Materials and Methodology - Shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/22264/11/11... ·...

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45 4. Materials and Methodology The present study is a case-control study aimed to screen the selected candidate genes involved in the aetiology of PCOS. About 280 number of PCOS subjects were ascertained for various epidemiological parameters, while 300 women without PCOS were subjected to molecular study to screen the mutations in TNF-α, PPAR-γ, SHBG, AR, CYP17, FST and ACE genes to conclude their possible role in the causation of the disease and also on their genotype phenotype correlations. 4.1. Subjects and source The samples were obtained from Government Maternity Hospital, Hyderabad after examination by a clinician and later confirmed by proper laboratory investigations. Ultrasound scan of ovaries were obtained for establishing the diagnosis. The samples were collected for duration of three years from July 2008 to December 2011. Inclusion Criteria The patients were selected based on Rotterdam criteria, (ESHRE, 2003) according to which a woman is said to have PCOS, if she has two of three clinical features; menstrual disturbance in the form of oligoammenorhea, hypomenoorhea or polymenorrohea, signs of hyperandrogenism such as acne, alopecia, hirsutism, premature pubarche and polycystic ovaries on ultrasound scan. Exclusion Criteria Women suffering from thyroid, androgen inducing tumors and Cushing‟s syndromes showing similar symptoms as that of PCOS have been excluded from the present study.Age matched ultrasound scanned normal healthy subjects served as controls for the present study. Controls were collected from family planning ward of Government Maternity Hospitals. All the controls subjects were fertile with normal ovaries on USG scan, without menstrual disturbance and with no signs or symptoms of hirsutism. All the control samples were screened for mutations in the genes planned for patient group. 4.1.1. Collection of Data The information from the subjects was collected using a specifically prepared proforma. The parents/relatives accompanying the patients were questioned specifically to obtain all the

Transcript of Materials and Methodology - Shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/22264/11/11... ·...

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4. Materials and Methodology

The present study is a case-control study aimed to screen the selected candidate genes

involved in the aetiology of PCOS. About 280 number of PCOS subjects were ascertained for

various epidemiological parameters, while 300 women without PCOS were subjected to

molecular study to screen the mutations in TNF-α, PPAR-γ, SHBG, AR, CYP17, FST and ACE

genes to conclude their possible role in the causation of the disease and also on their genotype

phenotype correlations.

4.1. Subjects and source

The samples were obtained from Government Maternity Hospital, Hyderabad after

examination by a clinician and later confirmed by proper laboratory investigations. Ultrasound

scan of ovaries were obtained for establishing the diagnosis. The samples were collected for

duration of three years from July 2008 to December 2011.

Inclusion Criteria

The patients were selected based on Rotterdam criteria, (ESHRE, 2003) according to

which a woman is said to have PCOS, if she has two of three clinical features; menstrual

disturbance in the form of oligoammenorhea, hypomenoorhea or polymenorrohea, signs of

hyperandrogenism such as acne, alopecia, hirsutism, premature pubarche and polycystic ovaries

on ultrasound scan.

Exclusion Criteria

Women suffering from thyroid, androgen inducing tumors and Cushing‟s syndromes

showing similar symptoms as that of PCOS have been excluded from the present study.Age

matched ultrasound scanned normal healthy subjects served as controls for the present study.

Controls were collected from family planning ward of Government Maternity Hospitals. All the

controls subjects were fertile with normal ovaries on USG scan, without menstrual disturbance

and with no signs or symptoms of hirsutism. All the control samples were screened for mutations

in the genes planned for patient group.

4.1.1. Collection of Data

The information from the subjects was collected using a specifically prepared proforma.

The parents/relatives accompanying the patients were questioned specifically to obtain all the

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details about the patient‟s menstrual history, clinical symptoms and the details of their family

history with respect to complex diseases. Complete clinical history of each patient and the history

of complex diseases in the members of first and second degree relatives were collected to ensure

that the risk of developing PCOS was extremely high in women with history of complex disease

background.

Epidemiological factors

Information on age, height, weight, waist/hip, dietary habits, menstrual details, obstetrics

and gynecological history, addictions (which include tobacco chewing, smoking, pan) was

collected from the cases and healthy subjects.

Body composition tests

Body composition is one measure of a person‟s overall physical fitness. Obesity is now

recognized as major risk factors for complex disorders like diabetes and cardiovascular problems.

The body mass index (BMI) is the indirect methods to access a person‟s body composition while,

waist to hip ratio (WHR) is another index of body fat distribution.

Body Mass Index (BMI)

The body mass index is a formula to access a person‟s body weight relative to height. It is an

indirect measure of body composition, because it correlates highly with body fat in most of the

people. BMI is calculated by dividing weight in kilograms by height in meters squared (kg/m2).

Studies by the National Center of Health Statistics revealed

BMI values less than 18.5 are underweight

BMI values from 18.5 to 24.9 are normal

Overweight is defined as a BMI of 25.0 to less than 29.9. People with BMIs in this range

have moderate risk of heart and blood vessel diseases.

Obesity is defined as a BMI of 30.0 or greater (based on criteria of World health

Organization). People with BMIs of 30 or more are at high risk of cardiovascular disease.

Extreme obesity is defined as a BMI of 40 or greater.

However, for the present study a value ≥25kg/m2 was considered as overweight/obese. We

considered the WHO criteria of BMI ≥25 to be the cut-off for distinguishing normal form

overweight/obese Indian women to be appropriate. A study by Snehalatha et al., 2003 in South

Indian women employed BMI>23 to be the cut-off for obese cases.

