Alzheimer's Research & Therapy

Background: Quantitative genome wide association studies (GWAS) primarily rely on additive linear models that compare average phenotypic differences between genotype groups. While effective for detecting common variants of moderate effect in large sample sizes, such approaches inherently reduce high resolution phenotypic data to summary statistics (group averages), potentially limiting the detection of subtle genotype phenotype relationships. Genomic Informational Field Theory (GIFT) is a recently developed methodology that preserves the fine-grained informational structure of quantitative traits by analysing ranked phenotypic configurations rather than relying solely on mean differences. Methods: We applied GIFT to genetic and neuropathological data from the Brains for Dementia Research cohort, a well characterised dataset of 563 individuals, and compared its performance with conventional GWAS. Principal component analysis (PCA) derived matrix was used to derive independent quantitative traits linked to from Alzheimer disease (AD) neuropathology measures (CERAD, Thal, Braak staging), with and without inclusion of age at death. Principal component analyses were performed using GWAS and GIFT frameworks on the same filtered genotype dataset. Results: Both GWAS and GIFT identified genome-wide significant associations (pvalue<0.000001) within the APOE locus (NECTIN2/TOMM40/APOE/APOC1), demonstrating concordance with established AD genetic variants. However, GIFT detected additional significant 19 SNPs beyond those identified by GWAS. Variants associated with AD pathology implicated genes involved in amyloid processing, neuronal apoptosis, synaptic function, neuroinflammation, and metabolic regulation. Notably, GIFT identified 29 loci associated with age at death related variation that were not detected by GWAS, highlighting genes linked to lipophagy, mitochondrial quality control, sphingolipid metabolism, frailty, and aging-related processes. Conclusions: GIFT recapitulates canonical GWAS findings while uncovering additional biologically relevant associations. By preserving the fine-grained structure of phenotypic data distributions and detecting non random genotype segregation across ranked trait values, GIFT enables the identification of associations that remained undetected by traditional average based GWAS approaches. These results demonstrate that rethinking analytical representation, rather than solely increasing sample size, can expand discovery potential of genetic association studies, offering a transparent and complementary framework for quantitative genomics in deeply phenotyped datasets.

Introduction: Neurodegenerative diseases (NDDs) including Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and non-AD dementias share chronic neuroinflammatory mechanisms that contribute to neuronal injury and disease progression. While anti-inflammatory therapies (AITs) are associated with reduced neurodegenerative disease risk, knowledge regarding the impact of biological sex and treatment duration across multiple NDDs remains limited. Methods: We conducted a retrospective cohort analysis using a large propensity-score-matched population (n = 190,308; 95,154 treated vs 95,154 untreated) to evaluate associations between long-term AIT exposure and incidence of major NDDs. Disease-specific and combined outcomes were assessed across drug classes (NSAIDs, corticosteroids, immunomodulators), sex, age, and therapy duration. Results: AIT exposure was associated with a significantly lower risk of developing any NDD (RR = 0.47, 95% CI 0.43-0.48, p < .0001) and was equally effective in both sexes. Risk reduction was observed for each individual disease: AD (RR = 0.40), non-AD dementia (RR = 0.51), PD (RR = 0.43), MS (RR = 0.25), and ALS (RR = 0.48). Among drug classes, immunomodulators conferred the largest reduction (RR = 0.19), followed by corticosteroids (RR = 0.41) and NSAIDs (RR = 0.42). Duration analyses revealed a graded benefit, with RR declining from 0.94 (<1 year) to 0.25 (>6 years). Risk reduction was strongest in older participants (75-79 years). Discussion: Chronic use of anti-inflammatory or immunomodulatory therapies was associated with substantially reduced incidence of multiple neurodegenerative diseases in both sexes. The strongest effects were observed with immunomodulator use and prolonged therapy duration, suggesting that sustained modulation of systemic inflammation confers broad neuroprotective effects in both sexes. These findings highlight the potential of targeting immune-inflammatory pathways for neurodegenerative disease prevention and can inform prospective mechanistic and interventional studies.

