Pub Date : 2026-02-01DOI: 10.64898/2026.01.28.26344973
Oz Kilim, Orsolya Pipek, Zsofia Sztupinszki, Ariana Huebner, Miklos Diossy, Aurel Prosz, David Moore, Mariam Jamal-Hanjani, Allan Hackshaw, Janos Fillinger, Judit Moldvay, Istvan Csabai, Charles Swanton, Zoltan Szallasi
The standard treatment for stage I lung adenocarcinoma is surgical resection, in most cases without additional systemic adjuvant treatment. A significant proportion of stage I cases recur with a less than 50% 5-year survival rate. There are clinical data suggesting that adjuvant treatment may improve survival in such recurrent cases. However, previously evaluated predictors such as the IASLC grading system from histological sections and transcriptomic profiles have not been sufficiently accurate and consistent for risk stratification and to guide therapeutic interventions. We hypothesized that these previously investigated diverse diagnostic measurements carry complementary information that may provide higher prognostic power when combined. Here we describe a multimodal deep learning method, PATH-ORACLE. This biomarker is built on top of the prospectively validated transcriptomic-based ORACLE score with the addition of routine histological sections processed by pre-trained foundation models. PATH-ORACLE predicts recurrence with an accuracy of over 85% in two independent cohorts. Given further validation this predictor could be used to prioritize stage IB patients for adjuvant chemotherapy in a more consistent fashion. Furthermore, for stage IA cases, PATH-ORACLE, combined with liquid biopsy-based monitoring may help identify high-risk patients suitable for adjuvant targeted therapy.
{"title":"A multimodal AI biomarker PATH-ORACLE improves prediction of recurrence in stage I lung adenocarcinoma.","authors":"Oz Kilim, Orsolya Pipek, Zsofia Sztupinszki, Ariana Huebner, Miklos Diossy, Aurel Prosz, David Moore, Mariam Jamal-Hanjani, Allan Hackshaw, Janos Fillinger, Judit Moldvay, Istvan Csabai, Charles Swanton, Zoltan Szallasi","doi":"10.64898/2026.01.28.26344973","DOIUrl":"https://doi.org/10.64898/2026.01.28.26344973","url":null,"abstract":"<p><p>The standard treatment for stage I lung adenocarcinoma is surgical resection, in most cases without additional systemic adjuvant treatment. A significant proportion of stage I cases recur with a less than 50% 5-year survival rate. There are clinical data suggesting that adjuvant treatment may improve survival in such recurrent cases. However, previously evaluated predictors such as the IASLC grading system from histological sections and transcriptomic profiles have not been sufficiently accurate and consistent for risk stratification and to guide therapeutic interventions. We hypothesized that these previously investigated diverse diagnostic measurements carry complementary information that may provide higher prognostic power when combined. Here we describe a multimodal deep learning method, PATH-ORACLE. This biomarker is built on top of the prospectively validated transcriptomic-based ORACLE score with the addition of routine histological sections processed by pre-trained foundation models. PATH-ORACLE predicts recurrence with an accuracy of over 85% in two independent cohorts. Given further validation this predictor could be used to prioritize stage IB patients for adjuvant chemotherapy in a more consistent fashion. Furthermore, for stage IA cases, PATH-ORACLE, combined with liquid biopsy-based monitoring may help identify high-risk patients suitable for adjuvant targeted therapy.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870720/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128216","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}
Pub Date : 2026-02-01DOI: 10.64898/2026.01.29.26345173
Xiaowei Yan, Qiwen Huang, Jiang Li, Hannah Husby, Powell Jose, Pragati Kenkare, Matthew Solomon, Fatima Rodriguez, Adrian M Bacong
Background: The 2023 AHA PREVENT (Predicting Risk of Cardiovascular Disease Events) equations were expected to replace the 2013 ACC/AHA Pooled Cohort Equations (PCE) for estimating atherosclerotic cardiovascular disease (ASCVD) risk. The real-world implications of this transition on statin eligibility and disparity are unknown.
Objectives: To evaluate how transitioning from PCE to AHA PREVENT alters statin eligibility across risk thresholds and racial and ethnic subgroups.
Design setting and participants: Retrospective cohort analyses of adults aged 40-75 years without diabetes, LDL-C ≥190 mg/dL, or prior statin use from Sutter Health (2010-2024) and NHANES (2011-2020). Ten-year ASCVD risk was estimated using both equations. Weighted analyses were applied to NHANES data.
Main outcomes and measures: Statin eligibility at PREVENT-ASCVD thresholds (3%, 4%, 5%, 6%, 7.5%) compared with PCE ≥7.5%, and the proportion of individuals reclassified below PREVENT-ASCVD thresholds.
Results: Among 229,839 Sutter Health patients (mean age 53.7 years; 53.8% women), 22.3% had PCE risk ≥7.5%. Among individuals above PREVENT-ASCVD 5% threshold level (18.0% in the cohort) 94.7% also met PCE criteria. However, 6.3% (11,866) would lose eligibility, disproportionately affecting non-Hispanic Black adults (18.7%) compared with non-Hispanic Asian adults (3.3%) among individuals who were below PREVENT-ASCVD 5% threshold. In NHANES (n=3,226; representing 32.7 million adults), 9.4% overall and 21.7% of non-Hispanic Black adults with PCE ≥7.5% lost eligibility at PREVENT-ASCVD 5% threshold level.
Conclusions: Transitioning from PCE to PREVENT recalibrates statin eligibility and may disproportionately affect non-Hispanic Black adults. Disparity-focused monitoring is essential for clinical implementation of this new model.
