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Biological Markers for Exposures

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Title: Biological Markers for Exposures


1
Biological Markers for Exposures
  • Epidemiology 243
  • Molecular Epidemiology of Cancer

2
Early Studies
  • MacMahon Geographical correlation of urinary
    estrogen concentrations with cancer of the breast
    (1974)
  • Cole MacMahon Urinary and blood estrogens and
    breast cancer in case-control studies (1969,1982,
    1983)
  • McMichael The relationship between cancer
    mortality and serum cholesterol concentrations
    (1984)

3
Recent Studies
  • Aflatoxins and hepatitis B on liver cancer in a
    cohort study, including measurements of urinary
    metabolites and nucleic acid adducts of aflatoxin
    (Ross, 1992, 1994)
  • The relationship between HPV and cervical cancer
    (Munoz, 1992, Bosch, 1995)

4
Application of biomarkers in Epidemiology
  • Molecular markers can be applied to increase the
    accuracy of measurements
  • of genetic and other acquired susceptibility to
    disease
  • of exposures that may cause or prevent disease
  • of exposures that confound or modify the
    associations between risk and other exposures
  • of disease itself
  • of factors that may determine the outcome of the
    disease such as precursors and stages

5
Application of biomarkers in Epidemiology
  • Biomarkers may also be used
  • to reduce the time interval between the relevant
    exposure and measurement of the putative effect
  • To increase the yield of information on disease
    pathogenesis
  • To increase the cost-effectiveness of
    epidemiological studies. More information is
    gained per unit cost.

6
Biomarker in Epidemiology Biomarkers of
Biological Agents
  • Biological agents associated with chronic
    infection and subsequent development of cancer
    are measured using serological or nucleic acid
    markers.

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Biomarker in Epidemiology Biomarkers of
Biological Agents
  • HPV DNA by PCR-based assays
  • HPV infection is often transient, especially in
    young women so that repeated sampling is required
    to assess persistent HPV infections

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Classification of Cervical Squamous Neoplasia
Dysplasia PapS. CIN scale Bethesda
Normal 1 Normal Normal
Infla. Atypia 2a Infla. atypia Normal
Koilocyt.Atypia 2b Koilocyto a. LG SIL
Mild dysplasia 3 CIN1 LG SIL
Moderate dysp. 3 CIN2 HG SIL
Severe dysp. 3 CIN3 HG SIL
Ca. in situ 4 CIN3 HG SIL
Invasive ca. 5 Invasive ca Invasive ca
17
HPV Testing and Typing
  • HPV infection is the main cause of cervical
    cancer. Transient in women. Only 10-20
    persistent infections are at risk of neoplasia
  • About 70 subtypes, of which 25 are tropic for
    genital tract. Those are subdivided into three
    categories

18
HPV Testing and Typing
  • HPV can be tested and typed by dot blot
    hybridization, southern blot hybridization,
    Hybrid Capture and PCR
  • High sensitivity but relatively low specificity,
    particular among young women
  • HPV typing has great potential as a primary
    screening tool for cervical cancer.

19
Biomarker in Epidemiology Biomarkers of
Biological Agents
  • HBV infection by serological assays.
  • There are serological markers that distinguish
    between past and persistent infections. HBV DNA
    detection in sera further refines the assessment
    of exposure.

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HBV
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Gender distribution among cases and controls
Gender Case N Control N P Value
Male 159 (77.94 )   287(69.16) 0.0221
Female 45 (22.06) 128(30.84)
204 415
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Self-reported hepatitis virus infection type
Hepatitis History Case N Control N Crude OR (95CI) Adjusted OR (95 CI)
No 108(60.34) 354(90.08) 1 1
HAV 16(8.94) 19(4.84) 2.77(1.385.57) 2.67(1.275.60)
HBV 55(30.73) 19(4.40) 11.30(6.2220.5) 14.52(7.3828.6)
HDV 0 (0) 1(0.26)
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The relationship between liver cirrhosis and
liver cancer
Liver cirrhosis Case N Control N Crude OR (95CI) Adjusted OR (95 CI)
No 149(86.6) 355(99.2)
Yes 23 (13.4) 3 (0.8) 18.3(5.4061.8) 22.1(6.1179.9)
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The relationship between HBV vaccine and liver
cancer
HBV vaccine Case N Control N Crude OR (95CI) Adjusted OR (95 CI)
No 157(96.32) 293(86.14) 1 1
Yes 6(3.68) 47(13.9) 0.24(0.100.57) 0.24(0.100.60)
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The distribution of HBsAg among cases and
controls
HBsAg Case N Control N Crude OR (95CI) Adjusted OR (95 CI)
Negative 72(35.29) 312(75.36) 1 1
Positive 132(64.71) 102(24.64) 5.59(3.958.18) 5.06(3.457.43)
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The distribution of anti-HCV among cases and
controls
HBsAg Case N Control N Crude OR (95CI) Adjusted OR (95 CI)
Negative 183(91.04) 403(97.11) 1 1
Positive 18 (8.96) 12 (2.89) 3.49(1.667.33) 3.21(1.467.06)
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Most frequent HBV infection spectrum in cases
and controls
TYPE HBsAg HBsAb HBeAg HBeAb HBcAb Crude OR (95CI) Adjusteda (95CI)
2 - - - - - 1.00 1.00
1 - - - - 0.24 (0.090.63) 0.23 (0.090.61)
3 - - - - 1.00 (0.492.03) 1.02 (0.492.11)

