Abstract
Objective
To harmonize standard operating procedures (SOPs) and standardize the recording of associated data for collection, processing, and storage of fluid biospecimens relevant to endometriosis.
Design
An international collaboration involving 34 clinical/academic centers and 3 industry collaborators from 16 countries on 5 continents.
Setting
In 2013, 2 workshops were conducted, followed by global consultation, bringing together 54 leaders in endometriosis research and sample processing worldwide.
Patient(s)
None.
Intervention(s)
Consensus SOPs were based on: [1] systematic comparison of SOPs from 18 global centers collecting fluid samples from women with and without endometriosis on a medium/large scale (publication on >100 cases), [2] literature evidence where available, or consultation with laboratory experts otherwise, and [3] several global consultation rounds.
Main Outcome Measure(s)
Standard recommended and minimum required SOPs for biofluid collection, processing, and storage in endometriosis research.
Result(s)
We developed recommended standard and minimum required SOPs for the collection, processing, and storage of plasma, serum, saliva, urine, endometrial/peritoneal fluid, and menstrual effluent, and a biospecimen data-collection form necessary for interpretation of sample-derived results.
Conclusion(s)
The Endometriosis Phenome and Biobanking Harmonisation Project SOPs allow endometriosis research centers to decrease variability in biofluid sample results, facilitating between-center comparisons and collaborations. The procedures are also relevant to research into other female conditions involving biofluid samples subject to cyclic reproductive influences. The consensus SOPs are based on the best available evidence; areas with limited evidence are identified as requiring further pilot studies. The SOPs will be reviewed based on investigator feedback, and through systematic tri-annual follow-up. Updated versions will be made available at: endometriosisfoundation.org/ephect.
Key Words: Endometriosis, standardization, standard operating procedures, biological fluid samples, EPHect
Discuss: You can discuss this article with its authors and with other ASRM members at http://fertstertforum.com/rahmioglun-werf-ephect-iii/
Many centers worldwide have been collecting blood and other fluid samples from women with and without endometriosis, with the aim of identifying potential diagnostic biomarkers and novel drug targets for the disease (1). Molecular profiles obtained toward these goals include, but are not limited to, changes at the deoxyribonucleic acid (DNA), ribonucleic acid (RNA), protein, and metabolite levels detected in various bodily fluids. However, variability in specimen collection, processing, and storage methods can act as a considerable source of bias and measurement error, obscuring or entirely preventing detection of disease-related molecular perturbations 2, 3.
Standard operating procedures (SOPs) and recommendations for blood collection in reproductive biology research have been published 4, 5, but none of these exist for other fluid specimens such as urine, saliva, or peritoneal and endometrial fluid. The majority of biospecimens collected for endometriosis research worldwide are collected and processed using different, sometimes nonspecified SOPs, making comparisons among studies, and data pooling, extremely difficult. Standardized collection of biospecimens across centers using internationally agreed-on SOPs—based on existing scientific evidence and consensus—is likely to reduce variability and facilitate comparability of results and enhance the detection of endometriosis biomarker relationships through multi-center collaborative studies. It would also allow meaningful comparison among different patient subpopulations and ethnic groups, and enable adequately powered, targeted studies on such groups that are less prone to between-center technical variability in results. Successful investigation of fluid markers among many centers, in both formally designed and ad hoc consortia utilizing de novo sample collection or pooled existing data, has been well established in the investigation of other disease outcomes 6, 7, 8, 9, 10, 11, 12.
Efforts to create and share evidence-based SOPs are underway in several research fields, such as those led by the National Cancer Institute (NCI) in the United States 13, 14, the Biobanking and Biomolecular Resource Research Infrastructure (BBMRI) program in Europe (15), and many other international organizations, for various purposes (Table 1). A successful model for the impact that standardized biobanking can have on research is British Columbia's multi-institutional and multidisciplinary ovarian cancer research group (OVCARE). Founded in 2000, this initiative has grown from a small group of researchers and disconnected research projects to a coherent team that is recognized internationally as leading the study of ovarian cancer, exemplified by a series of important biobank-based publications that have fundamentally changed the way ovarian cancer research is being performed 16, 17, 18.
Table 1.
List of major organizations that have published best-practice documents regarding biospecimen collections for research or clinical use.
| Organization | URL |
|---|---|
| National Cancer Institute: Biorepositories and Biospecimen Research Branch | http://biospecimens.cancer.gov/practices/ |
| International Society for Biological and Environmental Biorepositories (ISBER) | http://c.ymcdn.com/sites/www.isber.org/resource/resmgr/Files/2012ISBERBestPractices3rdedi.pdf |
| The International Agency for Research on Cancer (IARC) | http://ibb.iarc.fr/docs/recommendations_BRC.pdf |
| The Organisation for Economic Cooperation and Development (OECD) | http://www.oecd.org/dataoecd/7/13/38777417.pdf |
| Medical Research Council (MRC) | http://www.mrc.ac.uk/news-events/publications/human-tissue-and-biological-samples-for-use-in-research/ |
| Australian Biospecimen Network (ABN) | http://abrn.net/what-we-do/protocols/ |
| American Society of Clinical Pathology (ASCP) | http://www.ascp.org/PDF/BOC-PDFs/CMP/CMPBooklet.pdf |
The mission of the World Endometriosis Research Foundation (WERF) Endometriosis Phenome and Biobanking Harmonisation Project (EPHect) is to develop a consensus on standardization and harmonization of phenotypic surgical/clinical data and biologic sample–collection methods in endometriosis research. Specifically, EPHect provides evidence-based guidelines to facilitate large-scale, internationally collaborative, longitudinal, epidemiologically robust, translational biomarker and treatment target–discovery research in endometriosis. The guidelines are on: [1] detailed surgical and clinical and epidemiologic phenotyping (phenome) data to be collected from women with and without endometriosis to allow collaborative subphenotype discovery and validation analyses; and [2] SOPs for collection, processing, and long-term storage of biologic samples from women with and without endometriosis. To the best of our knowledge, this harmonization initiative is unique in terms of its scope, as it addresses standardization of phenotypic data collection and biologic sampling procedures simultaneously for a specific disease, based on consensus from a large group of academic and industrial leaders in endometriosis research. The initiative is a direct response to the key priorities of phenome data collection and SOP harmonization identified in Endometriosis Research Directions workshops held in 2008 (19) and 2011 (1), and it will allow the investigation of a substantial number of other research priorities highlighted.
The present article describes the development of evidence-based SOPs for the collection, processing, and storage of 6 fluid-sample types relevant to endometriosis research: blood, urine, saliva, peritoneal fluid, endometrial fluid, and menstrual fluid. The development of the surgical (EPHect SSF and MSF) (20) and clinical questionnaires (EPHect EPQ-S and EPQ-M) (21) for standardized phenotypic data collection were described in our 2 previous articles in the series; evidence-based SOPs for tissue (ectopic and eutopic endometrium, myometrium, and peritoneum) collection are described in our final article (22).
Methods
We conducted 2 workshops in March and July 2013, followed by several rounds of expert review, bringing together 54 leaders in endometriosis research and management and in sample processing from 34 clinical/academic centers and 3 industry collaborators in 16 countries to develop and reach consensus on evidence-based phenome collection and SOP guidelines (Fig. 1; 20). During workshop I and a subsequent consultation round, we identified 18 centers worldwide that collect biologic fluid samples from endometriosis cases and controls on a large scale (criterion: publication on >100 cases); all provided SOPs for sample collection, processing, and storage. Six fluid sample types were collected by the centers (blood, urine, saliva, peritoneal fluid, endometrial fluid, and menstrual fluid; Table 2). Quantities collected were often a balance between volumes sufficient to conduct a wide range of future experiments (biobanking); participant-based acceptability; and the costs of collection, processing, and long-term storage.
