medRxiv : the preprint server for health sciences最新文献

{"title":"Pathways to optimize a pediatric telemedicine and medication delivery service: A multi-level qualitative study in Haiti.","authors":"Frantz Emmanuel Garilus, Kerven Cassion, Youseline Cajusma, Katelyn E Flaherty, Jude Ronald Beausejour, Lerby Exantus, Valery M Beau de Rochars, Chantale Baril, Torben K Becker, Rochelle K Rosen, Eric J Nelson, Molly B Klarman","doi":"10.1101/2025.03.26.25324692","DOIUrl":"https://doi.org/10.1101/2025.03.26.25324692","url":null,"abstract":"<p><p>Telemedicine has secured a permanent role in healthcare delivery worldwide; however, scaling novel telemedicine applications presents challenges. Among the many emerging initiatives is the telemedicine and medication delivery service (TMDS) that our team established in Haiti to enable early access to pediatric care. To gain deeper insights into the challenges associated with scaling a TMDS, we conducted focus group discussions and administered written questionaries to TMDS staff, including physicians, nurses, and medication delivery drivers. We employed framework matrix analysis to identify and summarize insights into the challenges and opportunities associated with the TMDS model. We found key areas for improvement relate to obtaining quality information from virtual exams, the reliability of technology and communication infrastructure, the conditions required for effective in-person exams, the limited scope of the workflow and clinical resources, and long-term sustainability. These findings led to the development of essential action items, categorized into three domains: conceptual, physical and mission oriented. These action items will guide our internal efforts to scale the TMDS and hopefully catalyze improvements among similar telemedicine initiatives.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Encoding of pretrained large language models mirrors the genetic architectures of human psychological traits.","authors":"Bohan Xu, Nick Obradovich, Wenjie Zheng, Robert Loughnan, Lucy Shao, Masaya Misaki, Wesley K Thompson, Martin Paulus, Chun Chieh Fan","doi":"10.1101/2025.03.27.25324744","DOIUrl":"https://doi.org/10.1101/2025.03.27.25324744","url":null,"abstract":"<p><p>Recent advances in large language models (LLMs) have prompted a frenzy in utilizing them as universal translators for biomedical terms. However, the black box nature of LLMs has forced researchers to rely on artificially designed benchmarks without understanding what exactly LLMs encode. We demonstrate that pretrained LLMs can already explain up to 51% of the genetic correlation between items from a psychometrically-validated neuroticism questionnaire, without any fine-tuning. For psychiatric diagnoses, we found disorder names aligned better with genetic relationships than diagnostic descriptions. Our results indicate the pretrained LLMs have encodings mirroring genetic architectures. These findings highlight LLMs' potential for validating phenotypes, refining taxonomies, and integrating textual and genetic data in mental health research.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-enabled echocardiography as a surrogate for multi-modality aortic stenosis imaging: post-hoc analysis of a clinical trial.","authors":"Evangelos K Oikonomou, Neil J Craig, Gregory Holste, Sumukh Vasisht Shankar, Audrey White, Menaka Mahendran, David E Newby, Marc R Dweck, Rohan Khera","doi":"10.1101/2025.03.26.25324690","DOIUrl":"https://doi.org/10.1101/2025.03.26.25324690","url":null,"abstract":"<p><strong>Background: </strong>Accurate aortic stenosis (AS) phenotyping requires access to multimodality imaging which has limited availability. The Digital Aortic Stenosis Severity Index (DASSi), an AI biomarker of AS-related remodeling on 2D echocardiography, predicts AS progression independent of Doppler measurements. Whether DASSi-enhanced echocardiography provides a scalable alternative to multimodality AS imaging remains unknown. We sought to evaluate the ability of DASSi to define personalized AS progression profiles and validate its performance against multimodality imaging features of functional, structural, and biological disease severity.</p><p><strong>Methods: </strong>In the SALTIRE-2 trial of participants with mild-or-moderate AS, we performed blinded DASSi measurements (probability of severe AS, 0-to-1) on baseline transthoracic echocardiograms. We evaluated the association between baseline DASSi and (i) disease severity by hemodynamic (peak aortic valve velocity [AV-V _max ]), structural (CT-derived aortic valve calcium score [AVCS]) and biological features ([18F]sodium fluoride [NaF] uptake on Positron Emission Tomography-CT), (ii) disease progression (change in AV-V _max and AVCS), and (iii) incident aortic valve replacement (AVR). We used generalized linear mixed, or Cox models adjusted for risk factors and aortic valve area, as appropriate.