Sci Adv. 2025 Jan 17;11(3):eadn5596. doi: 10.1126/sciadv.adn5596. Epub 2025 Jan 17.

ABSTRACT

Cell lines and patient-derived xenografts are essential to cancer research; however, the results derived from such models often lack clinical translatability, as they do not fully recapitulate the complex cancer biology. Identifying preclinical models that sufficiently resemble the biological characteristics of clinical tumors across different cancers is critically important. Here, we developed MOBER, Multi-Origin Batch Effect Remover method, to simultaneously extract biologically meaningful embeddings while removing confounder information. Applying MOBER on 932 cancer cell lines, 434 patient-derived tumor xenografts, and 11,159 clinical tumors, we identified preclinical models with greatest transcriptional fidelity to clinical tumors and models that are transcriptionally unrepresentative of their respective clinical tumors. MOBER allows for transformation of transcriptional profiles of preclinical models to resemble the ones of clinical tumors and, therefore, can be used to improve the clinical translation of insights gained from preclinical models. MOBER is a versatile batch effect removal method applicable to diverse transcriptomic datasets, enabling integration of multiple datasets simultaneously.

PMID:39823329 | DOI:10.1126/sciadv.adn5596

Curr Treatm Opt Rheumatol. 2024 Dec;10(4):43-60. doi: 10.1007/s40674-024-00217-3. Epub 2024 Sep 16.

ABSTRACT

PURPOSE OF REVIEW: To summarize the current treatment landscape of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) in the context of the recent 2023 American College of Rheumatology/American College of Chest Physicians guideline for ILD treatment in systemic autoimmune rheumatic diseases.

RECENT FINDINGS: The guideline conditionally recommends mycophenolate, azathioprine, and rituximab for first-line RA-ILD therapy, with cyclophosphamide and short-term glucocorticoids as additional options. For RA-ILD progression after first line, mycophenolate, rituximab, nintedanib, tocilizumab, cyclophosphamide, and pirfenidone are conditionally recommended, while long-term glucocorticoids are conditionally recommended against. Only three randomized controlled trials (RCTs) enrolled patients with RA-ILD (total n=217). All other recommendations for RA-ILD were based on RCTs for other diseases or observational data. Antifibrotics might be particularly effective for patients with RA-ILD and the usual interstitial pneumonia pattern (RA-UIP). There is uncertainty of the utility of azathioprine and glucocorticoids in RA-UIP since these medications had worse outcomes compared to placebo in an RCT of patients with idiopathic pulmonary fibrosis. RA-ILD treatment decisions should consider articular activity, ILD activity, comorbidities, and potential for infection.

SUMMARY: We summarized the current treatment landscape for RA-ILD. Since only three RCTs included patients with RA-ILD, most guideline recommendations were conditional and based on low-quality evidence. This highlights the urgent need for additional high-quality RCT data for efficacy and safety of anti-inflammatory and antifibrotic medications for RA-ILD.

PMID:39822854 | PMC:PMC11735032 | DOI:10.1007/s40674-024-00217-3

J Gene Med. 2025 Jan;27(1):e70008. doi: 10.1002/jgm.70008.

ABSTRACT

BACKGROUND: The pathogenesis of idiopathic pulmonary fibrosis (IPF) remains unclear; previous studies revealed the underlying connection between IPF and diabetes, but there is no consensual opinion. This study is aimed at examining the association between Type 1 diabetes (T1D) and IPF using Mendelian randomization (MR).

METHOD: In our two-sample MR study, we selected single nucleotide polymorphisms (SNPs) that are strongly associated with T1D in a genome-wide association study (GWAS) from IEU (dataset: ebi-a-GCST005536) and obtained their corresponding effect estimates on T1D risk in an IPF GWAS from IEU (dataset: finn-b-IPF). We conducted a multivariable Mendelian randomization (MVMR) analysis to eliminate the interference of aging.

