Next-generation sequencing methylation profiling of subjects with obesity identifies novel gene changes

Day, Samantha E.; Coletta, Richard L.; Kim, Joon Young; Campbell, Latoya E.; Benjamin, Tonya R.; Roust, Lori R.; Filippis, Elena A. De; Dinu, Valentin; Shaibi, Gabriel Q.; Mandarino, Lawrence J.; Coletta, Dawn K.

doi:10.1186/s13148-016-0246-x

Cited by 24 publications

(37 citation statements)

References 39 publications

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“…Furthermore, we set out to identify similarities between whole-blood and the insulin responsive tissue, skeletal muscle. By using skeletal muscle methylation changes assessed in our previous study, 25 we found SLC19A1 to be a blood-based DNA methylation biomarker for that tissue. Not only were these DMCs decreased in methylation in both blood and skeletal muscle, but also the level of change was to a similar extent.…”

Section: Discussionmentioning

confidence: 85%

“…27 Interestingly, the distribution pattern of all detected CpG sites were similar to the patterns observed in our previous study in skeletal muscle. 25 The consistent coverage of the genome regardless of tissue type presents RRBS as a viable technique for cross-tissue analysis.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, we set out to identify blood-based biomarkers of methylation sites in genes that were also identified in skeletal muscle using our previously published data. 25 The skeletal muscle results are based on 11 lean and 9 obese (BMI > 30 kg/m 2 ; Table S3) patients. Of these individuals, 9 lean and 6 obese were in common with the individuals included in the whole-blood analyses.…”

Section: Potential Blood-based Biomarkers Of Skeletal Musclementioning

confidence: 99%

“…Of these individuals, 9 lean and 6 obese were in common with the individuals included in the whole-blood analyses. When we compared the significantly changing whole-blood DMCs (FDR; q < 0.05) with our previously published skeletal muscle data, 25 we identified 3 sites that were in common. One site (Chr.21:46,927,138) was in collagen, type XVIII, a 1 (COL18A1) and the other 2 sites (Chr.21:46,957,915 and Chr.21:46,957,981) were upstream of SLC19A1 (Fig.…”

Section: Potential Blood-based Biomarkers Of Skeletal Musclementioning

confidence: 99%

“…Metabolic data for some of these participants were included in a previous publication. 25 Demographics, anthropometric measurements, and screening blood tests were obtained on all participants. Body impedance analysis (BIA) was used to assess percent body fat.…”

Section: Participantsmentioning

confidence: 99%

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Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

et al. 2017

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Obesity can increase the risk of complex metabolic diseases, including insulin resistance. Moreover, obesity can be caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are not well defined. Therefore, the identification of novel epigenetic biomarkers of obesity allows for a more complete understanding of the disease and its underlying insulin resistance. The aim of our study was to identify DNA methylation changes in whole-blood that were strongly associated with obesity and insulin resistance. Whole-blood was obtained from lean (n D 10; BMI D 23.6 § 0.7 kg/m 2 ) and obese (n D 10; BMI D 34.4 § 1.3 kg/m 2 ) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing on genomic DNA isolated from the blood. We identified 49 differentially methylated cytosines (DMCs; q < 0.05) that were altered in obese compared with lean participants. We identified 2 sites (Chr.21:46,957,981 and Chr.21:46,957,915) in the 5' untranslated region of solute carrier family 19 member 1 (SLC19A1) with decreased methylation in obese participants (lean 0.73 § 0.11 vs. obese 0.09 § 0.05; lean 0.68 § 0.10 vs. obese 0.09 § 0.05, respectively). These 2 DMCs identified by obesity were also significantly predicted by insulin sensitivity (r D 0.68, P D 0.003; r D 0.66; P D 0.004). In addition, we performed a differentially methylated region (DMR) analysis and demonstrated a decrease in methylation of Chr.21:46,957,958,001 in SLC19A1 of ¡34.9% (70.4% lean vs. 35.5% obese). The decrease in whole-blood SLC19A1 methylation in our obese participants was similar to the change observed in skeletal muscle (Chr.21:46,957,981, lean

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Section: Discussionmentioning

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Potential Blood-based Biomarkers Of Skeletal Musclementioning

confidence: 99%

Section: Potential Blood-based Biomarkers Of Skeletal Musclementioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

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Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

et al. 2017

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Pyrosequencing Methylation Analysis

Poulin¹,

Zhou

Yan³

et al. 2018

Methods in Molecular Biology

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Pyrosequencing, a real-time sequencing technology, is considered a "gold standard" for quantitative allele quantification at single base resolution. Quantitative bisulfite Pyrosequencing determines DNA methylation level by analyzing artificial "C/T" SNPs at CpG sites within a specific Pyrosequencing assay. The bisulfite Pyrosequencing methylation assay design is DNA strand specific and the primer design should not contain any CpG sites and should be free of high-frequency mutations. Additionally Pyrosequencing assays must be tested for preferential amplification during bisulfite PCR to ensure the sequencing quantification accuracy and reproducibility. Pyrosequencing analysis gives a reproducible measurement of average methylation at several CpG sites within the Pyrosequencing assay directly from a PCR product, rapidly and accurately for many samples at a time. It is therefore well suited for clinical research, validation of whole-genome methylation screening results, and global methylation analysis using repetitive elements including LINE-1, Alu, and Sat2. Pyrosequencing reproducibility and accuracy result in low measurement variance, thereby increasing the likelihood of early detection of small changes in methylation levels that may become apparent in response to treatment. For example, the high reproducibility of the LINE-1 assay is important for detecting the relatively small daily changes in methylation levels associated with hypomethylation. This enables detection of differences in patterns between normal and disease tissue such as in tumor suppresser genes, and to determine global methylation changes in response drug treatments. Relatively low cost and easy automation allows the researcher to increase the experiment's sample population to detect trends that would otherwise not have a sufficient sampling basis for statistical significance.

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Genome-Wide Association Study of Gallstone Disease Identifies Novel Candidate Genomic Variants in a Latino Community of Southwest USA

Arora,

Jack,

Kumar

et al. 2023

J. Racial and Ethnic Health Disparities

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Next-generation sequencing methylation profiling of subjects with obesity identifies novel gene changes

Cited by 24 publications

References 39 publications

Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

Pyrosequencing Methylation Analysis

Genome-Wide Association Study of Gallstone Disease Identifies Novel Candidate Genomic Variants in a Latino Community of Southwest USA

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