1. Genetics and Genomics

Associations of genetic and infectious risk factors with coronary heart disease

  1. Flavia Hodel
  2. Zhi Ming Xu
  3. Christian Wandall Thorball
  4. Roxane de La Harpe
  5. Prunelle Letang-Mathieu
  6. Nicole Brenner
  7. Julia Butt
  8. Noemi Bender
  9. Tim Waterboer
  10. Pedro Manuel Marques-Vidal
  11. Peter Vollenweider
  12. Julien Vaucher
  13. Jacques Fellay  Is a corresponding author
  1. Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Switzerland
  2. Swiss Institute of Bioinformatics, Switzerland
  3. Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Switzerland
  4. Department of Medicine, Internal medicine, Lausanne University Hospital and University of Lausanne, Switzerland
  5. Division of Infections and Cancer Epidemiology, German Cancer Research Center, Germany
https://doi.org/10.7554/eLife.79742
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Cite this article
  1. Flavia Hodel
  2. Zhi Ming Xu
  3. Christian Wandall Thorball
  4. Roxane de La Harpe
  5. Prunelle Letang-Mathieu
  6. Nicole Brenner
  7. Julia Butt
  8. Noemi Bender
  9. Tim Waterboer
  10. Pedro Manuel Marques-Vidal
  11. Peter Vollenweider
  12. Julien Vaucher
  13. Jacques Fellay
(2023)
Associations of genetic and infectious risk factors with coronary heart disease
eLife 12:e79742.
https://doi.org/10.7554/eLife.79742
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6 figures, 3 tables and 1 additional file

Figures

Figure 1
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Prevalence of tested pathogens in CoLaus|PsyCoLaus study in participants with and without coronary heart disease (CHD).

Overall serostatus for the 22 pathogens are shown in the CHD-positive group (individuals with at least one CHD event during follow-up) or CHD-negative group. The y-axis indicates the relative percentage within each group. Pathogens are ranked in ascending order of overall seropositivity (all individuals combined).

Figure 1—source data 1

Data underlying Figure 1.

https://cdn.elifesciences.org/articles/79742/elife-79742-fig1-data1-v1.xlsx
Figure 2
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Hazard ratio (HR) and 95% confidence intervals of coronary heart disease (CHD) occurrence according to associated factors.

HR > 1 indicates an increased risk of CHD, whereas HR < 1 indicates a protective effect. p-Values (p) for each factor based on the multivariable Cox regression are shown.

Figure 2—source data 1

Data underlying Figure 2.

https://cdn.elifesciences.org/articles/79742/elife-79742-fig2-data1-v1.xlsx
Appendix 2—figure 1
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Pairwise correlations between quantitative characteristics significantly associated with coronary heart disease (CHD) risk in the univariable Cox proportional hazard models.

Pearson’s correlation values are displayed, along with linear fits between variables.

Appendix 2—figure 2
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Strength of association for each pair of categorical variables significantly associated with coronary heart disease (CHD) risk in univariable Cox proportional hazard models.

Cramer’s V values are displayed.

Appendix 2—figure 3
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Graphical test of proportional hazards assumption (Schoenfeld test).

The graphs show the scaled Schoenfeld residuals over time. The p-values (p) of the variables and the model as a whole were shown in the plot. A significant p-value (< 0.05) indicates that the variable violates the proportional hazard assumption. The solid line represents the smoothing fitted spline, and the dashed lines the confidence bands at two standard errors. Global Schoenfeld test p=0.58.

Appendix 2—figure 4
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Distribution of individuals according to their exposure to infectious agents (pathogen burden).

Bar plot showing the number of participants for each cumulative number of positive serological results, reflecting simultaneous ongoing chronic/latent infections. Sample sizes for each group are shown above the box.

Tables

Table 1
Baseline characteristics of 3459 CoLaus|PsyCoLaus participants by coronary heart disease (CHD) cases and controls.

p-Values are based on the t-test for continuous variables and Fisher’s exact test for categorical variables comparing the CHD cases and controls group.

