Assisted reproductive technology alters deoxyribonucleic acid methylation profiles in bloodspots of newborn infants  Molly S. Estill, M.S., Jay M. Bolnick,

Slides:



Advertisements
Similar presentations
Molecular characterization of uterine fibroids and its implication for underlying mechanisms of pathogenesis  Paul J. Hoffman, B.S., Dawn B. Milliken,
Advertisements

Kenneth I. Aston, Ph. D. , Philip J. Uren, Ph. D. , Timothy G
Figure 3. Active enhancers located in intergenic DMRs
Artificial oocyte activation with calcium ionophore does not cause a widespread increase in chromosome segregation errors in the second meiotic division.
Highly heterogeneous genomic landscape of uterine leiomyomas by whole exome sequencing and genome-wide arrays  Svetlana A. Yatsenko, M.D., Priya Mittal,
Report of results obtained in 2,934 women using donor sperm: donor insemination versus in vitro fertilization according to indication  Thamara Viloria,
Embryonic imprinting perturbations do not originate from superovulation-induced defects in DNA methylation acquisition  Michelle M. Denomme, B.Sc., Liyue.
Potential role of circulating microRNAs as a biomarker for unexplained recurrent spontaneous abortion  Weibing Qin, M.D., Ph.D., Yunge Tang, M.D., Ning.
Does an increased body mass index affect endometrial gene expression patterns in infertile patients? A functional genomics analysis  Ioanna A. Comstock,
Gene expression profiling of human peri-implantation endometria between natural and stimulated cycles  Yunao Liu, M.Sc., Kai-Fai Lee, Ph.D., Ernest H.Y.
Reporting in vitro fertilization cycles to the Society for Assisted Reproductive Technology database: where have all the cycles gone?  David Kulak, M.D.,
Agnieszka Malcher, M. S. , Natalia Rozwadowska, Ph. D
Impact of final oocyte maturation using gonadotropin-releasing hormone agonist triggering and different luteal support protocols on endometrial gene expression 
Window of implantation transcriptomic stratification reveals different endometrial subsignatures associated with live birth and biochemical pregnancy 
Kenneth I. Aston, Ph. D. , Philip J. Uren, Ph. D. , Timothy G
Expression of insulin-like growth factors (IGFs) and IGF signaling: molecular complexity in uterine leiomyomas  Lan Peng, M.D., Yong Wen, M.D., Yulong.
DMRT1 mutations are rarely associated with male infertility
Reducing multiples: a mathematical formula that accurately predicts rates of singletons, twins, and higher-order multiples in women undergoing in vitro.
Volume 9, Issue 3, Pages (September 2017)
Chun Feng, M. D. , Shen Tian, Ph. D. , Yu Zhang, M. D. , Jing He, M. D
Dynamics of nitric oxide, altered follicular microenvironment, and oocyte quality in women with endometriosis  Pravin T. Goud, M.D., Ph.D., Anuradha P.
Live birth of twins derived from zona-free oocytes
Ali Sazci, Ph. D. , Nesrin Ercelen, M. D. , Emel Ergul, M. S
Ying-Ying Yu, Ph. D. , Cui-Xiang Sun, Ph. D. , Yin-Kun Liu, Ph. D
Assessing loss of imprint methylation in sperm from subfertile men using novel methylation polymerase chain reaction Luminex analysis  Akiko Sato, M.E.,
Potential diagnostic utility of intermittent administration of short-acting gonadotropin- releasing hormone agonist in gonadotropin deficiency  Carrie.
Cited2 protein level in cumulus cells is a biomarker for human embryo quality and pregnancy outcome in one in vitro fertilization cycle  Yuan Fang, Ph.D.,
Microbiota of the seminal fluid from healthy and infertile men
Proteomic analysis of individual human embryos to identify novel biomarkers of development and viability  Mandy G. Katz-Jaffe, Ph.D., David K. Gardner,
Increased risk of incident chronic medical conditions in infertile men: analysis of United States claims data  Michael L. Eisenberg, M.D., Shufeng Li,
Methylation changes in mature sperm deoxyribonucleic acid from oligozoospermic men: assessment of genetic variants and assisted reproductive technology.
Embryo incubation and selection in a time-lapse monitoring system improves pregnancy outcome compared with a standard incubator: a retrospective cohort.