Waist Hip Ratio (WHR)

The WHR is considered a marker for central obesity. Waist circumference was measured

at the midpoint between lower border of the rib cage and the iliac crest. Hip circumference was

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measured at the level of trochanter in cms. Waist hip ratio (WHR) was calculated as waist

circumference divided by hip circumference. A woman with a WHR value of ≥ 0.8 was regarded

to have abdominal obesity.

Genetic Factors

Familial clustering of risk factors is implicated in the aetiopathophysiology of PCOS.

Hence, details regarding the family history of the diseased condition were collected. Pedigrees

were constructed extending over 2-3 generations and the presence of consanguinity in the

families were recorded to propose genetic models and for risk prediction.

4.1.2. Collection of Blood Samples

Blood samples were collected from PCOS subjects as well as from controls into sterile

vacutainers containing EDTA (Ethylene diamine tetra acetic acid) for collecting whole blood for

genomic DNA isolation which was used in molecular studies.

4.2. DNA isolation from blood (Lahari and Nerumbeg, 1991)

DNA is isolated by a rapid non enzymatic method involves salting out the cellular proteins by

dehydration and precipitation with saturated sodium chloride solution.

Equipment: Centrifuge, centrifuge tube, micro pipette, microtips (20-200µl), Water bath (55°C,

37°C), Eppendorfs tubes (1.5ml)

Reagents

5ml of whole blood

TKM1 BUFFER (Tris-10mM, KCl-10mM, MgCl2-10mM, EDTA-2mM)

TKM2 BUFFER (Tris-10mM, KCl-10mM, MgCl2-10mM, EDTA-2mM, NaCl-0.4mM)

Triton-X (1%)

10% SDS (Sodium Dodecyl Sulphate)

6M NaCl (Sodium Chloride)

TE Buffer (Tris HCl-10mM, EDTA-1mM)

PROCEDURE

1. Blood samples are collect in EDTA vacationers (can be stored at 4° c for a long period).

2. Samples are brought to the room temperature for DNA isolation.

3. Take 300µl of blood sample in eppendrof tube add 1000µl of TKM1 and 100µl of Triton

X (1%). Vortex it thoroughly and centrifuge for 10 minutes at 5000 rpm.

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4. Discard the supernatant into disinfectant (1% hypochlorite solution).

5. Repeat step 3 and 4 for 2-3 times or till we get white pellet (complete lysis of red blood

cells).

6. Add 300µl of TKM2 and 100µl of SDS and mix well until the pellet dissolve by using

the micropipette and incubate at room temperature for 30 minutes at 55° C in water bath.

7. After the 30 minutes incubation, take out the eppendorf tubes from the water bath and

add 80-90µl of 6M NaCl, mix well by inversion and centrifuge immediately at 10,000

rpm for 5 min ( to precipitate the proteins; Note- Do not delay the step).

8. Collect the supernatant containing DNA into a fresh eppendorf tube and add double the

volume of ice cold absolute ethanol (Note- Ethanol bottle should be always capped to

prevent evaporation). Invert the tubes several times slowly till the DNA precipitates.

9. Centrifuge the sample for 5 minutes at 10,000 rpm. Discard the supernatant and to the

DNA pellet add 300µl of ice-cold 70% ethanol, centrifuge at 12000 rpm for 5 minutes.

After centrifugation discard the supernatant and air dry the pellet overnight (keep it in

laminar air flow with the eppendorf lid open and covered with tissue paper).

10. Next day resuspend the pellet in 50-60µl of TE buffer and incubate in water bath at 37° C

for 15 minutes till DNA gets dissolved completely and store at -20°C for future use.

4.3. DNA QUANTIFICATION

a. Quantitative analysis

10 µl of DNA sample was diluted to 1ml with sterile deionised water and mixed well. The OD

value of the DNA was recorded at 260nm and 280 nm in a UV spectrophotometer. The readings

were corrected as necessary and the ratio of nucleic acid to protein (260/280nm) were obtained

which is equal to 2.0 for protein free DNA [Sambrook et al., 1989]. However a ratio of 1.8 is

acceptable. The absorbance at 260 nm was used to calculate the concentration of DNA sample.

Concentration of DNA (µg/ml) = OD at 260 X 50 X Dilution factor

b. Qualitative analysis

Qualitative analysis was carried out using 0.8% agarose gel in 1X TBE buffer. 0.56g of

agarose was dissolved in 70ml of 1X TBE buffer and boiled in a microwave oven to dissolve the

contents. The solution was cooled to 40oC and 5µl of ethidium bromide was added and poured

into a pre-arranged mould fitted with a comb. After 15-20 min the comb was removed and the

mould was placed in the electrophoretic unit, filled with 1XTBE buffer and the terminals

connected to the power supply. After 5min of pre-run, 3µl of DNA and 2µl of loading dye were

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loaded into the wells. Electrophoresis was carried out at 100V for 15mins and visualized under

UV transilluminator.

4.4. AGAROSE GEL ELECTROPHORESIS

Agarose gel electrophoresis is a method used in biochemistry and molecular biology to

separate DNA or RNA molecules by size. This is achieved by moving negatively charged nucleic

acid molecules through an agarose matrix with an electric field (electrophoresis). Shorter

molecules move faster and migrate farther than longer ones.

Requirements

Electrophoresis unit, DC power supply, micro pipettes, bromophenol blue, 40% sucrose,

loading dye, ethidium bromide, 1X TBE buffer.

Reagents

Bromophenol blue: To 25mg of bromophenol blue powder add 7ml of distilled water

along with 3ml of Glycerol.

40% Sucrose: 4gms of Sucrose dissolved in 10ml of distilled water.

Loading dye: To 40µl of 40% sucrose add 5µl of bromophenol blue

Ethidium bromide: 5mg of ethidium bromide is dissolved in 1ml of distilled water

(5mg/ml).

