Journal of the Endocrine Society

The insulin-like growth factor (IGF)/IGF-binding protein (IGFBP) axis has been implicated in diabetes mellitus and the associated burden of cardiovascular complications. Higher circulating levels of IGFBP-1 and IGFBP-2 have been established as markers of protection from incident type 2 diabetes, yet their associations with cardiovascular disease remain unclear. Utilising the UK Biobank (UKB) resource to integrate disease outcomes, plasma proteomics and MRI data, we examined associations of IGFBP-1 and IGFBP-2 with incident diabetes and cardiovascular disease. Approximately 50,000 UKB participants with plasma proteomic measurements for IGFBP-1 and IGFBP-2 were included. Multivariate Cox regression models revealed that participants in the highest quartiles of IGFBP-1 and IGFBP-2 had a substantially lower risk of incident diabetes (hazard ratio (HR) = 0.31 and 0.32 respectively), but, paradoxically, had increased risks of incident macrovascular disease, all-cause and cardiovascular-related mortality (HR = 1.81 and 2.39). Both proteins were negatively associated with HbA1c levels, triglyceride/HDL ratio and abdominal adiposity, yet positively associated with NT-proBNP, troponin I, cardiac chamber size and aortic dimensions. In summary, negative associations of IGFBP-1 and IGFBP-2 with incident diabetes mellitus did not translate to a reduced cardiovascular risk, suggesting potentially complex actions of IGFBP-1 and IGFBP-2 in the pathophysiology of cardiometabolic disease.

Background Unsupervised machine learning has become a cornerstone of computational phenotyping across clinical medicine, genomics, imaging, and multi-omics research. However, phenotype discovery relies on a sequence of analytical decisions - including missing-data handling, preprocessing, dimensionality reduction, clustering methodology, and stochastic initialization - that are rarely evaluated collectively. Although clustering stability has been extensively investigated, the robustness of complete analytical workflows remains largely unexplored. Results We developed an Analytical Perturbation Framework that systematically quantifies the robustness of phenotype discovery by perturbing complete unsupervised learning workflows rather than individual clustering algorithms. Using a real-world cohort of 1,286 women with polycystic ovary syndrome (PCOS), we generated 116 valid analytical pipelines comprising alternative preprocessing strategies, missing-data handling methods, dimensionality reduction approaches, clustering algorithms, and random initializations. Agreement between independently generated phenotype solutions was consistently low (median Adjusted Rand Index = 0.079), indicating substantial sensitivity of phenotype discovery to routine analytical decisions. Variance decomposition identified preprocessing as the largest contributor to phenotype instability (22.8%), followed by clustering methodology (14.6%), whereas stochastic initialization explained only 3.1% of the observed variability. At the patient level, most individuals exhibited reproducible phenotype assignments (median Patient Robustness Score = 0.719), although a substantial subgroup showed markedly lower assignment stability. Feature perturbation analyses identified follicle-stimulating hormone, anti-thyroglobulin antibodies, anti-thyroid peroxidase antibodies, total testosterone, luteinizing hormone, and androstenedione as the strongest contributors to computational robustness, rather than biological importance. Finally, phenotype solutions demonstrating greater computational robustness also exhibited greater biological coherence during independent validation.