Genome-wide sperm deoxyribonucleic acid methylation is altered in some men with abnormal chromatin packaging or poor in vitro fertilization embryogenesis 
Spontaneous fertility and in vitro fertilization outcome: new evidence of human papillomavirus sperm infection  Andrea Garolla, M.D., Bruno Engl, M.D.,
Influences on endometrial development during intrauterine insemination: clinical experience of 2,929 patients with unexplained infertility  Erin Foran.
Artificial oocyte activation with calcium ionophore does not cause a widespread increase in chromosome segregation errors in the second meiotic division.
Shi-Ling Chen, M. D. , M. Sc. , Xiao-Yun Shi, M. D. , M. Sc
G. Charles Ostermeier, Ph. D. , Robert J. Goodrich, B. S. , Michael P
Accurate single cell 24 chromosome aneuploidy screening using whole genome amplification and single nucleotide polymorphism microarrays  Nathan R. Treff,
Defects in imprinting and genome-wide DNA methylation are not common in the in vitro fertilization population  Verity F. Oliver, Ph.D., Harriet L. Miles,
Reply of the Authors Fertility and Sterility
Discovery of biomarkers of endometrial receptivity through a minimally invasive approach: a validation study with implications for assisted reproduction 
Sherman J. Silber, M.D.  Fertility and Sterility 
Variance in total levels of phospholipase C zeta (PLC-ζ) in human sperm may limit the applicability of quantitative immunofluorescent analysis as a diagnostic.
Epigenomic Profiling Reveals DNA-Methylation Changes Associated with Major Psychosis  Jonathan Mill, Thomas Tang, Zachary Kaminsky, Tarang Khare, Simin.
Andrew C. Bjonnes, M.S., Richa Saxena, Ph.D., Corrine K. Welt, M.D. 
Imprinting disorders and assisted reproductive technology
Volume 122, Issue 6, Pages (September 2005)
Normal birth after single-embryo transfer in a patient with excessive polypronuclear zygote formation following in vitro fertilization and intracytoplasmic.
Expression of leukemia inhibitory factor and its receptors is increased during differentiation of human embryonic stem cells  Lusine Aghajanova, M.D.,
Age-specific probability of live birth with oocyte cryopreservation: an individual patient data meta-analysis  Aylin Pelin Cil, M.D., Heejung Bang, Ph.D.,
Ongoing twin pregnancy after rescue intracytoplasmic sperm injection of unfertilized abnormal oocytes  Navid Esfandiari, D.V.M., Ph.D., H.C.L.D., E. Anne.
Value of the sperm deoxyribonucleic acid fragmentation level, as measured by the sperm chromatin dispersion test, in the outcome of in vitro fertilization.
Volume 10, Issue 3, Pages (March 2017)
Successful elective and medically indicated oocyte vitrification and warming for autologous in vitro fertilization, with predicted birth probabilities.
Human papillomavirus found in sperm head of young adult males affects the progressive motility  Carlo Foresta, M.D., Andrea Garolla, M.D., Daniela Zuccarello,
Highly heterogeneous genomic landscape of uterine leiomyomas by whole exome sequencing and genome-wide arrays  Svetlana A. Yatsenko, M.D., Priya Mittal,
Decreased fecundity and sperm DNA methylation patterns
Vaccinia virus–specific molecular signature in atopic dermatitis skin
Sperm deoxyribonucleic acid fragmentation as a prognostic indicator of assisted reproductive technology outcome  Mehdi Benchaib, M.D., Ph.D., Jacqueline.
Genetic evaluation procedures at sperm banks in the United States
Shilin Zhang, M. D. , Tao Wang, M. D. , Jun Yang, M. D. , Zhuo Liu, M
Elizabeth X. Wu, M.Sc., Paloma Stanar, Sai Ma, Ph.D. 
David H. Barad, M.D., M.S., Norbert Gleicher, M.D. 
Saad Elzanaty, M.D., Ph.D., Johan Malm, M.D., Ph.D. 
Volume 13, Issue 10, Pages (December 2015)
Array-based DNA methylation profiling in male infertility reveals allele-specific DNA methylation in PIWIL1 and PIWIL2  Carolin Friemel, Ole Ammerpohl,
Effect of two assisted oocyte activation protocols used to overcome fertilization failure on the activation potential and calcium releasing pattern  Dimitra.
Yinghui Ye, M. D. , Ph. D. , Chenming Xu, PhD. , Yuli Qian, B. Sc
Numerical chromosome anomalies detected in paternally derived pronuclei of tripronuclear zygotes after intracytoplasmic sperm injection  Ervin Macas,
Presentation transcript:

