---
_id: '9706'
abstract:
- lang: eng
text: 'Additional file 2: Supplementary Tables. The association of pre-adjusted
protein levels with biological and technical covariates. Protein levels were adjusted
for age, sex, array plate and four genetic principal components (population structure)
prior to analyses. Significant associations are emboldened. (Table S1). pQTLs
associated with inflammatory biomarker levels from Bayesian penalised regression
model (Posterior Inclusion Probability > 95%). (Table S2). All pQTLs associated
with inflammatory biomarker levels from ordinary least squares regression model
(P < 7.14 × 10− 10). (Table S3). Summary of lambda values relating to ordinary
least squares GWAS and EWAS performed on inflammatory protein levels (n = 70)
in Lothian Birth Cohort 1936 study. (Table S4). Conditionally significant pQTLs
associated with inflammatory biomarker levels from ordinary least squares regression
model (P < 7.14 × 10− 10). (Table S5). Comparison of variance explained by ordinary
least squares and Bayesian penalised regression models for concordantly identified
SNPs. (Table S6). Estimate of heritability for blood protein levels as well as
proportion of variance explained attributable to different prior mixtures. (Table
S7). Comparison of heritability estimates from Ahsan et al. (maximum likelihood)
and Hillary et al. (Bayesian penalised regression). (Table S8). List of concordant
SNPs identified by linear model and Bayesian penalised regression and whether
they have been previously identified as eQTLs. (Table S9). Bayesian tests of colocalisation
for cis pQTLs and cis eQTLs. (Table S10). Sherlock algorithm: Genes whose expression
are putatively associated with circulating inflammatory proteins that harbour
pQTLs. (Table S11). CpGs associated with inflammatory protein biomarkers as identified
by Bayesian model (Bayesian model; Posterior Inclusion Probability > 95%). (Table
S12). CpGs associated with inflammatory protein biomarkers as identified by linear
model (limma) at P < 5.14 × 10− 10. (Table S13). CpGs associated with inflammatory
protein biomarkers as identified by mixed linear model (OSCA) at P < 5.14 × 10− 10.
(Table S14). Estimate of variance explained for blood protein levels by DNA methylation
as well as proportion of explained attributable to different prior mixtures -
BayesR+. (Table S15). Comparison of variance in protein levels explained by genome-wide
DNA methylation data by mixed linear model (OSCA) and Bayesian penalised regression
model (BayesR+). (Table S16). Variance in circulating inflammatory protein biomarker
levels explained by common genetic and methylation data (joint and conditional
estimates from BayesR+). Ordered by combined variance explained by genetic and
epigenetic data - smallest to largest. Significant results from t-tests comparing
distributions for variance explained by methylation or genetics alone versus combined
estimate are emboldened. (Table S17). Genetic and epigenetic factors identified
by BayesR+ when conditioning on all SNPs and CpGs together. (Table S18). Mendelian
Randomisation analyses to assess whether proteins with concordantly identified
genetic signals are causally associated with Alzheimer’s disease risk. (Table
S19).'
article_processing_charge: No
author:
- first_name: Robert F.
full_name: Hillary, Robert F.
last_name: Hillary
- first_name: Daniel
full_name: Trejo-Banos, Daniel
last_name: Trejo-Banos
- first_name: Athanasios
full_name: Kousathanas, Athanasios
last_name: Kousathanas
- first_name: Daniel L.
full_name: McCartney, Daniel L.
last_name: McCartney
- first_name: Sarah E.
full_name: Harris, Sarah E.
last_name: Harris
- first_name: Anna J.
full_name: Stevenson, Anna J.
last_name: Stevenson
- first_name: Marion
full_name: Patxot, Marion
last_name: Patxot
- first_name: Sven Erik
full_name: Ojavee, Sven Erik
last_name: Ojavee
- first_name: Qian
full_name: Zhang, Qian
last_name: Zhang
- first_name: David C.
full_name: Liewald, David C.
last_name: Liewald
- first_name: Craig W.