Preparation of gel

Gels are cast by melting the agarose with desired volume of buffer until a clear, transparent

solution is achieved. The melted solution is then poured into a mould and allowed to harden upon

hardening; the agarose forms a matrix, when the electric field is applied across the gel.

1. To prepare 1% agarose gel, 0.25gms of agarose powder is mixed with 25ml of

electrophoresis (1X TBE). Then heated in a microwave oven until completely melted.

2. After cooling the solution to about 40°C, ethidium bromide is added; it is poured into a

casting tray containing a sample comb and allowed to solidify at room temperature.

PROCEDURE

1. After the gel has solidified, cover with buffer then the comb is removed, with care not to

rip the bottom of the wells.

2. Samples containing DNA mixed with loading dye are then loaded into the sample wells,

the lid and power leads are placed on the apparatus, and a current is applied (150V for

30min).

3. After electrophoresis the bands were visualized under UV transilluminator.

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4.5. ANALYSIS OF CANDIDATE GENES

Analysis of selected mutations was performed either by using tetra primer ARMS PCR,

PCR-RFLP, PCR-PAGE or by PCR SSCP. The list of the genes studied and the method

employed to carry out the analysis is mentioned below in Table 1.

Table 1: List of gene mutations studied, their location, region and the method employed

Genes Location Polymorphism Method

1 TNF-α -308 Promoter (rs1800629) G > A ARMS PCR

-1031 Promoter (rs1799964) T > C PCR, RFLP (Bbs I)

2 PPAR-γ Exon-2 (rs1801282) C > G PCR, RFLP (BstU I)

Exon-6 (rs3856806) C > T ARMS PCR

3 SHBG Promoter (TAAAA)n PCR, PAGE

Exon-8 (rs6259) G > A ARMS PCR

4 AR Exon-1 (CAG)n PCR, PAGE

Exon-1 (rs6152) G > A ARMS PCR

5 CYP17 -34 Promoter (rs743572) T > C ARMS PCR

Exon-1 (rs6162) C >T PCR, RFLP

6 FST Intron-1 (rs3797297) C > A ARMS PCR

Exon-5 (rs3203788) T > A PCR, RFLP

7 ACE Intron-16 (rs4646994) I/D PCR

4.5.1. DNA repeat polymorphism

Tandemly repeated DNA sequences are widespread throughout the human genome and

show sufficient variability among individuals in a population that they have become important in

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several fields including genetic mapping, linkage analysis and human identity testing. These

tandemly repeated regions of DNA are classified into several groups depending on the size of the

repeat region. Minisatellites (variable number of tandem repeats, VNTR‟s) have repeats with 9-

80bp while microsatellite (short tandem repeats, STR‟s) contain 2-5bp repeats.

Sex Hormone Binding Globulin (SHBG) Gene

The (TAAAA)n VNTR is responsible for located at approximately 800 bp upstream of

the SHBG transcription site in the liver and it has been linked to abnormal plasma SHBG levels

in women with PCOS, age at menarche, chronic heart disease, and semen quality in men. So far,

the identity of the transcription factors that might bind to this region of the SHBG promoter and

information about how variations in this pentanucleotide repeat might influence transcriptional

activity in an in vivo context remain elusive. The present study was made to find the association

of this VNTR variation with hyperandrogenism and PCOS.

PCR Amplification

Amplification was performed with 100ng genomic DNA, 1µl of 10X PCR buffer, 0.1µl

of each (10 pm) primers, 0.3µl of dNTPs (10mM) and 0.3 µl of Taq DNA polymerase (5U/µl) in

a total reaction volume of 10 µl using forward and reverse primers. The PCR products obtained

were subjected to PAGE.

Androgen Receptor (AR) gene

A CAG repeat polymorphism in exon-1 of the AR gene on X chromosome influences the

transactivation of the receptor, resulting variation in androgen activity that could be related to a

number of clinical conditions including PCOS. In view of evidence implicating the importance of

AR in androgen metabolic pathways, we aimed to investigate the involvement of AR gene in the

phenotypic expression of PCOS.

PCR Amplification

Amplification for AR (CAG)n repeats was done with 100ng genomic DNA, 1µl of 10X

PCR buffer, 0.15µl of 10 pmoles primers, 0.3µl of 10mM dNTPs and 0.3µl (5U/µl) Taq DNA

polymerase in a total reaction volume of 10µl using the primers forward and reverse primers. The

PCR products obtained were subjected to PAGE for the identifications of the various alleles as

described for AR (CAG) n repeat polymorphism.

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Table 2: Gene mutations studied, primers, conditions and their product size

Gene/ Region Primers Annealing

Temperatures

Product

Size

SHBG

(TAAAA)n

FP: 5'-GCTTGAACTCGAGAGGCAG-3'

RP:5'-CAGGGCCTAAACAGTCTAGCAGT-3'

65°C

160-195bp

AR

(CAG)n

FP: 5‟-GCTTGAAACTCGAGAGGCAG-3‟

RP: 5‟CAGGGCCTAACAGTCTAGCAGT-3‟

57.5°C

260-320bp

4.5.2. POLYACRYLAMIDE GEL ELECTROPHORESIS FOR SIZE DETERMINATION

Polyacrylamide gel can separate small DNA fragment (5-1000 bp) effectively than agarose gel.

