r²
= 0.253).
Table 8: Squared correlation (r²) values between alleles of ALOX5P and the
three coding ALOX5 SNPs

Allele Coding SNPs
r² values
Repeat number

g.20C>T g.8322G>A g.50778G>A
3- repeat allele 8.79 x 10-5 9.87 x 10-5 0.253 [G]
4- repeat allele 0.949 [T] 0.004 1.89 x 10-5
5-repeat allele 0.674 [C] 0.006 0.013
6-repeat allele 0.014 0.001 2.67 x 10-4
7-repeat allele 2.07 x 10-4 1.43 x 10-5 3.94 x 10-6
8-repeat allele 2.07 x 10-4 1.43 x 10-5 3.94 x 10-6
Highlighted cells show significant r² values.

In consensus with this correlation and allele frequencies, the most common
haplotype of the ALOX5P promoter variant and the coding ALOX5 SNPs in the
Asian Indian population was 5CGG with a frequency of 0.726 which combined the

42
5-repeat allele of the ALOX5P with the major alleles of all the 3 SNPs (Table 9).
The second most common haplotype was 4TGG at 0.179, which combined the 4-
repeat allele of ALOX5P with the minor allele of the g.20C>T SNP, and the major
allele of the g.8322G>A and g.50778G>A SNPs (Table 9). A little more than 50% of
the Asian Indian cohort was homozygous for the 5CGG haplotype (0.531; Table 9)
and a further 38.9% were heterozygous, of which 3.3% also possessed a second
haplotype containing the 5-repeat allele of the ALOX5P (underlined; Table 9). Two
thirds of this group were heterozygous for the 5CGG and 4TGG haplotypes (0.253)
and just over a fifth were heterozygous for the 5CGG and the 6CGG haplotypes
(0.086; Table 9). Three other haplotypes were found to be homozygous in the
individuals, the most common being 4TGG at a frequency of 0.051 followed by
6CGG and 3CGG at a frequency of 0.003 and 0.002 respectively (Table 9).
Table 9: Haplotypes and Diplotypes of identified ALOX5 polymorphisms with
its corresponding frequencies

Haplotype Frequency Diplotype Frequency
5CGG 0.726 5CGG / 5CGG 0.531
4TGG 0.179 4TGG / 5CGG 0.253
6CGG 0.046 5CGG / 6CGG 0.086
5CAG 0.017 4TGG / 4TGG 0.051
4CGG 0.012 5CGG / 5CAG 0.031
6TGG 0.010 4CGG / 6TGG 0.016
3CGG 0.003 3CGA / 5CGG 0.005
3CGA 0.002 6CGG / 6CGG 0.003
5CGA 0.001 4CGG / 5CGG 0.003
3TGG 0.001 4CGG / 5CGA 0.003
5TGG 0.001 5CGG / 6TGG 0.003
7CGG 0.001 3CGG / 3CGG 0.002
8CGG 0.001 3CGG / 5CGG 0.002

43
Haplotype Frequency Diplotype Frequency
3TGG / 4TGG 0.002
4CGG / 4TGG 0.002
4TGG / 5CAG 0.002
5CGG / 7CGG 0.002
5CGG / 8CGG 0.002
5CGG / 5TGG 0.002

Polymorphisms are ordered ALOX5P –g.20C>T – g.8322G>A – g.50778G>A.

Highlighted cells show haplotypes containing common ALOX5P 5-repeat allele.

Diplotypes containing the common ALOX5P 5-repeat allele but not the common allele of all three
SNPs are underlined.

3.2 Analysis of polymorphisms at the DG8S737 and rs1447295 loci in
Indian language groups

Recently, prostate cancer locus: DG8S737 microsatellite -1 allele and the
rs1447295 SNP A allele were reported by Amundadottir et al. to be in strong linkage
disequilibrium (LD) within the Icelandic HapMap Caucasian American and African,
and African American population (Amundadottir, Sulem et al. 2006). I sought to
determine the allele frequencies for these markers in Indians using the cohort of 14
language groups. Genotypes were determined and statistical analysis was performed
as described in Methods (Chapter II). Both the polymorphisms were found to be in
Hardy-Weinberg equilibrium (HWE) as shown in Table 10.
Table 9, Continued

44
Table 10: Allele frequencies of the polymorphisms at loci previously associated with prostate cancer, in Indian language
groups.

Prostate Cancer
Gene Name: Intragenic Intragenic
Nucleotide
Change:
MS C →A
Protein Change: None none
NCBI db
reference:
DG8S737 rs1447295

N -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5 +6 +7 C A

Mother Tongue

Assamese 26 0.000 0.040 0.000 0.000 0.000 0.020 0.120 0.020 0.060 0.180 0.220 0.100 0.060 0.080 0.080 0.020 0.000 0.000 0.880 0.120
Bengali 27 0.017 0.000 0.000 0.000 0.000 0.000 0.034 0.121 0.155 0.190 0.103 0.155 0.052 0.121 0.052 0.000 0.000 0.000 0.879 0.121
Gujarati 181 0.000 0.042 0.000 0.000 0.042 0.000 0.021 0.042 0.229 0.188 0.188 0.042 0.042 0.125 0.042 0.000 0.000 0.000 0.875 0.125
Hindi 29 0.023 0.023 0.000 0.012 0.012 0.012 0.128 0.035 0.151 0.209 0.116 0.093 0.035 0.070 0.023 0.035 0.023 0.000 0.814 0.186
Kannada 24 0.000 0.071 0.000 0.000 0.018 0.000 0.089 0.036 0.161 0.268 0.125 0.036 0.000 0.143 0.054 0.000 0.000 0.000 0.875 0.125
Kashmiri 24 0.000 0.000 0.000 0.000 0.000 0.000 0.060 0.060 0.120 0.220 0.120 0.200 0.040 0.120 0.060 0.000 0.000 0.000 0.960 0.040
Konkani 43 0.000 0.019 0.000 0.000 0.019 0.019 0.077 0.115 0.135 0.173 0.192 0.058 0.135 0.019 0.019 0.019 0.000 0.000 0.808 0.192
Malayalam 25 0.000 0.000 0.000 0.000 0.000 0.000 0.093 0.037 0.167 0.204 0.111 0.185 0.019 0.148 0.000 0.019 0.000 0.019 0.926 0.074
Marathi 26 0.000 0.000 0.000 0.000 0.037 0.000 0.074 0.037 0.093 0.278 0.111 0.130 0.056 0.093 0.056 0.037 0.000 0.000 0.889 0.111
Marwari 25 0.000 0.008 0.003 0.000 0.008 0.022 0.110 0.028 0.116 0.293 0.122 0.077 0.058 0.105 0.041 0.006 0.003 0.000 0.859 0.141
Oriya 27 0.000 0.000 0.019 0.019 0.058 0.038 0.058 0.135 0.077 0.173 0.173 0.096 0.038 0.077 0.019 0.019 0.000 0.000 0.692 0.308
Parsi 25 0.000 0.000 0.020 0.000 0.040 0.000 0.020 0.020 0.380 0.220 0.100 0.140 0.020 0.020 0.020 0.000 0.000 0.000 0.960 0.040
Punjabi 28 0.000 0.000 0.000 0.000 0.017 0.000 0.052 0.069 0.121 0.345 0.121 0.086 0.086 0.069 0.034 0.000 0.000 0.000 0.966 0.034
Tamil 29 0.000 0.000 0.000 0.000 0.018 0.018 0.161 0.018 0.125 0.143 0.143 0.143 0.054 0.107 0.054 0.018 0.000 0.000 0.839 0.161
Telugu 28 0.000 0.021 0.000 0.000 0.000 0.000 0.042 0.104 0.188 0.375 0.083 0.021 0.042 0.042 0.021 0.042 0.000 0.021 0.896 0.104