Figure 1.
Flow diagram depicting the WERF EPHect development and consensus process (biological fluid sample SOPs).
Table 2.
Number of centers, and the ranges of quantities collected for blood, urine, saliva, peritoneal fluid, endometrial fluid, and menstrual effluent.
| No. of centers | Quantities collected | |
|---|---|---|
| Blood | 18 | 10–35 ml |
| Urine | 6 | 20–120 ml |
| Saliva | 4 | 500 μl–2 ml |
| Peritoneal fluid | 8 | 1–25 ml |
| Endometrial fluid | 6 | 20–400 μl |
| Menstrual effluent | 3 | No data |
In addition to the information provided by the 18 centers, we searched for publicly available SOPs from general large-scale biobanking efforts (e.g., UK Biobank); large biorepositories (International Society for Biological and Environmental Biorepositories [ISBER]; the NCI Biorepositories and Biospecimen Research Branch [NCI-BBRB]; and the Australian Biospecimen Network [ABRN]). A systematic literature search was conducted in PubMed for English-language publications describing (crucial steps in) SOPs, using the following search terms: “standard operating procedure” with “endometriosis” or “blood” or “urine” or “endometrial fluid” or “peritoneal fluid” or “menstrual effluent” or “fluid samples” or “best practice” or “biobank.” Reference lists of retrieved articles were hand-searched for additional references and material. In addition, online material from biobanks and biorepositories was sought through the Google search engine with the same search terms. On the basis of this information, we compiled draft consensus SOPs, identifying steps that varied between center-specific SOPs, but for which little or no evidence could be obtained. Prior to workshop II, consensus documents and associated evidence and queries were distributed to the WERF EPHect Working Group. During workshop II, and a separate e-mail consultation process among those who were unable to attend the workshop, the final consensus SOPs were reviewed and agreed on (Supplemental Tables 1–6 and Appendixes 1–6, available online).
Although validity, reliability, and scientific advancement are the main goals of EPHect, an important point acknowledged by the WERF EPHect Working Group was that there are likely to be differences in resources and logistics among centers that may mean they are unable to adhere to some of the strictest protocol standards. All experts therefore agreed on 2 tiers for most steps in the SOPs: standard recommended and minimum required. We strongly advise standard recommended collection SOPs to be adopted when possible, as they will yield results that are least prone to variation and degradation of the samples; the minimum required SOP steps are offered to provide the fundamentals for standardization that need to be adhered to as an absolute minimum requirement given unavoidable logistical and budgetary circumstances. It is important to note that publications of results generated using samples collected following the WERF EPHect SOPs need to state explicitly which EPHect procedures were used and any alterations made to them. Following good scientific practice, we strongly recommend that each center maintain a copy of the details of the exact protocol used.
When collecting biologic samples for research purposes, additional data items need to be collected to allow interpretation of results from the samples, such as recent medication use by the participant and her menstrual-cycle phase at the time of sample collection. For this purpose, the WERF EPHect Working Group developed a consensus Biospecimen Form (Supplemental Appendix 7, available online) to be completed at each sample collection event.
Approval by an ethics committee or institutional review board was not required for formation of the WERF EPHect Working Group, review of existing literature, nor consensus regarding best practices for endometriosis research described within the WERF EPHect 4-article series. This endeavor did not include data from human subjects. A comprehensive list of declared conflicts of interest for each of the authors and members of the WERF EPHect Working Group is provided.
Results
Below, we describe the rationale behind the development of the WERF EPHect SOPs for the collection, processing, and storage of blood and its derivatives (serum, plasma, and red/white blood cells), urine, saliva, peritoneal fluid, endometrial fluid, and menstrual effluent.
Blood
Blood is most usefully banked after separation into its derivatives (serum, plasma, and red/white blood cells), to allow the widest possible future use (Fig. 2). Peripheral blood allows the measurement of a broad range of biomolecules, in both patients and healthy volunteers, and relatively large volumes can be collected. However, peripheral blood includes a complex mix of molecules reflecting many biologic processes in the body, in which biologic changes relevant to the disease may not be detected as readily as in a disease-related tissue. When collecting blood samples for a study, several important decisions need to be made regarding: [1] timing and conditions of sample collection; [2] use of anticoagulants and clot accelerators in collection tubes; [3] sample stability between collection and processing; [4] processing; and [5] long-term storage. We describe important aspects of each of these, and how they are dealt with in the SOPs. Eighteen EPHect centers provided blood SOPs for consensus agreement.
Figure 2.
Potential uses of blood constituents in genetic, expression, protein, and metabolite analyses.
Timing and conditions of sample collection
The time of day that blood is collected from a participant is crucial if the aim is to measure biomarkers that are affected by physiological state, circadian rhythms, fasting status, or other factors that could result in changes in the endogenous concentrations of these biomolecules. For example, many metabolic markers, as well as certain hormones such as insulin, change in concentration after food consumption. Therefore, the time since the participant had anything to eat or drink except plain water should be recorded, and ideally samples should be collected after a 10-hour fast (23). If blood samples are collected on the day of surgery, they should be collected prior to induction of anesthesia, as anesthetic drugs can have a profound effect on biomarker detection (24).
It is important to consider any other aspects of the timing of sample collection that could bias measurements. Recording the date of sample collection is universally important, particularly if biomarkers with seasonal variation (e.g., vitamin D) are of interest. Menstrual details including the last menstrual period (LMP) date should be recorded, to allow for menstrual cycle variation in analysis. Recent drugs used should be recorded. The WERF EPHect SOPs and biospecimen data collection form take account of these important considerations; however, if the investigator has a specific interest in a particular biomarker, it is advisable to test the sensitivity of its measurement to the specified sampling timing and conditions. An example would be the measurement of stress hormones (cortisol), which will be heavily influenced by not only the diurnal cycles but also the physiological and psychological state of the participant and time of day (25) and therefore should not be conducted on the day of surgery.
Anticoagulants and clot accelerators
The type of anticoagulant used in tubes for blood sample collection affects how the sample can be used (26). Detected concentration levels of certain biomarkers can vary with the type of anticoagulant used. For example, it has been shown that concentration of tumor necrosis factor–alpha and interleukin-6 are highest in ethylenediaminetetraacetic acid (EDTA) plasma in comparison to heparin and citrate plasma samples (27), which are the most commonly used types of anticoagulants. Particular anticoagulants are recommended, or even required, for certain analytical purposes (28). EDTA tubes are often the first preferred type, as they are suitable for a wide range of DNA-based and protein assays (26). Lithium–heparin is preferred for plasma-based metabolomic studies (26). Citrate tubes are recommended if the interest is to perform functional clotting-factor assays (26); however, this tube type is not commonly a priority as the liquid anticoagulant leads to lower biomarker concentrations as a result of dilution, dependent on the individual's hematocrit and sample volume (29).
To obtain serum samples, whole blood needs to be clotted and the supernatant (serum) removed. Clots form very slowly in tubes left untreated, and serum separator tubes with clot accelerators (most notably silica and thrombin) are available to speed up the process. Silica is most commonly used because of relatively low cost and because it does not appear to affect measurable concentrations for a range of different assays 30, 31, 32, 33. Serum samples are suitable for most clinical biochemistry and metabolomic studies, but they may not be optimal for other assays, such as proteomics, because clot-related peptides can contaminate the sample 34, 35. As an illustration of biobank-based collection tube prioritization, UK Biobank collects 45 ml of blood from each participant and prioritizes EDTA and lithium–heparin plasma tubes, as they apply to a wide range of DNA-based and protein assays. For serum collection, they use silica as a clotting factor (26).