Reagents

1X TBE electrophoretic running Buffer (pH-8)

29:1 W/W acrylamide and bisacrylamide

TEMED (N,N,N,N-tetra methylene diamine)

10% w/v ammonium per sulphate (APS)

10X TBE Buffer (pH-8.3)

Glass plates, spacer and combs to pour gel, DC power supply

PROCEDURE

1. Assemble the gel casting apparatus.

2. Prepare 12% Gel solution (4ml of 5xTBE Buffer, 8 ml of 29:1) acrylamide and

bisacrylamide, 7.3 ml Water, 700 μl APS, 7 μl TEMED. Vigorously agitate the solution

for 1minute.

3. Add 7 μl TEMED and immediately add 700 μl of 10% APS and mix thoroughly, pour the

acrylamide between the Gel plates and insert the comb. Allow the gel to polymerize for

30 seconds.

4. Fill the lower electrophoretic tank with 1x TBE Buffer. Place the Gel to lower tank. A

clamp the gel plate to the upper electrophoretic tank and fill it with 1x TBE Buffer.

5. Use a DC power supply to pre run warm the gel for 30 min at 50 volt.

6. Add 10x Loading Buffer to DNA sample and molecular MW marker and load on to gel.

7. Run the gel at 100 volt/cm, 25c, and taking care to avoid excessive heating. Run the gel

until the desired resolution is obtained, then the gel is silver stained to observe the bands.

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SILVER STAINING (Radojkovic and Kusic, 2000)

Reagents

Fixative: 10% glacial Acetic Acid.

AgNO3: 0.08 gm in 30 ml distilled water.

Developer: dissolve 0.6 gm NaCl in 30 ml distilled water and add 60μl formaldehyde.

Staining Procedure

1. Keep gel in fixative (10% Acetic Acid) for 15 min.

2. Discard fixative and rinse the gel twice with distilled water.

3. Keep the gel in staining solution for 10 min.

4. Rinse gel twice with distilled water.

5. Keep gel in developer till bands develop

6. Observed and interpret result.

4.5.3. Tetra primer-Amplification Refractory Mutation System PCR

(Shu et al., 2001)

ARMS PCR is a simple, effective and economical SNP genotyping method based on

allele specific (AS) primers. This procedure adopts principles of the tetra-primer PCR method and

the amplification refractory mutation system (ARMS). Four primers are required to amplify a

larger fragment from template DNA containing the SNP and two smaller fragments representing

each of the two AS products. Primers are designed in such a way that the amplicons of the alleles

differ in sizes and can be resolved by agarose gel electrophoresis. To enhance the specificity of

the reaction, in addition to the first mismatch at the 3′ end of the AS primers, an external

mismatch is also deliberately introduced at the third position from the 3′ end of each of the two

inner AS primers. From the primer design perspective, two sets of tetra primers for any SNP can

be designed theoretically according to AS primer orientation. Batch Primer 3 implements a batch

module to easily design two sets of tetra-primers for a SNP. In the present study tetra primer

ARMS PCR was employed in order to screen for the selected mutations in the SHBG, AR, TNF-

α, CYP17, PPAR-γ and FST genes.

Equipment

Thermocycler, agarose gel electrophoretic unit, DC power supply and gel documentation unit.

Reagents

10X PCR Buffer, 200µM dNTP‟s, Taq DNA polymerase (5U/µl), primers, template

DNA and sterile water.

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PCR Amplification

PCR amplification was performed with 100ng genomic DNA, 1µl of 10X PCR buffer,

0.15µl of 10 pmoles primers, 0.3µl of 10mM dNTPs and 0.3µl (5U/µl) Taq DNA polymerase in a

total reaction volume of 10µl using 4 sets of primers (outer forward, inner forward, outer reverse

and inner reverse). The primer sequences and PCR conditions are given in Table 2 given below.

Genotyping

10µl of PCR product was run on 2% agarose gel (described earlier) at 150V for 20min to

confirm amplification and type the genotypes (this step is common for all the markers hence not

mentioned again).

Interpretation

Analysis of the amplified DNA generated fragments of various sizes corresponding to

different alleles on electrophoresis. Based on the number of bands and fragment sizes visualized,

the samples were genotyped as homozygotes or heterozygotes for the mutations studied and given

under succeeding section 2.2.4 as gel pictures and figures nos. 3-8.

Table 3: List of primers and conditions for tetra primers ARMS PCR

Gene/

Mutation Primers Annealing Products in bps

TNF-α

-308

G>A

OF: 5′-ATGAAAGAAGAAGGCCTGCC - 3′ OR: 5′- GCACCTTCTGTCTCGGTTTC - 3′ IF: 5′-CAATAGGTTTTGAGGGGCATGA- 3′ IR: 5′-GAGGCTGAACCCCGTCCC - 3′

54°C

GG: 527,369

GA: 527,369,197

AA: 527, 197

PPAR-γ

Exon-6

T > C

OF: 5′-CCATATGTGCTTCCCCAGAC-3′ OR: 5′-GGGTGGGAAACACACAAGAC-3′ IF: 5′-GACAGATTGTCACGGAACAT-3′ IR: 5′-GATCACCTGCAGTAGCTGCACG-3′

54.3°C

TT: 509, 350

TC: 509,350,200

CC: 509, 200

SHBG

Exon-8

G > A

OF: 5′-ACATTGGAAACAGCTCAAGG-3′ OR: 5′-TTACAGGCGRGAGCCACCAC-3′ IF: 5′-CTACCTCCCTCTAGGAGAAA-3′ IR: 5′-GGCAAAAAGAGGTGGAAGAGTC-3′

59.1°C

GG: 614,237

GA: 614,418,237

AA: 614,418

AR

Exon-1

G>A

OF: 5′-CGCTGACCTTAAAGACATCC-3′ OR: 5′-GTATCTTCAGTGCTCTTGCC-3′ IF: 5′-AGCGGGAGAGCGAGGGAG-3′ IR: 5′-AAGTGGGAGCCCCCGAGGCT-3′

