A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

Rao, Shaoqi; Yuan, Manqiong; Zuo, Xiaoyu; Su, Weiyang; Fan, Zhengqiu; Huang, Ke; Lin, Mei-Hua; Ding, Yuanlin

doi:10.1371/journal.pone.0026435

Cited by 3 publications

(5 citation statements)

References 34 publications

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“…Several previous studies have successfully utilized gametic disequilibrium as a measure to detect interaction [28] , [29] , [30] , [31] , [32] . Gametic disequilibrium in turn has a direct impact on the entropy of gamete [16] .…”

Section: Methodsmentioning

confidence: 99%

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

et al. 2013

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Genome-wide analysis of gene-gene interactions has been recognized as a powerful avenue to identify the missing genetic components that can not be detected by using current single-point association analysis. Recently, several model-free methods (e.g. the commonly used information based metrics and several logistic regression-based metrics) were developed for detecting non-linear dependence between genetic loci, but they are potentially at the risk of inflated false positive error, in particular when the main effects at one or both loci are salient. In this study, we proposed two conditional entropy-based metrics to challenge this limitation. Extensive simulations demonstrated that the two proposed metrics, provided the disease is rare, could maintain consistently correct false positive rate. In the scenarios for a common disease, our proposed metrics achieved better or comparable control of false positive error, compared to four previously proposed model-free metrics. In terms of power, our methods outperformed several competing metrics in a range of common disease models. Furthermore, in real data analyses, both metrics succeeded in detecting interactions and were competitive with the originally reported results or the logistic regression approaches. In conclusion, the proposed conditional entropy-based metrics are promising as alternatives to current model-based approaches for detecting genuine epistatic effects.

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Section: Methodsmentioning

confidence: 99%

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

et al. 2013

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“…Failure to include epistasis in models of h 2 where it does exist inflates the estimate of h 2 for the trait (Zuk et al 2012). Recent developments in identifying epistatic interactions (Rao et al 2011;Ma et al 2012;Rajapakse et al 2012) hold promise for explaining some of the "missing" h 2 underlying CD risk.…”

Section: Presentation Pathophysiology and Genetics Of CDmentioning

confidence: 99%

Celiac Disease as a Model for the Evolution of Multifactorial Disease in Humans

Sams

Hawks

2014

Human Biology

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Abstract. Celiac disease (CD) is a multifactorial chronic inflammatory conditionthat results in injury of the mucosal lining of the small intestine upon ingestion of wheat gluten and related proteins from barley and rye. Although the exact mechanisms leading to CD are not fully understood, the genetic basis of CD has been relatively well characterized. In this review we briefly review the history of discovery, clinical presentation, pathophysiology, and current understanding of the genetics underlying CD risk. Then, we discuss what is known about the current distribution and evolutionary history of genes underlying CD risk in light of other evolutionary models of disease. Specifically, we conclude that the set of loci underlying CD risk did not cohesively evolve as a response to a single past selection event such as the development of agriculture. Rather, deterministic and stochastic evolutionary processes have both contributed to the present distribution of variation in CD risk loci. Selection has shaped some components of this network, but this selection appears to have occurred at different points in the past.Other parts of the CD risk network have likely arisen due to stochastic processes such as genetic drift. Celiac disease (CD) is a multifactorial chronic inflammatory condition that resultsin injury of the mucosal lining of the small intestine. The earliest descriptions of a condition with symptoms like CD date back to the first and second century writings of the Greek physician Arataeus (Simoons 1981;Losowsky 2008). The first modern description of CD is attributed to English physician Samuel Jones Gee, who was familiar with the writings of Arataeus. In 1888 (Dowd and Walker-Smith 1974;Simoons 1981;Losowsky 2008) Gee described the 'coeliac affection' as a condition of chronic indigestion associated with diarrhea, wasting, and weakness and common in people of all ages. Gee's report was the first to hypothesize dietary factors as a primary cause of the condition (Dowd and Walker-Smith 1974), and during the early twentieth century some workers noted the value of a starch free diet for prevention of CD (Haas 1924). Dicke and colleagues (1950, 1953) observed the detrimental effect of wheat flour (but not wheat starch) on CD patients experimentally confirming a role for diet as a driver of CD. Shortly thereafter, Anderson and colleagues (Anderson et al. 1952;Alvey et al. 1957) confirmed the effect of wheat on CD and identified wheat gluten as the primary culprit.CD appears to be an evolutionary paradox. Only since the 1950s have clinicians recognized that a gluten-free diet is an effective treatment (Barker and Liu 2008). Before that time, diagnosed and undiagnosed CD reduced the health and fitness of sufferers, with juvenile cases leading to malnutrition or death, and adult cases causing wasting, lack of adequate nutrition, greater susceptibility to infection, and direct reductions in fertility (Corrao et al. 2001;Soni and Badawy 2010). Despite these apparent costs, CD is common today (>1%) in several popul...

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“…Rao等 [9] 从群体进化角度解释基因互作与疾病之间的关系, 提出了基于固定指数(Fst)的两位点基因互作检测方法, 即将疾病人群和对照人群视为来自相同祖先的不同进化亚群, 并采用多元方差分析技术构建基因互作检验统计量Fst:…”

Section: Fst 方法unclassified

“…于疟疾出生队列研究数据, 发现Hb基因和α+-地中海贫血基因间存在互作 [9] RF法易于发现主效应微弱但与其他SNP有强联合效应的遗传变异 [12] , 能以较少的参数调整, 检验众多预测变量。Lunetta等 [13] 研究者提出改进的MDR法(OR-MDR) [15] 。该方法将…”

Section: Fst 方法unclassified

“…(GPNN) [19] 、支持向量机(Support vector machine) [20] 等; 这些方法识别基因互作的基本思想与上述方法有相似之处, 读者可参考相关文献。类风湿关节炎 [4] Fast-epistasis × × 不需估算单倍型; 计算复杂度低无法剖分互作效应和联合效应; 主效应和 LD 会增加假阳性率 PLINK 牛皮癣 [7] Fst × × 计算复杂度低; 功效较高无法剖分互作效应和联合效应 R 疟疾 [9] RF × √ 可分析稀疏数据; 发现非线性互作受主效应影响;…”

Section: Fst 方法unclassified

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Advances in development of gene-gene interaction analy-sis methods based on SNP data: a review

Luan¹,

Zuo²,

Liu³

et al. 2013

Hereditas (Beijing)

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The SNP-based association analysis has become one of the most important approaches to interpret the underlying molecular mechanisms for human complex diseases. Nevertheless, the widely-used singe-locus analysis is only capable of capturing a small portion of susceptible SNPs with prominent marginal effects, leaving the important genetic component, epistasis or joint effects, to be undetectable. Identifying the complex interplays among multiple genes in the genome-wide context is an essential task for systematically unraveling the molecular mechanisms for complex diseases. Many approaches have been used to detect genome-wide gene-gene interactions and provided new insights into the genetic basis of complex diseases. This paper reviewed recent advances of the methods for detecting gene-gene interaction, categorized into three types, model-based and model-free statistical methods, and data mining methods, based on their characteristics in theory and numerical algorithm. In particular, the basic principle, numerical implementation and cautions for application for each method were elucidated. In addition, this paper briefly discussed the limitations and challenges associated with detecting genome-wide epistasis, in order to provide some methodological consultancies for scientists in the related fields.

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A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

Cited by 3 publications

References 34 publications

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

Celiac Disease as a Model for the Evolution of Multifactorial Disease in Humans

Advances in development of gene-gene interaction analy-sis methods based on SNP data: a review

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