Epigenetics of the Non-Coding RNA Nc886 across Blood, Adipose Tissue and Skeletal Muscle in Offspring Exposed to Diabetes in Pregnancy
Open accessAbstract
Background: Diabetes in pregnancy is associated with increased risk of long-term metabolic disease in the offspring, potentially mediated by in utero epigenetic variation. Previously, we identified multiple differentially methylated single CpG sites in offspring of women with gestational diabetes mellitus (GDM), but whether stretches of differentially methylated regions (DMRs) can also be identified in adolescent GDM offspring is unknown. Here, we investigate which DNA regions in adolescent offspring are differentially methylated in blood by exposure to diabetes in pregnancy. The secondary aim was to characterize the RNA expression of the identified DMR, which contained the nc886 non-coding RNA. Methods: To identify DMRs, we employed the bump hunter method in samples from young (9–16 yr, n = 92) offspring of women with GDM (O-GDM) and control offspring (n = 94). Validation by pyrosequencing was performed in an adult offspring cohort (age 28–33 years) consisting of O-GDM (n = 82), offspring exposed to maternal type 1 diabetes (O-T1D, n = 67) and control offspring (O-BP, n = 57). RNA-expression was measured using RT-qPCR in subcutaneous adipose tissue and skeletal muscle. Results: One significant DMR represented by 10 CpGs with a bimodal methylation pattern was identified, located in the nc886/VTRNA2-1 non-coding RNA gene. Low methylation status across all CpGs of the nc886 in the young offspring was associated with maternal GDM. While low methylation degree in adult offspring in blood, adipose tissue, and skeletal muscle was not associated with maternal GDM, adipose tissue nc886 expression was increased in O-GDM compared to O-BP, but not in O-T1D. In addition, adipose tissue nc886 expression levels were positively associated with maternal pre-pregnancy BMI (p = 0.006), but not with the offspring’s own adiposity. Conclusions: Our results highlight that nc886 is a metastable epiallele, whose methylation in young offspring is negatively correlated with maternal obesity and GDM status. The physiological effect of nc886 may be more important in adipose tissue than in skeletal muscle. Further research should aim to investigate how nc886 regulation in adipose tissue by exposure to GDM may contribute to development of metabolic disease.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Adults and children exposed to GDM displayed hypomethylation of the nc886 DMR compared with controls.
“Adults and children exposed to GDM displayed hypomethylation of the nc886 DMR compared with controls”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
The Discussion reports nc886 DMR hypomethylation in young offspring exposed to GDM compared with controls, but says this pattern was not replicated in the adult offspring cohort. Table 2 likewise shows no significant difference in methylation-group frequencies among adult offspring (p = 0.42). The claim is supported for children, not adults. (LLM, conf=0.92)
Experimental — accuracy not yet measuredCollectively, maternal obesity and GDM may induce long-lasting epigenetic changes at the nc886 locus, potentially altering gene regulation across multiple tissues and contributing to the intergenerational transmission of metabolic risk.
“Collectively, these findings indicate that maternal obesity and GDM may induce long-lasting epigenetic changes at the nc886 locus, potentially altering gene regulation across multiple tissues and contributing to the intergenerational transmission of metabolic risk [165].”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
The Discussion (page not provided) reports nc886 hypomethylation in young offspring exposed to maternal GDM and obesity, and the Conclusions propose a possible role for adipose-tissue nc886 regulation in metabolic programming. But the Discussion says the methylation difference was not replicated in older offspring; the paper does not establish lasting exposure-related changes or altered gene regulation across multiple tissues. (LLM, conf=0.87)
Experimental — accuracy not yet measuredResults of studies investigating whether lifestyle and dietary interventions during gestation could mitigate adverse metabolic outcomes in offspring remain largely inconclusive.
“However, the results remain largely inconclusive [165].”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
The Discussion (page unavailable) says previous studies found lifestyle changes during pregnancy “not very effective,” which supports uncertainty about the benefit of gestational interventions. It does not establish that studies of lifestyle and dietary interventions found largely inconclusive results specifically for offspring metabolic outcomes; its examples chiefly concern maternal weight, fertility, and birth outcomes. (LLM, conf=0.78)
Experimental — accuracy not yet measuredHjort et al. (2024) identified a significant DMR encompassing the non-coding RNA nc886 (VTRNA2-1) locus in blood from children exposed to GDM compared with controls.