RESULT: In the outcome of inverse-variance weighted (IVW) method, T1D showed a promoting effect on IPF (odds ratio (OR): 1.132, p = 0.005). The statistics passed the MR-PRESSO test, and no outliers were observed (global test p = 0.238). MVMR study was performed, and the aging-adjusted result remains almost the same (OR = 1.132, OR_95% CI: 1.034-1.239, p = 0.007).

CONCLUSION: Our study shows a causal relation between T1D and IPF; further investigation should be conducted.

PMID:39822044 | DOI:10.1002/jgm.70008

J Hypertens. 2024 Nov 12. doi: 10.1097/HJH.0000000000003924. Online ahead of print.

ABSTRACT

OBJECTIVES: The effects of acute physical exercise in patients with resistant hypertension remain largely unexplored compared with hypertensive patients in general. We assessed the short-term effects of acute moderate-intensity (MICE) and high-intensity interval exercise (HIIE) on the clinic (BP) and 24-h ambulatory blood pressure (ABP) of patients with resistant hypertension.

METHODS: Using a crossover randomized controlled design, 10 participants (56 ± 7 years) with resistant hypertension performed three experimental sessions: MICE, HIIE, and control. MICE consisted of continuous treadmill exercise at an intensity of 3-4 metabolic equivalents of energy (METs) until completing 3 kcal/kg and was energy-matched to HIIE (which included six to eight intervals of 3 min duration at 6-7 METs interspersed with 1.5-min rests at 3 METs). In the control session, participants remained seated for 50 min. Flow-mediated vasodilation, autonomic nervous system balance (heart rate variability), exerkines [interleukin (IL)-6, IL-8, IL-15, vascular endothelial growth factor A, irisin, adiponectin, and angiopoietin] and 71 inflammatory-related proteins were also measured.

RESULTS: Compared with baseline, HIIE and MICE reduced clinic SBP immediately (P < 0.001 for both) and 90 min (P = 0.001 and P = 0.041, respectively) postexercise. HIIE and MICE also reduced clinic DBP immediately postexercise (P = 0.003 and P = 0.025). By contrast, no changes were found in the control session. On the other hand, no significant effects were noted for 24 h ABP measures or for the rest of variables.

CONCLUSION: Although in patients with resistant hypertension, acute aerobic exercise induces short-term reductions in clinic BP, this stimulus does not suffice to reduce 24 h ABP or to impact on potential biological mechanisms.

PMID:39823644 | DOI:10.1097/HJH.0000000000003924

STAR Protoc. 2025 Jan 16;6(1):103573. doi: 10.1016/j.xpro.2024.103573. Online ahead of print.

ABSTRACT

Drugs that target specific proteins often have off-target effects. We present a protocol using artificial neural networks to model cellular transcriptional responses to drugs, aiming to understand their mechanisms of action. We detail steps for predicting transcriptional activities, inferring drug-target interactions, and explaining the off-target mechanism of action. As a case study, we analyze the off-target effects of lestaurtinib on FOXM1 in the A375 cell line. For complete details on the use and execution of this protocol, please refer to Meimetis et al.1.

PMID:39823233 | DOI:10.1016/j.xpro.2024.103573

STAR Protoc. 2025 Jan 16;6(1):103577. doi: 10.1016/j.xpro.2024.103577. Online ahead of print.

ABSTRACT

The eukaryotic cell division cycle is a highly conserved process, featuring fluctuations in protein localization and abundance required for key cell cycle transitions. Here, we present a protocol for the spatiotemporal analysis of the proteome during the budding yeast cell division cycle using live-cell imaging. We describe steps for strain construction, cell cultivation, microscopy, and image analysis. Variations of this protocol can be applied for the spatiotemporal analysis of the proteome in different contexts, such as genetic and environmental perturbations. For complete details on the use and execution of this protocol, please refer to Litsios et al.1.