Background: We sought to determine the changing prevalence, incidence, and temporal trends in real-world, recorded diagnoses of metabolic dysfunction-associated steatotic liver disease (MASLD) and assess availability of fibrosis risk stratification following awareness campaigns and guideline updates over the last decade. Methods: This population-based cohort study identified MASLD diagnoses made between 2003 to 2022 in the UK primary-care Clinical Practice Research Datalink (CPRD) to estimate prevalence and incidence. A nested case-control analysis, utilising 1:4 age-, sex-, and general practice-matched controls, assessed clinical characteristics, availability of Fibrosis-4 (Fib-4) components, and its temporal trend pre- and post-2015. Findings: 11.7 million individuals were active in CPRD in 2022. 365,797 comprised the study cohort of people with a MASLD diagnosis (matched to 1,460,288 controls). From 2012-2022, recorded MASLD prevalence rose from 0.52% [N=51,028] to 2.42% [N=283,762] (p<0.001); recorded incidence doubled from 1.60 to 3.31 per 1000 person-years (p<0.001). People with MASLD diagnosis had a higher prevalence of type 2 diabetes (21.0% [N=76,640] vs 7.7% [N=112,812]) and hypertension (35.3% [N=129,156] vs 18.7% [N=273,502]). People of South Asian ethnicity were overrepresented in MASLD cohort but had the lowest availability of Fib-4 components (14.6% [N=4,467]; adjusted odds ratio 0.67, 95% CI: 0.65-0.70, vs White). Overall, Fib-4 availability increased pre- to post-2015 (4.3% [N=4,945] to 22.8% [N=56,634]). Among those with a calculable score, fewer South Asian individuals had indeterminate/high risk (18.6% [N=833] vs 35.3% [N=15,115] in White individuals, p<0.001). Interpretation: Recorded MASLD prevalence has increased 5-fold in a decade, yet a diagnostic gap persists. Fibrosis risk stratification has improved, but remains low and is potentially inequitable for people of South Asian ethnicity. Funding: Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA; Barts Charity. Keywords: Epidemiology, Real-world data, Real-world evidence, MASLD, Primary Care

Insulin resistance, an often-untreated precursor of type 2 diabetes mellitus (T2DM), is implicated in cognitive decline in adults, yet its impact on the developing brain in youth with obesity remains poorly understood. We investigate whether insulin resistance moderates the relation between hippocampal volume and unhealthy food-seeking in overweight and depressed youth ages 9-17 who completed an oral glucose tolerance test and a cognitive task assessing unhealthy food-seeking motivation at baseline, 6-, and 24-months follow-up, and structural MRI at baseline and 6-months follow-up. Insulin sensitivity moderated this relation: smaller baseline hippocampal subfield volumes predicted increased unhealthy food-seeking over 24 months (ps<0.05). Categorical grouping revealed subfield CA2/3 and 4 volumes predicted this relation among insulin-resistant (ps<0.05), but not insulin-sensitive (ps>0.10), youth, suggesting that threshold criteria for insulin resistance are physiologically meaningful. These findings identify a neuro-metabolic risk phenotype that precedes T2DM and may accelerate unhealthy food-seeking severity in youth with obesity.

Background: Prolonged unsupplemented spiritual fasting (USF), complete caloric abstinence motivated by spiritual practice, is undertaken by many communities worldwide, yet its physiological consequences remain poorly characterized. No prior study has documented continuous real-time monitoring during free-living fasting beyond 10 days. Methods: We conducted a self-controlled observational study of 23 experienced Jain practitioners undergoing USF. Seventeen completed at least 8 days of fasting (11 completed eight days, six continued to 30 days); six discontinued early. Continuous glucose monitoring (CGM) and blood biomarkers at baseline (Day-0), post-fasting (Day-9), and 60-day follow-up (Day-69) were obtained. Mood was assessed daily using PANAS. Within-participant comparisons used both parametric and non-parametric t-tests. Results: CGM revealed near-complete suppression of glycaemic variability within 24-48 hours of fasting onset, sustained throughout with no clinical hypoglycaemia in either cohort. Blood biomarkers showed transient perturbation during fasting -- including rises in hepatic enzymes, bilirubin, uric acid, creatinine, and lipid fractions -- broadly reversible by follow-up (Day-69). hsCRP rose during fasting then fell below baseline at follow-up (5.52{+/-}13.67 to 3.68{+/-}13.18 mg/L, p=0.034). HDL significantly rose above baseline (45.71{+/-}112.32 to 48.97{+/-}111.19, p=0.045) and LDL similarly declined below baseline (122.33{+/-}132.10 to 106.96{+/-}131.62 mg/dL, p=0.035); and then both significantly improved by follow-up. Thyroid axis suppression fully normalized by follow-up. Psychological wellbeing was maintained throughout. Conclusions: Extended USF produces a safely reversible pattern of acute physiological adaptation with net cardiometabolic benefit. Absence of clinical hypoglycaemia during 30-day water-only USF, documented here for the first time with CGM, provides empirical grounding for future controlled trials.