1 - - 4.74 (2.489.06) 3.91 (1.997.66)
2 - - - 8.9 (4.0019.73) 7.68 (3.2318.31)
3 - - 12.50 (4.7832.73) 11.55 (4.1831.90)
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The possible interaction between GSTM1 and
mildewed food
Mildewed food intake GSTM1 Case N Controls N Crude OR(95 CI) Adjusted OR(95CI) Further adjusted OR(95CI)
No Normal 45(25.6) 126(32.9) 1 1 1
Yes Normal 17(9.7) 29(7.6) 1.64(0.823.27) 1.81(0.873.76) 2.69(1.156.30)
No Null 86(48.9) 193(50.4) 1.25(0.821.91) 1.20(0.771.87) 1.38(0.842.25)
Yes Null 28(15.9) 35(9.1) 2.24(1.234.09) 2.67(1.365.23) 4.13(1.859.24)
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The possible interaction between GSTT1 and HBV
HBsAg GSTT1 Case N Control N Crude OR (95 CI) Adjusted OR (95CI) Further adjusted OR(95CI)
No Normal 36(19.0) 146(37.1) 1   1 1
Yes Normal 67(35.3) 54(13.7) 5.03(3.028.39) 4.49(2.637.67) 4.48(2.627.67)
No Null 27(14.2) 150(38.1) 0.73(0.421.26) 0.73(0.411.29) 0.68(0.381.22)
Yes Null 60(31.6) 44(11.2) 5.53(3.259.43) 4.91(2.818.60) 5.04(2.8513.9)
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The interaction between HBsAg and raw water
drinking
Raw water drinking HBsAg Case N Control N Crude OR (95 CI) Adjusted OR (95CI)
No Negative 32(17.30) 184(51.40) 1 1
Yes Negative 30(16.22) 83(23.18) 2.08(1.193.64) 1.84(1.033.28)
No Positive 63(34.05) 63(17.60) 5.75(3.449.60) 5.25(3.049.06)
Yes Positive 60(32.43) 28(7.82) 12.32(6.8622.11) 9.66(5.2217.89)
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The interaction between HBsAg and mildewed food
intake
Mildew food intake HBsAg Case N Control N Crude OR (95 CI) Adjusted OR (95CI)
No Negative 46(24.08) 151(62.13) 1 1
Yes Negative 21(10.99) 52(12.87) 2.20(1.214.00) 2.47(1.324.63)
No Positive 97(21.53) 87(21.53) 6.08(3.979.33) 5.41(3.468.45)
Yes Positive 27(14.14) 14(3.47) 10.52(5.1321.58) 10.82(5.0922.98)
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The interaction between HBsAg and alcohol drinking
Alcohol drinking HBsAg Case N Control N Crude OR (95 CI) Adjusted OR (95CI)
No Negative 34(17.71) 157(38.20) 1 1
Yes Negative 35(18.23) 153(37.23) 1.06(0.631.78) 1.06(0.562.00)
No Positive 53(27.60) 70(36.46) 5.00(2.928.54) 4.36(2.477.68)
Yes Positive 49(11.92) 52(12.65) 6.22(3.7110.41) 6.19(3.1312.25).
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The interaction between HBsAg and anti-HCV
Anti-HCV HBsAg Case N Control N Crude OR (95 CI) Adjusted OR (95CI)
No Negative 63(31.19) 304(73.08) 1 1
Yes Negative 6(2.97) 10(2.40) 2.90(1.028.26) 2.63(0.887.85)
No Positive 120(59.41) 100(24.04) 5.79(3.968.46) 5.20(3.497.76)
Yes Positive 13(6.44) 2(0.48) 31.37(6.91 42.44) 23.99(5.09 13.12)
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The interaction between HBsAg and family history
of liver cancer
Anti-HCV HBsAg Case N Control N Crude OR (95 CI) Adjusted OR (95CI)
No Negative 58(28.29) 284(68.27) 1 1
Yes Negative 14(6.83) 30(7.21) 2.285(1.414.58) 2.33(1.134.81)
No Positive 94(45.85) 93(22.36) 4.95(3.317.40) 4.52(2.966.92)
Yes Positive 39(19.02) 9(2.16) 21.22(9.7546.19) 24.14(10.34 6.35)
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Multivariate Logistic Regression Analysis
Selected Variables OR ( 95CI )
Age 0.95 (0.930.98)
Gender 1.71 (0.803.65)
Education 0.56 (0.380.82)
Mildewed food intake 2.64 (1.394.99)
Refrigerator using at home 0.30 (0.130.68)
Raw water drinking 1.19 (0.652.19)
Pack-year of smoking 1.00 (0.981.03)
Alcohol drinking 1.38 (0.722.62)
Characteristics
optimistic 0.40 (0.230.69)
Depressed 4.35 (1.4113.45)
Family history of liver cancer 4.81 (2.419.60)
HBsAg 6.93 (4.0711.78)
Anti-HCV 3.49(1.1011.07)
GSTM1 1.87 (1.093.21)
GSTT1 0.72 (0.431.21)
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Major Risk Factors for Stomach Cancer in Chinese
Population
  • Helicobacter pylori was the first bacterium to be
    officially recognized as a cancer-causing agent.