55.3°C

GG: 384,296

GA: 384,296,125

AA: 384,125

CYP17)

-34 T>C

OF: 5′-GAGCCCAGATACCATTCGCACTCTGG-3′ OR:5′-GCTTGAAGAAGTTGTTATGCATATGG-3′ IF: 5′-GAGTTGCCACAGCTCTTCTACTCCACC-3′ IR:5′-GGGTGCCGGCAGGCAAGATAGACAGCA-3′

63.2°C

TT: 500,327

TC: 500,327,226

CC: 500,226

FST

Intron-1

C > A

OF: 5′- GTTAACGCTGAAGCAGGGAA-3′ OR: 5′ CAGTGAGCAGCCCATAACTG-3′ IF: 5′-ATAAGTACCTATCTCATAA-3′ IR: 5′-GCAAATATTTCTTGCTAGG-3′

47.8°C

CC: 339,109

CA: 339,267,109

AA: 339, 267

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4.5.4. Restriction Fragment Length Polymorphism

Introduction: Restriction fragment length polymorphism analysis is used to identify a change

in the genetic sequence that occurs at a site called restriction site where restriction enzyme acts.

The variations generated by mutations either create or abolish the recognition sites for these

enzymes. RFLP is a key tool in DNA fingerprinting reflecting the existence of different alleles in

an individual. It provides a valuable marker for tracing the inheritance of the defect and also maps

a genetic disorder.

Principle: The basic technique for detecting RFLP involves fragmenting a sample of DNA by a

restriction enzyme which recognizes and cuts the PCR products whenever a specific restriction

site occurs; in a process called restriction digestion. These sequences are specific to each enzyme

and may be either four, six, eight, ten or twelve base pairs in length. If the recognition site (s) for

the enzyme is/are present, one or more fragments will be generated depending on the number of

sites (n+1 fragments, where n is the number of sites). These fragments separate on electrophoresis

into distinct bands depending on their sizes which can be determined using appropriate marker/

ladder with specific number of base pairs (50/100).

Equipment: Thermal cycler, electrophoretic unit, power supply, water bath.

Steps involved in Restriction Digestion analysis:

1. PCR amplification

2. Restriction Digestion

3. Electrophoresis (AGE or PAGE)

1. PCR Amplification

Amplification was performed with 10ng genomic DNA, 1µl 10X PCR buffer, 0.2µl of

10mM dNTP‟s, 0.1µl each for both forward and reverse primers, 0.2µl of Taq DNA polymerase

(5U/µl) and 7.4µl of sterile water in a total reaction volume of 10µl forward and reverse primers.

The primers and the PCR condition of the genes are given in Table 4.

Table 4: The primers and the PCR conditions for RFLP

Gene/Mutation Primers Annealing Temperature

TNF α -1031

promoter T > C

FP:5′-TATGTGATGGACTCACCAGG-3′ RP:5′-CCTCTACATGGCCCTGTCTT-3′

54°C

PPAR γ Exon 6

C > G

5′-GCC AAT TCA AGC CCA GTC-3′ 5′-GAT ATG TTT GCAGAC AGT GTA TCA

GTGAAG GAA TCG CTT TCC G-3′

53.5°C

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2. Restriction Digestion To 5µl of PCR product 2 U of restriction enzyme (depending on the mutation screened)

was added and incubated overnight at 37°C. The restriction enzyme used, their restriction site and

the effect of mutation on the restriction site is as follows

Table 5: The restriction enzyme used for the mutations studied

Gene Mutation Restriction

Enzyme Restriction site Effect of Mutation

TNF-α -1031 T > C Bbs I

No known function

PPAR-γ Exon-2 C>G BstU I

Missense

3. Agarose Gel electrophoresis: 3% agarose gel (as described earlier) was used for genotyping TNF α -1031 and PPAR γ

mutations.

Interpretation

Based on the number of bands/fragment sizes visualized, the samples were genotyped as

homozygous normal, homozygous mutant and as heterozygous for the mutation screened.

The PCR product size and the number of fragments generated after digestion in

homozygous normal, homozygous mutants and heterozygotes for different mutations planned for

the study are given below.

Table 6: Product sizes of different genotypes obtained after digestion with restriction enzymes

Mutation PCR product

size Homozygous

Normal Heterozygotes

Homozygous Mutants

TNF -1031 251bp 251bp 251, 180,71bp

180,71bp

PPARγ exon-6 270 bp 270bp 270,227,43bp

227,43bp

4.5.5. Single strand conformational polymorphism (Orita et al.,

1989)

SSCP is an electrophoretic separation of single stranded nucleic acid based on subtle

differences in sequence (often a single base pair) that results in a different secondary structure

and a measurable difference in mobility through a gel.

Principle: SSCP is based on the electrophoretic detection of conformational changes in single

stranded DNA molecules resulting from point mutations or other forms of nucleotide changes.

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The principle behind SSCP is that under non-denaturing conditions, single strand DNA fragments

have a folded structure which is specific to the nucleotide sequence of the DNA. Therefore single

strand DNA fragment migrate differently under non-denaturing electrophoretic conditions.

Equipment: Thermal cycler, vertical slab electrophoresis unit, DC power supply,

microcentrifuge, hot water bath.

For PCR: 10X PCR buffer, dNTPs, primers, Taq, sterile water

For PAGE

40% acrylamide solution

10% ammonium per sulphate (APS)

TEMED (N,N,N,N-tetra methylene diamine)

5X TBE (Tris Borate EDTA) buffer

Double distilled water

8-12% non denaturing polyacrylamide gels were used for SSCP. Based on the amplimer

length and mobility of the PCR products, appropriate gel percentage was used.