F
ST
0.007 0.020
p-value 1 1

45
Table 10, Continued
Gender
Female 237 0.002 0.021 0.004 0.002 0.019 0.011 0.078 0.044 0.146 0.251 0.129 0.099 0.057 0.078 0.049 0.011 0.000 0.000 0.880 0.120
Male 339 0.003 0.009 0.001 0.001 0.013 0.013 0.091 0.052 0.140 0.242 0.133 0.094 0.049 0.105 0.032 0.013 0.004 0.003 0.864 0.136

F
ST
0 0
p-value 1 1

Population

Cohort 576 0.003 0.014 0.003 0.002 0.016 0.012 0.085 0.050 0.142 0.245 0.130 0.098 0.052 0.094 0.039 0.012 0.003 0.002 0.871 0.129

HWE Constant 0.003 0.002
p-value 0.433 0.580

Welch modified t-test:
Europe 0.012
Asia 0.486
Africa 0.021
Americas

Alleles of DG8S737 were assigned based upon the change in the number of repeats away from that of the reference sequence in the NCBI database (23 AC
dinucleotide repeats). Allele -1 is equivalent to the prostate cancer risk-associated -8 allele reported by Amundadottir et al. that had 22 repeats (Amundadottir,
Sulem et al. 2006). P-values that were significant at <0.05 are shown in bold.

46
The DG8S737 microsatellite -1 allele and the rs1447295 SNP A allele were reported
by Amundadottir et al. to be in strong linkage disequilibrium (LD) within the
Icelandic (D' = 0.85; r²=0.52), HapMap Caucasian American (D' = 0.72; r² = 0.29)
and African (D' = 0.62; r²=0.21), and African American (D'= 0.48; r² = 0.12),
population (Amundadottir, Sulem et al. 2006). Interestingly, haplotype analysis
between DG8S737 and the rs1447295 in this Asian Indian cohort found that the rarer
-4 allele (19 repeats) of DG8S737 exhibited the greatest correlation with the A-allele
of rs1447295, along with being in strong LD (Table 11; D'= 0.802; r² = 0.403), while
the -1 allele was in complete LD with the A-allele rs1447295 (Table 11; D' = 1), but
was weakly correlated (r² = 0.048).
Table 11: Linkage disequilibrium (D') and the squared correlation (r²) values
between alleles of DG8S737 and rs1447295.

Allele D' r²
-10 0.551 0.005
-9 1.000 0.002
-8 1.000 0.000388
-7 0.326 0.001
-6 0.160 0.002
-5 0.812 0.055
-4 0.802 0.403 [A]
-3 0.345 0.043
-2 0.417 0.004
-1 1.000 0.048
0 1.000 0.022
1 0.972 0.015
2 1.000 0.008
3 0.866 0.012
4 1.000 0.006
5 1.000 0.002
6 0.551 0.005
7 0.326 0.001
Highlighted cell shows the rare -4 allele of DG8S737 with its corresponding D' and r² values.

Allele -1 is equivalent to the prostate cancer risk-associated -8 allele reported by Amundadottir et al.
that had 22 repeats (Amundadottir, Sulem et al. 2006), (in bold).

47
Hence, using the Asian Indian population in the analysis of the disease-associated
variants may assist in determining the true causative variant(s).

In this Asian Indian cohort, the -4 allele of DG8S737 microsatellite and the
minor A- allele of the rs1447295 SNP were found to represent 7.1% of the
haplotypes and a further 1.4% carried the -4 allele but the major C-allele (Table 12).
5.8% of the cohort carried an allele other than that -4 allele of the microsatellite
along with the minor A-allele of the SNP (Table 12), which was translated into the
genotypes of individuals where we found that 73.4% of this Asian Indian cohort was
homozygous for this haplotype (Table 12). We also found that 1.2% of this cohort
was homozygous for the haplotypes containing the -4 allele of the DG8S737 and the
minor A-allele of rs1447295, and a further 11.8% of individuals who were
heterozygous but possessed one haplotype containing the -4 allele and the minor A-
allele (Table 12). Of these, 1.8% had a second haplotype that contained the minor A-
allele of rs1447295 but not the -4 allele of DG8S737. Interestingly, there were no
haplotypes containing the -1 allele and the A allele, though the -1 allele was always
found associated with the C allele of rs1447295. However, 6.6% of the individuals
carried a single copy of both the -1 allele and the A allele (data not shown).
Table 12: Haplotype and diplotype frequencies for the -4 allele of the DG8S737
microsatellite and the rs1447295 alleles

Haplotype Frequency Diplotype Frequency
-4 / A 0.071 (-4 / A) / (-4 / A) 0.012
-4 / C 0.014 (-4 / C) / (-4 / A) 0.002
# / C 0.857 (# / A) / (-4 / A) 0.007
# / A 0.058 (# / C) / (-4 / A) 0.109
(# / C) / (-4 / C) 0.026
(# / C) / (# / A) 0.109
(# / C) / (# / C) 0.734
“#” denotes all other alleles of DG8S737 besides the -4 allele.

48
3.3 Discussion:
I have determined the frequencies of common polymorphisms previously
associated with an increased risk of atherosclerosis and prostate cancer (Table 1), in
a cohort of 576 Indian-born Asian Indians sampled in the United States.