Drug-induced liver injury (DILI) is an acute inflammatory liver disease caused not only by prescription and over-the-counter medications but also by health foods and dietary supplements. Typically, DILI patients recover once the causative substance is identified and discontinued. In contrast, autoimmune hepatitis (AIH) results from the immune-mediated destruction of hepatocytes due to a breakdown of self-tolerance mechanisms. Patients presenting with acute-onset AIH often lack characteristic clinical features, such as autoantibodies, and require prompt steroid treatment to prevent progression to liver failure. Liver biopsy currently remains the gold standard to differentiate acute DILI from AIH; however, general pathologists face significant diagnostic challenges due to overlapping histopathological features. This study integrates pathology expertise with deep learning-based artificial intelligence (AI) to differentiate DILI from AIH using histopathological images. Our AI model demonstrates promising classification accuracy (Accuracy 74%, AUC 0.81). This paper presents a detailed pathological analysis alongside AI methods, discusses the current model performance and limitations, and proposes directions for future improvements.

Gait variability is a critical functional indicator of dynamic balance and neurocognitive decline in health. Its translation into clinical practice is, however, challenged by a lack of age-related normative trajectories and reference values under real-world ecological settings. Furthermore, the conventional metrics used to estimate gait variability (Coefficient of Variation, CV; Standard Deviation, SD) have a fundamental methodological flaw: the inherent sensitivity of conventional metrics to the statistical outliers and environmental noise in real-world walking. In this study, we mitigate this factor by applying a robust statistical framework to quantify gait variability. Analysing a large-scale cohort of community-dwelling older adults (n=2,193), we first demonstrate that free-living gait data follows a heavy-tailed distribution, necessitating the use of robust estimators like the Robust Coefficient of Variation (RCV-MAD) and Median Absolute Deviation (MAD). Leveraging these metrics, we established the normative trajectory and reference values of real-world gait variability across the ageing lifespan, revealing a distinct, age-dependent increase in spatio-temporal fluctuations, indicating a decline in rhythmicity and steadiness with age. We further demonstrated the clinical utility of these robust metrics: RCV-MAD consistently yielded larger effect sizes than conventional CV in discriminating between fallers and non-fallers across all gait parameters. Furthermore, we illustrate the potential of long-term unsupervised monitoring to capture intrinsic variability during real-world walking. Validated for consistency and reliability, this robust framework provides the necessary ecological validity to transform gait variability into a standardised, rapid clinical metric for assessing functional decline at an early timepoint.

Importance: Dementia is common in Parkinson's disease (PD), causing greater disability than other symptoms, but varies in timing. Although visual deficits are linked with PD dementia, how these interact with genetic factors to predict PD dementia has not been characterised. Objective: To investigate whether visual deficits and genetic factors predict PD dementia. Design: Large prospective longitudinal case-control study, mean follow-up 32.7 (SD=12.3) months. Setting: Cases were recruited between 2017-2020 at 35 UK PD clinics. Participants: People with PD without dementia at baseline were included. Main outcomes and measures: Visual function was measured using a web-based platform. The main outcome measure was global cognition, measured as the Montreal Cognitive Assessment (MoCA). Blood samples were collected for genetics. Results: 450 patients with PD were included. Mean age of PD patients was 71.7 (SD=7.8), 68% male. Mean baseline MoCA was 27.7 (SD=1.7). 263 patients with PD were classed as poor-vision based on baseline visual tests: mean age 74.4 (SD=6.8) compared to 69.7 (SD=7.5) with good-vision. Poor-vision PD patients had higher rates of progression to mild cognitive impairment (PD-MCI) (HR=2.34, CI=1.58-3.48, pFDR=0.00062, age- and sex-corrected). The combination of genetic factors together with vision influenced outcomes. In good-vision PD patients, high-risk GBA1 gene variants were linked with greater progression to PD-MCI (HR=4.61, CI=1.73-12.28, pFDR=0.0068). Polygenic Risk Score (PRS) for both PD and Alzheimer's disease (AD) also modified cognitive survival when combined with vision status. High PD-PRS was associated with greater progression to PD-MCI in good-vision patients (HR=2.66, CI=1.21-5.81, pFDR=0.0381); and high AD-PRS with greater progression to PD-MCI in poor-vision PD patients (HR=1.91, CI=1.10-3.32, pFDR=0.04999). Combining high PD- and AD-PRS, compared to low PD- and AD-PRS in good-vision PD showed even higher progression to PD-MCI (HR=6.14, CI=1.36-27.83, pFDR=0.046). Simulations showed that adding visual and genetic stratification reduced sample size from n=705 to n=160 for clinical trials. Conclusions and relevance: Poor vision in PD predicts progression to PD-MCI and dementia. This combines with the effects of genetic factors including GBA risk variants and PD- and AD-PRS. These findings can enable enrichment of clinical trials for patients at higher risk of PD dementia, for more efficient trial design for interventions to slow progression.

