Citations

Abstract Background Individual environmental exposures, the exposome, can play an influential role in the development and progression of neurodegenerative diseases such as AD. The protein components of the main AD neuropathologies, amyloid (Aβ) plaques and tau neurofibrillary tangles (NFTs), can be measured using immunohistochemical and biochemical approaches. The main genetic risk factor for AD is the APOE e4 allele. APOE levels can also be measured in the brain. We hypothesize that social determinants of health, specifically alcohol and tobacco consumption, and the area deprivation index (ADI), could play a considerable role in severity of neuropathology and brain biochemical phenotypes of AD. Method We evaluated 478 neuropathologically characterized AD donors, from the Mayo Clinic Brain Bank. 469 samples had available biochemical measures (APOE, Aβ40, Aβ42, tau, and phospho‐tau (Thr231)), collected across three isolated fractions (soluble (TBS), membrane‐bound (TX), and insoluble (FA)) of the superior temporal gyrus. Exposome variables were extracted from the available records. ADI from the Neighborhood Atlas® version from the year 2015 was obtained from de‐identified addresses. ADI, smoking and alcohol were available for 263 of these donors and were examined for association with biochemical measures using linear regression adjusting for age at death and sex. Result Higher ADI levels representing neighborhoods with increased deprivation, were nominally associated (β=0.006, p =0.01) with soluble levels of APOE. Alcohol consumption was associated with lower levels of membrane bound APOE (β=‐0.23, p =0.04). Analysis with neuropathological variables including CAA ( N =454), Braak ( N =454), Thal ( N =454), Hippocampal sclerosis ( N =453), Lewy bodies ( N =455) will also be performed. Conclusion Different components of the social exposome may impact levels of core AD proteins. Additional analyses in expanded cohorts to further explore the associations with neuropathology are ongoing. We expect that understanding how the social exposome impacts specific aspects of neurodegenerative diseases will provide key insights into underlying, potentially modifiable, mechanisms of disease.

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer’s disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract Background & Aims: Alcohol is a leading global risk factor, over 200 diseases and injuries, but policy adoption varies. We updated the Alcohol Preparedness Index (API) to track global and regional policy trends from 2010–2019. Methods: Using WHO GISAH data for 141 countries, we scored five domains (policy frameworks; production/pricing/taxation; marketing/availability; drink-driving; monitoring/surveillance). The primary endpoint was % change in API. Trends were summarized by WHO region and correlates tested in adjusted regression. Results: In 2019, <25% of countries had a strong national alcohol plan and 40% had none. Production/pricing/taxation increased most (27%→78%); monitoring/surveillance reached strong levels in 47.5%. Median API increased from 57.0 [39.0–82.0] (2010) to 74.8 [58.3–83.5] (2016) and stayed above baseline in 2019 (67.8 [51.2–83.8]). Larger population predicted less API gain (β=−19.1, p<0.05); HDI and per-capita consumption did not. Conclusions: Global alcohol policy preparedness increased from 2010–2019.

PURPOSE To compare patient-reported and clinical outcomes between radical cystectomy (RC) and bladder-sparing therapy (BST) in patients with recurrent high-grade non–muscle-invasive bladder cancer (NMIBC). PATIENTS AND METHODS This pragmatic, prospective observational cohort study was designed with patients, who selected and prioritized outcomes. Eligible adults were candidates for both RC or BST, had previous induction Bacillus Calmette-Guérin (BCG), and received their last treatment within 12 months. The primary outcome was the EORTC-QLQ-C30 physical function scale at 12 months. Secondary outcomes included other EORTC-QLQ-C30 scales, depression, anxiety, bladder cancer–specific quality of life (QOL), financial burden, and cancer-specific outcomes. Targeted maximum likelihood estimation (TMLE) was used to calculate average treatment effect (ATE) estimates between arms. Inverse probability weighted risk ratios (wRR) were calculated using quasi-Poisson regression. RESULTS Of 570 participants (mean age 71.4 years; 21% female), 371 selected BST and 199 selected RC. Physical function was significantly worse in the RC arm at 3 months; by 9 months, there was no difference between arms, and at 12 months, physical function did not differ (ATE, 0.9; 95% CI, –0.6 to 2.4; P = .22). RC was associated with better emotional function, generic health-related QOL, and financial burden, and lower depression and anxiety, while BST was associated with better bowel and sexual health. Cancer-specific survival was 99% for BST versus 96% for RC (wRR, 0.99; 95% CI, 0.97 to 1.01). RC was associated with a higher risk of adverse events and serious adverse events, including a 90-day mortality rate of 2.5%. CONCLUSION Most patient-prioritized outcomes were similar or better among participants who chose RC compared with BST. These findings support the continued role of RC in managing recurrent high-grade NMIBC.

Abstract Background: For large language models (LLMs) to reach their potential as information technology tools that make medication use safer, clinically relevant benchmarks capable of automated grading and designed specifically to measure the performance of LLMs for medication tasks are required. The purpose of this study was to design a suite of benchmarking tests reflective of Comprehensive Medication Management (CMM; the standard of care for medication optimization) and quantify the baseline performance of the latest LLMs. Methods: We established six benchmarks representing critical stages of the CMM process: drug formulation matching, drug order (sig) generation, drug route matching, drug-drug interaction identification, renal dose identification, and drug-indication matching. For each benchmark, we curated a clinician-annotated dataset comprising 250 standardized input-output pairs including both inpatient and outpatient medications. We evaluated the clinical knowledge retrieval capabilities of three LLMs: GPT-4o-mini, MedGemma-27B, and LLaMA3-70B. We employed a zero-shot prompting strategy, excluding in-context examples, to assess the models’ internal clinical knowledge rather than their few-shot learning potential. To check reliability, each model was run three times using a temperature of 0.7 (a mid-range value of an LLM setting controlling text generation randomness). Performance was assessed using task-specific evaluation metrics including precision (positive predictive value), recall (sensitivity), F1-score, accuracy, and correctness consistency across trials. Results: Across six benchmarks, LLaMA3-70B demonstrated the highest performance in four tasks: drug-formulation matching (F1, 54.0% [95 CI: 50.1-58]), drug-order generation (accuracy, 88.0%), drug-route identification (F1, 74.3% [95 CI: 71-78]), and drug-indication identification (accuracy, 97.6% [95 CI: 95.6-99.2]). In the drug–drug interaction task, GPT-4o-mini achieved the highest overall accuracy (70.4% [95 CI: 64.8-75.7]). For renal dose–adjustment identification, GPT-4o-mini demonstrated the highest F1 score (83.3% [95 CI: 77.6-88]). Correctness-consistency scores ranged from 8.0% to 97.6% across benchmarks, with no model exhibiting uniformly superior consistency. Conclusions: Model performance varied substantially across medication-related tasks. LLaMA3-70B demonstrated promising baseline performance in tasks involving formulation, ordering, route, and indication. GPT-4o-mini showed potential advantages in drug–drug interaction detection and renal dose adjustment. These findings underscore the need for task-specific evaluation when deploying models for medication-focused clinical decision support.

Abstract Background The purpose of this study was to develop a series of benchmarks specifically for large language model (LLM) performance in the identification of drug-drug interactions (DDIs). Methods We evaluated six LLMs using a clinician-designed dataset of 750 DDI scenarios. Tasks included: (1) a pointwise two-drug classification task (2) a pairwise three-drug discrimination task and (3) a listwise 4–6 drug selection task. Zero-shot prompting was applied and performance was assessed using precision, recall, F1 score, accuracy, and self-consistency. Results Model performance varied by task structure and interaction severity. GPT-5-Chat demonstrated the highest recall and F1 score in the pointwise task (80.7% and 80.2%), whereas DrugGPT achieved superior accuracy in the pairwise (93.7%) and listwise task (92.6%). All models had improved performance with more severe compared to less severe DDIs (accuracy 72.0-99.2% vs. 58.3-86.7%). All models tended to have higher self-consistency in the pairwise and listwise experiments compared to the pointwise experiment (68.8-93.6% vs. 31.0-74.2%). No model exhibited uniformly high reliability across all tasks. Conclusions Current LLMs show inconsistent capabilities in identifying DDIs. Performance degrades as reasoning space expands with limited stability. These findings emphasize the need for multi-format evaluation frameworks and reliability-aware assessment when considering LLMs for medication-safety applications.

Abstract Introduction In 2018, our institution implemented a MALDI-TOF mass spectrometry (MS) method (Mass-Fix) to detect myeloma associated M-proteins in blood. Currently, the lab has performed more than 500K tests by Mass-Fix. While Mass-Fix has been found to be more sensitive and specific than IFE, an ESI-Q-TOF (High Resolution Mass-Fix) method has demonstrated the potential to detect M-proteins at significantly lower levels. Blood minimal residual disease (MRD) detection in lieu of bone marrow (BM) is desirable since blood is easier and less expensive to obtain and analyze. This feature can allow for more frequent MRD monitoring for myeloma patients. Methods 66 residual blood samples from myeloma patients with varying M-protein varying isotypes were diluted into healthy blood to estimate the limit of detection of HR-Mass-Fix method. 179 Rochester Mayo Clinic patients who had a clinically ordered BM MRD assessment by next generation flow (NGF) cytometry (2 x 10-6), a blood sample available within 7 days of the BM biopsy, and a pre-treatment measured M-protein mass by Mass-Fix were utilized to assess the concordance of the BM and blood MRD status. Results The average limit of detection (LOD) of the HR-Mass-Fix was found to be significantly lower than Mass-Fix (0.0003 g/dL and 0.01 g/dL, respectively). The treated patient cohort utilized for comparison consisted of 145 myeloma, 21 AL amyloid, 4 LPL lymphoma and 9 other PCDs. Comparing the Mass-Fix and HR-Mass-Fix results, 100% of blood positive MRD results by Mass-Fix were positive by HR-Mass-Fix. HR-Mass-Fix detected residual M-proteins (mass within +/- 1 Da of pre-treatment) in 29 samples (40%) that were negative by Mass-Fix. Thus, HR-Mass-Fix increased the overall blood MRD positivity rate from 57% by Mass-Fix to 78%. The BM NGF MRD positivity was lower at 54%. The overall agreement of blood and BM by Mass-Fix was 71% (kappa 0.4) which decreased to 0.63 (kappa 0.3) with HR-Mass-Fix. Most of the disagreements were HR-Mass-Fix Blood (+)/BM NGF (-). Blood M-protein MRD appeared to be affected by M-protein half-lives. To determine this, the M-protein isotype distribution of Blood/BM MRD status was compared the M-protein isotype distribution of the overall cohort. The half-lives are as follows: IgG 23 days, IgA 6 days, IgM 5 days and FLC 0.25 days. When both blood and BM were positive, the isotype distribution was not significantly different than the overall cohort. For blood(+)/BM(-) patients, IgG (with the longest half-life) were significantly overrepresented compared to the overall cohort (74% vs 51%) . For blood(-)/BM(+) cases, there were no IgG M-proteins, and the majority were FLC patients. These results suggest that patients with shorter half-life M-proteins (non-IgG) are more likely to be Blood MRD(-) than patients with longer half-life M-proteins. M-protein rate changes over time will likely be needed to resolve the M-protein half- life affect. Conclusions HR-Mass-Fix can significantly increase the detection of M-proteins in comparison to our current Mass-Fix method. Ig recycling was found to be a likely reason for the disagreement between BM and blood. Therefore, a negative blood MRD status by HR-Mass-Fix is most likely to be the most significant in predicting patient outcomes.

Abstract Introduction Matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS, mass fix) represents a sensitive and specific alternative to electrophoresis and immunofixation for quantifying monoclonal antibodies in patients with multiple myeloma (MM). Here we report real world data utilizing mass fix and compare its test characteristics to a gold standard of minimal residual disease (MRD) quantification utilizing next generation sequencing (NGS). Results All patients who had obtained mass fix and MRD testing by NGS as part of routine clinical care at Mayo Clinic Arizona were screened for this study. In total, 343 pairs of mass fix and NGS testing within 50 days of each other representing 269 unique patients with secretory multiple myeloma were included. Cases of IgD myeloma and those secreting only free light chains were excluded. The threshold of MRD negativity was set at &lt;1x10-6(less than one malignant cell in one million) and was assessed utilizing the clonoSEQ NGS assay. The median age of our cohort is 67, it is 44% female, and primarily Caucasian (88%) with a median follow-up of 7.3 months from testing date. FISH testing was performed in 96% of patients and at least one high risk cytogenetic abnormality (t(4;14), t(14;16), del(17p)) was found in 23% of patients. The t(11;14) translocation was found in 18%, +1q in 26%, and amp(1q) in 6% of evaluated patients. Notably, patients at all stages of treatment or disease status were included in our study. Induction treatment for newly diagnosed MM (NDMM, 133 patients) was mostly daratumumab-containing quadruplet (63%) or triplet drug regimens (36%). Autologous stem cell transplant (ASCT) was performed in 79% of NDMM and 80% of relapsed refractory MM patients (RRMM, 138 patients). Of the RRMM patients, 94% were triple class exposed and 41% were penta-exposed. Overall agreement between NGS and mass fix results was 65% (Kappa statistic: 0.31, 95% CI: 0.22 – 0.41). Most discordant cases were instances of mass fix negativity and NGS positivity (n = 89, 26% of all testing pairs). Only 7% of cases (n= 30) represented mass fix positivity with NGS negativity. Mass fix was able to define therapeutic monoclonal antibody by its unique mass spectrometric profile in 38 of the total test pairs that otherwise would have been considered disease associated. Of the 30 patients testing mass fix positive and NGS negative, 25 (83%) represent post-treatment evaluations. Thus, ongoing mass fix positivity represents monoclonal protein washout kinetics. All of these cases are noted to have declining mass fix levels at last follow up and 40% had undetectable monoclonal protein. The discordant mass fix negative and NGS positive cases were evenly distributed across NDMM and RRMM representing 32% and 20% of test pairs in each group, respectively. Amongst these 89 total test pairs, the median abundance of malignant clone by NGS was 10 cells per million (range 0.06 to 297,895). This is in contrast to 136 concordantly positive test pairs where the median was 2960 cells per million (range 0.353 to 1,017,360). The median monoclonal protein identified (in those with a quantifiable M-spike) was 0.30 g/dL. Receiver operating characteristic curves using NGS as gold standard found the optimal mass fix threshold to be 0.010g/dL (specificity 95%, sensitivity 51%) for NDMM patients and 0.046g/dL (specificity 84%, sensitivity 55%) in RRMM patients. Conclusions Development of a MRD assay based on peripheral blood sampling could greatly improve the ease and speed of obtaining these assessments. Our experience highlights both the great potential and need to identify appropriate clinical contexts for optimal use of mass fix MRD assessment. A significant limitation of our data is that low level monoclonal proteins without a previous reference above a threshold of 20mg/dL are not reported as positive and may account for a significant fraction of discordant cases reported here. All clonoSEQ NGS samples are referenced to a positive control greatly increasing specificity. The currently reported dataset is biased against mass fix as not all test pairs reported are known to have a positive reference. Further delineation of these cases is forthcoming. Previous reports have also noted that mass fix test characteristics can improve with time from treatment which will be assessed with future follow-up.

Parkinson's disease (PD) is a progressive neurodegenerative disease with multiple manifestations including both motor and non-motor symptoms. One manifestation of PD that is often overlooked is the sexual dysfunction (SD) that patients may experience. Individuals with PD can experience impairment in sexual desire, arousal or lubrication, orgasm, ejaculation, pain and the physical aspect of intimacy. This article aims to provide an overview of the current practices in the evaluation and treatment of sexual dysfunction in men in the context PD. Note that this article focuses on the male population as it reviews the available American Urology Association practice guidelines many practitioners follow, which focus on the male population. Sexual dysfunction guidelines for the female population are much more limited, and future work should review the existing literature and gaps to provide a more robust understanding of sexual dysfunction in PD. PD represents a particularly vulnerable population for development of sexual dysfunction given the multifactorial nature of its manifestations. Given its profound impact on not only the patient, but their partner, it is important to be aware of the various manifestations of SD when evaluating individuals with PD. Through thorough history taking and targeted psychosexual evaluation, we as practitioners can ensure a more holistic and comprehensive approach to caring for individuals with PD.