{"title":"Statin Eligibility Disparities with Transition from the Pooled Cohort Equations to the AHA PREVENT.","authors":"Xiaowei Yan, Qiwen Huang, Jiang Li, Hannah Husby, Powell Jose, Pragati Kenkare, Matthew Solomon, Fatima Rodriguez, Adrian M Bacong","doi":"10.64898/2026.01.29.26345173","DOIUrl":"https://doi.org/10.64898/2026.01.29.26345173","url":null,"abstract":"<p><strong>Background: </strong>The 2023 AHA PREVENT (Predicting Risk of Cardiovascular Disease Events) equations were expected to replace the 2013 ACC/AHA Pooled Cohort Equations (PCE) for estimating atherosclerotic cardiovascular disease (ASCVD) risk. The real-world implications of this transition on statin eligibility and disparity are unknown.</p><p><strong>Objectives: </strong>To evaluate how transitioning from PCE to AHA PREVENT alters statin eligibility across risk thresholds and racial and ethnic subgroups.</p><p><strong>Design setting and participants: </strong>Retrospective cohort analyses of adults aged 40-75 years without diabetes, LDL-C ≥190 mg/dL, or prior statin use from Sutter Health (2010-2024) and NHANES (2011-2020). Ten-year ASCVD risk was estimated using both equations. Weighted analyses were applied to NHANES data.</p><p><strong>Main outcomes and measures: </strong>Statin eligibility at PREVENT-ASCVD thresholds (3%, 4%, 5%, 6%, 7.5%) compared with PCE ≥7.5%, and the proportion of individuals reclassified below PREVENT-ASCVD thresholds.</p><p><strong>Results: </strong>Among 229,839 Sutter Health patients (mean age 53.7 years; 53.8% women), 22.3% had PCE risk ≥7.5%. Among individuals above PREVENT-ASCVD 5% threshold level (18.0% in the cohort) 94.7% also met PCE criteria. However, 6.3% (11,866) would lose eligibility, disproportionately affecting non-Hispanic Black adults (18.7%) compared with non-Hispanic Asian adults (3.3%) among individuals who were below PREVENT-ASCVD 5% threshold. In NHANES (n=3,226; representing 32.7 million adults), 9.4% overall and 21.7% of non-Hispanic Black adults with PCE ≥7.5% lost eligibility at PREVENT-ASCVD 5% threshold level.</p><p><strong>Conclusions: </strong>Transitioning from PCE to PREVENT recalibrates statin eligibility and may disproportionately affect non-Hispanic Black adults. Disparity-focused monitoring is essential for clinical implementation of this new model.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128033","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}
Pub Date : 2026-02-01DOI: 10.64898/2026.01.30.26344974
Han Yu, Sitki Cem Parlar, Konstantin Senkevich, Emma N Somerville, Zhao Zhang, Lang Liu, Meron Teferra, Jamil Ahmad, Farnaz Asayesh, Guy A Rouleau, Ziv Gan-Or
Background: The SLC25A46 gene encodes a mitochondrial carrier protein previously implicated in neuropathy and optic atrophy. Biallelic variants in SLC25A46 have been described in patients with Parkinson's disease (PD) with optic atrophy, but the evidence supporting a role in PD remains limited.
Objective: To assess whether SLC25A46 variants contribute to PD, REM sleep behavior disorder (RBD), or Dementia with Lewy Bodies (DLB).
Methods: We examined common variants using four representative PD genome-wide association studies (GWAS) and an RBD GWAS and applied Summary-data-based Mendelian Randomization (SMR) to evaluate whether genetically regulated expression of SLC25A46 shows a causal association with the risk of PD or RBD. Rare variant analyses were conducted in four cohorts of European descent: Accelerated Medicines Partnership: Parkinson's Disease (AMP-PD) PD (3,051 PD, 3,667 controls), UK Biobank (3,267 PD, 14,939 proxy, 54,800 controls), RBD (1,376 RBD, 2,580 controls), and AMP-PD DLB (2,605 DLB, 1,894 controls). Optimal Sequence Kernel Association test (SKAT-O) and meta-analysis were used to assess rare variants.
Results: No associations were observed between SLC25A46 variants and PD, RBD, or DLB. SMR analyses revealed no evidence supporting a causal relationship between SLC25A46 expression and PD or RBD risk. Rare variant burden analyses did not identify significant associations after multiple-testing correction across cohorts or meta-analyses.
Conclusion: SLC25A46 variants showed no evidence of association, suggesting the gene does not play a major role in PD, RBD, or DLB risk.