Sample stability between collection and processing/storage
The time lapse between sample collection and processing/storage, as well as temperature conditions, are crucial variables affecting the stability of molecules in samples. In general, keeping samples at 4°C (or on ice) from collection until storage minimizes enzymatic degradation of many biomolecules (36). The length of time for which biomolecules are stable is variable. DNA is one of the most stable biomolecules (36); certain metabolites begin to degrade within 2 hours after blood sample collection (37), whereas substantial degradation of messenger ribonucleic acid (mRNA) occurs within the first half hour (4).
For most uses, therefore, blood samples should be processed and stored as soon as possible (within 2 hours) or at most within 4 hours 37, 38. If there is a longer delay in processing, pilot studies should be conducted to test the stability of individual biomarkers, as some biomarkers are stable for up to 48 hours 39, 40. Such pilot studies to test measurement sensitivity are recommended as standard in any case where the biomolecule of interest is defined from the outset. RNA integrity is maintained with the immediate postcollection addition of commercially available inhibitors of RNAse enzymes such as RNAlater® or PAXgene tubes®, although these can be costly on a large scale (26). RNAse inhibitors compromise the utility of the samples for other assays, and therefore a separate blood sample aliquot specific for RNA analysis should be collected if possible within study budget constraints. Live cells harvested for direct experiments or culture are stable at room temperature for up to 48 hours, but within that time window, they should be either cultured or cryopreserved in liquid nitrogen (LN2) after pretreatment with dimethylsulfoxide (DMSO) to avoid cell rupture 26, 41.
Processing
Centrifugation is performed to separate blood into its constituent components. The duration, speed, and temperature conditions under which centrifugation is performed vary considerably among centers. For example, the UK Biobank centrifuges blood samples at 2,500 x g for 10 minutes at 4°C (26), and the NCI recommends centrifuging 1,100–1,300 x g for 10–20 minutes at room temperature (38). We suggest centrifugation at 2,500 x g for 10 minutes, based on the typical parameter values observed in the contributing EPHect centers, and in line with the UK Biobank. We recommend cooled (4°C) centrifugation as standard to avoid any effect of temperature on unknown biomarker stability. It is key for each center to apply centrifuge parameters of duration, speed, and temperature consistently across all samples processed; record these; and report them in all publications derived from the samples.
Long-term storage
The number and volume of the sample aliquots created should strike a balance between minimizing future freeze–thaw cycles and use of freezer space. Repeated freeze–thaw cycles are detrimental to the stability of biomolecules in some samples and should be avoided by creating multiple small-volume aliquots (100–500 μl) upfront before freezing 41, 42. If freezer space is limited, initial aliquots can be made in larger volumes (1.8–4.5 ml) and then aliquoted into smaller volumes the first time the aliquot is accessed.
Stability studies for a range of biomolecules have shown that samples should be stored as a minimum requirement in −80°C mechanical freezers for long-term storage (36). In the 1990s, a study showed that, depending on the location of the sample in the mechanical 80°C freezers, the actual temperature can fluctuate between −90°C and −43.5°C (43).
Liquid nitrogen freezers, which are colder and have less temperature variability than mechanical freezers (34), are recommended for standard long-term sample storage; however, they are more expensive and require access to a regular LN2 source. If several LN2 freezers are in the same room, oxygen sensors are required. Furthermore, −80°C and LN2 freezers need to be manually checked at least twice a week for temperature variations, and every freezer should be equipped with an alarm system to detect such variation. In addition, it is important to: [1] split samples from the same individual between freezers in case of a freezer malfunction, and [2] have an empty backup freezer available if possible. Freezers must be connected to power generators to ensure continued functioning during a power emergency, and to battery backups to protect them from power variations. An emergency plan must be designed that clearly specifies responsibilities and tasks to personnel if samples need to be moved to backup freezers.
Urine
Urine has been widely used in metabolomic and proteomic studies for biomarker, hormone, and related metabolite detection 37, 44, 45 because of its easy, non-invasive collection in large quantities (46). A potential disadvantage is the unknown relevance of the molecules excreted in urine to the disease of interest. Furthermore, creatinine needs to be measured in samples to determine urine concentration, as this varies substantially within individuals over time (47). Six EPHect centers provided urine-sample SOPs.
Sample collection
The presence of host cells (e.g., harboring viruses) or bacterial cells in urine is a potential source of contamination that can influence the metabolic profile (37). Therefore, a “clean catch” protocol for sample collection is preferred, as it reduces the incidence of cellular and microbial contamination. The timing of sample collection for urine is complex, because each urine sample reflects what was metabolized and excreted since the previous void. The most comprehensive protocol collects all urine voided over a 24-hour period, which reflects excretion over the course of 1 day. However, this protocol may be unacceptable to some participants, or impossible for logistical or budgetary reasons. As an alternative, an overnight collection (collecting all urine from bedtime to the first morning void) may be preferred. First morning void samples can be collected, which represent the overnight period unless the participant voided during the night (23) and are better than a “spot urine” sample collected at a random time during the day 26, 46. If spot urines are collected, information should be collected on the timing of the last pre-collection void. The WERF EPHect standard recommendation is to collect clean catch, first morning void samples, with time of last food/drink consumption, any night voiding, and time of sample collection, recorded using the EPHect Biospecimen Form (Supplemental Appendix 7).
Sample stability, processing, and storage
The EPHect standard recommendation is to maintain urine samples at 4°C (or on ice) until processing and storage, to reduce the effects of possible enzymatic/cellular activities (37), and to store within 2 hours of collection. If first morning void urine samples are collected, the participant should keep the collected sample in the refrigerator and either bring the sample on ice to the clinic, or ship it on ice overnight, in which case the sample should be processed and stored within a maximum of 48 hours (28). Long-term storage of urine samples should ideally be in LN2 freezers or in −80°C freezers (see blood storage section).
Saliva
Saliva samples are often used for DNA studies when blood sampling is not desirable or feasible (48), although an obstacle is that the sample can be contaminated with bacterial DNA (49). Saliva can also be used to measure other biomolecules such as hormones, with the limitation that only free (unbound) hormones are present and thus the concentrations are relatively low (50). Four EPHect centers provided saliva SOPs.
Sample collection
Several methods are available for collecting saliva for DNA, including “swish and spit,” saliva collection kits for DNA (e.g., Oragene®, DNAgard®, Norgen®), or swabs. The swish and spit method or Oragene® kits are recommended as standard in EPHect, providing the best DNA quality and yield 51, 52, 53. For general biomarker studies, the “passive drool” method for sample collection is preferred over other methods that stimulate saliva production (e.g., chewing on cotton), as the latter can alter hormone levels (50). In addition, actively spitting has been shown to tighten muscles and may affect flow rate and concentration of proteins in saliva 54, 55. The amount of saliva collected is important for DNA yield (56). We recommend collection of 2 ml of saliva as the standard, with 1 ml as the minimum amount. To encourage participants to provide a sufficient sample, they can be shown pictures that can visually stimulate saliva production (e.g., pictures of lemons). Timing of saliva collection may be important, particularly if measuring stress biomarkers (46) and collecting time/date information are critical. In addition, it is important to record when the participant last brushed their teeth; chewed gum; smoked; or consumed alcohol, spicy food, or fishy food within the last 24 hours, as these can affect sample quality (see EPHect Biospecimen Form, Supplemental Appendix 7).
Sample stability, processing, and storage
Some salivary hormones are relatively stable in samples kept at room temperature for up to 1 week, although contamination with mold can be problematic. Thus, EPHect recommends keeping the sample chilled (4°C) 57, 58. For extraction of DNA using commercial saliva collection kits, the product instructions should be followed. Long-term storage should be in −80°C freezers as a minimum requirement, or in LN2 freezers per standard (see blood storage section).
