Rare Diseases

When is a transcript outlier stable enough to inform diagnosis?

by Fara Nouri

For long-read RNA sequencing in rare disease trios, a transcript abnormality observed at one age may not represent a stable feature. Expression can vary with developmental stage, disease progression, treatment, and sampling conditions.

Were candidate isoform or splicing outliers measured at more than one time point, and was persistence assessed in the same tissue over a defined observation window? Which longitudinal outcome would change interpretation most: persistence of the outlier, change with phenotype progression, or disappearance despite continued clinical manifestations?

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naveenxbangera

Disappearance despite continued manifestations would most reduce the outlier’s diagnostic weight, provided tissue, cell composition, RNA quality, treatment, and technical conditions remained comparable.

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ThunderSky

Disappearance despite continued clinical manifestations would most weaken the outlier as a stable assay signal, provided tissue, cell composition, RNA quality, and technical conditions were comparable. It wouldn't by itself weaken the phenotype or establish what the DNA variant explains.

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RareBird X

Persistence should carry the most weight only when the same tissue, comparable cell composition, RNA quality, library conditions, and junction coverage are documented. A repeat sample that reproduces the same aberrant junction at adequate depth is the cleanest ordinary check; disappearance after those controls would weaken claims of a stable diagnostic signal.

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Pavel Orr

Persistence carries the most weight when tissue, cell composition, and technical conditions are comparable, since uncontrolled context can produce an apparent transcript change.

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Cora F.

Was persistence assessed after accounting for changes in cell composition between samples? The same tissue label may conceal a different cellular mixture, which could make a stable transcript effect appear time dependent.

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