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Background: Technologies such as in vitro fertilization (IVF) are increasingly used to compensate for the loss of fertility associated with increasing maternal age and decline in oocyte quality. During IVF, superovulation yields more oocytes than are required, and the selection of oocytes for fertilization and implantation is based on poorly defined morphological features which are subject to user bias. Aim: We aim to develop a deep radiomic signature based on an artificial intelligence (AI) model in order to identify oocyte morphological changes corresponding to reproductive ageing in bright field images captured by optical light microscopy. This approach has potential for application in assessment of human oocytes. Method: Oocytes were collected from three groups of C57BL/6J female mice: young (4- to 5-week-old), aged (12-month-old) mice and aged mice treated with the NAD+ precursor nicotinamide mononucleotide (NMN), a treatment recently shown to rejuvenate aspects of fertility in aged mice. Deep learning, swarm intelligence and discriminative analysis were applied to images of mouse oocytes taken by bright field microscopy to identify a highly informative deep radiomic signature (DRS) of oocyte morphology. Approximately 25 oocyte images were derived from each group. Results: This signature distinguished morphological changes in oocytes associated with maternal ageing, which are imperceptible to an experienced embryologist, with 92% accuracy (AUC[Formula: see text]1), reflecting the age-induced decline in oocyte quality. We then employed the DRS to evaluate the impact of the NMN treatment. The DRS signature classified 60% of oocytes from NMN-treated aged mice as having a ‘young’ morphology, demonstrating the signature’s sensitivity to improvements in quality and reinforcing its applicability for oocyte selection. Conclusion: Our data illustrate the power of DRS for recognizing morphological features of cellular ageing, which outperforms current subjective methods relying on visual grading for the recognition and classification of oocytes based on maternal age.

The purpose of this study is to develop a deep radiomic signature based on an artificial intelligence (AI) model. This radiomic signature identifies oocyte morphological changes corresponding to reproductive aging in bright field images captured by optical light microscopy. Oocytes were collected from three mice groups: young (4- to 5-week-old) C57BL/6J female mice, aged (12-month-old) mice, and aged mice treated with the NAD+ precursor nicotinamide mononucleotide (NMN), a treatment recently shown to rejuvenate aspects of fertility in aged mice. We applied deep learning, swarm intelligence, and discriminative analysis to images of mouse oocytes taken by bright field microscopy to identify a highly informative deep radiomic signature (DRS) of oocyte morphology. Predictive DRS accuracy was determined by evaluating sensitivity, specificity, and cross-validation, and was visualized using scatter plots of the data associated with three groups: Young, old and Old + NMN. DRS could successfully distinguish morphological changes in oocytes associated with maternal age with 92% accuracy (AUC~1), reflecting this decline in oocyte quality. We then employed the DRS to evaluate the impact of the treatment of reproductively aged mice with NMN. The DRS signature classified 60% of oocytes from NMN-treated aged mice as having a ‘young’ morphology. In conclusion, the DRS signature developed in this study was successfully able to detect aging-related oocyte morphological changes. The significance of our approach is that DRS applied to bright field oocyte images will allow us to distinguish and select oocytes originally affected by reproductive aging and whose quality has been successfully restored by the NMN therapy.

Summary: Reproductive aging in female mammals is an irreversible process associated with declining oocyte quality, which is the rate-limiting factor to fertility. Here, we show that this loss of oocyte quality with age accompanies declining levels of the prominent metabolic cofactor nicotinamide adenine dinucleotide (NAD+). Treatment with the NAD+ metabolic precursor nicotinamide mononucleotide (NMN) rejuvenates oocyte quality in aged animals, leading to restoration in fertility, and this can be recapitulated by transgenic overexpression of the NAD+-dependent deacylase SIRT2, though deletion of this enzyme does not impair oocyte quality. These benefits of NMN extend to the developing embryo, where supplementation reverses the adverse effect of maternal age on developmental milestones. These findings suggest that late-life restoration of NAD+ levels represents an opportunity to rescue female reproductive function in mammals. : Declining oocyte quality is considered an irreversible feature of aging and is rate limiting for human fertility. Bertoldo et al. show that reversing an age-dependent decline in NAD(P)H restores oocyte quality, embryo development, and functional fertility in aged mice. These findings may be relevant to reproductive medicine. Keywords: oocyte, nicotinamide adenine dinucleotide (NAD+), nicotinamide mononucleotide (NMN), SIRT2, female fertility, infertility, reproductive aging, aging, embryo development, in vitro fertilization

Abstract Chemotherapy induced ovarian failure and infertility is an important concern in female cancer patients of reproductive age or younger, and non-invasive, pharmacological approaches to maintain ovarian function are urgently needed. Given the role of reduced nicotinamide adenine dinucleotide phosphate (NADPH) as an essential cofactor for drug detoxification, we sought to test whether boosting the NAD(P)+ metabolome could protect ovarian function. We show that pharmacological or transgenic strategies to replenish the NAD+ metabolome ameliorates chemotherapy induced female infertility in mice, as measured by oocyte yield, follicle health, and functional breeding trials. Importantly, treatment of a triple-negative breast cancer mouse model with the NAD+ precursor nicotinamide mononucleotide (NMN) reduced tumour growth and did not impair the efficacy of chemotherapy drugs in vivo or in diverse cancer cell lines. Overall, these findings raise the possibility that NAD+ precursors could be a non-invasive strategy for maintaining ovarian function in cancer patients, with potential benefits in cancer therapy.

Background and Aims: Chemotherapy induced ovarian failure and infertility is an important concern in female cancer patients of reproductive age or younger, and non-invasive, pharmacological approaches to prevent chemotherapy induced infertility are urgently needed. Here we investigate whether pharmacological elevation of nicotinamide adenine dinucleotide (NAD+) ameliorates chemotherapy induced female infertility in mice. Method: 8-week-old C57BL6 female mice were treated +/- chemotherapy (doxorubicin, Dox; 10 mg/kg) and +/- nicotinamide mononucleotide (NMN; 200 mg/kg i.p. once and 2 g/L in drinking water on-going), an orally bioavailable metabolic precursor to NAD+. Effects on fertility were measured by impact on ovarian reserve and folliculogenesis, ovulation rates and breeding performance. Effects on the ovarian NAD+ metabolome were assessed by mass spectrometry. A potential adverse effect of NMN on the efficiency of chemotherapy was assessed using a xenograft model of mammary cancer. Results: NMN treatment did not prevent a decline in the ovarian reserve caused by chemotherapy but did maintain the health of the remaining primordial follicle and total follicle populations, leading to a restoration in oocyte yield in chemo-treated mice (Dox vs Dox+NMN; P