Genome-wide associations with metabolic syndrome among UK Biobank participants reporting use of second-generation antipsychotics

Abstract

Objectives: Second-generation antipsychotic (SGA) medications are frequently prescribed for mental health conditions; however, they are associated with an increased risk of metabolic syndrome (MetS). We aimed to identify genetic associations of SGA-associated MetS (SGA-MetS) using genome-wide approaches within the UK Biobank. We also set out to evaluate if genetically predicted obesity is associated with an increased risk of SGA-MetS.

Methods: We defined SGA-MetS based on the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) criteria using cross-sectional data from 1318 UK Biobank participants who reported being on an SGA medication. An SGA-MetS case was defined as meeting three or more of the five NCEP-ATP III criteria. We performed a genome-wide association study (GWAS) and gene-based analysis to identify significant variants and gene associations. We computed the polygenic risk score (PGS) for body mass index (BMI) using 2,100,302 variants validated for obesity and metabolic traits from imputed single-nucleotide polymorphism (SNP) data. We tested the association of PGS-BMI with SGA-MetS using logistic regression.

Results: GWAS identified suggestive associations (p < 1 × 10^-5) on chromosome 15. The variant rs12914956 in CHD2 was associated with increased risk of SGA (odds ratio (OR) = 1.73, 95% confidence interval (CI) = 1.4-2.4, p = 3.6 × 10^-7). The gene-based analysis identified significant gene associations with RBFOX1 (p = 4.85 × 10^-7), PTPRD (p = 7.6 × 10^-7), CSMD1 (p = 2.2 × 10^-6), and CHD2 (p = 1.3 × 10^-6). The PGS-BMI (β = 0.23, p = 6.8 × 10^-5), was associated with increased MetS in a model adjusted for age, sex, physical activity, alcohol consumption, antidepressant medications, schizophrenia diagnosis, and principal components of ancestry.

Conclusion: Using a gene-based analysis, we identified significant gene associations with SGA-MetS that have been previously associated with obesity and metabolic traits. The PGS-BMI was associated with MetS, suggesting that a genetic predisposition to a higher BMI may increase the risk of SGA-MetS. Future research should replicate the findings in a larger dataset with more diverse populations.

Keywords: genome wide association study; metabolic syndrome; pharmacogenomics; second generation antipsychotics.

FIGURE 1

Genome wide association results. Panel (A): Manhattan plot; panel (B): Locus zoom plot in chromosome 15. The dashed red line in panel A represents genome‐wide significance for GWAS.

FIGURE 2

Gene‐based association results. This plot was generated using the multi‐marker analysis of GenoMic annotation performed within FUMA. The red dashed line represents genome‐wide significance for the gene‐based analysis.

FIGURE 3

Association of SGA–MetS with BMI PGS. Frequent alcohol consumption was defined as consuming alcohol daily or three or four times weekly, compared to those who reported drinking occasionally or not consuming alcohol. Physical activity was defined as meeting the 2017 UK Physical activity guidelines of 150 min of moderate activity per week or 75 min of vigorous activity. Townsend, Townsend Deprivation Index. The association of variables, including the polygenic risk score (PGS) for body mass index (BMI), is presented as odds ratios with 95% confidence intervals. For PGS BMI, OR represents the association with one standard deviation increase in the PGS of BMI.