RESUMO
The main limitation to long-term lung transplant (LT) survival is chronic lung allograft dysfunction (CLAD), which leads to irreversible lung damage and significant mortality. Individual factors can impact CLAD, but no large genetic investigation has been conducted to date. We established the multicentric Genetic COhort in Lung Transplantation (GenCOLT) biobank from a rich and homogeneous sub-part of COLT cohort. GenCOLT collected DNA, high-quality GWAS (genome-wide association study) genotyping and robust HLA data for donors and recipients to supplement COLT clinical data. GenCOLT closely mirrors the global COLT cohort without significant variations in variables like demographics, initial disease and survival rates (P > 0.05). The GenCOLT donors were 45 years-old on average, 44% women, and primarily died of stroke (54%). The recipients were 48 years-old at transplantation on average, 45% women, and the main underlying disease was chronic obstructive pulmonary disease (45%). The mean follow-up time was 67 months and survival at 5 years was 57.3% for the CLAD subgroup and 97.4% for the non-CLAD subgroup. After stringent quality controls, GenCOLT gathered more than 7.3 million SNP and HLA genotypes for 387 LT pairs, including 91% pairs composed of donor and recipient of European ancestry. Overall, GenCOLT is an accurate snapshot of LT clinical practice in France and Belgium between 2009 and 2018. It currently represents one of the largest genetic biobanks dedicated to LT with data available simultaneously for donors and recipients. This unique cohort will empower to run comprehensive GWAS investigations of CLAD and other LT outcomes.
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There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.
Assuntos
Biomarcadores , Rejeição de Enxerto , Transplante de Rim , Humanos , Transplante de Rim/efeitos adversos , Biomarcadores/urina , Biomarcadores/sangue , Feminino , Masculino , Estudos Prospectivos , Pessoa de Meia-Idade , Adulto , França/epidemiologia , Estudos de Coortes , Transplantados/estatística & dados numéricosRESUMO
While nearly all computational methods operate on pseudonymized personal data, re-identification remains a risk. With personal health data, this re-identification risk may be considered a double-crossing of patients' trust. Herein, we present a new method to generate synthetic data of individual granularity while holding on to patients' privacy. Developed for sensitive biomedical data, the method is patient-centric as it uses a local model to generate random new synthetic data, called an "avatar data", for each initial sensitive individual. This method, compared with 2 other synthetic data generation techniques (Synthpop, CT-GAN), is applied to real health data with a clinical trial and a cancer observational study to evaluate the protection it provides while retaining the original statistical information. Compared to Synthpop and CT-GAN, the Avatar method shows a similar level of signal maintenance while allowing to compute additional privacy metrics. In the light of distance-based privacy metrics, each individual produces an avatar simulation that is on average indistinguishable from 12 other generated avatar simulations for the clinical trial and 24 for the observational study. Data transformation using the Avatar method both preserves, the evaluation of the treatment's effectiveness with similar hazard ratios for the clinical trial (original HR = 0.49 [95% CI, 0.39-0.63] vs. avatar HR = 0.40 [95% CI, 0.31-0.52]) and the classification properties for the observational study (original AUC = 99.46 (s.e. 0.25) vs. avatar AUC = 99.84 (s.e. 0.12)). Once validated by privacy metrics, anonymous synthetic data enable the creation of value from sensitive pseudonymized data analyses by tackling the risk of a privacy breach.
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KiT-GENIE is a monocentric DNA biobank set up to consolidate the very rich and homogeneous DIVAT French cohort of kidney donors and recipients (D/R) in order to explore the molecular factors involved in kidney transplantation outcomes. We collected DNA samples for kidney transplantations performed in Nantes, and we leveraged GWAS genotyping data for securing high-quality genetic data with deep SNP and HLA annotations through imputations and for inferring D/R genetic ancestry. Overall, the biobank included 4217 individuals (n = 1945 D + 2,272 R, including 1969 D/R pairs), 7.4 M SNPs and over 200 clinical variables. KiT-GENIE represents an accurate snapshot of kidney transplantation clinical practice in Nantes between 2002 and 2018, with an enrichment in living kidney donors (17%) and recipients with focal segmental glomerulosclerosis (4%). Recipients were predominantly male (63%), of European ancestry (93%), with a mean age of 51yo and 86% experienced their first graft over the study period. D/R pairs were 93% from European ancestry, and 95% pairs exhibited at least one HLA allelic mismatch. The mean follow-up time was 6.7 years with a hindsight up to 25 years. Recipients experienced biopsy-proven rejection and graft loss for 16.6% and 21.3%, respectively. KiT-GENIE constitutes one of the largest kidney transplantation genetic cohorts worldwide to date. It includes homogeneous high-quality clinical and genetic data for donors and recipients, hence offering a unique opportunity to investigate immunogenetic and genetic factors, as well as donor-recipient interactions and mismatches involved in rejection, graft survival, primary disease recurrence and other comorbidities.
