<?xml version='1.0'?>
<!DOCTYPE art SYSTEM 'http://www.biomedcentral.com/xml/article.dtd'>
<art>
	<ui>bcr1320</ui>
	<ji>BCJ</ji>
	<fm>
		<dochead>Commentary</dochead>
		<bibl>
			<title>
				<p><it>CYP17 </it>and breast cancer: no overall effect, but what about interactions?</p>
			</title>
			<aug>
				<au id="A1" ca="yes">
					<snm>Little</snm>
					<fnm>Julian</fnm>
					<insr iid="I1"/>
					<email>jlittle@uottawa.ca</email>
				</au>
				<au id="A2">
					<snm>Simard</snm>
					<fnm>Jacques</fnm>
					<insr iid="I2"/>
				</au>
			</aug>
			<insg>
				<ins id="I1">
					<p>Canada Research Chair in Human Genome Epidemiology, Department of Epidemiology and Community Medicine, University of Ottawa, Ontario, Canada</p>
				</ins>
				<ins id="I2">
					<p>Canada Research Chair in Oncogenetics, Cancer Genomics Laboratory, Oncology and Molecular Endocrinology Research Center, CHUQ Research Center and Laval University, Quebec, Canada</p>
				</ins>
			</insg>
			<source>Breast Cancer Research</source>
			<issn>1465-5411</issn>
			<pubdate>2005</pubdate>
			<volume>7</volume>
			<issue>6</issue>
			<fpage>238</fpage>
			<lpage>242</lpage>
			<url>http://breast-cancer-research.com/content/7/6/238</url>
			<note>See related research articles by Verla-Tebit et al (<url>http://breast-cancer-research.com/content/7/4/R455</url>), Chang et al (<url>http://breast-cancer-research.com/content/7/4/R513</url>) and Einarsdottir et al (<url>http://breast-cancer-research.com/content/7/4/R890</url>).</note>
			<xrefbib>
				<pubidlist><pubid idtype="pmpid">16280038</pubid><pubid idtype="doi">10.1186/bcr1320</pubid>
				</pubidlist></xrefbib>
		</bibl>
		<history>
			<pub>
				<date>
					<day>20</day>
					<month>9</month>
					<year>2005</year>
				</date>
			</pub>
		</history>
		<cpyrt>
			<year>2005</year>
			<collab>BioMed Central Ltd</collab>
		</cpyrt>
		<abs>
			<sec>
				<st>
					<p>Abstract</p>
				</st>
				<p>Three large studies published in recent issues of <it>Breast Cancer Research </it>reported no overall evidence of an association between the <it>CYP17 </it>5'-untranslated region <it>Msp</it>A1 polymorphism and breast cancer. The present commentary briefly highlights a few important observations and discusses some additional approaches to further assessment of associations between <it>CYP17 </it>common variants and breast cancer risk. In particular, the evolution of evidence on breast cancer and the <it>CYP17 Msp</it>A1 variant suggests that determination of possible interactions between gene variants postulated to influence risk and nongenetic risk factors would be more efficiently accomplished by pooled analyses, ideally involving all studies of breast cancer, than by attempting to synthesize published information. Furthermore, such analyses would also be relevant to investigation of potential gene&#8211;gene interactions between <it>CYP17 </it>and other common variants in genes encoding enzymes that are involved in the synthesis and inactivation of sex steroid hormones, preferably using optimal sets of single nucleotide polymorphisms.</p>
			</sec>
		</abs>
	</fm>
	<bdy>
		<sec>
			<st>
				<p>Introduction</p>
			</st>
			<p>The importance of hormonal factors in the aetiology of breast cancer and its response to treatment are firmly established, and so it would be expected that factors that modulate hormonal exposure will modify risk. However, in three recent large studies of breast cancer <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp> there was no overall evidence of association with the <it>CYP17 </it>5'-untranslated region <it>Msp</it>A1 polymorphism, which is in contrast to some earlier work. This polymorphism has been of interest to breast cancer investigators because the enzyme encoded by the gene, namely cytochrome P450c17, functions at key branch points in steroid hormone biosynthesis. Human P450c17 predominantly catalyzes the formation of the precursor dehydroepiandrosterone (DHEA), which is converted into androgens and/or oestrogens in the ovary and in peripheral intracrine tissues (e.g. breast, bone, skin and adipose tissue) through tissue-specific enzymatic pathways <abbrgrp><abbr bid="B4">4</abbr><abbr bid="B5">5</abbr><abbr bid="B6">6</abbr></abbrgrp>. Current evidence does not support the involvement of this polymorphism in <it>CYP17 </it>transcriptional regulation <abbrgrp><abbr bid="B7">7</abbr><abbr bid="B8">8</abbr><abbr bid="B9">9</abbr></abbrgrp>. Whereas the <it>CYP17 Msp</it>A1 genotype has been found to be associated with circulating oestrogen levels in premenopausal women in some studies <abbrgrp><abbr bid="B10">10</abbr></abbrgrp>, in recent large population-based studies <abbrgrp><abbr bid="B11">11</abbr></abbrgrp> no association with oestradiol concentrations in either premenopausal or postmenopausal women was observed, and in postmenopausal women there were no clear associations with circulating levels of oestrogens or androgens <abbrgrp><abbr bid="B12">12</abbr><abbr bid="B13">13</abbr></abbrgrp>. However, because of the limitations of functional assays, there is a strong argument that the primary emphasis should be on epidemiological evidence for its association with breast cancer risk <abbrgrp><abbr bid="B14">14</abbr></abbrgrp>.</p>