Table 7: Composition for appropriate gel percentage

Gel Composition 8% 10% 12% 14%

30% acrylamide 8ml 10ml 12ml 14ml

10X TBE 4ml 4ml 4ml 4ml

10% APS 300µl 300µl 300µl 300µl

TEMED 20µl 20µl 20µl 20µl

Double distilled water 27.7ml 25.7ml 23.7ml 21.7ml

Loading Dye 1. 95% Formamide 2. 10mM NaOH 3. 20mM EDTA 4. 0.05% Bromophenol blue 5. 0.05%

Xylene cyanol

Reagents

Acrylamide solution (30%): 29gms of acrylamide and 1g of bisacrylamide are dissolved

in double distilled water and the volume is made up to 100ml.

10X TBE Buffer: 107.8gms Tris base, 55g of boric acid and 7.44 gm of EDTA are added

one after the other and dissolved to 8.3 with boric acid and final volume is made upto 1

liter.

10% APS: 10g APS is dissolved in 100ml of double distilled water.

58

Procedure

The above reagents were mixed in the proportions mentioned above and poured into

sealed glass plates of a vertical PAGE apparatus. The comb was inserted till the gel sets. The

glass plates with the gel were fitted to the PAGE apparatus and given a pre-run for 20mins in 1X

TBE running buffer so that the temperature of the gel reaches to atleast 40oC before loading the

samples.

Sample preparation

Amplified products were mixed with equal volumes of formamide loading buffer

(formamide 0.9 g/ml, 10 mM NaOH, 11 mM EDTA), denatured at 95°C for 10 min and quenched

on ice for 5 min prior to loading. 8 μl of diluted samples were loaded onto 10% non-denaturing

polyacrylamide gel and placed in Consortium electrophoresis unit at 150 Volts and 15 mA current

till the bromophenol blue dye front leaves the gel for about 6-12 hours based on the length of the

product at 25oC. After electrophoresis, band pattern was visualized by silver staining according to

the protocol of Orita et al. On a stained SSCP gel, mobility shift was recognized as an aberrant

band pattern compared to the control sample's band pattern.

Silver Staining

Requirements

Fixative solution

10% alcohol 50ml methanol

0.5% acetic acid 2.5 ml

Made upto 500ml with distilled water

Silver nitrate solution: 150mg silver nitrate dissolved in 300ml of distilled water

Developer: 15ml NAOH, 3ml formaldehyde made upto 1000ml with distilled water.

Procedure

1. The gel was removed from the buffer tank, the glass plates and spacer were disassembled.

2. The gel was transferred to a clean staining tray using gloves and washed with wash

solution for 30′.

3. The wash solution was discarded and the gel was incubated in silver nitrate solution for

10′.

4. The silver nitrate solution was then poured off the gel was rinsed with triple distilled

water for 20s.

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5. Water was then discarded and the gel was rinsed with little amount of developer solution

until a black precipitate was formed and then discarded.

6. The remaining developer solution was poured into the staining tray and the gel was

stained with constant shaking until the bands were visualized.

7. The developer solution was discarded and the staining was stopped by leaving the gel in

fixing solution for 10′.

8. The gel was photographed and the results were recorded in gel documentation system.

Interpretation:

The samples were genotyped as homozygous mutant when there was a shift in mobility

of both the bands of the patient sample in comparison to the control samples and as heterozygotes

when 3 or 4 were present. The exact nature of the mutation was then confirmed by sequencing.

Table 8: List of primers and conditions for SSCP

Gene/Mutation Primers Annealing Products in bps

CYP17

rs6162

5′-CAT-TCG-CAC-TCT-GGA-GTC-3′ 47.9° C 232

3′-AGG-CTC-TTG-GGG-TAC-TTG-5′

FST

rs3203788

FP: 5′-CTCATCACAGATGTATTATA-3′ 52° C 284

RP: 5′-GGCAGCAAGGTTAAAAATCG-3′

4.6. DNA Sequencing

It is a process of determining the nucleotide order of a given DNA fragment. Due to lack

of facilities for sequencing in the lab, all the sequencing reactions were done through

commercial sources. The sequences were interpreted using Finch/ chromas software.

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1.2.4 GEL PICTURES

Figure 17: Gel picture showing genotypes and sequence analysis of TNF-α -308 G>A polymorphism using forward primer

TNF-α -308 GG genotype

TNF-α -308 GA genotype

TNF-α -308 AA genotype

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Figure 18: Gel picture showing genotypes and sequence analysis of TNF-α -1031 T>C using forward primer

TNF-α -1031 TT genotype

TNF-α -1031 TC genotype

TNF-α -1031 CC genotype

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Figure 19: Gel picture showing genotypes and sequence analysis of PPAR-γ exon-2 polymorphism of using forward primer

PPAR-γ exon-2 CC genotype

PPAR-γ exon-2 CG genotype

PPAR-γ exon-2 GG genotype

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Figure 20: Gel picture showing genotypes and sequence analysis of PPAR-γ exon 6 C>T polymorphism gene using forward primer

PPAR-γ exon-6 CC genotype

PPAR-γ exon-6 CT genotype

PPAR-γ exon-6 TT genotype

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Figure 21: Gel picture showing genotypes and sequence analysis of

SHBG (TAAAA)n polymorphism gene using forward primer

SHBG (TAAAA)n

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Figure 22: Gel picture showing SHBG exon-8 G>A genotypes and sequence analysis of exon-8 G>A polymorphism gene using forward primer.