OverallN = 3249 (100%)ControlsN = 3249 (93.93%)CHD casesN = 210 (6.07%)p
Baseline characteristics
Age (mean [SD])52.83 [10.48]52.34 [10.36]60.34 [9.53]<0.001
BMI (mean [SD])25.51 [4.31]25.41 [4.27]27.11 [4.62]<0.001
Systolic blood pressure (mean [SD])129.04 [18.40]128.32 [18.01]140.18 [20.60]<0.001
HDL cholesterol (mean [SD])1.66 [0.43]1.67 [0.43]1.49 [0.41]<0.001
LDL cholesterol (mean [SD])3.34 [0.92]3.33 [0.92]3.48 [0.91]0.018
Total cholesterol (mean [SD])5.60 [1.03]5.59 [1.02]5.73 [1.04]0.051
Sex = male (%)1592 (46.0)1448 (44.6)144 (68.6)<0.001
Statin = yes (%)296 (8.6)242 (7.4)54 (25.7)<0.001
Average gross monthly income (in CHF):0.029
<2999 (%)178 (5.1)161 (5.0)17 (8.1)
3000–4999 (%)452 (13.1)425 (13.1)27 (12.9)
5000–6999 (%)552 (16.0)517 (15.9)35 (16.7)
7000–9499 (%)504 (14.6)468 (14.4)36 (17.1)
9500–13,000 (%)338 (9.8)323 (9.9)15 (7.1)
>13,000 (%)344 (9.9)335 (10.3)9 (4.3)
Refused or missing (%)1091 (31.5)1020 (31.4)71 (33.8)
Smoking = yes (%)883 (25.5)820 (25.2)63 (30.0)0.146
Genetics
CHD-PRS (mean [SD])0.00 [1.00]−0.02 [0.99]0.26 [1.01]<0.001
Biomarkers of inflammation
hs-CRP (mean [SD])0.09 [0.46]0.08 [0.46]0.22 [0.44]<0.001
TNF-α (mean [SD]) – 63 NAs0.46 [0.38]0.46 [0.38]0.53 [0.35]0.013
IL-1β (mean [SD]) – 1’319 NAs0.17 [0.64]0.17 [0.64]0.14 [0.67]0.637
IL-6 (mean [SD]) – 294 NAs0.24 [0.58]0.24 [0.58]0.28 [0.55]0.398
Persistent pathogens
Human polyomaviruses:
BKPyV = seropositive (%)2912 (84.2)2735 (84.2)177 (84.3)1.000
JCPyV = seropositive (%)1812 (52.4)1696 (52.2)116 (55.2)0.434
HPyV6 = seropositive (%)2948 (85.2)2759 (84.9)189 (90.0)0.056
WUPyV = seropositive (%)3309 (95.7)3105 (95.6)204 (97.1)0.362
Human herpes viruses:
HSV-1 = seropositive (%)2547 (73.6)2373 (73.0)174 (82.9)0.002
HSV-2 = seropositive (%)601 (17.4)564 (17.4)37 (17.6)0.998
CMV = seropositive (%)1868 (54.0)1756 (54.0)112 (53.3)0.897
EBV = seropositive (%)3350 (96.8)3147 (96.9)203 (96.7)1.000
HHV-6A = seropositive (%)865 (25.0)800 (24.6)65 (31.0)0.049
HHV-6B = seropositive (%)1373 (39.7)1295 (39.9)78 (37.1)0.480
HHV-7 = seropositive (%)1846 (53.4)1746 (53.7)100 (47.6)0.099
KSHV = seropositive (%)141 (4.1)133 (4.1)8 (3.8)0.983
VZV = seropositive (%)3047 (88.1)2853 (87.8)194 (92.4)0.061
Parvovirus:
PVB-19 = seropositive (%)2420 (70.0)2277 (70.1)143 (68.1)0.595
Bacteria:
C. trachomatis = seropositive (%)1213 (35.1)1120 (34.5)93 (44.3)0.005
F. nucleatum = seropositive (%)520 (15.0)473 (14.6)47 (22.4)0.003
H. pylori = seropositive (%)685 (19.8)645 (19.9)40 (19.0)0.846
S. gallolyticus = seropositive (%)135 (3.9)130 (4.0)5 (2.4)0.322
Parasite:
T. gondii = seropositive (%)1445 (41.8)1349 (41.5)96 (45.7)0.262
Appendix 1—table 1
Characteristics of infectious agent-specific antigens used on the Multiplex Serology platform in CoLaus|PsyCoLaus.
FamilyPathogenAntigen(Predicted) functionDef. of seropositivity is based onReference
Human polyomavirusesBKVVP1Major capsid proteinNAKjaerheim et al., 2007; Gossai et al., 2016; Robles et al., 2015
JCVVP1Major capsid proteinNAKjaerheim et al., 2007; Gossai et al., 2016; Robles et al., 2015
HPyV6VP1Major capsid proteinNAKjaerheim et al., 2007; Gossai et al., 2016; Robles et al., 2015
WUPyVVP1Major capsid proteinNAKjaerheim et al., 2007; Gossai et al., 2016; Robles et al., 2015
Human herpes virusesCMVpp150Tegument proteinAt least two positiveBrenner et al., 2018
pp52DNA binding protein
pp28Capsid protein
EBVZEBRAReplication activatorAt least two positiveBrenner et al., 2018
EA-DReplication (polymerase accessory subunit)
VCA p18Capsid protein
EBNA1Replication, latent viral infection
HHV-6IE1BPotential transactivatorAny HHV-6=at least one positive HHV-6A=IE1A and/or p100HHV-6B=IE1B and/or p101KBassig et al., 2018; Engdahl et al., 2019; Freuer et al., 2020
IE1APotential transactivator
p101KPotential tegument protein
p100Potential tegument protein
HHV-7U14Potential tegument proteinNAValidation ongoing
HSV-1gGMembrane glycoproteinNABrenner et al., 2019a
HSV-2mgGMembrane glycoproteinNABrenner et al., 2019a
KSHVLANA3Replication and long-term persistenceAt least one positiveValidation ongoing
K8.1Structural glycoprotein
VZVgE/gIEnvelope glycoproteinNABrenner et al., 2019a
ParvovirusB19VP1uniqueMinor capsid proteinNABrenner et al., 2019b
Rubella virus*RVE1Class II viral fusion proteinNABrenner et al., 2019b
C. trachomatisCtpGP3Virulence factorNATrabert et al., 2019
C. tetani*CtTetXToxoid (heavy chain)NABrenner et al., 2019b
Corynebacterium diphtheriae*CdDTAToxoid (intracellular)NABrenner et al., 2019b
F. nucleatumFnFn0264Adhesin (FadA)At least one positive (experimental)Butt et al., 2019
Fn1449Type Va secretion system (Fap2)
Fn1859Porin (FomA)
H. pyloriHpHP 10 GroELChaperoninAt least three positiveMichel et al., 2009
HP 73 UreaseAUrease alpha subunit
HP 547 CagAPathogenesis
HP 875 CatalaseDetoxification
HP 887 VacAPathogenesis
HP 1564 OMPCell envelope
S. gallolyticusSgGallo2178Pil1 pilus subunit (major pilin)NAButt et al., 2016; Butt et al., 2017
T. gondiiTgp22Surface proteinAt least one positiveBrenner et al., 2019a
sag-1Surface protein
  1. *