Aims Metformin remains the primary treatment for type 2 diabetes, yet over 40% of patients fail to maintain glycaemic control. We aimed to identify patients unlikely to respond to metformin prior to treatment initiation and to evaluate whether on-treatment management can improve glycaemic outcomes in suboptimal responders, informing early treatment decisions. Materials and Methods We analyzed 59,881 longitudinal HbA1c measurements from 7,105 patients with type 2 diabetes receiving metformin monotherapy using real-world electronic health records from Kaiser Permanente Northern California with up to six years of follow-up. We integrated demographic, clinical, genetic, and pharmacological factors to characterize metformin responder phenotypes and quantify the impact of adherence and weight control on time to glycaemic failure. Results Three distinct trajectory-based phenotypes were identified: good (63.6%), poor (8.9%), and non-responders (27.5%). Poor responders initially achieved glycaemic targets but lost control within 2.5 years, while non-responders showed minimal HbA1c reduction and failed within 1 year. Five baseline factors-HbA1c, age at diagnosis, body mass index, sex, and estimated glomerular filtration rate-classified phenotypes with good discrimination (area under the receiver operating characteristic curve = 0.84). Incorporating on-treatment HbA1c further enhanced identification of non-responders. Among suboptimal responders, weight control and improved adherence delayed glycaemic failure by approximately 7 months; however, eventual glycaemic failure remained likely. Conclusions We characterized three clinically relevant metformin responder phenotypes and showed that suboptimal responders can be identified early using baseline features. Poor and non-responders are unlikely to achieve durable glycaemic control with metformin alone and may require alternative treatment strategies.

Prenatal alcohol exposure (PAE) is a major cause of neurodevelopmental disorders, yet most children are diagnosed late or misdiagnosed. Neuroplacentology suggest that placental factors released into maternal and/or umbilical cord blood contribute to fetal brain development. Consistently, a preclinical inter-organ transcriptomic database revealed that PAE disrupts the expression ratio of angiogenic and inflammatory factors suggesting an angio-inflammatory response. This study aimed i) to assay, by multiplex immunoassay, angiogenic and inflammatory factors in maternal and umbilical cord blood from alcohol-consuming women and ii) to perform a maternofetal analysis according to neonatal sex. Afterwards, dysregulated factors from mothers who gave birth to females or males were submitted to STRING and ShinyGO analyses. Results showed that PAE differently altered the distribution profiles of dysregulated angiogenic and inflammatory factors in maternal and umbilical cord blood. Moreover, sex-specific differences were observed, with 36% of dysregulated proteins specific to males, 48% to females, and 16% common to both. STRING analysis revealed robust functional protein-protein interactions linking together inflammatory and angiogenic clusters while the ShinyGO analysis identified enriched pathways related to vascular shear stress. These findings provide the first maternofetal analysis of combined angiogenic and inflammatory factors from alcohol-consuming mothers.

