Sustained effects on immune cell subsets and autoreactivity in multiple sclerosis patients treated with oral cladribine

Introduction

Cladribine tablet therapy is an efficacious treatment for multiple sclerosis (MS). Recently, we showed that one year after the initiation of cladribine treatment, T and B cell crosstalk was impaired, reducing potentially pathogenic effector functions along with a specific reduction of autoreactivity to RAS guanyl releasing protein 2 (RASGRP2). In the present study we conducted a longitudinal analysis of the effect of cladribine treatment in patients with RRMS, focusing on the extent to which the effects observed on T and B cell subsets and autoreactivity after one year of treatment are maintained, modulated, or amplified during the second year of treatment.

Methods

In this case-control exploratory study, frequencies and absolute counts of peripheral T and B cell subsets and B cell cytokine production from untreated patients with relapsing-remitting MS (RRMS) and patients treated with cladribine for 52 (W52), 60 (W60), 72 (W72) and 96 (W96) weeks, were measured using flow cytometry. Autoreactivity was assessed using a FluoroSpot assay.

Results

We found a substantial reduction in circulating memory B cells and proinflammatory B cell responses. Furthermore, we observed reduced T cell responses to autoantigens possibly presented by B cells (RASGRP2 and a-B crystallin (CRYAB)) at W52 and W96 and a further reduction in responses to the myelin antigens myelin basic protein (MBP) and myelin oligodendrocyte glycoprotein (MOG) after 96 weeks.

Conclusion

We conclude that the effects of cladribine observed after year one are maintained and, for some effects, even increased two years after the initiation of a full course of treatment with cladribine tablets.

A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non-small cell lung cancer

The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and overall survival (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions and transition times from enrollment to response, progression, and death, and evaluating transition-specific dose effects. This study aims to apply the multistate pharmacometric modeling and simulation framework in a dose optimization setting of bintrafusp alfa, a fusion protein targeting TGF-β and PD-L1. A multistate model with six states (stable disease [SD], response, progression, unknown, dropout, and death) was developed to describe the totality of endpoints data (time to response, PFS, and OS) of 80 patients with non-small cell lung cancer receiving 500 or 1200 mg of bintrafusp alfa. Besides dose, evaluated predictor of transitions include time, demographics, premedication, disease factors, individual clearance derived from a pharmacokinetic model, and tumor dynamic metrics observed or derived from tumor size model. We found that probabilities of progression and death upon progression decreased over time since enrollment. Patients with metastasis at baseline had a higher probability to progress than patients without metastasis had. Despite dose failed to be statistically significant for any individual transition, the combined effect quantified through a model with dose-specific transition estimates was still informative. Simulations predicted a 69.2% probability of at least 1 month longer, and, 55.6% probability of at least 2-months longer median OS from the 1200 mg compared to the 500 mg dose, supporting the selection of 1200 mg for future studies.

Model-based prediction of progression-free survival for combination therapies in oncology

Progression-free survival (PFS) is an important clinical metric for comparing and evaluating similar treatments for the same disease within oncology. After the completion of a clinical trial, a descriptive analysis of the patients' PFS is often performed post hoc using the Kaplan-Meier estimator. However, to perform predictions, more sophisticated quantitative methods are needed. Tumor growth inhibition models are commonly used to describe and predict the dynamics of preclinical and clinical tumor size data. Moreover, frameworks also exist for describing the probability of different types of events, such as tumor metastasis or patient dropout. Combining these two types of models into a so-called joint model enables model-based prediction of PFS. In this paper, we have constructed a joint model from clinical data comparing the efficacy of FOLFOX against FOLFOX + panitumumab in patients with metastatic colorectal cancer. The nonlinear mixed effects framework was used to quantify interindividual variability (IIV). The model describes tumor size and PFS data well, and showed good predictive capabilities using truncated as well as external data. A machine-learning guided analysis was performed to reduce unexplained IIV by incorporating patient covariates. The model-based approach illustrated in this paper could be useful to help design clinical trials or to determine new promising drug candidates for combination therapy trials.