“identified a significant DMR encompassing the non-coding RNA nc886 (VTRNA2-1) locus”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
The nc886 (VTRNA2-1) locus is known to undergo maternal imprinting in approximately 75% of offspring and is considered a metastable epiallele sensitive to periconceptional environmental conditions.
“a region known to undergo maternal imprinting in approximately 75% of offspring and considered a metastable epiallele sensitive to periconceptional environmental conditions [165].”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
Follow-up analyses in an independent cohort of adult offspring revealed a conserved bimodal methylation pattern of nc886 across blood, skeletal muscle, and subcutaneous adipose tissue, consistent with its epigenetic metastability.
“Follow-up analyses in an independent cohort of adult offspring (the Copenhagen Offspring Cohort) revealed a conserved bimodal methylation pattern of nc886 across blood, skeletal muscle, and subcutaneous adipose tissue, consistent with its epigenetic metastability.”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
Methylation levels of nc886 were inversely correlated with nc886 RNA expression, particularly in adipose tissue.
“methylation levels were inversely correlated with nc886 RNA expression, particularly in adipose tissue.”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
Increased nc886 expression in adipose tissue was associated with higher maternal pre-pregnancy BMI, elevated fasting insulin and C-peptide, and lower HDL cholesterol in the offspring.
“Increased nc886 expression in adipose tissue was associated with higher maternal pre-pregnancy BMI, as well as elevated fasting insulin and C-peptide and lower HDL cholesterol in the offspring”
From Maternal Overnutrition and Fetal Programming: Long-Term Metabolic, Cognitive, and Epigenetic Consequences (2026) · cites this paper as [165]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Aryee, M. J., Jaffe, A. E., Bravo, H. C., Ladd‐Acosta, C., Feinberg, A. P., Hansen, K. D., & Irizarry, R. A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu049 · Cited by 4,423 · see citing works
DNA methylation arrays as surrogate measures of cell mixture distribution
Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., Wiencke, J. K., & Kelsey, K. T. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-86 · Cited by 3,175 · see citing works
Adapting to obesity with adipose tissue inflammation
Reilly, S. M., & Saltiel, A. R. (2017) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2017.90 · Cited by 1,204 · see citing works
Tobacco smoking leads to extensive genome-wide changes in DNA methylation
Zeilinger, S., Kühnel, B., Klopp, N., Baurecht, H., Kleinschmidt, A., Gieger, C., Weidinger, S., Lattka, E., Adamski, J., Peters, A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063812 · Cited by 824 · see citing works
Clausen, T. D., Mathiesen, E. R., Hansen, T., Pedersen, O., Jensen, D. M., Lauenborg, J., & Damm, P. (2008) · Diabetes Care · doi:10.2337/dc07-1596 · Cited by 724 · see citing works
Self-citationBump hunting to identify differentially methylated regions in epigenetic epidemiology studies
Jaffe, A. E., Murakami, P. N., Lee, H.-J., Leek, J. T., Fallin, M. D., Feinberg, A. P., & Irizarry, R. A. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr238 · Cited by 687 · see citing works
Damm, P., Houshmand-Oeregaard, A., Kelstrup, L., Lauenborg, J., Mathiesen, E. R., & Clausen, T. D. (2016) · Diabetologia · doi:10.1007/s00125-016-3985-5 · Cited by 620 · see citing works
Self-citationMaternal nutrition at conception modulates DNA methylation of human metastable epialleles
