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. 2015 Oct 6;112(40):E5503-12.
doi: 10.1073/pnas.1508736112. Epub 2015 Sep 21.

Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

Kun Sun  1 , Peiyong Jiang  1 , K C Allen Chan  2 , John Wong  3 , Yvonne K Y Cheng  4 , Raymond H S Liang  5 , Wai-kong Chan  6 , Edmond S K Ma  6 , Stephen L Chan  7 , Suk Hang Cheng  1 , Rebecca W Y Chan  1 , Yu K Tong  1 , Simon S M Ng  3 , Raymond S M Wong  8 , David S C Hui  9 , Tse Ngong Leung  10 , Tak Y Leung  4 , Paul B S Lai  11 , Rossa W K Chiu  1 , Yuk Ming Dennis Lo  12
Affiliations

Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

Kun Sun et al. Proc Natl Acad Sci U S A. .

Abstract

Plasma consists of DNA released from multiple tissues within the body. Using genome-wide bisulfite sequencing of plasma DNA and deconvolution of the sequencing data with reference to methylation profiles of different tissues, we developed a general approach for studying the major tissue contributors to the circulating DNA pool. We tested this method in pregnant women, patients with hepatocellular carcinoma, and subjects following bone marrow and liver transplantation. In most subjects, white blood cells were the predominant contributors to the circulating DNA pool. The placental contributions in the plasma of pregnant women correlated with the proportional contributions as revealed by fetal-specific genetic markers. The graft-derived contributions to the plasma in the transplant recipients correlated with those determined using donor-specific genetic markers. Patients with hepatocellular carcinoma showed elevated plasma DNA contributions from the liver, which correlated with measurements made using tumor-associated copy number aberrations. In hepatocellular carcinoma patients and in pregnant women exhibiting copy number aberrations in plasma, comparison of methylation deconvolution results using genomic regions with different copy number status pinpointed the tissue type responsible for the aberrations. In a pregnant woman diagnosed as having follicular lymphoma during pregnancy, methylation deconvolution indicated a grossly elevated contribution from B cells into the plasma DNA pool and localized B cells as the origin of the copy number aberrations observed in plasma. This method may serve as a powerful tool for assessing a wide range of physiological and pathological conditions based on the identification of perturbed proportional contributions of different tissues into plasma.

Keywords: circulating tumor DNA; epigenetics; liquid biopsy; noninvasive prenatal testing; transplantation monitoring.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Schematic illustration of the principle of plasma DNA tissue mapping by genome-wide methylation sequencing and its applications.
Fig. 2.
Fig. 2.
Pie charts depicting the results of the tissue DNA mixing experiment. Mixtures of DNA comprising varying input percentages of DNA extracted from the placenta, liver, and blood cells were prepared. The mixtures included 100% input from one of the three tissues (100% input), 75% input of one tissue plus 25% input of one other tissue (75% + 1 input), 75% input of one tissue plus 12.5% each of the other two tissues (75% + 2 input), 50% input from each of two tissues (50% + 1 input), and 50% input of one tissue plus 25% each of the other two tissues (50% + 2 input). Methylation deconvolution was performed for these mixture samples and the measured tissue percentages are shown on the right of each input condition.
Fig. 3.
Fig. 3.
Correlations between the measured and input tissue percentages for the tissue DNA mixture experiment. A–C correspond to data points obtained for each of the three tested tissue types, namely, blood cells, placenta, and liver, respectively.
Fig. 4.
Fig. 4.
Percentage contributions of different tissues to plasma DNA for 15 pregnant women. Each bar corresponds to the results of one sample. The different colors represent the contributions of different tissues into plasma.
Fig. 5.
Fig. 5.
Correlation between the placental contributions deduced by plasma DNA tissue mapping analysis and the fetal DNA fractions based on the analysis of fetal-specific SNP alleles.
Fig. 6.
Fig. 6.
Correlation between the fractions of plasma DNA contributed by the transplanted graft deduced by plasma DNA tissue mapping and the donor DNA fractions determined using donor-specific SNP alleles. The triangles represent the results of liver transplant recipients and the dots represent the results of bone marrow transplant recipients.
Fig. 7.
Fig. 7.
Percentage of plasma DNA contributed by the liver among healthy controls and patients with HCC as deduced by plasma DNA tissue mapping analysis.
Fig. 8.
Fig. 8.
Correlation between the fractions of plasma DNA contributed by the liver based on plasma DNA tissue mapping analysis and the tumor-derived plasma DNA fractions determined by GAAL analysis.
Fig. 9.
Fig. 9.
Schematic illustration showing the principle of analyzing the tissue of origin for plasma DNA copy number aberrations using plasma DNA tissue mapping. Three clinical scenarios are illustrated: (A) pregnancy involving a trisomy 21 fetus; (B) cancer; and (C) pregnancy with concurrent malignancy. Ref Chr, reference chromosome.
Fig. 10.
Fig. 10.
∆M values across different tissues for pregnant women each carrying a fetus with trisomy 21 (T21). In each of the five cases, the value of ∆M was highest for the placenta, suggesting that the copy number aberrations originated from the placenta.
Fig. S1.
Fig. S1.
∆M values across different tissues for pregnant women each carrying a fetus with trisomy 21 (T21). The methylation markers on all of the autosomes except chromosome 21 were randomly divided into two sets, namely, set A and set B. The randomization was implemented using a series of random numbers (ranged from 0 to 1) generated by a computer. A marker associated with a random number less than 0.5 was assigned to set A; otherwise, it would be assigned to set B. In this analysis, set A included markers originating from chromosomes 1, 2, 4, 5, 6, 8, 12, 14, 15, 17, and 22, and set B included markers originating from chromosomes 3, 7, 9, 10, 11, 13, 16, 18, 19, and 20. Plasma DNA tissue mapping was conducted using each set of markers. The ∆M values shown represent the difference in contributions of a particular tissue to plasma DNA using markers in sets A and B.
Fig. 11.
Fig. 11.
∆M values across different tissues for the HCC patients. ∆M represents the difference in the contributions of a particular tissue to plasma DNA between regions exhibiting copy number gains and copy number losses. For each case, the highest ∆M is shown in orange. Other ∆M values are shown in gray. The tissue with the highest ∆M is considered as the tissue of origin of the copy number aberration. HCC, hepatocellular carcinoma.
Fig. S2.
Fig. S2.
∆M values across different tissues for the HCC patients. The ∆M values shown represent the difference in contributions of a particular tissue to plasma DNA between two sets of randomly selected regions without plasma DNA copy number aberrations.
Fig. 12.
Fig. 12.
Elucidation of the tissue of origin for the copy number aberrations identified in the plasma of a pregnant woman with concurrent follicular lymphoma. (A) Genome-wide DNA sequencing analysis for copy number aberration detection among specimens collected from the patient. From outside to inside: buffy coat of the pretreatment blood sample, lymph node biopsy, plasma sample collected before treatment, and plasma sample collected after treatment. The chromosome ideogram is shown in clockwise manner at the outermost ring. Each dot represents a 1-Mb region. Green, red, and gray dots represent regions with copy number gains, copy number losses, and without copy number aberrations, respectively. (B) ∆M values across different tissues for the pretreatment plasma sample of this patient. The B cells show the highest ∆M value, suggesting that the copy number aberrations were derived from B cells.
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