We propose a lesion-centric phenotype learning pipeline for interpretable breast ultrasound (BUS). Predicted lesion masks are used for mask-weighted pooling of segmentation-encoder latents, producing compact embeddings that suppress background influence; a lightweight calibration step improves cross-dataset consistency. We cluster embeddings to discover latent phenotypes and relate phenotype structure to morphology descriptors (compactness, boundary sharpness). On BUSI and BUS-UCLM with external testing on BUS-BRA, lesion-centric pooling and calibration improve separability and enable strong malignancy probing (AUC 0.982), outperforming radiomics and a standard CNN baseline. A simple rule-gated generator further improves BI-RADS-style descriptor consistency on difficult cases.

Protocadherin-12 (PCDH12), a cell-adhesion protein belonging to the non-clustered protocadherin family, plays a crucial role in the establishment and regulation of neuronal connections and communication. Bi-allelic loss-of-function (LoF) variants in the PCDH12 gene have been associated with several neurodevelopmental disorders (NDDs) such as diencephalic-mesencephalic junction dysplasia (DMJD) syndrome, cerebral palsy, and cerebellar ataxia, often accompanied by ocular abnormalities. However, genotypes exhibit variable expressivity. Affected individuals sharing the same PCDH12 variant presenting differing phenotypic severities have posed major challenges towards identification of the underlying pathogenic mechanisms. Here, we report three affected individuals from two families, each harbouring non-truncating pathogenic missense variants in PCDH12. The patients are compound heterozygous, with each individual carrying one extracellular [c.1742T>G (p.Val581Gly) and c.1861_2del/insCA (p.Ile621His)] and one intracellular variant [c.3370C>T (p.Arg1124Cys) and c.3445G>A (p.Asp1149Asn] on each allele. The children present with a range of phenotypes similar to those associated with LoF variants. One child exhibited microcephaly and seizures, while the two siblings displayed developmental delays and severe behavioral disorders. All three children experienced some degree of visual impairment. The missense variants provided new insights into the neurodevelopmental consequences of compromised PCDH12 function by distinguishing the specific consequences associated with dysfunction in the extracellular versus intracellular domains of PCDH12. All identified missense variants are predicted to be deleterious and destabilizing. The expression of PCDH12 in HEK293T and HeLa cells demonstrated that PCDH12 is expressed effectively, regardless of the presence of missense variants. However, the extracellular variants p.Val581Gly and p.Ile621His compromised the stability of PCDH12's homophilic adhesion. Additionally, we found evidence of an interaction between PCDH12 and the extracellular domain of the epilepsy-associated PCDH19 protein. PCDH12 extracellular missense variants also negatively impact this interaction. Our study provides evidence that PCDH12 mediates both homophilic and heterophilic interactions. Our findings also highlight the importance of stable PCDH12-mediated adhesion, emphasizing the need to further study the functional consequences of PCDH12 missense variants on brain and visual system development.