Dominguez-Salas, P., Moore, S. E., Baker, M. S., Bergen, A. W., Cox, S. E., Dyer, R. A., Fulford, A. J., Guan, Y., Laritsky, E., Silver, M. J., et al. (2014) · Nature Communications · doi:10.1038/ncomms4746 · Cited by 506 · see citing works
Nakamura, T., Furuhashi, M., Li, P., Cao, H., Tuncman, G., Sonenberg, N., Görgün, C. Z., & Hotamışlıgil, G. S. (2010) · Cell · doi:10.1016/j.cell.2010.01.001 · Cited by 498 · see citing works
Koestler, D. C., Christensen, B. C., Karagas, M. R., Marsit, C. J., Langevin, S. M., Kelsey, K. T., Wiencke, J. K., & Houseman, E. A. (2013) · Epigenetics · doi:10.4161/epi.25430 · Cited by 251 · see citing works
Multi-omics signatures of the human early life exposome
Maître, L., Bustamante, M., Hernandéz-Ferrer, C., Thiel, D., Lau, C. E., Siskos, A., Vives-Usano, M., Ruiz-Arenas, C., Pelegrí-Sisó, D., Robinson, O., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34422-2 · Cited by 230 · see citing works
Effect of physical activity and/or healthy eating on GDM risk: The DALI Lifestyle Study
Simmons, D., Devlieger, R., van Assche, A., Jans, G., Galjaard, S., Corcoy, R., Adelantado, J. M., Dunne, F., Desoye, G., Harreiter, J., et al. (2016) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2016-3455 · Cited by 225 · see citing works
Self-citationSilver, M. J., Kessler, N. J., Hennig, B. J., Domínguez-Salas, P., Laritsky, E., Baker, M. S., Coarfa, C., Hernández‐Vargas, H., Castelino, J. M., Routledge, M. N., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0660-y · Cited by 191 · see citing works
Mulder, R. H., Neumann, A., Cecil, C. A. M., Walton, E., Houtepen, L. C., Simpkin, A. J., Rijlaarsdam, J., Heijmans, B. T., Gaunt, T. R., Felix, J. F., et al. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddaa280 · Cited by 165 · see citing works
Lee, K., Kunkeaw, N., Jeon, S. H., Lee, I., Johnson, B. H., Kang, G., Bang, J. Y., Park, H. S., Leelayuwat, C., & Lee, Y. S. (2011) · RNA · doi:10.1261/rna.2701111 · Cited by 165 · see citing works
Howe, C. G., Cox, B., Fore, R., Jungius, J., Kvist, T., Lent, S., Miles, H. E., Salas, L. A., Rifas‐Shiman, S. L., Starling, A. P., et al. (2019) · Diabetes Care · doi:10.2337/dc19-0524 · Cited by 160 · see citing works
The role and interaction of imprinted genes in human fetal growth
Moore, G. E., Ishida, M., Demetriou, C., Al-Olabi, L., Leon, L. J., Thomas, A. C., Abu-Amero, S., Frost, J. M., Stafford, J. L., Chaoqun, Y., et al. (2015) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2014.0074 · Cited by 155 · see citing works
Grunnet, L. G., Hansen, S., Hjort, L., Madsen, C. M., Kampmann, F. B., Thuesen, A. C. B., Granstrømi, C., Strøm, M., Maslova, E., Frikke‐Schmidt, R., et al. (2017) · Diabetes Care · doi:10.2337/dc17-0514 · Cited by 126 · see citing works
Self-citationMaître, L., Júlvez, J., López-Vicente, M., Warembourg, C., Tamayo, I., Philippat, C., Gützkow, K. B., Guxens, M., Andrušaitytė, S., Basagaña, X., et al. (2021) · Environment International · doi:10.1016/j.envint.2021.106523 · Cited by 121 · see citing works
Hjort, L., Martino, D., Grunnet, L. G., Naeem, H., Maksimovic, J., Olsson, A. H., Zhang, C., Ling, C., Olsen, S. F., Saffery, R., et al. (2018) · JCI Insight · doi:10.1172/jci.insight.122572 · Cited by 114 · see citing works
Self-citationLegro, R. S., Hansen, K. R., Diamond, M. P., Steiner, A. Z., Coutifaris, C., Cedars, M. I., Hoeger, K. M., Usadi, R., Johnstone, E. B., Haisenleder, D. J., et al. (2022) · PLoS Medicine · doi:10.1371/journal.pmed.1003883 · Cited by 113 · see citing works