Peritoneal Fluid
Peritoneal fluid, present in the abdominal/pelvic cavity, reflects its specific microenvironment and has been used by a number of studies to investigate the roles of various constituent molecules in relation to endometriosis 59, 60, 61. Peritoneal fluid volume increases during the follicular phase of the menstrual cycle and decreases thereafter (60). Eight EPHect centers contributed their SOPs for peritoneal fluid collection.
Sample collection
During laparoscopy, after entry into the pelvic cavity, the peritoneal fluid is aspirated using a syringe or suction device (20). If no or very limited peritoneal fluid is found, a lavage method can be used to wash the peritoneal surfaces with 10 ml of sterile, normal saline solution using a laparoscopic needle, and manual aspiration can be performed using a syringe. This peritoneal lavage fluid (PLF) can be processed as peritoneal fluid, but the supernatant from PLF should be regarded with caution, as molecular profiles may vary depending on the collection method used. This method should be recorded (EPHect Biospecimen Form, Supplemental Appendix 7), along with menstrual data, as cycle phase may affect the concentration of molecules measured (61). Pilot studies are needed that compare the peritoneal microenvironments when sampling is performed using these different aspiration and lavage methods.
Sample stability, processing, and storage
The sample should be kept cool (on wet ice/at 4°C), and the processing time should be kept to a minimum to minimize degradation of molecules. The collected peritoneal fluid should be centrifuged in the laboratory, and the supernatant and the pellet (the cell fraction) should be stored separately, per standard, in LN2 freezers set at −80°C or lower (see blood storage section).
Endometrial Fluid and Menstrual Effluent
Endometrial fluid is found in the endometrial cavity in the uterus 62, 63 and reflects its specific microenvironment. Menstrual effluent has been used for investigating molecules in menstruation/endometrium-related processes, such as angiogenesis and endometrial repair (64). Six EPHect centers provided endometrial fluid SOPs; 3 provided menstrual effluent SOPs.
Sample collection
Collection of an endometrial fluid sample is possible and advisable without administration of any pre-medication or anesthetics, since it is unknown if, and how quickly, medications can alter the expression of molecules in this microenvironment. If pre-medication or anesthetics are used, a record should be made of time of sample collection relative to administration. Endometrial fluid should not be collected during the menstrual cycle phase. Endometrial fluid is typically collected through an embryo-transfer catheter connected to a syringe 20, 63. If fluid volume is insufficient for the research purpose, a uterine lavage can be performed through slow infusion and withdrawal of 4 ml of normal, sterile saline solution into the uterine cavity (65). This uterine lavage fluid (ULF) can be processed as endometrial fluid, but the supernatant from ULF should be regarded with caution.
When comparing protein profiles of endometrial fluid collected using these two sampling techniques (66), both proved to be satisfactory sampling methods that enabled subsequent analysis of uterine fluid components. However, they provided substantially different protein profiles. The method of collection therefore needs to be recorded (EPHect Biospecimen Form, Supplemental Appendix 7).
Menstrual effluent is collected during the menstrual phase with a diaphragm or mixing cannula (64). For informative analysis of both endometrial fluid and menstrual effluent, menstrual cycle data should be recorded using the EPHect Biospecimen Form (Supplemental Appendix 7).
Sample stability, processing, and storage
The recommendation from EPHect is that endometrial fluid samples be kept cool (on wet ice/at 4°C) during processing and transferred to a screw top vial before centrifugation, with the supernatant and pellet stored separately. If the volume of the sample is not large enough for centrifugation, i.e., was collected with an embryo-transfer cannula, the cannula can be snap-frozen immediately in LN2/dry ice. For long-term storage, samples should, per standard, be stored in LN2 freezers set at −80°C or lower (see blood storage section).
Biospecimen Form
The EPHect Biospecimen Form includes data items that the WERF EPHect Working Group agreed were essential to record from the participant when collecting biological samples. As mentioned above, data relevant to fluid biospecimen collections included an assessment of menstrual phase on the day of sample collection because various molecules are likely to be expressed at different levels in different phases of the menstrual cycle 67, 68, 69, 70, 71. Regularity of a participant's typical menstrual cycle should be recorded, along with LMP and ideally—through follow-up—the first day of the next menstrual cycle 72, 73, to allow accurate calculation of the cycle day on the day of sample collection. The EPHect Biospecimen Form also includes questions concerning parameters surrounding urine collection. EPHect recommends as standard the universal collection of samples before administration of any pre-medication or anesthetics where possible, as these could interfere with downstream molecular analyses, and any medication a participant has taken recently should be recorded.
The form also includes places to record weight, height, and waist and hip circumference, as measured by a research nurse. The EPHect Working Group agreed that these data are crucial to record because of the consistent phenotypic and genetic associations of obesity-related traits with endometriosis (74). It is critical that the anthropometric measurements are made using a method standardized both within and between studies, particularly for traits prone to measurement variability such as waist and hip circumference. We recommend the use of the National Health and Nutrition Examination Survey (NHANES) III guidelines (adapted from World Health Organization guidelines) for measuring waist and hip circumference 75, 76, described in Supplemental Appendix 8, available online.
Discussion
We have provided WERF EPHect consensus SOPs for the collection of blood, urine, saliva, endometrial fluid, peritoneal fluid, and menstrual effluent in endometriosis research, together with a Biospecimen Form to collect additional data required for informative analysis of the samples. This consensus was developed and agreed on by 34 clinical/academic institutions and 3 industry collaborators from 16 countries across 5 continents. Adoption of the SOPs, and of the surgical and clinical data collection instruments described in our previous articles 20, 21, represents a ground-breaking opportunity for endometriosis research centers to decrease variability in—and increase validity of—their results, and to allow new comparisons and collaborations among centers 1, 19.
The SOPs presented focus on downstream analysis of biomolecules such as DNA, RNA, proteins, and metabolites, with specific relevance to endometriosis research. They may not be suited to the quantification of environmental chemicals in the sample, which may require different collection equipment as well as different SOPs. Although we focus on relevance to endometriosis research, these SOPs are clearly also relevant to research into other female conditions likely to use fluid samples that are subject to cyclical reproductive influences.
Although the consensus SOPs were based on the best evidence available, there were steps for which this evidence was limited. Specific evidence is lacking on the most effective duration, speed, and temperature conditions for centrifugation of blood samples. More pilot studies are needed on how the lavage methods used in both endometrial and peritoneal fluid collection affect downstream results for specific molecules.
All questionnaires and SOPs produced by the WERF EPHect Working Group are freely available for use by investigators, subject to signed, written, informed consent obtained from each patient, and local ethical approval for the study according to ethical principles for clinical research summarized in the Declaration of Helsinki. To enable the multi-center collaborations, envisaged by the WERF EPHect initiative, it is essential that centers adopting the WERF EPHect instruments and SOPs ensure that patients provide informed consent that allows their data and biological samples to be used in future multi-center (inter)national collaborations, and that appropriate ethics committee and institute review board approval is obtained.
The evidence base for all EPHect data collection instruments and SOPs will be reviewed continuously based on feedback provided by investigators, and through systematic surveys and follow-up reviews after 1 year, and every 3 years thereafter. Thus, investigators are strongly encouraged to provide such feedback. Updates of instruments will remain freely accessible to the research community through the WERF EPHect website (endometriosisfoundation.org/ephect). We ask that publication of results that are generated using WERF EPHect data and SOPs appropriately reference the sources, including version numbers, of the instruments used. In the next phase of the EPHect initiative, WERF aims to amalgamate a voluntary registry of centers using EPHect data collection tools and biological sample SOPs that would offer any investigator a transparent platform for establishing new collaborations.
