Eur J Med Genet. 2026 Oct 12:105108. doi: 10.1016/j.ejmg.2026.105108. Online ahead of print.
ABSTRACT
Takotsubo syndrome (TTS) is a stress-induced left ventricular (LV) cardiomyopathy with an unclear genetic predisposition. We investigated whether single nucleotide polymorphisms (SNPs) previously associated with other cardiomyopathies or LV physiological traits contribute to TTS susceptibility. We conducted a case-control study based on the French multicentre TAKOGENE study (NCT01520610), including 261 unrelated TTS patients and 259 sex- and age-matched controls presenting with acute coronary syndrome. All participants were of European ancestry. A total of 325 SNPs were selected from large-scale genome-wide association studies of cardiomyopathies (n=202) and LV structural/functional traits (n=123), derived from polygenic risk scores. Genotyping was performed using the Infinium OmniExpressExome-8 array. Associations were assessed by logistic regression under an additive model, adjusted for age and sex, with group-specific Bonferroni correction. A sensitivity analysis compared the 261 TTS cases with 973 French population controls from the EPP3 cohort. After quality control and statistical analysis, seventeen SNPs (nine related to cardiomyopathies and eight to LV traits) showed nominal associations (P < 0.05), but none remained significant after group-specific Bonferroni correction. The strongest signal was observed for rs6885658 in the CPEB4 gene (OR 1.62, 95% CI 1.23-2.15; P = 5.8 × 10-4) related to cardiomyopathy traits. The EPP3 population-control sensitivity analysis was consistent with the primary analysis, with no association remaining significant after correction. In conclusion, common genetic variants previously associated with cardiomyopathies or LV traits do not appear to have a major effect on TTS risk. These findings support a disease-specific polygenic architecture of TTS, distinct from that underlying chronic cardiomyopathies and baseline LV traits. Future studies should explore alternative approaches, such as pathway-based analyses focusing on stress-response mechanisms.
PMID:42863705 | DOI:10.1016/j.ejmg.2026.105108