罗塞塔表型协调方法有助于找到复杂认知性状的关系数量性状基因座。
The Rosetta Phenotype Harmonization Method Facilitates Finding a Relationship Quantitative Trait Locus for a Complex Cognitive Trait.
作者信息
Petrill Stephen A, Klamer Brett G, Buyske Steven, Willcutt Erik G, Gruen Jeffrey R, Francis David J, Flax Judy F, Brzustowicz Linda M, Bartlett Christopher W
机构信息
Department of Psychology, College of Arts and Sciences, The Ohio State University, Columbus, OH 43210, USA.
Center for Biostatistics, The Ohio State University, Columbus, OH 43210, USA.
出版信息
Genes (Basel). 2023 Aug 31;14(9):1748. doi: 10.3390/genes14091748.
Genetics researchers increasingly combine data across many sources to increase power and to conduct analyses that cross multiple individual studies. However, there is often a lack of alignment on outcome measures when the same constructs are examined across studies. This inhibits comparison across individual studies and may impact the findings from meta-analysis. Using a well-characterized genotypic (brain-derived neurotrophic factor: BDNF) and phenotypic constructs (working memory and reading comprehension), we employ an approach called Rosetta, which allows for the simultaneous examination of primary studies that employ related but incompletely overlapping data. We examined four studies of BDNF, working memory, and reading comprehension with a combined sample size of 1711 participants. Although the correlation between working memory and reading comprehension over all participants was high, as expected (ρ = 0.45), the correlation between working memory and reading comprehension was attenuated in the BDNF Met/Met genotype group (ρ = 0.18, n.s.) but not in the Val/Val (ρ = 0.44) or Val/Met (ρ = 0.41) groups. These findings indicate that Met/Met carriers may be a unique and robustly defined subgroup in terms of memory and reading comprehension. This study demonstrates the utility of the Rosetta method when examining complex phenotypes across multiple studies, including psychiatric genetic studies, as shown here, and also for the mega-analysis of cohorts generally.
遗传学研究人员越来越多地整合来自多个来源的数据,以增强效力并开展跨越多个个体研究的分析。然而,当在不同研究中考察相同的构念时,结果测量往往缺乏一致性。这阻碍了个体研究之间的比较,可能会影响荟萃分析的结果。我们使用一种名为罗塞塔(Rosetta)的方法,通过一个特征明确的基因型(脑源性神经营养因子:BDNF)和表型构念(工作记忆和阅读理解),该方法允许同时考察采用相关但不完全重叠数据的原始研究。我们考察了四项关于BDNF、工作记忆和阅读理解的研究,合并样本量为1711名参与者。尽管所有参与者的工作记忆和阅读理解之间的相关性如预期般较高(ρ = 0.45),但在BDNF Met/Met基因型组中,工作记忆和阅读理解之间的相关性减弱(ρ = 0.18,无统计学意义),而在Val/Val(ρ = 0.44)或Val/Met(ρ = 0.41)组中则没有减弱。这些发现表明,就记忆和阅读理解而言,Met/Met携带者可能是一个独特且定义明确的亚组。本研究证明了罗塞塔方法在考察多个研究中的复杂表型时的效用,包括此处所示的精神遗传学研究,以及一般队列的大型分析。