Abstract Background: Conventional MRI cannot reliably distinguish radiation necrosis (RN) from recurrent metastasis after cranial radiotherapy, as both can show similar enhancement despite different biology. We tested whether these entities are mechanically non-equivalent in vivo and separable by MRE-derived viscoelastic metrics and perilesional interface-instability features. Methods: In a prospective, histopathology-anchored cohort, 11 post-radiotherapy enhancing lesions were classified as RN (n=3) or recurrent/progressive tumor (n=8). MRE was acquired at 3.0 T with single-frequency 60-Hz excitation to derive storage modulus (G'), loss modulus (G''), and complex shear modulus magnitude (|G*|). Co-primary endpoints were median tumor G' and |G*|, each tested one-sided (RN > tumor) with Holm correction across the two co-primary tests. Median tumor G'' was tested two-sided. A prespecified secondary 6-endpoint family (absolute and tumor/NAWM-normalized G', G'', and |G*|) was analyzed with Benjamini-Hochberg FDR control. Exploratory instability mapping in a 0- 6 mm peritumoral shell generated interface-topology metrics, including convexity. Results: Absolute tumor-core medians were higher in RN than tumor for |G*| (1.79 vs 1.32 kPa; Cliff's {delta} = 0.67; q = 0.10), G' (1.62 vs 1.09 kPa; {delta} = 0.50; q = 0.14), and G'' (0.81 vs 0.46 kPa; {delta} = 0.75; q = 0.10). NAWM normalization improved separation: tumor/NAWM |G*| (2.26 vs 1.41; {delta} = 0.92; q = 0.04) and tumor/NAWM G'' (2.67 vs 0.87; {delta} = 1.00; q = 0.04) were FDR-significant. Convexity also differentiated RN from tumor (0.49 vs 0.36; {delta} = 1.00; MWU p = 0.01). Conclusions: Tumor/NAWM G'', tumor/NAWM |G*|, convexity, and tumor G'' emerged as the strongest candidate features, indicating that RN is mechanically harder and more dissipative than recurrent metastasis. Signal strength was high (Cliff's {delta} up to 1.00) but should be interpreted cautiously given sample size. Exploratory analyses further suggest that instability mapping captures biologically relevant interface behavior. These findings support a mechanics-based RN-versus-recurrence framework and justify prespecified, preregistered external validation.

Background and Purpose: Magnetic resonance imaging (MRI) for radiation therapy treatment planning is currently being used in many anatomical sites to better visualize soft tissue landmarks, a technique known as an MRI simulation. A core component of modern MRI simulation configurations are the use of external laser positioning systems (ELPS) to help set up the patient. Though necessary for accurate and reproducible patient setup, the ELPS, if left on during imaging, may interfere negatively with image quality due to leaking electronic noise, of which MRI is sensitive to. It is currently unknown whether this leakage of electronic noise may further affect quantitative values derived from clinically employed relaxometric, diffusion, and fat fraction sequences. Therefore, in this study, we aim to characterize the impact of MRI simulation lasers on general image quality and quantitative imaging accuracy. Materials and Methods: First, a cine acquisition was used to visualize the real-time changes in image signal-to-noise ratio (SNR) from when the ELPS was deactivated to activated. To validate this effect quantitatively, the SNR was measured using the American College of Radiology (ACR) recommended protocol in a homogeneous phantom with the integrated body, 18-channel UltraFlex small, 18-channel UltraFlex large, 32-channel spine, and 16-channel shoulder coils. Next, a geometric distortion algorithm was tested in two vendor-provided phantoms while using the integrated body coil and the ACR Large Phantom protocol was tested. Finally, a series of quantitative MRI scans were performed using a CaliberMRI Model 137 Mini Hybrid phantom to validate quantitative T1, T2, and ADC while a Calimetrix PDFF-R2* phantom was used for quantitative PDFF and R2*. All scans were performed with both the ELPS both deactivated and activated. Results: Visible electronic noise artifacts were seen when using the integrated body coil when the ELPS was activated on the cine acquisition which led to a four-fold decrease in SNR using the ACR protocol. This SNR drop was not seen when using the remaining tested coils. The automatic fiducial detection algorithm was affected negatively by ELPS activation leading to misidentification when identified perfectly with the ELPS deactivated. Degradation in image intensity uniformity, percent signal ghosting, and low contrast object detectability was seen during ACR Large Phantom testing using the 20-channel Head/Neck coil. Concordance across quantitative MRI values was similar when the ELPS was both deactivated and activated while a consistent increase in standard deviation inside the ADC vials was seen when the ELPS was activated. Discussion: The extra noise induced from the activation of the ELPS during imaging should be avoided due to its potential to unnecessarily increase image noise. This is particularly true when conducting mandatory quality assurance testing for image quality and geometric distortion which utilize the integrated body coil which is most susceptible to ELPS-induced noise. Clear clinical guidelines should be implemented to make this issue known to the MRI technologists, physicists, and other relevant staff using an MRI with a supplementary ELPS for patient alignment.

