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PubMed2024

An insight into the causal relationship between sarcopenia-related traits and venous thromboembolism: A mendelian randomization study.

BACKGROUND: As a geriatric syndrome, sarcopenia has a high prevalence in the old population and represents an impaired state of health with adverse health outcomes. A strong clinical interest in its relationship with venous thromboembolism (VTE), which is a complex trait disease with a heterogeneous annual incidence rate in different countries, has emerged. The relationship between sarcopenia and venous thromboembolism has been reported in observational studies but the causality from sarcopenia to VTE remained unclarified. We aimed to assess the causal effect of sarcopenia on the risk of VTE with the two-sample Mendelian randomization (MR) method. METHODS: Two sets of single-nucleotide polymorphisms (SNPs), derived from two published genome-wide association study (GWAS) meta-analyses and genetically indexing muscle weakness and lean muscle mass separately, were pooled into inverse variance weighted (IVW), weighted median and MR-Egger analyses. RESULTS: No evidence was found for the causal effect of genetically predicted muscle weakness (IVW: OR = 0.90, 95% CI = 0.76-1.06, p = 0.217), whole body lean mass (IVW: OR = 1.01, 95% CI = 0.87-1.17, p = 0.881) and appendicular lean mass (IVW: OR = 1.13, 95% CI = 0.82-1.57, p = 0.445) on the risk of VTE. However, both genetically predicted whole-body lean mass and appendicular lean mass can causally influence diabetes mellitus (IVW of whole-body lean mass: OR = 0.87, 95% CI = 0.78-0.96, p = 0.008; IVW of appendicular lean mass: OR = 0.71, 95% CI = 0.54-0.94, p = 0.014) and hypertension (IVW of whole-body lean mass: OR = 0.92, 95% CI = 0.87-0.98, p = 0.007; IVW of appendicular lean mass: OR = 0.84, 95% CI = 0.73-0.96, p = 0.013). CONCLUSIONS: Genetically predicted sarcopenia does not causally influence VTE directly, but it might still have an indirect effect on VTE incidence via diabetes mellitus and hypertension.

Humans↗

PubMed2026

The effect of antiretroviral therapy adherence on viral load suppression rate among people living with HIV in Ethiopia: A systematic review and meta-analysis.

BACKGROUND: Antiretroviral therapy (ART) adherence is a key determinant of viral load suppression among people living with HIV (PLHIV). In Ethiopia, evidence on the magnitude of ART adherence and its effect on virological outcomes remains fragmented. This systematic review and meta-analysis aimed to estimate the pooled prevalence of ART adherence and viral load suppression, and to measure the association between adherence and viral suppression among PLHIV in Ethiopia. METHODS: This systematic review and meta-analysis used the PRISMA checklist for systematic reviews and meta-analyses. The review protocol has been registered onPROSPERO:(CRD420251125899). PubMed, ScienceDirect, Scopus, Epistemonikos, and Google Scholar were searched. The quality of included articles has been evaluated with a Newcastle-Ottawa Scale (NOS), adapted for observational studies. A random-effects model using restricted maximum likelihood (REML) with Knapp-Hartung adjustment was used to estimate pooled prevalence and odds ratio. Heterogeneity was assessed using I2, τ2, and Cochran's Q test. RESULTS: A total of 39 studies were included in the final analysis. The pooled prevalence of good ART adherence was 79.4% (95% CI: 74.8%-83.4%), while the pooled viral load suppression rate was 77.5% (95% CI: 72.5%-81.8%). The pooled odds ratio showed that good ART adherence was strongly associated with viral load suppression (OR = 6.30, 95% CI: 4.84-8.19). Substantial heterogeneity was observed across studies for both adherence and viral suppression outcomes (I2 > 90%). CONCLUSIONS: ART adherence and viral load suppression among PLHIV in Ethiopia are relatively high but remain below global targets. Good adherence was significantly associated with virologic suppression, highlighting adherence as a critical modifiable factor for achieving optimal treatment outcomes. Strengthening adherence support interventions is essential to improve virological success and advance progress toward HIV epidemic control.

Humans↗

PubMed2025

Alterations in DNA Methylation, Proteomic, and Metabolomic Profiles in African Ancestry Populations with APOL1 Risk Alleles.