Progress in other disease fields has shown that substantial advances can be made, particularly in terms of disease classification and biomarker identification, if biological sample collection from multiple sites can be combined; to this end, sample size and validity can be maximized through the use of standardized ongoing, long-term participant enrollment, sample collection, and storage. In addition, WERF EPHect envisages that adoption of the recommended standardized procedures will allow such significant advances to be made in the field of endometriosis, opening up new opportunities for international collaborations between academic as well as industry endometriosis research centers, and shedding new light on the etiology and methods for non-invasive diagnosis of this heterogeneous, enigmatic disease.
Acknowledgment
The WERF EPHect Working Group thanks Mohamed Ibrahim for the formatting of the SOP tables.
Footnotes
The complete alphabetical list representing the WERF EPHect Working Group is as follows: G.D. Adamson, C. Allaire, R. Anchan, C.M. Becker, M.A. Bedaiwy, G.M. Buck Louis, C. Calhaz-Jorge, K. Chwalisz, T.M. D'Hooghe, A. Fassbender, T. Faustmann, A.T. Fazleabas, I. Flores, A. Forman, I. Fraser, L.C. Giudice, M. Gotte, P. Gregersen, S.-W. Guo, T. Harada, D. Hartwell, A.W. Horne, M.L. Hull, L. Hummelshoj, M.G. Ibrahim, L. Kiesel, M.R. Laufer, K. Machens, S. Mechsner, S.A. Missmer, G.W. Montgomery, A. Nap, M. Nyegaard, K.G. Osteen, C.A. Petta, N. Rahmioglu, S.P. Renner, J. Riedlinger, S. Roehrich, P.A. Rogers, L. Rombauts, A. Salumets, E. Saridogan, T. Seckin, P. Stratton, K.L. Sharpe-Timms, S. Tworoger, P. Vigano, K. Vincent, A.F. Vitonis, U.-H. Wienhues-Thelen, P.P. Yeung Jr., P. Yong, and K.T. Zondervan.
N.R. has nothing to disclose. A.F. has nothing to disclose. A.F.V. has nothing to disclose. S.S.T. has nothing to disclose. L.H. reports remuneration by WERF for project management. T.M.D. receives research and travel grants from Ferring Pharmaceuticals and Merck Serono, Merck, Besins, and Pharmaplex, and consultancy fees from Astellas, Bayer Pharma AG, Proteomika, Roche Diagnostics International Ltd, and Teva. G.D.A. is Chairman and CEO of Advanced Reproductive Care, Inc.; has received consulting fees from Bayer Pharmaceuticals, Glycotope, and Ziva Medical; and has received research funding from Auxogyn and Labcorp. L.C.G. is an academic associate with Quest Diagnostics. C.M.B. reports grants from Bayer Healthcare and consultant fees from Roche Diagnostics. K.T.Z. reports grants from Wellcome Trust; and consultancies with AbbVie Inc, Bayer HealthCare, and Roche Diagnostics. S.A.M. is a non-remunerated board member of WERF.
The WERF EPHect Working Group (not listed in the author list): C.A. is on the Actavis advisory board, Bayer Pharma AG advisory board, and is a Johnson and Johnson speaker; K. C. is employed by AbbVie and holds stock in this company; T.F. is employed by Bayer Pharma AG; L.K. receives speaker fees from Bayer Pharma AG and consultancy fees from Roche Diagnostics International Ltd; K.M. is employed by Bayer Pharma AG; A.N. receives consulting fees from Merck Serono and MSD; C.A.P. is a consultant for Bayer Pharma AG and is a non-remunerated board member of WERF. S.P.R. receives consultancy fees from Roche Diagnostics International Ltd, Gedeon-Richter, and Ethicon, and honorarium for lectures from Jenapharm; J. R. is employed by Roche Diagnostics International Ltd; S.R. is employed by Bayer Pharma AG; E.S. receives honoraria from Ethicon and Gedeon-Richter for providing training to healthcare professionals; U.-H.W.-T. is employed by Roche Diagnostics International Ltd; P.P.Y. is a consultant for Lumenis; P.V. is a consultant for Roche Diagnostics International Ltd; K.V. receives honoraria and travel expenses for lectures from Bayer Pharma AG. R.A has nothing to disclose. M.A. B.D. has nothing to disclose. G.M. Buck Louis has nothing to disclose. C.C.-J. has nothing to disclose. A.T.F. has nothing to disclose. I.F. has nothing to disclose. A.F. has nothing to disclose. I.F. has nothing to disclose. M.G. has nothing to disclose. P.G. has nothing to disclose. S.-W.G. has nothing to disclose. T.H. has nothing to disclose. D.H. has nothing to disclose. A.W.H. has nothing to disclose. M.L.H. has nothing to disclose. M.G. I. has nothing to disclose. M.R.L. has nothing to disclose. S.M. has nothing to disclose. G.W.M. has nothing to disclose. M.N. has nothing to disclose. K.G.O. has nothing to disclose. P.A.R. has nothing to disclose. L.R. is a non-remunerated board member of WERF. A.S. has nothing to disclose. T. Seckin has nothing to disclose. P. Stratton has nothing to disclose. K.L.S.-T. has nothing to disclose. P.Y. has nothing to disclose.
N.R., A.F, and A.F.V. should be considered similar in author order; C.M.B., K.T.Z., and S.A.M. jointly directed this work.
This work was funded by the WERF through grants from AbbVie Inc, Bayer Pharma AG, and Roche Diagnostics International Ltd. K.T.Z. is supported by a Wellcome Trust Career Development Fellowship (grant no. WT085235/Z/08/Z); S.A.M. and A.F.V. are supported, in part, by the J. Willard and Alice S. Marriott Foundation contribution to the Boston Center for Endometriosis, and S.A.M by a National Institutes of Health (NIH) Eunice Kennedy Shriver National Institute of Child Health and Human Development grant (grant no. HD57210); P.S. is supported by the Intramural Program of the National Institutes of Health and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant no. HD008769-11); C.M.B. was supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the Department of Health's National Institute for Health Research Biomedical Research Centres Scheme; I.F. is supported by the Puerto Rico Science and Technology Trust (grant no. 2013-000032); N.R. was supported by an MRC grant (grant no. MR/K011480/1); M.G.I. holds a scholarship from the Ernst Schering Foundation and an Elsa Neumann Stipendium des Landes Berlin; K.V. is supported by an National Institute for Health Research Academic Clinical Lecturer Award; A.W.H. is supported by grants from the Chief Scientist Office Scotland, Wellbeing of Women, and Health Technology Assessment; K.G.O. is supported by a grant from the Endometriosis Association; L.C.G. acknowledges funding support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Specialized Cooperative Centers Program in Reproduction and Infertility Research (grant no. U54HD 055764).
Contributor Information
Krina T. Zondervan, Email: krinaz@well.ox.ac.uk.
