Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study

Abstract

Large-scale population phenotyping for molecular epidemiological studies is subject to all the usual criteria of analytical chemistry. As part of a major phenotyping investigation we have used high-resolution 1H NMR spectroscopy to characterize 24-h urine specimens obtained from population samples in Aito Town, Japan (n = 259), Chicago, IL (n = 315), and Guangxi, China (n = 278). We have investigated analytical reproducibility, urine specimen storage procedures, interinstrument variability, and split specimen detection. Our data show that the multivariate analytical reproducibility of the NMR screening platform was >98% and that most classification errors were due to urine specimen handling inhomogeneity. Differences in metabolite profiles were then assessed for Aito Town, Chicago, and Guangxi population samples; novel combinations of biomarkers were detected that separated the population samples. These cross-population differences in urinary metabolites could be related to genetic, dietary, and gut microbial factors.

Figure 1.

Summary of INTERMAP study design serving as basis for ¹H NMR metabonomic urinalysis protocol. Collection of 24-h urine specimens during visits 2 and 4, respectively, 1 day after visit 1 and 3. 8.3% of the specimens split at source and given different identification labels. All the specimens were analyzed by ¹H NMR.

Figure 2.

Position and dispersion parameters and coefficients of variation for the quality control urine specimens. (A) Mean spectrum in the δ1.0−8.00 range, (B) standard deviation spectrum in the δ1.0−δ8.00 range, (C) coefficient of variation spectrum in the δ1.0−δ8.00 range, (D) distribution of the coefficients of variation in the δ1.0−δ8.00 range, (E) mean spectrum in the δ1−δ4 range, (F) standard deviation spectrum in the δ1−δ4 range, (G) coefficient of variation spectrum in the δ1−δ4 range, and (H) distribution of the coefficients of variation in the δ1−δ4 range.

Figure 3.

Identification of split urine specimens by hierarchical clustering trees of 600-MHz ¹H NMR spectra. (A) Single linkage dendrogram for the American female 40–49 year group for the total spectrum, (B) NMR spectra of the two replicate specimens marked with * in (B) and their difference. The vertical axis in the dendrogram corresponds to the aggregation value computed, as described in the Experimental Section, summarizing the measure of dissimilarity (≥0) between clusters or initial samples. To identify the split urine specimens, a fixed length has been assigned to the “leaves” (i.e., individual specimens) of the clustering tree. Specimens that are very similar (i.e., splits) aggregate close to 0 (i.e., low dissimilarity).

Figure 4.

600-MHz ¹H NMR spectra of human urine from (A) a Japanese, (B) a Chinese, and (C) an American man. Principal assignments are marked. Key: TMAO–trimethylamine-N-oxide (the inset spectra are shown to give an indication of the spectral complexity); D) Pattern recognition of geographical origin using PC-LDA (n) 852). This model was computed with 0.01 ppm buckets in the δ0.16–9.76 range using 29 principal components for pre-compression before LDA.