KEY POINTS: We aimed to elucidate potential methylation, proteomic, and metabolomic mechanisms by which APOL1 variants may be linked to kidney disease. We report distinct methylation profiling between APOL1 risk allele carriers and noncarriers, many near APOL gene family. We report higher APOL1 protein and lower C18:1 cholesteryl ester in two risk allele carriers. BACKGROUND: The APOL1 high-risk haplotype has been associated with CKD and the deterioration of kidney function, particularly in populations with West African ancestry. However, the mechanisms by which APOL1 risk variants increase the risk for kidney disease and its progression have not been fully elucidated. METHODS: We compared methylation (N=3191; 715 [22%] carriers), proteomic (N=1240; 169 [14%] carriers), and metabolomic (N=6309; 674 [11%] carriers) profiles in African and Hispanic/Latino carriers of two APOL1 high-risk alleles (G1/G1, G2/G2, G1/G2) and noncarriers (G0/G0), excluding heterozygotes (G0/G1, G0/G2), from the Population Architecture using Genomics and Epidemiology Consortium and UK Biobank. In each study, the associations between the APOL1 high-risk haplotype and up to 722,719 cytosine-phosphate-guanine (CpG) sites, 2923 proteins, or 836 metabolites were estimated using covariate-adjusted linear regression models, followed by fixed-effects sample size–weighted meta-analyses. RESULTS: Significant associations were observed between APOL1 high-risk haplotype and methylation at 52 CpG sites, with 48 located on chromosome 22 and 18 in the vicinity of APOL1–4 and MYH9. All significant CpG sites near APOL2 were hypomethylated, whereas those near APOL3 and APOL4 were hypermethylated. APOL1-associated CpG sites were also identified in genes involved in ion transport and mitochondrial stress pathways. Sensitivity analyses indicated consistent yet attenuated effects among heterozygotes, supporting an additive effect of APOL1 risk alleles. Further analyses of the 52 CpG sites identified two near APOL4 exhibiting G1-specific effects, eight associated with CKD but none with eGFR, and three showing heterogeneity by CKD status. In addition, carrying two APOL1 risk alleles was associated with higher plasma APOL1 protein (β=1.12, PFDR = 2.26e-70) and lower C18:1 cholesteryl ester metabolite (Z=−4.50, PFDR = 4.83e-3). CONCLUSIONS: Our results demonstrate differential methylation, proteomic, and metabolomic profiles associated with APOL1 high-risk haplotypes.

APOL1↗

PubMed1992

Pharmacologic therapy of mild to moderate hypertension: possible generalizability to diabetics.

This article reviews the evidence on pharmacologic therapy of hypertension in reducing morbidity and mortality from stroke and coronary heart disease (CHD) and considers the possible generalizability of these findings to diabetics. For malignant hypertension, benefits are large and obvious from uncontrolled case series. For severe hypertension, conclusive benefits have been shown in several randomized trials. For mild to moderate hypertension, however, it is necessary to consider meta-analyses of all individual trials. The most comprehensive of these shows reductions of 42% for total stroke (95% Cl, -33 to -50%; P < 0.0001) and 14% for all CHD (95% Cl, -4 to -22%; P < 0.01). The applicability to diabetics is unclear because they were excluded from most of the trials. The Hypertension Detection and Follow-Up Program included diabetics and reported subgroup analyses. The reduction in mortality among the actively treated diabetics of 5% was less than the 17% achieved in nondiabetics. It is unclear, however, whether the mortality reductions are truly different or reflect the play of chance. Because of the higher incidence of CHD events among diabetics with hypertension, a similar relative benefit would result in a much greater absolute risk reduction. Further, the drugs used adversely affect lipid and glucose metabolism. New antihypertensive drugs without these side effects may further improve the risk-to-benefit ratio of antihypertensive treatment, especially in diabetics, who are at a several-fold absolute increased risk or cardiovascular disease.(ABSTRACT TRUNCATED AT 250 WORDS)

Antihypertensive Agents↗

PubMed2025

Generative AI Models in Time-Varying Biomedical Data: Scoping Review.