All polymorphisms, except ALOX5 g.20C>T were found to be in HWE and a
low F
ST
value was obtained suggesting no significant population subdivision
identified between the different subpopulations (Table 7). The failure to apply HWE
for the ALOX5 g.20C>T SNP is most likely due to chance; however, it could also be
due to the Wahlund effect, genetic drift, or differing selection between the
subpopulations. The ALOX5 g.8322G>A and g.50778G>A SNPs were found to be
present only in some of the Asian Indian subpopulations investigated here. There
was no evident pattern to these differences with regards to the clustering of these
subpopulations within India, and it is possible that these differences have resulted
from either the different origins of the subpopulations during the peopling of India
and strengthened by their practice of endogamy (Bamshad, Kivisild et al. 2001;
Basu, Mukherjee et al. 2003), or admixture introduced by the differential migration
of non-Indian populations into regions of India during the course of its history
(Partha 1998; Cann 2001). Their absence in the Gujarati population, for which we
have around seven times the number of individuals of the other subpopulations,
would suggest that their absence in the other subpopulations is not necessarily due to
a lack of a sufficient sample size for their detection.

49

Interestingly, the MAF of atherosclerosis (ALOX5P, ALOX5, g.8322G>A
and 50778G>A) – associated polymorphisms were found to be comparable to those
of European populations, and those associated with prostate cancer (DG8S737 and
rs1447295), to African populations. However, none showed a high resemblance to
the populations of Asia.

An association between changes away form the common allele (5 repeats) in
a recent-polymorphism (ALOX5P) comprised of Sp1 binding sites in the promoter
region of ALOX5 and atherosclerosis has been reported (Dwyer, Allayee et al. 2004).
Analysis of ALOX5P in the Asian Indian cohort showed six alleles, of which the five
Sp-1 binding site repeats-allele had the highest frequency of 0.745 (Table 10). This
was followed by the allele with four Sp-1 binding site repeats at a frequency of
0.192, and the other alleles accounting for the remaining 0.064. 56.4% of the
individuals were homozygous for the common allele containing five Sp-1 binding
site repeats, and 92.5% of the individuals had at least one copy of that common
allele. The remaining 7.5% of individuals had two variant alleles (Table 10). This is
higher than the 5.96% reported for a cohort of individuals of mixed-ethnicity
unaffected by atherosclerosis, who also reported 94.0% of the individuals with at
least one copy of the common allele (Dwyer, Allayee et al. 2004). The same study
also reported that variant alleles were most common in blacks (24.0%), and Asians
and Pacific Islanders (19.4%), than Hispanic (3.6%) and non-Hispanic whites

50
(3.1%). The frequency of variants in the Asian Indian cohort would suggest that they
are closer to Caucasians than Asians. However, the Asian Indian population has an
elevated incidence of CAD compared with these other populations (Wilson,
Christiansen et al. 1989; Enas 1991; Enas and Mehta 1995; Enas, Garg et al. 1996;
Enas and Senthilkumar 2001). It may therefore, be possible that there is a particular
variant allele of ALOX5P that predisposes to CAD, whilst the other variants, and the
common allele, do not, but further research is required to investigate this.

Three coding SNPs have also been identified in the ALOX5 gene (g.20C>T,
g.8322G>A and g.50778G>A) and these appear to be in partial or complete LD with
the alleles of the ALOX5P (personal communication – Dr. H. Allayee). Haplotype
analysis of the four ALOX5 polymorphisms in this Asian Indian cohort found that
there is LD between alleles of the ALOX5P and coding SNPs. Major allele of
g.20C>T SNP is in LD with the 5-allele and the minor allele is in LD with the 4-
allele, and the major allele of g.50778G>A SNP is in LD with the 3-allele (Table
9).Close to half of the cohort contains haplotypes containing variant alleles of the
ALOX5P, with 8.1% of the cohort homozygous for variant haplotypes (Table 10).
As discussed above, these variant alleles have been previously associated with an
increased risk of developing atherosclerosis in other populations, indicating that this
latter group will be at greatest risk in this cohort. However, their frequency is much
lower than that of CAD in the Asian Indian population.

51
The -1 allele is the most common allele of the DG8S737 microsatellite and
has been associated with an increased risk of prostate cancer in other populations.
Interestingly, it is also the common allele in this Indian cohort but, whilst this
common allele has been reported to be in strong LD with the minor allele A-allele of
the SNP rs1447295 in these populations, we have found that a different allele (-4
allele) is in strong LD with the minor A-allele of the SNP 1447295 in this Asian
Indian cohort. Further case-control studies on Asian Indian prostate cancer may
allow for the identification of true causative variant(s). The frequency of these
polymorphisms is also still far higher that the frequency of prostate cancer in the
Asian Indian population (10 per 100,000) (Hsing, Tsao et al. 2000; Quinn and Babb
2002), suggesting that the behavior of these polymorphisms in the prediction of
prostate cancer risk may be different in the Asian Indian population from those
previously reported.

We have found that the frequencies of the disease/trait-associated minor
alleles of many of the polymorphisms investigated in this cohort did not correlate
with their prevalence in the Asian Indian population. This is expected since both the
diseases are known to be complex and result from a combination of variants at
multiple genetic loci as well as environmental factors. Differences in genetic
backgrounds and environmental heterogeneity between populations will have a
modifying effect on the correlation of polymorphisms with disease/trait prevalence.
The degree of complexity between these disease/traits will also vary, as some, such

52
as CAD, are known to be highly complex. One might therefore, not expect the
correlation of factors associated with CAD to be strong, and therefore it indicates
that the environmental and/or other genetic factors make a stronger contribution to
the presentation of the disease/trait in Asian Indians than these variants alone.

53
CHAPTER IV
Association studies on Coronary Artery Disease in Asian Indians

4.1 Statistical analysis of genotypes at the ALOX5 locus in CAD
cases and controls

As stated previously, the ALOX5 gene has been associated with
atherosclerosis and has initiated a great interest in the possible role of genes involved
in inflammation in this disease. The common (wild-type) 5-lipoxygenase allele has
five tandem Sp1 motifs which are G/C rich. The variant allele has either less than
five or more than five tandem Sp1 motifs. A large increase in carotid intima-media
thickness was reported among carriers of two variant 5-lipoxygenase promoter
alleles as compared with carriers of the common allele (Dwyer, Allayee et al. 2004).
Dwyer et al also observed that the diet-gene interactions suggest an effect of
genotype on atherosclerosis mediated by the 5-lipoxygenase pathway.