Background: Randomized controlled trials have shown that computed tomographic (CT) screening reduces lung cancer mortality. Improved identification of at-risk groups, by leveraging non-smoking risk factors, could help refine screening selection. Aim: To evaluate polygenic risk scores (PRSs) and ambient air pollution (AAP) exposure for risk stratification in the NELSON lung cancer screening cohort. Methods: Two PRSs (PRS-McKay/PRS-Byun) and several AAPs (including nitrogen dioxide, ozone, and particulate matter [PM]) were assessed in the NELSON lung cancer screening trial (N=7,364). PRSs were validated in the Rotterdam Study (N=11,493). Associations with lung cancer, mortality, screening results, and discriminative ability to distinguish lung cancer were evaluated. Results: PRS-McKay and PRS-Byun were associated with lung cancer (odds ratio [OR] per SD [95%CI]: 1.22 [1.08-1.37] and 1.28 [1.13-1.44], respectively) and lung cancer-specific mortality (OR [95%CI]: 1.24 [1.05-1.47], for both), but not with non-lung cancer mortality (OR [95%CI]: 1.01 [0.94-1.10] and 1.03 [0.95-1.12], respectively). Exposure to PM2.5 was associated with lung cancer (OR [95%CI]: 1.11 [1.01-1.22]). PM constituents were associated with adenocarcinoma, particularly PM10 (OR [95%CI]: 1.16 [1.01-1.32]) and ultra-fine particles (OR [95%CI]: 1.16 [1.04-1.30]). PRS and AAP added modestly to the discriminative ability for lung cancer on top of pack-years, age, and sex (area under the curve [95%CI]: 0.659 [0.624-0.695] vs. 0.643 [0.608-0.679]). Conclusions: PRSs and exposure to PM were associated with lung cancer in a high-risk screening population. The primary potential of PRSs may reside in refining lung cancer screening selection toward individuals at higher risk of dying from lung cancer specifically.

Background Functional neurological disorder (FND), one of the most common neurological conditions, affects women almost twice as frequently as men. The reasons for this are unknown, and there has been minimal research into how physiological and pathological features of women's health interact with symptoms of FND. Methods We conducted an online survey assessing the effect of several aspects of women's health with the severity of symptoms of FND. Results 484 people completed the survey. Among the 223 who had regular or fairly regular menstrual cycles, a strong difference across the menstrual cycle was seen, with symptoms at their best in the follicular phase, worsening in the luteal phase, and worst in the pre-menstrual period and the menses. This effect was not moderated by a proxy measure of pre-menstrual dysphoric disorder (PMDD). Participants who were taking the combined oral contraceptive (COC, n=43) and progesterone-based contraception (n=80) were more likely to report symptom improvement from starting the medication than worsening. When compared to menstruating participants who were not taking the COC, participants taking the COC reported less worsening in their symptoms of FND in the luteal, pre-menstrual, and menstrual phases. Of the 99 women who had passed menopause since developing FND, 76% reported worsening of their FND symptoms after menopause. Discussion This study demonstrates interactions between several aspects of women's health and symptoms of FND. The observed pattern of symptom fluctuation across hormonal states suggests a potential modulatory role of oestrogen, warranting further targeted investigation.

Background: Monoclonal antibodies have emerged as a prophylactic strategy to prevent symptomatic SARS-CoV-2 infection in immunocompromised individuals. However, the evolutionary and clinical implications of breakthrough infections under this regime remain unclear. Methods: A male in their 80s with a haematological/oncological diagnosis received a 2000 mg intravenous infusion of sotrovimab in March 2023 and was diagnosed with COVID-19 by RT-qPCR from a nasopharyngeal swab in August 2023. Weekly samples (n=24) were collected through February 2024 (171 days). All samples underwent whole-genome sequencing, with select mutations subjected to functional assessment. Findings: Sequencing identified the GE.1 lineage at all timepoints. An intra-host recombination event in ORF1ab (positions 8942-12458) was detected prior to 23 weeks post-detection, followed by a 14-fold increase in viral load (7.42e+06 to 1.00e+08 RNA copies/mL) and a marked shift in the viral population. E340D, a sotrovimab resistance mutation, was detected at low abundance (46%) within the first week post-infection, fluctuated over time, and was nearly fixed by week 15 (107 days) post-detection. We assessed five spike mutations - V36M, S98F, and V213G in the N-terminal domain, Y505P in the receptor-binding domain, and P681Q near the S1/S2 cleavage site - and additionally evaluated the impact of E340D. V36M conferred the highest infectivity across all cell lines, with the most significant effect in low-TMPRSS2 cells. While all mutations showed enhanced infectivity with the addition of E340D, the effect was most pronounced in mutations with lower baseline infectivity. The addition of E340D significantly decreased relative neutralizing titres for V36M, S98F, and V213G, enabling escape from neutralizing antibodies in XBB-responsive individuals, illustrating an enhanced phenotypic advantage. Patient neutralizing activity was absent pre-sotrovimab, and sotrovimab-induced neutralization was further compromised by selection of E340D. Interpretation: Sotrovimab pre-exposure prophylaxis in an immunocompromised patient did not prevent SARS-CoV-2 infection, and selected for resistant mutation E340D, with unexpected fitness consequences across non-receptor binding domain spike regions.

