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Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape

Proteomics identifies complement protein signatures in patients with alcohol-associated hepatitis.

Diagnostic challenges continue to impede development of effective therapies for successful management of alcohol-associated hepatitis (AH), creating an unmet need to identify noninvasive biomarkers for AH. In murine models, complement contributes to ethanol-induced liver injury. Therefore, we hypothesized that complement proteins could be rational diagnostic/prognostic biomarkers in AH. Here, we performed a comparative analysis of data derived from human hepatic and serum proteome to identify and characterize complement protein signatures in severe AH (sAH). The quantity of multiple complement proteins was perturbed in liver and serum proteome of patients with sAH. Multiple complement proteins differentiated patients with sAH from those with alcohol cirrhosis (AC) or alcohol use disorder (AUD) and healthy controls (HCs). Serum collectin 11 and C1q binding protein were strongly associated with sAH and exhibited good discriminatory performance among patients with sAH, AC, or AUD and HCs. Furthermore, complement component receptor 1-like protein was negatively associated with pro-inflammatory cytokines. Additionally, lower serum MBL associated serine protease 1 and coagulation factor II independently predicted 90-day mortality. In summary, meta-analysis of proteomic profiles from liver and circulation revealed complement protein signatures of sAH, highlighting a complex perturbation of complement and identifying potential diagnostic and prognostic biomarkers for patients with sAH.

Humans

On the origin of C3 nephritic factor (antibody to the alternative pathway C3 convertase): evidence for the Adam and Eve concept of autoantibody production.

The antibody to the alternative pathway C3 convertase, designated C3 nephritic factor or C3NeF, is an autoantibody that is produced in everyone from the time of birth. The elaboration of C3NeF utilizes germline V-region genes which undergo antigen-driven affinity maturation, resulting in an autoantibody that is produced in large amounts with high affinity and narrow specificity. Our data also suggest that under normal conditions, the idiotypic network may play an important part in the control of this autoantibody. Further, a defect in the network with loss of control or inappropriate stimulation may be an underlying mechanism in the unrestricted production of C3NeF in patients with membranoproliferative glomerulonephritis.

Adult

RBC-GEM: A genome-scale metabolic model for systems biology of the human red blood cell.

Advancements with cost-effective, high-throughput omics technologies have had a transformative effect on both fundamental and translational research in the medical sciences. These advancements have facilitated a departure from the traditional view of human red blood cells (RBCs) as mere carriers of hemoglobin, devoid of significant biological complexity. Over the past decade, proteomic analyses have identified a growing number of different proteins present within RBCs, enabling systems biology analysis of their physiological functions. Here, we introduce RBC-GEM, one of the most comprehensive, curated genome-scale metabolic reconstructions of a specific human cell type to-date. It was developed through meta-analysis of proteomic data from 29 studies published over the past two decades resulting in an RBC proteome composed of more than 4,600 distinct proteins. Through workflow-guided manual curation, we have compiled the metabolic reactions carried out by this proteome to form a genome-scale metabolic model (GEM) of the RBC. RBC-GEM is hosted on a version-controlled GitHub repository, ensuring adherence to the standardized protocols for metabolic reconstruction quality control and data stewardship principles. RBC-GEM represents a metabolic network is a consisting of 820 genes encoding proteins acting on 1,685 unique metabolites through 2,723 biochemical reactions: a 740% size expansion over its predecessor. We demonstrated the utility of RBC-GEM by creating context-specific proteome-constrained models derived from proteomic data of stored RBCs for 616 blood donors, and classified reactions based on their simulated abundance dependence. This reconstruction as an up-to-date curated GEM can be used for contextualization of data and for the construction of a computational whole-cell models of the human RBC.