Assisted reproductive technology alters deoxyribonucleic acid methylation profiles in bloodspots of newborn infants  Molly S. Estill, M.S., Jay M. Bolnick, M.D., Robert A. Waterland, Ph.D., Alan D. Bolnick, M.D., Michael P. Diamond, M.D., Stephen A. Krawetz, Ph.D.  Fertility and Sterility  Volume 106, Issue 3, Pages 629-639.e10 (September 2016) DOI: 10.1016/j.fertnstert.2016.05.006 Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Figure 1 Intracytoplasmic sperm injection and IUI compared with NAT show differential methylation of clusters and gene bodies. (A) Total counts of differentially methylated clusters between conception groups for males and females, shown in blue and pink, respectively. Red bracket indicates comparisons of FH and FZ with IUI, presenting the greater degree of differential methylation in the FH vs. IUI comparison than that of FZ vs. IUI. (B) Distribution of the change in the β-value for statistically significant clusters, as a function of conception comparison. Changes in the female and male comparisons are shown in light red and blue, respectively. (C) Pie chart labeled “Genome Annotation” indicates the proportion of the human genome that lies within exons, introns, promoters, and intergenic regions. The pie chart labeled as “Cluster Annotation” provides the proportion of all statistically significant clusters (regardless of methylation change) that overlap exons, introns, promoters, and intergenic regions. Clusters that overlay one or more features are denoted as “partial.” Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Figure 2 Metastable epialleles at DUSP22 and SPATC1L show considerable and concerted differential methylation. University of California Santa Cruz (UCSC) genome browser representation of female comparisons between conception groups for MEs located at (A) DUSP22 and (B) SPATC1L. Hypermethylated clusters and hypomethylated clusters are colored in blue and orange, respectively. Cluster heights represent the magnitude of methylation change, in scale with the y axis. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 1 Samples and conception group comparisons subject to differential methylation analysis. (A) Number of individuals analyzed in this study, according to conception type and gender. (B) Directional arrows indicate that the conception group at the source of the arrow is the methylation dataset (control) against which that at the termination of the arrow (case) is being compared. (C) Pipeline provided by ChAMP was used to filter, normalize, and apply batch correction, to obtain corrected methylation values. Aclust was then implemented to calculate methylation changes in probe clusters, followed by downstream analyses. Concurrently, the same corrected methylation values are analyzed using a linear model to calculate differential methylation of individual probes and verify the results obtained from Aclust. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 2 Estimated blood cell composition does not affect the bloodspot methylation. Singular value decomposition analysis was performed, through the ChAMP pipeline, to determine the effect of blood cell proportions, estimated using the estimatecellcount function in minifi, on sample methylation. The association of each principle component with plate, assay characteristics, and blood cell proportions is indicated using P values. A black rectangle indicates the P value slots for the various blood cell types, abbreviated as follows: CD8 T-cells (CD8T), CD4 T-cells (CD4T), natural killer cells (NK), B-cells (Bcell), monocytes (Mono), and granulocytes (Gran). Assay characteristics are abbreviated as follows: bisulfite conversion (BSC), and hybridization (Hyb). Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 3 Unsupervised clustering of bloodspot methylation using principle component analysis does not effectively segregate the different conception groups. Principle component analysis of BMIQ-normalized 450k probes, filtered to only contain the allowed 394,454 probes for all bloodspot samples. Normal contour lines, at an ellipse probability of 68%, are indicated for each group. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 4 Trends in differentially methylated clusters between males and females of identical conception groups. Hypermethylation in the female group (compared with a male control) is shown in red, whereas hypomethylation is presented in blue. (A) Counts of clusters differentially methylated between females and males of the same conception group. (B) Counts of gene bodies differentially methylated between females and males of the same conception group. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 5 Trends in non-normalized differentially methylated clusters indicates marked differences between conception groups. Differentially methylated clusters generated from non-normalized β-values for (A) males and (B) females. (C) Differentially methylated clusters generated from non-normalized β-values for comparisons between males and females. Hypermethylated and hypomethylated clusters are represented in red and blue, respectively. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 6 Trends in differentially methylated probes, as determined by limma, are similar to trends seen using Aclust. Bars indicate the total counts of differentially methylated probes as calculated using limma, for males and females (shown in blue and red, respectively), for each conception comparison. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 7 Intracytoplasmic sperm injection and IUI show considerable differential methylation in gene bodies compared with NAT. Bars indicate the counts of differentially methylated gene bodies between conception groups. Counts of differentially methylated gene bodies generated for (A) male- and (B) female-specific comparisons. Hypermethylated and hypomethylated gene bodies are represented in red and blue, respectively. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 8 Enhancers consistently altered in ICSI groups compared with NAT. Populations of hypermethylated and hypomethylated enhancers altered in the IUI, FH, or FZ vs. NAT comparison were identified and enumerated. Quantities of hyper- or hypomethylated enhancers are denoted as “Hyper” and “Hypo,” respectively. The quantity of enhancers found in common between two or more comparisons and exhibiting identical methylation trends (e.g., increased or decreased methylation in both comparisons) are indicated in the intersections of the Venn diagram. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 9 Certain imprinted genes associated with metabolism and cancer exhibit differential methylation. UCSC genome browser images of promoter and gene bodies of imprinted genes (A) H19, (B) IGF2. Hypermethylated clusters and hypomethylated clusters are colored in blue and orange, respectively. Cluster heights represent the magnitude of methylation change, in scale with the y axis. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions

Supplemental Figure 10 Metastable epialleles adjacent to SFT2D3, WDR33, and LIMS2 are hypomethylated, only in the male comparisons, when comparing infertile groups with NAT. UCSC representation of male and female comparisons between conception groups for metastable epialleles located upstream of SFT2D3, WDR33, and LIMS2. Hypermethylated clusters and hypomethylated clusters are colored in blue and orange, respectively. Cluster heights represent the magnitude of methylation change, in scale with the y axis. Fertility and Sterility 2016 106, 629-639.e10DOI: (10.1016/j.fertnstert.2016.05.006) Copyright © 2016 American Society for Reproductive Medicine Terms and Conditions