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PURPOSE Patients with cancer take different types of medications with varying schedules and settings. They are also sometimes instructed to stop medications due to toxicity. To measure self-reported nonadherence in this heterogeneous population, we modified and evaluated a measure originally developed to assess nonadherence to daily oral antihypertensives, the Domains of Subjective Extent of Nonadherence (DOSE-Nonadherence). METHODS The measure was refined in an iterative process incorporating feedback from patient investigators and participant interviews in English and Spanish. Branching logic was added for participant selection of medication administration setting: (1) only home, (2) only clinic, or (3) partly home/partly clinic. Participants reported their adherence to medications taken over a setting-specific reference period (1 week for home, 1 month for clinic medications). Participants who missed medications then reported on reasons for nonadherence. Adherence was dichotomized for analysis (complete adherence v any nonadherence). For participants who received clinic-administered medications, concordance between chart-abstracted and self-reported adherence was evaluated. RESULTS Seventy-three participants completed the measure (68% English; 32% Spanish; 86% female; 44% age ≥60 years). The majority had breast cancer; 64% had metastatic disease. Twenty-six percent (15/58) of participants who received medication in clinic and 24% (11/46) of those who took medication at home reported nonadherence. Participants felt able to respond accurately to both reference periods and perceived all reasons for nonadherence to be relevant. Among participants who completed the final version of the measure for clinic-administered medication, 96% (26/27) accurately reported their adherence compared with chart-abstracted data. CONCLUSION Our results support the validity of the DOSE-Nonadherence-Cancer for assessing cancer treatment nonadherence. This measure can be used to assess nonadherence in patients with cancer receiving a broad array of systemic therapies.

Background and Objectives The genetic basis of adult-onset multiple sclerosis (MS) is well-studied, but less is known about pediatric-onset MS (pedMS), comprising approximately 5% of all MS onsets. Mendelian randomization (MR) studies have demonstrated evidence for a causal association between MS and both 25-hydroxyvitamin D [25(OH)D] serum levels and genetic variation related to vitamin D receptor (VDR) binding. The objective was to identify whether VDR binding variants (VDR-BVs) previously implicated in adult-onset MS were associated with pedMS using genetic instrumental variables (GIVs). Methods Using previously identified VDR-BVs to construct individual GIVs with two-sample MR, we investigated associations with pedMS in 725 cases and 592 controls of European ancestry from the US Network of Pediatric MS Centers. Associations between each VDR-BV and pedMS were estimated using logistic regression adjusting for the first three genome-wide principal components. A significant interaction between a VDR-BV and 25(OH)D GIV provided evidence for a causal association unbiased by pleiotropy. Results One VDR-BV, rs2531804, previously associated with adult-onset MS, was also significantly associated with pedMS after multiple testing correction. Discussion This study is the first to use VDR-BVs from previous MR studies to demonstrate causal differences in VDR binding at a locus contributing to pedMS susceptibility.

Abstract Introduction Comparing sleep and rest-activity rhythms (RARs) across the spectrum of cognitive aging can reveal novel risk factors and potential mechanisms underlying dementia disorders. However, our current understanding is restricted by differences in sleep measurement, limited longitudinal data, and heterogeneous cognitive aging processes. We aimed to determine (1) which sleep/RAR features exhibit meaningful changes within three distinct cognitive pathways; and (2) which sleep/RAR features differ between cognitive aging pathways prior to and after the onset of mild cognitive impairment (MCI) and/or dementia. Methods Longitudinal self-reported sleep and actigraphy data were obtained from 1,449 participants in the Rush Memory and Aging Project (mean age= 81.2±7.1 years, 75.2% female, 5.2% Black, 94.8% White). We applied flexible cubic spline models to quantify differences in the levels and trajectories of sleep amount (self-reported duration; actigraphy rest interval length and alpha), regularity (actigraphy interdaily stability, intradaily variability, and midpoint standard deviation), and timing (self-reported midpoint; actigraphy midpoint and acrophase) within and between three cognitive aging pathways over 12 years: Normal Cognitive Aging (‘Normal’), Progression to MCI (‘Stable MCI’), and Progression to Dementia (‘Dementia’). Models were adjusted for key sociodemographic and health variables. Results Sleep amount was lowest in the Dementia pathway prior to MCI or dementia, but increased with age, most rapidly following dementia. The greatest effect was observed in self-reported duration (standardized mean change, d[95%CI]=0.912 [0.47, 1.36]. Regularity declined across all pathways, most rapidly after cognitive diagnoses, with the largest increases in intradaily variability occurring among the Stable MCI (d=0.97 [0.70, 1.23]) and Dementia paths (d=1.11 [0.84, 1.38). Shifts toward earlier sleep timing were observed in actigraphy measures across all three pathways (-0.54≤d≤-0.31). Conclusion Shorter sleep amount in cognitively healthy older adults may be a risk factor or prodromal indicator of dementia, while longer sleep amounts and decreasing regularity following dementia may reflect neurodegeneration. Advances in sleep timing may be less useful as a clinical indicator of future cognitive impairment or decline. Differences between self-reported and actigraphy-measured sleep/RAR outcomes may reflect distinct underlying mechanisms, warranting further research. Support (if any) NIH: T32HL082610, RF1AG056331, R01AG052488, R01AG071638, RF1AG070436, R01AG17917