		</sec>
		<sec>
			<st>
				<p><it>CYP17 </it>genotype and breast cancer risk</p>
			</st>
			<p>The effects of genetic factors in aetiology might be expected to become stronger with earlier age at onset. The results of previous studies of the association between the <it>Msp</it>A1 variant and breast cancer with earlier age of onset were inconsistent <abbrgrp><abbr bid="B7">7</abbr><abbr bid="B15">15</abbr><abbr bid="B16">16</abbr><abbr bid="B17">17</abbr><abbr bid="B18">18</abbr><abbr bid="B19">19</abbr><abbr bid="B20">20</abbr><abbr bid="B21">21</abbr><abbr bid="B22">22</abbr><abbr bid="B23">23</abbr><abbr bid="B24">24</abbr><abbr bid="B25">25</abbr><abbr bid="B26">26</abbr></abbrgrp>. This may in part be due to differences in study methods. For example, some studies were not population based <abbrgrp><abbr bid="B16">16</abbr><abbr bid="B18">18</abbr><abbr bid="B19">19</abbr><abbr bid="B22">22</abbr><abbr bid="B26">26</abbr></abbrgrp>, which renders them susceptible to the effects of selection bias. In one <abbrgrp><abbr bid="B17">17</abbr></abbrgrp> a substantial proportion of cases was prevalent, which would bias the results if <it>CYP17 </it>genotype influenced survival. The studies differed markedly in size, and so they varied in statistical power to detect an effect.</p>
			<p>The three most recent studies <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp> were population based, and only cases with newly incident disease were included. One included women clearly defined as premenopausal (aged 50 years and under who still had menstrual cycles or who reported natural amenorrhoea for less than 6 months before diagnosis/interview) resident in two regions of southern Germany <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. Data on 527 cases with <it>in situ </it>or invasive disease diagnosed during the period 1992&#8211;1995 were compared with data on 904 control individuals randomly selected from population registers and matched with cases in terms of age and study region. These represent about 80% of individuals on whom interview data had been obtained, and the losses represent the strict application of criteria for selecting women who were premenopausal and genotyping failure. There were no differences between the cases and controls for whom genotype data were available and the total cases and controls interviewed in terms of the distribution of sociodemographic factors or putative risk factors for breast cancer.</p>
			<p>Compared with homozygotes for the A1 allele, the age-adjusted odds ratio (OR) for breast cancer in heterozygotes was 1.02 (95% confidence interval [CI] 0.80&#8211;1.31) and the OR in homozygotes for the A2 allele was 1.18 (95% CI 0.87&#8211;1.61) <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. These estimates were little changed with further adjustment for breast cancer risk factors. Possible effect modification was examined for age at menarche, oral contraceptive use, parity, age at first full-term pregnancy, and breastfeeding status. Such a modification was apparent only for parity, with increased risk among nulliparous women homozygous for the A2 allele.</p>
			<p>The second study <abbrgrp><abbr bid="B2">2</abbr></abbrgrp> included women aged under 60 years diagnosed in Melbourne or Sydney (Australia) during the period 1992&#8211;1999, with stratified sampling of cases so that half were diagnosed at age under 40 years. A total of 2303 (1208 under 40 years old; 1095 aged 40&#8211;59 years) cases with invasive breast cancer were identified from cancer registries <abbrgrp><abbr bid="B27">27</abbr></abbrgrp>. Interviews were completed for 1578 (69%). After excluding women who were not white, cases aged under 40 years in whom <it>BRCA1 </it>and <it>BRCA2 </it>mutations were found (<it>n </it>= 41), and genotyping failures, 1284 cases were included in the analysis <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>. A total of 1531 controls were selected from electoral rolls by proportional random sampling, based on the expected age distribution of cases, of whom 1021 (67%) were interviewed <abbrgrp><abbr bid="B27">27</abbr></abbrgrp>; 679 were included in the analysis. There is overlap with an earlier report <abbrgrp><abbr bid="B15">15</abbr></abbrgrp> on 369 cases diagnosed under 40 years during the period 1992&#8211;1995 and 284 controls. The analysis was stratified by menopausal status.</p>
