Genometric analysis of quantitative traits

数量性状的基因组分析

• 批准号: 8750674
• 负责人: alexander f wilson
• 金额: $ 152.48万
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8750674
• 关键词: 16p; 16q; Address; African American; Agonist; American; BMP2 gene; Blood Platelets; Candidate Disease Gene; Case-Control Studies; Caucasians; Caucasoid Race; Chromosomes; Chromosomes, Human, Pair 20; Chromosomes, Human, Pair 7; Clinical; Collaborations; Computer Simulation; Computer software; Craniosynostosis; Custom; DNA Markers; Data; Dependency; Development; Dideoxy Chain Termination DNA Sequencing; Disease; Equation; Etiology; European; Extended Family; Family; Family Relationship; Genes; Genetic; Genetic Heterogeneity; Genets; Genome; Genotype; Goals; Heritability; Human; Idiopathic scoliosis; Individual; Linear Models; Linear Regressions; Link; Linkage Disequilibrium; Meta-Analysis; Methodology; Methods; Modeling; NF1 gene; National Human Genome Research Institute; Nature; Nuclear Family; Parents; Phenotype; Platelet aggregation; Play; Population; Programming Languages; Property; Quantitative Genetics; Regression Analysis; Reporting; Research; Research Design; Role; Sampling; Sampling Studies; Sequence Analysis; Signal Transduction; Single Nucleotide Polymorphism; Single Nucleotide Polymorphism Map; Statistical Methods; Stratification; Structure; Students; Test Result; Testing; Time; United States National Institutes of Health; Universities; Untranslated Regions; Variant; Vertebral column; Weight; Work; Writing; base; density; family structure; follow-up; genetic analysis; genetic linkage analysis; genetic variant; genome wide association study; insight; medical schools; method development; next generation; next generation sequencing; novel; population based; proband; research study; screening; simulation; statistics; trait; web site

Methods Development Because the non-independence of marker data is particularly relevant in next generation sequencing data, most of the theoretical work during the past year has focused on the testing, implementation and extension of Tiled regression, a linear regression based method for intra-familial tests of association that address non-independence both at the marker and observational level. Although most of the major methodological development has been completed, extensions implemented during the past year have focused on the incorporation of penalized regression methods and the use of family data, and the use of simulation to test the statistical properties of these methods in tiled regression when compared to the use of stepwise regression. The tiled regression methodology has been implemented in the Tiled Regression Analysis Package (TRAP), a software package written in the R programming language. The package is freely available on the NHGRI website: http://research.nhgri.nih.gov/software/TRAP. Simulation experiments to test the statistical properties of tiled regression Two simulation projects were completed during the past year and the results are being prepared for submission Suktitipat et al, Kim et al.. The Suktitpat et al. project focused on the statistical properties of tiled regression compared to those of simple linear regression. Tiled regression had comparable power, a more conservative type I error and a lower FDR than corresponding results from simple linear regression of single markers in a GWAS setting. Kim et al. investigated penalized regression methods as an alternative to stepwise regression. Results from this study suggested that stepwise regression outperformed penalized regression when the causal variants are present in the genotyping data, but penalized regression methods outperformed stepwise methods when the causal variant were not among the variants genotyped. Thus, penalized methods may be more appropriate for a GWAS, whereas stepwise methods may be the preferred approach for next generation whole genome data. In a related simulation project, the use of generalized estimating equations