    Pathogens not taken forward due to lack of vaccination history in CoLaus|PsyCoLaus and/or the difficulty in identifying target antigens to ensure specificity of the test.

Appendix 1—table 2
Association of risk factors with coronary heart disease (CHD) based on the univariable Cox proportional hazard analyses.
VariableHR* (95% CI)*p
Baseline characteristics
SCORE21.72 (1.61–1.85)2.87×10-61
Statin3.82 (2.80–5.22)3.13×10-17
Average gross monthly income0.85 (0.76–0.96)7.27×10-3
Genetics
CHD-PRS1.32 (1.16–1.51)4.29×10-5
PC174-28 (0.03–195096)0.28
PC20.12 (00.0–728)0.64
PC30.33 (0.00–1131)0.79
Biomarkers of inflammation
hs-CRP†1.91 (1.42–2.55)1.51×10-5
TNF-α†1.43 (1.05–1.96)2.46×10-2
IL-1β†0.93 (0.70–1.25)0.64
IL-6†1.10 (0.88–1.37)0.42
Human polyomaviruses
BKPyV1.05 (0.72–1.52)0.80
JCPyV1.14 (0.87–1.50)0.35
HPyV61.66 (1.06–2.61)2.74×10-2
WUPyV1.45 (0.65–3.27)0.37
Human herpes viruses
HSV-11.88 (1.30–2.68)6.52×10-4
HSV-21.05 (0.74–1.50)0.78
CMV1.00 (0.76–1.31)0.99
EBV0.97 (0.46–2.06)0.94
HHV-6A1.39 (1.03–1.86)2.89×10-2
HHV-6B0.93 (0.70–1.23)0.59
HHV-70.79 (0.60–1.03)8.33×10-2
KSHV0.89 (0.44–1.80)0.74
VZV1.70 (1.02–2.82)4.25×10-2
Parvovirus
PVB-190.90 (0.68–1.21)0.49
Bacteria.
C. trachomatis1.45 (1.11–1.91)7.22×10-3
F. nucleatum1.66 (1.20–2.29)2.32×10-3
H. pylori0.95 (0.67–1.34)0.78
S. gallolyticus0.62 (0.26–1.51)0.29
Parasite
T. gondii1.17 (0.90–1.54)0.25
Pathogen burden1.11 (1.03–1.18)3.25×10−3
  1. *

    HR = hazard ratio, CI = confidence interval.

  2. †

    log10-transformed.

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  1. Flavia Hodel
  2. Zhi Ming Xu
  3. Christian Wandall Thorball
  4. Roxane de La Harpe
  5. Prunelle Letang-Mathieu
  6. Nicole Brenner
  7. Julia Butt
  8. Noemi Bender
  9. Tim Waterboer
  10. Pedro Manuel Marques-Vidal
  11. Peter Vollenweider
  12. Julien Vaucher
  13. Jacques Fellay
(2023)
Associations of genetic and infectious risk factors with coronary heart disease
eLife 12:e79742.
https://doi.org/10.7554/eLife.79742