Wearable devices present transformative opportunities for personalized healthcare through continuous monitoring of digital biomarkers; however, individual variations in device wear time could mask or otherwise impact signal identification. Despite the widespread adoption of wearable devices in research, no comprehensive framework exists for understanding how wear time varies across populations or for addressing wear time-related biases in analysis. Using Fitbit data from 11,901 participants in the All of Us Research Program, we conducted the first large-scale systematic assessment of wearable device wear time across demographics, social determinants of health, lifestyle factors, mental health symptoms, and disease. Our findings revealed that wear time was higher among males and increased with age, income, and education, but decreased with depressive, anxiety, and anhedonia symptoms, with reductions more pronounced following clinical diagnoses compared to symptom-based classifications. Individuals with chronic conditions displayed differential levels of wear time compared to healthy controls. Critically, we demonstrate that the widely used [&ge;]10-hour daily compliance threshold, while appropriate for some research contexts, can disproportionately exclude days of data from disease populations: among individuals with major depressive disorder, 74.4% of data days were excluded compared to 20.9% for controls. We propose a flexible methodological framework including standard compliance thresholds, wear time covariate adjustment, metric normalization, propensity score matching, and adaptive thresholds that can be applied individually or in combination to optimize wearable data retention across diverse research contexts. These findings establish wear time as a critical methodological consideration for wearable device research and provide guidance for advancing equitable and rigorous digital health analytics.

Multiple sclerosis (MS) is a chronic neurodegenerative disease characterised by progressive neurological disability and heterogeneous symptom trajectories. Current clinical monitoring methods, including magnetic resonance imaging (MRI) and episodic neurological assessments, provide limited insight into subtle disease progression and functional changes. Digital health technologies integrating multimodal biosignals and behavioural assessments may enable continuous monitoring and personalised rehabilitation in patients with MS. This study aims to evaluate the clinical utility of the BodyMirror Clinical MS platform, a multimodal SaMD that combines wearable biosensors, neuroscience-based games, and machine learning to remotely monitor disease progression and deliver personalised neurorehabilitation for individuals with multiple sclerosis. This study is a prospective, randomised, double-blind, controlled, multisite clinical trial enrolling 400 participants (300 individuals with multiple sclerosis and 100 healthy controls). MS participants will be randomly assigned (1:1) to either an adaptive neurorehabilitation intervention group or a control group receiving non therapeutic digital activities matched for engagement and exposure. Participants will perform three 30-minute sessions per week over 24 months using the BodyMirror platform. The system integrates multiple biosignals, including electroencephalography (EEG), electromyography (EMG), inertial measurement unit (IMU) motion data, speech analysis, and behavioural performance metrics to generate digital biomarkers of neurological function. The primary endpoint is a change in Expanded Disability Status Scale (EDSS) score from baseline to 24 months. Secondary outcomes include changes in Multiple Sclerosis Functional Composite (MSFC), MRI brain volume, cognitive performance, patient-reported outcomes, adherence to digital rehabilitation, and health economic outcomes.

Background Whole-genome sequencing (WGS) has improved the diagnosis of rare genetic disorders, yet interpretation of non-coding variants that affect splicing remains challenging. In silico predictions alone are insufficient, and short-read RNA sequencing may fail to capture complex or low-abundance splicing events. Targeted amplicon-based long-read RNA sequencing (Amp-LRS) offers a cost-effective approach for functional validation of candidate splice-altering variants. Methods We applied Amp-LRS to five patients with neurological disorders (central nervous system, peripheral nervous system, or muscle) harbouring candidate non-coding variants predicted to alter splicing. RNA was extracted from fibroblasts or peripheral blood, and full-length transcript amplicons were sequenced using Oxford Nanopore Technologies. Nonsense-mediated decay (NMD) inhibition was performed on fibroblast cultures using cycloheximide. Results Amp-LRS validated all five candidate variants, including intronic and UTR variants in POLR3A, OPA1, PYROXD1, GDAP1, and SPG11. Aberrant splicing events included exon skipping, intron retention, cryptic splice site activation, and pseudoexon inclusion, often resulting in frameshifts and premature termination codons. For POLR3A and OPA1, multiple abnormal isoforms arose from single variants, highlighting the complexity of splicing disruption. Some pathogenic effects were detectable only in a minority of reads and variably enriched by NMD inhibition, consistent with being hypomorphic. The approach was successfully applied using accessible tissues and enabled multiplexed sequencing at low per-sample cost. Conclusions Amp-LRS is a sensitive, versatile, and cost-effective method for functional assessment of non-coding splice-altering variants identified by WGS. By enabling full-length transcript analysis from accessible tissues, this approach improves interpretation of variants of uncertain significance and could enhance molecular diagnosis in rare neurological diseases.