We used community-based sampling to recruit Asian Indians with a
diagnosis of self-reported CAD, angina pectoris or MI and who report having had an
angioplasty, stenting or coronary artery bypass surgery. This sampling also recruited
healthy Indian control individuals who were >55 years of age and no history of
angiographically proven coronary artery disease to ensure they are disease-free given
the complexity of the disease. We analyzed four common polymorphisms in the
ALOX5 gene in a cohort of 243 case-control individuals of Asian Indian descent.
The microsatellite under study is located in the promoter region of the gene and three

54
SNPs: g.20C>T, g.8322G>A and g.50778G>A located in exon 1, exon 2 and exon 6,
respectively were also examined. We used PHASE to analyze the microsatellite data
and fastPHASE to analyze the SNP data. The linkage disequilibrium (LD) between
the SNPs and the alleles of the microsatellite were calculated using R (Table 13).
Table 13: Squared correlation (r²) values between alleles of ALOX5P and the
three coding ALOX5 SNPs in cases, controls and all subjects.

Cases
r² values
Allele
g.20C>T g.8322G>A g.50778G>A

4 0.318 0.003 0.000
5 0.009 0.002 0.000
6 0.010 0.000279 0.000

Controls r² values
Allele
g.20C>T g.8322G>A g.50778G>A

4 0.320 0.000144 0.000
5 0.007 0.003 0.000
6 0.001 0.000340 0.000

All
r² values
Allele
g.20C>T g.8322G>A g.50778G>A

4 0.319 0.0000723 0.000
5 0.00035 0.002 0.000
6 0.003 0.000317 0.000
Highlighted cells show significant r² values.

Haplotype analysis of the ALOX5P and the three ALOX5 SNPs in this case-
control cohort found an unpredictable squared correlation (r²; Table 13). Only the
allele 4 in cases, controls and all individuals was found to be moderately correlated
with the minor T-allele of the g.20C>T SNP (r²= 0.318 in cases; r²= 0.320 in controls

55
and r²=0.319 in all individuals). The other SNPs did not have a significant r² value
with respect to the three different alleles of ALOX5P (alleles 4, 5 and 6).
Table 14: Haplotypes of identified ALOX5 polymorphisms with their
corresponding frequency

Cases Controls All
Haplotype Frequency Haplotype Frequency Haplotype Frequency
3CGG 0.006 3CGG 0 3CGG 0.002
3TGA 0.006 3TGA 0 3TGA 0.002
4CGG 0.128 4CGG 0.201 4CGG 0.177
4TGG 0.056 4TGG 0.035 4TGG 0.041
4TGA 0.006 4TGA 0 4TGA 0.002
5CGG 0.628 5CGG 0.553 5CGG 0.57
5CAG 0.006 5CAG 0.004 5CAG 0.004
5TGG 0.117 5TGG 0.158 5TGG 0.146
5TAG 0 5TAG 0.004 5TAG 0.002
6CGG 0.044 6CGG 0.039 6CGG 0.045
6TGG 0 6TGG 0.007 6TGG 0.006
7CGG 0.006 7CGG 0 7CGG 0.002
Highlighted cells show significant frequency.

The most common haplotype of the ALOX5P promoter variant and the
coding ALOX5 SNPs in the Asian Indian population was 5CGG with a frequency of
0.570 which combined the 5-repeat allele of the promoter with the major alleles of
all the 3 SNPs (Table 14). When considering only cases, the frequency was 0.628
and when considering only controls, the frequency was 0.553. This allele frequencies
between cases and controls did not show a statistically significant difference (p value
= 0.25).The odds of a person carrying the 5CGG haplotype and developing CAD is
1.37 times a person not carrying the 5CGG haplotype (OR=1.37). The second most
common haplotype was 4CGG at 0.177 in all and 0.128 and 0.201 in cases and
controls respectively, which combined the 4-repeat allele of ALOX5P with the major

56
allele of the g.20C>T SNP, and the major allele of the g.8322G>A and g.50778G>A
SNPs (Table 14). These allele frequencies in cases and controls also did not show a
statistically significant difference either (p value = 0.167).
Table 15: Diplotypes of identified ALOX5 polymorphism with its corresponding
frequency

ALL
Diplotype Frequency
5CGG 5CGG 0.494
4CGG 5TGG 0.272
5CGG 6CGG 0.066
4CGG 5CGG 0.045
4TGG 4TGG 0.037
5CGG 5TGG 0.021
4CGG 6TGG 0.012
6CGG 6CGG 0.012
5CGG 5CAG 0.008
4CGG 4CGG 0.008
3TGA 5CGG 0.004
5CGG 7CGG 0.004
4TGG 5CGG 0.004
3CGG 4TGA 0.004
4CGG 5TAG 0.004
4CGG 4TGG 0.004

A little less than 50% of the Asian Indian case-control cohort was
homozygous for the 5CGG haplotype (0.494; Table 15) and a further 42.8% were
heterozygous, of which 30.5% also possessed a second haplotype containing the 5-
repeat allele of the ALOX5P (underlined; Table 15). Around 30% of the individuals
were heterozygous for the 4CGG and 5TGG haplotypes (0.272) and just about 7%
were heterozygous for the 5CGG and the 6CGG haplotypes (0.066; Table 15).

57
4.2 Discussion
Analysis of ALOX5P in the Asian Indian CAD case-control cohort showed
five alleles, of which the five Sp-1 binding site repeats-allele had the highest
frequency of 0.722 (Table 14). This was followed by the allele with four Sp-1
binding site repeats at a frequency of 0.222, and the other alleles accounting for the
remaining 0.057. 49.4% of the individuals were homozygous for the common allele
containing five Sp-1 binding site repeats. These results were consistent with those
obtained with the larger cohort sampled for population genetics studies (Chapter III).
The allele frequency of the five Sp-1 binding motif was 0.745 (Table 9). The four-
allele frequency was 0.192 and the other alleles accounted for 0.064 (Table 9).

Three coding SNPs have also been identified in the ALOX5 gene (g.20C>T,
g.8322G>A and g.50778G>A) and these appear to be in partial or complete LD with
the alleles of the ALOX5P (personal communication; Dr. H. Allayee). Haplotype
analysis of the four ALOX5 polymorphisms in this Asian Indian case-control cohort
found that there is moderate correlation between one allele of the ALOX5P and one
coding SNP. The minor allele of g.20C>T SNP is moderately correlated with the 4-
allele of the promoter (Table 13). This is consistent with the results obtained in the
larger Asian Indian cohort (Table 8) but, contrastingly there is no significant
correlation in the case-control cohort of the 3-allele and SNP in exon 6 and 5-allele
and SNP in exon 1, as seen in the larger Asian Indian cohort (Table 8). The SNP in

58
exon 6 has an r² value of 0.0 which means that there is no correlation between
changes in the alleles at the ALOX5P and changes in the SNP in exon 6.