</p><p><strong>Results: </strong>We analyzed 134 participants (72 [IQR: 69-78] years, 27 [20.1%] women) with a mean baseline DASSi of 0.51 (standard deviation [SD]: 0.19). DASSi was independently associated with disease severity: each SD increase was associated with higher AV-V _max (+0.21 [95%CI: 0.12-0.30] m/sec), AVCS (+284 [95%CI: 101-467] AU) and [18F]NaF TBR _max (+0.17 [95%CI: 0.04-0.31]). Higher DASSi was also associated with disease progression by Doppler (AV-V _max ) and CT (AVCS) at 24 months ( <i>p</i> _interaction for DASSi ( <i>x</i> ) time<0.001), and future AVR (75 events over 5.5 [IQR: 2.4-7.2] years, adj.HR 1.47 [95%CI: 1.12-1.94] per SD).</p><p><strong>Conclusions: </strong>DASSi is associated with functional, structural and biological features of AS severity as well as disease progression and outcomes. DASSi-enhanced echocardiography provides a readily accessible alternative to multimodality imaging of AS which has potential value both in clinical practice and as a clinical trial biomarker.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143804747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An internet-assisted sleep, dietary, and physical activity intervention to support weight-loss among postpartum people (Sleep GOALS): Protocol for a pilot randomized controlled trial.","authors":"Marquis S Hawkins, Esa M Davis, Kaleab Z Abebe, Kathleen M McTigue, Namhyun Kim, Mariska Goswami, Daniel J Buysse, Judy C Chang, Michele D Levine","doi":"10.1101/2025.03.25.25324617","DOIUrl":"https://doi.org/10.1101/2025.03.25.25324617","url":null,"abstract":"<p><strong>Background: </strong>Postpartum weight retention and maternal obesity are associated with short- and long-term maternal morbidity and mortality risk. Most weight-loss interventions among postpartum individuals follow evidence-based lifestyle recommendations but have produced only modest effects and had substantial heterogeneity. We developed a novel internet-assisted weight management intervention for postpartum people that integrates concepts for improving sleep health within a diet and physical activity-focused intervention. We describe the intervention protocol and discuss how the pilot study's findings will inform future development and evaluation.</p><p><strong>Methods: </strong>We will recruit 40 postpartum individuals with overweight or obesity from Western Pennsylvania to participate in a single-blind, parallel-arm, randomized controlled trial design. Participants will be randomized at a 1:1 ratio to the Sleep GOALS (Goal-focused Online Access to Lifestyle Support) intervention or education control group. The Sleep GOALS intervention includes interactive lessons addressing sleep, diet, physical activity, behavioral self-monitoring tools, and a lifestyle coach to provide accountability, encouragement, and personalized support. The education control will receive brochures from the American Academy of Sleep Medicine (e.g., sleep hygiene, sleep in women), SNAP education connection (e.g., family-friendly activities, meal planning), and the U.S. Department of Health and Human Services (e.g., physical activity promotion during and after pregnancy). Primary study outcomes include the intervention feasibility (i.e., recruitment, enrollment, attrition rates, intervention engagement) and acceptability (i.e., participant ratings of the intervention delivery, curricula, approach to behavioral self-monitoring, action plans, intervention platform, and coaching). Secondary outcomes include weight loss and retention of pregnancy and postpartum weight gain.</p><p><strong>Discussion: </strong>Incorporating a holistic approach that addresses sleep health alongside diet and physical activity, the Sleep GOALS intervention aims to not only facilitate weight loss but also enhance overall maternal well-being. Pilot testing will help us identify and refine factors related to the conduct of the planned larger, definitive trial and estimate the change in secondary outcomes.