Immune cell type signature discovery and random forest classification for analysis of single cell gene expression datasets

Background

Robust immune cell gene expression signatures are central to the analysis of single cell studies. Nearly all known sets of immune cell signatures have been derived by making use of only single gene expression datasets. Utilizing the power of multiple integrated datasets could lead to high-quality immune cell signatures which could be used as superior inputs to machine learning-based cell type classification approaches.

Results

We established a novel workflow for the discovery of immune cell type signatures based primarily on gene-versus-gene expression similarity. It leverages multiple datasets, here seven single cell expression datasets from six different cancer types and resulted in eleven immune cell type-specific gene expression signatures. We used these to train random forest classifiers for immune cell type assignment for single-cell RNA-seq datasets. We obtained similar or better prediction results compared to commonly used methods for cell type assignment in independent benchmarking datasets. Our gene signature set yields higher prediction scores than other published immune cell type gene sets in random forest-based cell type classification. We further demonstrate how our approach helps to avoid bias in downstream statistical analyses by re-analysis of a published IFN stimulation experiment.

Discussion and conclusion

We demonstrated the quality of our immune cell signatures and their strong performance in a random forest-based cell typing approach. We argue that classifying cells based on our comparably slim sets of genes accompanied by a random forest-based approach not only matches or outperforms widely used published approaches. It also facilitates unbiased downstream statistical analyses of differential gene expression between cell types for significantly more genes compared to previous cell classification algorithms.

Molecular signature associated with cladribine treatment in patients with multiple sclerosis

Introduction

Little is known about the molecular profiling associated with the effect of cladribine in patients with multiple sclerosis (MS). Here, we aimed first to characterize the transcriptomic and proteomic profiles induced by cladribine in blood cells, and second to identify potential treatment response biomarkers to cladribine in patients with MS.

Methods

Gene, protein and microRNA (miRNA) expression profiles were determined by microarrays (genes, miRNAs) and mass spectrometry (proteins) in peripheral blood mononuclear cells (PBMCs) from MS patients after in vitro treatment with cladribine in its active and inactive forms. Two bioinformatics approaches to integrate the three obtained datasets were applied: (i) a multiomics discriminant analysis (DIABLO - Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies); and (ii) a multi-stage integration of features selected in differential expression analysis on each dataset and then merged. Selected molecules from the in vitro study were quantified by qPCR ex vivo in PBMCs from MS patients receiving cladribine.

Results

PBMCs treated in vitro with cladribine were characterized by a major downregulation of gene, protein, and miRNA expression compared with the untreated cells. An intermediate pattern between the cladribine-treated and untreated conditions was observed in PBMCs treated with cladribine in its inactive form. The differential expression analysis of each dataset led to the identification of four genes and their encoded proteins, and twenty-two miRNAs regulating their expression, that were associated with cladribine treatment. Two of these genes (PPIF and NHLRC2), and three miRNAs (miR-21-5p, miR-30b-5p, and miR-30e-5p) were validated ex vivo in MS patients treated with cladribine.

Discussion

By using a combination of omics data and bioinformatics approaches we were able to identify a multiomics molecular profile induced by cladribine in vitro in PBMCs. We also identified a number of biomarkers that were validated ex vivo in PBMCs from patients with MS treated with cladribine that have the potential to become treatment response biomarkers to this drug.

NUAK1 governs centrosome replication in pancreatic cancer via MYPT1/PP1β and GSK3β-dependent regulation of PLK4

