The complex nature of polygenic diseases encompasses a wide range of related pathologies arising from heterogeneous molecular mechanisms and exhibiting a diversity of disease phenotypes. In fact, individuals diagnosed with the same disease can have vastly differing pathophenotypes as a consequence of genomic context and novel molecular interactions governed by personalized omic networks or reticulotypes. This variety of manifestations poses significant challenges in the development of precision treatments. The increasing availability of deep phenomics and multiomics data from select patient populations (such as those with common cardiovascular diseases) has stimulated the development of a variety of computational disease subtyping approaches to identify distinct subgroups with unique underlying pathogenic mechanisms. In this presentation, I will outline the essential elements of the computational approaches useful in selecting, integrating, and clustering multiomic and phenomic data, and do so with examples from heart failure and atherothrombosis. The strategies presented and those in development will ultimately contribute to the ongoing evolution of precision medicine.
Maiorino Enrico, Loscalzo Joseph. Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping. Arteriosclerosis, Thrombosis, and Vascular Biology. Vol. 43(7):1111–1123. 2023. Ovid Technologies (Wolters Kluwer Health). [Cross Ref]
Wang Rui-Sheng, Maron Bradley A., Loscalzo Joseph. Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases. Arteriosclerosis, Thrombosis, and Vascular Biology. Vol. 43(4):493–503. 2023. Ovid Technologies (Wolters Kluwer Health). [Cross Ref]
Lilja Sandra, Li Xinxiu, Smelik Martin, Lee Eun Jung, Loscalzo Joseph, Marthanda Pratheek Bellur, Hu Lang, Magnusson Mattias, Sysoev Oleg, Zhang Huan, Zhao Yelin, Sjöwall Christopher, Gawel Danuta, Wang Hui, Benson Mikael. Multi-organ single-cell analysis reveals an on/off switch system with potential for personalized treatment of immunological diseases. Cell Reports Medicine. Vol. 4(3)2023. Elsevier BV. [Cross Ref]