Back

Molecular and Cellular Determinants of Human Iron Overload Cardiomyopathy

Modak, S.; Greenberg, L.; Stump, W. T.; Greenberg, A. E.; Huebsch, N.; Greenberg, M. J.

2026-02-04 biophysics
10.64898/2026.02.02.703307 bioRxiv
Show abstract

Iron overload cardiomyopathy (IOC) is a serious heart condition that is caused by elevated levels of systemic iron. IOC is characterized by both systolic and diastolic dysfunction as well as arrhythmias. It has been challenging to isolate the cardiac-specific cellular and molecular mechanisms driving IOC because the disease affects multiple interconnected organ systems. Here, we leverage stem cell technologies, cardiac tissue engineering, and protein reconstitution assays to model key aspects of human IOC in vitro and to probe the cellular and molecular mechanisms driving cardiac dysfunction. We demonstrate that human engineered heart tissues consisting of both cardiomyocytes and cardiac fibroblasts faithfully recapitulate key aspects of the human disease, including reduced systolic function, impaired diastolic function, and increased prevalence of arrhythmogenic events. We demonstrate that while both cardiomyocytes and cardiac fibroblasts show increased intracellular iron levels, leading to reduced viability, cardiomyocytes show higher levels of iron accumulation and higher levels of reactive oxygen species production. Moreover, we show that in a tissue, iron overload has little effect on the action potential kinetics; however, it directly impacts the amplitude and kinetics of the calcium transient, potentially driving arrhythmogenesis. Finally, we demonstrate that iron overload decreases force production, in part, through oxidative damage of sarcomeric proteins and direct iron-based inhibition of myosin. In summary, our results reveal new insights into the cellular and molecular mechanisms of human IOC pathogenesis, and they establish new in vitro models that can be harnessed to faithfully recapitulate key aspects of the human disease phenotype. HighlightsO_LIContractile aspects of iron overload cardiomyopathy have been difficult to study in vitro. C_LIO_LIWe developed engineered heart tissues to model key aspects of the human disease. C_LIO_LIIn vitro iron overload reduces contractility and induces arrhythmogenesis. C_LIO_LIIron differentially affects cardiomyocytes and cardiac fibroblasts. C_LIO_LIIron overload directly impacts the actomyosin contractile apparatus. C_LI

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Circulation Research
39 papers in training set
Top 0.1%
28.3%
2
Circulation
66 papers in training set
Top 0.2%
12.8%
3
Journal of Molecular and Cellular Cardiology
39 papers in training set
Top 0.1%
10.7%
50% of probability mass above
4
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 10%
6.5%
5
Nature Communications
4913 papers in training set
Top 32%
5.0%
6
eLife
5422 papers in training set
Top 33%
2.4%
7
Scientific Reports
3102 papers in training set
Top 55%
1.8%
8
Cell Reports
1338 papers in training set
Top 23%
1.7%
9
Cell
370 papers in training set
Top 11%
1.7%
10
Nature Cardiovascular Research
28 papers in training set
Top 0.4%
1.3%
11
Science Translational Medicine
111 papers in training set
Top 4%
1.3%
12
iScience
1063 papers in training set
Top 23%
1.1%
13
EMBO Molecular Medicine
85 papers in training set
Top 3%
1.0%
14
Advanced Science
249 papers in training set
Top 16%
0.9%
15
JCI Insight
241 papers in training set
Top 6%
0.9%
16
Circulation: Genomic and Precision Medicine
42 papers in training set
Top 1.0%
0.9%
17
Development
440 papers in training set
Top 3%
0.8%
18
Biophysical Journal
545 papers in training set
Top 5%
0.8%
19
Nature Biomedical Engineering
42 papers in training set
Top 2%
0.8%
20
Cardiovascular Research
33 papers in training set
Top 1.0%
0.8%
21
Science Advances
1098 papers in training set
Top 29%
0.8%
22
Journal of General Physiology
56 papers in training set
Top 0.2%
0.8%
23
PLOS Computational Biology
1633 papers in training set
Top 25%
0.7%
24
Neuron
282 papers in training set
Top 9%
0.7%
25
Cells
232 papers in training set
Top 7%
0.7%
26
Cell Reports Medicine
140 papers in training set
Top 9%
0.7%
27
Nature
575 papers in training set
Top 17%
0.7%
28
Science
429 papers in training set
Top 21%
0.7%
29
Developmental Cell
168 papers in training set
Top 13%
0.5%