SHBG exon-8 GG genotype

SHBG exon-8 GA genotype

SHBG exon-8 AA genotype

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Figure 23: Gel picture showing AR(CAG)n genotypes and sequence of the region containing

18 CAG repeats

AR (CAG)n repeats

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Figure 24: Gel picture showing AR exon-1 G>A genotypes and sequence analysis of AR exon-1 polymorphism gene using forward primer.

AR exon-1 GG genotype

AR exon-1 GA genotype

AR exon-1 AA genotype

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Figure 25: Gel picture showing CYP17 -34 T>C genotypes and sequence analysis of -34 polymorphism gene using forward primer.

CYP17 -34 TT genotype

CYP17 -34 TC genotype

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CYP17 -34 CC genotype

Figure 26: Gel picture showing CYP17 exon-1 C>T genotypes and sequence analysis of exon-1 polymorphism gene using forward primer.

CYP17 exon-1 CC genotype

CYP17 exon-1 CT genotype

CYP17 exon-1 TT genotype

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Figure 27: Gel picture showing FST intron-1 C>A genotypes and sequence analysis of FST intron-1 polymorphism gene using forward primer.

FST intron-1 CC genotype

FST intron-1 CA genotype

FST intron-1 AA genotype

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Figure 28: Gel picture showing FST exon-5 T>A genotypes and sequence analysis of FST exon-5 polymorphism gene using forward primer.

FST exon-5 TT genotype

FST exon-5 TA genotype

FST exon-5 AA genotype

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Figure 29: Gel picture showing ACE I/D genotypes

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4.7. Data Analysis The epidemiological and molecular data generated in the present study was analyzed

using SPSS software (version 17.0) and online statistical tools. The various statistical methods

employed in analysis are mentioned below.

4.7.1. Descriptive Statistics

Descriptive statistics describes the main features of a collection of data. It provides

simple summaries about the sample and about the observations that have been made. This forms

the basis of the initial description of the data for a particular investigation. It appears in the form

of a table giving the overall sample size, subgroups sample size demographic or clinical

characteristics. Body mass index (BMI), waist hip ratio (WHR) and age at onset (AAO) was

expressed as mean (X) ± standard deviation (SD).

4.7.2. Test of Significance

Online test of significance calculator (http://graphpad.com/quickcalcs/ttest1.cfm) was

used for drawing conclusions. It is used for comparisons of sample mean with population mean,

two sample means, sample proportion with population proportion or comparison of two sample

proportions by using either t-test or Z-test. A p-value of <0.05 was considered to be statistically

significant.

4.7.3. Chi-square test (Preacher KJ, 2001)

The differences in the distribution of categorical and continuous variables between

patient and controls and within the patients group were calculated using chi-square test. Online

chi square calculator (www.quantpsy.org/chisq/chisq ) was used for analysis. The greater tested the

difference between the two percentages in the two categories will be reflected in higher values of

chi-square. A chi-square incorporating Yates correction for continuity was used as this correction

is often employed to improve the accuracy of the null condition sample distribution of chi-square.

4.7.4. Relative Risk Estimation (Odds Ratio)

The Odds ratio describes the strength of association or non-independence between two

groups and it is generally computed for case control study. The odds for exposure among cases

and controls are computed as Odds ratio which provides fairly accurate estimate of relative risk. It

was calculated by using an online statistical tool (http://www.vassarstats.net/odds2x2.html). The

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results are displayed along with OR value, confidence interval (CI) and a p-value. The CI will

provide the range within which the OR value lie. Its value ranges between 0 and infinity. A value

close to 1 indicates no difference between the patient and control. Values less than 1 suggest a

protective role while values greater than 1 suggests predisposing effect.

4.7.5. Allele and Genotype frequencies

Allele and genotype frequencies are calculated using Hardy Weinberg calculator (Court

Lab www.tufts.edu). Allele frequency is the proportion of all copies of a gene that is made up of a

particular gene variant. It can be expressed as fraction or percentage. Allele frequencies are used

to depict the amount of genetic diversity at the individual, population and species level.

p = 2 X No. of Homozygotes (Wild type) + No. of heterozygotes

2 X Total No. of individuals

Genotype frequency = No. of individual (given genotype)

Total No. of individuals

Where p and q are allelic frequencies. Allele and genotype frequencies always sum to

less than or equal to one. Genotype frequency in a population is the number of individuals with a

given genotype divided by the total number of individuals in a population.

4.7.6. Step-wise Multiple Logistic Regression Analysis

Step-wise Multiple Logistic Regression analysis was performed by using SPSS (17th

version). It relates the proportion of a dependent variable to an independent variable. Maximum

likelihood method was used to fit a regression line to log-transferred data rather than the least

squares method. Logistic regression is useful to predict the presence/absence of a characteristic/

outcome based on values of a set of predictor variables. It is well suited to models where the

dependent variables are dichotomous. Logistic regression coefficient can be used to estimate odds

ratio for each of the independent variables in the model. For each variable in the equation, logistic

regression computes a coefficient (beta), standard error, Wald statistic, odds ratio confidence

intervals for odds ratio, log likelihood terms. In the present investigation, stepwise logistic

q = 2 X No. of Homozygotes (Mutant type) + No. of heterozygotes

2 X Total No. of individuals

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regression was used to evaluate the association of epidemiological and genetic variables with

PCOS. Presence/absence of PCOS was considered as dependent variable, dichotomous

independent variables were considered as categorical variables with coding 1 for presence and 0

for absence. Absence of an outcome/factor was taken as reference category. Independent

variables that were entered into the equation (at p<0.05) were considered as predictor variables

for PCOS.

