OMICs Signatures Linking Persistent Organic Pollutants to Cardiovascular Disease in the Swedish Mammography Cohort

Abstract

Cardiovascular disease (CVD) development may be linked to persistent organic pollutants (POPs), including organochlorine compounds (OCs) and perfluoroalkyl and polyfluoroalkyl substances (PFAS). To explore underlying mechanisms, we investigated metabolites, proteins, and genes linking POPs with CVD risk. We used data from a nested case-control study on myocardial infarction (MI) and stroke from the Swedish Mammography Cohort - Clinical (n = 657 subjects). OCs, PFAS, and multiomics (9511 liquid chromatography-mass spectrometry (LC-MS) metabolite features; 248 proteins; 8110 gene variants) were measured in baseline plasma. POP-related omics features were selected using random forest followed by Spearman correlation adjusted for confounders. From these, CVD-related omics features were selected using conditional logistic regression. Finally, 29 (for OCs) and 12 (for PFAS) unique features associated with POPs and CVD. One omics subpattern, driven by lipids and inflammatory proteins, associated with MI (OR = 2.03; 95% CI = 1.47; 2.79), OCs, age, and BMI, and correlated negatively with PFAS. Another subpattern, driven by carnitines, associated with stroke (OR = 1.55; 95% CI = 1.16; 2.09), OCs, and age, but not with PFAS. This may imply that OCs and PFAS associate with different omics patterns with opposite effects on CVD risk, but more research is needed to disentangle potential modifications by other factors.

Keywords: cardiovascular disease; genetics; metabolomics; multiomics; nested case-control study; persistent organic pollutants; proteomics.

Figure 1

Flowchart of the analytical approach and the number of samples available in each step. Abbreviations: CVD, cardiovascular disease; MI, myocardial infarction; OC, organochlorine compounds; PCA, principal component analysis; PFAS, perfluoroalkyl and polyfluoroalkyl substances.

Figure 2

POP- and CVD-related proteins and metabolite features and their associations with composite CVD, MI, and stroke and their correlations with exposure component scores (OC_C and PFAS_C). Associations are presented as log odds ratio and 95% confidence intervals derived from model 1 (matching factors age and sample year, education, family history of CVD, smoking habits, physical activity, and healthy diet score) and sensitivity model 2 (additionally adjusted for BMI, HDL, LDL, triglycerides, and hypertension). Correlations are adjusted for age, sample year, education, healthy diet score, and additionally for BMI for the OC components. Ordered by communities (from Figure 3). Abbreviations: CVD, cardiovascular disease; Cer, ceramide; DG, diacylglycerol; DHA, docosahexaenoic acid; FGF-21, fibroblast growth factor 21; GDF-15, growth differentiation factor 15; GPL, glycerophospholipid; IL-6, interleukin 6; LDL-receptor, low-density lipoprotein receptor; MI, myocardial infarction; OC-C, organochlorine compound component; OPG, osteoprotegerin; PFAS-C, per- and polyfluoroalkyl substance component; TG, triglyceride; tPA, tissue plasminogen activator; uPAR, urokinase-type plasminogen activator receptor.

Figure 3

Estimated network structure of the Gaussian Graphical Model with partial Spearman correlation coefficients of (a) 29 OC- and CVD-related omics features and (b) 12 PFAS- and CVD-related omics features. Detected communities (Spinglass algorithm) share the same color. Abbreviations: Cer, ceramide; DG, diacylglycerol; DHA, docosahexaenoic acid; FGF-21, fibroblast growth factor 21; GDF-15, growth differentiation factor 15; GPL, glycerophospholipid; IL-6, interleukin 6; LDL-receptor, low-density lipoprotein receptor; MI, myocardial infarction; OC-C, organochlorine compound component; OPG, osteoprotegerin; PFAS-C, per- and polyfluoroalkyl substance component; RN, reverse-phase negative mode; RP, reverse-phase positive mode; TG, triglyceride; tPA, tissue plasminogen activator; uPAR, urokinase-type plasminogen activator receptor.

Figure 4

Associations of POP- and CVD-related omics subpatterns 1 and 2 with exposure components (OC_C and PFAS_C), age, BMI, lipids, and CVD outcomes. The triplot represents the 41 selected omics features and their (1) correlations with POP exposure components, age, and BMI and their (2) risk of MI and stroke. Correlations are unadjusted or adjusted for age, sample year, education, healthy diet score, and additionally for BMI for the OC_C. Associations are presented as odds ratio and 95% confidence intervals derived from model 1 (matching factors age and sample year, education, family history of CVD, smoking habits, physical activity, and healthy diet score). Abbreviations: Cer, ceramide; DG, diacylglycerol; DHA, docosahexaenoic acid; FGF-21, fibroblast growth factor 21; GDF-15, growth differentiation factor 15; GPL, glycerophospholipid; MI, myocardial infarction; OC-C, organochlorine compound component; PFAS-C, per- and polyfluoroalkyl substance component; TG, triglyceride; tPA, tissue plasminogen activator; uPAR, urokinase-type plasminogen activator receptor.