Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, the Netherlands; International Max Planck Research School for Language Sciences, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, the Netherlands.
Department of Human Genetics, Radboudumc, 6500 HB Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6500 GL Nijmegen, the Netherlands.
Am J Hum Genet. 2021 Feb 4;108(2):346-356. doi: 10.1016/j.ajhg.2021.01.007. Epub 2021 Jan 28.
Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability.
虽然大规模的统计分析可以可靠地识别疾病与基因的关系,但它们无法准确捕捉基因型与表型的相关性或疾病机制。我们使用多条独立的证据表明,单个基因 SATB1 中的不同变体类型会导致临床表现重叠但明显不同的神经发育障碍。对携带 SATB1 变体的 42 个人进行临床评估,确定了明显的基因型与表型关系,这些关系与通过功能测定建立的不同病理生理机制相关。CUT1 和 CUT2 DNA 结合域中的错义变体导致更强的染色质结合、转录抑制增加,以及严重的表型。相比之下,预测导致杂合不足的变体与更轻微的临床表现相关。对于逃避无意义介导的衰变的具有提前终止蛋白的变体的个体,也观察到类似的轻微表型,这些变体转录活跃但在细胞内定位错误。我们的结果表明,深入的突变特异性基因型与表型研究对于捕捉疾病的复杂性和解释表型变异性至关重要。