Humans

Cell type resolved MR based on brain single cell eQTLs corroborated by single cell RNA sequencing uncovers neuroimmune and vascular programs in intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) lacks effective neuroprotective therapies. We integrated cell type–resolved genetic inference with single-cell profiling to map putative causal programs and multicellular circuitry relevant to ICH. METHODS: Cis-eQTLs from eight human brain cell types were used as instruments for two-sample Mendelian randomization (MR), with an ICH meta-analysis from large biobanks and a stroke consortium as the outcome. Instruments were LD-pruned and restricted to strong variants (F > 10). Inverse-variance weighting (IVW) was the primary estimator, supported by robustness methods, heterogeneity/pleiotropy diagnostics, and false discovery rate control. Experimental validation used mouse collagenase ICH single-cell RNA-seq at 24 h (n = 3 sham; n = 3 ICH) with Seurat integration, composition testing, Slingshot pseudotime, and CellChat. An independent mouse cohort underwent qRT–PCR for selected genes. RESULTS: The ICH meta-analysis showed acceptable genomic control, supporting downstream MR. We identified 524 nominal gene–cell type associations, with a glia-weighted signal landscape. Enrichment implicated autophagy/mitophagy, antigen processing, cytoskeletal and vesicular trafficking, endothelial matrix–adhesion programs, ferroptosis, and myelin stress pathways. In mouse scRNA-seq, disease-associated microglia expanded with reciprocal loss of homeostatic microglia and increased neutrophils and T cells. Prioritized genes showed directional concordance; qRT–PCR confirmed ARPC3 and EIF2AK2 upregulation and TBCK and SPECC1 downregulation in ICH versus sham. Pseudotime supported a shift toward disease-associated microglial states, and CellChat indicated increased network interaction strength with microglia and endothelium as hubs. CONCLUSIONS: Cell type–specific MR combined with single-cell validation highlights neuroimmune and neurovascular programs in ICH and links genetic signals to state transitions and inferred intercellular communication.

Animals

Possible linking and treatment between Parkinson's disease and inflammatory bowel disease: a study of Mendelian randomization based on gut-brain axis.

BACKGROUND: Mounting evidence suggests that Parkinson's disease (PD) and inflammatory bowel disease (IBD) are closely associated and becoming global health burdens. However, the causal relationships and common pathogeneses between them are uncertain. Furthermore, they are uncurable. Thus, we aimed to identify the causal relationships and novel therapeutic targets shared between them based on their common pathophysiological mechanisms in gut-brain-axis (GBA). METHODS: A meta-analysis on bidirectional Mendelian randomization (MR) utilizing various datasets was performed to estimate their causal relationship. Then, pleiotropic analysis under the composite null hypothesis (PLACO) with functional mapping combined with annotation of genetic associations (FUMA) analysis were conducted to identify pleiotropic genes. Next, blood, brain and intestine expression quantitative trait locus (eQTL) were taken to perform drug-target MR finding common causal genes in two diseases. Colocalization analysis ensured the eQTLs of corresponding gene colocalized with disease. Enrichment analysis and protein‒protein interaction (PPI) network were done to explore common pathogenesis pathways. Genes passed all analysis were regarded as drug targets. RESULTS: Our MR meta-analysis revealed the bidirectional causal relationship between diseases, with combined ORs for PD on IBD, CD, UC (1.050 [95% CI 1.014-1.086], 1.044 [95% CI 0.995-1.095], 1.063 [95% CI 1.016-1.120]); for IBD, CD, UC on PD (1.003 [95% CI 0.973-1.034], 1.035 [95% CI 1.004-1.067], 1.008 [95% CI 0.977-1.040]). Overall, 277, 216 and 201 genes were identified as pleiotropic genes between PD and IBD, CD, UC. Total of 733 genes were classified as tier 3 (found in only one tissue) druggable targets, 57 as tier 2 (found in two tissues, 51 protein-coding genes) and 9 as tier 3 (found in three tissues). Among 60 protein-coding druggable targets over tier 2, 18 overlapped with pleiotropic genes and enriched in mitochondria, antigen presentation, processing and immune cell regulation pathways. Three druggable genes (LRRK2, RAB29 and HLA-DQA2) passed colocalization analysis. LRRK2 and RAB29 were reported to be pleiotropic genes, and RAB29 and HLA-DQA2 were reported for the first time as potential drug targets. CONCLUSIONS: This study established a reliable causal relationship, possible shared drug targets and common pathogenesis pathways of two diseases, which had important implications for intervention and treatment of two diseases simultaneously.