We did not find statistically significant evidence for the association of the
ALOX5 locus with CAD in this cohort. This may be due the small size of the cohort
and additional sampling underway in the laboratory will address this issue.
Alternatively, this locus may not play a significant role in CAD in Indians but
additional studies will be required to confirm or refute this possibility.

59
CHAPTER V
Endogamic exogamy in Gujarati Patels of India: Work in progress
Social stratification in India is evident as social classes that are defined by a
number of endogamous groups often termed as j ātis or castes. Within a j āti, there exist
exogamous groups known as gotras, or gols, which refer to the lineage or clan of a person.
Societal rules governing marriage are similar in diverse regions of India. There is typically a
strict definition of the clan, gol or gotra from within which an individual’s mate may be
selected and a sanction against marriage to any individual from within his or her own gotra.
Patels who originate from the state of Gujarat practice this form of “endogamic exogamy.”
Members of a village do not marry anybody from their own village and may only marry an
individual from one of the other villages within a specified group of villages. We have
studied one such group: the Chh Gaam Patels which comprises Patels from six
villages, to determine the number of founders and occurrence of any genetic isolation
due to the endogamic marriage practices. In order to determine the genetic structure
of this group, the lab has previously obtained genotypes at 800 microsatellite loci
and 400 indel loci. My contribution was to obtain genotypes at Y- chromosome
microsatellite and SNP markers to define haplogroups seen in the various
individuals. Haplogroups are defined by patterns seen in the alleles of these slowly
mutating SNP markers. Identification of the Y-chromosome haplogroup can provide
an interesting glimpse into the deep ancestry of one’s paternal line. Genotype
determination on an ABI3100 yields a fragment size for the locus in any given
individual and despite the fact that size standards are used, the size of an amplified
locus determined in two different laboratories can vary and thus, an international

60
nomenclature has been established that is based on the repeat size corresponding to a
fragment size based on genotyping of a common set of samples such as the Human
Genome Diversity or HapMap samples. In this manner, our data can be compared to
Y-chromosome haplogroup data on world-wide populations published by other
laboratories. My role was to determine genotypes for Y-chromosome markers and
translate the genotypes into a repeat number. The microsatellite markers included
loci with di-, tri-, tetra- and sometimes longer nucleotide repeats. These repeat
numbers will be used to obtain haplogroups and carry out haplogroup analysis. The
endogamic exogamy is practiced much more rigorously in the paternal lineage (i.e. it
is more common for a Chh Gaam Patel male to marry a non-Chh Gaam female
(albeit typically a Gujarati Patel from a different exogamic group of 5, 24 or 32
villages, for example). We obtained Unique Event Polymorphisms (UEP) in the non-
recombining portion of the Y chromosome (NRY). UEPs are neutral mutations that
are believed to have arisen just once during human, or population, evolution, and
they are commonly single nucleotide (SNPs) or insertion/deletion (indel)
polymorphisms. When investigating the origins of a population, UEP haplogroups,
or discrete combinations of UEPs, allow for the deconvolution of the paternal
origins. The haplogroups thus obtained will help form a phylogenetic tree which will
enable us to know the origins of our population.

We examined 168 India-born Gujarati male individuals sampled in the
United States. Some males used in this cohort belonged to the same group of the

61
larger Asian Indian language group used to determine allele frequencies in ALOX5
and prostate cancer. Genotypes were obtained at six Y-STR microsatellites and five
biallelic single nucleotide polymorphisms.

For four of the six microsatellites, we found fragment lengths using fragment
analysis as described in the Methods section (Chapter II). Fragment lengths are
obtained based on the number of repeat structures an individual has for the respective
microsatellite. These fragment lengths were used to calculate the repeat numbers
based on calibrated Pakistani Hazara samples from the Human Genome Diversity
Panel (HGDP) (Table 12). The Hazara samples were used as a standard since they
are a part of the HGDP Cell Line Panel, used to obtain knowledge about genetic
structure of modern human populations to aid in obtaining an inference of human
evolutionary history to test the correspondence of predefined groups with those
inferred from individual multilocus genotypes (Cann 2002; Rosenberg, Pritchard et
al. 2002). Repeat numbers will aid in designating haplogroups and only these
haplogroups are used internationally to form the phylogenetic tree to understand
lineage. Hence, these repeat numbers have to be calibrated on international standards
and the Hazara samples have a standard fragment length and corresponding repeat
number, which we can utilize to assign our fragment lengths.
Table 16: Calibration of fragment sizes using Hazara samples

DYS
marker
Number of
alleles Hazara samples Study samples
Fragment size Repeat number Fragment size Repeat number
DYS19 5 alleles 203 16 191 13
207 17 195 14

62
Table 16, Continued
DYS
marker
Number of
alleles Hazara samples Study samples
Fragment size Repeat number Fragment size Repeat number
199 15
203 16
207 17
DYS390 4 alleles 213 23 209 22
221 25 213 23
217 24
221 25
DYS391 3 alleles 285 10 281 9
285 10
289 11
DYS392 5 alleles 250 11 247 10
250 11
253 12
256 13
259 14

For the other two microsatellites, we used male HapMap samples and did
fragment analysis along with the study sample and based on the fragment size
obtained and repeat numbers already present, we calibrated our study samples for
these microsatellites (Table 13).
Table 17: Calibration of fragment sizes using HapMap samples.

DYS
marker
Number of
alleles HapMap sample Study sample
Fragment size(bps) Repeat number
Fragment size
(bps) Repeat number
DYS437 7 alleles 194 14 190 13
191 13.1
192 13.2
194 14
195 14.1
199 15.1
203 16.1
DYS439 6 alleles 254 11 240 7.2
246 9
250 10

63
DYS
marker
Number of
alleles HapMap sample Study sample

254 11
258 12
262 13

We used John Butler’s method of nomenclature for assigning the repeat
numbers (J.M.Butler 2003).