PMID:39823231 | DOI:10.1016/j.xpro.2024.103577

Nat Biotechnol. 2025 Jan 16. doi: 10.1038/s41587-024-02535-2. Online ahead of print.

ABSTRACT

The complex nature of the immunosuppressive tumor microenvironment (TME) requires multi-agent combinations for optimal immunotherapy. Here we describe multiplex universal combinatorial immunotherapy via gene silencing (MUCIG), which uses CRISPR-Cas13d to silence multiple endogenous immunosuppressive genes in the TME, promoting TME remodeling and enhancing antitumor immunity. MUCIG vectors targeting four genes delivered by adeno-associated virus (AAV) (Cd274/Pdl1, Lgals9/Galectin9, Lgals3/Galectin3 and Cd47; AAV-Cas13d-PGGC) demonstrate significant antitumor efficacy across multiple syngeneic tumor models, remodeling the TME by increasing CD8+ T-cell infiltration while reducing neutrophils. Whole transcriptome profiling validates the on-target knockdown of the four target genes and shows limited potential off-target or downstream gene alterations. AAV-Cas13d-PGGC outperforms corresponding shRNA treatments and individual gene knockdown. We further optimize MUCIG by employing high-fidelity Cas13d (hfCas13d), which similarly showed potent gene silencing and in vivo antitumor efficacy, without weight loss or liver toxicity. MUCIG represents a universal method to silence multiple immune genes in vivo in a programmable manner, offering broad efficacy across multiple tumor types.

PMID:39820813 | DOI:10.1038/s41587-024-02535-2

Brief Bioinform. 2024 Nov 22;26(1):bbaf015. doi: 10.1093/bib/bbaf015.

ABSTRACT

The volume of microbiome data is growing at an exponential rate, and the current methodologies for big data mining are encountering substantial obstacles. Effectively managing and extracting valuable insights from these vast microbiome datasets has emerged as a significant challenge in the field of contemporary microbiome research. This comprehensive review delves into the utilization of foundation models and transfer learning techniques within the context of microbiome-based classification and prediction tasks, advocating for a transition away from traditional task-specific or scenario-specific models towards more adaptable, continuous learning models. The article underscores the practicality and benefits of initially constructing a robust foundation model, which can then be fine-tuned using transfer learning to tackle specific context tasks. In real-world scenarios, the application of transfer learning empowers models to leverage disease-related data from one geographical area and enhance diagnostic precision in different regions. This transition from relying on "good models" to embracing "adaptive models" resonates with the philosophy of "teaching a man to fish" thereby paving the way for advancements in personalized medicine and accurate diagnosis. Empirical research suggests that the integration of foundation models with transfer learning methodologies substantially boosts the performance of models when dealing with large-scale and diverse microbiome datasets, effectively mitigating the challenges posed by data heterogeneity.

PMID:39820436 | DOI:10.1093/bib/bbaf015

Nat Commun. 2025 Jan 16;16(1):715. doi: 10.1038/s41467-025-56042-2.

ABSTRACT

Plants, with intricate molecular networks for environmental adaptation, offer groundbreaking potential for reprogramming with predictive genetic circuits. However, realizing this goal is challenging due to the long cultivation cycle of plants, as well as the lack of reproducible, quantitative methods and well-characterized genetic parts. Here, we establish a rapid (~10 days), quantitative, and predictive framework in plants. A group of orthogonal sensors, modular synthetic promoters, and NOT gates are constructed and quantitatively characterized. A predictive model is developed to predict the designed circuits' behavior accurately. Our versatile and robust framework, validated by constructing 21 two-input circuits with high prediction accuracy (R2 = 0.81), enables multi-state phenotype control in both Arabidopsis thaliana and Nicotiana benthamiana in response to chemical inducers. Our study achieves predictable design and application of synthetic circuits in plants, offering valuable tools for the rapid engineering of plant traits in biotechnology and agriculture.