Humans

A systematic review and meta-analysis of visuospatial attentional deficits in Parkinson's patients.

Parkinson's disease (PD) is a neurodegenerative condition primarily characterized by motor deficits, yet cognitive impairments are increasingly recognized. While deficits in executive functioning are well documented even in the absence of cognitive decline, evidence of attentional deficits in PD remains inconsistent, and the role of motor symptom lateralization is unclear. In this systematic review and meta-analysis, we examined visual attention in right-handed, cognitively unimpaired idiopathic PD patients, focusing on the canonical attentional domains (sustained, selective, divided) and processes (alerting, endogenous and exogenous orienting, reorienting), as well as visuospatial bias. Four databases were searched for studies comparing PD patients with healthy controls. Meta-analytic estimates were derived using Hedges' g within random-effects models, and studies that could not be quantitatively integrated were summarized narratively. In addition, studies directly comparing patients with left- and right-predominant motor symptoms (LPD vs. RPD) were reviewed qualitatively. Across 51 studies, PD patients exhibited deficits in sustained, selective, and divided attention. Among attentional processes, only exogenous orienting was impaired, whereas alerting, endogenous orienting, and reorienting were preserved. Findings from the few studies examining visuospatial bias indicated small, context-dependent shifts in spatial attention rather than a consistent directional bias. These findings indicate that PD patients show visual-attentional impairments, particularly under high-demand conditions, while basic alertness and voluntary orienting appear preserved. Exogenous orienting deficits and subtle rightward spatial tendencies in LPD suggest disruption of right-hemisphere attentional networks. These results have implications for early cognitive assessment, rehabilitation strategies, and understanding the neural bases of attentional dysfunction in PD.

Humans

A Risk Score for Polycystic Ovary Syndrome Based on Meta-Analysis and Machine Learning of Gut Microbiota Signatures.

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine and metabolic disorder among reproductive-age women, in which emerging evidence suggests a substantial role played by the gut microbiota. To comprehensively evaluate gut microbiota alterations in PCOS and identify microbial biomarkers through integrated analysis, a systematic search of PubMed, Web of Science, and Embase was conducted for studies employing 16S rRNA gene sequencing of fecal samples from PCOS cohorts. Ten eligible PCOS cohorts, comprising 858 individuals, were included in the study, from which a risk score was derived using a 20-gene gut microbial signature associated with PCOS. Meta-analysis at the genus level identified that Subdoligranulum, NK4A214_group, and Collinsella significantly decreased, and Bacteroides increased in PCOS across multiple cohorts. Machine learning analysis identified a 20-genus microbial signature using the least absolute shrinkage and selection operator (LASSO) method, which was used to construct a risk score with an AUC of 0.835 in diagnosis prediction. Network analysis further identified Negativibacillus and Lachnospiraceae_UCG_010 as potential driver microbes in PCOS. The analysis in this study highlights key alterations in the gut microbiota across PCOS cohorts. The identified gut microbial signature and derived LASSO-based risk model offer novel insights and a potential tool for PCOS diagnosis.

Polycystic Ovary Syndrome

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses.

OBJECTIVE: Numerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations. METHODS: Relevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software. RESULTS: As for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways "positive regulation of cytosolic calcium ion concentration" and "inositol phosphate-mediated signaling" and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility. CONCLUSION: Herein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Bayes Theorem

Precisely designed keystone metabolites boost shrimp disease resistance by recruiting symbionts via the lipoxin A4-AP-1 pathway.

