Abstract P1015: Human Blood Proteome Profiles Across Middle and Late Adulthood Exhibit Three Life-Stage Waves Differentially Linked to Age-Related Diseases

Introduction: The circulating proteome has emerged as a crucial resource for predicting biological aging. Recent studies identified life-stage specific waves of proteomic expression; however, little is known about the relations between life-stage proteomic waves and age-related disorders. Hypothesis: Life-stage proteomic waves during middle and late adulthood are differentially associated with diseases and mortality. Methods: The study included a total of 53,105 participants (aged 39-70 years) from the UK Biobank study, with the measurements of 2,922 Olink plasma proteins. We used differential expression-sliding window analysis (DE-SWAN) to analyze differential expression of protein levels within a window of 10 years, while sliding the window in increments of 2 year from middle to old. We constructed a coefficient-weighted protein scores for aging waves, and then used the Cox models to assess the associations between protein scores and the risk of 22 leading diseases and mortality. Results: We identified three distinct life-stage proteomic waves peaking at ages 50, 56, and 67, comprising 943, 708, and 1,103 differentially expressed proteins, respectively. Protein scores from all waves showed significant and varying associations with 10 diseases across neurodegenerative, cardiovascular, autoimmune, respiratory, metabolic, and liver categories. The protein scores of age 56 wave demonstrated the strongest associations with most diseases including ischaemic stroke, ischaemic heart disease, rheumatoid arthritis, systemic lupus erythematosus, chronic obstructive pulmonary disease, lung cancer, and mortality (Hazard ratio [HR] ranges: 1.30-2.10). There were distinct association patterns for specific diseases. For instance, Alzheimer's dementia showed a peak risk at age 56 (HR 1.34), rising from age 50 (HR 1.25) and remaining essentially unchanged at age 67 (HR 1.31). In contrast, vascular dementia displayed consistently higher risk at ages 50 and 56 (HR 1.59), followed by a decline at age 67 (HR 1.48). Liver diseases showed a unique pattern, with the highest risk at age 50 (HR 2.74), followed by a gradual but monotonically decrease through ages 56 (HR 2.38) and 67 (HR 2.00). Conclusions: Our findings indicate life-stage specific association patterns between circulating proteomic profiles and risks of a wide spectrum of diseases, highlighting the essentiality of age-based strategies in prevention and treatment of diseases.

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Journal
Circulation
Published
2025-03-11
DOI
https://doi.org/10.1161/cir.151.suppl_1.p1015
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
Field-Weighted Citation Impact
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article

Abstract P1015: Human Blood Proteome Profiles Across Middle and Late Adulthood Exhibit Three Life-Stage Waves Differentially Linked to Age-Related Diseases

Hao Ma, Yoriko Heianza, Dong‐Qing Ye, Xuan Wang et al.
Circulation
Cardiovascular Health and Risk Factors
article

Abstract P1015: Human Blood Proteome Profiles Across Middle and Late Adulthood Exhibit Three Life-Stage Waves Differentially Linked to Age-Related Diseases

Hao Ma, Yoriko Heianza, Dong‐Qing Ye, Xuan Wang, Jie Zhang, Xiang Li
article en

Abstract

Introduction: The circulating proteome has emerged as a crucial resource for predicting biological aging. Recent studies identified life-stage specific waves of proteomic expression; however, little is known about the relations between life-stage proteomic waves and age-related disorders. Hypothesis: Life-stage proteomic waves during middle and late adulthood are differentially associated with diseases and mortality. Methods: The study included a total of 53,105 participants (aged 39-70 years) from the UK Biobank study, with the measurements of 2,922 Olink plasma proteins. We used differential expression-sliding window analysis (DE-SWAN) to analyze differential expression of protein levels within a window of 10 years, while sliding the window in increments of 2 year from middle to old. We constructed a coefficient-weighted protein scores for aging waves, and then used the Cox models to assess the associations between protein scores and the risk of 22 leading diseases and mortality. Results: We identified three distinct life-stage proteomic waves peaking at ages 50, 56, and 67, comprising 943, 708, and 1,103 differentially expressed proteins, respectively. Protein scores from all waves showed significant and varying associations with 10 diseases across neurodegenerative, cardiovascular, autoimmune, respiratory, metabolic, and liver categories. The protein scores of age 56 wave demonstrated the strongest associations with most diseases including ischaemic stroke, ischaemic heart disease, rheumatoid arthritis, systemic lupus erythematosus, chronic obstructive pulmonary disease, lung cancer, and mortality (Hazard ratio [HR] ranges: 1.30-2.10). There were distinct association patterns for specific diseases. For instance, Alzheimer's dementia showed a peak risk at age 56 (HR 1.34), rising from age 50 (HR 1.25) and remaining essentially unchanged at age 67 (HR 1.31). In contrast, vascular dementia displayed consistently higher risk at ages 50 and 56 (HR 1.59), followed by a decline at age 67 (HR 1.48). Liver diseases showed a unique pattern, with the highest risk at age 50 (HR 2.74), followed by a gradual but monotonically decrease through ages 56 (HR 2.38) and 67 (HR 2.00). Conclusions: Our findings indicate life-stage specific association patterns between circulating proteomic profiles and risks of a wide spectrum of diseases, highlighting the essentiality of age-based strategies in prevention and treatment of diseases.

CirculationVol. 151(Suppl_1)
Tulane University (US), Anhui University (CN)
Openalex Percentile: Top 87%
Cardiovascular Health and Risk Factors
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