The AMP-activated protein kinase (AMPK)-related kinase NUAK1 (NUAK family SNF1-like kinase 1) has emerged as a potential vulnerability in MYC-dependent cancer but the biological roles of NUAK1 in different settings are poorly characterised, and the spectrum of cancer types that exhibit a requirement for NUAK1 is unknown. Unlike canonical oncogenes, NUAK1 is rarely mutated in cancer and appears to function as an obligate facilitator rather than a cancer driver per se. Although numerous groups have developed small-molecule NUAK inhibitors, the circumstances that would trigger their use and the unwanted toxicities that may arise as a consequence of on-target activity are thus undetermined. Reasoning that MYC is a key effector of RAS pathway signalling and the GTPase KRAS is almost uniformly mutated in pancreatic ductal adenocarcinoma (PDAC), we investigated whether this cancer type exhibits a functional requirement for NUAK1. Here, we show that high NUAK1 expression is associated with reduced overall survival in PDAC and that inhibition or depletion of NUAK1 suppresses growth of PDAC cells in culture. We identify a previously unknown role for NUAK1 in regulating accurate centrosome duplication and show that loss of NUAK1 triggers genomic instability. The latter activity is conserved in primary fibroblasts, raising the possibility of undesirable genotoxic effects of NUAK1 inhibition.

Large scale application of the Finnish diabetes risk score in Latin American and Caribbean populations: a descriptive study

Background

The prevalence of type 2 diabetes (T2D) continues to increase in the Americas. Identifying people at risk for T2D is critical to the prevention of T2D complications, especially cardiovascular disease. This study gauges the ability to implement large population-based organized screening campaigns in 19 Latin American and Caribbean countries to detect people at risk for T2D using the Finnish Diabetes Risk Score (FINDRISC).

Methods

This cross-sectional descriptive analysis uses data collected in a sample of men and women 18 years of age or older who completed FINDRISC via eHealth during a Guinness World Record attempt campaign between October 25 and November 1, 2021. FINDRISC is a non-invasive screening tool based on age, body mass index, waist circumference, physical activity, daily intake of fruits and vegetables, history of hyperglycemia, history of antihypertensive drug treatment, and family history of T2D, assigning a score ranging from 0 to 26 points. A cut-off point of ≥ 12 points was considered as high risk for T2D.

Results

The final sample size consisted of 29,662 women (63%) and 17,605 men (27%). In total, 35% of subjects were at risk of T2D. The highest frequency rates (FINDRISC ≥ 12) were observed in Chile (39%), Central America (36.4%), and Peru (36.1%). Chile also had the highest proportion of people having a FINDRISC ≥15 points (25%), whereas the lowest was observed in Colombia (11.3%).

Conclusions

FINDRISC can be easily implemented via eHealth technology over social networks in Latin American and Caribbean populations to detect people with high risk for T2D. Primary healthcare strategies are needed to perform T2D organized screening to deliver early, accessible, culturally sensitive, and sustainable interventions to prevent sequelae of T2D, and reduce the clinical and economic burden of cardiometabolic-based chronic disease.

Evaluating the TUITEK® patient support program in supporting caregivers of children diagnosed with growth hormone deficiency in Argentina

Introduction

The appropriate use of recombinant human growth hormone (r-hGH) treatment provides an opportunity to improve growth outcomes among pediatric patients with growth hormone deficiency (GHD). However, a major challenge in clinical practice is to adequately recognize and address factors that negatively affect treatment adherence. TUITEK® patient support program (PSP) was designed to help caregivers of children diagnosed with GHD to personalize the care pathway, improve adherence, and achieve better outcomes. Effectiveness of TUITEK® PSP has been demonstrated previously in a smaller sample (n = 31) in Taiwanese population. Here, we present the results from Argentina.

Methods

TUITEK® PSP was piloted among 76 caregivers of children with GHD administering r-hGH using easypod™ (Merck KGaA, Darmstadt, Germany) auto-injector device in Argentina. Based on TUITEK® personalization questionnaire, caregivers were assigned to high- and low-risk groups across four categories that may influence adherence, including disease and treatment coherence (DTC), self-administration (SA), treatment-related anxiety (TRA), and emotional burden (EB). The caregivers who were included in atleast one high-risk group had the provision of telephone calls with a nurse practitioner every 2 weeks for 3 months. The Wilcoxon signed-rank test was employed to assess changes in questionnaire-based scoring patterns between baseline and follow-up evaluations.

