We performed a GWAS for metabolites from 14 cohorts from Europe, totaling up to
24,925 individuals (cohorts are described in
Table 1,
Supplementary Table 2 and
Supplementary Notes 1) to include
as many samples with NMR metabolite data and genome-wide SNP array data as
possible. Written informed consent was obtained from all participants. Studies
were approved by the following ethical committees: Ethical Committee of Oulu
University Faculty of Medicine for NFBC 1966; Ethics Committee of the National
Public Health Institute for Health2000 and HBCS; Helsinki University Hospital
Coordinating Ethical Committee for FINRISK and Twins; The KORA studies have been
approved by the ethics committee of the Bavarian Medical Association; NTR,
Central Ethics Committee on Research Involving Human Subjects of the VU
University Medical Center, Amsterdam; EGCUT, Ethics Review Committee on Human
Research of the University of Tartu; ERF, medical ethics board of the Erasmus MC
Rotterdam, the Netherlands; LLS, Medical Ethical Committee of the Leiden
University Medical Centre; and Ethics Committee of the Hospital District of
Southwest Finland for YFS. Individuals under lipid-lowering medication or
pregnant were excluded form the analyses. FINRISK cohorts included genotype
batches PredictCVD, COROGENE, DILGOM and FINRISK97. Estonian biobank had two
genotype batches included in this study: EGCUT and PROTE. Genotype batches were
analysed separately. We used an additive model implemented in analysis software
(
Supplementary Table 2) for
each cohort. All studies were approved by local ethical committees. SNPs were
imputed up to 39 million markers using a 1000 Genomes Project March 2012 version
as described in
Supplementary Table
2 (ref. 27 (
link)). The genomic positions used
throughout this study are human genome build 39. Each cohort was analysed
separately and SNPs with accurate imputation (proper info>0.4) and minor
allele count >3 were combined in fixed-effects meta-analysis using double
genomic control correction, that is, both individual cohort results and
meta-analysis results were corrected for the genomic inflation factor as
implemented in GWAMA28 (
link). Variants, after filtering and
meta-analysis, present in more than seven studies were considered for the final
results. A genome-wide significance level was set to 2.27 ×
10
−9 correcting for 22 independent tests as the
metabolite data are correlated (standard genome-wide significance threshold of 5
× 10
−8/22, the number of principal components
explaining over 95% of the variance in the metabolomics data). The number
of independent tests was derived from the number of principal components that
explain over 95% of variation in the metabolite data. All traits gave
genomic inflation factors in the meta-analysis less than 1.034 showing that
there was little evidence of systematic bias in the test statistics. Quantile
plots for measurements listed in
Supplementary Table 1 are presented in
Supplementary Fig. 5.
Kettunen J., Demirkan A., Würtz P., Draisma H.H., Haller T., Rawal R., Vaarhorst A., Kangas A.J., Lyytikäinen L.P., Pirinen M., Pool R., Sarin A.P., Soininen P., Tukiainen T., Wang Q., Tiainen M., Tynkkynen T., Amin N., Zeller T., Beekman M., Deelen J., van Dijk K.W., Esko T., Hottenga J.J., van Leeuwen E.M., Lehtimäki T., Mihailov E., Rose R.J., de Craen A.J., Gieger C., Kähönen M., Perola M., Blankenberg S., Savolainen M.J., Verhoeven A., Viikari J., Willemsen G., Boomsma D.I., van Duijn C.M., Eriksson J., Jula A., Järvelin M.R., Kaprio J., Metspalu A., Raitakari O., Salomaa V., Slagboom P.E., Waldenberger M., Ripatti S, & Ala-Korpela M. (2016). Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nature Communications, 7, 11122.
