Sliz, Eeva;
Shin, Jean;
Ahmad, Shahzad;
Williams, Dylan M;
Frenzel, Stefan;
Gauß, Friederike;
Harris, Sarah E;
... NeuroCHARGE Working Group, .; + view all
(2022)
Circulating Metabolome and White Matter Hyperintensities in Females and Males.
Circulation
, 145
(14)
pp. 1040-1052.
10.1161/CIRCULATIONAHA.121.056892.
Preview |
Text
Schott_Circulating Metabolome and White Matter Hyperintensities in Females and Males_AAM.pdf Download (1MB) | Preview |
Abstract
BACKGROUND: White matter hyperintensities (WMH) are identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness; WMH are a major risk factor of stroke, dementia, and death. Currently, there are no large-scale studies testing associations between WMH and circulating metabolites. METHODS: We studied up to 9,290 individuals (50.7% females, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion-recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample, and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age*sex, and technical covariates, and our fully adjusted models were additionally adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted p-values (pFDR)<0.05 were considered significant. RESULTS: n the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (pFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in males (pFDR.full.adj=1.40×10^{-7}) and in both the pooled sample (pFDR.full.adj=1.66×10^{-4}) and statin-nontreated (pFDR.full.adj=1.65×10^{-6}) subsample. In males, HPP explained 3-14% of variance in WMH. In males and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins, and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride-to-total-lipids and lower cholesteryl ester-to-total-lipids ratios within these particles. In females, the only significant association was with higher level of glucuronate (pFDR=0.047). CONCLUSIONS: Circulating metabolomic measures, including multiple lipid measures (e.g., lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and non-lipid metabolites (e.g., hydroxyphenylpyruvate, glucuronate) associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain sizable proportion of WMH variance.
Archive Staff Only
 |
View Item |