Results

Statistically significant changes (p < 0.05) in questionnaire scores between baseline and follow-up evaluations were observed across the four categories. The mean/median DTC (n = 11) and SA (n = 23) scores changed from 2.45/3 and 2.17/2, respectively, to 4/4, with all the caregivers moving to low-risk group following program completion (100%) for both categories. The mean/median TRA score (n = 40) changed from 3.58/3 to 2.5/2 and 67.5% of patients (27/40) moved to low-risk group. The mean/median EB score (n = 32) changed from 3.69/3 to 3.13/3 however, none of the caregivers moved to low-risk group (0%).

Conclusion

TUITEK® PSP is a simple, practical, and time-efficient interventional tool that can be used to address key adherence-related issues among caregivers of children with GHD and provide personalized adherence support. Our findings demonstrate that TUITEK® PSP has the potential to improve treatment adherence and self-management, thereby improving growth outcomes in Argentina.

Identification and characterization of a novel SNAT2 (SLC38A2) inhibitor reveals synergy with glucose transport inhibition in cancer cells

SNAT2 (SLC38A2) is a sodium-dependent neutral amino acid transporter, which is important for the accumulation of amino acids as nutrients, the maintenance of cellular osmolarity, and the activation of mTORC1. It also provides net glutamine for glutaminolysis and consequently presents as a potential target to treat cancer. A high-throughput screening assay was developed to identify new inhibitors of SNAT2 making use of the inducible nature of SNAT2 and its electrogenic mechanism. Using an optimized FLIPR membrane potential (FMP) assay, a curated scaffold library of 33934 compounds was screened to identify 3-(N-methyl (4-methylphenyl)sulfonamido)-N-(2-trifluoromethylbenzyl)thiophene-2-carboxamide as a potent inhibitor of SNAT2. In two different assays an IC₅₀ of 0.8–3 µM was determined. The compound discriminated against the close transporter homologue SNAT1. MDA-MB-231 breast cancer and HPAFII pancreatic cancer cell lines tolerated the SNAT2 inhibitor up to a concentration of 100 µM but in combination with tolerable doses of the glucose transport inhibitor Bay-876, proliferative growth of both cell lines was halted. This points to synergy between inhibition of glycolysis and glutaminolysis in cancer cells.

Cladribine Treatment for MS Preserves the Differentiative Capacity of Subsequently Generated Monocytes, Whereas Its Administration In Vitro Acutely Influences Monocyte Differentiation but Not Microglial Activation

Cladribine (2-chlorodeoxyadenosine, 2CdA) is one of the most effective disease-modifying drugs for multiple sclerosis (MS). Cladribine is a synthetic purine nucleoside analog that induces cell death of lymphocytes and oral cladribine treatment leads to a long-lasting disease stabilization, potentially attributable to immune reconstitution. In addition to its effects on lymphocytes, cladribine has been shown to have immunomodulatory effects on innate immune cells, including dendritic cells and monocytes, which could also contribute to its therapeutic efficacy. However, whether cladribine can modulate human macrophage/microglial activation or monocyte differentiation is currently unknown. The aim of this study was to determine the immunomodulatory effects of cladribine upon monocytes, monocyte-derived macrophages (MDMs) and microglia. We analyzed the phenotype and differentiation of monocytes from MS patients receiving their first course of oral cladribine both before and three weeks after the start of treatment. Flow cytometric analysis of monocytes from MS patients undergoing cladribine treatment revealed that the number and composition of CD14/CD16 monocyte subsets remained unchanged after treatment. Furthermore, after differentiation with M-CSF, such MDMs from treated MS patients showed no difference in gene expression of the inflammatory markers compared to baseline. We further investigated the direct effects of cladribine in vitro using human adult primary MDMs and microglia. GM-CSF-derived MDMs were more sensitive to cell death than M-CSF-derived MDMs. In addition, MDMs treated with cladribine showed increased expression of costimulatory molecules CD80 and CD40, as well as expression of anti-inflammatory, pro-trophic genes IL10 and MERTK, depending on the differentiation condition. Cladribine treatment in vitro did not modulate the expression of activation markers in human microglia. Our study shows that cladribine treatment in vitro affects the differentiation of monocytes into macrophages by modulating the expression of activation markers, which might occur similarly in tissue after their infiltration in the CNS during MS.