Abstract RATIONALE: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality worldwide. We previously published the polygenic transcriptome risk score (PTRS) which uses the cumulative effect of predicted gene expression to construct genetic predictors for complex diseases, and we demonstrated the value of PTRS for COPD built on Genotype-Tissue Expression (GTEx) Lung tissue with significantly improved cross-ancestry portability. However, the postmortem collection and lack of lung disease status on GTEx samples likely affect results. We hypothesized that the performance of PTRS will be improved by using disease-relevant expression quantitative trait loci (eQTLs) to construct the score. Here, we aimed to improve performance of PTRS by leveraging disease-relevant eQTLs. METHODS: We constructed two transcriptome prediction models, Elastic Net (EN) and Prediction Using Models Informed by Chromatin conformation and Epigenomics (PUMICE), using TOPMed lung RNA-seq data from the Lung Tissue Research Consortium (LTRC), which included COPD patients undergoing lung surgery. We compared their performance with two published models built on RNA-seq from GTEx Lung tissue, GTEx-EN and GTEx-PUMICE. We first integrated each of four transcriptome models with multi-ancestry GWAS of FEV1/FVC ratio (Shrine et al. 2023) to generate transcriptome-wide association study (TWAS) results, which produced trait-associated genes. Pathway analysis was then conducted on significant TWAS genes. Finally, the PTRS was computed on TWAS genes that were included in the top 20 significantly enriched pathways. We tested performance of PTRS in race-stratified analysis for moderate-to-severe and severe COPD in COPDGene. RESULTS: Our models produced more significant TWAS genes (FDR<0.05) and had more overlaps with genes identified for FEV1/FVC ratio from Shrine et al. 2023 compared to two GTEx models (Fig. A). Additionally, our models had significantly higher AUC for predicting both moderate-to-severe and severe COPD in race-stratified analysis. The mean AUC from LTRC-EN for predicting severe COPD was 0.57 and 0.55 respectively for EUR and AFA, which was significantly higher than mean AUC of 0.54 and 0.51 from GTEx-EN (Delong p-value=8.15x10-10 for EUR and 1.42x10-3 for AFA) (Fig. B). Similarly, the PTRS derived from our models produced higher Odds Ratios (OR) per standard deviation. The mean OR from LTRC-PUMICE for moderate-to-severe COPD was 1.25 and 1.18 respectively for EUR and AFA, while it was 1.17 and 1.12 from GTEx-PUMICE (Fig. C). CONCLUSIONS: Our study demonstrates the value of leveraging disease-relevant RNA-seq to construct transcriptome prediction models and their improvement on identifying lung function genes and predicting COPD across ancestries.

AbstractINTRODUCTIONComparing sleep and rest–activity rhythms across different cognitive aging pathways can identify novel risk factors and potential mechanisms. However, our current understanding is restricted by differences in sleep measurement, limited longitudinal data, and heterogeneous cognitive aging processes.METHODSWe applied cubic splines to longitudinal self‐reported sleep and actigraphy data from 1449 participants in the Rush Memory and Aging Project and quantified differences in the levels and trajectories of sleep amount, regularity, and timing within and between three cognitive aging pathways: normal, stable mild cognitive impairment, dementia.RESULTSSleep amount was lowest in the dementia pathway prior to cognitive impairment but increased with age, most rapidly after dementia. Regularity declined across all pathways, most rapidly after cognitive diagnoses. Timing advanced across all pathways.DISCUSSIONShorter sleep amount in cognitively healthy older adults may be a risk factor or prodromal indicator of dementia, while longer sleep amounts and decreasing regularity may reflect neurodegeneration.Highlights We quantified longitudinal changes in sleep across three cognitive‐aging pathways. We incorporated both subjective and objective measures of sleep health. Self‐report duration increased noticeably from before to after cognitive diagnosis. Sleep irregularity increased most prominently after cognitive diagnosis. Advances in sleep timing occurred in both normal and pathological aging.

ABSTRACTImmune thrombotic thrombocytopenic purpura (iTTP) is characterized by microangiopathic hemolytic anemia, thrombocytopenia, and microvascular occlusion secondary to acquired ADAMTS13 deficiency. Contemporary data regarding iTTP treatment practices in the US, including the use of caplacizumab, are lacking. We aimed to characterize the demographics and therapies, including medications and apheresis practices, in patients with iTTP in the US. We retrospectively analyzed iTTP cases at 15 sites in the US that provide comprehensive care for patients with iTTP. The time‐period assessed was from January 1, 2017 to December 31, 2021. Our primary objective was to analyze data by iTTP episode, inclusive of initial episodes and relapses. A total of 390 iTTP episodes were reported for 280 unique individuals (187 females, 93 males). Thirty‐day mortality was 3.7% (14/374), and 6‐month mortality was 7.4% (27/367). TPE details were reported for 343 episodes, among which 261 underwent at least one procedure (median 6, IQR 3–11). Among the 261 episodes with at least one therapeutic plasma exchange (TPE) performed, 82.0% (214/261) used only plasma. Caplacizumab was used either alone or in combination with other agents in 43 (11.0%) episodes. Management strategies for iTTP remain varied across centers in the US, with a variety of combinations for TPE replacement fluids and therapeutic agents, as well as limited use of caplacizumab. Further research and standardization of treatment regimens may further reduce mortality in this condition.