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Major Risk Factors for Stomach Cancer in Chinese
Population
  • Helicobacter pylori Infection. Nitrates and
    nitrites are substances commonly found in cured
    meats, some drinking water, and certain
    vegetables, that can be converted by Helicobacter
    pylori, into compounds that have been found to
    cause stomach cancer in animals.

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Figure 1a H.pylori and gastric cancer -
Prospective studies meta-analysis of non cardia
cancer cases.
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Figure 1b H.pylori and gastric cancer -
Prospective studies meta-analysis of cardia
cancer cases.
53
H. Pylori Infection and Stomach Cancer in Whites
at MSKCC
  • H. Pylori case/control OR
  • no 69/54 1.00
  • yes 67/15 3.50 (1.80-6.79)
  • Infection rates
  • 21.7 in controls
  • 49.3 in cases

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Biomarker in Epidemiology Biomarkers of Internal
Dose
  • Biomarker of internal dose of external chemical
    exposures are measurements of a parent compound
    or its metabolites in an accessible biological
    matrix, such as serum or urine

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Biomarker in Epidemiology Biomarkers of Internal
Dose
  • The half-life of the external agent or its
    metabolites in the body
  • The pattern of the exposure it is measuring
    (regular exposure or infrequent exposure)
  • Whether the secular trends have occurred in that
    exposure (e.g., smoking cessation)
  • Direct or indirect influence of the disease

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Urine Test Kit for Tobacco Use
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Marker for Internal Dose
  • Fat-soluble substance such as DDT metabolites
  • Persist over time
  • Will not be affected by disease status

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DDT
  • DDT (dichlorodiphenyltrichloroethane) is a
    commercial organochlorine insecticide that has
    been used in countries around the world. It has
    been used widely on agricultural crops as well as
    for "vector control" - the control of insects
    that carry such diseases as malaria and typhus

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DDT
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DDT
  • This organochlorine insecticide can be considered
    as the pesticide of the greatest historical
    significance, due to its effect on the
    environment, agriculture, and human health.
  • First synthesized by a German graduate student in
    1873, it was rediscovered by Dr. Paul Mueller, a
    Swiss entomologist, in 1939 while searching for a
    long-lasting insecticide for the clothes moth.

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DDT
  • DDT subsequently proved to be extremely effective
    against flies and mosquitoes, ultimately leading
    to the award of the Nobel Prize in medicine for
    Dr. Mueller in 1948.
  • Effective January 1, 1973 the Environmental
    Protection Agency (EPA) officially canceled all
    uses of DDT, but not before more than 1 billion
    kilograms of DDT had been introduced into the
    United States.

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Biomarker of Dietary Intake
  • Whether it is a good indicator of intake
  • Whether it is a long- or short-term marker
  • Whether there is a need for multiple measurements
  • Whether it is acceptable for researcher and the
    subject
  • Whether it is compatible with study design

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Main component of green Tea Catechins 
(-)-Epigallocatechin gallate ((-)EGCg)
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Adduct as Biomarker
  • Chemicals can bind covalently to cellular
    macromolecules such as nucleic acids and protein.
    The product of this addition of a chemical moiety
    to a macromolecule is termed an adduct

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Adduct as Biomarker
  • Adduct may be highly specific for carcinogen of
    interest, but not necessarily specific for a
    given exposure because of multiple sources of
    carcinogen with environment
  • Adduct formation normally occurs after the
    metabolic activation of the carcinogen DNA
    repair may follow adduct formation

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Adduct as Biomarker
  • The persistent of the adducts is determined by
  • Chemical stability of the adduct itself
  • The turnover of macromolecule to which the
    chemical is bound

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Adduct as Biomarker
  • A half-life of adducts on proteins (HB and
    albumin) a few weeks to months
  • A half-life of DNA adducts a few hours to
    several years depending on cell type concerned

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Adduct as Biomarker
  • Adducts can be measured at
  • Blood
  • Exfoliated cells
  • Tissue
  • Urine (metabolites of adducts)

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Group 1 Carcinogenic to Humans
  • Tobacco Smoking
  • Tobacco Products, Smokeless
  • 4-Aminobiphenyl (4-ABP)
  • Benzene
  • Carmium
  • Chromium
  • 2-Naphthylamine (2-NA)
  • Nickel
  • Polonium-210 (Radon)
  • Vinyl Chloride

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Group 2A Probably Carcinogenic to Humans
  • Acrylonitrile
  • Benzoapyrene
  • Benzoaanthracene
  • 1,3-Butadiene
  • Dibenz(a,h)anthracene
  • Formaldehyde
  • N-Nitrosodiethylamine
  • N-Nitrosodimethylamine

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PHIP DNA Adducts
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P32 postlabeling
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