Genome-wide association scans for secondary traits using case-control samples.
Genome-wide association scans for secondary traits using case-control samples.
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DOI：
10.1002/gepi.20424
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发表时间：
2009-12
影响因子：
2.1
通讯作者：
Kraft, Peter
中科院分区：
文献类型：
--
作者：
Monsees, Genevieve M.;Tamimi, Rulla M.;Kraft, Peter
关键词：
全基因组关联研究需要相当大的投资，因此研究人员经常研究在同一组对象上收集的多个特征，以实现回报最大化。然而，许多GWAS采用了病例对照设计；不正确地考虑病例对照确证可能导致对标记和次要性状之间的关联的偏颇估计。我们表明，在没有标记-次要性状关联的零假设下，忽略病例对照状态确定或分层的幼稚分析具有适当的I型错误率，除非标记和次要性状都与疾病风险独立相关。在另一种假设下，当次要性状与疾病风险无关时，这些方法是无偏见的。我们还表明，反抽样概率加权(IPW)回归提供了标记-次要性状关联的无偏估计。我们使用仿真来量化朴素方法和IPW方法的I类误差、功率和偏差。IPW回归在我们考虑的所有情况下都有适当的I型误差，但比天真分析的威力要小。如果标记物独立于疾病风险，那么天真分析的偏差很小。考虑到大多数被测试的标记与疾病风险无关，幼稚的分析提供了标记-次要性状关联的有效测试和几乎没有偏见的估计。当有证据表明次要性状和被测试的标记物都与原发疾病相关时，必须小心，我们通过分析FGFR2中的标记物与乳腺癌病例对照样本中乳房X光摄影密度之间的关系来说明这种情况。
Genome-wide association studies (GWAS) require considerable investment, so researchers often study multiple traits collected on the same set of subjects to maximize return. However, many GWAS have adopted a case-control design; improperly accounting for case-control ascertainment can lead to biased estimates of association between markers and secondary traits. We show that under the null hypothesis of no marker-secondary trait association, naïve analyses that ignore ascertainment or stratify on case-control status have proper Type I error rates except when both the marker and secondary trait are independently associated with disease risk. Under the alternative hypothesis, these methods are unbiased when the secondary trait is not associated with disease risk. We also show that inverse-probability-of-sampling-weighted (IPW) regression provides unbiased estimates of marker-secondary trait association. We use simulation to quantify the Type I error, power and bias of naïve and IPW methods. IPW regression has appropriate Type I error in all situations we consider, but has lower power than naïve analyses. The bias for naïve analyses is small provided the marker is independent of disease risk. Considering the majority of tested markers in a GWAS are not associated with disease risk, naïve analyses provide valid tests of and nearly unbiased estimates of marker-secondary trait association. Care must be taken when there is evidence that both the secondary trait and tested marker are associated with the primary disease, a situation we illustrate using an analysis of the relationship between a marker in FGFR2 and mammographic density in a breast cancer case-control sample.
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影响因子：
2.1
作者：
LAURITZEN, SL;DAWID, AP;LEIMER, HG
通讯作者：
LEIMER, HG
影响因子：
30.8
作者：
Loos, Ruth J. F.;Lindgren, Cecilia M.;Li, Shengxu;Wheeler, Eleanor;Zhao, Jing Hua;Prokopenko, Inga;Inouye, Michael;Freathy, Rachel M.;Attwood, Antony P.;Beckmann, Jacques S.;Berndt, Sonja I.;Bergmann, Sven;Bennett, Amanda J.;Bingham, Sheila A.;Bochud, Murielle;Brown, Morris;Cauchi, Stephane;Connell, John M.;Cooper, Cyrus;Smith, George Davey;Day, Ian;Dina, Christian;De, Subhajyoti;Dermitzakis, Emmanouil T.;Doney, Alex S. F.;Elliott, Katherine S.;Elliott, Paul;Evans, David M.;Farooqi, I. Sadaf;Froguel, Philippe;Ghori, Jilur;Groves, Christopher J.;Gwilliam, Rhian;Hadley, David;Hall, Alistair S.;Hattersley, Andrew T.;Hebebrand, Johannes;Heid, Iris M.;Herrera, Blanca;Hinney, Anke;Hunt, Sarah E.;Jarvelin, Marjo-Riitta;Johnson, Toby;Jolley, Jennifer D. M.;Karpe, Fredrik;Keniry, Andrew;Khaw, Kay-Tee;Luben, Robert N.;Mangino, Massimo;Marchini, Jonathan;McArdle, Wendy L.;McGinnis, Ralph;Meyre, David;Munroe, Patricia B.;Morris, Andrew D.;Ness, Andrew R.;Neville, Matthew J.;Nica, Alexandra C.;Ong, Ken K.;O'Rahilly, Stephen;Owen, Katharine R.;Palmer, Colin N. A.;Papadakis, Konstantinos;Potter, Simon;Pouta, Anneli;Qi, Lu;Randall, Joshua C.;Rayner, Nigel W.;Ring, Susan M.;Sandhu, Manjinder S.;Scherag, Andre;Sims, Matthew A.;Song, Kijoung;Soranzo, Nicole;Speliotes, Elizabeth K.;Syddall, Holly E.;Teichmann, Sarah A.;Timpson, Nicholas J.;Tobias, Jonathan H.;Uda, Manuela;Vogel, Carla I. Ganz;Wallace, Chris;Waterworth, Dawn M.;Weedon, Michael N.;Willer, Cristen J.;Wraight, Vicki L.;Yuan, Xin;Zeggini, Eleftheria;Hirschhorn, Joel N.;Strachan, David P.;Ouwehand, Willem H.;Caulfield, Mark J.;Samani, Nilesh J.;Frayling, Timothy M.;Vollenweider, Peter;Waeber, Gerard;Mooser, Vincent;Deloukas, Panos;McCarthy, Mark I.;Wareham, Nicholas J.;Barroso, Ines
通讯作者：
Barroso, Ines
影响因子：
2.1
作者：
Robins, JM;Smoller, JW;Lunetta, KL
通讯作者：
Lunetta, KL
影响因子：
30.8
作者：
Sanna, Serena;Jackson, Anne U.;Mohlke, Karen L.
通讯作者：
Mohlke, Karen L.
影响因子：
64.8
作者：
Chanock, Stephen J.;Manolio, Teri;Collins, Francis S.
通讯作者：
Collins, Francis S.