Assuntos
Transplante de Rim , Humanos , Masculino , Pessoa de Meia-Idade , Feminino , Bancos de Espécimes Biológicos , Doadores Vivos , Sobrevivência de Enxerto/genética , DNARESUMO
OBJECTIVE: Pituitary adenoma (PA) is one of the three major components of multiple endocrine neoplasia type 1 (MEN1). Recent studies have suggested that MEN1-associated PAs are less aggressive than initially estimated. We propose an analysis of the outcome of PAs with a standard of care treatment in a nationwide cohort of MEN1 patients. DESIGN: Retrospective observational nationwide cohort study using the MEN1 patient registry from the French Group of Endocrine Tumours (GTE). METHODS: The GTE database population consists of 1435 patients with MEN1. This analysis focused on 551 patients recruited after 2000 with at least 3 years of follow-up. The study outcome was tumour progression of PA defined by an increase in Hardy classification (HC) during follow-up according to referring physician regular reports. RESULTS: Among 551 MEN1 patients (index and related), 202 (36.7%) had PA, with 114 (56.4%) diagnosed by MEN1-related screening. PAs were defined according to HC as microadenoma (grade I) in 117 cases (57.9%), macroadenoma in 59 (29.2%) with 20 HC grade II and 39 HC grades III-IV and unspecified in 26 (12.8%). They were prolactinomas in 92 cases (45.5%) and non-secreting in 73 (36.1%). After a median follow-up of 3 years among the 137 patients with HC grades I-II, 4 patients (2.9%) presented tumour progression. CONCLUSION: PAs in patients with MEN1 are less aggressive than previously thought. Tumour progression is rare with a standard of care monitoring and treatment, especially in related patients who mostly present non-secreting microadenoma. MRI monitoring for asymptomatic MEN1 patients should be reduced accordingly.
Assuntos
Neoplasia Endócrina Múltipla Tipo 1/patologia , Neoplasias Hipofisárias/patologia , Adulto , Estudos de Coortes , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Estudos RetrospectivosRESUMO
In colorectal cancer (CRC), a high density of T lymphocytes represents a strong prognostic marker in subtypes of CRC. Optimized immunotherapy strategies to boost this T-cell response are still needed. A good candidate is the inflammasome pathway, an emerging player in cancer immunology that bridges innate and adaptive immunity. Its effector protein caspase-1 matures IL-18 that can promote a T-helper/cytotoxic (Th1/Tc1) response. It is still unknown whether tumor cells from CRC possess a functional caspase-1/IL-18 axis that could modulate the Th1/Tc1 response. We used two independent cohorts of CRC patients to assess IL-18 and caspase-1 expression by tumor cells in relation to the density of TILs and the microsatellite status of CRC. Functional and multiparametric approaches at the protein and mRNA levels were performed on an ex vivo CRC explant culture model. We show that, in the majority of CRCs, tumor cells display an activated and functional caspase-1/IL-18 axis that contributes to drive a Th1/Tc1 response elicited by TILs expressing IL-18Rα. Furthermore, unsupervised clustering identified three clusters of CRCs according to the caspase-1/IL-18/TIL density/interferon gamma (IFNγ) axis and microsatellite status. Together, our results strongly suggest that targeting the caspase-1/IL-18 axis can improve the anti-tumor immune response in subgroups of CRC.
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BACKGROUND AND PURPOSE: The ever-growing availability of imaging led to increasing incidentally discovered unruptured intracranial aneurysms (UIAs). We leveraged machine-learning techniques and advanced statistical methods to provide new insights into rupture intracranial aneurysm (RIA) risks. METHODS: We analysed the characteristics of 2505 patients with intracranial aneurysms (IA) discovered between 2016 and 2019. Baseline characteristics, familial history of IA, tobacco and alcohol consumption, pharmacological treatments before the IA diagnosis, cardiovascular risk factors and comorbidities, headaches, allergy and atopy, IA location, absolute IA size and adjusted size ratio (aSR) were analysed with a multivariable logistic regression (MLR) model. A random forest (RF) method globally assessed the risk factors and evaluated the predictive capacity of a multivariate model. RESULTS: Among 994 patients with RIA (39.7%) and 1511 patients with UIA (60.3 %), the MLR showed that IA location appeared to be the most significant factor associated with RIA (OR, 95% CI: internal carotid artery, reference; middle cerebral artery, 2.72, 2.02-3.58; anterior cerebral artery, 4.99, 3.61-6.92; posterior circulation arteries, 6.05, 4.41-8.33). Size and aSR were not significant factors associated with RIA in the MLR model and antiplatelet-treatment intake patients were less likely to have RIA (OR: 0.74; 95% CI: 0.55-0.98). IA location, age, following by aSR were the best predictors of RIA using the RF model. CONCLUSIONS: The location of IA is the most consistent parameter associated with RIA. The use of 'artificial intelligence' RF helps to re-evaluate the contribution and selection of each risk factor in the multivariate model.