PMID:39820378 | DOI:10.1038/s41467-025-56042-2

BMC Med Inform Decis Mak. 2025 Jan 16;25(1):29. doi: 10.1186/s12911-024-02821-8.

ABSTRACT

BACKGROUND: Molecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is essential in this rapidly evolving field facing fast-growing data and changing clinical processes. This study addresses the gap in understanding the evolution of software and visualization needs within MTBs and evaluates the current state of digital support. Alignment between user requirements and software development is crucial to avoid waste of resources and maintain trust.

METHODS: In two consecutive nationwide medical informatics projects in Germany, surveys and expert interviews were conducted as stage 1 (n = 14), stage 2 (n = 30), and stage 3 (n = 9). Surveys, via the SoSci Survey tool, covered participants' roles, working methods, and support needs. The second survey additionally addressed requirements for visualization solutions in molecular tumor boards. These aimed to understand diverse requirements for preparation, implementation, and documentation. Nine semi-structured expert interviews complemented quantitative findings through open discussion.

RESULTS: Using quantitative and qualitative analyses, we show that existing digital tools may improve therapy recommendations and streamline MTB case preparation, while continuous training and system improvements are needed.

CONCLUSIONS: Our study contributes to the field by highlighting the importance of developing user-centric, customizable software solutions that can adapt to the fast-paced environment of MTBs to advance personalized oncology. In doing so, it lays the foundation for further advances in personalized medicine in oncology and points to a shift towards more efficient, technology-driven clinical decision-making processes. This research not only enriches our understanding of the integration of digital tools into MTBs, but also signals a broader shift towards technological innovation in healthcare.

PMID:39819625 | DOI:10.1186/s12911-024-02821-8

Annu Rev Plant Biol. 2025 Jan 16. doi: 10.1146/annurev-arplant-083123-060254. Online ahead of print.

ABSTRACT

More than 500 million years ago, a streptophyte algal population established a foothold on land and started terraforming Earth through an unprecedented radiation. This event is called plant terrestrialization and yielded the Embryophyta. Recent advancements in the field of plant evolutionary developmental biology (evo-devo) have propelled our knowledge of the closest algal relatives of land plants, the zygnematophytes, highlighting that several aspects of plant cell biology are shared between embryophytes and their sister lineage. High-throughput exploration determined that routes of signaling cascades, biosynthetic pathways, and molecular physiology predate plant terrestrialization. But how do they assemble into biological programs, and what do these programs tell us about the principal functions of the streptophyte cell? Here, we make the case that streptophyte algae are unique organisms for understanding the systems biology of the streptophyte cell, informing on not only the origin of embryophytes but also their fundamental biology.

PMID:39819561 | DOI:10.1146/annurev-arplant-083123-060254

Elife. 2025 Jan 17;13:RP95273. doi: 10.7554/eLife.95273.

ABSTRACT

Induced pluripotent stem cell (iPSC) technology is revolutionizing cell biology. However, the variability between individual iPSC lines and the lack of efficient technology to comprehensively characterize iPSC-derived cell types hinder its adoption in routine preclinical screening settings. To facilitate the validation of iPSC-derived cell culture composition, we have implemented an imaging assay based on cell painting and convolutional neural networks to recognize cell types in dense and mixed cultures with high fidelity. We have benchmarked our approach using pure and mixed cultures of neuroblastoma and astrocytoma cell lines and attained a classification accuracy above 96%. Through iterative data erosion, we found that inputs containing the nuclear region of interest and its close environment, allow achieving equally high classification accuracy as inputs containing the whole cell for semi-confluent cultures and preserved prediction accuracy even in very dense cultures. We then applied this regionally restricted cell profiling approach to evaluate the differentiation status of iPSC-derived neural cultures, by determining the ratio of postmitotic neurons and neural progenitors. We found that the cell-based prediction significantly outperformed an approach in which the population-level time in culture was used as a classification criterion (96% vs 86%, respectively). In mixed iPSC-derived neuronal cultures, microglia could be unequivocally discriminated from neurons, regardless of their reactivity state, and a tiered strategy allowed for further distinguishing activated from non-activated cell states, albeit with lower accuracy. Thus, morphological single-cell profiling provides a means to quantify cell composition in complex mixed neural cultures and holds promise for use in the quality control of iPSC-derived cell culture models.

