Whole-genome sequence association analysis of blood proteins in a longitudinal wellness cohort

Abstract

Background: The human plasma proteome is important for many biological processes and targets for diagnostics and therapy. It is therefore of great interest to understand the interplay of genetic and environmental factors to determine the specific protein levels in individuals and to gain a deeper insight of the importance of genetic architecture related to the individual variability of plasma levels of proteins during adult life. Methods: We have combined whole-genome sequencing, multiplex plasma protein profiling, and extensive clinical phenotyping in a longitudinal 2-year wellness study of 101 healthy individuals with repeated sampling. Analyses of genetic and non-genetic associations related to the variability of blood levels of proteins in these individuals were performed. Results: The analyses showed that each individual has a unique protein profile, and we report on the intraindividual as well as inter-individual variation for 794 plasma proteins. A genome-wide association study (GWAS) using 7.3 million genetic variants identified by whole-genome sequencing revealed 144 independent variants across 107 proteins that showed strong association (P < 6 × 10 −11) between genetics and the inter-individual variability on protein levels. Many proteins not reported before were identified (67 out of 107) with individual plasma level affected by genetics. Our longitudinal analysis further demonstrates that these levels are stable during the 2-year study period. The variability of protein profiles as a consequence of environmental factors was also analyzed with focus on the effects of weight loss and infections. Conclusions: We show that the adult blood levels of many proteins are determined at birth by genetics, which is important for efforts aimed to understand the relationship between plasma proteome profiles and human biology and disease.

Integration of molecular profiles in a longitudinal wellness profiling cohort

“…This agrees with the finding that signatures of circulating proteomes are highly individual specific 45 . In addition, we recently reported that the human blood level of many proteins during adult life is to a large extent affected by genetics, confirming the unique and stable individual patterns of the proteome profiles 46 . Among the most variable proteins we find human growth hormone 1 and 2 (GH1 and GH2) 29 , which may be depending on the large variation in expression levels between men and women with growth hormone levels reported to be sex, age, BMI and exercise dependent 47 .…”

“…The liver marker GGT was identified in relation to inflammatory markers such as IL-6 and this is not unexpected since the liver plays a pivotal role in inflammation by draining circulating lipids (TG and free fatty acids), and triggering cytokines release, which in turn promote CRP hepatocyte production 53 . The strong relationship between CRP and IL-6 has been recently reported along with other cytokines 46 , and the integrated CRP-centric perspective may shed light on CRP roles in inflammatory-based disorders. This study also involves a very comprehensive longitudinal profiling of immune cell composition in healthy individuals 54 .…”

Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes

“…Consistent with previous studies [21][22][23][29][30][31][32] , we found that age and sex had a widespread effect on plasma protein levels, each explaining on average 2.8% of the total observed variability (Figure 1, Supplementary Table 1, Methods). Similar figures were observed for the subset of immune-related proteins, i.e.…”

Longitudinal plasma protein profiling of newly diagnosed type 2 diabetes

“…Of the 52 subjects, 51 (98%) completed the 3-month follow-up visit. The non-diabetes control group consisted of 94 participants that completed the second year in the longitudinal Swedish SciLifeLab SCAPIS Wellness Profiling (S3WP) program [ [9] , [10] , [11] ] and did not have diabetes as judged from repeated fasting glucose and HbA1c measurements as well as baseline OGTT. The control group were examined twice during the same time-period and at the same site as the diabetes subjects (2016–2018, Wallenberg Laboratory, Gothenburg), and the mean values from these examinations were used in the data analysis.…”

“…Recently, we have conducted a large research program to analyze “wellness” in the general population involving the molecular phenotypes of a longitudinal cohort, the Swedish SciLifeLab SCAPIS Wellness Profiling (S3WP) program. This has led to several articles regarding “wellness”, including Zhong et al., [9] , Dodig-Crnkovic et al. [10] and Tebani et al.…”