{"title":"Lack of genetic evidence for a role of SLC25A46 in alpha-synucleinopathies.","authors":"Han Yu, Sitki Cem Parlar, Konstantin Senkevich, Emma N Somerville, Zhao Zhang, Lang Liu, Meron Teferra, Jamil Ahmad, Farnaz Asayesh, Guy A Rouleau, Ziv Gan-Or","doi":"10.64898/2026.01.30.26344974","DOIUrl":"https://doi.org/10.64898/2026.01.30.26344974","url":null,"abstract":"<p><strong>Background: </strong>The <i>SLC25A46</i> gene encodes a mitochondrial carrier protein previously implicated in neuropathy and optic atrophy. Biallelic variants in <i>SLC25A46</i> have been described in patients with Parkinson's disease (PD) with optic atrophy, but the evidence supporting a role in PD remains limited.</p><p><strong>Objective: </strong>To assess whether <i>SLC25A46</i> variants contribute to PD, REM sleep behavior disorder (RBD), or Dementia with Lewy Bodies (DLB).</p><p><strong>Methods: </strong>We examined common variants using four representative PD genome-wide association studies (GWAS) and an RBD GWAS and applied Summary-data-based Mendelian Randomization (SMR) to evaluate whether genetically regulated expression of <i>SLC25A46</i> shows a causal association with the risk of PD or RBD. Rare variant analyses were conducted in four cohorts of European descent: Accelerated Medicines Partnership: Parkinson's Disease (AMP-PD) PD (3,051 PD, 3,667 controls), UK Biobank (3,267 PD, 14,939 proxy, 54,800 controls), RBD (1,376 RBD, 2,580 controls), and AMP-PD DLB (2,605 DLB, 1,894 controls). Optimal Sequence Kernel Association test (SKAT-O) and meta-analysis were used to assess rare variants.</p><p><strong>Results: </strong>No associations were observed between <i>SLC25A46</i> variants and PD, RBD, or DLB. SMR analyses revealed no evidence supporting a causal relationship between <i>SLC25A46</i> expression and PD or RBD risk. Rare variant burden analyses did not identify significant associations after multiple-testing correction across cohorts or meta-analyses.</p><p><strong>Conclusion: </strong><i>SLC25A46</i> variants showed no evidence of association, suggesting the gene does not play a major role in PD, RBD, or DLB risk.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128268","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.29.26345179
John V Pluvinage, David Acero-Garces, Giacomo Greco, Carson E Moseley, Sukhman Sidhu, Kelsey C Zorn, Sravani Kondapavulur, Megan Richie, Vanja Douglas, Sonam Mohan, John Neely, Stefano Masciocchi, Pietro Businaro, Alexis García Sarreón, Ariadna Gifreu, Krista McCutcheon, Colette Caspar, Colin Zamecnik, Asritha Tubati, Andoni I Asencor, Madina Tugizova, Martineau Louine, Leah Zuroff, Josiah Gerdts, Mary Karalius, Alyssa Nylander, Max Liu, Iyas Daghlas, Leena Suleiman, Todd Nguyen, Benjamin Meyer, Karen Ibarra, Felicia Chow, Alexandra Galati, Yair Mina, Camilo Toro, Min Kang, Maulik Shah, Elan L Guterman, Catherine G Suen, Chu-Yueh Guo, Carolyn Bevan, Sarah F Wesley, Kathryn Kvam, Sydney Lee, Ahmed Abdelhak, Thomas Martin, Yun-Han Huang, Sarah B Berman, Jenny Linnoila, John Engstrom, Andrew McCaddon, Ari J Green, Ralph Green, Bruce Cree, Stephen Hauser, Joseph L DeRisi, Samuel J Pleasure, Jeffrey M Gelfand, Gary Álvarez Bravo, Matteo Gastaldi, Carlos A Pardo, Michael R Wilson
Background: Disorders affecting the spinal cord (myelopathies) can cause severe disability. Despite diagnostic advances, approximately 12-18% of myelopathy cases continue to elude an etiological diagnosis, hampering effective treatment.
Methods: This retrospective, multicenter, tertiary care cohort study conducted from 2014 to 2025 evaluated archived biofluids from patients with IM, known autoimmune myelitis, or other neurological diseases (ONDs). Proteome-wide phage display was used to discover novel autoantibodies. Targeted immunoassays were used to screen for a candidate autoantibody. Downstream metabolites were measured in the cerebrospinal fluid (CSF).
Results: Autoantibodies targeting the transcobalamin receptor (CD320) responsible for cellular transport of vitamin B12 were identified in 18 out of 32 IM patients (56%) in a discovery cohort. Bioactive B12 concentration was decreased in the CSF of anti-CD320 positive patients compared to OND controls ( P = 0.0273), indicative of autoimmune B12 central deficiency (ABCD). Compared to anti-CD320 negative IM cases, anti-CD320 positive IM cases demonstrated a higher frequency of subacute time course (56% vs 7%, P = 0.008), normal CSF profile (83% vs 50%, P = 0.044), and dorsolateral spinal cord abnormalities on magnetic resonance imaging (MRI) (61% vs 7%, P = 0.003). In two independent validation cohorts comprising 94 and 25 patients with IM, anti-CD320 was detected in 43 (46%) and 12 (48%) patients, respectively. Comorbid anti-CD320 was detected in a smaller proportion of patients with other known autoimmune etiologies of myelopathy. Five anti-CD320 positive IM patients received B12 supplementation with or without concurrent immunosuppression, and four out of five clinically improved.
Conclusions: ABCD is associated with a substantial proportion of IM. Screening for anti-CD320 followed by metabolic confirmation of a CNS-restricted B12 deficiency may be considered in the diagnostic evaluation of myelopathy.
{"title":"Anti-CD320 Autoantibodies and Central Nervous System Vitamin B12 Deficiency in Idiopathic Myelopathy.","authors":"John V Pluvinage, David Acero-Garces, Giacomo Greco, Carson E Moseley, Sukhman Sidhu, Kelsey C Zorn, Sravani Kondapavulur, Megan Richie, Vanja Douglas, Sonam Mohan, John Neely, Stefano Masciocchi, Pietro Businaro, Alexis García Sarreón, Ariadna Gifreu, Krista McCutcheon, Colette Caspar, Colin Zamecnik, Asritha Tubati, Andoni I Asencor, Madina Tugizova, Martineau Louine, Leah Zuroff, Josiah Gerdts, Mary Karalius, Alyssa Nylander, Max Liu, Iyas Daghlas, Leena Suleiman, Todd Nguyen, Benjamin Meyer, Karen Ibarra, Felicia Chow, Alexandra Galati, Yair Mina, Camilo Toro, Min Kang, Maulik Shah, Elan L Guterman, Catherine G Suen, Chu-Yueh Guo, Carolyn Bevan, Sarah F Wesley, Kathryn Kvam, Sydney Lee, Ahmed Abdelhak, Thomas Martin, Yun-Han Huang, Sarah B Berman, Jenny Linnoila, John Engstrom, Andrew McCaddon, Ari J Green, Ralph Green, Bruce Cree, Stephen Hauser, Joseph L DeRisi, Samuel J Pleasure, Jeffrey M Gelfand, Gary Álvarez Bravo, Matteo Gastaldi, Carlos A Pardo, Michael R Wilson","doi":"10.64898/2026.01.29.26345179","DOIUrl":"https://doi.org/10.64898/2026.01.29.26345179","url":null,"abstract":"<p><strong>Background: </strong>Disorders affecting the spinal cord (myelopathies) can cause severe disability. Despite diagnostic advances, approximately 12-18% of myelopathy cases continue to elude an etiological diagnosis, hampering effective treatment.</p><p><strong>Methods: </strong>This retrospective, multicenter, tertiary care cohort study conducted from 2014 to 2025 evaluated archived biofluids from patients with IM, known autoimmune myelitis, or other neurological diseases (ONDs). Proteome-wide phage display was used to discover novel autoantibodies. Targeted immunoassays were used to screen for a candidate autoantibody. Downstream metabolites were measured in the cerebrospinal fluid (CSF).</p><p><strong>Results: </strong>Autoantibodies targeting the transcobalamin receptor (CD320) responsible for cellular transport of vitamin B12 were identified in 18 out of 32 IM patients (56%) in a discovery cohort. Bioactive B12 concentration was decreased in the CSF of anti-CD320 positive patients compared to OND controls ( <i>P</i> = 0.0273), indicative of autoimmune B12 central deficiency (ABCD). Compared to anti-CD320 negative IM cases, anti-CD320 positive IM cases demonstrated a higher frequency of subacute time course (56% vs 7%, <i>P</i> = 0.008), normal CSF profile (83% vs 50%, <i>P</i> = 0.044), and dorsolateral spinal cord abnormalities on magnetic resonance imaging (MRI) (61% vs 7%, <i>P</i> = 0.003). In two independent validation cohorts comprising 94 and 25 patients with IM, anti-CD320 was detected in 43 (46%) and 12 (48%) patients, respectively. Comorbid anti-CD320 was detected in a smaller proportion of patients with other known autoimmune etiologies of myelopathy. Five anti-CD320 positive IM patients received B12 supplementation with or without concurrent immunosuppression, and four out of five clinically improved.</p><p><strong>Conclusions: </strong>ABCD is associated with a substantial proportion of IM. Screening for anti-CD320 followed by metabolic confirmation of a CNS-restricted B12 deficiency may be considered in the diagnostic evaluation of myelopathy.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128019","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.13.26344041
Tomisin Adebari, Viola Fanfani, Marouen Ben Guebila, Derrick DeConti, Katherine Hoff Shutta, Camila M Lopes-Ramos, Lauren Hsu, Dawn L DeMeo, John Quackenbush, Tara Eicher
Background: Glioblastoma multiforme (GBM) is an aggressive brain tumor that is notoriously resistant to treatment, with an average survival time of 17 months. While the overall outcome is poor for both males and females, sex differences in GBM incidence and outcome suggest sex-specific biological mechanisms underlie tumorigenesis. In contrast, low-grade glioma (LGG) is a less aggressive brain tumor that tends to have a better prognosis and a longer survival time.
Methods: To understand mechanisms contributing to treatment resistance in GBM in both males and females, we inferred gene regulatory networks (GRNs) for males and females with LGG and GBM using RNA-seq data from The Cancer Genome Atlas (TCGA). We analyzed these to identify both sex-specific and sex-stratified gene regulation in GBM.
Results: We found few sex-specific differences in gene regulation in individuals with LGG, consistent with the lack of evidence for significant clinical endpoints dependent on sex. However, in GBM-we found sex-specific differential targeting of several pathways, including hypoxia and related pathways (carbohydrate metabolism, innate immune processes, and extracellular matrix pathways) known to be dysregulated in hypoxic conditions. In comparing between individuals with GBM, we found that females exhibited a greater degree of co-regulation between hypoxia with the aforementioned downstream pathways than did males.
Conclusions: Our results suggest that dysregulation of hypoxia-related pathways in GBM plays a female-specific role in resistance to treatment and overall outcomes.