BACKGROUND: Trajectory modeling is a long-standing challenge in the application of computational methods to health care. In the age of big data, traditional statistical and machine learning methods do not achieve satisfactory results as they often fail to capture the complex underlying distributions of multimodal health data and long-term dependencies throughout medical histories. Recent advances in generative artificial intelligence (AI) have provided powerful tools to represent complex distributions and patterns with minimal underlying assumptions, with major impact in fields such as finance and environmental sciences, prompting researchers to apply these methods for disease modeling in health care. OBJECTIVE: While AI methods have proven powerful, their application in clinical practice remains limited due to their highly complex nature. The proliferation of AI algorithms also poses a significant challenge for nondevelopers to track and incorporate these advances into clinical research and application. In this paper, we introduce basic concepts in generative AI and discuss current algorithms and how they can be applied to health care for practitioners with little background in computer science. METHODS: We surveyed peer-reviewed papers on generative AI models with specific applications to time-series health data. Our search included single- and multimodal generative AI models that operated over structured and unstructured data, physiological waveforms, medical imaging, and multi-omics data. We introduce current generative AI methods, review their applications, and discuss their limitations and future directions in each data modality. RESULTS: We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and reviewed 155 articles on generative AI applications to time-series health care data across modalities. Furthermore, we offer a systematic framework for clinicians to easily identify suitable AI methods for their data and task at hand. CONCLUSIONS: We reviewed and critiqued existing applications of generative AI to time-series health data with the aim of bridging the gap between computational methods and clinical application. We also identified the shortcomings of existing approaches and highlighted recent advances in generative AI that represent promising directions for health care modeling.

Artificial Intelligence↗

PubMed2026

Smartphone Apps for Preventing Adolescent Health Problems Among Health Care Professionals: Systematic Search and Quality Assessment.

BACKGROUND: Health care professionals must consider multiple dimensions of prevention when consulting with adolescents. Identifying risky behaviors early in adolescence is crucial for reducing both morbidity and mortality. General practitioners are increasingly eager to incorporate digital tools for prevention into their consultations with adolescents; however, the relevance and clinical validity of these digital tools are not always established or well-known. Consequently, primary care professionals require guidance and support in selecting relevant mobile health (mHealth) tools. OBJECTIVE: The aim of this study is to identify relevant and useful digital apps to help primary care professionals detect at-risk adolescents across all recommended areas of prevention: orthopedics, mental health, substance abuse, risk behaviors, sexual health, vaccinations, social relationships, and nutrition. METHODS: A systematic review of smartphone apps, with an analysis of content quality, was carried out by 4 researchers using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The App Store and Google Play Store platforms were surveyed. The inclusion criteria were as follows: free of charge, date of last update, availability in French or English, relevance of the preventive approach to adolescents, and scientific validation. Four health care professionals assessed the apps: 2 selected the apps relevant to health care professionals, then 3 analyzed these apps using the French version of the Mobile App Rating Scale (MARS-F). Intraclass correlation coefficient, model (2,1) (2-way random effects, absolute agreement, single measures); standard error of measurement; and mean absolute error were also calculated. RESULTS: A total of 976 apps were identified, 49 of which had disappeared from the platforms prior to analysis. Nine apps were retained. Seven (0.72%) were included after evaluation using the MARS-F: 2 on mental health and 5 on sexual health (including 3 on contraception only). The mean MARS-F interrater score ranged from 2.5/5 to 3.8/5. The global MARS-F score demonstrated a pooled SD of 0.60 and an intraclass correlation coefficient (2,1) of 0.0003, resulting in a calculated standard error of measurement of 0.60. The average discrepancy between raters was a mean absolute error of 0.53. CONCLUSIONS: No similar studies have been identified in the literature that specifically focus on mobile apps designed to support health care professionals in delivering preventive care to adolescents. Of the 8 areas of prevention identified as relevant for adolescents, only 3 are addressed by the apps validated through our methodology (5 focus on sexual health). Consequently, current apps are insufficient to support health care professionals in their overall preventive work with adolescents. Such a review should be conducted systematically prior to the development of any new tool to prevent duplication and channel creative efforts toward truly innovative digital solutions. Furthermore, a thorough analysis of relevant, recommended websites is essential, as these resources complement the use of mobile apps designed for health care professionals.