WERF EPHect Working Group:
G.D. Adamson, C. Allaire, R. Anchan, C.M. Becker, M.A. Bedaiwy, G.M. Buck Louis, C. Calhaz-Jorge, K. Chwalisz, T.M. D'Hooghe, A. Fassbender, T. Faustmann, A.T. Fazleabas, I. Flores, A. Forman, I. Fraser, L.C. Giudice, M. Gotte, P. Gregersen, S.-W. Guo, T. Harada, D. Hartwell, A.W. Horne, M.L. Hull, L. Hummelshoj, M.G. Ibrahim, L. Kiesel, M.R. Laufer, K. Machens, S. Mechsner, S.A. Missmer, G.W. Montgomery, A. Nap, M. Nyegaard, K.G. Osteen, C.A. Petta, N. Rahmioglu, S.P. Renner, J. Riedlinger, S. Roehrich, P.A. Rogers, L. Rombauts, A. Salumets, E. Saridogan, T. Seckin, P. Stratton, K.L. Sharpe-Timms, S. Tworoger, P. Vigano, K. Vincent, A.F. Vitonis, U.-H. Wienhues-Thelen, P.P. Yeung, Jr., P. Yong, and K.T. Zondervan
Supplementary data
References
- 1.Rogers P.A., D'Hooghe T.M., Fazleabas A., Giudice L.C., Montgomery G.W., Petraglia F. Defining future directions for endometriosis research: workshop report from the 2011 World Congress of Endometriosis in Montpellier, France. Reprod Sci. 2013;20:483–499. doi: 10.1177/1933719113477495. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ransohoff D.F., Gourlay M.L. Sources of bias in specimens for research about molecular markers for cancer. J Clin Oncology. 2010;28:698–704. doi: 10.1200/JCO.2009.25.6065. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Tworoger S.S., Hankinson S.E. Use of biomarkers in epidemiologic studies: minimizing the influence of measurement error in the study design and analysis. Cancer Causes Control. 2006;17:889–899. doi: 10.1007/s10552-006-0035-5. [DOI] [PubMed] [Google Scholar]
- 4.Sheldon E., Vo K.C., McIntire R.A., Aghajanova L., Zelenko Z., Irwin J.C. Biobanking human endometrial tissue and blood specimens: standard operating procedure and importance to reproductive biology research and diagnostic development. Fertil Steril. 2011;95:2120–2122.e12. doi: 10.1016/j.fertnstert.2011.01.164. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Fassbender A., Vodolazkaia A., Saunders P., Lebovic D., Waelkens E., De Moor B. Biomarkers of endometriosis. Fertil Steril. 2013;99:1135–1145. doi: 10.1016/j.fertnstert.2013.01.097. [DOI] [PubMed] [Google Scholar]
- 6.Bojesen S.E., Pooley K.A., Johnatty S.E., Beesley J., Michailidou K., Tyrer J.P. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nature Genet. 2013;45:371–384. doi: 10.1038/ng.2566. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Earp M.A., Kelemen L.E., Magliocco A.M., Swenerton K.D., Chenevix-Trench G., Australian Cancer S. Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA. Human Genet. 2014;133:481–497. doi: 10.1007/s00439-013-1383-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Eliassen A.H., Hendrickson S.J., Brinton L.A., Buring J.E., Campos H., Dai Q. Circulating carotenoids and risk of breast cancer: pooled analysis of eight prospective studies. J Natl Cancer Inst. 2012;104:1905–1916. doi: 10.1093/jnci/djs461. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Endogenous Hormones and Breast Cancer Collaborative Group, G. Key T.J., Appleby P.N., Reeves G.K., Travis R.C. Sex hormones and risk of breast cancer in premenopausal women: a collaborative reanalysis of individual participant data from seven prospective studies. Lancet Oncol. 2013;14:1009–1019. doi: 10.1016/S1470-2045(13)70301-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Mitta V.P., Christen W.G., Glynn R.J., Semba R.D., Ridker P.M., Rimm E.B. C-reactive protein and the incidence of macular degeneration: pooled analysis of 5 cohorts. JAMA Ophthal. 2013;131:507–513. doi: 10.1001/jamaophthalmol.2013.2303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Rizzato C., Campa D., Pezzilli R., Soucek P., Greenhalf W., Capurso G. ABO blood groups and pancreatic cancer risk and survival: results from the PANcreatic Disease ReseArch (PANDoRA) consortium. Oncol Rep. 2013;29:1637–1644. doi: 10.3892/or.2013.2285. [DOI] [PubMed] [Google Scholar]
- 12.Rudolph A., Hein R., Lindstrom S., Beckmann L., Behrens S., Liu J. Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome-wide interaction study. Endocrine-related Cancer. 2013;20:875–887. doi: 10.1530/ERC-13-0349. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Moore H.M. The NCI Biospecimen Research Network. Biotechnic Histochem. 2012;87:18–23. doi: 10.3109/10520295.2011.591833. [DOI] [PubMed] [Google Scholar]
- 14.Vaught J., Lockhart N.C. The evolution of biobanking best practices. Clin Chim Acta. 2012;413:1569–1575. doi: 10.1016/j.cca.2012.04.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Yuille M., van Ommen G.J., Brechot C., Cambon-Thomsen A., Dagher G., Landegren U. Biobanking for Europe. Briefings Bioinformatics. 2008;9:14–24. doi: 10.1093/bib/bbm050. [DOI] [PubMed] [Google Scholar]
- 16.Heravi-Moussavi A., Anglesio M.S., Cheng S.W., Senz J., Yang W., Prentice L. Recurrent somatic DICER1 mutations in nonepithelial ovarian cancers. New Engl J Med. 2012;366:234–242. doi: 10.1056/NEJMoa1102903. [DOI] [PubMed] [Google Scholar]
- 17.Shah S.P., Kobel M., Senz J., Morin R.D., Clarke B.A., Wiegand K.C. Mutation of FOXL2 in granulosa-cell tumors of the ovary. New EnglJ Med. 2009;360:2719–2729. doi: 10.1056/NEJMoa0902542. [DOI] [PubMed] [Google Scholar]
- 18.Wiegand K.C., Shah S.P., Al-Agha O.M., Zhao Y., Tse K., Zeng T. ARID1A mutations in endometriosis-associated ovarian carcinomas. New Engl J Med. 2010;363:1532–1543. doi: 10.1056/NEJMoa1008433. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Rogers P.A., D'Hooghe T.M., Fazleabas A., Gargett C.E., Giudice L.C., Montgomery G.W. Priorities for endometriosis research: recommendations from an international consensus workshop. Reprod Sci. 2009;16:335–346. doi: 10.1177/1933719108330568. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Becker C.M., Stratton P., Hummelshoj L., Missmer S.M., Zondervan K.T., Missmer S.A. World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project: I. Surgical phenotype data collection in endometriosis research. Fertil Steril. 2014;102:1213–1222. doi: 10.1016/j.fertnstert.2014.07.709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Vitonis A.F., Rahmioglu N., Fassbender A., Buck Louis G.M., Hummelshoj L., Giudice L.C. World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project: II. Clinical and covariate phenotype data collection in endometriosis research. Fertil Steril. 2014;102:1223–1232. doi: 10.1016/j.fertnstert.2014.07.1244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Fassbender A., Rahmioglu N., Vitonis A.F., Vigano P., Giudice L.C., D'Hooghe T.M., Hummelshoj L. WERF Endometriosis Phenome and Biobanking Harmonisation Project: IV. Tissue collection, processing, and storage in endometriosis research. Fertil Steril. 2014;102:1244–1253. doi: 10.1016/j.fertnstert.2014.07.1209. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Peplies J., Gunther K., Bammann K., Fraterman A., Russo P., Veidebaum T. Influence of sample collection and preanalytical sample processing on the analyses of biological markers in the European multicentre study IDEFICS. Int J Obesity. 2011;35(Suppl 1):104–112. doi: 10.1038/ijo.2011.41. [DOI] [PubMed] [Google Scholar]