4.7.7. Haplotype analysis and Linkage disequilibrium Estimation

Haploview (http://www.broad.mit.edu/mpg/haploview/contact.php) is a software package

that provides computation of linkage disequilibrium statistics and population haplotype patterns

from primary genotype data in a visually appealing and interactive interface. Haploview

generates marker quality statistics, Linkage disequilibrium (LD) information, haplotype blocks,

population haplotype frequency and single marker association statistics. Haploview calculates

several pair-wise measures of LD, which it uses to create a graphical representative. Haploview

analyses family/ case-control based data and the program uses a two marker expectation-

maximization (EM) ignoring missing data to estimate the maximum likelihood values of the four

gamete frequencies, from which the D‟, LOD and r2 calculations can be derived. Each square

displays the amount of LD between a pair of markers. LD is the non-random association of alleles

at two or more loci; not necessarily on the same chromosome. The strength of LD between two

markers is given by the intensity of color of the box. In crossing areas multiallelic D‟ value

corresponds to the level of recombination between two blocks. LD ranges from 0 to 100 which

are denoted as D‟ (ranges from 0 to 1) value 1 indicates no evidence of recombination between

the two blocks and D‟ value 0 indicates maximum amount of recombination between two blocks.

4.7.8. Gene-gene interactions using Multifactor Dimensionality

Reduction (MDR)

MDR is a data mining strategy for detecting and characterizing non-linear interactions

among discrete attributes (e.g. SNPs, gender etc) that are predictive of a discrete outcome [e.g.

case-control status]. The MDR software combines attributes selection; attributes construction

classification with cross-validation to provide a powerful approach to modeling interactions.

MDR is a non-parametric and model-free method alternative to logistic regression for deducting

and characterizing non-linear interactions among discrete genetic and environmental attributes

(Moore et al., 2006). In the present study MDR software package (version 2.0 beta 8.4) was used

for deducting gene-gene interactions in PCOS with respect to susceptibility in a case-control data.

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This method is based on a multi-locus and multi gene approach consistent with the nature of

complex - trait disease. There is a possibility that the gene and other parameters showing

association with a disease may be functionally related with the pathogenesis of the condition.

Alternatively, these genes may act as good markers to study the disease causing genes lying in

their neighborhood. The data generated in the present study may throw light on these aspects.

Thus the study aimed also as potential for predictive and preventive approaches that can be used

in the management of the condition.

4.7.9. Insilico Analysis

An SNP prediction algorithm polymorphism phenotyping (polyphen-2) was used to

predict the effect of the selected mutations on protein function in the present study.

4.7.9.1. Polyphen-2

Polyphen-2 is an automated tool for prediction of possible impact of an amino-acid

substitution on the structure and function of a human protein. This prediction is based on a

number of features comprising the sequence, phylogenetic and structural information

characterizing this substitution. The amino acid replacement may be incompatible with the

spectrum of substitutions observed in the family of homologous proteins. Polyphen-2 identifies

homologues of the input sequence via BLAST search in the uniref100 database. The set of

BLAST hits is filtered to retain its hits that have:

Sequence identity to the input sequence in the range 30-94%, inclusively, and

Alignment with the query sequence not smaller than 75 residues in length.

Sequence identity is defined as the number of matches divided by the complete alignment

length. The resulting multiple alignment is used by the PSIC software (position-specific

independent counts) to calculate the so-called profile matrix. Elements of the matrix (profile

scores) are logarithmic ratios of the likelihood of given amino acid occurring at a particular

position to the likelihood of this amino acid occurring at any position (back ground frequency).

Polyphen-2 computes the difference between profiles scores of both allelic variants in the

polymorphic positions. Big positive values of this difference may indicate that this study

substitution is rarely or never observed in the protein family. Polyphen-2 also shows the number

of aligned sequence at the query position. This no. may be used to assess the reliability of profile

score calculations.

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Polyphen-2 predicts the functional significance of an allelic replacement from its

individual features by Naive Bayes classifier trained using supervised mention-learning. For a

mutation, Polyphen-2 calculates Naive Bayes posterior probability that this mutation is damaging

and reports estimates of false positive rate (FPR), the chance that the mutation is classified as

damaging when it is in fact non-damaging and true positive rate (TPR), chance that the mutation

is classified as damaging when it is indeed damaging). A mutation is also appraised qualitatively,

as benign, possibly damaging or probably damagingly based on pairs of false positive rates

(FPR threshold). Mutations with their posterior probability score associated with estimated false

positive rates at or below the first (lower) FPR value are predicted to be probable damaging

(more confident prediction). Mutations with the posterior probability scores associated with false

positive rates at or below that second (higher) FPR value are predicted to be possible damaging

(less confident prediction). Mutations with estimated false positive rates above the second

(higher) FPR value are classified as benign. If the lack of data does not allow making a prediction

then the outcome is reported as unknown (Adzhubei et al.,2010).

4.7.9.2. Functional significance of SNP’s using FASTSNP

FASTSNP stands for functional analysis and selection tool for single nucleotide

polymorphism. The online tool FASTSNP [Yuan et al., 2006] was used to determine the impact

of all the SNP‟s analyzed in this study. FASTSNP can be used to determine the impact of the

synonymous SNP‟s, UTR region SNP‟s and intronic SNP‟s. The FASTSNP server

(http://FASTSNP.ibms.sinica.edu.tw/) follows the decision tree principle with external web

service access to transcription factor search which predicts whether a non-coding SNP alters the

transcription factor binding site of a gene. By accessing a variety of heterogeneous biological

databases and analytical tools, FASTSNP is able to identify SNP„s most likely to have functional

effects such as changes to the transcriptional level and pre-mRNA splicing. The score is given on

the basis of levels of risk with a ranking of 0, 1, 2, 3, 4, 5. This signifies the levels of no, very

low, low, medium, higher and very high effect respectively.