Purpose: Nonresponse to routinely collected patient-reported outcome measures (PROMs) threatens the representativeness of aggregated data. We characterized patient-, provider-, and clinic-level factors associated with PROMIS Global-10 nonresponse in routine radiation oncology care. Methods: In this retrospective cohort study, all adults seen at five Mass General Brigham radiation oncology clinics over one year were included. The primary outcome was patient-level nonresponse, defined as never completing the portal-administered Global-10 versus completing it at least once. Using iterative mixed-effects logistic regression, we modeled patient-, provider-, and clinic-level factors. Results: Among 12,214 patients, 71 providers, and five clinics, patient- and appointment-level response rates were 35.4% and 10.9%, with patient-level response ranging nearly fivefold across clinics (12.8% to 66.2%). In Model 1, male sex, lower education, not working, and recent surgery had higher odds of nonresponse, and longer time since diagnosis lower odds. After provider- and clinic-level factors were added, patient sex, education, and employment became nonsignificant, whereas recent surgery (adjusted odds ratio [aOR] 1.97) and longer time since diagnosis (aOR 0.46 for >12 months) persisted. A provider's historical collection rate was protective but attenuated at the clinic level. There, a later program launch (aOR 0.29) and higher historical collection rate (aOR 0.79) correlated with lower nonresponse, whereas academic versus community setting did not. Conclusions: Nonresponse to routinely collected PROMs is a multilevel phenomenon driven substantially by clinic-level implementation factors, not patient characteristics alone. Because response rate is only a proxy for representativeness, PROMs programs and PRO-based performance measures should prioritize representative collection over volume.

Controlled human infection models (CHIMs) are increasingly used in infectious disease research to study pathogen dynamics and evaluate interventions under controlled conditions. However, these studies are resource-intensive and involve ethical and safety constraints, making efficient study design critical. Dose-finding is a key early component in CHIMs, where the aim is to identify a challenge dose that achieves a target infection probability. Traditional rule-based designs are commonly used but can be inefficient, motivating the use of model-based adaptive approaches such as the Bayesian Continual Reassessment Method (CRM). Although CRM has been extensively studied and widely adopted in Phase I oncology trials for identifying the maximum tolerated dose of therapeutics, its application in CHIM settings remains limited, particularly when the endpoint of interest is infection. This tutorial provides step-by-step guidance for implementing a Bayesian CRM in dose-finding CHIMs, using an oropharyngeal Neisseria gonorrhoeae challenge as a motivating case study. The framework outlines key design components, including dose-grid specification, dose-response model, prior elicitation, Bayesian updating, decision rules, and stopping criteria, with particular emphasis on a clinically interpretable parameterisation. Trial operating characteristics are evaluated through simulation studies under multiple dose-response scenarios and prior-predictive analyses, and compared with a commonly used '3+3' type rule-based design. This work highlights the advantages of Bayesian model-based designs for dose-finding in CHIMs over classic rule-based designs and provides a structured, reproducible framework for implementing CRM, supporting their application in future CHIM studies.

Background and Aims The optimal treatment for first episodes and first recurrences of Clostridioides difficile infections (CDI) is unknown and there is emerging evidence for pulse and taper (P-T) regimens. Therefore, we sought to estimate the relative efficacy of treatment options. Methods MEDLINE and CENTRAL were searched from database inception to May 21, 2025 and unpublished conference abstracts were searched from recent infectious disease conferences. RCTs on the treatment of first episodes or first recurrences of CDI comparing fixed-dose or P-T regimens of fidaxomicin or vancomycin were included. The primary and secondary outcomes were 40- and 56-day CDI recurrence, respectively. A random-effects network meta-analysis on the risk ratio (RR) scale was conducted using a standard regimen (10-14 days) of vancomycin as the comparator. Treatments were ranked using the surface under the cumulative ranking curve (SUCRA). Results 8 RCTs were included comprising a total of 2181 patients. For 40-day recurrence, fidaxomicin P-T had the highest probability of ranking best (RR=0.10, 95%Confidence Interval [95%CI]=0.10-0.49, SUCRA=1.00), followed by vancomycin P-T (RR=0.49, 95%CI=0.32-0.76, SUCRA=0.61), fixed-dose fidaxomicin (RR=0.61, 95%CI=0.49-0.76, SUCRA=0.39), and, finally, fixed-dose of vancomycin (SUCRA=0.00). The treatments ranked in the same order for 56-day recurrence, though only 3 RCTs reported on this timepoint. Conclusion Vancomycin P-T, fidaxomicin P-T, and fixed-dose fidaxomicin were all superior to a fixed-dose vancomycin. Head-to-head comparative effectiveness RCTs are needed to quantify their relative effect sizes of and impact on long-term prevention of recurrent CDI.

Background The 2022-2023 global mpox outbreak highlighted the critical need for robust genomic surveillance capabilities to track mpox virus (MPXV) evolution and transmission dynamics. Methods Building upon our established SARS-CoV-2 sequencing infrastructure, we implemented a Molecular Loop probe-based long-read sequencing approach using Pacific Biosciences Sequel II technology for comprehensive MPXV genomic surveillance across the United States (US). From August 2024 to June 2025, we generated 326 high-quality whole genome sequences from residual mpox-positive clinical specimens collected by Labcorp across all 10 US Department of Health and Human Services regions. Results Our analysis identified two samples containing clade Ib MPXV in January and June 2025 and captured shifting trends in clade IIb diversity, with 13 distinct lineages observed. We also identified multiple instances of large (~1.6-17.6kb) deletions proximal to the inverted terminal repeats in clade IIb genomes. APOBEC3 mutation analysis indicated substantial evidence of human-to-human transmission among both clades. Further, we observed significantly higher APOBEC3-associated SNPs per kilobase (P<0.001) in clade IIb genomic variable regions relative to their central conserved region. Our assay exhibited strong reproducibility across biological replicates from individual patients and accuracy was confirmed via parallel sequencing of select specimens by US Centers for Disease Control and Prevention (CDC) using metagenomic sequencing. We also demonstrated via custom simulation that our assay discriminates all known MPXV clades and lineages, including those we have not observed in the US. Conclusions Our integrated nationwide surveillance system facilitates real-time genomic tracking of outbreak evolution, with demonstrated capacity across SARS-CoV-2 and MPXV, positioning this platform for rapid deployment during future pathogen emergence.