DJExpress: An Integrated Application for Differential Splicing Analysis and Visualization

RNA-seq analysis of alternative pre-mRNA splicing has facilitated an unprecedented understanding of transcriptome complexity in health and disease. However, despite the availability of countless bioinformatic pipelines for transcriptome-wide splicing analysis, the use of these tools is often limited to expert bioinformaticians. The need for high computational power, combined with computational outputs that are complicated to visualize and interpret present obstacles to the broader research community. Here we introduce DJExpress, an R package for differential expression analysis of transcriptomic features and expression-trait associations. To determine gene-level differential junction usage as well as associations between junction expression and molecular/clinical features, DJExpress uses raw splice junction counts as input data. Importantly, DJExpress runs on an average laptop computer and provides a set of interactive and intuitive visualization formats. In contrast to most existing pipelines, DJExpress can handle both annotated and de novo identified splice junctions, thereby allowing the quantification of novel splice events. Moreover, DJExpress offers a web-compatible graphical interface allowing the analysis of user-provided data as well as the visualization of splice events within our custom database of differential junction expression in cancer (DJEC DB). DJEC DB includes not only healthy and tumor tissue junction expression data from TCGA and GTEx repositories but also cancer cell line data from the DepMap project. The integration of DepMap functional genomics data sets allows association of junction expression with molecular features such as gene dependencies and drug response profiles. This facilitates identification of cancer cell models for specific splicing alterations that can then be used for functional characterization in the lab. Thus, DJExpress represents a powerful and user-friendly tool for exploration of alternative splicing alterations in RNA-seq data, including multi-level data integration of alternative splicing signatures in healthy tissue, tumors and cancer cell lines.

Inhibitors of Human 5-Lipoxygenase Potently Interfere With Prostaglandin Transport

5-Lipoxygenase (5-LO) is the key enzyme in the formation of pro-inflammatory leukotrienes (LT) which play an important role in a number of inflammatory diseases. Accordingly, 5-LO inhibitors are frequently used to study the role of 5-LO and LT in models of inflammation and cancer. Interestingly, the therapeutic efficacy of these inhibitors is highly variable. Here we show that the frequently used 5-LO inhibitors AA-861, BWA4C, C06, CJ-13,610 and the FDA approved compound zileuton as well as the pan-LO inhibitor nordihydroguaiaretic acid interfere with prostaglandin E₂ (PGE₂) release into the supernatants of cytokine-stimulated (TNFα/IL-1β) HeLa cervix carcinoma, A549 lung cancer as well as HCA-7 colon carcinoma cells with similar potencies compared to their LT inhibitory activities (IC₅₀ values ranging from 0.1–9.1 µM). In addition, AA-861, BWA4C, CJ-13,610 and zileuton concentration-dependently inhibited bacterial lipopolysaccharide triggered prostaglandin (PG) release into human whole blood. Western Blot analysis revealed that inhibition of expression of enzymes involved in PG synthesis was not part of the underlying mechanism. Also, liberation of arachidonic acid which is the substrate for PG synthesis as well as PGH₂ and PGE₂ formation were not impaired by the compounds. However, accumulation of intracellular PGE₂ was found in the inhibitor treated HeLa cells suggesting inhibition of PG export as major mechanism. Further, experiments showed that the PG exporter ATP-binding cassette transporter multidrug resistance protein 4 (MRP-4) is targeted by the inhibitors and may be involved in the 5-LO inhibitor-mediated PGE₂ inhibition. In conclusion, the pharmacological effects of a number of 5-LO inhibitors are compound-specific and involve the potent inhibition of PGE₂ export. Results from experimental models on the role of 5-LO in inflammation and pain using 5-LO inhibitors may be misleading and their use as pharmacological tools in experimental models has to be revisited. In addition, 5-LO inhibitors may serve as new scaffolds for the development of potent prostaglandin export inhibitors.