BACKGROUND: Gut metabolites and symbionts are indispensable for host health, yet the precise identification of keystone metabolites and construction of synthetic microbial communities (SynComs) to enhance disease resistance remains limited. RESULTS: Using Litopenaeus vannamei as a model, we identified pyruvic acid and DL-glutamine (1:2) as keystone metabolites by borrowing the microbial ecology principles of bio-indicators and driver taxa. Dietary supplementation with these metabolites sufficiently protected shrimp from white feces syndrome (WFS). Multi-omics analyses demonstrated that keystone metabolites exerted positive effects by enriching beneficial Ruegeria lacuscaerulensis, Bacillus subtilis and Nioella nitratireducens, strengthening the gut network stability, and enhancing shrimp immunity, which collectively potentiated WFS resistance. The recruited three strains were consumers and producers of the two keystone metabolites, and discriminative strains between healthy and diseased shrimp across global datasets. A SynCom constructed from the three strains (4:3:2) replicated the efficacy of keystone metabolites. Both keystone metabolites and SynCom elevated shrimp gut and hepatopancreas lipoxin A4 (LXA4) levels, which suppressed the pro-inflammatory transcription factor AP-1, as validated by in vivo inhibition assay. CONCLUSIONS: Our findings demonstrate that precisely designed keystone metabolites enhance shrimp disease resistance through the recruitment of key symbionts-LXA4-AP-1 axis. The rationally designed keystone metabolites and SynCom are compelling biocontrol solutions in improving host disease resistance. Video Abstract.

Animals

Discovering diabetes complications-related microRNAs: meta-analyses and pathway modeling approach.

PURPOSE: MicroRNAs(miRNA) play an important role in the pathogenesis of diabetic complications by regulating gene expression. The objective of this paper is to investigate micoRNA expression in diabetic nephropathy (DN), diabetic retinopathy (DR), diabetic neuropathy (DNP), and diabetic cardiopathy (DC). METHODS: We conducted this systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement and retrieved eligible microRNA-related studies of diabetic complications from PubMed, Embase, and Web of science databases. We enriched pathways corresponding to differentially expressed miRNAs using the miRPath tool on the DIANA website, and predicted their target genes with DIANA microT-CDS and TargetScan. RESULTS: Although many of the selected studies were of high scientific quality, the results were heterogeneous. Among the 71 selected articles, 79 miRNAs were differentially expressed in various complications of diabetes, of which miRNA126, miRNA192 and 17 others were reported in at least two or more studies. A total of 156 target genes were predicted and 103 pathways were obtained by KEGG enrichment analysis. CONCLUSION: This comprehensive systematic evaluation provides experimental evidence statistics for miRNAs as circulating biomarkers and highlights promising biomarkers. These results provide preliminary data to further investigate the role of miRNAs in the diagnosis and therapeutic targets of human diabetic complications and support future broader longitudinal studies to better substantiate the role of dysregulated miRNAs as potential biomarkers and therapeutic targets of diabetic complications.

Humans

Protein-protein interactions reveal key genes in rice response to salt stress: a meta-analysis.

The salt-tolerant genes (STGs) play important roles in protecting plants against salt stress. Although various types of STGs have been systematically characterized in plant species, the key genes (KGs) regulating salt stress tolerance in rice (Oryza sativa L.) remain elusive. This study focused on the identification and characterization of the members of STGs in rice through integrated bioinformatic and molecular approaches, including chromosomal location, physicochemical characteristics, protein-protein interaction, and expression profiles of the identified genes. A total of 164 differentially expressed genes (DEGs) were systematically identified as responsive to salt tolerance and sorted out potential 12 kg (OsHSP20.2, OsGFP2, OsBBTI2, OsEN20.6, OsUBC17, OsACD5, OsPEAB5, OsDP11, OsDFP5, OsWD40.7, OsEP11.1, and OsGRAM12) through the CytoHubba algorithms analysis. Physicochemical characterization indicated substantial variation among KGs, including genomic sequences (824-4051 bp), amino acid length (148-659 aa), molecular weight (16.39-71.35 kDa), and isoelectric point (4.66-10.37). Protein-protein interaction (PPI) network prediction indicated intricate functional associations among key STGs. Gene Ontology (GO) enrichment analysis revealed that the KGs are involved in numerous biological processes and molecular functions. Moreover, gene homology results revealed that KGs have multiple relationships with other plant species. Co-expression network analysis revealed that 12 kg are potentially involved in the regulatory mechanisms underlying the biological process. Relative gene expression through the comparative threshold (ΔΔCT) of qRT-PCR revealed that the KGs are salt-induced and may play crucial roles in rice responses to salt stress. Tissue-specific expression patterns revealed that the KGs significantly altered expression levels across different tissues and under stress. This systematic investigation demonstrated that the 12 identified genes may play roles in the development of salt-tolerant rice varieties.

Oryza

Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta-Analyses.

OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.

Humans

Unravelling the biological nexus of smoking and postpartum depression: a meta-analysis and functional genomics approach.

PURPOSE: Postpartum depression (PPD) is a prevalent psychological condition among birthing women. While several psycho-socio-economic and neurobiological factors influence its development, its relationship with smoking behavior and nicotine addiction remains largely inconclusive. METHODS: In this combinatorial study, we first evaluate the relationship between smoking and depressive behaviors in postpartum women using data extracted from pertinent primary epidemiological studies. Additionally, to discern the molecular and cellular mechanisms underlying this association, we identified common genetic elements and evaluated their functional attributes using in silico analyses. RESULTS: Meta-analytical assessment of systematically collected data from 38 studies indicated that smoking women are twice as likely to develop PPD, compared to their non-smoking counterparts. While geocultural attributes did not affect this relationship, timing of smoking was a significant moderator, with current and gestational smoking statuses being more strongly linked with PPD outcome, compared to the past smoking habit. Further, depression scores in smoking postpartum women were higher than those in non-smoking controls. Analysis of the common protein-encoding genes underlying the pathophysiology of nicotine addiction and PPD revealed several critical hub proteins (viz., AKT1, JUN, CTNNB1, PTEN, EGFR, ESR1, SRC, STAT3, FN1, IL1B, IL6, TNF, TP53, GAPDH, INS, MYC, and ALB) which were predicted to alter multiple pathophysiological pathways associated with transcriptional expression, intra- and intercellular signaling transduction, metabolism, and immune functions. CONCLUSION: Our results indicate that smoking is strongly associated with depressive behavior in postpartum women, although this association involve mediation of additional environmental and psychosocial elements. Moreover, network analysis of common genetic elements identified several potentially disrupted neurophysiological pathways in postpartum women with smoking and depressive behaviors which may aid in characterizing the underlying relationship between the two conditions.

Humans

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.

Humans

Strategies to improve recruitment to randomised trials.