Studies usually involve a different type of Y-chromosome marker known as
SNPs (along with insertions and deletions) which have a much slower mutation rate
than microsatellites. A SNP test would be the only way of identifying one's
haplogroup for certain. However some conclusions can be drawn about haplogroup
classification by looking just at the Y chromosome marker value patterns as
mentioned above. SNaPshot is a recent method used popularly for SNP analysis and
was performed as described in the Methods section (Chapter II). It is also called the
primer extension method. We used it to determine the derived or ancestral allele of
the various SNPs on the Y chromosome. This would also aid to make a phylogenetic
tree along with the microsatellites. Y- chromosome Alu-insertion Polymorphism
(YAP or DYS287), was the first SNP used in Y-chromosome analysis (J.M.Butler
2003). It is present in most Africans, but absent in many European populations
(J.M.Butler 2003). It is called as an insertion-element, since it is either present or
absent in males. If it is present then a fragment of 413bp peaks, or else it peaks at
99bp. The other SNPs are called “M” indicating “marker” and this was a
nomenclature was given by a group of scientists in Stanford (J.M.Butler 2003).
Table 17, Continued

64
When a variation is observed at the marker, the allele is called a “derived allele”
(J.M.Butler 2003). These derived and ancestral alleles also aid in designating
haplogroups. We have a list of five SNPs for which we performed the SNaPshot
reaction and obtained the alleles (Table 18).
Table 18: List of the SNPs and their corresponding alleles

SNPs Allele
YAP Derived Allele of Alu+
M134 Ancestral allele G
M82 Ancestral allele A
M69 Ancestral allele T
M95 Ancestral allele C

These data as well as the microsatellite and mitochondrial genotype data are
being analyzed to determine if the restricted marital practice within the same
geographic region has resulted in limited genetic differentiation and effective
“genetic isolation”. The number of founders and the extent of admixture will also be
determined. Genotyping of the Y-chromosome markers was extremely challenging,
since it is haploid. It has a high dropout rate of nearly 40% at the Marshfield
genotyping facility as compared to the 1-2% rate for autosomal markers.

Some of the Y chromosome microsatellites for which fragment sizes have
been obtained and are in the process of calibration for repeat numbers are: DYS438,
DYS425, DYS426, and DYS393. Haplogroups thus obtained will aid to complete the
phylogenetic tree.

65
CHAPTER VI
Conclusions and future direction:
Although India comprises more than one sixth of the world’s human
population, no large-scale studies on genetic factors that contribute to common
diseases have yet been conducted. Ongoing westernization and the concurrent dietary
and life-style changes have resulted in an alarming rise in the incidence of many
common diseases of complex etiology such as coronary artery disease and type-2
diabetes. The high prevalence of endogamy as well as endogamic exogamy, and
relatively low admixture present in this population distinguishes it from most other
populations presently used in genetic studies as it represents a distinct genetic
background that is largely unaffected by admixture. In some cases, such as coronary
artery disease, Asian Indians exhibit unique characteristics that distinguish them
from the other populations, suggesting that unique causative factors underlie this and
possibly other related disease. Our lab has previously confirmed that the Asian
Indian population can be used as a single population in genetic studies using
microsatellites and in del polymorphisms, despite their strict social and cultural
divisions (Rosenberg, Mahajan et al. 2006). These results support the inclusion of the
Asian Indian population in modern genetic association studies as it appears to exhibit
unique genotype-phenotype correlations that may yield new insights into the
underlying causes of common disease that are not available in other population.

66
Coronary artery disease is considered an important public health problem not
only in the developed countries like the US, but also in developing countries like
India. With changing lifestyle in developing countries like India, particularly in
urban areas, chronic diseases such as CAD are making an increasingly important
contribution to mortality statistics of such countries. This is true even in the absence
of traditional risk factors such as high cholesterol. Even non-smoking vegetarians
under the age of 40 years who exercise regularly are often at high risk. The death
rates from heart disease in the Indian diaspora have been 50% to 300% higher than
Americans, Europeans, Chinese, and Japanese, irrespective of gender, religion, or
social class (EA 2005-2006). During the past 30 years, the average age of a first
heart attack increased by ten years in the U.S., but decreased by ten years in India
(EA 2005-2006). Epidemiological studies over a period of the last 30 years have
identified risk factors, which predispose an individual to coronary atherosclerosis.
The large numbers of studies carried out on the etiology of CAD have improved the
ability to stratify risk in a clinical setting. Hence, to better understand the genetics
underlying coronary artery disease in Asian Indians, we carried out a case-control
study in Asian Indians. We examined the ALOX5 gene which was reported to be
involved in atherosclerosis in other populations (Dwyer, Allayee et al. 2004), but we
did not find statistically significant evidence for the association of the ALOX5 locus
with CAD in this Asian Indian case-control cohort. This may be due the small size of
the cohort and additional sampling underway in the laboratory will address this issue.
Alternatively, this locus may not play a significant role in CAD in Indians but

67
additional studies will be required to confirm or refute this possibility. RNA has been
prepared from cases and a subset of controls (healthy and preferably >70 years of
age) and comparative gene expression analysis planned for the future will guide
additional association studies. In addition, genome-wide association studies which
will soon become the method of choice for disease association studies will also be
conducted in the future.
According to historical data, the rules of endogamy have been followed since
the middle ages in India. It is believed that small clusters might have been created
within the populations. These clusters may share socio-cultural patterns and because
of the close mating system, they might also share the same genetic background. In
the present study, we have initiated studies to determine the genetic structure of a
group practicing endogamic exogamy and the data are being analyzed to determine if
the restricted marital practice within the same geographic region has resulted in
limited genetic differentiation and effective “genetic isolation”. The number of
founders and the extent of admixture will also be determined. These studies will add
to the cumulative picture about genetic variation in India and in its people who span
a significant geographic and linguistic distance, and guide studies aimed at dissecting
the etiology of the many complex diseases that are rising at a burgeoning rate both
within India and in the diaspora.

68
CHAPTER VII
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Appendices

Appendix A:

Prevalence of Common Disease-associated Polymorphisms
in Asian Indians
Trevor J. Pemberton
1
, Niyati U. Mehta
1,3
, David Witonsky
5
, Anna Di Rienzo
5
,
Hooman Allayee
1,2
, David V. Conti
2
,and Pragna I. Patel
1,3,4 *

1
Institute for Genetic Medicine,
2
Department: of Preventive Medicine,
3
Department
of Biochemistry and Molecular Biology, and the
4
Center for Craniofacial Molecular
Biology, Keck School of Medicine, University of Southern California, Los Angeles,
CA.
5
Department of Human Genetics, University of Chicago, Chicago, IL.
* author to whom correspondence should be addressed.
e-mail addresses:
TJP – trevorp@usc.edu
NM – niyatime@usc.edu
DW – dwitonsk@genetics.uchicago.edu
AD – dirienzo@genetics.bsd.uchicago.edu
HA – hallayee@usc.edu
DVC – dconti@usc.edu
PIP
*
– pragna@usc.edu

Keywords: India, genetic polymorphism, common disease.