Integrated Digital Health Solutions in the Management of Growth Disorders in Pediatric Patients Receiving Growth Hormone Therapy: A Retrospective Analysis

Digital health has seen rapid advancements over the last few years in helping patients and their healthcare professionals better manage treatment for a variety of illnesses, including growth hormone (GH) therapy for growth disorders in children and adolescents. For children and adolescents requiring such therapy, as well as for their parents, the treatment is longitudinal and often involves daily injections plus close progress monitoring; a sometimes daunting task when young children are involved. Here, we describe our experience in offering devices and digital health tools to support GH therapy across some 40 countries. We also discuss how this ecosystem of care has evolved over the years based on learnings and advances in technology. Finally, we offer a glimpse of future planned enhancements and directions for digital health to play a bigger role in better managing conditions treated with GH therapy, as well as model development for adherence prediction. The continued aim of these technologies is to improve clinical decision making and support for GH-treated patients, leading to better outcomes.

Low Maternal DLK1 Levels at 26 Weeks Is Associated With Small for Gestational Age at Birth

Detecting SGA (small for gestational age) during pregnancy improves the fetal and neonatal prognosis. To date, there is no valid antenatal biomarker of SGA used in clinical practice. Maternal circulating DLK1 (delta-like non-canonical notch ligand 1) levels have been shown to be significantly lower in pregnant women at 36 weeks of gestation (WG) who delivered a SGA newborn than in controls. Data in the literature are contradictory on the association between maternal circulating DLK1 levels and placental vascular dysfunction. The objective was to determine if maternal DLK1 levels in the second trimester of pregnancy are predictive of SGA, and to assess whether the measurement of DLK1 levels in maternal blood could be a means to distinguish SGA with placental vascular dysfunction from that due to other causes. We conducted a nested cased-control study within the EDEN mother-child cohort. 193 SGA (birth weight < 10^th percentile) and 370 mother-child control (birth weight between the 25^th and 75^th percentile) matched pairs were identified in the EDEN cohort. Maternal circulating DLK1 levels at 26 WG were significantly lower for children born SGA than for controls (27.7 ± 8.7 ng/mL vs 30.4 ± 10.6 ng/mL, p = 0.001). Maternal blood DLK1 levels in the first quartile (DLK1 < 22.85 ng/mL) were associated with an odds ratio for SGA of 1.98 [1.15 - 3.37]. DLK1 was less predictive of SGA than ultrasound, with an area under the curve of 0.578. Maternal circulating DLK1 levels were not significantly different in cases of SGA with signs of placental vascular dysfunction (n = 63, 27.1 ± 9.2 ng/mL) than in those without placental dysfunction (n = 129, 28.0 ± 8.5 ng/mL, p = 0.53). The level of circulating DLK1 is reduced in the second trimester of pregnancy in cases of SGA at birth, independently of signs of placental vascular dysfunction. However, DLK1 alone cannot predict the risk of SGA.

Praziquantel Treatment of Schistosoma mansoni Infected Mice Renders Them Less Susceptible to Reinfection