			<p>In premenopausal women (1043 cases, 529 controls), compared with A1 homozygotes, the OR for breast cancer in heterozygotes was 0.88 (95% CI 0.70&#8211;1.11) and in A2 homozygotes the OR was 1.09 (95% CI 0.79&#8211;1.51) <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>. As in the German study <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>, adjustment for putative risk factors had little effect on these estimates. Thus, the increased risk in A2 homozygotes that was apparent in women aged under 40 years in a report on a subset of these data <abbrgrp><abbr bid="B15">15</abbr></abbrgrp> was no longer detectable. In postmenopausal women (241 cases, 150 controls), the OR for heterozygotes was 1.09 (95% CI 0.70&#8211;1.70) and for A2 homozygotes the OR was 1.23 (95% CI 0.66&#8211;2.31). In view of the finding in the earlier study that the increased risk for A2 homozygotes appeared to be confined to women with a family history of breast cancer in a first-degree or second-degree relative <abbrgrp><abbr bid="B15">15</abbr></abbrgrp>, the overall analysis was stratified by family history, defined as breast cancer in a first-degree relative <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>. Among women with such a family history, the OR associated with homozygosity for the A2 genotype was 2.5; this was not a statistically significant finding. For other possible effect modifications, the authors defined risk categories as in the study conducted by Ambrosone and coworkers <abbrgrp><abbr bid="B20">20</abbr></abbrgrp>, which they considered to be the most comprehensive previous assessment of effect modification. Possible effect modification was examined for age at menarche, oral contraceptive use, age at first birth, use of hormone replacement therapy and age at menopause. No evidence of effect modification was found for premenopausal breast cancer. For postmenopausal women there was a suggestion that the increased risk for breast cancer associated with later age at menopause was confined to women homozygous for the A1 allele.</p>
			<p>The third study <abbrgrp><abbr bid="B3">3</abbr></abbrgrp> was restricted to postmenopausal women resident in Sweden in the period 1993&#8211;1995. Long-term users of menopausal hormones and women with diabetes mellitus were over-sampled. Comparison was made between 1544 cases of invasive breast cancer (73% of potentially eligible cases) identified through cancer registers, and 1502 controls (61% of those potentially eligible) selected from the Swedish Total Population Registry. Compared with A1 homozygotes, the OR for breast cancer in A2 homozygotes was 1.0 (95% CI 0.8&#8211;1.3) and that for heterozygotes was also unity. This lack of association is consistent with most previous studies in which results specific to postmenopausal women were presented <abbrgrp><abbr bid="B21">21</abbr><abbr bid="B22">22</abbr><abbr bid="B23">23</abbr><abbr bid="B24">24</abbr><abbr bid="B25">25</abbr><abbr bid="B26">26</abbr><abbr bid="B28">28</abbr></abbrgrp>, although in studies in Indian <abbrgrp><abbr bid="B27">27</abbr></abbrgrp> and Japanese <abbrgrp><abbr bid="B19">19</abbr></abbrgrp> women the A2A2 genotype was associated with increased risk. This lack of association was also observed when ductal and lobular tumours were analyzed separately. Possible effect modification was examined for menopausal hormone use, age at menarche, age at menopause, age at first birth, parity, and body mass index. Effect modification was apparent only for age at menarche, with A2 homozygotes having an increased risk associated with an early age at menarche and age at menopause, and with A2 carriers having a reduced risk associated with an early age at menopause. Unlike in other studies <abbrgrp><abbr bid="B29">29</abbr></abbrgrp>, age at menarche was not associated with overall breast cancer risk in this study.</p>
