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具有多个表型类别的复杂疾病的连锁分析:模拟研究及在双相情感障碍数据中的应用

Linkage analysis of complex disorders with multiple phenotypic categories: simulation studies and application to bipolar disorder data.

作者信息

Levinson D F

机构信息

Department of Psychiatry, MCP Hahnemann School of Medicine, Allegheny University of the Health Sciences, Philadelphia, Pennsylvania, USA.

出版信息

Genet Epidemiol. 1997;14(6):653-8. doi: 10.1002/(SICI)1098-2272(1997)14:6<653::AID-GEPI17>3.0.CO;2-P.

Abstract

The problem of linkage analysis of disorders with multiple possible phenotypes (diagnostic spectrum) is considered. A modification is proposed to Ott's [1994] method of down-weighting the contribution of broader diagnoses by reducing penetrance ratios for affected cases. A "robust weighting" strategy considers only the robustness of a set of ratios across a range of true genetic models. Practical models for lod-score analysis will typically employ a high penetrance ratio (> 10) for "core" cases, and ratios between 2 and 5 for broader cases. Results suggest that an additive parametric analysis correlates highly with dominant, recessive and nonparametric linkage (NPL) analyses. A weighted, additive model is then applied to a modified NIMH bipolar chromosome 18 data set (Genetic Analysis Workshop 10) and compared with NPL analyses under narrow and broad diagnostic models. The weighted model performed well. The introduction of similar weights into nonparametric analyses may prove more useful.

摘要

本文考虑了具有多种可能表型(诊断谱)的疾病的连锁分析问题。提出了一种对Ott [1994]方法的修正,即通过降低患病病例的外显率来降低宽泛诊断的贡献权重。一种“稳健加权”策略仅考虑一系列真实遗传模型下一组比率的稳健性。用于对数优势比分(lod-score)分析的实际模型通常对“核心”病例采用高外显率(>10),对宽泛病例采用2至5之间的比率。结果表明,加性参数分析与显性、隐性和非参数连锁(NPL)分析高度相关。然后将加权加性模型应用于修改后的美国国立精神卫生研究所双相情感障碍18号染色体数据集(遗传分析研讨会10),并与狭义和广义诊断模型下的NPL分析进行比较。加权模型表现良好。在非参数分析中引入类似权重可能会更有用。

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