Background: Platform trials are an efficient trial design which enable testing of multiple interventions simultaneously. They could advance knowledge of treatments for intracerebral haemorrhage (ICH). We aimed to investigate the views of clinicians involved in stroke research on recruitment to a future platform trial for ICH. Methods: Between April and July 2025, we conducted a UK-wide online survey of clinicians actively involved in stroke research using convenience sampling through professional organisations. Participants considered factors related to the consent process and research environment and could provide optional free text responses about additional barriers or facilitators to recruitment. We used descriptive statistics for quantitative data and content analysis for qualitative data. Results: Among 73 respondents, 46 (63%) were female, 36 (50%) were stroke physicians, 24 (34%) nurses, 6 (8%) allied health professionals, and 7 (10%) were in other roles. 36 (49%) had >20 years of clinical experience, 45 (61%) reported spending <10% of their role in research. 66 (91%) thought that a platform trial would be a good option for testing interventions for patients with stroke due to ICH. Across 11 modifiable factors, clinicians most frequently rated perceived importance of the research question as a facilitator of recruitment (94%), while clinician preference for specific treatments was most frequently rated as a barrier (48%). Two themes emerged from free text responses: study design and infrastructure. Regarding study design respondents perceived consent procedures (n=9), study materials (n=8), study procedures (n=8), eligibility assessment (n=6), the research question (n=3) and randomization (n=3) as important for a future platform trial. Regarding infrastructure, emergent factors were staffing (n=17), local research culture and capacity (n=9), research governance and delivery (n=6), and training (n=6). Conclusion: The overwhelming majority of respondents from the UK clinical stroke community supported a platform trial for ICH, although the influence of survey responder bias is unknown.

With significant population fractions in many societies who refuse vaccines, it is important to reconsider how vaccination is incorporated into compartmental epidemiology models. It is still most common to apply the vaccination rate to the entire class of susceptibles, rather than to use the more realistic assumption that the vaccination rate function should depend only on the population of susceptibles who are willing and able to receive a vaccination. This study uses a simple generic disease model to address two questions: (1) How much error is introduced in key model outcomes by neglecting vaccine unwillingness?, and (2) Can the error be reduced by incorporating vaccine unwillingness into the vaccination rate constant rather than the rate diagram? The answers depend greatly on the time scale of interest. For the endemic time scale, where longterm behavior is studied with equilibrium point analysis, the error in neglecting unwillingess is large and cannot be improved upon by decreasing the vaccination rate constant. For the epidemic time scale, where the first big epidemic wave is studied with numerical simulations, the error can still be significant, particularly for diseases that are relatively less infectious and vaccination programs that are relatively slow.

A critical challenge in endocrine neurosurgery is intraoperative discrimination between normal pituitary tissue and pituitary neuroendocrine tumors (PitNETs). Suggesting the universal persistence of near-infrared autofluorescence (NIRAF) in endocrine organs and inspired by routine clinical use of NIRAF for parathyroid gland identification, we discovered that pituitary NIRAF can be employed for label-free transsphenoidal surgery guidance. Ex vivo confocal spectral imaging of 33 specimens identified secretory granules as the dominant long-wavelength fluorescence source and showed that normal pituitary had higher granule content than PitNETs. For the first time, we made use of the pituitary NIRAF during surgery and assessed its performance for pituitary/adenoma separation in vivo for 27 surgeries and showed near-perfect separability between pituitary and non-pituitary measurement sites with ROC-AUC of 0.98. The obtained results clearly demonstrate that the suggested method, based on the solid microscopic background, has the potential for clinical translation and paves the way for enhanced gland preservation during resection.