as a method for including family information in a linear regression model was investigated and compared it to a variance component approach (VCA) Suktitipat et al. 2012, Hum Hered. Although the VCA makes complete use of phenotyping, genotyping and family relationships, the computational time for VCA in whole-genome data in families is considerable. The power and type I error rate for a linear model with GEE clustering with a robust variance estimator, in clusters based on extended family structure (GEEExt) and clusters based on nuclear family structure split from the original extended family structure (GEESpl), was compared to that of VCA. The type I error rate for GEEExt was marginally higher than the nominal rate when the MAF was < 0.1, and close to nominal rate when MAF &#8805; 0.2. All methods gave consistent effect estimates and had similar power. The GEE extension to a linear model with a robust variance estimator was the computationally fastest and provided a reasonable alternative to the VCA for screening family data. Collaborations Familial Idiopathic Scoliosis Two analyses focusing on candidate regions and phenotypic subsets in the Familial Idiopathic Scoliosis (FIS) project were completed during the past year. 1) Candidate regions on 9q and 16p-16q, previously identified as linked to FIS in a study of 202 families (Miller et al. 2005), were genotyped with a custom high-density map of SNPs in order to identify candidate genes and prioritize them for next generation sequence analysis. Nominally significant linkage results were found for markers in both candidate regions. Results from intra-familial tests of association and tiled regression corroborated the linkage findings and identified possible candidate genes suitable for follow-up with next generation sequencing in these same families Miller et al. Human Hered 2012. 2) Tilley et al. Spine 2013 used the family data from Miller et al. 2001 in an attempt to replicate an association between FIS and the CHD7 gene on 8q12.2 in an independent sample of families of European descent. Model-independent linkage analysis and tests of association were performed for the previously reported 22 significant single nucleotide polymorphisms (SNPs) in the CHD7 gene in 244 families with familial idiopathic scoliosis (FIS). Results from the tests of associations from this study and the previous study were combined in a weighted meta-analysis. No significant results (P < 0.01) were found for linkage analysis or tests of association between genetic variants of the CHD7 and FIS in this study sample, failing to replicate the findings from the previous study. Furthermore, no significant results (P < 0.01) were found from meta-analysis of the results from the tests of association from this sample and from the previous sample. No association between the SNPs in the CHD7 gene and FIS within this study sample was found, failing to replicate the earlier findings. Sagittal craniosynostosis Justice et al. Nat Genet 2012, as part of a long-term collaboration with Dr. Simeon (Boyd) Boyadjiev at UC Davis, reported a genome-wide association study (GWAS) for non-syndromic sagittal craniosynostosis using 130 European American case-parent trios. The strongest association was observed in a 120 kb region in the 3 UTR of BMP2 on chromosome 20, flanked by rs1884302 and rs6140226. The second strongest association was found in a 167 kb region of BBS9 on chromosome 7 between rs10262453 and rs17724206, with the strongest association being to rs10262453. These associations were replicated in an independent Caucasian population of 186 unrelated probands with non-syndromic sagittal craniosynostosis and 564 unaffected controls for rs1884302 and rs10262453. These findings suggest that the BMP2 and/or BBS9 genes may be involved in the etiology of the development of sagittal craniosynostosis. The GeneSTAR project (Drs. Diane and Lewis Becker, Johns Hopkins University School of Medicine) In this study, Kim et al. PLoS One 