- 24.Thorpe J.D., Duan X., Forrest R., Lowe K., Brown L., Segal E. Effects of blood collection conditions on ovarian cancer serum markers. PloS One. 2007;2:e1281. doi: 10.1371/journal.pone.0001281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Gatti R., Antonelli G., Prearo M., Spinella P., Cappellin E., De Palo E.F. Cortisol assays and diagnostic laboratory procedures in human biological fluids. Clin Biochem. 2009;42:1205–1217. doi: 10.1016/j.clinbiochem.2009.04.011. [DOI] [PubMed] [Google Scholar]
- 26.Elliott P., Peakman T.C., Biobank U.K. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol. 2008;37:234–244. doi: 10.1093/ije/dym276. [DOI] [PubMed] [Google Scholar]
- 27.Flower L., Ahuja R.H., Humphries S.E., Mohamed-Ali V. Effects of sample handling on the stability of interleukin 6, tumour necrosis factor-alpha and leptin. Cytokine. 2000;12:1712–1716. doi: 10.1006/cyto.2000.0764. [DOI] [PubMed] [Google Scholar]
- 28.Holland N.T., Smith M.T., Eskenazi B., Bastaki M. Biological sample collection and processing for molecular epidemiological studies. Mutation Res. 2003;543:217–234. doi: 10.1016/s1383-5742(02)00090-x. [DOI] [PubMed] [Google Scholar]
- 29.Palmer-Toy D.E., Szczepiorkowski Z.M., Shih V., Van Cott E.M. Compatibility of the Abbott IMx homocysteine assay with citrate-anticoagulated plasma and stability of homocysteine in citrated whole blood. Clin Chem. 2001;47:1704–1707. [PubMed] [Google Scholar]
- 30.Kyama C.M., Overbergh L., Debrock S., Valckx D., Vander Perre S., Meuleman C. Increased peritoneal and endometrial gene expression of biologically relevant cytokines and growth factors during the menstrual phase in women with endometriosis. Fertil Steril. 2006;85:1667–1675. doi: 10.1016/j.fertnstert.2005.11.060. [DOI] [PubMed] [Google Scholar]
- 31.Kyama C.M., Overbergh L., Mihalyi A., Meuleman C., Mwenda J.M., Mathieu C. Endometrial and peritoneal expression of aromatase, cytokines, and adhesion factors in women with endometriosis. Fertil Steril. 2008;89:301–310. doi: 10.1016/j.fertnstert.2007.02.057. [DOI] [PubMed] [Google Scholar]
- 32.Kyama C.M., T'Jampens D., Mihalyi A., Simsa P., Debrock S., Waelkens E. ProteinChip technology is a useful method in the pathogenesis and diagnosis of endometriosis: a preliminary study. Fertil Steril. 2006;86:203–209. doi: 10.1016/j.fertnstert.2005.12.024. [DOI] [PubMed] [Google Scholar]
- 33.Tomassetti C., Meuleman C., Pexsters A., Mihalyi A., Kyama C., Simsa P. Endometriosis, recurrent miscarriage and implantation failure: is there an immunological link? Reprod Biomed Online. 2006;13:58–64. doi: 10.1016/s1472-6483(10)62016-0. [DOI] [PubMed] [Google Scholar]
- 34.Rai A.J., Gelfand C.A., Haywood B.C., Warunek D.J., Yi J., Schuchard M.D. HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples. Proteomics. 2005;5:3262–3277. doi: 10.1002/pmic.200401245. [DOI] [PubMed] [Google Scholar]
- 35.Tammen H., Schulte I., Hess R., Menzel C., Kellmann M., Mohring T. Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display. Proteomics. 2005;5:3414–3422. doi: 10.1002/pmic.200401219. [DOI] [PubMed] [Google Scholar]
- 36.Peakman T.C., Elliott P. The UK Biobank sample handling and storage validation studies. Int J Epidemiol. 2008;37(Suppl 1):i2–6. doi: 10.1093/ije/dyn019. [DOI] [PubMed] [Google Scholar]
- 37.Bernini P., Bertini I., Luchinat C., Nincheri P., Staderini S., Turano P. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR. 2011;49:231–243. doi: 10.1007/s10858-011-9489-1. [DOI] [PubMed] [Google Scholar]
- 38.Tuck M.K., Chan D.W., Chia D., Godwin A.K., Grizzle W.E., Krueger K.E. Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group. J Proteome Res. 2009;8:113–117. doi: 10.1021/pr800545q. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Hankinson S.E., London S.J., Chute C.G., Barbieri R.L., Jones L., Kaplan L.A. Effect of transport conditions on the stability of biochemical markers in blood. Clin Chem. 1989;35:2313–2316. [PubMed] [Google Scholar]
- 40.Townsend M.K., Clish C.B., Kraft P., Wu C., Souza A.L., Deik A.A. Reproducibility of metabolomic profiles among men and women in 2 large cohort studies. Clin Chem. 2013;59:1657–1667. doi: 10.1373/clinchem.2012.199133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Holland N.T., Pfleger L., Berger E., Ho A., Bastaki M. Molecular epidemiology biomarkers—sample collection and processing considerations. Toxicol Appl Pharmacol. 2005;206:261–268. doi: 10.1016/j.taap.2004.10.024. [DOI] [PubMed] [Google Scholar]
- 42.Grizzle W.E., Semmes O.J., Bigbee W., Zhu L., Malik G., Oelschlager D.K. The need for review and understanding of SELDI/MALDI mass spectroscopy data prior to analysis. Cancer Informatics. 2005;1:86–97. [PMC free article] [PubMed] [Google Scholar]
- 43.Su S.C., Garbers S., Rieper T.D., Toniolo P. Temperature variations in upright mechanical freezers. Cancer Epidemiol Biomarkers Prevention. 1996;5:139–140. [PubMed] [Google Scholar]
- 44.Mallick P., Kuster B. Proteomics: a pragmatic perspective. Nature Biotechnol. 2010;28:695–709. doi: 10.1038/nbt.1658. [DOI] [PubMed] [Google Scholar]
- 45.Silberring J., Ciborowski P. Biomarker discovery and clinical proteomics. Trends Analytic Chem. 2010;29:128. doi: 10.1016/j.trac.2009.11.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Hankinson S.E., Tworoger S.S. In: Rothman N., Hainaut P., Schulte P., Smith M., Boffetta P., Perera F., editors. Vol. 163. IARC Scientific Publication, Lyon, France; 2012. Assessment of the Hormonal Milieu. (Molecular epidemiology: principles and practices). [Google Scholar]
- 47.Saude E.J., Adamko D., Rowe B.H., Marrie T., Sykes B.D. Variation of metabolites in normal human urine. Metabolomics. 2007;3:439–451. [Google Scholar]
- 48.Koni A.C., Scott R.A., Wang G., Bailey M.E., Peplies J., Bammann K. DNA yield and quality of saliva samples and suitability for large-scale epidemiological studies in children. Int J Obesity. 2011;35(Suppl 1):113–118. doi: 10.1038/ijo.2011.43. [DOI] [PubMed] [Google Scholar]
- 49.Abraham J.E., Maranian M.J., Spiteri I., Russell R., Ingle S., Luccarini C. Saliva samples are a viable alternative to blood samples as a source of DNA for high throughput genotyping. BMC Med Genomics. 2012;5:19. doi: 10.1186/1755-8794-5-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Shirtcliff E.A., Granger D.A., Schwartz E., Curran M.J. Use of salivary biomarkers in biobehavioral research: cotton-based sample collection methods can interfere with salivary immunoassay results. Psychoneuroendocrinology. 2001;26:165–173. doi: 10.1016/s0306-4530(00)00042-1. [DOI] [PubMed] [Google Scholar]