Humans↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Effectiveness of Wearable Digital Therapeutics in Improving Sleep Outcomes Among Individuals With Insomnia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Wearable devices are increasingly used for sleep monitoring and as adjunctive treatment. Existing meta-analyses mostly pool composite digital therapies and rarely isolate stand-alone wearables or distinguish between objective and subjective end points. Whether stand-alone wearable interventions improve sleep outcomes in adults with insomnia, and which factors moderate treatment heterogeneity, remains unclear. OBJECTIVE: This study aims to evaluate the effectiveness of wearable digital interventions on sleep outcomes in adults with insomnia versus control strategies and explore moderators of effectiveness, including device-wearing position, intervention duration, and control type, using meta-regression. METHODS: This systematic review and meta-analysis was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses) 2020 statement and the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses Literature Search Extension) guideline. Five electronic databases and clinical trial registries were searched from inception to May 18, 2026. Eligible studies were randomized controlled trials (RCTs) evaluating wearable digital interventions in adults with insomnia compared with sham, waitlist, usual care, or active control conditions and had an intervention duration of at least 1 week. Study screening, data extraction, and risk-of-bias assessment were carried out independently by 2 reviewers. Pooled estimates were calculated using a restricted maximum likelihood random-effects model with the Hartung-Knapp-Sidik-Jonkman correction. Heterogeneity was assessed using the I² statistic, and 95% prediction intervals (PIs) were calculated for the primary analyses. The certainty of evidence was rated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. RESULTS: Sixteen RCTs (N=910) were included. Wearable digital interventions were associated with a significant reduction in objective sleep-onset latency (SOL; mean difference [MD] -4.52, 95% CI -8.38 to -0.67, PI -9.52 to 0.47 min) and a significant improvement in subjective sleep efficiency (SE; MD 2.00%, 95% CI 1.90%-2.11%, PI 1.85%-2.15%). Subjective total sleep time (TST) also showed a significant increase (MD 19.11, 95% CI 2.98-35.24, PI -16.20 to 54.43 minutes). Meta-regression showed that control type, intervention duration, and device location did not explain the heterogeneity of the insomnia severity index (ISI) (R²=0). Sensitivity analysis confirmed the robustness of pooled ISI estimates, and an Egger test indicated no small-study effects (P=.07). Certainty of evidence ranged from moderate to high. CONCLUSIONS: Wearable digital interventions provide selective benefits for objective SOL, subjective SE, and subjective TST in adults with insomnia, with no improvement in overall ISI. Despite statistically significant effects on several sleep parameters, wide PIs, substantial heterogeneity, and limited study numbers indicate preliminary, nonconclusive findings. Wearables should be viewed as affordable adjunctive tools requiring further validation, not substitutes for first-line cognitive behavioral therapy for insomnia. Large-scale, long-term RCTs with standardized protocols and patient-level external validation are required to consolidate the evidence base.

Humans↗

PubMed1992

Oral contraceptives and cancer of the cervix uteri. A meta-analysis.

AIM AND OBJECTIVE: Because the findings of epidemiologic studies of the relationship between oral contraceptive use and cervical cancer have not been consistent, we reanalyzed the relationship. DESIGN: Meta-analysis of studies published to date. SETTING AND SUBJECTS: Papers were located by searching the MEDLINE data base, supplemented by a hand search of all the references in the articles recovered. MEASUREMENTS: Studies were graded as to quality. Two meta-analyses were performed: one including all the studies gathered and one including methodologically acceptable studies only. The method of Woolf was used to combine relative risks. Heterogeneity of the effect was assessed. MAIN RESULTS: Fifty-one published studies were collected: 21 case-control, 18 cross-sectional, and 12 cohort designs. Twenty-one of these were considered as methodologically acceptable, but only 18 could be pooled. The main results observed were: relative risks was 1.52 (1.3-1.8) for dysplasia, 1.52 (1.3-1.8) for carcinoma in situ, and 1.21 (1.1-1.4) for invasive cancer. A significant linear dose-response effect was observed in dysplasia, carcinoma in situ, and invasive cervical cancer. Heterogeneity of the effect was present in some of the former estimates. CONCLUSIONS: Oral contraceptive use may be a risk factor for all stages of the natural history of cervical cancer, which may imply an initiator effect. Limitations to this research are discussed.

Carcinoma in Situ↗

PubMed2026

Evaluation of population-specific polygenic risk scores for blood lipids: insights from Taiwanese cohorts and multiancestry meta-analysis.

BACKGROUND: Blood lipids are heritable risk factors for cardiovascular disease (CVD), a leading cause of mortality worldwide. However, the genetic architecture of lipid traits and the performance of polygenic risk scores (PRSs) remain underexplored in East Asian (EAS) populations, including Taiwanese Han individuals. METHODS: We conducted genome-wide association studies and PRS analyses for five lipid traits: total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and the ratio of low-density lipoprotein cholesterol to total cholesterol. Lipid profile data were obtained from the China Medical University Hospital cohort. PRSs were evaluated on the basis of their correlations with measured lipid levels. To evaluate trans-ancestry PRS transferability, localized models were systematically compared against models derived from discovery-stage GWAS meta-analyses incorporating five ancestry groups from the Global Lipids Genetics Consortium. The performance of the PRS models in predicting lipid-related diseases was evaluated through receiver operating characteristic curve analyses. RESULTS: The population-specific PRS models explained 11%-40% of the variance in lipid levels within the target cohort. Models leveraging global multiancestry GWAS meta-analysis weights revealed limited predictive performance (r 2 = 0.04-0.19), whereas analyses incorporating EAS-specific data yielded higher correlations (r 2 = 0.13-0.30), although these correlations did not exceed those derived from the hospital-based cohort alone. When combined with age and sex, the PRS models demonstrated strong predictive performance for coronary artery disease, atherosclerosis, and ischemic stroke, with area under the curve values of 0.910, 0.926, and 0.854, respectively. CONCLUSION: Population-specific PRS models derived from a Taiwanese population outperformed meta-analysis-derived frameworks in predicting lipid levels and demonstrated substantial potential for predicting CVD risk, indicating the importance of ancestry-matched genetic studies in precision medicine.