The World Health Organization (WHO) validated Sri Lanka had eliminated lymphatic filariasis as a public health problem in 2016, the second country in Southeast Asia to attain this status. However, post-validation surveillance has identified sporadic cases of brugian filariasis. The reemergence of Brugia malayi infections in Sri Lanka warrants urgent investigations. Recent studies have shown that the parasite responsible for the reemergence is a novel zoonotic Brugia sp. maintained among dogs that is closely related but distinct to the human-infecting B. malayi species. The current study employed morphological and morphometric assessments, revealing that this novel zoonotic Brugia sp. is within the B. malayi morphological range. Molecular characterization of three genomic regions, the nuclear genomic region SLXI, the non-coding region HhaI, and the mitochondrial genomic region COXI confirmed it as a genetic variant more closely related to B. malayi than to B. pahangi. Phylogenetic analysis further indicated it as a distinct genomic variant, closely related to a B. malayi-like parasite reported from India. Notably, that same parasite was identified in infected humans, animals, and potential vector mosquitoes. This, together with the detection of both human and animal blood within the same brugian infective mosquitoes, and delineating the canine origin of the parasites in human infections, provides compelling evidence supporting zoonotic transmission of this parasite. To our knowledge, this is the first report demonstrating the presence of the same brugian parasite in humans, domestic animals, and potentially infective mosquitoes in Sri Lanka, supported by multi-genomic evidence. The recent identification of multiple potential mosquito vector species suggests that this parasite may have undergone adaptive changes, facilitating its ability to overcome the species barrier. These findings substantiate the long-held hypothesis of zoonotic transmission of the reemerged brugian parasite, highlighting significant implications for ongoing surveillance and control strategies.

Background: Opioid use disorder (OUD) is heritable, yet most genome-wide association studies (GWAS) have focused on European populations, leaving the genetic architecture of OUD in non-European populations underexplored. Methods: We conducted GWAS of OUD across three ancestries using electronic health records and genomic data from 52,357 All of Us Research Program participants (8,912 cases; 43,445 matched opioid-exposed controls; 48.5% female). Participants were stratified into European (EUR), African (AFR), and Admixed American (AMR) ancestry groups for logistic regression GWAS, with independent replication in the Million Veteran Program. We then applied the deep-learning model AlphaGenome to predict the tissue-specific transcriptomic and splicing consequences of top risk variants across 13 reward-pathway brain regions. Results: We identified and replicated a novel DDX6 risk locus, alongside established OPRM1 and FURIN signals. AlphaGenome predicted the DDX6 regulatory allele downregulates the stress-resistance gene FOXR1 in the nucleus accumbens, while the protective OPRM1 variant (rs1799971) upregulates OPRM1 expression across reward networks. Other signals of interest included IL6R and SHISA9 (EUR); GHR (AFR); and ASTN2 (AMR). Conclusions: This study identifies DDX6 as a novel OUD risk locus, replicates associations with OPRM1 and FURIN, and highlights biologically plausible ancestry-specific signals in AFR and AMR populations. We also replicated top variants in an independent population. Finally, integrating GWAS with deep-learning annotations provides specific, localized biological hypotheses to guide future experimental validation and targeted therapeutics.

Stochastic epidemic models are a cornerstone of infectious disease epidemiology and are often used to study intervention scenarios. However, large run-to-run variability can make intervention effects difficult to estimate precisely. We revisit the epidemic Sellke construction, which assigns each individual an infection threshold for the cumulative infection hazard such that, conditional on the thresholds, the epidemic trajectory becomes deterministic. This enables coupling of simulations with and without an intervention, yielding low-variance effect estimates even when outcomes such as final size or peak incidence vary widely between runs. We develop an exact, event-driven implementation that maintains infection and recovery events in priority queues. Cumulative infection-hazard updates require O(log N) time per event, yielding overall complexity O(Elog N) for E events in a population of size N. The implementation achieves computational performance comparable to the classical Gillespie algorithm while naturally accommodating non-Markovian infectious periods and complex infectiousness profiles. We illustrate the approach using distance-dependent spread of avian influenza between poultry farms in the Netherlands and a multilayer population with households, schools, and workplaces. In both examples, coupling enables efficient within-run comparisons of intervention scenarios across stochastic realisations.

Estimating dengue force of infection (FOI) is essential for understanding transmission dynamics and targeting intervention programmes, yet surveillance data in endemic settings required for estimations are often incomplete, with varying formats. We developed a Bayesian hierarchical catalytic model that jointly fits age-stratified case data, aggregate case data, and seroprevalence surveys within a single framework, incorporating external covariates to improve parameter identifiability. Synthetic validation showed that covariates alone recovered accurate FOI point estimates even when most districts contributed only aggregate data, but did so with poorly calibrated uncertainty; anchoring the model with a single seroprevalence survey was necessary to bring credible interval coverage close to nominal. Applied to 128 districts across Java and Bali, Indonesia (2016-2024), the model revealed substantial spatial heterogeneity in FOI and reporting rates. Many districts in Java exceeded the WHO-suggested seroprevalence threshold for vaccine introduction, yet were classified as low-priority when using reported incidence as prioritisation criterion, particularly in areas with weak surveillance. Model-based seroprevalence estimation, integrating multiple data sources, offers a more consistent basis for identifying high-priority districts for vaccine introduction, and is less susceptible to surveillance bias than reported incidence.

Background Post-infection conditions (PICs), such as Long Covid, are associated with heterogeneous, fluctuating symptoms that profoundly affect daily functioning. Despite moderate-certainty evidence from the NIHR-funded LISTEN trial (COV-LT2-0009) that personalised self management support improves outcomes and may reduce societal and economic impacts of Long Covid, many people living with PICs still receive condition-specific services, generic advice, or stand-alone digital tools that do not address their complex needs. Aim To map care approaches in general practice and synthesise UK evidence for PIC management. Design and setting Scoping review and online survey. Method A two-phase study was conducted: (1) a scoping review of UK evidence on PIC management in general practice; and (2) a supplementary online survey of practitioners working in UK general practice to provide contextual insights. Results The scoping review identified 32 studies focused on Long Covid. One study included a comparator group (ME/CFS). Study populations were predominantly white ethnicity and female. Evidence for non-Covid PICs in UK general practice was largely absent. The supplementary survey (n=46) provided preliminary practice-level insights. Healthcare practitioners reported varied PIC presentations, diagnostic uncertainty, limited referral pathways, inequitable access, and low confidence in managing PICs. Conclusion Evidence informing PIC management in UK general practice remains predominantly Long Covid-focused and may not reflect the range of PICs encountered in practice. While survey findings are preliminary and require confirmation in larger samples, they highlight uncertainty around PIC management. Further research is needed to evaluate whether existing Long Covid pathways should be expanded or complemented by broader PIC models. Keywords general practice; Long Covid; self-management; post-viral syndromes

Objective: There is a bidirectional relationship between emotional distress and pain. However, this relationship is understudied in people with HIV in low-resource settings. This study sought to describe the temporal relationship between emotional distress and pain in people with HIV. Design: Longitudinal observational study. Methods: Participants with virally suppressed HIV, reporting either no pain or persistent pain at baseline, provided weekly remote ratings of distress, worst pain, and average pain using 0-10 visual analogue scales. Within-individual fluctuations in distress and pain were visualised over time. Group-level correlations were determined using Spearman's correlation tests. Cumulative link mixed models assessed whether distress and pain each predicted the other in the following week. Results: 72 participants provided responses over 49 weeks. The participants had a median (IQR) age of 43 (37-51) years, 63% (n=45) were unemployed and most were females (n=51;71%). Distress and pain fluctuated concurrently within individuals: distress was positively correlated with worst pain ({rho}=0.66, 95% CI= 0.60-0.72, p<0.001) and average pain ({rho}=0.70, 95% CI=0.64-0.75, p<0.001) intensity within the same week. Worst pain (OR=1.42, 95% CI=1.17-1.71, p<0.001) and average pain (OR=1.43, 95% CI=1.20-1.71, p<0.001) intensity both predicted distress in the next week. Distress predicted worst pain intensity (OR=1.25, 95% CI=1.07-1.46, p=0.023) but not average pain intensity (OR=1.19, 95% CI=1.01-1.40, p=0.152) in the next week. Conclusions: The temporal relationship between distress and worst pain intensity was bidirectional, whereas distress did not temporally predict average pain intensity. Both pain and emotional distress should receive attention from HIV research and clinical care in low-resource settings.