PMID:39819559 | DOI:10.7554/eLife.95273

Elife. 2025 Jan 17;13:RP95485. doi: 10.7554/eLife.95485.

ABSTRACT

Live-cell microscopy routinely provides massive amounts of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell-cell interactions in live-cell imaging data. CausalXtract methodology combines network-based and information-based frameworks, which is shown to discover causal effects overlooked by classical Granger and Schreiber causality approaches. We showcase the use of CausalXtract to uncover novel causal effects in a tumor-on-chip cellular ecosystem under therapeutically relevant conditions. In particular, we find that cancer-associated fibroblasts directly inhibit cancer cell apoptosis, independently from anticancer treatment. CausalXtract uncovers also multiple antagonistic effects at different time delays. Hence, CausalXtract provides a unique computational tool to interpret live-cell imaging data for a range of fundamental and translational research applications.

PMID:39819525 | DOI:10.7554/eLife.95485

ACS Chem Biol. 2025 Jan 17. doi: 10.1021/acschembio.4c00553. Online ahead of print.

ABSTRACT

Developing novel nonribosomal peptides (NRPs) requires a comprehensive understanding of the enzymes involved in their biosynthesis, particularly the substrate amino acid recognition mechanisms in the adenylation (A) domain. This study focused on the A domain responsible for adenylating l-2,4-diaminobutyric acid (l-Dab) within the synthetase of polymyxin, an NRP produced by Paenibacillus polymyxa NBRC3020. To date, investigations into recombinant proteins that selectively adenylate l-Dab─exploring substrate specificity and enzymatic activity parameters─have been limited to reports on A domains found in enzymes synthesizing l-Dab homopolymers (pldA from S. celluloflavus USE31 and pddA from S. hindustanus NBRC15115), which remain exceedingly rare. The polymyxin synthetase in NBRC3020 contains five A domains specific to l-Dab, distributed across five distinct modules (modules 1, 3, 4, 5, 8, and 9). In this study, we successfully obtained soluble A domain proteins from modules 1, 5, 8, and 9 by preparing module-specific recombinant proteins. These proteins were expressed in E. coli BAP-1, purified via Ni-affinity chromatography, and demonstrated high specificity for l-Dab. Through sequence homology analysis, three-dimensional structural modeling, docking simulations to estimate substrate-binding sites, and functional validation using alanine mutants, we identified Glu281 and Asp344 as critical residues for recognizing the side chain amino group of l-Dab, and Asp238 as essential for recognizing its main chain amino group in the A domain. Notably, these key residues were conserved not only across the A domains in modules 1, 5, 8, and 9 of P. polymyxa NBRC3020 but also in those of the P. polymyxa PKB1 strain, as confirmed by sequence homology analysis. Interestingly, in pldA and pddA, the key residues involved in recognizing the side-chain amino group of l-Dab, which are conserved among polymyxin synthetases of NBRC3020 and PKB1 strain, were not observed. This suggests a potentially different mechanism for l-Dab recognition.

PMID:39818748 | DOI:10.1021/acschembio.4c00553

Drug Dev Res. 2025 Feb;86(1):e70045. doi: 10.1002/ddr.70045.