LDL-C/TC ratio↗

PubMed2026

Genetic associations in sepsis and ARDS.

Critical illness syndromes, such as sepsis and acute respiratory distress syndrome (ARDS), are characterized by substantial clinical heterogeneity and remain major causes of morbidity and mortality worldwide. Increasing evidence suggests that genetic variation contributes to susceptibility, disease severity, and clinical outcomes in critically ill patients. However, the molecular mechanisms linking genetic predisposition to the pathophysiology of sepsis and ARDS remain incompletely understood. In this review, we evaluated genetic associations reported in sepsis and ARDS, including 13 genome-wide studies identifying 19 unique single-nucleotide polymorphisms (SNPs) across 17 distinct genomic loci, as well as 21 meta-analyses of candidate-gene studies identifying 21 SNPs across 16 genes. The identified variants were primarily associated with pathways involved in pathogen recognition, immune and inflammatory signaling, leukocyte recruitment, and endothelial dysfunction. Collectively, these findings support a polygenic basis for susceptibility to critical illness and highlight several biologically relevant pathways that may contribute to sepsis and ARDS pathogenesis. Improved understanding of the functional consequences of these variants may facilitate the identification of potential therapeutic targets and support the development of precision-guided approaches to critical care.

ARDS↗

PubMed2021

Genetic Relationship Between Endometriosis and Melanoma.

Epidemiological studies have observed that risk of endometriosis is associated with history of cutaneous melanoma and vice versa. Evidence for shared biological mechanisms between the two traits is limited. The aim of this study was to investigate the genetic correlation and causal relationship between endometriosis and melanoma. Summary statistics from genome-wide association meta-analyses (GWAS) for endometriosis and melanoma were used to estimate the genetic correlation between the traits and Mendelian randomization was used to test for a causal association. When using summary statistics from separate female and male melanoma cohorts we identified a significant positive genetic correlation between melanoma in females and endometriosis (r g = 0.144, se = 0.065, p = 0.025). However, we find no evidence of a correlation between endometriosis and melanoma in males or a combined melanoma dataset. Endometriosis was not genetically correlated with skin color, red hair, childhood sunburn occasions, ease of skin tanning, or nevus count suggesting that the correlation between endometriosis and melanoma in females is unlikely to be influenced by pigmentary traits. Mendelian Randomization analyses also provided evidence for a relationship between the genetic risk of melanoma in females and endometriosis. Colocalization analysis identified 27 genomic loci jointly associated with the two diseases regions that contain different causal variants influencing each trait independently. This study provides evidence of a small genetic correlation and relationship between the genetic risk of melanoma in females and endometriosis. Genetic risk does not equate to disease occurrence and differences in the pathogenesis and age of onset of both diseases means it is unlikely that occurrence of melanoma causes endometriosis. This study instead provides evidence that having an increased genetic risk for melanoma in females is related to increased risk of endometriosis. Larger GWAS studies with increased power will be required to further investigate these associations.