83
Abstract
Background. Asian Indians display a high prevalence of diseases linked to changes
in diet and environment that have arisen as their lifestyle has become more
westernized. Using 1200 genome-wide polymorphisms in 432 individuals from 15
Asian Indian language groups, we have recently shown that: (i) Indians constitute a
distinct cluster, and (ii) despite the geographic and linguistic diversity of the groups
they exhibit a low level of genetic heterogeneity.
Results. We investigated the prevalence of common polymorphisms that have been
associated with diseases, such as atherosclerosis (ALOX5), hypertension (CYP3A5,
AGT, GNB3), diabetes (CAPN10, TCF7L2, PTPN22), prostate cancer (DG8S737,
rs1447295), Hirschsprung disease (RET), and age-related macular degeneration
(AMD; CFH, LOC387715). In addition, we examined polymorphisms associated
with skin pigmentation (SLC24A5) and the ability to taste phenylthiocarbamide
(TAS2R38), within a cohort of 576 India-born Asian Indians sampled in the United
States. This sample consisted of individuals whose mother tongue is one of 14 of the
23 “official” languages recognized in India as well as individuals whose mother
tongue is Parsi. Analysis of the data revealed that allele frequency differences
between the different Asian Indian groups were small, and many polymorphisms
were found at a frequency similar to those of European and African populations but
not other Asian populations. Interestingly, the frequencies of many of the
polymorphisms were found to differ from that of their associated disease when
compared with trends in other populations. In addition, the ALOX5 g.8322G>A and

84
g.50778G>A, and PTPN22 g.36677C>T SNPs were found to be present in a subset
of the Asian Indian groups. Furthermore, a latitudinal cline was identified both for
the allele frequencies of the SNPs associated with hypertension (CYP3A5, AGT,
GNB3), as well as those associated with the ability to taste phenylthiocarbamide
(TAS2R38).
Conclusions. Although caution is warranted due to the fact that this US-sampled
Indian cohort may not represent a random sample from India, our results support the
inclusion of the Asian Indian population in genetic studies as it appears to exhibit
unique genotype as well as phenotype characteristics that may yield new insights
into the underlying causes of common diseases that are not available in other
populations.

85
Appendix B:
Abstract submitted to American Society of Human Genetics
Meeting, San Diego 2007.

Endogamic-exogamy in Gujarati Patels F. Li
1
, T.J. Pemberton
1
, N. U. Mehta
1,2
, J.
Belmont
2
, C. Tyler-Smith
3
, N.A. Rosenberg
4
and P.I. Patel
1,2
1) Institute for Genetic
Medicine, and Department of Biochemistry and Molecular Biology
2
, University of
Southern California, Los Angeles, CA, 3) Institute for Molecular Genetics, Baylor
College of Medicine, Houston, TX 4) Wellcome Trust Sanger Institute, Wellcome
Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK 5) Department of
Human Genetics, University of Michigan, Ann Arbor, MI.

Social stratification in India is evident as social classes that are defined by a
number of endogamous groups often termed as j ātis or castes. The j ātis themselves
exist among one of the four varnas or classes namely, Brahmin, Kshatriya, Vaishya
and Shudra. Within a j āti, there exist exogamous groups known as gotras, or gols,
and refer to the lineage or clan of a person. Societal rules governing marriage are
similar in diverse regions of India. There is typically a strict definition of the clan,
gol or gotra from within which an individual’s mate may be selected and a sanction
against marriage to any individual from within his or her own gotra. This typically
translates into a surname or gotra endogamy. Thus, while consanguinity is strictly
avoided and there is randomness in mate selection, there is likely degree of gene
flow restriction. Patels who originate from the state of Gujarat practice this form

86
“exogamic endogamy” i.e. members of a village do not marry anybody from their
own village but may only marry an individual from one of the other villages within a
specified group of villages. We have studied one such group: the Chh Gaam Patels
which comprises Patels from 6 villages namely, Dharmaj, Karamsad, Nadiad,
Sojitra, Bhadran and Vaso, and this groups constitutes the largest gol amongst Patels.
In order to determine the genetic structure of this group, we have obtained
genotypes at 800 microsatellite loci and 400 indel loci. Y- chromosome and
mitochondrial haplogroup analysis has also been conducted. These data are being
analyzed to determine if the restricted marital practice within the same geographic
region has resulted in limited genetic differentiation and effective “genetic isolation”.
The number of founders and the extent of admixture will also be determined.

87
Appendix C:

Abstract submitted to American Society of Human Genetic Meeting,
San Diego 2007.

Assessment of genes involved in inflammation in coronary artery disease in
Asian Indians. N.U. Mehta
1,2
, G. Mendoza-Fandino
1,2
, T. J. Pemberton
1
, J.
Hartiala
1
, D. Conti
3
, P. Kotha
4
, H. Allayee
1,3
, and P.I. Patel
1,2
. 1) Institute for Genetic
Medicine, 2) Department of Biochemistry and Molecular Biology, and 3)
Department of Preventive Medicine, University of Southern California, Los Angeles,
CA 4) RICADIA, 5555 Reservoir Drive Suite 309, San Diego, CA
Our long term goal is to identify genetic risk factors underlying coronary artery
disease (CAD) in Asian Indians. The prevalence and severity of CAD in individuals
of Asian Indian origin is four- to five-fold higher when compared to other ethnic
groups. CAD is severe, extensive and follows an apparently much more aggressive
course in Asian Indians than in other ethnic groups. CAD rates are unusually high in
Asian Indian women and natural protection from CAD seen in Caucasian
premenopausal women is apparently not present in Asian Indian women. We have
conducted community-based sampling of Asian Indians with CAD and gender-
matched control Asian Indian subjects >60 y of age without CAD. Blood samples
were collected for serum and plasma chemistries, and for RNA and DNA isolation.
Previous studies have shown an association between the gene encoding arachidonate
5-lipoxygenase (5-LO; ALOX5), the rate-limiting enzyme in the production of
leukotrienes (LTs) and atherosclerosis in various populations. Primarily, deviation
away from the common 5-allele of the ALOX5 promoter microsatellite (ALOX5P)

88
has been associated with an increased risk of atherosclerosis. We initially examined
the prevalence and allele frequencies of the various alleles of ALOX5P in a cohort of
Asian Indians sampled for population genetics studies. Six ALOX5P alleles were
noted in the Asian Indian cohort, with 56.4% of individuals were homozygous for
the common allele of five Sp1-binding site repeats, and 92.5% of individuals had at
least one copy of the common allele, with the remaining 7.5% of individuals having
two variant alleles. This is higher than the 5.96% reported for a cohort of individuals
of mixed-ethnicity, who reported 94.0% of individuals with at least one copy of the
common allele. We are now examining both ALOX5 and other genes in the
inflammatory pathway, including arachidonate 5-lipoxygenase-activating protein and
leukotriene A4 hydrolase, in this case-control cohort and these results will be
presented.