BACKGROUND: Recruiting participants to randomised controlled trials (RCTs) is challenging. Identifying effective recruitment strategies would benefit health research: poor recruitment leads to underpowered trials, reducing the reliability of findings and increasing the risk of wasted resources, ethical concerns, and trial failure. Evidence to inform recruitment strategies is increasingly generated through Studies Within A Trial (SWATs), which are methodological studies embedded within host RCTs. This is an update of a review last published in 2018. OBJECTIVES: Primary: to quantify the effects of strategies to improve recruitment of participants to RCTs. Secondary: to evaluate recruitment strategies' cost-effectiveness and impact on retention, and the equity, diversity, and inclusion (EDI) characteristics of recruited participants. SEARCH METHODS: We used MEDLINE, Embase, and six other databases to identify the studies included in the review. We also sought unpublished recruitment SWATs through social media and targeted email dissemination to trial methodology networks. The latest search date was 16 February 2023. SELECTION CRITERIA: We included randomised SWATs evaluating trial recruitment strategies embedded in healthcare and non-healthcare trials. We excluded quasi-randomised, hypothetical, questionnaire-only, retention-only, or clinician incentive studies. DATA COLLECTION AND ANALYSIS: Primary outcome: proportion of eligible participants or centres recruited. SECONDARY OUTCOMES: cost-effectiveness, retention rates, and EDI characteristics of included participants. We conducted random-effects meta-analysis for strategies evaluated in at least two studies; otherwise, we synthesised results narratively. We reported effects as risk differences (RDs) with 95% confidence intervals (CIs), and assessed between-trial heterogeneity. We used GRADE to assess the certainty of evidence for the primary outcome. We expressed cost-effectiveness as the incremental cost per additional participant recruited in pounds sterling (GBP). MAIN RESULTS: We identified 91 eligible studies (53 new to this update), providing 94 comparisons and involving at least 176,747 participants. Eighty-one studies involved strategies aimed at trial participants, while 10 evaluated strategies aimed at recruiters. All were healthcare studies. We found 65 recruitment strategies; 49 were evaluated in a single study. Only five strategies were supported by high-certainty evidence according to GRADE criteria, and we focus on these strategies in the summary below. Open-label trials versus blinded, placebo trials. Open-label trials recruited more participants than blinded trials (RD 10%, 95% CI 8% to 12%; 3 studies, 9004 participants), corresponding to approximately 10 additional participants per 100 approached. The studies involved mostly women in the UK and Estonia. No cost or retention data were reported. Telephone reminder versus no telephone reminder. Telephone reminders to people who did not respond to an initial postal invitation boosted recruitment by 6% (95% CI 3% to 9%; 2 studies, 1450 participants), in trials with low underlying recruitment (we are less certain for trials with over 10% recruitment). The studies involved people with a mean age of 58 years in Canada and Norway. No cost or retention data were reported. Recruitment primer letter versus no letter. Pre-recruitment letters and leaflets designed to encourage participation made little or no difference to recruitment (absolute improvement 1%, 95% CI -1% to 2%; 2 studies, 5376 participants), and were associated with increased costs compared to not sending a primer (incremental cost: GBP 2.08). The studies involved mostly older white people in the UK and Ireland. Multimedia information via a digital link/QR code plus paper participant information leaflet (PIL) versus paper PIL alone. This made little or no difference to recruitment (absolute improvement 0%, 95% CI -1% to 1%; 7 studies, 11,612 participants) and retention (absolute improvement 0%, 95% CI -2% to 3%; 5 studies, 7403 participants), and increased costs compared to not including multimedia information (incremental cost: GBP 0.78). The studies involved people in the UK. Optimised, user-tested PIL versus standard PIL. Optimising participant information leaflets (e.g. through user-testing the leaflet with the target population to shape its content, format, and appearance) made little or no difference to recruitment: absolute improvement was 0% (95% CI 0% to 1%; 6 studies, 27,805 participants). The studies involved people in the UK. Only one study reported EDI data; participants were mostly older women. No cost or retention data were reported. We had moderate-certainty evidence for 13 other strategies; confidence was often reduced because the results came from single studies. Seven strategies involved changes to how potential participants received information; four involved changes to trial conduct; one targeted the recruiter or recruitment site; and one tested non-monetary incentives. We had much less confidence in the other 47 comparisons because the studies had design flaws, were single studies, or had very uncertain results. Costs were reported in only 17 of 91 studies. Strategy impact on retention was reported in 15 studies. All but one study (99%) were from high-income countries. The most reported demographics were age (49 studies), sex (32 studies), gender (27 studies), and education level (16 studies). AUTHORS' CONCLUSIONS: The evidence on strategies to improve trial recruitment remains broad but lacks depth. Of 65 strategies evaluated, only five were supported by high-certainty evidence. Open-label trial designs and telephone reminders to non-responders increased recruitment, while optimised participant information leaflets, recruitment primer letters, and multimedia information provided alongside a paper participant information leaflet had little or no effect. Reporting of participant characteristics was poor, limiting assessment of equity, diversity, and inclusion across most studies. Evidence is heavily skewed toward high-income countries. Future research must prioritise evaluations in low-to-middle-income settings and consistently report cost, retention, and EDI outcomes. We strongly urge the methodology research community to strengthen the evidence base by prioritising replications of existing strategies over the development and testing of new ones. FUNDING: National Institute for Health and Care Research (Advanced Fellowship, Adwoa Parker, reference:NIHR302256). Health Research Board, Republic of Ireland, Evidence Synthesis Ireland (grant ESI-2021-001) REGISTRATION: This review updates an earlier Cochrane review, which was first published in 2002 and subsequently updated in 2007, 2010, and 2018. Previous versions of the review and their protocols are available at: https://doi.org/10.1002/14651858.MR000013.pub2 https://doi.org/10.1002/14651858.MR000013.pub3 https://doi.org/10.1002/14651858.MR000013.pub4 https://doi.org/10.1002/14651858.MR000013.pub5 https://doi.org/10.1002/14651858.MR000013.pub6.

Randomized Controlled Trials as Topic