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective SARS-CoV-2 Booster Vaccination in Immunosuppressant-Treated Systemic Autoimmune Disease Patients in a Randomized Controlled Trial.","authors":"Meggan Mackay, Catriona A Wagner, Ashley Pinckney, Jeffrey A Cohen, Zachary S Wallace, Arezou Khosroshahi, Jeffrey A Sparks, Sandra Lord, Amit Saxena, Roberto Caricchio, Alfred Hj Kim, Diane L Kamen, Fotios Koumpouras, Anca D Askanase, Kenneth Smith, Joel M Guthridge, Gabriel Pardo, Yang Mao-Draayer, Susan Macwana, Sean McCarthy, Matthew A Sherman, Sanaz Daneshfar Hamrah, Maria Veri, Sarah Walker, Kate York, Sara Tedeschi, Jennifer Wang, Gabrielle Dziubla, Mike Castro, Robin Carroll, Sandeep Narpala, Bob C Lin, Leonid Serebryannyy, Adrian McDermott, William T Barry, Ellen Goldmuntz, James McNamara, Aimee S Payne, Amit Bar-Or, Dinesh Khanna, Judith A James","doi":"10.1101/2025.03.25.25324558","DOIUrl":"https://doi.org/10.1101/2025.03.25.25324558","url":null,"abstract":"<p><strong>Background: </strong>Autoimmune disease patients on immunosuppressants exhibit reduced humoral responses to primary COVID-19 vaccination. Booster vaccine responses and the effects of holding immunosuppression around vaccination are less studied. We evaluated the efficacy and safety of additional vaccination in mycophenolate mofetil/mycophenolic acid (MMF/MPA)-, methotrexate (MTX)-, and B cell-depleting therapy (BCDT)-treated autoimmune disease patients, including the impact of withholding MMF/MPA and MTX.</p><p><strong>Methods: </strong>In this open-label, multicenter, randomized trial, 22 MMF/MPA-, 26 MTX-, and 93 BCDT-treated autoimmune disease patients with negative or suboptimal antibody responses to initial COVID-19 vaccines (BNT162b2, mRNA-1273, or AD26.COV2.S) received a homologous booster. MMF/MPA and MTX participants were randomized (1:1) to continue or withhold treatment around vaccination. The primary outcome was the change in anti-Wuhan-Hu-1 receptor-binding domain (RBD) concentrations at 4 weeks post-additional vaccination. Secondary outcomes included adverse events, COVID-19 infections, and autoimmune disease activity through 48 weeks.</p><p><strong>Results: </strong>Additional vaccination increased anti-RBD concentrations in MMF/MPA and MTX patients, irrespective of whether immunosuppression was continued or withheld. BCDT-treated patients also demonstrated increased anti-RBD concentrations, albeit lower than MMF/MPA- and MTX-treated cohorts. COVID-19 infections occurred in 30-46% of participants, were predominantly mild, and included only two non-fatal hospitalizations. Additional vaccination was well-tolerated, with low frequencies of severe disease flares and adverse events.</p><p><strong>Conclusion: </strong>Additional COVID-19 vaccination is effective and safe in immunosuppressant-treated autoimmune disease patients, regardless of whether MMF/MPA or MTX is withheld. <b>Trial Registration.</b> ClinicalTrials.gov (NCT#05000216).</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prenatal Exposure to Gestational Diabetes Mellitus is Associated with Greater Pre-pubertal BMI Growth and Faster Post-pubertal Cortical Thinning During Peri-adolescence.","authors":"Eustace Hsu, Trevor A Pickering, Shan Luo","doi":"10.1101/2025.03.25.25324581","DOIUrl":"https://doi.org/10.1101/2025.03.25.25324581","url":null,"abstract":"<p><strong>Background: </strong>The longitudinal trajectory of body mass index (BMI) and brain structure development during peri-adolescence is not clearly defined in offspring prenatally exposed to gestational diabetes mellitus (GDM) vs. un-exposed offspring.</p><p><strong>Methods: </strong>Participants between age 9 and 10 years (N=9,583) were included from the Adolescent Brain and Cognitive Development (ABCD) Study and followed yearly though 4-year follow-up. GDM and puberty status were self-reported. BMI was calculated yearly, and MRI assessed brain structure biennially. Mixed-effects models analyzed trajectories of BMI and brain structural measures between groups controlling for sociodemographic covariates, and linear spline was defined with a knot at onset of puberty.</p><p><strong>Results: </strong>There was an interaction of exposure by age in change in BMI [β (95% CI) = 0.032 (0.008, 0.056), <i>P</i> =0.009] and mean cortical thickness [β (95% CI) = -0.038 (-0.071, -0.004), <i>P</i> =0.027]. The former was driven by greater pre-pubertal increases in BMI [β (95% CI) = 0.051 (0.002, 0.100), <i>P</i> =0.043], whereas the latter was driven by faster post-pubertal declines in cortical thickness among GDM-exposed offspring [β (95% CI) = -0.051 (-0.095, -0.007), <i>P</i> =0.046].</p><p><strong>Conclusion: </strong>Prenatal GDM exposure is associated with greater pre-pubertal increases in BMI and faster post-pubertal cortical thinning in youth age between 9 and 15.</p><p><strong>Practitioner points: </strong>- Prenatal GDM exposure is associated with greater pre-pubertal increases in BMI and faster post-pubertal cortical thinning in youth age between 9 and 15.