Back

Rapid functional classification of cardiac genetic variants directly informs precision cardiology

Wang, X.; Chen, P.-T.; Mayourian, J.; Ripple, L.; Tharani, Y.; Shang, T.; Pavlaki, N.; Shani, K.; Jang, Y.; Janson, C.; Mah, D.; Parker, K. K.; Pu, W. T.; Ha, T.; Bezzerides, V.

2026-04-19 bioengineering
10.64898/2026.04.15.718512 bioRxiv
Show abstract

Large-scale clinical genome sequencing yields vast numbers of variants of unknown significance (VUSs). The high frequency of VUSs and the paucity of platforms to characterize their functional impact pose significant challenges for clinical decision making. Here, we present an integrated end-to-end platform, REVi-SCOPE (Rapid evaluation of variants in single cells by optogenetics and prime editing), for characterization of the impact of VUSs on cardiac physiology. Our strategy consists of (1) introduction of variants directly into wild-type (WT) human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) via prime editing; (2) optogenetic assessment of calcium and membrane voltage dynamics in single hiPSC-CMs within the pool of edited and unedited cells; and (3) in situ single-cell genotyping of the phenotyped hiPSC-CMs with single-allele resolution. By optimizing and integrating each of these steps, we created a platform that enables VUS characterization in 10 days. We validated the REVi-SCOPEs capabilities by analyzing the properties of established arrhythmogenic variants. We then used REVi-SCOPE to reveal the functional impact of a VUS, TRPM4A320V, identified in a child with a conduction block. Together, our results show that REVi-SCOPE enables functional characterization of VUSs linked to cardiac arrhythmias with unprecedented throughput.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Nature Communications
4913 papers in training set
Top 9%
16.9%
2
Nature Methods
336 papers in training set
Top 1%
9.7%
3
Nature Biomedical Engineering
42 papers in training set
Top 0.1%
9.7%
4
Nature Medicine
117 papers in training set
Top 0.2%
8.1%
5
Science Translational Medicine
111 papers in training set
Top 0.3%
6.1%
50% of probability mass above
6
Science
429 papers in training set
Top 6%
6.1%
7
Cell Systems
167 papers in training set
Top 3%
4.2%
8
Advanced Science
249 papers in training set
Top 6%
3.5%
9
Nature
575 papers in training set
Top 8%
3.0%
10
Nature Genetics
240 papers in training set
Top 3%
3.0%
11
Circulation
66 papers in training set
Top 1%
3.0%
12
Nucleic Acids Research
1128 papers in training set
Top 9%
2.0%
13
Nature Machine Intelligence
61 papers in training set
Top 2%
1.6%
14
Science Advances
1098 papers in training set
Top 21%
1.4%
15
Cell
370 papers in training set
Top 13%
1.3%
16
Nature Biotechnology
147 papers in training set
Top 5%
1.3%
17
Nature Cardiovascular Research
28 papers in training set
Top 0.4%
1.2%
18
Cell Reports Medicine
140 papers in training set
Top 6%
1.2%
19
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 39%
1.2%
20
EMBO Molecular Medicine
85 papers in training set
Top 3%
1.2%
21
Cell Genomics
162 papers in training set
Top 5%
0.9%
22
Nature Neuroscience
216 papers in training set
Top 5%
0.9%
23
Genome Medicine
154 papers in training set
Top 8%
0.8%
24
Scientific Reports
3102 papers in training set
Top 74%
0.8%
25
Communications Biology
886 papers in training set
Top 23%
0.8%