- 51.Hansen T.V., Simonsen M.K., Nielsen F.C., Hundrup Y.A. Collection of blood, saliva, and buccal cell samples in a pilot study on the Danish nurse cohort: comparison of the response rate and quality of genomic DNA. Cancer Epidemiol Biomarkers Prev. 2007;16:2072–2076. doi: 10.1158/1055-9965.EPI-07-0611. [DOI] [PubMed] [Google Scholar]
- 52.Livy A., Lye S., Jagdish C.K., Hanis N., Sharmila V., Ler L.W. Evaluation of quality of DNA extracted from buccal swabs for microarray based genotyping. Indian J Clin Biochem. 2012;27:28–33. doi: 10.1007/s12291-011-0154-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Walker A.H., Najarian D., White D.L., Jaffe J.F., Kanetsky P.A., Rebbeck T.R. Collection of genomic DNA by buccal swabs for polymerase chain reaction-based biomarker assays. Environ Health Perspect. 1999;107:517–520. doi: 10.1289/ehp.99107517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Mohamed R., Campbell J.L., Cooper-White J., Dimeski G., Punyadeera C. The impact of saliva collection and processing methods on CRP, IgE, and Myoglobin immunoassays. Clin Trans Med. 2012;1:19. doi: 10.1186/2001-1326-1-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Navazesh M., Kumar S.K. University of Southern California School of Dentistry. Measuring salivary flow: challenges and opportunities. J Am Dental Assoc. 2008;139(Suppl):35S–40S. doi: 10.14219/jada.archive.2008.0353. [DOI] [PubMed] [Google Scholar]
- 56.Pulford D.J., Mosteller M., Briley J.D., Johansson K.W., Nelsen A.J. Saliva sampling in global clinical studies: the impact of low sampling volume on performance of DNA in downstream genotyping experiments. BMC Med Genomics. 2013;6:20. doi: 10.1186/1755-8794-6-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Chiappin S., Antonelli G., Gatti R., De Palo E.F. Saliva specimen: a new laboratory tool for diagnostic and basic investigation. Clin Chim Acta. 2007;383:30–40. doi: 10.1016/j.cca.2007.04.011. [DOI] [PubMed] [Google Scholar]
- 58.Rockett J.C., Buck G.M., Lynch C.D., Perreault S.D. The value of home-based collection of biospecimens in reproductive epidemiology. Environ Health Perspect. 2004;112:94–104. doi: 10.1289/ehp.6264. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Kalu E., Sumar N., Giannopoulos T., Patel P., Croucher C., Sherriff E. Cytokine profiles in serum and peritoneal fluid from infertile women with and without endometriosis. J Obstet Gyn Res. 2007;33:490–495. doi: 10.1111/j.1447-0756.2007.00569.x. [DOI] [PubMed] [Google Scholar]
- 60.Koninckx P.R., Kennedy S.H., Barlow D.H. Pathogenesis of endometriosis: the role of peritoneal fluid. Gynecol Obstet Investigation. 1999;47(Suppl 1):23–33. doi: 10.1159/000052856. [DOI] [PubMed] [Google Scholar]
- 61.Pupo-Nogueira A., de Oliveira R.M., Petta C.A., Podgaec S., Dias J.A., Jr., Abrao M.S. Vascular endothelial growth factor concentrations in the serum and peritoneal fluid of women with endometriosis. Int J Gyn Obstet. 2007;99:33–37. doi: 10.1016/j.ijgo.2007.04.033. [DOI] [PubMed] [Google Scholar]
- 62.Ametzazurra A., Matorras R., Garcia-Velasco J.A., Prieto B., Simon L., Martinez A. Endometrial fluid is a specific and non-invasive biological sample for protein biomarker identification in endometriosis. Human Reprod. 2009;24:954–965. doi: 10.1093/humrep/den450. [DOI] [PubMed] [Google Scholar]
- 63.Casado-Vela J., Rodriguez-Suarez E., Iloro I., Ametzazurra A., Alkorta N., Garcia-Velasco J.A. Comprehensive proteomic analysis of human endometrial fluid aspirate. J Proteome Res. 2009;8:4622–4632. doi: 10.1021/pr9004426. [DOI] [PubMed] [Google Scholar]
- 64.Malik S., Day K., Perrault I., Charnock-Jones D.S., Smith S.K. Reduced levels of VEGF-A and MMP-2 and MMP-9 activity and increased TNF-alpha in menstrual endometrium and effluent in women with menorrhagia. Human Reprod. 2006;21:2158–2166. doi: 10.1093/humrep/del089. [DOI] [PubMed] [Google Scholar]
- 65.Scotchie J.G., Fritz M.A., Mocanu M., Lessey B.A., Young S.L. Proteomic analysis of the luteal endometrial secretome. Reprod Sci. 2009;16:883–893. doi: 10.1177/1933719109337165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Hannan N.J., Nie G., Rainzcuk A., Rombauts L.J., Salamonsen L.A. Uterine lavage or aspirate: which view of the intrauterine environment? Reprod Sci. 2012;19:1125–1132. doi: 10.1177/1933719112443879. [DOI] [PubMed] [Google Scholar]
- 67.Aghajanova L., Giudice L.C. Molecular evidence for differences in endometrium in severe versus mild endometriosis. Reprod Sci. 2011;18:229–251. doi: 10.1177/1933719110386241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Burney R.O., Talbi S., Hamilton A.E., Vo K.C., Nyegaard M., Nezhat C.R. Gene expression analysis of endometrium reveals progesterone resistance and candidate susceptibility genes in women with endometriosis. Endocrinology. 2007;148:3814–3826. doi: 10.1210/en.2006-1692. [DOI] [PubMed] [Google Scholar]
- 69.Kao L.C., Germeyer A., Tulac S., Lobo S., Yang J.P., Taylor R.N. Expression profiling of endometrium from women with endometriosis reveals candidate genes for disease-based implantation failure and infertility. Endocrinology. 2003;144:2870–2881. doi: 10.1210/en.2003-0043. [DOI] [PubMed] [Google Scholar]
- 70.Talbi S., Hamilton A.E., Vo K.C., Tulac S., Overgaard M.T., Dosiou C. Molecular phenotyping of human endometrium distinguishes menstrual cycle phases and underlying biological processes in normo-ovulatory women. Endocrinology. 2006;147:1097–1121. doi: 10.1210/en.2005-1076. [DOI] [PubMed] [Google Scholar]
- 71.Fassbender A., Verbeeck N., Bornigen D., Kyama C.M., Bokor A., Vodolazkaia A. Combined mRNA microarray and proteomic analysis of eutopic endometrium of women with and without endometriosis. Human Reprod. 2012;27:2020–2029. doi: 10.1093/humrep/des127. [DOI] [PubMed] [Google Scholar]
- 72.Baird D.D., McConnaughey D.R., Weinberg C.R., Musey P.I., Collins D.C., Kesner J.S. Application of a method for estimating day of ovulation using urinary estrogen and progesterone metabolites. Epidemiology. 1995;6:547–550. doi: 10.1097/00001648-199509000-00015. [DOI] [PubMed] [Google Scholar]
- 73.Waller K., Swan S.H., Windham G.C., Fenster L., Elkin E.P., Lasley B.L. Use of urine biomarkers to evaluate menstrual function in healthy premenopausal women. Am J Epidemiology. 1998;147:1071–1080. doi: 10.1093/oxfordjournals.aje.a009401. [DOI] [PubMed] [Google Scholar]
- 74.Shah D.K., Correia K.F., Vitonis A.F., Missmer S.A. Body size and endometriosis: results from 20 years of follow-up within the Nurses' Health Study II prospective cohort. Human Reprod. 2013;28:1783–1792. doi: 10.1093/humrep/det120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.CDC. National Health and Nutrition Examination Survey III: Body Measurements (Anthropometry). Centers for Disease Control, Rockville, Maryland, USA; 1988.
- 76.McDowell MA, Fryar CD, Ogden CL. Anthropometric reference data for children and adults: United States, 1988-1994. Vital and health statistics Series 11, Data from the national health survey, Hyattsville, Maryland; 2009:1–68. [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.