ABSTRACT

Famotidine is an H2 receptor antagonist and is currently used on a large scale in gastroenterology. However, Famotidine may also cause severe toxicity to organ systems, including the blood system, digestive system, and urinary system. The objective of this study was to scientifically and systematically investigate the adverse events (AEs) of Famotidine in the real world through the FDA Adverse Event Reporting System (FAERS) database. A disproportionality analysis was used to quantify the signals of AEs associated with Famotidine in FAERS data from the first quarter of 2004 to the first quarter of 2023. The clinical features, onset time, oral and intravenous administration and severe consequences of Famotidine induced AEs were further analyzed. Among the four tests, we found several AEs that were not mentioned in the drug label. For example, abdominal pain upper, abdominal discomfort, dyspepsia, liver disorder, gastrooesophageal reflux disease, and rhabdomyolysis. These AEs are consistent with the drug instructions. Interestingly, we found several unreported AEs, such as: cerebral infarction, hypocalcaemia, hallucination, visual, hypomagnesaemia, hypoparathyroidism, diabetes insipidus, vulvovaginal candidiasis, retro-orbital neoplasm, neuroblastoma recurrent, and malignant cranial nerve neoplasm. Most of our findings are consistent with clinical observations and drug labels, and we also found possible new and unexpected AEs signals, which suggest the need for prospective clinical studies to confirm these results and explain their relationships. Our findings provide valuable evidence for further safety studies.

PMID:39821365 | DOI:10.1002/ddr.70045

Drugs. 2025 Jan 17. doi: 10.1007/s40265-024-02133-1. Online ahead of print.

ABSTRACT

Liposomal irinotecan (Onivyde®), also known as liposomal pegylated irinotecan, has been developed with the intent of maximising anti-tumour efficacy and minimising drug-related toxicities compared with conventional formulations of this topoisomerase 1 inhibitor. In combination with fluorouracil, leucovorin and oxaliplatin (NALIRIFOX), liposomal irinotecan is approved in the USA and the EU for first-line therapy of eligible patients with metastatic pancreatic adenocarcinoma. In a phase III clinical trial, NALIRIFOX significantly improved overall survival (OS) and progression free survival (PFS) compared with gemcitabine plus nanoparticle albumin bound paclitaxel (nab-paclitaxel) as first-line treatment of patients with metastatic pancreatic ductal adenocarcinoma (mPDAC). The safety profile of NALIRIFOX was generally manageable, with diarrhoea, hypokalaemia and neutropenia being the most common grade ≥ 3 treatment-emergent adverse events. Although further analyses will help position the liposomal irinotecan-containing regimen NALIRIFOX in first-line treatment of metastatic pancreatic adenocarcinoma, current evidence indicates that it is a useful addition to treatment options in this patient population.

PMID:39820839 | DOI:10.1007/s40265-024-02133-1

Immunopharmacol Immunotoxicol. 2025 Jan 16:1-13. doi: 10.1080/08923973.2025.2454030. Online ahead of print.

ABSTRACT

BACKGROUND: The incidence of hepatic immune-related adverse events has increased with the wide use of immune checkpoint inhibitors, some immune-mediated hepatotoxicity cases are severe and lack of clinical recommendations.

OBJECTIVE: This study aimed to evaluate the efficacy of artificial liver support systems (ALSS) in the treatment of immune-mediated hepatotoxicity.

METHODS: This retrospective case series included six patients with grade 4 hepatotoxicity with high bilirubin induced by immune checkpoint inhibitors treated between January 1, 2019, to December 31, 2021. All patients received ALSS treatment.

RESULTS: After treatment and recovery, four of the six patients experienced improvement in hepatotoxicity, with total bilirubin levels reduced to ≤ grade 2, and two patients achieved complete recovery (total bilirubin grade = 0).

CONCLUSION: ALSS serve as a therapeutic option for severe immune-mediated hepatotoxicity.

PMID:39819181 | DOI:10.1080/08923973.2025.2454030

Am J Hosp Palliat Care. 2025 Jan 17:10499091251313757. doi: 10.1177/10499091251313757. Online ahead of print.