Ding, M., Chavarro, J. E., Olsen, S. F., Lin, Y., Ley, S. H., Bao, W., Rawal, S., Grunnet, L. G., Thuesen, A. C. B., Mills, J. L., et al. (2018) · Diabetologia · doi:10.1007/s00125-018-4637-8 · Cited by 106 · see citing works
Self-citationLadd‐Acosta, C., Feinberg, J. I., Brown, S. C., Lurmann, F., Croen, L., Hertz‐Picciotto, I., Newschaffer, C. J., Feinberg, A. P., Fallin, M. D., & Volk, H. E. (2019) · Environment International · doi:10.1016/j.envint.2019.02.028 · Cited by 100 · see citing works
Camino, T., Lago‐Baameiro, N., Bravo, S. B., Molares-Vila, A., Sueiro, A. M., Couto‐González, I., Baltar, J., Casanueva, E. F., & Pardo, M. (2021) · Translational research · doi:10.1016/j.trsl.2021.01.006 · Cited by 90 · see citing works
Williamson, A., Norris, D. M., Yin, X., Broadaway, K. A., Moxley, A. H., Vadlamudi, S., Wilson, E. P., Jackson, A., Ahuja, V., Andersen, M. K., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01408-9 · Cited by 82 · see citing works
Self-citationLee, K.-S., Park, J., Lee, K., Richardson, L. E., Johnson, B. H., Lee, H., Lee, J., Kim, S.-B., Kwon, O.-H., Song, K. S., et al. (2014) · Oncotarget · doi:10.18632/oncotarget.2047 · Cited by 77 · see citing works
Hjort, L., Novakovic, B., Grunnet, L. G., Maple-Brown, L. J., Damm, P., Desoyé, G., & Saffery, R. (2019) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(19)30078-6 · Cited by 76 · see citing works
Self-citationAn evaluation of statistical methods for DNA methylation microarray data analysis
Li, D., Xie, Z., Pape, M., & Dye, T. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0641-x · Cited by 72 · see citing works
nc886 is induced by TGF-β and suppresses the microRNA pathway in ovarian cancer
Ahn, J., Lee, H., Lee, J., Lee, Y.-S., Park, J., Kim, S., Hwang, J.-A., Kunkeaw, N., Jung, S. Y., Kim, T. J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03556-7 · Cited by 71 · see citing works
Brier, A.-S. B., Loft, A., Madsen, J. G. S., Rosengren, T., Nielsen, R., Schmidt, S. F., Liu, Z. Z., Yan, Q., Gronemeyer, H., & Mandrup, S. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1156 · Cited by 64 · see citing works
Mother–child transmission of epigenetic information by tunable polymorphic imprinting
Carpenter, B. L., Zhou, W., Madaj, Z., DeWitt, A. K., Ross, J. P., Grønbæk, K., Liang, G., Clark, S. J., Molloy, P. L., & Jones, P. A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1815005115 · Cited by 58 · see citing works
Developmental programming of offspring adipose tissue biology and obesity risk
Rodgers, A., & Sferruzzi-Perri, A. N. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00790-w · Cited by 57 · see citing works
Kelstrup, L., Hjort, L., Houshmand‐Oeregaard, A. S., Clausen, T. D., Hansen, N. S., Broholm, C., Borch‐Johnsen, L., Mathiesen, E. R., Vaag, A. A., & Damm, P. (2016) · Diabetes · doi:10.2337/db16-0227 · Cited by 56 · see citing works
Self-citationRaab, R., Michel, S., Günther, J., Hoffmann, J., Stecher, L., & Hauner, H. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-020-01075-7 · Cited by 47 · see citing works
Gadd, D. A., Hillary, R. F., McCartney, D. L., Shi, L., Stolicyn, A., Robertson, N., Walker, R. M., McGeachan, R. I., Campbell, A., Shen, X., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32319-8 · Cited by 45 · see citing works
Diagnosing gestational diabetes mellitus in the Danish National Birth Cohort
Olsen, S. F., Houshmand‐Oeregaard, A., Granström, C., Langhoff‐Roos, J., Damm, P., Bech, B. H., Vaag, A. A., & Zhang, C. (2016) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.13083 · Cited by 40 · see citing works