- It is important to recognize puberty as a window of vulnerability for altered brain development among youth prenatally exposed to GDM.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974987/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease.","authors":"Meenal Rawlani, Hirotaka Ieki, Christina Binder, Victoria Yuan, I-Min Chiu, Ankeet Bhatt, Joseph E Ebinger, Yuki Sahashi, Andrew P Ambrosy, Paul Cheng, Alan C Kwan, Susan Cheng, David Ouyang","doi":"10.1101/2025.03.25.25324627","DOIUrl":"https://doi.org/10.1101/2025.03.25.25324627","url":null,"abstract":"<p><p>Accurate understanding of biological aging and the impact of environmental stressors is crucial for understanding cardiovascular health and identifying patients at risk for adverse outcomes. Chronological age stands as perhaps the most universal risk predictor across virtually all populations and diseases. While chronological age is readily discernible, efforts to distinguish between biologically older versus younger individuals can, in turn, potentially identify individuals with accelerated versus delayed cardiovascular aging. This study presents a deep learning artificial intelligence (AI) approach to predict age from echocardiogram videos, leveraging 2,610,266 videos from 166,508 studies from 90,738 unique patients and using the trained models to identify features of accelerated and delayed aging. Leveraging multi-view echocardiography, our AI age prediction model achieved a mean absolute error (MAE) of 6.76 (6.65 - 6.87) years and a coefficient of determination (R ² ) of 0.732 (0.72 - 0.74). Stratification by age prediction revealed associations with increased risk of coronary artery disease, heart failure, and stroke. The age prediction can also identify heart transplant recipients as a discontinuous prediction of age is seen before and after a heart transplant. Guided back propagation visualizations highlighted the model's focus on the mitral valve, mitral apparatus, and basal inferior wall as crucial for the assessment of age. These findings underscore the potential of computer vision-based assessment of echocardiography in enhancing cardiovascular risk assessment and understanding biological aging in the heart.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143804746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The missing link: Electronic health record linkage across species offers opportunities for improving One Health.","authors":"Kathleen R Mullen, Nadia Saklou, Adam Kiehl, Toan C Ong, G Joseph Strecker, Sabrina Toro, Sue VandeWoude, Ian M Brooks, Tracy Webb, Melissa A Haendel","doi":"10.1101/2025.03.25.25324490","DOIUrl":"https://doi.org/10.1101/2025.03.25.25324490","url":null,"abstract":"<p><strong>Objective: </strong>Significant opportunities for understanding the co-occurrence of conditions across species in coincident households remain untapped. We determined the feasibility of creating a Companion Care Registry (CCR) for analysis of health data from the University of Colorado Health (UCHealth) patients and their companion animals who received veterinary care at the geographically-adjacent Colorado State University Veterinary Teaching Hospital (CSU-VTH).</p><p><strong>Materials and methods: </strong>Using a hybrid deterministic and probabilistic record linkage method, non-medical Personally Identifiable Information was securely matched to determine the total number of UCHealth patients within the HIPAA-compliant Health Data Compass Research Data Warehouse (2015-2024) who took a companion animal to the CSU-VTH (2019-2024).</p><p><strong>Results: </strong>12,115 matches were identified, indicating 29% of CSU-VTH clients were UCHealth patients.</p><p><strong>Discussion: </strong>The overlap between CSU-VTH clients and UCHealth patients underscores the potential feasibility and utility of a CCR.</p><p><strong>Conclusion: </strong>This work provides a mechanism to evaluate environmental and inter-species influences on One Health.