Beyond transient control of the infection, additional benefits of mass drug administration of praziquantel in endemic communities have been suggested in communities but not mechanistically investigated experimentally. The present study sought to evaluate the additional and hitherto unreported benefits of repeated mass drug administration of praziquantel. We used a tractable mouse model of Schistosoma mansoni infection to assess the effects of repeated infection-treatment cycles on the host susceptibility to reinfection. Parasitaemia was assessed by quantification of Schistosoma egg burden in liver tissues and morbidity was followed up by histological observation of liver lesions by microscopy and using biochemical measurement of liver transaminases. Immune responses were further determined by serum probing of schistosoma-specific antibodies, cytokines and quantification of liver cellular and soluble mediator responses by flow cytometry and ELISA, respectively. At similar ages and comparable gender distribution, groups of mice undergoing higher number of infections treatment cycles over a longer period, remained susceptible to reinfection by the parasite, as judged by the presence of eggs and the associated increasing pathology in the liver tissues. However, notably, there was a clear and significantly higher propensity to lower egg burden upon reinfection when compared to counterparts undergoing a lower number of infection-treatment cycles. This relative reduction of susceptibility to infection was paralleled by a more robust humoral response against parasite antigens, elevated serum IL-4 and liver cytokines. Of note, praziquantel treatment of infected mice left them at a higher baseline of serum IL-4, IgE and liver cytokines but lower CD4+ T cell -derived cytokines when compared to infected non-treated mice supporting an immunological treatment-induced advantage of previously infected mice over naïve mice and infected/not treated mice. Notably, repeated infection-treatment cycles did not preclude the infection-driven aggravation of collagen deposition in the livers over time and was corroborated by a more robust local production of inflammatory cytokines in the most exposed livers. Taken together, our data reveal that treatment of S. mansoni-infected hosts with praziquantel rewires the immune system to a conformation less permissive to subsequent reinfection in mice. Provided the data are translatable from mouse to human, our findings may provide mechanistic support to the potential benefits of more frequent MDAs in high transmission areas to allow rapid acquisition of protective immunity against reinfection.

Effect of Genetic Variants of Gonadotropins and Their Receptors on Ovarian Stimulation Outcomes: A Delphi Consensus

BACKGROUND

A Delphi consensus was conducted to evaluate the influence of single nucleotide polymorphisms (SNPs) in genes encoding gonadotropin and gonadotropin receptors on clinical ovarian stimulation outcomes following assisted reproductive technology (ART) treatment.

METHODS

Nine experts plus two Scientific Coordinators discussed and amended statements plus supporting references proposed by the Scientific Coordinators. The statements were distributed via an online survey to 36 experts, who voted on their level of agreement or disagreement with each statement. Consensus was reached if the proportion of participants agreeing or disagreeing with a statement was >66%.

RESULTS

Eleven statements were developed, of which two statements were merged. Overall, eight statements achieved consensus and two statements did not achieve consensus. The statements reaching consensus are summarized here. (1) SNP in the follicle stimulating hormone receptor (FSHR), rs6166 (c.2039A>G, p.Asn680Ser) (N=5 statements): Ser/Ser carriers have higher basal FSH levels than Asn/Asn carriers. Ser/Ser carriers require higher amounts of gonadotropin during ovarian stimulation than Asn/Asn carriers. Ser/Ser carriers produce fewer oocytes during ovarian stimulation than Asn/Asn or Asn/Ser carriers. There is mixed evidence supporting an association between this variant and ovarian hyperstimulation syndrome. (2) SNP of FSHR, rs6165 (c.919G>A, p.Thr307Ala) (N=1 statement): Few studies suggest Thr/Thr carriers require a shorter duration of gonadotropin stimulation than Thr/Ala or Ala/Ala carriers. (3) SNP of FSHR, rs1394205 (-29G>A) (N=1 statement): Limited data in specific ethnic groups suggest that A/A allele carriers may require higher amounts of gonadotropin during ovarian stimulation and produce fewer oocytes than G/G carriers. (4) SNP of FSH β-chain (FSHB), rs10835638 (-211G>T) (N=1 statement): There is contradictory evidence supporting an association between this variant and basal FSH levels or oocyte number. (5) SNPs of luteinizing hormone β-chain (LHB) and LH/choriogonadotropin receptor (LHCGR) genes (N=1 statement): these may influence ovarian stimulation outcomes and could represent potential future targets for pharmacogenomic research in ART, although data are still very limited.

CONCLUSIONS

This Delphi consensus provides clinical perspectives from a diverse international group of experts. The consensus supports a link between some variants in gonadotropin/gonadotropin receptor genes and ovarian stimulation outcomes; however, further research is needed to clarify these findings.