			<p>In all three studies <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp> there was more than 80% power to detect an OR of 1.5 or more at the 0.05 level of statistical significance. As noted in the Australian study <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>, detection of departure from multiplicative joint effects requires at least four times the number of subjects than would a study aimed only at detecting the main effects of genotype and another risk factor <abbrgrp><abbr bid="B30">30</abbr></abbrgrp>. Therefore, the lack of consistency between the findings of the Australian study <abbrgrp><abbr bid="B2">2</abbr></abbrgrp> and the much smaller study (96 premenopausal cases and 86 controls; 111 postmenopausal cases and 102 controls) conducted by Ambrosone and coworkers <abbrgrp><abbr bid="B20">20</abbr></abbrgrp> may reflect the play of chance. There is consistency between the German <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> and Australian <abbrgrp><abbr bid="B2">2</abbr></abbrgrp> studies of premenopausal women in the lack of evidence of a differential effect of <it>CYP17 </it>genotype on risk associated with age at menarche, age at first birth, or use of oral contraceptives. The Swedish study <abbrgrp><abbr bid="B3">3</abbr></abbrgrp> of postmenopausal women detected an interaction with age at menarche, which was interpreted as a chance finding. In contrast to the German study <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>, neither the Swedish <abbrgrp><abbr bid="B3">3</abbr></abbrgrp> nor Australian <abbrgrp><abbr bid="B2">2</abbr></abbrgrp> studies showed an increased risk associated with presence of the A2 allele in nulliparous premenopausal women (OR based on crude analysis of data presented in Table 3 in reference <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>, assuming all parous women had age at first birth recorded, heterozygotes and A2 homozygotes combined: 0.94, 95% CI 0.61&#8211;1.46). Crude analysis of the German data <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> suggests that homozygosity for the A2 variant is inversely associated (OR 0.32, 95% CI 0.10&#8211;1.04) with risk for premenopausal breast cancer in women with a family history of the disease in first-degree relatives, which is in contrast to the Australian study <abbrgrp><abbr bid="B2">2</abbr></abbrgrp>.</p>
			<p>In the German <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> and Swedish <abbrgrp><abbr bid="B3">3</abbr></abbrgrp> studies there was no association between <it>CYP17 </it>genotype and stage of breast cancer. This is compatible with most <abbrgrp><abbr bid="B7">7</abbr><abbr bid="B17">17</abbr><abbr bid="B21">21</abbr><abbr bid="B25">25</abbr><abbr bid="B31">31</abbr><abbr bid="B32">32</abbr><abbr bid="B33">33</abbr></abbrgrp> but not all <abbrgrp><abbr bid="B16">16</abbr><abbr bid="B24">24</abbr><abbr bid="B34">34</abbr></abbrgrp> previous studies, in which a variety of definitions of extent of disease were used.</p>
			<p>One previous study <abbrgrp><abbr bid="B23">23</abbr></abbrgrp> suggested that a high intake of lignans &#8211; plant compounds that are metabolized in the gut to produce the phyto-oestrogens enterolactone and enterodiol &#8211; is associated with a more marked reduction in OR for breast cancer in women who have an A2 allele than in A1 homozygotes. A concern is that this joint effect has been investigated in other studies but not reported. It is noteworthy that associations between intake of lignans and breast cancer was reported in a subset of participants in the German study <abbrgrp><abbr bid="B35">35</abbr></abbrgrp>.</p>
		</sec>
		<sec>
			<st>
				<p>Conclusion</p>
			</st>
			<p>In the analyses of breast cancer in younger women, possible interactions between <it>CYP17 </it>genotype and other gene variants affecting the tissue-specific synthesis and metabolism of steroid hormones do not appear to have been investigated. The metabolism of any exposure is likely to depend on the balance between the relative activities of all of the enzymes in the metabolic pathway <abbrgrp><abbr bid="B36">36</abbr></abbrgrp>. This concept is of particular importance bearing in mind the role played by P450c17 in the synthesis of DHEA, a precursor of active androgens as well as oestrogens, which exert opposite effects in breast cancer development <abbrgrp><abbr bid="B5">5</abbr></abbrgrp>. In some studies of breast cancer in general (i.e. not specifically in premenopausal women), suggestions of an interaction with the 17&#946;-hydroxysteroid dehydrogenase type 1 <abbrgrp><abbr bid="B28">28</abbr><abbr bid="B37">37</abbr></abbrgrp> and with <it>CYP1A1 </it>and catechol-<it>O</it>-methyltransferase <abbrgrp><abbr bid="B26">26</abbr></abbrgrp> variants were observed. Pooled analyses would facilitate the investigation of gene&#8211;gene interactions.</p>