Background and objectives STXBP1-related disorder (STXBP1-RD), caused by pathogenic variants in the STXBP1 gene, is a rare neurodevelopmental condition, characterized by early-onset seizures, developmental delay, intellectual disability (ID), and prominent motor dysfunction. Despite the high prevalence of motor symptoms, systematic gait characterization remains limited. We therefore aimed to quantitively assess gait in individuals with STXBP1-RD. Methods In this cross-sectional study, we included ambulatory patients aged 6 years or older with genetically confirmed STXBP1-RD. Instrumented 3D Gait Analysis (i3DGA) was performed to objectively quantify gait. Functional mobility was assessed with the Functional mobility scale (FMS) and Mobility Questionnaire 28 (MobQues28). Caregiver health-related quality of life was evaluated using the PedsQL-Family Impact Module (PedsQL-FIM). We explored associations between gait, functional mobility, STXBP1-variant type and clinical features (ID, age at seizure onset, seizure frequency, age at onset of independent walking). Correspondence between i3DGA and the Edinburgh Visual Gait Score (EVGS), an observational gait assessment, was investigated. Results Eighteen participants were included. Compared to typically developing peers, individuals with STXBP1-RD had significantly reduced walking speed, step and stride length. Gait patterns were highly variable, with the most frequent pattern being an externally rotated foot progression angle (FPA), present in 11/18 participants. At home, 93.75% of the participants (16/18) walked independently, yet community mobility was more variable: 11/16 (68.75%) walked independently, 2/16 (12.50%) with aid and 3/16 (18.75%) used a wheelchair, indicating increasing limitations with distance and environmental complexity. Earlier acquisition of independent walking strongly predicted later unassisted ambulation at community level (p<0.001). Median MobQues28 score was 57.14% and median PedsQL-FIM score was 60.42%, indicating a moderate level of mobility limitations and reduced health-related quality of life of caregivers. EVGS was highly positive correlated with i3DGA (p= 0.001). Discussion Quantitative gait analysis in individuals with STXBP1-RD demonstrates heterogenous kinematic deviations, with an externally rotated FPA emerging as the most common pattern. Age at independent walking was a clinically relevant predictor of later functional mobility. EVGS showed strong correspondence with i3DGA and may offer a more practical, semi-quantitative assessment for broader use. These findings inform clinical decision-making and guide the selection of scalable outcome measures for natural history studies and interventional trials.

Background Persistent inequities in immunisation coverage, particularly among zero-dose and under-immunised children, continue to challenge Pakistan's Expanded Programme on Immunization. Weak feedback loop, inconsistent data quality, and limited real-time monitoring impede effective decision-making. This Implementation Research was conducted under the MAINSTREAM Initiative funded by Alliance for Health Policy and Systems Research (AHPSR) and supported by the Aga Khan Community Health Services Department and National Institutes of Health Pakistan to design, implement, and evaluate a digital monitoring and action planning tool to strengthen data-driven decision-making within routine immunisation systems. Methodology/Principal Findings A co-creation approach was employed to design a digital monitoring solution through inclusive consultations, key informant interviews, and focus group discussions with EPI Punjab at provincial and district levels. The solution included a customised mobile application for data collection and a Power BI visualisation dashboard to map low-coverage areas, identify drivers of dropouts and zero-dose children, and capture caregivers' information sources to inform targeted communication. The intervention was piloted in 60 households across six clusters of a Union Council of District Lahore. Advanced analytics identified reasons for non-vaccination and missed opportunities, generating tailored recommendations and practical plans for program managers. The analysis assessed acceptability, adoption, fidelity, and perceived scalability through field observations, system use, and stakeholder feedback. The co-developed digital tool enhanced visibility of coverage gaps through UC-level mapping, real-time dashboards, and structured action planning. Pilot testing in Lahore showed strong acceptability, ease of use, fidelity, and adaptability among managers, supervisors, and vaccinators. Scalability and sustainability potential were demonstrated, though barriers included leadership turnover, system fragmentation, workload pressures, and resource constraints. Conclusion The tool demonstrated feasibility to strengthen immunisation equity, accountability, and responsiveness. Co-creation with stakeholders enhanced ownership, operational relevance, and adoption, while complementing existing platforms. Sustainability will depend on effective integration, local ownership, capacity building, and accountability, while scalability requires interoperability, resource commitment, policy support, and alignment with existing workflows.

