Population-Scale Studies of Protein S Abnormalities and Thrombosis

Abstract

Importance: Clinical decision-making in thrombotic disorders is impeded by long-standing uncertainty regarding the magnitude of venous and arterial thrombosis risk associated with low protein S. Population-scale multiomic datasets offer an unprecedented opportunity to answer questions regarding the epidemiology and clinical impacts of protein S deficiency.

Objective: To evaluate the risk associated with protein S deficiency across multiple thrombosis phenotypes.

Design, setting, and participants: Cross-sectional study using longitudinal population cohorts derived from the UK Biobank (n = 426 436) and the US National Institutes of Health All of Us (n = 204 006) biorepositories. UK Biobank participants were enrolled in 2006-2010 (last follow-up, May 19, 2020) and underwent whole exome sequencing, with a subset (n = 44 431) having protein S levels measured by high-throughput plasma proteomics. Recruitment for All of Us began in 2017 and is ongoing, with participants receiving germline whole genome sequencing. Both cohorts include individual-level data on demographics, laboratory measurements, and clinical outcomes.

Exposure: Presence of rare germline genetic variants in PROS1, segmented by functional impact score (FIS), an in silico prediction of the probability that a genetic variant will disrupt protein activity.

Main outcomes and measures: Firth logistic regression and linear regression modeling were used to evaluate the thrombosis risk associated with low plasma protein S levels and PROS1 variants across a range of FIS ratings.

Results: The UK Biobank cohort was 54.3% female, with a median age of 58.3 (IQR, 50.5-63.7) years at enrollment. Most participants (95.6%) were of European ancestry, and 18 011 had experienced a venous thromboembolism (VTE). In this population cohort, heterozygosity for the highest-risk PROS1 variants with an FIS of 1.0 (nonsense, frameshift, and essential splice site disruptions) was rare (adjusted prevalence, 0.0091% in the UK and 0.0178% in the US) and associated with markedly increased risk of VTE (odds ratio [OR], 14.01; 95% CI, 6.98-27.14; P = 9.09 × 10-11). Plasma proteomics (n = 44 431) demonstrated that carriers of these variants had total protein S levels that were 48.0% of normal (P = .02 compared with noncarriers). In contrast, less damaging missense variants (FIS ≥0.7) occurred more commonly (adjusted prevalence, 0.22% in the UK and 0.20% in the US) and were associated with marginally reduced plasma protein S concentrations and a smaller point estimate for VTE risk (OR, 1.977; 95% CI, 1.552-2.483; P = 1.95 × 10-7). Associations between PROS1 and VTE at both FIS cutoffs were independently validated in the All of Us cohort with similar effect sizes. No association was detected between the presence of coding PROS1 variants and 3 forms of arterial thrombosis: myocardial infarction, peripheral artery disease, and noncardioembolic ischemic stroke. The presence of PROS1 variants correlated poorly with low plasma protein S levels, and protein S deficiency was significantly associated with VTE and peripheral artery disease regardless of PROS1 variant carrier status. The elevated risk of VTE associated with germline loss of function in PROS1 was evident in Kaplan-Meier survival analysis and appeared to persist throughout life (log-rank P = .0005).

Conclusions and relevance: True inherited loss of function in PROS1 is rare but represents a stronger risk factor for VTE in the general population than previously understood. Acquired, environmental, or trans-acting genetic factors are more likely to cause circulating protein S deficiency than coding variation in PROS1, and low plasma protein S is associated with VTE.

Figure 1.. Association of PROS1 Variant Carrier Status With Venous Thromboembolism in the UK Biobank (n = 426 436)

BMI indicates body mass index; CRP, C-reactive protein; FIS, functional impact score; and VTE, venous thromboembolism. Panel A shows the filtering strategy used to identify qualifying rare variants. In total, 1028 individuals had a rare (minor allele frequency ≤0.1%) variant in PROS1, of whom 961 had associated phenotypic data and were included in the primary analysis. In panel B, the yellow arrowhead indicates the variant set that was used in the primary analysis. In panel C, variants with an FIS of 0.7 or greater are shown in yellow and high-confidence loss-of-function variants (FIS = 1.0) in blue. A total of 10 essential splice site variants (FIS = 1.0) fell outside exon boundaries and are not shown. Grayed-out values represent the N- to C-terminal amino acid position along the protein S molecule. In panel D, the association between PROS1 variant carrier status (FIS ≥0.7) and VTE was evaluated in a Firth logistic regression model adjusting for known VTE risk factors as well as sequencing batch and the first 10 principal components of genetic ancestry (not shown). ^aData are mean (SD) or No./total No. BMI is calculated as weight in kilograms divided by height in meters squared. CRP reference range: <1 mg/dL.

Figure 2.. Secondary Analyses of Protein S Deficiency

FIS indicates functional impact score; GADPH, glyceraldehyde 3-phosphate dehydrogenase; HCLOF, high-confidence loss of function; MI, myocardial infarction; NCEIS, noncardioembolic ischemic stroke; L-NPX, linearized NPX; PAD, peripheral artery disease; and VTE, venous thromboembolism. A, Firth logistic regression models adjusting for age, sex, vitamin K antagonist use (plasma protein S <60% analysis only), and the first 10 principal components of genetic ancestry were used to quantify effect size estimates for VTE risk across different case definitions of protein S deficiency in UK Biobank data. B, Firth logistic regression for VTE was repeated across a range of FIS thresholds, adjusted for age, sex, and the first 10 principal components of genetic ancestry. Effect size estimates are nominally significant at all cutoffs displayed (P ≤ 3.06 × 10⁻⁵). The median follow-up interval was 11.14 (IQR, 9.71-12.57) years. C, Cumulative incidence of VTE after study enrollment according to PROS1 variant carrier status and variant FIS (n = 439 765). Historical (prevalent) VTE events occurring prior to study enrollment were excluded. D, Firth logistic regression analysis was performed for each of 4 thrombosis phenotypes, adjusted for age, sex, and ancestry. Separate models were generated to evaluate PROS1 variant carrier status at an FIS of 0.7 or greater and an FIS of 1.0. The reference value (odds ratio, 1.0) reflects PROS1 variant noncarriers (wild type). E, Total plasma protein S levels measured by Olink proteomics according to FIS cutoff (n = 44 431). F, Scatterplot of distribution of total plasma protein S levels vs concentrations of GAPDH, a standard plasma housekeeping protein (n = 44 431). The blue and yellow vertical lines represent the median plasma protein S values for PROS1 variant carriers with an FIS of 0.7 or greater and an FIS of 1.0, respectively.

Figure 3.. Validation Analyses in the National Institutes of Health All of Us Dataset (n = 204 006)

FIS indicates functional impact score; HCLOF, high-confidence loss of function; and VTE, venous thromboembolism. A, Firth logistic regression models for VTE, adjusted for age, sex, and ancestry, were generated to evaluate the effects of PROS1 variant carrier status at an FIS of 0.7 or greater and an FIS of 1.0. B, Kaplan-Meier survival analysis comparing incident VTE occurring after study enrollment in the All of Us dataset (n = 198 535) in PROS1 variant carriers and noncarriers. Historical (prevalent) VTE events occurring prior to study enrollment were excluded.