{"title":"Gene regulatory network analysis identifies dysregulation of hypoxia pathways as contributing to glioblastoma multiforme treatment resistance in females.","authors":"Tomisin Adebari, Viola Fanfani, Marouen Ben Guebila, Derrick DeConti, Katherine Hoff Shutta, Camila M Lopes-Ramos, Lauren Hsu, Dawn L DeMeo, John Quackenbush, Tara Eicher","doi":"10.64898/2026.01.13.26344041","DOIUrl":"https://doi.org/10.64898/2026.01.13.26344041","url":null,"abstract":"<p><strong>Background: </strong>Glioblastoma multiforme (GBM) is an aggressive brain tumor that is notoriously resistant to treatment, with an average survival time of 17 months. While the overall outcome is poor for both males and females, sex differences in GBM incidence and outcome suggest sex-specific biological mechanisms underlie tumorigenesis. In contrast, low-grade glioma (LGG) is a less aggressive brain tumor that tends to have a better prognosis and a longer survival time.</p><p><strong>Methods: </strong>To understand mechanisms contributing to treatment resistance in GBM in both males and females, we inferred gene regulatory networks (GRNs) for males and females with LGG and GBM using RNA-seq data from The Cancer Genome Atlas (TCGA). We analyzed these to identify both sex-specific and sex-stratified gene regulation in GBM.</p><p><strong>Results: </strong>We found few sex-specific differences in gene regulation in individuals with LGG, consistent with the lack of evidence for significant clinical endpoints dependent on sex. However, in GBM-we found sex-specific differential targeting of several pathways, including hypoxia and related pathways (carbohydrate metabolism, innate immune processes, and extracellular matrix pathways) known to be dysregulated in hypoxic conditions. In comparing between individuals with GBM, we found that females exhibited a greater degree of co-regulation between hypoxia with the aforementioned downstream pathways than did males.</p><p><strong>Conclusions: </strong>Our results suggest that dysregulation of hypoxia-related pathways in GBM plays a female-specific role in resistance to treatment and overall outcomes.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128023","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.29.26344899
Evelynne S Fulda, Bennett J Waxse, Slavina B Goleva, Tam C Tran, Henry J Taylor, Caitlin P Bailey, Dana L Wolff-Hughes, Huan Mo, Chenjie Zeng, Jacob M Keaton, Tracey M Ferrara, Anya Topiwala, Aiden Doherty, Joshua C Denny
<p><strong>Background: </strong>Insufficient physical activity (PA) is associated with higher risk of morbidity and premature mortality. Wearable devices offer a scalable, objective measurement of physical activity, but most studies reduce these data to a single activity metric measured over a fixed 7-day period. We compared different wearable-derived phenotyping approaches to understand their impact on activity-disease associations.</p><p><strong>Methods: </strong>We analyzed 11 million days of Fitbit data from 29,351 participants in the <i>All of Us</i> Research Program, deriving four daily activity metrics (step count, peak 1-min cadence, peak 30-min cadence, and heart rate per step) across five time-windows (1-day, 1-week, 1-month, 6-months, 1-year). We performed phenome-wide analyses on >700 incident and >1,300 prevalent disease outcomes identified from linked electronic health records.</p><p><strong>Findings: </strong>Among participants with EHR and Fitbit data (mean age 57.3 years, 69% female, 47% with >1 year of Fitbit data), all 20 phenotypes were highly correlated (median Pearson r = 0.71). Longer measurement windows yielded stronger and more stable associations, with 1-year step count associated with 373 prevalent and 37 incident outcomes (versus 231 and 17 for 1-day step count) after Bonferroni-correction, including novel associations with chronic pain syndrome, SARS-CoV-2, and autoimmune disease. Differences between prevalent and incident associations suggest that activity metrics can act as both early markers of disease or risk factors.</p><p><strong>Interpretation: </strong>These findings highlight how large-scale, longitudinal wearable data can advance understanding of health and disease and inform scalable approaches for clinical risk stratification.</p><p><strong>Funding: </strong>National Institutes of Health Intramural Research Program, Wellcome Trust.</p><p><strong>Research in context: </strong><b>Evidence before this study:</b> Low levels of physical activity relate to numerous health outcomes. However, prior studies are limited by a focus on disease prevalence and by a lack of examination across a broad range of health outcomes. Further, the strength of these associations, depends on how physical activity is measured. Prior work shows that wearable devices capture activity more reliably than self-report surveys and typically yield stronger associations with disease risk. Most wearable-based studies rely on short monitoring windows: often seven days or fewer. To our knowledge, no study has systematically evaluated how the duration of wearable-based phenotyping influences estimates of disease risk.To explore this, we searched PubMed using the terms "wearable phenotyping" AND "disease risk", resulting in 48 articles published between 2016 and 2025. Although some studies compared different wearable-derived phenotypes (e.g., step count vs. sleep duration) or explored how the number of observed days affects data quality, none dir
{"title":"11 million days of longitudinal wearable data reveal novel future health insights.","authors":"Evelynne S Fulda, Bennett J Waxse, Slavina B Goleva, Tam C Tran, Henry J Taylor, Caitlin P Bailey, Dana L Wolff-Hughes, Huan Mo, Chenjie Zeng, Jacob M Keaton, Tracey M Ferrara, Anya Topiwala, Aiden Doherty, Joshua C Denny","doi":"10.64898/2026.01.29.26344899","DOIUrl":"https://doi.org/10.64898/2026.01.29.26344899","url":null,"abstract":"<p><strong>Background: </strong>Insufficient physical activity (PA) is associated with higher risk of morbidity and premature mortality. Wearable devices offer a scalable, objective measurement of physical activity, but most studies reduce these data to a single activity metric measured over a fixed 7-day period. We compared different wearable-derived phenotyping approaches to understand their impact on activity-disease associations.</p><p><strong>Methods: </strong>We analyzed 11 million days of Fitbit data from 29,351 participants in the <i>All of Us</i> Research Program, deriving four daily activity metrics (step count, peak 1-min cadence, peak 30-min cadence, and heart rate per step) across five time-windows (1-day, 1-week, 1-month, 6-months, 1-year). We performed phenome-wide analyses on >700 incident and >1,300 prevalent disease outcomes identified from linked electronic health records.</p><p><strong>Findings: </strong>Among participants with EHR and Fitbit data (mean age 57.3 years, 69% female, 47% with >1 year of Fitbit data), all 20 phenotypes were highly correlated (median Pearson r = 0.71). Longer measurement windows yielded stronger and more stable associations, with 1-year step count associated with 373 prevalent and 37 incident outcomes (versus 231 and 17 for 1-day step count) after Bonferroni-correction, including novel associations with chronic pain syndrome, SARS-CoV-2, and autoimmune disease. Differences between prevalent and incident associations suggest that activity metrics can act as both early markers of disease or risk factors.</p><p><strong>Interpretation: </strong>These findings highlight how large-scale, longitudinal wearable data can advance understanding of health and disease and inform scalable approaches for clinical risk stratification.</p><p><strong>Funding: </strong>National Institutes of Health Intramural Research Program, Wellcome Trust.</p><p><strong>Research in context: </strong><b>Evidence before this study:</b> Low levels of physical activity relate to numerous health outcomes. However, prior studies are limited by a focus on disease prevalence and by a lack of examination across a broad range of health outcomes. Further, the strength of these associations, depends on how physical activity is measured. Prior work shows that wearable devices capture activity more reliably than self-report surveys and typically yield stronger associations with disease risk. Most wearable-based studies rely on short monitoring windows: often seven days or fewer. To our knowledge, no study has systematically evaluated how the duration of wearable-based phenotyping influences estimates of disease risk.To explore this, we searched PubMed using the terms \"wearable phenotyping\" AND \"disease risk\", resulting in 48 articles published between 2016 and 2025. Although some studies compared different wearable-derived phenotypes (e.g., step count vs. sleep duration) or explored how the number of observed days affects data quality, none dir","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128255","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.27.26344860
Christiana Westlin, Cristina Bleier, Andrew J Guthrie, Sara A Finkelstein, Julie Maggio, Jessica Ranford, Julie MacLean, Ellen Godena, Daniel Millstein, Jennifer Freeburn, Caitlin Adams, Christopher D Stephen, Ibai Diez, David L Perez
Background: Clinical trajectories in functional neurological disorder (FND) are variable, and the mechanisms underlying this heterogeneity remain poorly understood.
