Increasing Adiposity Is Associated With QTc Interval Prolongation and Increased Ventricular Arrhythmic Risk in the Context of Metabolic Dysfunction: Results From the UK Biobank

Abstract

Background: Small-scale studies have linked obesity (Ob) and metabolic ill-health with proarrhythmic repolarisation abnormalities. Whether these are observed at a population scale, modulated by individuals' genetics, and confer higher risks of ventricular arrhythmias (VA) are not known.

Methods and results: Firstly, using the UK Biobank, the association between adiposity and QTc interval was assessed in participants with a resting 12-lead ECG (n = 23,683), and a polygenic risk score (PRS) was developed to investigate any modulatory effect of genetics. Participants were also categorised into four phenotypes according to the presence (+) or absence (-) of Ob, and if they were metabolically unhealthy (MU+) or not (MU-). QTc was positively associated with body mass index (BMI), body fat (BF), waist:hip ratio (WHR), and hip and waist girths. Individuals' genetics had no significant modulatory effect on QTc-prolonging effects of increasing adiposity. QTc interval was comparably longer in those with metabolic perturbation without obesity (Ob-MU+) and obesity alone (Ob+MU-) compared with individuals with neither (Ob-MU-), and their co-existence (Ob+MU+) had an additive effect on QTc interval. Secondly, for 502,536 participants in the UK Biobank, odds ratios (ORs) for VA were computed for the four clinical phenotypes above using their past medical records. Referenced to Ob-MU-, ORs for VA in Ob-MU+ men and women were 5.96 (95% CI: 4.70-7.55) and 5.10 (95% CI: 3.34-7.80), respectively. ORs for Ob+MU+ were 6.99 (95% CI: 5.72-8.54) and 3.56 (95% CI: 2.66-4.77) in men and women, respectively.

Conclusion: Adiposity and metabolic perturbation increase QTc to a similar degree, and their co-existence exerts an additive effect. These effects are not modulated by individuals' genetics. Metabolic ill-health is associated with a higher OR for VA than obesity.

Keywords: QTc interval; metabolic syndrome; obesity; polygenic risk score; ventricular arrhythmia.

FIGURE 1

Increasing adiposity is associated with increased QTc interval, after adjusting for sociodemographic, co-morbidity, and lifestyle factors. The change in QTc per unit and per standard deviation (SD) increment of in adiposity [quantified by BMI, body mass index (kg/m²); BF, body fat (%); WHR, waist:hip ratio (unit); HG, hip girth (cm); and WG, waist girth (cm)] are shown for the pooled cohort (A) and stratified by sex (B,C). Model 1 adjusted for sociodemographic factors; model 2 adjusted for lifestyle and comorbidities. All results presented reached significance p < 0.001. Results for QTc change per unit increment in WHR is provided in the main text.

FIGURE 2

Polygenic risk score (PRS) for genetically determined QT interval does not modulate the association between increasing adiposity and QTc interval. The change in QTc per unit (A) and per standard deviation (SD) (B) increment in adiposity [quantified by BMI, body mass index (kg/m²); BF, body fat (%); WHR, waist:hip ratio (unit); HG, hip girth (cm); WG, waist girth (cm)] are shown stratified by sex. Model 3 is adjusted for PRS in addition to sociodemographic and lifestyle factors and comorbidities as in model 2 (Figure 1). All results presented for model 3 in (A,B) reached significance p < 0.001. (C) There was no significant interaction between PRS and the adiposity:QTc relationships (P-interaction, PRS with adiposity:QTc) in either sex, suggesting genetics do not modulate the relationship between adiposity and QTc.

FIGURE 3

The QTc interval prolongs comparably with increasing adiposity in men and women stratified by PRS. The change in the QTc per unit and per SD increment of adiposity [quantified by BMI, body mass index (kg/m²); HG, hip girth (cm); WG, waist girth (cm); WHR, waist; hip ratio (unit)] is shown stratified according to low (<25%), intermediate (25–75%), and high (>75%) PRS, representing high, intermediate, and low repolarisation reserve, respectively for men (A) and women (B). All associations between QTc and adiposity measures reached statistical significance with p < 0.001.

FIGURE 4

Obesity and metabolic perturbation are independently associated with longer QTc interval and their effects are additive when they co-exist. Differences in the QTc interval (ΔQTc) referenced to the non-obese metabolically healthy (Ob-MU-) group for each clinical phenotype, in pooled (A) and sex-stratified (B,C) analysis. The p-values for the interactions between PRS and phenotype:QTc are shown in the in-set table (D) Ob, obese; MU, metabolically unhealthy; +, presence; –, absence; CI, confidence interval; PRS, polygenic risk score.