endometriosis↗

PubMed2026

SARS-CoV-2-related immune dysregulation and biologically plausible pathways to lymphomagenesis: a PRISMA-ScR-based scoping review.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related immune dysregulation has generated interest in diagnostic pathology because infection-related inflammation, long coronavirus disease (COVID)-related immune disturbance, and post-vaccination lymphoid reactions may overlap with lymphoid-biological mechanisms and complicate the distinction between reactive lymphoid proliferations and lymphoid neoplasia. AIM: This scoping review aimed to map biologically plausible pathways through which SARS-CoV-2-associated immune perturbation may intersect with lymphomagenesis-related mechanisms, emphasizing diagnostic implications rather than causality. MATERIALS AND METHODS: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). PubMed∕MEDLINE, Scopus, and Web of Science were searched from January 2020 to March 2026, with selected pre-2020 sources retained for mechanistic or diagnostic relevance. Sources were charted across mechanistic, immunological, virological, clinicopathological, and diagnostic domains. RESULTS: After screening and eligibility assessment, 63 sources were retained for thematic synthesis. Evidence clustered around lymphoma-relevant but non-specific mechanisms, including inflammatory signaling, impaired immune surveillance, latent oncogenic viral reactivation, prolonged germinal-center activity with activation-induced cytidine deaminase (AID)-related genomic vulnerability, and lymphoid microenvironment remodeling. These mechanisms appear most relevant in predisposed hosts with chronic immune dysregulation, latent viral infection, defective deoxyribonucleic acid (DNA) repair, or occult abnormal lymphoid clones. Infection and vaccination are distinct contexts, because infection may produce broader immune disruption, whereas most post-vaccination nodal events are reactive and self-limited. CONCLUSIONS: Current evidence supports biological plausibility rather than a direct or generalizable causal relationship. The main diagnostic implication is careful clinicopathological correlation and distinction between reactive lymphoid proliferations and lymphoid neoplasia in post-COVID-19 and post-vaccination settings.

Humans↗

PubMed2026

Multi-Ancestry Survival GWAS of Substance Use Initiation in the ABCD Study.

BACKGROUND: Substance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. METHODS: We conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes-alcohol, nicotine, cannabis, and any substance use-using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochran's Q and I 2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. RESULTS: In the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol ~ 1 × 10-7, any ~ 1 × 10-7, cannabis ~ 5 × 10-8, nicotine ~ 1 × 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 × 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. CONCLUSIONS: Survival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

ABCD↗

PubMed2026

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us.

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide ("All by All") computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

Journal Article↗

PubMed2026

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries. We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis. Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in ANKRD12 implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in NAA15 link protein acetylation processes to type 2 diabetes risk. BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.

Journal Article↗

PubMed2026

Evolving Role of Immunotherapy in Advanced Esophageal Squamous Cell Carcinoma: Are Programmed Death-Ligand 1 (PD-L1) Cutoffs Still Relevant?

Immune checkpoint inhibitors have transformed the management of advanced esophageal squamous cell carcinoma (ESCC) across first-line, second-line, and perioperative settings. Programmed death-ligand 1 (PD-L1) expression has served as the principal biomarker guiding patient selection for these agents, yet it is measured inconsistently across trials and antibody platforms, and its predictive value has come under renewed scrutiny as follow-up data have matured. This review synthesizes the pivotal randomized trials that established anti-programmed cell death protein-1 therapy in ESCC, critically appraises the pooled and patient-level meta-analyses that have re-examined outcomes across biomarker subgroups, and situates recent regulatory reassessment of PD-L1 thresholds within this broader evidence base. Assay heterogeneity between scoring systems, discordance across antibody clones, and the biological distinction between PD-L1 as a prognostic versus a predictive marker are examined as sources of continued uncertainty. The review concludes by considering emerging genomic and microenvironmental biomarkers that may eventually complement or refine PD-L1-based patient selection, and offers a framework for interpreting a single expression threshold as an approximate, assay-dependent stratifier rather than a precise biological boundary.

combined positive score↗

PubMed1992

[Mishaps with anti-arrhythmic agents used to reduce mortality after infarction].

The presence of isolated and/or repetitive ventricular arrhythmias following myocardial infarction identifies a group of patients at increased risk of death. The availability of anti-arrhythmic drugs, noticeably drugs with class I activity, efficient at suppressing arrhythmias has led to the hope that their administration could reduce post-myocardial infarction mortality. However, this hypothesis has not been confirmed. The Cardiac Arrhythmia Suppression Trial, which was designed to have the power to test the hypothesis that suppression of ventricular arrhythmias is associated with a decrease in mortality following myocardial infarction, even showed an increase in mortality with two drugs with class I activity. Several meta-analyses have confirmed that administration of class I antiarrhythmic drugs is of no clinical benefit in patients with non sustained ventricular arrhythmias following myocardial infarction. Ongoings studies are testing the hypothesis that such benefit could exist with amiodarone. The clinical benefit of beta-blockers, in terms of reduction of both total and sudden death post-myocardial infarction, has been clearly documented and mandates their administration in this setting. Futures studies of anti-arrhythmic drugs will have to focus on groups of patients at increased risk of arrhythmic death.

Amiodarone↗