Objective: This longitudinal study examined resting-state functional connectivity predictors and mechanisms of symptom change in FND.
Methods: Thirty-two adults with FND (motor and/or seizure phenotypes) completed baseline questionnaires and a functional MRI (fMRI) session, followed by naturalistic treatment for 6.8±0.8 months. All participants completed follow-up questionnaires; 28 individuals completed a follow-up fMRI. At each timepoint, three graph-theory network metrics of functional connectivity were computed: weighted-degree (centrality), integration ( between-network connectivity), and segregation ( within-network connectivity). Analyses adjusted for age, sex, anti-depressants, head motion, time between sessions, and baseline score-of-interest, with cluster-wise correction. Results were contextualized against 50 age-, sex-, and head motion-matched healthy controls (HCs).
Results: Based on patient-reported Clinical Global Impression of Improvement, 59.4% improved, 31.3% were unchanged, and 9.3% worsened. Psychometric scores of core FND symptoms and non-core physical symptoms showed variable trajectories, with no group-level changes. Greater improvement in core FND symptoms was associated with higher baseline between-network integrated connectivity and reduced integration longitudinally within salience, frontoparietal, and default mode network regions. Right anterior insula integration emerged as a prognostic marker and mechanistic site of reorganization, with the most improved participants showing elevated baseline integration compared to HCs. Increased baseline within-network segregated connectivity in dorsal attention network regions correlated with non-core physical symptom improvement. Findings remained significant adjusting for FND phenotype.
Conclusions: This study identified large-scale network interactions as potential prognostic and mechanistically-relevant sites of reorganization related to symptom change in FND.
{"title":"Functional Connectivity Predictors and Mechanisms of Symptom Change in Functional Neurological Disorder.","authors":"Christiana Westlin, Cristina Bleier, Andrew J Guthrie, Sara A Finkelstein, Julie Maggio, Jessica Ranford, Julie MacLean, Ellen Godena, Daniel Millstein, Jennifer Freeburn, Caitlin Adams, Christopher D Stephen, Ibai Diez, David L Perez","doi":"10.64898/2026.01.27.26344860","DOIUrl":"https://doi.org/10.64898/2026.01.27.26344860","url":null,"abstract":"<p><strong>Background: </strong>Clinical trajectories in functional neurological disorder (FND) are variable, and the mechanisms underlying this heterogeneity remain poorly understood.</p><p><strong>Objective: </strong>This longitudinal study examined resting-state functional connectivity predictors and mechanisms of symptom change in FND.</p><p><strong>Methods: </strong>Thirty-two adults with FND (motor and/or seizure phenotypes) completed baseline questionnaires and a functional MRI (fMRI) session, followed by naturalistic treatment for 6.8±0.8 months. All participants completed follow-up questionnaires; 28 individuals completed a follow-up fMRI. At each timepoint, three graph-theory network metrics of functional connectivity were computed: weighted-degree (centrality), integration ( <i>between-network</i> connectivity), and segregation ( <i>within-network</i> connectivity). Analyses adjusted for age, sex, anti-depressants, head motion, time between sessions, and baseline score-of-interest, with cluster-wise correction. Results were contextualized against 50 age-, sex-, and head motion-matched healthy controls (HCs).</p><p><strong>Results: </strong>Based on patient-reported Clinical Global Impression of Improvement, 59.4% improved, 31.3% were unchanged, and 9.3% worsened. Psychometric scores of core FND symptoms and non-core physical symptoms showed variable trajectories, with no group-level changes. Greater improvement in core FND symptoms was associated with higher baseline <i>between-network</i> integrated connectivity and reduced integration longitudinally within salience, frontoparietal, and default mode network regions. Right anterior insula integration emerged as a prognostic marker and mechanistic site of reorganization, with the most improved participants showing elevated baseline integration compared to HCs. Increased baseline <i>within-network</i> segregated connectivity in dorsal attention network regions correlated with non-core physical symptom improvement. Findings remained significant adjusting for FND phenotype.</p><p><strong>Conclusions: </strong>This study identified large-scale network interactions as potential prognostic and mechanistically-relevant sites of reorganization related to symptom change in FND.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146127585","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}
Pub Date : 2026-01-30DOI: 10.64898/2025.12.19.25342620
Sheng Qian, Kaixuan Luo, Xiaotong Sun, Wesley Crouse, Lifan Liang, Jing Gu, Matthew Stephens, Siming Zhao, Xin He
Recent studies showed that expression QTLs, even from trait-related tissues, explained a small fraction of complex trait heritability. A natural strategy to close this gap is to incorporate molecular QTLs (molQTLs) beyond gene expression, across diverse tissue/cellular contexts. Yet, integrating such QTL data presents analytical challenges. Molecular traits often share QTLs or have QTLs in high LD, complicating the attribution of GWAS signals to specific molecular traits. Our simulations showed that commonly used colocalization and TWAS methods have highly inflated false positive rates in such settings. Building on our earlier work, we developed multi-group causal TWAS (M-cTWAS), for integrating QTLs of different modalities and contexts. M-cTWAS is able to estimate the contribution of each group of molQTLs to the trait heritability, and using such information, identifies the causal molecular traits, informing the modalities and contexts through which genetic variations act on the phenotype. M-cTWAS showed improved control of false discoveries than commonly used methods. Using M-cTWAS, we found that QTLs of multiple modalities greatly increased the explained heritability compared to using eQTLs alone, and enabled the discovery of many more risk genes of a range of complex traits. In conclusion, M-cTWAS effectively integrates diverse molecular QTLs with GWAS to enable causal gene discovery.
