Metabolomics is a systems biology tool providing small molecule signatures of disease etiology. In order to estimate the biologic variability of the human serum metabolome, this study calculated intraclass correlation coefficients (ICCs) for 178 stably-detected metabolites measured by untargeted chromatography/mass spectrometry. We studied a subsample of 60 participants (57% males, 70% Caucasians, aged 73.77±5.3 years) in the Atherosclerosis Risk in Communities (ARIC) Study who provided two fasting serum samples 4–6 weeks apart. The median ICC across all metabolites was 0.60, and 82% of metabolites had at least fair variability (i.e., ICC>= 0.40). There was variation in the medium-term variability among metabolites, with those in the pathways of amino acid and lipid metabolism showing relatively high ICCs, and those in the carbohydrate pathway showing relatively low ICCs. The results of this study provide a valuable resource for future study design and outcome interpretation of mass spectrometry-based metabolomic studies in epidemiology.
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References
1.
AbramsJJ, GinsbergH, and GrundySM. (1982). Metabolism of cholesterol and plasma triglycerides in nonketotic diabetes mellitus. Diabetes, 31, 903–910.
2.
BennionLJ, and GrundySM. (1977). Effects of diabetes mellitus on cholesterol metabolism in man. N Engl J Med, 296, 1365–1371.
3.
BijariPB, AntigaL, WassermanBA, and SteinmanDA. (2011). Scan-Rescan reproducibility of carotid bifurcation geometry from routine contrast-enhanced MR angiography. J Magn Reson Imaging, 33, 482–489.
4.
BrufauG, StellaardF, PradoK, et al. (2010). Improved glycemic control with colesevelam treatment in patients with type 2 diabetes is not directly associated with changes in bile acid metabolism. Hepatology, 52, 1455–1464.
5.
CatellierDJ, AleksicN, FolsomAR, and BoerwinkleE. (2008). Atherosclerosis Risk in Communities (ARIC) Carotid MRI flow cytometry study of monocyte and platelet markers: Intraindividual variability and reliability. Clin Chem, 54, 1363–1371.
6.
ChamblessLE, McMahonRP, BrownSA, PatschW, HeissG, and ShenYL. (1992). Short-term intraindividual variability in lipoprotein measurements: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Epidemiol, 136, 1069–1081.
7.
ChengS, RheeEP, LarsonMG, et al. (2012). Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation, 125, 2222–2231.
8.
EvansAM, DehavenCD, BarrettT, MitchellM, and MilgramE. (2009). Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem, 81, 6656–6667.
9.
EvansDA, BennettDA, WilsonRS, et al. (2003). Incidence of Alzheimer disease in a biracial urban community: Relation to apolipoprotein E allele status. Arch Neurol, 60, 185–189.
10.
FleissJ. (1986). The Design and Analysis of Clinical Experiments. John Wiley & Sons, New York, NY.
11.
FloegelA, DroganD, Wang-SattlerR, et al. (2011). Reliability of serum metabolite concentrations over a 4-month period using a targeted metabolomic approach. PLoS One, 6, e21103.
12.
FullerW. (1987). Measurement Error Models. John Wiley, New York.
13.
Investigators TA. (1987). Atherosclerosis Risk in Communities Study. Operations manual. No. 9: Hemostasis determinations, version 1.0.National Heart, Lung, and Blood Institute., Bethesda, MD.
14.
Investigators TA. (1989). The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol, 129, 687–702.
15.
LewisGD, AsnaniA, and GersztenRE. (2008). Application of metabolomics to cardiovascular biomarker and pathway discovery. J Am Coll Cardiol, 52, 117–123.
16.
MaJ, FolsomAR, EckfeldtJH, LewisL, and ChamblessLE. (1995). Short- and long-term repeatability of fatty acid composition of human plasma phospholipids and cholesterol esters. The Atherosclerosis Risk in Communities (ARIC) Study Investigators. Am J Clin Nutr, 62, 572–578.
