bioRxivNeurosciencePreprint
Neuropathy target esterase activity predicts retinopathy among PNPLA6 disorders
James Liu, Yi HeiD, Cara LwiniD, Marina Han, Bin GuaniD, Amelia NaikiD, Chelsea Bender, Nia Moore, Laryssa A. HuryniD, Yuri V. SergeeviD, Haohua QianiD, Yong ZengiD, Lijin DongiD, Pinghu Liu, Jingqi Lei, Carl J. Haugen, Lev PrasoviD, Ruifang Shi, Hélène DollfusiD, Petros AristodemouiD, Yannik LaichiD, Andrea Hilary NemethiD, John Taylor, Susan M. DownesiD, Maciej Robert KrawczynskiiD, , Robert B. HufnageliD
Abstract
Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism, and hair anomalies. PNPLA6 encodes Neuropathy target esterase (NTE), yet the role of NTE dysfunction on affected tissues in the large spectrum of associated disease remains unclear. We present a clinical meta-analysis of a novel cohort of 23 new patients along with 95 reported individuals with PNPLA6 variants that implicate missense variants as a driver of disease pathogenesis. Measuring esterase activity of 46 disease-associated and 20 common variants observed across PNPLA6-associated clinical diagnoses unambiguously reclassified 10 variants as likely pathogenic and 36 variants as pathogenic, establishing a robust functional assay for classifying PNPLA6 variants of unknown significance. Estimating the overall NTE activity of affected individuals revealed a striking inverse relationship between NTE activity and the presence of retinopathy and endocrinopathy. This phenomenon was recaptured in vivo in an allelic mouse series, where a similar NTE threshold for retinopathy exists. Thus, PNPLA6 disorders, previously considered allelic, are a continuous spectrum of pleiotropic phenotypes defined by an NTE genotype:activity:phenotype relationship. This relationship and the generation of a preclinical animal model pave the way for therapeutic trials, using NTE as a biomarker.
- organism: human
- organism: mouse
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 1
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