89
Appendix D:

WE NEED YOU…..

We are studying genetic risk factors that
underlie heart disease in the Asian Indian
population. Two types of individuals are
needed for our study.:
- Individuals who have been diagnosed
with heart disease
- Individuals who are greater than 60
years of age that have no history of
heart disease
If you, or anyone you know, is interested
in participating in this study, please
contact us for further information about
this study.
Visit: www.usc.edu/RICADIA for further
information

DID YOU KNOW?

• Asian Indians are affected by heart
disease four to five times more
frequently than those of other ethnic
backgrounds.

• Heart disease in Asian Indians is
commonly more premature and more
severe than in individuals of other
ethnic backgrounds.

• In 5 – 10 years, medicines will be
prescribed based on one’s genetic
background.

• Most large-scale genetic studies on
heart disease have not included
Indians and it is important that
Indians are studied so appropriate
medicines can be designed in the
future.

HAVE YOU OR ANYONE YOU KNOW BEEN
DIAGNOSED WITH HEART DISEASE?

Contact:
Pragna Patel, Ph.D., Professor
USC Institute for Genetic Medicine
2250 Alcazar Street (IGM 240)
Los Angeles, CA 90033. USA.
Phone: (323)442-2751
E-mail: pragna@usc.edu

Purushotham Kotha, M.D.
Medical Director
RICADIA
(Risk intervention in coronary artery disease
in Asian-Indians)
5555 Reservoir Drive Suite 309
San Diego, CA 92120
Phone: (619)229-1995
E-mail: pkotha@heartsmart.info

90
Appendix E:
Coronary Artery Disease in the Indian
population
Principal Investigator: Pragna Patel, Ph.D.
Institute for Genetic Medicine, University of Southern California, Los Angeles, CA
90033
http://www.usc.edu/CADI

PLEASE COMPLETE THIS QUESTIONNAIRE IN FULL
BEFORE SEEING A MEMBER OF STAFF

Full Name (First, Middle, Last):
Address:
Street Apt. # City State
Zip Code
Phone Number: Home: Cellular: Work:
E-mail Address:
Date of Birth (mm/dd/yyyy): / / Sex: Male Female
Religion: Caste:
Mother Tongue:

Year of entry into the United States of America (yyyy):
Name of Your Home City/Village (include state and country):
Name of Fathers Home City/Village (include state and country):
Name of Mothers Home City/Village (include state and country):

Do you have private health insurance? Yes No
If yes, which company, if no, which federal plan are you with:

What diet do you follow? Vegetarian Non-Vegetarian

91
Do you Smoke? Never In the Past, but you have now quit Currently.
If you currently smoke, or have in the past, how many packets per week? 1-3 4-6 10
How many alcoholic beverages do you consume per week? None 1-3 4-6 6+
How many caffeinated beverages do you consume per week? None 1-3 4-6 6+
How affected are you by mosquitoes? Never Slightly Sometimes
Always

Have you been previously diagnosed with any of the following (check all that apply):
Heart Disease Hypertension
High/Low Blood Pressure (delete as appropriate) Palpitations
Atherosclerosis Angina
Heart Attack Stroke
High Triglycerides High Cholesterol
Type-1 Diabetes Type-2 Diabetes
Multiple Sclerosis Psoriasis
Gallstones and/or Pancreatitis Lupus
Erectile Dysfunction Presbycusis

Do you suffer regularly (more than once per week) with any of the following (check all that
apply):
Dizziness / Light-headedness / Fainting Persistent Nausea or Vomiting
Heartburn / Indigestion Anxiety / Depression / Sleep
Problem
Chest Discomfort and/or Pain Heavy Sweating
Shortness of Breath Arthritis
Persistent Headaches / Migraines Joint / Muscle Problem

Are you currently receiving medication for any of the following:
Heart Disease High Cholesterol
High Triglycerides Angina
Liver Problems Kidney Problems
High/Low Blood Pressure (delete as appropriate) Diabetes
Erectile Dysfunction Inflammation

Are you currently taking any other medications? Yes No

92
If yes, which medication(s) and for what condition(s):

.

Do any health conditions run in your family? Yes No
If yes, which condition(s): .

.

Office Use Only:
Lab ID #: Collection Date: / / Collection Location:
Blood (Y/N): Tube Type: Purple Yellow PAXgene Volume (ml): .
Tube Type: Purple Yellow PAXgene Volume (ml): .
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Abstract (if available)

Abstract There are over a billion Asian Indians in the world and they comprise one-sixth of the world's population. One of the major health concerns facing Indians, both those in India and in the diaspora, is the rapid increase in the incidence of common diseases such as heart disease and type 2 diabetes. Until recently, no large-scale population genetics study had included the Asian Indian population.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Mehta, Niyati U. (author)

Core Title Study of genetic variation in Asian Indians -- applications to complex diseases and endogamic exogamy

School Keck School of Medicine

Degree Master of Science

Degree Program Biochemistry and Molecular Biology

Degree Conferral Date 2007-08

Publication Date 07/26/2007

Defense Date 06/26/2007

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag association study,coronary artery disease,endogamy,India,OAI-PMH Harvest,polymorphism,prostate cancer

Place Name India (countries)

Language English

Advisor Patel, Pragna (committee chair), Allayee, Hooman (committee member), Tokes, Zoltan A. (committee member)

Creator Email niyatime@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m678

Unique identifier UC1169329

Identifier etd-Mehta-20070726 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-520960 (legacy record id),usctheses-m678 (legacy record id)

Legacy Identifier etd-Mehta-20070726.pdf

Dmrecord 520960

Document Type Dissertation

Rights Mehta, Niyati U.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu