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Background and Aims: Cholangiocarcinoma (CCA) is a rare but aggressive malignancy with poorly understood genetic susceptibility. To date, genome-wide association studies (GWAS) investigating germline variants associated with CCA risk remain limited. We aimed to identify genetic risk loci for CCA and its clinical subtypes through comprehensive GWAS and post-GWAS analyses. Approach and Results: We conducted a GWAS of 2366 CCA cases and 11,750 controls of European ancestry. Genome-wide significant loci ( p <5×10 −8 ) were identified and further examined through fine-mapping, functional annotation, and HLA imputation. Subgroup analyses were conducted by CCA subtypes and primary sclerosing cholangitis (PSC) status. Cross-trait linkage disequilibrium score regression and Mendelian randomization were employed to investigate the shared genetic architecture and potential causal relationships with a diverse range of traits. We identified 1 new genome-wide significant variant, rs535777 (OR=1.44), near HLA-DRB1/DQA1 associated with CCA, and 2 variants associated with extrahepatic CCA: rs116224263 (OR=0.17) in LINC02506 at 4p15.1 and rs6914950 (OR=1.63) near HLA-DRB1/DQB1 . Stratified analyses revealed rs2395184 (OR=3.51) near HLA-DRA/DRB5 associated with PSC-related CCA, and rs142674434 (OR=2.98) in THSD7A at 7p21.3 associated with non-PSC-related CCA. HLA imputation uncovered new amino acid residues associated with disease risk. Cross-trait analyses identified shared genetic signals between CCA and anthropometric, lipidemic, lifestyle, and medical traits. Mendelian randomization supported putative causal associations for 12 traits with CCA or its subtypes. Conclusions: Our large-scale GWAS highlights new genetic variants and HLA-linked mechanisms underlying CCA susceptibility. Integrating multi-step post-GWAS approaches enhances understanding of CCA pathogenesis and may facilitate the development of risk biomarkers for early detection and precision prevention strategies.

INTRODUCTION Recent work has identified unique cognitive profiles for early‐onset Alzheimer's disease (EOAD) relative to late‐onset Alzheimer's disease (LOAD), however, examination has been limited in determining whether the association between age and cognitive severity at presentation also differs across conditions. METHODS A series of linear spline regression models was conducted across baseline cognitive data from 325 EOAD and 314 LOAD participants, after accounting for education, sex, and apolipoprotein ε4 status. RESULTS Significant differences existed in the relationship between baseline age and cognitive performance between EOAD and LOAD samples for Processing Speed/Attention, Executive Functioning, and Episodic Immediate Memory. Younger participants from both EOAD and LOAD groups performed disproportionately worse on non‐amnestic cognitive domains, with this occurring to a greater extent in EOAD than LOAD. DISCUSSION In the age of disease‐modifying treatments, results highlight the importance of assessing for cognitive declines in individuals starting much earlier than age 65. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants each displayed cognitive impairments relative to same‐aged peers across most domains. Both groups displayed positive relationships between impairment among non‐amnestic cognitive domains and baseline age. This relationship displayed a significantly greater effect in EOAD than LOAD, with domains of Processing Speed/Attention and Executive Functioning skills being the most pronounced. Of those participants developing AD, age displayed a disproportionate impact on their symptom onset.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Background: Cardiac CT acquired during the acute stroke imaging protocol is an emerging diagnostic modality to detect cardiac thrombi. We aimed to determine its diagnostic yield in a large, international, multicenter study. Methods: We performed an individual patient data meta-analysis by pooling prospective and retrospective observational data of patients with acute ischemic stroke (AIS) who underwent cardiac CT (ECG-gated or non-ECG-gated) as part of the acute imaging protocol between May 2018 and June 2024. We excluded patients with a TIA or stroke mimic. The primary outcome was the proportion of patients with a cardiac thrombus detected on cardiac CT. Secondary outcomes were additional scan time and radiation dose, comparison of yield with echocardiography, and 90-day mortality and recurrent ischemic stroke rates. Results: We included 3940 patients from 4 hospitals (median age 74 [IQR 63-82], 58.0% male, median NIHSS 6 [IQR 3-12], median time onset to hospital arrival 100 minutes [IQR 62-185]). Atrial fibrillation at baseline was present in 23.1% patients, and 29.6% had a large vessel occlusion. Cardiac CT was non-diagnostic in 17 (0.4%) patients. In total, cardiac CT detected 254 cardiac thrombi in 243/3923 (6.2%) patients. Thrombi were located in the left atrial appendage (n=193), left atrium (n=19), and left ventricle (n=42). Of 95/243 (39.1%) patients with a cardiac thrombus that underwent echocardiography (median interval cardiac CT-echocardiography: 2 days), transthoracic echocardiography detected a thrombus in 18/92 (19.6%) patients and transesophageal echocardiography in 2/5 (40.0%) patients. The diagnostic yield in patients that underwent both modalities was higher for cardiac CT (OR 7.5 [CI 4.0-15.3], p<0.001). Median additional scan time was 6 minutes (IQR 5-7) for ECG-gated and 17 seconds (IQR 15-63) for non-ECG-gated cardiac CT. Median additional radiation dose was 5.4mSv (IQR 3.0-7.6). Patients with a cardiac thrombus on cardiac CT had higher 90-day mortality than those without a thrombus (33.3% vs 14.6%, p<0.001). We found no difference in 90-day recurrent stroke rate (5.4% vs 4.4%, p=0.50). Conclusion: Routine cardiac CT performed during the acute stroke imaging protocol detects a cardiac thrombus in 1 out of 16 patients with AIS, with a 7-times higher yield than routine echocardiography. Mortality rate was doubled in patients with a cardiac thrombus, but 90-day stroke recurrence risk did not differ.

Introduction: Spinal cord infarction (SCI) is a rare but serious neurological condition that accounts for 1-2% of all ischemic strokes and can lead to significant disability. Despite its clinical importance, existing studies are limited by small sample sizes that lack national generalizability, and little is known about post-discharge events such as hospital readmissions. We aimed to evaluate factors associated with all-cause hospital readmissions among hospitalizations with primary diagnosis of SCI, utilizing the Nationwide Readmissions Database (NRD). Methods: NRD data were abstracted from 2016 to 2022 including all hospitalizations of adult patients (≥18 years) with a primary diagnosis of SCI. Multiple-predictor logistic regression models were estimated to assess the association of demographic and clinical variables with all-cause 90-day readmissions. We included specific comorbidities often used in comorbidity scoring systems and added conditions or complications that are known to be associated with SCI. Statistically significant covariates from the unadjusted model were retained in the multiple-predictor model. Odds ratios (OR) with associated 95% Confidence intervals (CI) and p-values were reported. Results: From 2016 to 2022, there were an estimated 3321 hospitalizations with a primary diagnosis of SCI, out of which 27% (95% CI: 24-30%) were readmitted within 90 days. Demographic factors that were associated with lower odds of readmission included private insurance (vs. Medicare) and high-income quartile (Fig. 1). [AH1] [AAs2] Clinical factors that were associated with increased odds of readmission included autonomic dysfunction (OR = 5.44, 95% CI: 1.86 to 15.94), renal disease (OR = 3.57, 95% CI: 1.83 to 6.96), liver disease (OR = 2.40, 95% CI: 1.34 to 4.32), full clinical associations shown in Figure 2. Conclusion: We identified several clinical and demographic factors that were significantly associated with increased all-cause readmissions after SCI hospitalizations. Autonomic dysfunction and renal disease were among the top predictors of readmissions. We uncovered socioeconomic disparities in readmissions rates following SCI. This data may assist vascular neurologists, physicians and healthcare administrators in reducing readmissions after SCI and addressing these disparities. Additionally, our results can guide future studies focusing on the management of this rare entity.

Background: The rate of intracardiac thrombus detection in the hyperacute phase of stroke varies from 5% to 12% between studies. Our aim was to compare the thrombus detection rate between ECG-gated and non-ECG-gated cardiac CT protocols in acute stroke patients, using data from a large, international, multicentre registry. Methods: We conducted an individual patient data meta-analysis by pooling prospective and retrospective observational data from stroke patients assessed at four comprehensive stroke centres who underwent either ECG-gated or non-ECG-gated cardiac CT (extended CT angiography or two-phase non-ECG-gated cardiac CT) as part of the acute stroke imaging protocol between May 2018 and June 2024. The primary outcome was the proportion of patients with a cardiac thrombus in gated vs non gated techniques. Results: Of 3,940 patients, 1,474 (37.4%) underwent ECG-gated and 2,466 (62.6%) non-ECG-gated cardiac CT. Patients in the ECG-gated group were younger (median age 72 [IQR 62–81] vs. 74 [IQR 64–82] years, p = 0.000) and had a lower NIHSS at baseline (median 5 [IQR 2–12] vs. 6 [IQR 3–13], p < 0.00). There was a higher rate of thrombus detection with ECG-gated CT compared to non-gated CT (7.5% vs. 5.5%, p = 0.011. The association remained significant after adjusting for age, sex, baseline NIHSS score, and baseline atrial fibrillation (adjusted OR 1.87, 95% CI 1.42–2.47, p = 0.000). ECG-gated CT was associated with lower radiation dose (3.6 vs. 6.3 mSv, p = 0.000) but longer acquisition time (5.8 vs. 0.28 min, p = 0.000). Conclusion: ECG-gated cardiac CT has a higher detection rate for intracardiac thrombus detection compared to non-ECG-gated CT in patients with acute ischemic stroke.

Abstract Early-onset Alzheimer’s disease (EOAD) and Late-onset AD (LOAD) differ in clinical presentations and rates of progression. We aimed to compare baseline and longitudinal tau PET burden, and their relationship with clinical variables in amyloid-PET positive, cognitively impaired participants from the Longitudinal Early-Onset Alzheimer’s Disease Study (EOAD; n=390) and Alzheimer’s Disease Neuroimaging Initiative (LOAD; n=211). Patients with EOAD showed higher baseline tau PET retention, broader neuroanatomical involvement and faster accumulation rates over time compared to LOAD, after adjusting for amyloid load and clinical stage. Tau PET showed stronger correlations with baseline amyloid burden and clinical measures of global cognition and function in EOAD than LOAD. We conclude that earlier age of onset in AD is linked to a more aggressive tauopathy, which in turn is a primary driver of clinical decline. These findings suggest that optimal therapeutic targets and strategies may differ between EOAD and LOAD. One Sentence Summary Younger patients with Alzheimer’s disease show more aggressive tau spread, suggesting age of onset defines distinct disease pathways with key clinical implications.

This cohort study examines the clinical implementation of timely consolidation with antiresorptive therapy to preserve bone mineral density gains and reduce fracture risk.