Crossmark

Machine learning reveals heterogeneous associations between environmental factors and cardiometabolic diseases across polygenic risk scores

Crossref DOI link: https://doi.org/10.1038/s43856-024-00596-7

Published Online: 2024-09-20

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Naito, Tatsuhiko https://orcid.org/0000-0002-2779-4600
Inoue, Kosuke

Namba, Shinichi https://orcid.org/0000-0002-7486-3146
Sonehara, Kyuto https://orcid.org/0000-0002-4536-1761
Suzuki, Ken https://orcid.org/0000-0003-1065-3593
,

Matsuda, Koichi https://orcid.org/0000-0001-7292-2686
Kondo, Naoki

Toda, Tatsushi https://orcid.org/0000-0002-0717-1123
Yamauchi, Toshimasa

Kadowaki, Takashi https://orcid.org/0000-0002-5428-3582
Okada, Yukinori https://orcid.org/0000-0002-0311-8472
License Information

Text and Data Mining valid from 2024-09-20

Version of Record valid from 2024-09-20
More Information

Article History

Received: 12 October 2023

Accepted: 22 August 2024

First Online: 20 September 2024

Competing interests

: The authors declare no competing interests.