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974984/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequencing and health data resource of children of African ancestry.","authors":"Leah C Kottyan, Scott Richards, Morgan E Tracy, Lucinda P Lawson, Beth Cobb, Steve Esslinger, Margaret Gerwe, James Morgan, Alka Chandel, Leksi Travitz, Yongbo Huang, Catherine Black, Agboade Sobowale, Tinuke Akintobi, Monica Mitchell, Andrew F Beck, Ndidi Unaka, Michael Seid, Sonja Fairbanks, Michelle Adams, Tesfaye Mersha, Bahram Namjou, Michael W Pauciulo, Jeffrey R Strawn, Robert T Ammerman, Daniel Santel, John Pestian, Tracy Glauser, Cynthia A Prows, Lisa J Martin, Louis Muglia, John B Harley, Iouri Chepelev, Kenneth M Kaufman","doi":"10.1101/2025.03.22.25324419","DOIUrl":"https://doi.org/10.1101/2025.03.22.25324419","url":null,"abstract":"<p><strong>Purpose: </strong>Individuals who self-report as Black or African American are historically underrepresented in genome-wide studies of disease risk, a disparity particularly evident in pediatric disease research. To address this gap, Cincinnati Children's Hospital Medical Center (CCHMC) established a biorepository and developed a comprehensive DNA sequencing resource including 15,684 individuals who self-identified as African American or Black and received care at CCHMC.</p><p><strong>Methods: </strong>Participants were enrolled through the CCHMC Discover Together Biobank and sequenced. Admixture analyses confirmed the genetic ancestry of the cohort, which was then linked to electronic medical records.</p><p><strong>Results: </strong>High-quality genome-wide genotypes from common variants accompanied by medical record-sourced data are available through the Genomic Information Commons. This dataset performs well in genetic studies. Specifically, we replicated known associations in sickle cell disease ( <i>HBB</i> , p = 4.05 × 10 ^⁻ ¹□□), anxiety ( <i>PLAA3</i> , p = 6.93 × 10 ^⁻ □), and asthma ( <i>PCDH15</i> , p = 5.6 × 10 ^⁻ ¹□), while also identifying novel loci associated with asthma severity.</p><p><strong>Conclusion: </strong>We present the acquisition and quality of genetic and disease-associated data and present an analytical framework for using this resource. In partnership with a community advisory council, we have co-developed a valuable framework for data use and future research.</p><p><strong>Graphical abstract: </strong></p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974803/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wildfire Smoke Exposure is Associated with Decreased Sperm Concentration and Total Motile Sperm Count.","authors":"Lillian X Lindell, Sarah K Holt, Erin Petersen, Navya Gunaje, Arash Amighi, Amanda Haack, Anthony Bui, Ryan Nasseri, Theodore Crisostomo-Wynne, Catherine J Karr, Charles H Muller, Thomas J Walsh, Tristan M Nicholson","doi":"10.1101/2025.03.09.25323436","DOIUrl":"https://doi.org/10.1101/2025.03.09.25323436","url":null,"abstract":"<p><strong>Objective: </strong>As wildfires become more prevalent, their impact on fertility warrants evaluation. We aimed to examine the impact of smoke exposure on semen analysis parameters of intrauterine insemination patients in the greater Seattle, WA area. We hypothesized that wildfire smoke exposure was associated with a decline in total motile sperm count.</p><p><strong>Design: </strong>Retrospective cohort study.</p><p><strong>Subjects: </strong>Patients undergoing fertility treatments at the University of Washington in 2018-2022.</p><p><strong>Exposure: </strong>Subjects were exposed to seasonal wildfire events in the fall of 2018, 2020, and 2022. Pre-exposure semen was a diagnostic fresh sample prior to each respective wildfire event while post-exposure semen was taken at time of intrauterine insemination (IUI) during the wildfire smoke exposure windows. All subjects acted as their own controls in a paired pre-post analysis.</p><p><strong>Main outcome measures: </strong>Primary outcome measure was total motile sperm count; secondary outcomes measures are semen volume, sperm concentration, total sperm count, total progressively motile sperm count, percent motile sperm, percent progressively motile sperm.</p><p><strong>Results: </strong>We identified 84 subjects who underwent IUI across the 2018 (n = 27), 2020 (n = 30), and 2022 (n = 27) wildfire smoke events. Median time between initial semen analysis and semen analysis for IUI was 4 months. We observed a decline in sperm concentration, total sperm count, total motile sperm count, and total progressively motile sperm count. We also observed an increase in percent progressively motile sperm. These trends did not differ across event year.</p><p><strong>Conclusions: </strong>Our results are consistent with a prior small study demonstrating that wildfire smoke exposure is associated with declines in sperm quality. These findings highlight the need for further research on the effects of wildfire smoke exposure on human sperm and fertility treatments, especially as smoke exposures are expected to increase with climate change.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11952483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143757257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}