Amino Acid-Level Signal-to-Noise Analysis Aids in Pathogenicity Prediction of Incidentally Identified TTN-Encoded Titin Truncating Variants.

Journal Article (Journal Article)

BACKGROUND: TTN, the largest gene in the human body, encodes TTN (titin), a protein that plays key structural, developmental, and regulatory roles in skeletal and cardiac muscle. Variants in TTN, particularly truncating variants (TTNtvs), have been implicated in the pathogenicity of cardiomyopathy. Despite this link, there is also a high burden of TTNtvs in the ostensibly healthy general population. This complicates the diagnostic interpretation of incidentally identified TTNtvs, which are of increasing abundance given expanding clinical exome sequencing. METHODS: Incidentally identified TTNtvs were obtained from a large referral database of clinical exome sequencing (Baylor Genetics) and compared with rare population variants from genome aggregation database and cardiomyopathy-associated variants from cohort studies in the literature. A subset of TTNtv-positive children evaluated for cardiomyopathy at Texas Children's Hospital was retrospectively reviewed for clinical features of cardiomyopathy. Amino acid-level signal-to-noise analysis was performed. RESULTS: Pathological hotspots were identified within the A-band and N-terminal I-band that closely correlated with regions of high percent-spliced in of exons. Incidental TTNtvs and population TTNtvs did not localize to these regions. Variants were reclassified based on current American College of Medical Genetics and Genomics criteria with incorporation of signal-to-noise analysis among Texas Children's Hospital cases. Those reclassified as likely pathogenic or pathogenic were more likely to have evidence of cardiomyopathy on echocardiography than those reclassified as variants of unknown significance. CONCLUSIONS: Incidentally found TTNtvs are common among clinical exome sequencing referrals. Pathological hotspots within the A-band of TTN may be informative in determining variant pathogenicity when incorporated into current American College of Medical Genetics and Genomics guidelines.

Full Text

Duke Authors

Cited Authors

  • Connell, PS; Berkman, AM; Souder, BM; Pirozzi, EJ; Lovin, JJ; Rosenfeld, JA; Liu, P; Tunuguntla, H; Allen, HD; Denfield, SW; Kim, JJ; Landstrom, AP

Published Date

  • February 2021

Published In

Volume / Issue

  • 14 / 1

Start / End Page

  • e003131 -

PubMed ID

  • 33226272

Pubmed Central ID

  • 33226272

Electronic International Standard Serial Number (EISSN)

  • 2574-8300

Digital Object Identifier (DOI)

  • 10.1161/CIRCGEN.120.003131

Language

  • eng

Conference Location

  • United States