An exposome-wide investigation of 2923 Olink proteins with non-genetic factors in Chinese adults DOI Creative Commons
Andri Iona, Baihan Wang, Jonathan Clarke

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

Abstract Background Previous studies in European populations have identified a large number of genetic variants affecting plasma levels Olink proteins, but little is known about the non-genetic factors influencing particularly Chinese populations. Methods We measured 2,923 using Explore platform, 2,006 participants China Kadoorie Biobank. Linear regression analyses were used to assess cross-sectional associations individual proteins with 37 exposures across multiple domains (e.g. socio-demographic, lifestyle, environmental, sample processing, reproductive factors, clinical measurements, and health-related indices), adjusted for potential confounders testing. These further replicated compared similar Europeans. Results Overall 31 associated at least one protein, age (n=1,154), sex (n=827), BMI (n=869) showing highest associations, followed by frailty index (n=597), SBP (n=479), RPG (n=387), ambient temperature (n=292), HBsAg-positivity (n=282), diet physical activity associations. Likewise, examined, 65% exposure, three (CDHR2, CKB, PLAT) largest baseline characteristics (n=14). The patterns differed sex, chiefly due differences lifestyle factors. Over 90% proteomic key current study UK Conclusions In adults, exposome-wide assessment wide range exposures, which could inform future research priorities analytic strategies.

Language: Английский

An exposome-wide investigation of 2923 Olink proteins with non-genetic factors in Chinese adults DOI Creative Commons
Andri Iona, Baihan Wang, Jonathan Clarke

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

Abstract Background Previous studies in European populations have identified a large number of genetic variants affecting plasma levels Olink proteins, but little is known about the non-genetic factors influencing particularly Chinese populations. Methods We measured 2,923 using Explore platform, 2,006 participants China Kadoorie Biobank. Linear regression analyses were used to assess cross-sectional associations individual proteins with 37 exposures across multiple domains (e.g. socio-demographic, lifestyle, environmental, sample processing, reproductive factors, clinical measurements, and health-related indices), adjusted for potential confounders testing. These further replicated compared similar Europeans. Results Overall 31 associated at least one protein, age (n=1,154), sex (n=827), BMI (n=869) showing highest associations, followed by frailty index (n=597), SBP (n=479), RPG (n=387), ambient temperature (n=292), HBsAg-positivity (n=282), diet physical activity associations. Likewise, examined, 65% exposure, three (CDHR2, CKB, PLAT) largest baseline characteristics (n=14). The patterns differed sex, chiefly due differences lifestyle factors. Over 90% proteomic key current study UK Conclusions In adults, exposome-wide assessment wide range exposures, which could inform future research priorities analytic strategies.

Language: Английский

Citations

1