Discovery and characterization of a monogenetic insult, caveolin-3-V37L, that precipitated oligo-proteomic perturbations governing repolarization reserve

Pharmacogenomic markers associated with drug-induced QT prolongation: a systematic review

AIM

To systematically assess clinical studies involving patients undergoing drug therapy, comparing different genotypes to assess the relationship with changes in QT intervals, with no limitations on study design, setting, population, dosing regimens, or duration.

METHODS

This systematic review followed PRISMA guidelines and a pre-registered protocol. Clinical human studies on PGx markers of diQTP were identified, assessed using standardized tools, and categorized by design. Gene associations were classified as pharmacokinetic or pharmacodynamic. Identified genes underwent pathway enrichment analyses. Drugs were classified by third-level Anatomical Therapeutic Chemical (ATC) codes. Descriptive statistics were computed by study category and drug classes.

RESULTS

Of 4,493 reports, 84 studies were included, identifying 213 unique variants across 42 drug classes, of which 10% were replicated. KCNE1-Asp85Asn was the most consistent variant. Most findings (82%) were derived from candidate gene studies, suggesting bias toward known markers. The diQTP-associated genes were mainly linked to "cardiac conduction" and "muscle contraction" pathways (false discovery rate = 4.71 × 10-14). We also found an overlap between diQTP-associated genes and congenital long QT syndrome genes.

CONCLUSION

Key genes, drugs, and pathways were identified, but few consistent PGx markers emerged. Extensive, unbiased studies with diverse populations are crucial to advancing the field.

REGISTRATION

A protocol was pre-registered at PROSPERO under registration number CRD42022296097.

DATA DEPOSITION

Data sets generated by this review are available at figshare: DOI: 10.6084/m9.figshare.27959616.

Clinical Utility of Protein Language Models in Resolution of Variants of Uncertain Significance in KCNQ1, KCNH2, and SCN5A Compared With Patch-Clamp Functional Characterization

BACKGROUND

Genetic testing for cardiac channelopathies is the standard of care. However, many rare genetic variants remain classified as variants of uncertain significance (VUS) due to lack of epidemiological and functional data. Whether deep protein language models may aid in VUS resolution remains unknown. Here, we set out to compare how 2 deep protein language models perform at VUS resolution in the 3 most common long-QT syndrome-causative genes compared with the gold-standard patch clamp.

METHODS

A total of 72 rare nonsynonymous VUS (9 KCNQ1, 19 KCNH2, and 50 SCN5A) were engineered by site-directed mutagenesis and expressed in either HEK293 cells or TSA201 cells. Whole-cell patch-clamp technique was used to functionally characterize these variants. The protein language models, evolutionary scale modeling, version 1b and AlphaMissense, were used to predict the variant effect of missense variants and compared with patch clamp.

RESULTS

Considering variants in all 3 genes, the evolutionary scale modeling, version 1b model had a receiver operating characteristic curve-area under the curve of 0.75 (P=0.0003). It had a sensitivity of 88% and a specificity of 50%. AlphaMissense performed well compared with patch-clamp with an receiver operating characteristic curve-area under the curve of 0.85 (P<0.0001), sensitivity of 80%, and specificity of 76%.

CONCLUSIONS

Deep protein language models aid in VUS resolution with high sensitivity but lower specificity. Thus, these tools cannot fully replace functional characterization but can aid in reducing the number of variants that may require functional analysis.