Absence of sperm RNA elements correlates with idiopathic male infertility.

Approximately 13% of the general reproductive age population are challenged with fertility problems( 1 ). The American Society for Reproductive Medicine estimates that male factors and female factors contribute approximately equally to this condition, with the remaining one-quarter likely a combination of factors from both partners. After 12 months of unprotected intercourse without pregnancy, affected couples typically begin to seek care and explore the possibility of fertility treatments( 2 ). Today upwards of one-percent of the children born in the United States of America are conceived using Assisted Reproductive Techniques (ART)( 3 ). Typically, to establish the appropriate clinical treatment and minimize the risk of failure, an extensive evaluation of the female, and to a lesser extent the male, is undertaken. If no severe male or female factors are detected, fertility treatments such as Timed Intercourse (TIC) or Intrauterine Insemination (IUI) are recommended in combination with ovarian stimulation. After 3 or 4 unsuccessful IUI cycles or if either severe male or female factor is detected In Vitro Fertilization (IVF) with or without Intracytoplasmic Sperm Injection (ICSI) are suggested. Initial male factor assessment includes a review of reproductive history (time of subfertility, existence of previous pregnancies and sexual function), family history (consanguinity and familiar infertility history), relevant diseases (diabetes and mumps among others) and exposure to factors that negatively impact fertility (drugs, lifestyle and occupation) along with a comprehensive physical examination. The male contribution is further evaluated by semen analysis, with intra-individual variation gauged through the results of two semen analyses separated by a period of up to one month( 2 ). Assessment primarily relies on a defined series of semen parameters that include volume, sperm concentration, sperm motility, and sperm morphology. Other specific measures that may complement the workup include DNA fragmentation, the presence of antisperm antibodies, endocrine status, genetic and cytogenetic markers such as AZFa or AZFb Y microdelections representative of azoospermia. Although the evaluation of general semen parameters like sperm count, motility, and morphology may be useful in the diagnosis of obvious cases of male infertility where specific etiologic factors may be apparent, no single or set of semen parameters are highly predictive of male fertility status within the general population( 4 ). Current clinical practice focuses on whether there are sufficient spermatozoa with satisfactory motility and morphology to reach and likely fertilize the oocyte. Their utility in selecting the least invasive fertility treatment for idiopathic infertile couples appears limited( 5 ). Spermatozoa are not just a vehicle that simply delivers the male genomic contribution to the oocyte. Upon fertilization, the spermatozoon provides a complete, highly structured and epigenetically marked genome, that together with a defined compliment of RNAs and proteins, play a distinct role in early embryonic development( 6 , 7 ). While several studies have explored the effect of genetic variants such as SNP's( 8 ), copy number variants( 9 ), differential genome packaging( 10 ), differential methylation( 11 ), proteomic changes( 12 ), and differential sperm RNAs( 13 , 14 ) in male infertility, comparatively few have examined their effect within the context of the reproductive clinic( 15 - 19 ). Characterization of the RNAs retained in sperm by Next Generation Sequencing (NGS) has recently been reported( 20 - 22 ). In contrast with earlier array-based approaches, RNA-seq has revealed a rich and complex population of unique coding and non-coding transcripts such as sperm-specific isoforms, intronic retained and otherwise unannotated elements, and long and small non-coding RNAs( 20 - 22 ). The large number of unique sperm transcripts is suggestive of regulatory roles( 20 , 22 ) influencing fertilization, early embryogenesis, and the phenotype of the offspring( 20 , 23 ). The utility of spermatozoal microarray-based approaches to predict the outcome of different fertility treatments has met with varying degrees of success( 17 , 18 ). The intricacies of spermatozoal RNAs as revealed by NGS analysis( 22 ) suggest that this technology is much better suited to the task. The objective of this initial study was to evaluate the diagnostic potential of NGS as a prognostic assay of spermatozoal RNAs that can predict the birth outcome after different fertility treatments.

