Research landscape of genetics in dilated cardiomyopathy: insight from a bibliometric analysis

Background: Dilated cardiomyopathy (DCM) is a heterogeneous myocardial disorder with diverse genetic or acquired origins. Notable advances have been achieved in discovering and understanding the genetics of DCM. This study aimed to depict the distribution of the main research forces, hotspots, and frontiers in the genetics of DCM, thus shaping future research directions. Methods: Based on the documents published in the Web of Science Core Collection database from 2013 to 2022, co-authorship of authors, institutions, and countries/regions, co-citation of references, and co-occurrence of keywords were conducted respectively to present the distribution of the leading research forces, research hotspots, and emerging trends in the genetics of DCM. Results: 4,141 documents were included, and the annual publications have steadily increased. Seidman, Christine E, Meder, Benjamin, Sinagra, Gianfranco were the most productive authors, German Centre for Cardiovascular Research was the most productive institution, and the USA, China, and Germany were the most prolific countries. The co-occurrence of keywords has generated 8 clusters, including DCM, lamin a/c, heart failure, sudden cardiac death, hypertrophic cardiomyopathy, cardiac hypertrophy, arrhythmogenic cardiomyopathy, and next-generation sequencing. Frequent keywords with average publication time after 2019 mainly included arrhythmogenic cardiomyopathy, whole-exome sequencing, RBM 20, phenotype, risk stratification, precision medicine, genotype, and machine learning. Conclusion: The research landscape of genetics in DCM is continuously evolving. Deciphering the genetic profiles by next-generation sequencing and illustrating pathogenic mechanisms of gene variants, establishing innovative treatments for heart failure and improved risk stratification for SCD, uncovering the genetic overlaps between DCM and other inherited cardiomyopathies, as well as identifying genotype-phenotype correlations are the main research hotspots and frontiers in this field.