The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing

Am J Hum Genet. 2024 May 2;111(5):841-862. doi: 10.1016/j.ajhg.2024.03.007. Epub 2024 Apr 8.

Abstract

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

Keywords: RNA sequencing; RNA-seq; clinically accessible tissue; fibroblast; genetic diagnosis; induced neuron; isoform; neurological disorder; transcriptome; transdifferentiation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Cell Transdifferentiation* / genetics
  • Female
  • Fibroblasts* / cytology
  • Fibroblasts* / metabolism
  • Humans
  • Male
  • Nervous System Diseases / diagnosis
  • Nervous System Diseases / genetics
  • Neurons* / cytology
  • Neurons* / metabolism
  • RNA-Seq / methods
  • Reproducibility of Results
  • Sequence Analysis, RNA* / methods
  • Transcriptome