The ability of spermatozoal RNAs to predict the Live Birth (LB) for various fertility treatments was assessed within the context of the idiopathic infertile couple to ascertain if the underlying cause could be attributed to a male factor. As summarized in Table 1A , no significant differences between the choice of treatment modality as a function of the different patient variables including age or any of the semen parameters were observed, consistent with idiopathic infertility (one tailed ANOVA or Kruskal–Wallis test, p>0.05). Female age was significantly higher in couples that did not achieve pregnancy ( Table 1 B ; two tailed t-test, p=0.024) and this could attributed to unsuccessful IVF/ICSI ( Table 1 C ; two tailed t-test, p=0.004). A set of SREs required for live birth by natural conception were identified within positive group control I (LB by TIC during the first spermatogenic cycle and first attempt). Of the 278,605 sperm RNA elements surveyed, only elements that ranked above the 99 th percentile and were essentially at equivalent levels across group control I samples (IQR negative; outside InterQuartile Range ≥ 1.5X (Q3-Q1)) were defined as SREs required for natural conception. A total of 648 met the stringent criteria to be classified as required SREs (above the 99 th percentile rank present at a constant level in the control group). Nine of these 648 SREs corresponded to intergenic regions, 12 to sperm-specific intronic elements, and 42 were within 24 different non-coding RNAs all of which are likely regulatory. However the majority (585) were within exonic regions of 262 different genes, of which 40% were ontologically classified as associated with spermatogenesis, sperm physiology, fertility and early embryogenesis prior to implantation ( Figure 1 ). To discern whether SREs were indicative of fertility treatment outcome, all Group II test samples were assessed as a function of the required SRE abundance within these samples. As shown in Figures 2A (left and middle panels) all 648 required SRE were present in the control group and in 37 of the 56 samples within group II. As summarized in Figure 2B , the samples presenting all SREs have a 72% rate of success to achieve a LB within the first two treatment cycles (6 months). In comparison, as in Figures 2A (right panel), one third of the samples from group II have at least one SRE absent ( Supplemental Figure 1 ). Although the proportion of male or female factor ascribed to idiopathic infertility remains to be established, the proportion of patients identified with some SRE absent is similar to the expected rate ( 24 , 25 ). No correlation between the number of SREs absent and semen parameters and age of partners were observed ( Supplemental Figure 2 ). Samples with all SREs present have a similar high rate of LB for both TIC/IUI and ART, which is 77 and 75% respectively ( Figure 3A ). However the absence of some of the SREs reduces the LB rate by TIC/IUI from 77% to 27%, while the LB rate remains similar for ART (78%; Figure 3B ). As observed in Figure 3C , patients with all SREs are more likely to achieve LB by TIC/IUI as compared to those with some SRE(s) absent (two tailed Fisher exact test, p = 0.012). These significant differences were supported by a power of 0.7 and α error of 0.029. In comparison, when treated by ART, no differences in the number of SREs that were absent were observed when the LB and NLB groups were compared (two tailed Mann-Whitney, p=0.783). This is consistent with the view that ART may be able to “rescue” some otherwise impaired sperm functions such as transit to oocyte and/or fertilization as represented by functions of the genes corresponding to the missing SREs. Interestingly, six of the Group II couples failed to achieve a LB even by ART. A significantly higher female age was observed in this group (p=0.004 two tailed t test; Table 1C ) suggesting a potential age related female factor but only three of the six subjects were over 35 years of age. Of the couples that failed to achieve LB by ART with partners ≤ 35 years of age two did not have a complete set of SREs. These included NDRG1 (stress response), TESK1 (kinase), DBN1 (stabilizes gap junctions) and CAMTA2 (calcium dependent transcription factor) that are associated with embryogenesis or implantation. The results of an independent group of test samples (group III) are summarized in Table 2 . Group III-i was comprised of five couples from an independent fertility clinic. The presence of all SREs was confirmed and in all cases LB was achieved. In two cases, LB was achieved spontaneously or by IUI while the remaining three cases directly employed ART. The presence of all SREs in the samples suggests that SREs may provide a measure of male fecundity across clinics. Group III-ii was comprised four samples in which an unknown female factor was suggested. This was supported by the observation that in three of the couples ( Table II samples 6-8) since after a series of failed fertility treatments, a gestational carrier (GC) yielded successful results. The causative female factor was confirmed in Sample 9 ( Table 2 ii ) by the presentation of stage 2 endometriosis. All SREs were present in three (samples 7-9) of the four samples (samples 6-9). Two SREs were lacking in the sample 6 suggesting that they could be rescued by ART. The spectrum of test set analyses directly speaks to the utility of sperm RNA as a marker of fecundity.

