LUPUS NEXUS: DEVELOPING A LUPUS REGISTRY, BIOREPOSITORY AND DATA EXCHANGE PLATFORM TO ACCELERATE PRECISION MEDICINE IN LUPUS
Notice bibliographique
Résumé
PV153 / #118 Poster Topic: AS17 - Miscellaneous Background/Purpose Systemic lupus erythematosus remains a disease of high unmet medical need. Protean manifestations and the lack of clear understanding of etiology, pathogenesis, and disease subgroups hinder the development and application of targeted therapeutic approaches. Community-wide access to a longitudinal, highly curated, centralized patient dataset with linked biospecimens and molecular data is critical to enable advances in this area. To address this unmet need, the Lupus Research Alliance created the Lupus Nexus (LNx), a lupus registry, biorepository and data exchange platform. Methods To ensure that the design of LNx reflected the needs of the research and patient communities, LNx was developed with guidance from over 100 individuals representing clinicians and scientists from academia and industry, governmental and nonprofit groups, and patients with lupus. A Steering Committee was formed to provide leadership, oversight and direction to the design, implementation and governance of LNx including the oversight of 8 Working Groups (WGs) (Table 1) charged with developing individual components of the program. Members of the WG included experts in clinician- and patient-reported outcomes, registries, biorepositories, bioinformatics, biospecimen analyses, and lived lupus experience. Many of these individuals have transitioned to roles on active Advisory Boards to continue to provide guidance on LNx operations. The LNx has 3 main components: a registry, a biorepository, and a data exchange platform. The registry and biorepository are first being established through the Lupus Landmark Study (LLS), a prospective, longitudinal observational study that began in 2023. The LLS will enroll up to 3,500 people living with lupus into 4 cohorts-new onset, extra-renal flare, active lupus nephritis, prevalent- and will follow them over 5 years. Participants are recruited from 24 sites across the LRA Lupus Clinical Investigators Network. The registry includes medical information (full medical, familial autoimmune, serological, medications, vaccination history), clinician-reported outcomes (SLEDAI Flare Index, SLICC/ACR Damage Index, neuropsychiatric SLE, SLEDAI-2K, PGA-VAS), and patient-reported outcomes (sociodemographic, health habits, SLAQ, PROMIS, Lupus Erythematosus Quality of Life). The biorepository includes genomic DNA, RNA, plasma, serum, PBMC[AK1], urine, saliva, stool and tissue. The data exchange platform is a federated Trusted Research Environment (TRE) that aggregates datasets and provides a high-performance infrastructure with portals for researcher and patient communities. The researcher portal allows for biospecimen search and data mining using native analytical tools, while the patient community portal allows individuals to view their study data with supportive interpretative services and to connect with other patients. Raw data from biospecimen analyses will be deposited in the TRE, amassing a deep and comprehensive dataset over time. Table 1. Steering Committee and Working Group overview Results As of 11/04/24, there are 174 participants enrolled into the registry (Table 2). Actual enrollment in the 4 cohorts is 10% new onset, 18% active lupus nephritis, 25% extra-renal flare, and 46% prevalent cases, with 35% Black patients, 20% Hispanic/Latino patients, and 12% Asian/Pacific Islander patients. Over 2200 unique samples (subject x timepoint x sample type) have been collected and plans are underway for specific biomarker analyses to stimulate broader community utilization. Table 2. Recruitment demographics Conclusions LNx is a unique resource for researchers and patients that will help accelerate precision medicine for lupus ( www.lupusnexus.org ). The LRA acknowledges the many experts that have contributed to its creation, especially those individuals living with lupus and their care partners.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,128 | 0,108 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,009 | 0,013 |
| Science ouverte | 0,004 | 0,022 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,030 | 0,017 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».