Self-citationJedynak, P., Tost, J., Calafat, A. M., a-Flin, E. B., Busato, F., Forhan, A., Heude, B., Jakobi, M., Rousseaux, S., Schwartz, J. D., et al. (2021) · Environmental Pollution · doi:10.1016/j.envpol.2021.118024 · Cited by 37 · see citing works
Ienasescu, H., Li, K., Andersson, R., Vitezic, M., Rennie, S., Chen, Y., Vitting‐Seerup, K., Lagoni, E., Boyd, M., Bornholdt, J., et al. (2016) · Database · doi:10.1093/database/baw144 · Cited by 34 · see citing works
Chi, G. C., Liu, Y., MacDonald, J. W., Reynolds, L. M., Enquobahrie, D. A., Fitzpatrick, A. L., Kerr, K. F., Budoff, M. J., Lee, S., Siscovick, D. S., et al. (2021) · Epigenetics · doi:10.1080/15592294.2021.1900028 · Cited by 32 · see citing works
Muirhead, R., Kizirian, N. V., Lal, R., Black, K. I., Davies, A. P., Nassar, N., Baur, L. A., Sainsbury, A., Sweeting, A., Markovic, T., et al. (2021) · Nutrients · doi:10.3390/nu13093200 · Cited by 31 · see citing works
The Noncoding RNA nc886 Regulates PKR Signaling and Cytokine Production in Human Cells
Golec, E., Lind, L., Qayyum, M., Blom, A. M., & King, B. C. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1701234 · Cited by 30 · see citing works
Zhang, C., Hu, F. B., Olsen, S. F., Vaag, A. A., Gore‐Langton, R. E., Chavarro, J. E., Bao, W., Yeung, E. H., Bowers, K. A., Grunnet, L. G., et al. (2014) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.12425 · Cited by 30 · see citing works
Self-citationFetal Hyperglycemia Changes Human Preadipocyte Function in Adult Life
Hansen, N. S., Strasko, K. S., Hjort, L., Kelstrup, L., Houshmand‐Oeregaard, A. S., Schrölkamp, M., Schultz, H. S., Schéele, C., Pedersen, B. K., Ling, C., et al. (2017) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2016-3907 · Cited by 29 · see citing works
Self-citationFort, R. S., Garat, B., Sotelo-Silveira, J. R., & Duhagon, M. A. (2020) · Non-Coding RNA · doi:10.3390/ncrna6010007 · Cited by 29 · see citing works
Carpenter, B. L., Remba, T. K., Thomas, S. L., Madaj, Z., Brink, L. T., Tiedemann, R. L., Odendaal, H. J., & Jones, P. A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2026580118 · Cited by 29 · see citing works
Marttila, S., Viiri, L. E., Mishra, P. P., Kühnel, B., Matías‐García, P. R., Lyytikäinen, L., Ceder, T., Mononen, N., Rathmann, W., Winkelmann, J., et al. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01132-3 · Cited by 29 · see citing works
Sabir, J. S. M., Omri, A. E., Shaik, N. A., Banaganapalli, B., Al‐Shaeri, M., Alkenani, N. A. H., Hajrah, N. H., Awan, Z. A., Zrelli, H., Elango, R., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0214337 · Cited by 29 · see citing works
Human Adipogenesis is Associated with Genome-Wide DNA Methylation and Gene-Expression Changes
Broholm, C., Olsson, A. H., Perfilyev, A., Gillberg, L., Hansen, N. S., Ali, A., Mortensen, B., Ling, C., & Vaag, A. A. (2016) · Epigenomics · doi:10.2217/epi-2016-0077 · Cited by 25 · see citing works
Self-citationVTRNA2-1: Genetic Variation, Heritable Methylation and Disease Association
Dugué, P., Yu, C., McKay, T., Wong, E. M., Joo, J. E., Tsimiklis, H., Hammet, F., Mahmoodi, M. S., Theys, D., kConFab, et al. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052535 · Cited by 24 · see citing works
Roustaei, Z., Räisänen, S., Gissler, M., & Heinonen, S. T. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-034839 · Cited by 19 · see citing works
Mishra, M. K., Kane, A. E., Young, A. P., & Howlett, S. E. (2022) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2022.111762 · Cited by 13 · see citing works
Low-grade inflammation in young adults exposed to intrauterine hyperglycemia
