Comorbidities in hereditary angioedema-A population-based cohort study

Abstract

Background: In hereditary angioedema (HAE), low levels (type 1) or defect in function (type 2) of the serine-protease inhibitor C1 Inhibitor protein results in activation of the classical pathway of the complement system as well as the contact system. Here, we investigated the risk of comorbidities in HAE.

Methods: Individuals with HAE (n = 239; identified through a physician made diagnosis) and a control cohort from the general population (n = 2383; matched for age, gender, and county of residence) were compared with the Swedish inpatient, cause of death, cancer, and prescription registers. Conditional logistic regression was used to analyze the data.

Results: Increased risk of cardiovascular disease (odds ratio [OR] 1.83; 95% confidence interval [CI] 1.32-2.54), including arterial (OR 6.74; 95% CI 1.89-24.06) and venous thromboembolic disease (OR 4.20; 95% CI 2.42-7.23) as well as hypertension (OR 1.64; 95% CI 1.12-2.39) was seen in HAE. There was also an increased number of individuals diagnosed with hyperlipidemia (OR 2.01; 95% CI 1.16-3.50) among HAE patients. Furthermore, the risk of autoimmune disease was increased (OR 1.65; 95% CI 1.15-2.35) being particularly pronounced for systemic lupus erythematosus (OR 71.87; 95% CI 8.80-586.7). The risk of having two or more autoimmune diseases was also higher among HAE patients (p = 0.017). In contrast, the risk of cancer was not increased. Data from the prescription register revealed higher prescription rates of drugs against hypertension, hypothyroidism, and hyperlipidemia among HAE patients.

Conclusions: The results warrant for awareness and prevention of comorbid conditions, in particular, thromboembolic and autoimmune diseases in HAE. Future prophylactic interventions may modify these risks.

Keywords: autoimmunity; cardiovascular disease; complement; epidemiology; hereditary angioedema (HAE).

FIGURE 1

Cumulative incidence of cardiovascular disease comparing individuals suffering from hereditary angioedema (cases) and a background population (controls). All cases and controls (A), men (B), and women (C). Log rank test was used to determine statistical significance. Antihypertensive (D) and lipid‐lowering medication (E) prescribed among cases and controls, respectively, during the time period 2006–2019. Linear mixed regression models were used in order to account for the dependency over calendar year when studying associations between cases and controls and drug use expressed as proportions over calendar year. An interaction term was fitted to address potential changes in the outcome of interest

FIGURE 2

Cumulative incidence of autoimmune disease comparing individuals suffering from hereditary angioedema (cases) and a background population (controls). All cases and controls (A), men (B), and women (C). Log‐rank test was used to determine statistical significance. (D) Prescription of thyroid hormone substitution among cases and controls, respectively, during the time period 2006–2019. Linear mixed regression models were used in order to account for the dependency over calendar year when studying associations between cases and controls and drug use expressed as proportions over calendar year. An interaction term was fitted to address potential changes in the outcome of interest

FIGURE 3

Allergic disease and asthma in hereditary angioedema. In total (A), men (B), and. women (C). Prescription of asthma medication (inhaled corticosteroids and/or b2‐agonists) (D) and antihistamines (E) prescribed among cases and controls respectively during the time period 2006–2019. Linear mixed regression models were used in order to account for the dependency over calendar year when studying associations between cases and controls and drug use expressed as proportions over calendar year. An interaction term was fitted to address potential changes in the outcome of interest