			<p>It should also be kept in mind that the determination of the impact of genetic variant(s) on tissue-specific intracellular sex steroid concentrations has inherent limitations, because these levels do not correlate with measurements of circulating sex steroid levels. Indeed, the serum testosterone and oestradiol levels reflect predominantly the contribution of direct sex steroid secretion by the ovaries and/or adrenals <abbrgrp><abbr bid="B5">5</abbr></abbrgrp>. A better approach to estimating DHEA conversion into active androgens and oestrogens would be to measure circulating conjugated metabolites, such as glucuronidated metabolites <abbrgrp><abbr bid="B38">38</abbr></abbrgrp>.</p>
			<p>There has been considerable concern about the potential impact of publication bias on the body of knowledge on gene&#8211;disease associations <abbrgrp><abbr bid="B39">39</abbr><abbr bid="B40">40</abbr><abbr bid="B41">41</abbr></abbrgrp>. The potential for selective publication of results can only increase as a result of the application of a combination of a tremendous expansion in genotyping potential and exploratory statistical analyses in studies with limited sample sizes <abbrgrp><abbr bid="B42">42</abbr><abbr bid="B43">43</abbr><abbr bid="B44">44</abbr></abbrgrp>. This problem is compounded for gene&#8211;environment and gene&#8211;gene interactions because, in addition to the larger number of potential comparisons implicit in the concept of multiple interacting variables, authors face the problem that large tables of gene&#8211;environment interaction estimates are very cumbersome and difficult to assemble in publishable format <abbrgrp><abbr bid="B45">45</abbr></abbrgrp>. This inevitably increases the potential for publication bias.</p>
			<p>Therefore, the publication of the null overall findings on <it>CYP17 </it>5'-untranslated region <it>Msp</it>A1 genotype and breast cancer, and of the effect modifications investigated <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr></abbrgrp> is particularly welcome. Is there a need for further studies of this polymorphism and breast cancer? The accrued evidence does not indicate any substantial overall effect in white populations, but it is insufficient to exclude an effect in other populations. For the latter, integration of evidence across studies will most efficiently be accomplished using systematic review and pooled analysis methods, such as have been applied in human genome epidemiology reviews <abbrgrp><abbr bid="B46">46</abbr></abbrgrp>. Possible interaction with family history and with nongenetic risk factors has been observed in some studies but has not been replicated. Review of the studies on <it>CYP17 </it>illustrates the difficulties of synthesizing evidence on such interactions, notably differences in definition and categorization of variables and in methods of analysis. Pooled analysis, sometimes described as meta-analysis of individual patient data, offers many advantages over the meta-analysis of the results of studies, including consistent determination of subgroup effects, standardization of definitions of cases and variables, and better control of confounding <abbrgrp><abbr bid="B47">47</abbr><abbr bid="B48">48</abbr></abbrgrp>. This approach will be facilitated by the development of networks of investigators researching gene&#8211;disease associations <abbrgrp><abbr bid="B49">49</abbr></abbrgrp>.</p>
			<p>Is there a need for further studies of genetic variation in <it>CYP17 </it>and breast cancer? In single studies, no association has been reported with a G&#8211;A transition in the promoter region in Japan <abbrgrp><abbr bid="B19">19</abbr></abbrgrp> or with the c198t or g255t single nucleotide polymorphisms (SNPs) in England <abbrgrp><abbr bid="B13">13</abbr></abbrgrp>. The two SNPs in the latter study, together with the <it>Msp</it>A1 variant (t34c), tag the three common haplotypes in the coding region <abbrgrp><abbr bid="B50">50</abbr></abbrgrp>. Although the haplotype tagging SNP approach may prove a valuable direction for gene disease&#8211;association studies, there is considerable debate about the optimal strategies for selecting SNPs <abbrgrp><abbr bid="B51">51</abbr><abbr bid="B52">52</abbr><abbr bid="B53">53</abbr></abbrgrp>. In theory, additional genotyping of samples from studies already completed would be an efficient way to confirm the presence or absence of effect, with synthesis of the evidence across studies.</p>
		</sec>
		<sec>
			<st>
				<p>Abbreviations</p>
			</st>
			<p>OR = odds ratio; CI = confidence interval; DHEA = dehydroepiandrosterone; SNP = single nucleotide polymorphism.</p>
		</sec>
		<sec>
			<st>
				<p>Competing interests</p>
			</st>
			<p>The author(s) declare that they have no competing interests.</p>
		</sec>
	</bdy>
	<bm>
		<refgrp>