{"title":"Integrating multi-omics and multi-context QTL data with GWAS reveals the genetic architecture of complex traits and improves the discovery of risk genes.","authors":"Sheng Qian, Kaixuan Luo, Xiaotong Sun, Wesley Crouse, Lifan Liang, Jing Gu, Matthew Stephens, Siming Zhao, Xin He","doi":"10.64898/2025.12.19.25342620","DOIUrl":"https://doi.org/10.64898/2025.12.19.25342620","url":null,"abstract":"<p><p>Recent studies showed that expression QTLs, even from trait-related tissues, explained a small fraction of complex trait heritability. A natural strategy to close this gap is to incorporate molecular QTLs (molQTLs) beyond gene expression, across diverse tissue/cellular contexts. Yet, integrating such QTL data presents analytical challenges. Molecular traits often share QTLs or have QTLs in high LD, complicating the attribution of GWAS signals to specific molecular traits. Our simulations showed that commonly used colocalization and TWAS methods have highly inflated false positive rates in such settings. Building on our earlier work, we developed multi-group causal TWAS (M-cTWAS), for integrating QTLs of different modalities and contexts. M-cTWAS is able to estimate the contribution of each group of molQTLs to the trait heritability, and using such information, identifies the causal molecular traits, informing the modalities and contexts through which genetic variations act on the phenotype. M-cTWAS showed improved control of false discoveries than commonly used methods. Using M-cTWAS, we found that QTLs of multiple modalities greatly increased the explained heritability compared to using eQTLs alone, and enabled the discovery of many more risk genes of a range of complex traits. In conclusion, M-cTWAS effectively integrates diverse molecular QTLs with GWAS to enable causal gene discovery.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128189","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.02.26343331
Emmanuel Fle Chea
<p><strong>Background: </strong>The ATN (Amyloid/Tau/Neurodegeneration) framework provides a theory-driven approach to Alzheimer's disease (AD) classification using binary biomarker cutoffs, while unsupervised machine learning offers data-driven phenotyping. The concordance between these approaches in population-representative samples remains incompletely characterized.</p><p><strong>Objective: </strong>To compare plasma ATN classification with data-driven clustering methods and evaluate their associations with cognitive outcomes in a nationally representative cohort.</p><p><strong>Methods: </strong>We analyzed plasma biomarkers (Abeta42/40 ratio, p-tau181, NfL, GFAP) from 4,465 participants aged >=51 years in the Health and Retirement Study 2016 Venous Blood Study. ATN profiles were classified using literature-based cutoffs. We applied k-means clustering, Gaussian mixture modeling, and variational autoencoder (VAE) dimensionality reduction to identify data-driven biomarker phenotypes. Agreement between ATN and clustering was quantified using adjusted Rand index (ARI) and normalized mutual information (NMI). Longitudinal analyses examined associations with cognitive decline over 4 years (2016-2020).</p><p><strong>Results: </strong>The analytic sample included 4,465 individuals (mean age 69.7+/-10.4 years; 58.7 percent female; 75.8 percent non-Hispanic White). ATN classification yielded 14 profiles, with A+/T-/N- (27.4 percent) and A-/T-/N- (22.6 percent) most prevalent (Figure 2). K-means clustering identified 4 optimal clusters with distinct biomarker signatures. Agreement between ATN and clusters was modest (ARI=0.119, NMI=0.113). Sensitivity analysis excluding GFAP from clustering reduced agreement substantially (ARI=0.03 vs 0.119 with GFAP, 74.5 percent decrease), demonstrating that GFAP accounts for most of the observed concordance between clustering and ATN classification, with only one-third arising from the shared three biomarkers. Additional sensitivity analyses confirmed that k=4 provides finer biomarker resolution than k=3 by retaining biomarker-extreme subgroups, and that Cluster 4 represents a stable biological structure across distance metrics despite its small size. Cluster 1 (n=51, 1.2 percent) showed severe pathology; Cluster 3 (n=3,479, 78.6 percent) represented the largest and most heterogeneous group, encompassing the broad spectrum of minimal to moderate pathology across all ATN profiles; Cluster 4 (n=14, 0.3 percent) represented a small but stable non-AD biomarker-defined subgroup (Jaccard=0.779). The VAE revealed a localized nonlinear structure. Silhouette values in the latent space are not directly comparable to clustering silhouettes, but the VAE embedding showed clearer local separation, whereas PCA explained more variance (67.1 percent). Both ATN and clusters predicted 4-year cognitive decline (ATN R2=0.024, p<0.001; Clusters R2=0.019, p<0.001).</p><p><strong>Conclusions: </strong>Theory-driven ATN classification and da
