Citations

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Objectives To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.88-1.26 ATT). Even more extreme divergence in estimates was observed for differences between SP-2 and SP-3 with respect to methamphetamine/amphetamine, (IPTW-ATE: PR=1.51, 95% CI: 0.79-2.89; IPTW-ATT: PR=2.36, 95% CI: 1.36-4.12); vs Matching: PR=2.71, 95%CI: 1.47-4.99) and cocaine (IPTW-ATE: PR=1.15, 95% CI: 0.55-2.38; IPTW-ATT: PR=1.81, 95% CI: 1.03-3.18); vs Matching: PR=1.38, 95%CI: 0.76-2.53). Conclusion The combination of a rare exposure and a rare outcome can produce challenges for commonly used confounding adjustment strategies, and it is often best to compare different modeling approaches to gain greater insight.

Importance Ischemic heart disease (IHD), the leading cause of death in the US, is predominantly due to modifiable risk factors. Estimates of IHD mortality attributable to risk factors provide evidence for health policy decision-making. Objective To estimate the burden of IHD death attributable to risk factors in the US from 1990-2023. Design, Setting, and Participants The Global Burden of Disease Study 2023 (GBD 2023) used vital records and a broad set of epidemiologic data to estimate IHD death rates, risk factor exposure, and relative risk curves for risk-outcome pairs for 1990-2023 for the general population. Data analysis was performed from October 2024 to December 2025. Exposure Twelve metabolic, behavioral, and environmental risk factors. Main Outcomes and Measures The primary outcomes were IHD death rates per 100 000 persons, counts, and attributable risks from 1990-2023 by age, sex, and US state. Estimates include 95% uncertainty intervals (UI). IHD death rates were estimated using ensemble modeling methods. Risk exposures were estimated using bayesian meta-regression methods. Relative risks were estimated following the Burden of Proof framework. Results In 2023, there were 473 000 IHD deaths (95% UI, 414 000-510 000) in the US, a decrease of 58.7% (95% UI, 56.8%-61.0%) in age-standardized rate since 1990. Between 2010 and 2023, there was a 19.0% decrease (95% UI, 15.0%-22.9%) for males and a 24.5% decrease (95% UI, 20.3%-29.7%) for females in IHD death rates. High systolic blood pressure (SBP), dietary risks, and high low-density lipoprotein cholesterol (LDL-C) were the leading risk factors for IHD deaths in 2023, accounting for 47.2% (95% UI, 36.4%-57.0%), 38.6% (95% UI, 17.2%-56.8%), and 28.5% (95% UI, 19.3%-39.6%) of IHD deaths, respectively. Increased exposure to several risk factors substantially increased their attributable burden for IHD deaths in 2023, with high fasting plasma glucose (FPG) increasing 38.8% (95% UI, 11.5%-81.1%) and high body mass index (BMI) increasing 54.5% (95% UI, 41.8%-66.3%) since 1990. Smoking and particulate matter pollution had the greatest decrease in attributable IHD mortality since 1990, at 33.3% (95% UI, 23.6%-41.7%) and 74.9% (95% UI, 46.7%-88.8%), respectively. Conclusion and Relevance Per the results of this systematic analysis of GBD 2023, a total of 88.7% (95% UI, 83.4%-92.5%) of IHD deaths were attributable to modifiable risk factors in the US in 2023, with high SBP, dietary risks, and high LDL-C being the greatest contributors. High BMI and high FPG showed the largest attribution increases, while exposure to other risks did not increase significantly for the population.

Introduction Cognitive symptoms such as ‘brain fog’ are frequent and disabling in patients with SLE. We aimed to develop and validate the Lupus Brain Fog Severity Scale (LBFSS), the first patient-reported outcome measure (PROM) for cognitive symptoms in SLE. Methods The LBFSS was developed using a multi-step international approach involving healthcare professionals and patients with SLE. Patients provided free-text descriptions of brain fog, generating candidate domains through thematic analysis (step 1). Domains were rated for relevance (step 2) and those retained converted into self-assessable items (step 3). The pilot LBFSS was iteratively refined (step 4). The finalised LBFSS was validated (step 5) in a large international SLE cohort. Psychometric evaluation included internal consistency, exploratory factor analysis and assessment of construct, convergent, known-groups and criterion-related validity. Results In step 1, 147 SLE participants across 39 countries generated 21 domains for cognitive symptoms, of which 13 were retained in consensus (step 2), converted into self-assessable items (step 3) and iteratively refined using patient and physician feedback. In step 5, validation of the LBFSS instrument in 378 patients from 36 countries demonstrated high internal consistency (Cronbach’s α=0.95) and a unidimensional structure explaining 62.2% of variance. LBFSS scores were significantly higher in participants reporting brain fog (p<0.0001), confirming known-group validity. Construct validity was supported by significant correlations with functional impact and symptom severity (ρ=0.46–0.65, p<0.0001), strong convergent validity with the Perceived Deficits Questionnaire-20 (ρ=0.84, p<0.0001) while the discriminative performance for presence versus absence of self-reported brain fog was high (area under the curve=0.85). Conclusion The LBFSS is a new, valid and feasible PROM to assess brain fog and cognitive symptoms in SLE.

Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight. Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS. Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets. Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts. Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.

Abstract Background Patients with breast cancer undergoing chemotherapy experience multiple symptoms that cause decrements in quality of life. A deeper understanding of serum metabolites as biomarkers may guide in predicting symptom occurrence and severity. This study evaluated change in serum metabolite levels from before chemotherapy (T1) to after the initial first or second cycle of chemotherapy (T2), after the third cycle of chemotherapy (T3) and finally after a month of chemotherapy completion (T4). Change in metabolite levels were analyzed in association with symptom occurrence. Methods Patients with breast cancer (n = 10) completed study measures at four timepoints. Neuropsychological and gastrointestinal (GI) symptoms were evaluated using the Memorial Symptom Assessment Scale. Dietary intake was assessed using the NHANES Dietary Screener Questionnaire. Serum metabolites were analyzed using gas chromatography-mass spectrophotometry. Results Five patients experienced > 3 GI symptoms at T2 and T3. At all 4 timepoints, ≥ 6 patients experienced moderate to severe neuropsychological symptoms severity. Daily mean intake of fiber, whole grain, and calcium were less than the recommended guidelines. Compared to T1, long chain fatty acid and amino acid derivative levels decreased at T2 and T3 (p < 0.05). Increase in metabolite levels of glucose-6-phosphate (p = 0.02) and 6-phosphogluconate (p = 0.05) at T2 were associated with fatigue occurrence. Conclusions Patients experienced several gastrointestinal and neuropsychological symptoms during chemotherapy and early survivorship. Chemotherapy-induced changes in metabolites involved in cellular energy metabolism may explain patient symptom experience. Metabolite level changes overtime may reflect inadequate dietary intake. Larger sample size studies may guide in building metabolic prediction models for symptom burden.

Racial and ethnic survival disparities exist in pediatric and young adult acute lymphoblastic leukemia (ALL), with differential treatment toxicity and setting of care as possible drivers. Whether treatment cost and utilization disparities exist, or how they may contribute to differences in ALL survival, is unknown. Patients with ALL diagnosed between 2000 and 2019 at ages 1 to 24 years were identified using ICD-9/10 codes in the administrative claims data from the OptumLabs Data Warehouse and the Surveillance, Epidemiology, and End Results program. Sex, race and ethnicity, age, year, and subtype of ALL diagnosis were collected. Reimbursed treatment cost and utilization (number of inpatient and outpatient days) were computed over the initial 8 months of treatment. Regression models assessed associations with demographic and clinical characteristics. Survival analyses assessed associations between race and ethnicity and overall survival. Among 374 individuals with ALL, treatment costs were 57% lower for Black patients than for White patients (estimate 0.43, 95% CI: 0.19-0.96; P =0.04). Utilization was similar across groups, though Black patients had 24% fewer outpatient visits (estimate 0.76, 95% CI: 0.58-0.99; P =0.04). No significant differences in survival were detected, but observations are consistent with previous reports. Despite a small sample size, the statistically significantly lower cost and utilization among Black relative to White ALL patients are concerning and warrant further research.

Introduction: Advance care planning (ACP) supports goal-concordant care but remains underused nationally. In resident clinics, limited continuity, short visits, and lack of standardized workflows create barriers to ACP integration. In our Community Internal Medicine resident clinic, ACP discussion was documented in 2.5% of annual physicals, and 19.6% of paneled patients had an advance directive (AD) on file. We aimed to increase ACP documentation from 2.5% to 12.5% within 1 year without increasing perceived resident workflow burden. Methods: We conducted a resident-led quality improvement project using Lean Six Sigma methodology. Three interventions were implemented sequentially: nursing distribution of ACP brochures, an electronic medical record DotPhrase to prompt and document ACP discussions, and targeted patient portal outreach to patients without an AD before annual visits. The primary outcome was documented ACP discussion during annual physicals. Secondary outcomes included AD uploads and ACP consult referrals. The balancing measure was resident-perceived workflow burden. Charts were reviewed over 5-week periods at baseline (n = 118) and after each implementation phase (n = 132, 158, 129). Results: ACP documentation increased from 2.5% at baseline to 12.2%, 17.1%, and 24.0% across sequential phases (χ 2 (3) = 24.74, P < 0.0001). Pairwise comparisons versus baseline were significant (all P ≤ 0.005). AD upload rate increased from 1.7 to 6.0 per month, and ACP consult referrals increased from 0.0% to 10.9%. Mean perceived workflow burden decreased from 4.9 to 3.0. Conclusion: Workflow-embedded interventions improved ACP documentation, AD uploads, and ACP referrals without increasing perceived resident burden.