OBJECTIVE: To accurately determine mitochondrial DNA (mtDNA) levels in human blastocysts. DESIGN: Retrospective analysis. SETTING: IVF clinic. PATIENT(S): A total of 1,396 embryos derived from 259 patients. INTERVENTION(S): Blastocyst-derived trophectoderm biopsies were tested by next-generation sequencing (NGS) and quantitative real-time polymerase chain reaction (qPCR). MAIN OUTCOME MEASURE(S): For each sample the mtDNA value was divided by the nuclear DNA value, and the result was further subjected to mathematical analysis tailored to the genetic makeup of the source embryo. RESULT(S): On average the mathematical correction factor changed the conventionally determined mtDNA score of a given blastocyst via NGS by 1.43% ± 1.59% (n = 1,396), with maximal adjustments of 17.42%, and via qPCR by 1.33% ± 8.08% (n = 150), with maximal adjustments of 50.00%. Levels of mtDNA in euploid and aneuploid embryos showed a statistically insignificant difference by NGS (euploids n = 775, aneuploids n = 621) and by qPCR (euploids n = 100, aneuploids n = 50). Blastocysts derived from younger or older patients had comparable mtDNA levels by NGS ("young" age group n = 874, "advanced" age group n = 514) and by qPCR ("young" age group n = 92, "advanced" age group n = 58). Viable blastocysts did not contain significantly different mtDNA levels compared with unviable blastocysts when analyzed by NGS (implanted n = 101, nonimplanted n = 140) and by qPCR (implanted n = 49, nonimplanted n = 51). CONCLUSION(S): We recommend implementation of the correction factor calculation to laboratories evaluating mtDNA levels in embryos by NGS or qPCR. When applied to our in-house data, the calculation reveals that overall levels of mtDNA are largely equal between blastocysts stratified by ploidy, age, or implantation potential.
OBJECTIVE: To accurately determine mitochondrial DNA (mtDNA) levels in human blastocysts. DESIGN: Retrospective analysis. SETTING: IVF clinic. PATIENT(S): A total of 1,396 embryos derived from 259 patients. INTERVENTION(S): Blastocyst-derived trophectoderm biopsies were tested by next-generation sequencing (NGS) and quantitative real-time polymerase chain reaction (qPCR). MAIN OUTCOME MEASURE(S): For each sample the mtDNA value was divided by the nuclear DNA value, and the result was further subjected to mathematical analysis tailored to the genetic makeup of the source embryo. RESULT(S): On average the mathematical correction factor changed the conventionally determined mtDNA score of a given blastocyst via NGS by 1.43% ± 1.59% (n = 1,396), with maximal adjustments of 17.42%, and via qPCR by 1.33% ± 8.08% (n = 150), with maximal adjustments of 50.00%. Levels of mtDNA in euploid and aneuploid embryos showed a statistically insignificant difference by NGS (euploids n = 775, aneuploids n = 621) and by qPCR (euploids n = 100, aneuploids n = 50). Blastocysts derived from younger or older patients had comparable mtDNA levels by NGS ("young" age group n = 874, "advanced" age group n = 514) and by qPCR ("young" age group n = 92, "advanced" age group n = 58). Viable blastocysts did not contain significantly different mtDNA levels compared with unviable blastocysts when analyzed by NGS (implanted n = 101, nonimplanted n = 140) and by qPCR (implanted n = 49, nonimplanted n = 51). CONCLUSION(S): We recommend implementation of the correction factor calculation to laboratories evaluating mtDNA levels in embryos by NGS or qPCR. When applied to our in-house data, the calculation reveals that overall levels of mtDNA are largely equal between blastocysts stratified by ploidy, age, or implantation potential.
Authors: Amber M Klimczak; Lucia E Pacheco; Kelsey E Lewis; Niloofar Massahi; Jon P Richards; William G Kearns; Antonio F Saad; John R Crochet Journal: J Assist Reprod Genet Date: 2018-03-05 Impact factor: 3.412
Authors: Neelke De Munck; Alberto Liñán; Ibrahim Elkhatib; Aşina Bayram; Ana Arnanz; Carmen Rubio; Nicolas Garrido; Barbara Lawrenz; Human M Fatemi Journal: J Assist Reprod Genet Date: 2019-08-07 Impact factor: 3.412
Authors: Xin Tao; Jessica N Landis; Rebecca L Krisher; Francesca E Duncan; Elena Silva; Agnieszka Lonczak; Richard T Scott; Yiping Zhan; Tinchun Chu; Richard T Scott; Nathan R Treff Journal: J Assist Reprod Genet Date: 2017-10-24 Impact factor: 3.412
Authors: Ana Arnanz; Neelke De Munck; Aşina Bayram; Ahmed El-Damen; Andrea Abdalla; Ibrahim ElKhatib; Laura Melado; Barbara Lawrenz; Human M Fatemi Journal: J Assist Reprod Genet Date: 2020-05-06 Impact factor: 3.412