2013 used a sequencing approach to identify additional exonic variants in PEAR1 that may also determine variability in platelet aggregation. A target region on chromosome 1q23.1 including the entire PEAR1 gene was Sanger sequenced in 104 subjects selected on the basis of hyper- and hypo- aggregation across three different platelet agonists. Single-variant and collapsed multi-variant burden tests for association were performed. Of the 235 variants identified though sequencing, 104 were novel and ten of these were missense variants. More rare variants (MAF < 5%) were noted in African Americans compared to European Americans (108 vs. 45). The common intronic GWAS-identified variant (rs12041331) demonstrated the most significant association signal in the African American sample; no association was seen for additional exonic variants in this group. Sequencing approaches confirm that a common intronic variant has the strongest association in African Americans, and show that additional exonic variants play a role in platelet aggregation in European Americans. Other ongoing collaborations include: 1) Clinical characterization of NF1 (Dr. Douglas Stewart, NIH/NCI) 2) The ClinSeq project (Les Biesecker, NIH/NHGRI) 3) Bechet disease (Dr. Daniel Kastner, NIH/NHGRI) 4) Variation in metabolites in the Irish Trinity Student Study (Dr. Larry Brody, NHGRI)

方法开发 由于标记数据的非独立性在下一代测序数据中特别重要，因此过去一年的大部分理论工作都集中在 Tiled 回归的测试、实施和扩展上，Tiled 回归是一种基于线性回归的方法，用于家族内关联测试，解决标记和观察水平上的非独立性问题。 虽然大部分主要方法的开发已经完成，但去年实施的扩展主要集中在惩罚回归方法的结合和家庭数据的使用，以及与使用逐步回归相比，使用模拟来测试这些方法在平铺回归中的统计特性。 平铺回归方法已在平铺回归分析包 (TRAP) 中实现，这是一个用 R 编程语言编写的软件包。 该软件包可在 NHGRI 网站上免费获取：http://research.nhgri.nih.gov/software/TRAP。 测试平铺回归统计特性的模拟实验 去年完成了两个模拟项目，正在准备提交结果 Suktitipat 等人、Kim 等人。项目重点关注平铺回归与简单线性回归相比的统计特性。 与 GWAS 设置中单个标记的简单线性回归的相应结果相比，平铺回归具有相当的功效、更保守的 I 型错误和更低的 FDR。 金等人。研究了惩罚回归方法作为逐步回归的替代方法。 这项研究的结果表明，当基因分型数据中存在因果变异时，逐步回归优于惩罚回归，但当因果变异不在基因分型变异中时，惩罚回归方法优于逐步方法。 因此，惩罚方法可能更适合 GWAS，而逐步方法可能是下一代全基因组数据的首选方法。 在相关的模拟项目中，研究了使用广义估计方程作为将家庭信息包含在线性回归模型中的方法，并将其与方差分量法 (VCA) Suktitipat 等人进行了比较。 2012，嗡嗡声。 尽管 VCA 完全利用了表型分型、基因分型和家族关系，但家族全基因组数据中 VCA 的计算时间相当可观。 将具有鲁棒方差估计器的 GEE 聚类线性模型、基于扩展族结构 (GEEExt) 的聚类和基于从原始扩展族结构分裂的核心族结构 (GEESpl) 的聚类的功效和 I 类错误率与 VCA 进行了比较。 当 MAF < 0.1 时，GEEExt 的 I 类错误率略高于名义率，而当 MAF ≥ 0.2 时，接近名义率。 所有方法都给出了一致的效果估计并且具有相似的功效。 GEE 扩展到具有稳健方差估计器的线性模型，计算速度最快，并且为筛选家庭数据提供了 VCA 的合理替代方案。 合作 家族性特发性脊柱侧弯 去年完成了两项针对家族性特发性脊柱侧凸 (FIS) 项目中候选区域和表型子集的分析。 1) 9q 和 16p-16q 上的候选区域先前在 202 个家族的研究中被鉴定为与 FIS 相关（Miller 等人，2005 年），使用定制的 SNP 高密度图谱进行基因分型，以便识别候选基因并优先考虑它们以进行下一代序列分析。 两个候选区域中的标记均发现了名义上显着的连锁结果。 家族内关联测试和平铺回归的结果证实了连锁发现，并确定了适合在这些相同家族中进行下一代测序的可能候选基因 Miller 等人。人类遗传2012。 2）蒂利等人。 Spine 2013 使用了 Miller 等人的家庭数据。 2001 年，试图在欧洲血统家庭的独立样本中复制 FIS 与 8q12.2 上的 CHD7 基因之间的关联。 对先前报道的 244 个家族性特发性脊柱侧凸 (FIS) 家族的 CHD7 基因中的 22 个显着单核苷酸多态性 (SNP) 进行了模型独立连锁分析和关联测试。 本研究和先前研究的关联检验结果被合并在加权荟萃分析中。 在本研究样本中，CHD7 和 FIS 遗传变异之间的连锁分析或关联测试未发现显着结果（P < 0.01），未能复制先前研究的结果。 此外，对该样本和先前样本的关联测试结果进行荟萃分析，未发现显着结果（P < 0.01）。 本研究样本中未发现 CHD7 基因中的 S​​NP 与 FIS 之间存在关联，未能重复早期的发现。 矢状位颅缝早闭 正义等人。 Nat Genet 2012，作为与加州大学戴维斯分校的 Simeon (Boyd) Boyadjiev 博士长期合作的一部分，报告了一项针对非综合征矢状颅缝早闭的全基因组关联研究 (GWAS)，该研究使用了 130 名欧洲裔美国病例父母三人组。在 20 号染色体上 BMP2 3 UTR 的 120 kb 区域中观察到最强的关联，两侧为 rs1884302 和 rs6140226。 第二强关联发现于 7 号染色体上 rs10262453 和 rs17724206 之间 BBS9 的 167 kb 区域，最强关联是 rs10262453。 这些关联在 186 名患有非综合征矢状颅缝早闭的无关先证者和 564 名未受影响的 rs1884302 和 rs10262453 对照的独立白人群体中得到了复制。 这些发现表明 BMP2 和/或 BBS9 基因可能参与矢状颅缝早闭发生的病因学。 GeneSTAR 项目（约翰·霍普金斯大学医学院 Diane 和 Lewis Becker 博士） 在这项研究中，Kim 等人。 PLoS One 2013 使用测序方法来鉴定 PEAR1 中的其他外显子变异，这些变异也可能决定血小板聚集的变异性。染色体 1q23.1 上的目标区域（包括整个 PEAR1 基因）在 104 名受试者中进行了桑格测序，这些受试者是根据三种不同血小板激动剂的高聚集和低聚集而选择的。 进行了单变量和折叠多变量负荷测试的关联性。通过测序鉴定出 235 个变体，其中 104 个是新变体，其中 10 个是错义变体。与欧洲裔美国人相比，非裔美国人的罕见变异（MAF < 5%）更为罕见（108 比 45）。常见的内含子 GWAS 识别变异 (rs12041331) 在非裔美国人样本中表现出最显着的关联信号；在该组中没有发现其他外显子变异的关联。测序方法证实，常见的内含子变异在非裔美国人中具有最强的关联性，并表明其他外显子变异在欧洲裔美国人的血小板聚集中发挥作用。 其他正在进行的合作包括： 1) NF1 的临床特征（Douglas Stewart 博士，NIH/NCI） 2) ClinSeq 项目（Les Biesecker，NIH/NHGRI） 3) Bechet 病（Daniel Kastner 博士，NIH/NHGRI） 4) 爱尔兰三一学生研究中代谢物的变化（Larry Brody 博士，NHGRI）