ABSTRACT

BACKGROUND: Nausea and vomiting significantly impact the quality of life in palliative care. Due to various underlying causes, treatment approaches vary. However, scientific evidence on pharmacotherapeutic management is limited, complicating treatment decisions. Objective is to assess the current antiemetic treatment approach in palliative care in Germany.

METHODS: A retrospective observational study (15 months) was conducted, evaluating clinical records of adult patients admitted to palliative care in a German hospital. Symptom burden (Integrated Palliative care Outcome Scale (IPOS®)), suspected aetiology, antiemetics, treatment quality and drug-related problems (DRPs) were evaluated.

RESULTS: We included 330 patients (median age 71 years, 50.9% female), of which 172 (52%) experienced nausea/vomiting in 230 treatment episodes. Symptoms were more prevalent in cancer-patients (P = 0.002) and women (P = 0.002). Main aetiologies were intestinal obstruction (59/230, 25.7%), hypomotility (31/230, 16.1%), and raised intracranial pressure (23/230, 10.0%). Nearly 70% experienced a reduction of symptom burden within the first 3 days, with faster symptom relief and shorter episodes in cancer patients compared to non-cancer patients (median length 3d vs 2d). DRPs were documented in 213/230 episodes (92.6%), indicating high interaction potential of antiemetics (87.4%). Manifest DRPs affected patients due to ineffective treatment (29.0%) or side effects (6.5%).

CONCLUSIONS: One-third experienced inadequate symptom control with the current treatment, underscoring the complexity of managing nausea/vomiting in palliative care and the need for a systematic approach. This study emphasizes the importance of evidence-based guidelines and further research into underutilized antiemetics, along with improved medical education in an interdisciplinary team to enhance treatment quality.

PMID:39819071 | DOI:10.1177/10499091251313757

Mayo Clin Proc. 2025 Jan 14:S0025-6196(24)00546-9. doi: 10.1016/j.mayocp.2024.10.016. Online ahead of print.

NO ABSTRACT

PMID:39818680 | DOI:10.1016/j.mayocp.2024.10.016

J Adolesc Health. 2025 Jan 16:S1054-139X(24)00551-2. doi: 10.1016/j.jadohealth.2024.10.033. Online ahead of print.

ABSTRACT

PURPOSE: Despite growing concerns about trends in cocaine use, there is a shortage of longitudinal research that prospectively examines risk and protective factors associated with cocaine initiation and use in general youth populations. This study addresses this gap.

METHODS: Growing Up in Ireland is a nationally representative cohort. Individual, family, and socio-environmental exposures associated with incident past-year cocaine use at ages 17 (N = 5965) and 20 (n = 4549) were assessed with survey-weighted logistic regression using generalised estimating equations. Prevalent past-year cocaine use at 20 (N = 4679) was analysed using generalised estimating equations complemented by gradient-boosted decision trees and Shapley explanations.

RESULTS: 221 (3.7%) self-reported cocaine use at 17 and 1072 (22.9%) at 20. Alcohol use at 14 or younger was associated with eight times the odds of cocaine use at 17 (aOR 8.0, 95% CI 1.7-37.3) and 19 times at 20 (aOR 19.2, 95% CI 8.6-43.2). Peer cannabis use was associated with 7 times the odds of cocaine use at 17 (aOR 7.3, 95% CI 2.9-18.3) and double at 20 (aOR 2.4, 95% CI 1.8-3.2). Growing up in a neighbourhood where substance use was common doubled the odds of cocaine use at 17 (aOR 2.4, 95% CI 1.3-4.4). Shapley explanations revealed individual-specific positive or negative impacts of exposures.

DISCUSSION: Cocaine use among 20-year-olds in Ireland is higher than reported internationally, and increases sharply between the ages of 17 and 20, suggesting a need for interventions targeting this age group. However, associations with early adolescent factors suggest that early interventions may also be important.

PMID:39818654 | DOI:10.1016/j.jadohealth.2024.10.033