Except for cases where examination of sperm reveals gross deficiencies in count, motility, or morphology, it is clear that current standard tests have a limited capacity to discern male factor infertility for couples presenting with idiopathic infertility( 26 ) and thereby be predictive of fertility treatments. This observation emphasizes the need to develop alternative strategies like NGS affords. In comparison to somatic cells RNA-seq data from sperm is characterized by the variability of absolute transcript abundance between samples due to the physiological fragmentation of spermatozoal RNAs as part of the extrusion of the cytoplasm as each spermatozoon is formed. However, this did not affect the 648 comparatively small exon-sized SREs that show no variability in 32 of the 35 TIC/IUI cases that achieved LB. It appears that the SREs that were absent in the 3 LB TIC/IUI cases were not diagnostic and perhaps could be removed from consideration. Their validation in a larger population will clarify which are essential for diagnosis and may be reflective of their role towards the birth of a healthy child. Standard clinical practice often utilizes TIC or IUI as the initial treatment for couples with idiopathic infertility. It is not until after 2-4 IUI cycles have failed that ART is recommended. The results shown in this study suggest that with all 648 SREs, couples that present for reproductive counselling have a significant high success rate (77%) using TIC/IUI in comparison when some SREs are absent (27%: two tailed Fisher tests p=0.012). When validated and if implemented as part of the clinical assessment, the absence of an SRE may suggest the earlier use of ART that given current practice could reduce the time to achieve LB. Approximately 40% of the SREs are within exonic regions of genes that are known to be involved in spermatogenesis, sperm motility, fertilization and the first steps of embryogenesis prior to implantation. This corresponds to 262 genes that when impaired would not be bypassed by TIC or IUI, but could likely be remediated using ART. This may reflect sperm no longer having to transit the woman's upper reproductive tract to reach the oocyte and that only those embryos that have shown successful fertilization and initial development are transferred to women using ART. However, some SREs are absent in patients where ART was not successful. Their contribution to the mechanism of successful fertilization and early embryogenesis remains to be elucidated. It is possible that these RNAs are critical for implantation and/or embryogenesis, and thus in these instances even ART cannot lead to a viable pregnancy as is perhaps exemplified in the absence of transcription factor CAMTA2 . RNA-seq data also affords the opportunity to SNP genotype each population of sperm RNAs that perhaps can reflect a series of health modifiers ( 27 ). For example, within this initial study 102 SREs were derived from 35 genes that have been associated with a spectrum of genetic disorders from enolase deficiency to Parkinson disease. This is of note given the global allelic imbalance in the gene expression favoring the paternal expression of these genes associated with complex diseases( 28 ) that may be compounded when the paternal effect of diet and environment on the future health of the child is considered ( 29 ). Continued development of this sperm RNA-seq methodology is expected to reveal genomic variants from this data( 27 ) that will better inform on the underlying origin of male infertility and possibly predict the future health of the child. The use of spermatozoal RNA NGS identified a set of molecular biomarkers that shows its potential to predict the success rate of the fertility treatments used. In comparison to a smaller microarray based study where 26 differential mRNAs were identified ( 18 ), NGS analysis identified 648 SREs suggesting that RNA-seq technology may more completely resolve variances in RNA profiles for the complex sperm cell.. The statistically significant differences observed in non-invasive treatment outcome based on the presence or absence of the complete set of SREs (two tailed Fisher test p=0.012) supports the view that sperm RNA analysis has the potential to effect clinical care for idiopathic infertile couples when used to assess the likelihood of success of TIC/IUI prior to employing ART. This may permit an informed choice towards a treatment paradigm that would help the female partner to avoid undergoing invasive procedures such as egg collection. The results of this 0.7 powered study should encourage a larger, blinded and controlled prospective analysis of patients using non-invasive treatments to ensure its utility prior to its introduction into the fertility clinic. Nevertheless, with the rapidly decreasing cost of NGS, deep sequencing of sperm RNA has the distinct potential to afford clinical benefit while enhancing our understanding of the father's contribution to the birth and life of a healthy child.

