Ngo Kathie J, Wong Darice Y, Huang Alden Y, Lee Hane, Nelson Stanley F, Fogel Brent L
Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Clinical Neurogenomics Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Mol Med. 2025 May 24;31(1):205. doi: 10.1186/s10020-025-01257-8.
Genetic ataxias are clinically heterogenous neurodegenerative conditions often involving rare or private mutations and it is often difficult to assign pathogenicity to rare gene variants solely based on DNA sequencing. An effective functional assay from an easy-to-obtain biospecimen would aid this assessment and be of high clinical value. SETX encodes a ubiquitous DNA/RNA helicase crucial for resolving R-loops and maintaining genome stability. Loss-of-function mutations cause a recessive disorder, Ataxia with Oculomotor Apraxia Type 2 (AOA2).
Here we utilize Weighted Gene Co-expression Network Analysis (WGCNA) from patient blood to construct an AOA2-specific transcriptomic signature as a biomarker to evaluate SETX variants in patients clinically suspected of having AOA2.
WGCNA from peripheral blood RNA of 11 AOA2 patients from 7 families initially identified a single gene module that was modestly effective in distinguishing individuals with AOA2 from controls (sensitivity 73%, specificity 97%) and was able to robustly differentiate AOA2 patients from those with genetically distinct, yet phenotypically similar, neurological disorders (sensitivity 100%, specificity 100%). An independent derivation of the transcriptional biomarker identified a dual module model that was able to better distinguish individuals with AOA2 from controls (sensitivity 100%, specificity 97%). As validation, we examined a second cohort of 21 patients from 13 families and demonstrate that this dual module transcriptional biomarker could discriminate patients clinically suspected of AOA2 from controls (57%, 95%CI: 34%-78%). Overall, the transcriptional biomarker was able to separate AOA2 subjects (n = 32) from controls (n = 35) with 72% sensitivity and 97% specificity. Notably, this transcriptomic biomarker enabled verification of the first pathogenic SETX mutation found in a non-canonical transcript, expanding the spectrum of mutations that contribute to AOA2.
Our study identified a transcriptional biomarker that was able to differentiate AOA2 from controls and from other related neurological disorders, consequently expanding the spectrum of known pathogenic mutations. This proof-of-concept study illustrates that transcriptional biomarkers may be used to validate variants of uncertain significance in known genetic diseases.
遗传性共济失调是临床上异质性的神经退行性疾病，常涉及罕见或个体特有的突变，仅基于DNA测序往往难以确定罕见基因变异的致病性。从易于获取的生物样本中进行有效的功能分析将有助于这一评估，具有很高的临床价值。SETX编码一种普遍存在的DNA/RNA解旋酶，对解决R环和维持基因组稳定性至关重要。功能丧失突变会导致一种隐性疾病，即2型伴动眼性失用的共济失调（AOA2）。
在此，我们利用患者血液中的加权基因共表达网络分析（WGCNA）构建AOA2特异性转录组特征作为生物标志物，以评估临床怀疑患有AOA2的患者中的SETX变异。
对来自7个家庭的11名AOA2患者的外周血RNA进行WGCNA分析，最初确定了一个单一基因模块，该模块在区分AOA2患者和对照方面有一定效果（敏感性73%，特异性97%），并且能够可靠地区分AOA2患者与那些具有遗传差异但表型相似的神经系统疾病患者（敏感性100%，特异性100%）。转录生物标志物的独立推导确定了一个双模块模型，该模型能够更好地区分AOA2患者和对照（敏感性100%，特异性97%）。作为验证，我们检查了来自13个家庭的21名患者的第二个队列，并证明这个双模块转录生物标志物可以将临床怀疑患有AOA2的患者与对照区分开来（57%，95%CI：34%-78%）。总体而言，转录生物标志物能够以72%的敏感性和97%的特异性将AOA2受试者（n = 32）与对照（n = 35）区分开来。值得注意的是，这种转录组生物标志物能够验证在一个非规范转录本中发现的第一个致病性SETX突变，扩大了导致AOA2的突变谱。
我们的研究确定了一种转录生物标志物，它能够将AOA2与对照以及其他相关神经系统疾病区分开来，从而扩大了已知致病突变的谱。这项概念验证研究表明，转录生物标志物可用于验证已知遗传疾病中意义不确定的变异。
