Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study.
Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study.
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DOI：
10.1186/1471-2350-8-s1-s15
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发表时间：
2007-09-19
影响因子：
--
通讯作者：
Wolf PA
中科院分区：
文献类型：
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作者：
Seshadri S;DeStefano AL;Au R;Massaro JM;Beiser AS;Kelly-Hayes M;Kase CS;D'Agostino RB Sr;Decarli C;Atwood LD;Wolf PA
脑磁共振成像（MRI）和认知测试可以识别与中风、痴呆和阿尔茨海默病（AD）风险增加相关的遗传性内表型。我们进行了全基因组关联（GWA）和连锁分析，探索这些内表型在社区为基础的样本的遗传基础。共705名无中风和痴呆的Fragrance参与者（年龄62 ± 9岁，50%男性）接受了体积脑MRI和认知测试（1999-2002年），进行了基因分型。我们使用线性模型，通过加性模型中的广义估计方程（GEE）和基于家族的关联检验（FBAT）调整一级关系，以关联合格的单核苷酸多态性（SNPs，Affytelium 100 K人类基因芯片上70，987个常染色体，次要等位基因频率≥ 0.10，基因型调用率≥ 0.80，和Hardy-Weinberg平衡p值≥ 0.001）与9项MRI测量（包括全脑（TCBV）、脑叶、心室和白色高信号（WMH）体积）和6项认知因素/测试（评估语言和视觉空间记忆、视觉扫描和运动速度、阅读、抽象推理和命名。我们利用10，592个信息SNP和613个短串联重复序列确定了多点身份，并使用方差分量分析计算LOD得分。在FBAT分析中，最强的基因-表型关联在SORL 1（rs 1131497; p = 3.2 × 10-6）和抽象推理之间，在GEE分析中，最强的基因-表型关联在CDH 4（rs 1970546; p = 3.7 × 10-8）和TCBV之间。SORL 1在淀粉样前体蛋白加工中起作用，并与AD的风险相关。在50个最强的关联（GEE和FBAT各25个）中，还有其他生物学上有趣的基因。在163个中风、AD和记忆障碍的候选基因中，28个基因的多态性与研究的内表型相关，p < 0.001。我们证实了我们先前报道的4号染色体上WMH的连锁，并描述了阅读能力与18号染色体上标记物（GATA 11 A06）的连锁，该标记物先前与阅读障碍有关（LOD评分= 2.2和5.1）。我们的研究结果表明，与临床神经系统疾病相关的基因对亚临床表型也有可检测的影响。这些假设生成数据说明了使用无偏方法来发现可能参与大脑老化的新途径，并可用于复制其他研究中的观察结果。
Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample. A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores. The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 × 10-6) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 × 10-8) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1). Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.