A retrospective study was designed to investigate whether spermatozoal RNAs could predict the outcome of various fertility treatment options used in the care of idiopathic infertile couples. RNA sequencing was used to obtain the spermatozoal RNA profile of patients included in the study. Several sperm RNA elements required for natural conception were defined and tested using the sperm of idiopathic infertile males of couples that underwent non-invasive or invasive treatments. Sample size was dictated by the availability of patients matching the strict criteria in the fertility clinics powering the study to 0.7 with an α error of 0.029. Semen samples were collected after IRB approval and informed consent from a total of 96 patients from the CReATe Fertility Centre, Toronto, Canada (Site 1) and the Harvard School of Public Health, Boston, USA (Site 2), then processed and frozen at -80°C. Only couples presenting with unexplained infertility by standard procedures as confirmed by a reproductive endocrinologist and andrologist were recruited to the study. All participants underwent some reproductive treatment ((TIC), (IUI), (IVF), or (ICSI)) due to their inability to achieve a successful live birth by spontaneous conception. Non-invasive treatments (TIC and IUI) were the first fertility treatment used in approximately 80% of the patients with a success rate of 65% in the two first cycles. After some unsuccessful IUI cycles (2.6 cycles in average) 26% of patients underwent ART treatments achieving 85% success in the first cycle. In contrast, 20% of the patients made the initial personal treatment decision to directly undergo ART with a success rate of 50% in first cycle. Couples were excluded from this study when the male partner considerably deviated from the standard semen parameters. This included males presenting with less than 10 million motile sperm indicative of a negative association of TMC and IUI outcomes ( 30 ). In addition, a female partner exhibiting low ovarian reserve validated by Anti-Müllerian Hormone (AMH) level (<15.7 pmol/L) or known history of hormonal disorders, showing evidence of stage 3 or 4 endometriosis, a history of chemotherapy or pelvic irradiation, as well as patients unable or unwilling to consent were excluded from the study. Semen parameters were assessed as described in the Supplemental Methods and this designated day 0 of a 90 day cycle corresponding to one complete spermatogenic cycle. The deidentified frozen samples were processed and analyzed at Wayne State University under the IRB protocols H-06-67-96 and HIC 095701MP2F. Sperm RNA from 96 samples was isolated, quality assessed, deep sequenced, and analyzed as described in the Supplementary Methods. The 72 samples passing all the sequence quality measures were divided into 3 groups for post hoc statistical analysis. Group I samples were used to determine the required sperm RNA elements (SREs) for “natural conception” live birth. This positive control population was derived from seven couples that summarily achieved a live birth by controlling the optimal fertility window (TIC) during the first cycle monitored for intercourse timing. This was considered the same as natural conception. The abundance of all members of this composite group of SREs was assessed within the remaining 65 samples that represented various fertility treatments. Group II test samples were comprised of (i) 29 couples treated by TIC after the first spermatogenic cycle or IUI (ii) 13 couples that were unsuccessful with IUI that subsequently utilized ART and (iii) 14 couples that personally decided to undergo ART after semen assessment. The Group III test samples were comprised of (i) samples from five couples from independent fertility clinic, that achieved a live birth and (ii) four likely female factor couples, three of whom only achieved a live birth with the use of a gestational carrier suggestive of a female factor, and the fourth presenting with stage 2 endometriosis, a known female factor. The results corresponding to the 72 RNA-seq data sets are available at the GEO (NCBI) repository ( GSE65683 ). Statistical analyses were performed using SigmaPlot, version 11 (Systat Software, San Jose, CA) and statistical tests were considered significant at p < 0.05. According to the normality of the parameter tested (male and female age, sperm motility, DFI index are normally distributed in contrast to total millions of sperm cells, sperm morphology and number of SREs absent), a parametric one-way analysis of variance (ANOVA) test or non-parametric Kruskal–Wallis one-way analysis of variance by ranks (α= 0.05) was used to detect differences in the average of different seminal parameters or SREs that were absent between the groups based on the treatment used. According to the normality of the parameter tested, a parametric Student's t-test or non-parametric Mann-Whitney U test (two tailed, α= 0.05) was used to detect differences in the average of different seminal parameters or SREs absent between the samples that achieved live birth (LB) or failed (NLB) within each group. Two tailed Fisher's exact test (α= 0.05) was used to compare the success rate of different fertility treatments in the presence or absence of the complete set of SREs. Gpower version 3.1 was used to calculate the power of the two tailed Fisher's exact test (α= 0.05) ( 31 ).