Kelstrup, L., Clausen, T. D., Mathiesen, E. R., Hansen, T. F., & Damm, P. (2012) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2012.04.023 · Cited by 11 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Schiera, G., Macajone, G., Volpes, S., Greco, L., Di Liegro, C. M., Serio, G., Caradonna, F., & Naselli, F. (2026) · Cells · doi:10.3390/cells15040366 · Cited by 8 · see citing works
Bui, V. N. V., Daugaard, T. F., Sørensen, B. S., & Nielsen, A. L. (2024) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2024.150395 · Cited by 5 · see citing works
The Relationship Between Socioeconomic Status and Omphalocele Prevalence
Colquitt, L., & Burjonrappa, S. C. (2025) · Journal of Pediatric Surgery · doi:10.1016/j.jpedsurg.2025.162225 · Cited by 1 · see citing works
Badre, R. S., & Kumar, A. (2025) · International Journal of Information Technology · doi:10.1007/s41870-025-02968-1
Wei, X., Jiang, J., Feng, W., Tan, Y., Sun, C., Liu, J., Yang, Z., Yang, G., & Luo, X. M. (2026) · Biomedicines · doi:10.3390/biomedicines14010224
Huang, Y., Hou, K., Tsai, M., Liu, K., Ho, M.-Y., Yeh, J., Chen, C., Chia, C.-Y., Fan, W., Hsieh, I.-C., et al. (2026) · Obesity · doi:10.1002/oby.70268
Small Noncoding RNAs: Vault RNAs and Agotrons
Haseltine, W. A., & Patarca, R. (2026) · Springer eBooks · doi:10.1007/978-3-032-30270-0_6
- Authors
- Hjort, L., Bredgaard, S. S., Manitta, E., Marques, I., Sørensen, A. E., Martino, D., Grunnet, L. G., Kelstrup, L., Houshmand-Oeregaard, A., Clausen, T. D., Mathiesen, E. R., Olsen, S. F., Saffery, R., Barrès, R., Damm, P., Vaag, A. A., & Dalgaard, L. T.
- Affiliations
- University of Copenhagen (DK)
- Roskilde University (DK)
- Rigshospitalet (DK)
- The Kids Research Institute Australia (AU)
- Herlev Hospital (DK)
- Statens Serum Institut (DK)
- The University of Melbourne (AU)
- Lund University (SE)
- Corresponding author
- Hjort, Line
- Dalgaard, Louise Torp
- ORCID
- Venue
- Clinical Epigenetics
- Published
- 2024-05-07
- Volume
- 16
- Issue
- 1
- Pages
- 61-61
- ISSN
- 1868-7075 (ISSN-L)
- 1868-7083
- PMC
- PMC11077860
- OpenAlex
- W4396708228
- Cited by
- 6
- References
- 52
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 1
- FWCI
- 4.06
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Clinical Epigenetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- HAL (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Lund University Publications (Lund University) (submittedVersion)
- RUCforsk (Roskilde University) (submittedVersion, cc-by)
- Funders
- Fhv. Dir. Leo Nielsen og Hustru Karen Margrethe Nielsens Legat for Lægevidenskabelig Grundforskning
- Civilingeniør Frode V. Nyegaard og Hustru’s Fond
- A.P. Møller Fonden
- Lægeforeningens Forskningfond
- Novo Nordisk Fonden (NNF17SA0031406)
- The Danish Diabetes Association
- Novo Nordisk Foundation Center for Basic Metabolic Research (NNF18CC0034900)
- The Innovation Fund Denmark (09-067124)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Birth, Development, and Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
- Keywords
- gestational diabetes mellitus, non-coding RNA, DNA methylation, differentially methylated regions, epigenetics, offspring of diabetic mothers, maternal type 1 diabetes, maternal obesity, pre-pregnancy body mass index, adipose tissue, skeletal muscle, blood, epialleles, metabolic disease risk, adolescent offspring, RNA expression
- MeSH terms
- Adipose Tissue, Adolescent, Adult, Child, Diabetes Mellitus, Type 1, Female, Humans, Male, Pregnancy, Prenatal Exposure Delayed Effects, Diabetes, Gestational, Muscle, Skeletal, CpG Islands, DNA Methylation, RNA, Untranslated, Epigenesis, Genetic, RNA, Long Noncoding
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review