Deep sequencing of DNA from urine of kidney allograft recipients to estimate donor/recipient-specific DNA fractions.

Kidney transplantation is the treatment of choice for patients with end-stage kidney failure, but transplanted allograft could be affected by viral and bacterial infections and by immune rejection. The standard test for the diagnosis of acute pathologies in kidney transplants is kidney biopsy. However, noninvasive tests would be desirable. Various methods using different techniques have been developed by the transplantation community. But these methods require improvements. We present here a cost-effective method for kidney rejection diagnosis that estimates donor/recipient-specific DNA fraction in recipient urine by sequencing urinary cell DNA. We hypothesized that in the no-pathology stage, the largest tissue types present in recipient urine are donor kidney cells, and in case of rejection, a larger number of recipient immune cells would be observed. Extensive in-silico simulation was used to tune the sequencing parameters: number of variants and depth of coverage. Sequencing of DNA mixture from 2 healthy individuals showed the method is highly predictive (maximum error < 0.04). We then demonstrated the insignificant impact of familial relationship and ethnicity using an in-house and public database. Lastly, we performed deep DNA sequencing of urinary cell pellets from 32 biopsy-matched samples representing two pathology groups: acute rejection (AR, 11 samples) and acute tubular injury (ATI, 12 samples) and 9 samples with no pathology. We found a significant association between the donor/recipient-specific DNA fraction in the two pathology groups compared to no pathology (P = 0.0064 for AR and P = 0.026 for ATI). We conclude that deep DNA sequencing of urinary cells from kidney allograft recipients offers a noninvasive means of diagnosing acute pathologies in the human kidney allograft.

Alterations in long noncoding RNAs in women with and without polycystic ovarian syndrome.

Long noncoding RNAs (lncRNAs) are RNA transcripts over 200 nucleotides long that are not translated into protein; however, there is increasing evidence of their regulatory functions. To date, there are few studies measuring lncRNA in control women or women with polycystic ovary syndrome (PCOS). OBJECTIVE: To determine lncRNA differences between PCOS and control women. DESIGN: Cross sectional study. PATIENTS: Twenty four anovulatory women with all three diagnostic features of PCOS compared to 24 control women in the follicular phase of their menstrual cycle from a PCOS biobank. RESULTS: Women with PCOS were age and weight matched compared to the control women but were significantly insulin resistant and hyperandrogenemic (P < .01). Eight lncRNA (P < .05) were detected that differed between PCOS and control women, but only MIRLET7BHG correlated with body mass index (r = .66, P < .05). No lncRNA correlated with antimullerian hormone (AMH) levels, insulin resistance (HOMA-IR) or the free androgen index (FAI). Ingenuity pathway assessment (IPA) did not identify any functional pathways for the lncRNAs. CONCLUSION: LncRNAs differ between anovulatory PCOS and control women in the follicular phase of the menstrual cycle. It is unclear if this is due to inherent differences between PCOS and control women or due to changes in lncRNA that are menstrual cycle dependent. However, their IPA did not identify linked pathways, likely because few functions are as yet assigned to these lncRNAs.