Variation in the SERPINA6/SERPINA1 locus alters morning plasma cortisol, hepatic corticosteroid binding globulin expression, gene expression in peripheral tissues, and risk of cardiovascular disease

Abstract

The stress hormone cortisol modulates fuel metabolism, cardiovascular homoeostasis, mood, inflammation and cognition. The CORtisol NETwork (CORNET) consortium previously identified a single locus associated with morning plasma cortisol. Identifying additional genetic variants that explain more of the variance in cortisol could provide new insights into cortisol biology and provide statistical power to test the causative role of cortisol in common diseases. The CORNET consortium extended its genome-wide association meta-analysis for morning plasma cortisol from 12,597 to 25,314 subjects and from ~2.2 M to ~7 M SNPs, in 17 population-based cohorts of European ancestries. We confirmed the genetic association with SERPINA6/SERPINA1. This locus contains genes encoding corticosteroid binding globulin (CBG) and α1-antitrypsin. Expression quantitative trait loci (eQTL) analyses undertaken in the STARNET cohort of 600 individuals showed that specific genetic variants within the SERPINA6/SERPINA1 locus influence expression of SERPINA6 rather than SERPINA1 in the liver. Moreover, trans-eQTL analysis demonstrated effects on adipose tissue gene expression, suggesting that variations in CBG levels have an effect on delivery of cortisol to peripheral tissues. Two-sample Mendelian randomisation analyses provided evidence that each genetically-determined standard deviation (SD) increase in morning plasma cortisol was associated with increased odds of chronic ischaemic heart disease (0.32, 95% CI 0.06-0.59) and myocardial infarction (0.21, 95% CI 0.00-0.43) in UK Biobank and similarly in CARDIoGRAMplusC4D. These findings reveal a causative pathway for CBG in determining cortisol action in peripheral tissues and thereby contributing to the aetiology of cardiovascular disease.

Fig. 1

a Manhattan plot of −log10 P values of the SNP-based association analysis of morning plasma cortisol (n = 25,314). The locus on chr14 spans SERPINA6 and SERPINA1 genes; no other loci reached genome-wide significance. b, c Zoomed in Manhattan plot (LocusZoom plot) of −log10 P values of the SNP-based association analysis of morning plasma cortisol (n = 25,314). These show two (of the four) LD blocks (r² > 0.3) in this locus

Fig. 2

Tissue-specific association of cortisol-related SNPs with gene expression in STARNET. a LocusZoom plot showing genomic loci of given SNPs against measure of significance (−log10 (p value)) for an eQTL analysis in liver for all SNPs within 100 Kb of SERPINA6. Squares represent the 21 significant cis-eQTLs (q ≤ 0.05) that are also at genome-wide significance in CORNET (p ≤ 5 × 10⁻⁸). b Genotypic effect of representative SNP for LD block 2 (rs2736898) on SERPINA6 gene expression in liver. c Global tissue-specific effects on gene expression for rs2736898 represented as Q–Q plots for genes in liver, subcutaneous fat and visceral abdominal fat describing observed p values vs. those expected by chance. Deviation from expected uniform distribution described by Kolmogorov–Smirnov test p value (Ks-test)

Fig. 3

Scatterplot showing colocalisation of joint signal from CORNET GWAMA and SERPINA6 cis-eQTLs from STARNET-liver. Includes all SNPs within 100 Kb of SERPINA6 that were present in both datasets (n = 535). Colour bar indicates degree of LD with rs2736898. Formal colocalisation analysis with Coloc indicates 99.2% probability of the presence of a shared causal variant within LD block 2 mediating GWAMA and SERPINA6 cis-eQTL signal

Fig. 4

Causal estimates of a 1 SD increase in morning plasma cortisol on relevant disease and trait outcomes. Estimates are from two-sample Mendelian randomisation analyses using inverse variance weighting to combine estimates from each genetic variant. a Outcomes from UK Biobank (chronic ischaemic heart disease, cases = 8755, controls = 328,444; myocardial infarction, cases = 7790, controls = 328,893; diabetes mellitus, cases = 16,183, controls = 320,290; body mass index, sample size = 336,107; osteoporosis, cases = 5266, controls = 331,893); (b) Equivalent outcomes from non-UK Biobank sources—CARDIoGRAMplusC4D (coronary heart disease, cases = 60,801, controls = 123,504; myocardial infarction, cases = 43,676, controls = 128,199), DIAGRAM (type 2 diabetes, cases = 26,488, controls = 83,964), GIANT (BMI, sample size = 339,224) and GEFOS (lumber spine mineral density, sample size = 28,498)

Fig. 5

Bidirectional causal estimates of the effect of the disease or trait on morning plasma cortisol. Estimates are from two-sample Mendelian randomisation analyses using inverse variance weighting to combine estimates from each genetic variant