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					<p><it>CYP17 5'-UTR Msp </it>A1 polymorphism and the risk of premenopausal breast cancer in a German population-based case&#8211;control study</p>
				</title>
				<aug>
					<au>
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				<aug>
					<au>
						<snm>Mitrunen</snm>
						<fnm>K</fnm>
					</au>
					<au>
						<snm>Jourenkova</snm>
						<fnm>N</fnm>
					</au>
					<au>
						<snm>Kataja</snm>
						<fnm>V</fnm>
					</au>
					<au>
						<snm>Eskelinen</snm>
						<fnm>M</fnm>
					</au>
					<au>
						<snm>Kosma</snm>
						<fnm>VM</fnm>
					</au>
					<au>
						<snm>Benhamou</snm>
						<fnm>S</fnm>
					</au>
					<au>
						<snm>Vainio</snm>
						<fnm>H</fnm>
					</au>
					<au>
						<snm>Uusitupa</snm>
						<fnm>M</fnm>
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					<au>
						<snm>Hirvonen</snm>
						<fnm>A</fnm>
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				</aug>
				<source>Cancer Epidemiol Biomarkers Prev</source>
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				<aug>
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						<snm>Hamajima</snm>
						<fnm>N</fnm>
					</au>
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						<snm>Iwata</snm>
						<fnm>H</fnm>
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					<au>
						<snm>Obata</snm>
						<fnm>Y</fnm>
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					<au>
						<snm>Matsuo</snm>
						<fnm>K</fnm>
					</au>
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						<snm>Mizutani</snm>
						<fnm>M</fnm>
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						<snm>Iwase</snm>
						<fnm>T</fnm>
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						<snm>Miura</snm>
						<fnm>S</fnm>
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						<snm>Okuma</snm>
						<fnm>K</fnm>
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						<snm>Ohashi</snm>
						<fnm>K</fnm>
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						<snm>Tajima</snm>
						<fnm>K</fnm>
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						<snm>McCann</snm>
						<fnm>SE</fnm>
					</au>
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						<snm>Moysich</snm>
						<fnm>KB</fnm>
					</au>
					<au>
						<snm>Freudenheim</snm>
						<fnm>JL</fnm>
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					<au>
						<snm>Ambrosone</snm>
						<fnm>CB</fnm>
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						<snm>Shields</snm>
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				<aug>
					<au>
						<snm>Helzlsouer</snm>
						<fnm>KJ</fnm>
					</au>
					<au>
						<snm>Huang</snm>
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						<snm>Strickland</snm>
						<fnm>PT</fnm>
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						<snm>Hoffman</snm>
						<fnm>S</fnm>
					</au>
					<au>
						<snm>Alberg</snm>
						<fnm>AJ</fnm>
					</au>
					<au>
						<snm>Comstock</snm>
						<fnm>GW</fnm>
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					<au>
						<snm>Bell</snm>
						<fnm>DA</fnm>
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				</aug>
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				<aug>
					<au>
						<snm>Haiman</snm>
						<fnm>CA</fnm>
					</au>
					<au>
						<snm>Hankinson</snm>
						<fnm>SE</fnm>
					</au>
					<au>
						<snm>Spiegelman</snm>
						<fnm>D</fnm>
					</au>
					<au>
						<snm>Colditz</snm>
						<fnm>GA</fnm>
					</au>
					<au>
						<snm>Willett</snm>
						<fnm>WC</fnm>
					</au>
					<au>
						<snm>Speizer</snm>
						<fnm>FE</fnm>
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					<au>
						<snm>Kelsey</snm>
						<fnm>KT</fnm>
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						<snm>Hunter</snm>
						<fnm>DJ</fnm>
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				</aug>
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				<aug>
					<au>
						<snm>Huang</snm>
						<fnm>CS</fnm>
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					<au>
						<snm>Chern</snm>
						<fnm>HD</fnm>
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					<au>
						<snm>Chang</snm>
						<fnm>KJ</fnm>
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					<au>
						<snm>Cheng</snm>
						<fnm>CW</fnm>
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						<snm>Hsu</snm>
						<fnm>SM</fnm>
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						<snm>Shen</snm>
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					<au>
						<snm>Chacko</snm>
						<fnm>P</fnm>
					</au>
					<au>
						<snm>Rajan</snm>
						<fnm>B</fnm>
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					<au>