Understanding host susceptibility to Mycobacterium tuberculosis (Mtb) is critical for the development of new vaccines. Certain individuals "resist" becoming infected with Mtb despite intensive exposure; however, it is unknown whether there is a genetic basis for "resistance" to Mtb infection across populations. Here we conducted a genome-wide association study (GWAS) of resistance to Mtb infection by carefully characterizing exposure to TB patients among 4,058 close contacts in India, Brazil, and South Africa. 476 (12%) "resisters" remained free of Mtb infection despite substantial exposure to highly infectious TB patients. GWAS identified a novel chromosome 13 locus (rs1295104126) associated with resistance across the multi-ancestry meta-analysis. Comparing Mtb-infection to all uninfected contacts, irrespective of exposure, yielded a different locus on chromosome 6 (rs28752534), near the HLA-II region. These findings demonstrate a common genetic basis for resistance to Mtb infection across multi-ancestral cohorts with potential to elucidate novel mechanisms of protection from Mtb infection.

Background: Quadriceps weakness may reduce sagittal plane shock absorption during landing, shifting load toward the frontal plane and increasing knee abduction moment (KAM), a biomechanical risk factor for anterior cruciate ligament (ACL) injuries. Purpose: The purpose of this study was to evaluate the association between isokinetic quadriceps strength and peak KAM during drop vertical jump landing in adolescent athletes. Study Design: Secondary analysis of previously collected data. Methods: Healthy adolescent athletes completed quadriceps strength testing using an isokinetic dynamometer and a biomechanical assessment during a drop vertical jump task. Quadriceps strength was quantified as peak concentric torque and the peak external KAM was calculated during the landing phase on the dominant limb. Both strength and KAM were normalized to body mass. Linear regression was used to examine the association between normalized quadriceps strength and peak external KAM on the dominant limb. Results: The association between quadriceps strength and peak normalized KAM on the dominant limb was not statistically significant ({beta} = -0.053 (95% CI [-0.137 to 0.030]), F(1,119) = 1.62, R2 = 0.013, p = 0.206). Quadriceps strength explained only 1.3% of the variance in peak KAM, indicating a negligible association between these variables in this cohort. Discussion: Quadriceps strength was not associated with peak normalized KAM during landing, suggesting that frontal-plane knee loading during a drop vertical jump is not meaningfully explained by maximal concentric quadriceps strength alone. KAM appears to be driven more by multi-joint movement strategy and neuromuscular coordination than by the capacity of a single muscle group.

Objectives: Compare Anterior Cruciate Ligament (ACL) Return to Sport after Injury (ACL-RSI) scores over time following ACL reconstruction (ACLR) between male and female patients aged 15 to 25 years with primary ACL injuries and ACL reinjuries. Design: Retrospective cohort design. Setting: Sports physical therapy clinics. Participants: 332 patients aged 15-25 years who underwent ACLR following either primary ACL injury or ACL reinjury, either contralateral or ipsilateral graft reinjury, and had at least one observation of the ACL-RSI. Main Outcome Measures: ACL-RSI score. Results: ACL-RSI scores significantly increased over time post- ACLR (p < .001), males reported significantly higher scores compared to females (p < .001), and patients with contralateral ACL reinjury demonstrated higher scores than those with ipsilateral ACL graft reinjury (p = .006), though there was no difference in scores between patients with primary ACL injury and ACL reinjury. A significant interaction effect of sex and injury status was also observed (p = .009), generally demonstrating that females had lower psychological readiness compared to males across injury statuses. Conclusions: ACL-RSI following ACLR varies based on biological sex and time post-ACLR, though ACL reinjury, independent of the reinjured leg, does not appear to effect scores compared to primary ACL injury.