full_name: Ritchie, Craig W.
last_name: Ritchie
- first_name: Kathryn L.
full_name: Evans, Kathryn L.
last_name: Evans
- first_name: Elliot M.
full_name: Tucker-Drob, Elliot M.
last_name: Tucker-Drob
- first_name: Naomi R.
full_name: Wray, Naomi R.
last_name: Wray
- first_name: 'Allan F. '
full_name: 'McRae, Allan F. '
last_name: McRae
- first_name: Peter M.
full_name: Visscher, Peter M.
last_name: Visscher
- first_name: Ian J.
full_name: Deary, Ian J.
last_name: Deary
- first_name: Matthew Richard
full_name: Robinson, Matthew Richard
id: E5D42276-F5DA-11E9-8E24-6303E6697425
last_name: Robinson
orcid: 0000-0001-8982-8813
- first_name: 'Riccardo E. '
full_name: 'Marioni, Riccardo E. '
last_name: Marioni
citation:
ama: Hillary RF, Trejo-Banos D, Kousathanas A, et al. Additional file 2 of multi-method
genome- and epigenome-wide studies of inflammatory protein levels in healthy older
adults. 2020. doi:10.6084/m9.figshare.12629697.v1
apa: Hillary, R. F., Trejo-Banos, D., Kousathanas, A., McCartney, D. L., Harris,
S. E., Stevenson, A. J., … Marioni, R. E. (2020). Additional file 2 of multi-method
genome- and epigenome-wide studies of inflammatory protein levels in healthy older
adults. Springer Nature. https://doi.org/10.6084/m9.figshare.12629697.v1
chicago: Hillary, Robert F., Daniel Trejo-Banos, Athanasios Kousathanas, Daniel
L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, et al. “Additional
File 2 of Multi-Method Genome- and Epigenome-Wide Studies of Inflammatory Protein
Levels in Healthy Older Adults.” Springer Nature, 2020. https://doi.org/10.6084/m9.figshare.12629697.v1.
ieee: R. F. Hillary et al., “Additional file 2 of multi-method genome- and
epigenome-wide studies of inflammatory protein levels in healthy older adults.”
Springer Nature, 2020.
ista: Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson
AJ, Patxot M, Ojavee SE, Zhang Q, Liewald DC, Ritchie CW, Evans KL, Tucker-Drob
EM, Wray NR, McRae AF, Visscher PM, Deary IJ, Robinson MR, Marioni RE. 2020. Additional
file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein
levels in healthy older adults, Springer Nature, 10.6084/m9.figshare.12629697.v1.
mla: Hillary, Robert F., et al. Additional File 2 of Multi-Method Genome- and
Epigenome-Wide Studies of Inflammatory Protein Levels in Healthy Older Adults.
Springer Nature, 2020, doi:10.6084/m9.figshare.12629697.v1.
short: R.F. Hillary, D. Trejo-Banos, A. Kousathanas, D.L. McCartney, S.E. Harris,
A.J. Stevenson, M. Patxot, S.E. Ojavee, Q. Zhang, D.C. Liewald, C.W. Ritchie,
K.L. Evans, E.M. Tucker-Drob, N.R. Wray, A.F. McRae, P.M. Visscher, I.J. Deary,
M.R. Robinson, R.E. Marioni, (2020).
date_created: 2021-07-23T08:59:15Z
date_published: 2020-07-09T00:00:00Z
date_updated: 2023-08-22T07:55:36Z
day: '09'
department:
- _id: MaRo
doi: 10.6084/m9.figshare.12629697.v1
has_accepted_license: '1'
license: https://creativecommons.org/licenses/by/4.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.6084/m9.figshare.12629697.v1
month: '07'
oa: 1
oa_version: Published Version
other_data_license: CC0 + CC BY (4.0)
publisher: Springer Nature
related_material:
record:
- id: '8133'
relation: used_in_publication
status: public
status: public
title: Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory
protein levels in healthy older adults
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2020'
...