17.
MenniC, FaumanE, ErteI, et al. (2013). Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes, 62, 4270–4276.
18.
NewgardCB, AnJ, BainJR, et al. (2009). A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab, 9, 311–326.
19.
OhtaT, MasutomiN, TsutsuiN, et al., (2009). Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats. Toxicol Pathol, 37, 521–535.
20.
PirmanDA, EfuetE, DingXP, et al. (2013). Changes in cancer cell metabolism revealed by direct sample analysis with MALDI mass spectrometry. PLoS One, 8, e61379.
21.
SampsonJN, BocaSM, ShuXO, et al. (2013). Metabolomics in epidemiology: Sources of variability in metabolite measurements and implications. Cancer Epidemiol Biomarkers Prev, 22, 631–640.
22.
SaudeE, AdamkoD, RoweB, MarrieT, and SykesB. (2007). Variation of metabolites in normal human urine. Metabolomics, 3, 439–451.
23.
ShultzSJ, WidemanL, MontgomeryMM, and LevineBJ. (2011). Some sex hormone profiles are consistent over time in normal menstruating women: Implications for sports injury epidemiology. Br J Sports Med, 45, 735–742.
24.
SreekumarA, PoissonLM, RajendiranTM, et al. (2009). Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature, 457, 910–914.
25.
SteinerC, OthmanA, SaelyCH, et al., (2011). Bile acid metabolites in serum: Intraindividual variation and associations with coronary heart disease, metabolic syndrome and diabetes mellitus. PLoS One, 6, e25006.
26.
SuhreK, MeisingerC, DoringA, et al., (2010). Metabolic footprint of diabetes: A multiplatform metabolomics study in an epidemiological setting. PLoS One, 5, e13953.
27.
SuhreK, ShinSY, PetersenAK, et al., (2011). Human metabolic individuality in biomedical and pharmaceutical research. Nature, 477, 54–60.
28.
SwannJR, WantEJ, GeierFM, et al., (2011). Systemic gut microbial modulation of bile acid metabolism in host tissue compartments. Proc Natl Acad Sci USA, 108Suppl 1, 4523–4530.
29.
TownsendMK, ClishCB, KraftP, et al. (2013). Reproducibility of metabolomic profiles among men and women in 2 large cohort studies. Clin Chem, 59, 1657–1667.
30.
VerghesePB, CastellanoJM, and HoltzmanDM. (2011). Apolipoprotein E in Alzheimer's disease and other neurological disorders. Lancet Neurol, 10, 241–252.
31.
WagenknechtL, WassermanB, ChamblessL, et al. (2009). Correlates of carotid plaque presence and composition as measured by MRI: The Atherosclerosis Risk in Communities Study. Circ Cardiovasc Imaging, 2, 314–322.
32.
WangTJ, LarsonMG, VasanRS, et al. (2011). Metabolite profiles and the risk of developing diabetes. Nat Med, 17, 448–453.
33.
WeirJP. (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res, 19, 231–240.
34.
WetmoreDR, JoseloffE, PilewskiJ, et al. (2010). Metabolomic profiling reveals biochemical pathways and biomarkers associated with pathogenesis in cystic fibrosis cells. J Biol Chem, 285, 30516–30522.
35.
WikoffWR, GangoitiJA, BarshopBA, and SiuzdakG. (2007). Metabolomics identifies perturbations in human disorders of propionate metabolism. Clin Chem, 53, 2169–2176.
36.
ZhengY, YuB, AlexanderD, et al. (2013a). Associations between metabolomic compounds and incident heart failure among African Americans: The ARIC Study. Am J Epidemiol, 178, 534–542.
37.
ZhengY, YuB, AlexanderD, et al., (2013b). Metabolomics and incident hypertension among blacks: The atherosclerosis risk in communities study. Hypertension, 62, 398–403.
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