						<snm>Mathew</snm>
						<fnm>BS</fnm>
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					<au>
						<snm>Joseph</snm>
						<fnm>T</fnm>
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						<snm>Wu</snm>
						<fnm>AH</fnm>
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					<au>
						<snm>Seow</snm>
						<fnm>A</fnm>
					</au>
					<au>
						<snm>Arakawa</snm>
						<fnm>K</fnm>
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					<au>
						<snm>Van Den Berg</snm>
						<fnm>D</fnm>
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						<snm>Lee</snm>
						<fnm>HP</fnm>
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						<snm>Yu</snm>
						<fnm>MC</fnm>
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						<snm>Henderson</snm>
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						<snm>Pike</snm>
						<fnm>MC</fnm>
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						<snm>Bernstein</snm>
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						<snm>Ross</snm>
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						<snm>Dite</snm>
						<fnm>GS</fnm>
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					<au>
						<snm>Jenkins</snm>
						<fnm>MA</fnm>
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					<au>
						<snm>Southey</snm>
						<fnm>MC</fnm>
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						<snm>Hocking</snm>
						<fnm>JS</fnm>
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						<snm>Giles</snm>
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					<au>
						<snm>McCredie</snm>
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						<snm>Venter</snm>
						<fnm>DJ</fnm>
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						<snm>Hopper</snm>
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						<snm>Weston</snm>
						<fnm>A</fnm>
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					<au>
						<snm>Pan</snm>
						<fnm>CF</fnm>
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					<au>
						<snm>Bleiweiss</snm>
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						<snm>Ksieski</snm>
						<fnm>HB</fnm>
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					<au>
						<snm>Roy</snm>
						<fnm>N</fnm>
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					<au>
						<snm>Maloney</snm>
						<fnm>N</fnm>
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						<snm>Wolff</snm>
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						<snm>Kuligina</snm>
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					</au>
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						<snm>Togo</snm>
						<fnm>AV</fnm>
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					<au>
						<snm>Suspitsin</snm>
						<fnm>EN</fnm>
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					<au>
						<snm>Grigoriev</snm>
						<fnm>MY</fnm>
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						<snm>Pozharisskiy</snm>
						<fnm>KM</fnm>
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					<au>
						<snm>Chagunava</snm>
						<fnm>OL</fnm>
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						<snm>Berstein</snm>
						<fnm>LM</fnm>
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						<snm>Theillet</snm>
						<fnm>C</fnm>
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						<snm>Hanson</snm>
						<fnm>KP</fnm>
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						<snm>Thorlacius</snm>
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						<snm>Jonasson</snm>
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						<snm>Sigfusson</snm>
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						<snm>Tryggvadottir</snm>
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						<snm>Coetzee</snm>
						<fnm>GA</fnm>
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						<snm>Kolonel</snm>
						<fnm>LN</fnm>
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						<snm>Ross</snm>
						<fnm>RK</fnm>
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						<snm>Linseisen</snm>
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						<snm>Piller</snm>
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					<au>
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						<snm>McKean-Cowdin</snm>
						<fnm>R</fnm>
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					<au>
						<snm>Labrie</snm>
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						<snm>Belanger</snm>
						<fnm>A</fnm>
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						<snm>Candas</snm>
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