{"title":"ATN Classification and Machine-Learned Plasma Biomarker Phenotypes Reveal Distinct Alzheimer's Pathology in a Population-Based Cohort.","authors":"Emmanuel Fle Chea","doi":"10.64898/2026.01.02.26343331","DOIUrl":"10.64898/2026.01.02.26343331","url":null,"abstract":"<p><strong>Background: </strong>The ATN (Amyloid/Tau/Neurodegeneration) framework provides a theory-driven approach to Alzheimer's disease (AD) classification using binary biomarker cutoffs, while unsupervised machine learning offers data-driven phenotyping. The concordance between these approaches in population-representative samples remains incompletely characterized.</p><p><strong>Objective: </strong>To compare plasma ATN classification with data-driven clustering methods and evaluate their associations with cognitive outcomes in a nationally representative cohort.</p><p><strong>Methods: </strong>We analyzed plasma biomarkers (Abeta42/40 ratio, p-tau181, NfL, GFAP) from 4,465 participants aged >=51 years in the Health and Retirement Study 2016 Venous Blood Study. ATN profiles were classified using literature-based cutoffs. We applied k-means clustering, Gaussian mixture modeling, and variational autoencoder (VAE) dimensionality reduction to identify data-driven biomarker phenotypes. Agreement between ATN and clustering was quantified using adjusted Rand index (ARI) and normalized mutual information (NMI). Longitudinal analyses examined associations with cognitive decline over 4 years (2016-2020).</p><p><strong>Results: </strong>The analytic sample included 4,465 individuals (mean age 69.7+/-10.4 years; 58.7 percent female; 75.8 percent non-Hispanic White). ATN classification yielded 14 profiles, with A+/T-/N- (27.4 percent) and A-/T-/N- (22.6 percent) most prevalent (Figure 2). K-means clustering identified 4 optimal clusters with distinct biomarker signatures. Agreement between ATN and clusters was modest (ARI=0.119, NMI=0.113). Sensitivity analysis excluding GFAP from clustering reduced agreement substantially (ARI=0.03 vs 0.119 with GFAP, 74.5 percent decrease), demonstrating that GFAP accounts for most of the observed concordance between clustering and ATN classification, with only one-third arising from the shared three biomarkers. Additional sensitivity analyses confirmed that k=4 provides finer biomarker resolution than k=3 by retaining biomarker-extreme subgroups, and that Cluster 4 represents a stable biological structure across distance metrics despite its small size. Cluster 1 (n=51, 1.2 percent) showed severe pathology; Cluster 3 (n=3,479, 78.6 percent) represented the largest and most heterogeneous group, encompassing the broad spectrum of minimal to moderate pathology across all ATN profiles; Cluster 4 (n=14, 0.3 percent) represented a small but stable non-AD biomarker-defined subgroup (Jaccard=0.779). The VAE revealed a localized nonlinear structure. Silhouette values in the latent space are not directly comparable to clustering silhouettes, but the VAE embedding showed clearer local separation, whereas PCA explained more variance (67.1 percent). Both ATN and clusters predicted 4-year cognitive decline (ATN R2=0.024, p<0.001; Clusters R2=0.019, p<0.001).</p><p><strong>Conclusions: </strong>Theory-driven ATN classification and da","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12803393/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145992367","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}
Pub Date : 2026-01-30DOI: 10.64898/2026.01.28.26345064
Muhammad N Aslam, Danielle Kim Turgeon, Shannon McClintock, Ron Allen, Ananda Sen, James Varani
Introduction: Previous studies have shown that Aquamin ® , a multi-mineral extract from red marine algae, enhances barrier integrity proteins in the human colon. These findings prompted further investigation into Aquamin ® 's effects on gastrointestinal barrier function and permeability.
Methods: Subjects with mild or in remission ulcerative colitis (UC) and healthy controls were enrolled in an open-label trial and received Aquamin ® capsules (800 mg calcium/day) for 90 days. Intestinal permeability was evaluated before and after the 90-day intervention by urinary mannitol excretion after ingestion of a 5 g mannitol solution, with collections across several time intervals (pre-drink, 0-2 h, 2-8 h, and 8-24 h). The primary outcome was the change in mannitol excretion. Serum samples were also collected to assess liver and renal function.
Results: In this pilot study ( NCT04855799 ), which included UC patients and healthy controls (n = 8 per group), baseline urine mannitol levels in the 0-2 h sample were 54% higher in UC patients compared to healthy subjects (p = 0.006). Following 90 days of Aquamin ® supplementation, urinary mannitol levels in UC patients decreased by 28%, 26%, and 41% at the 0-2 h, 2-8 h, and 8-24 h timepoints, respectively; the reduction at the 0-2 h interval reached statistical significance (p = 0.015). Overall, Aquamin ® supplementation reduced total post-intervention mannitol excretion by 29% (p = 0.024). Aquamin ® was well tolerated, with no serious adverse events reported. The serum metabolic panel revealed a modest but statistically significant reduction in alkaline phosphatase levels after 90 days of intervention.
Conclusion: These results provide preliminary evidence that Aquamin ® supplementation beneficially modulates gut barrier function and supports epithelial integrity in UC patients. These findings support further investigation of Aquamin ® as a safe and promising adjunct to current UC management strategies, with potential utility as a barrier therapy in UC.
Summary: Aquamin ® supplementation for 90 days reduced intestinal permeability in ulcerative colitis patients, as measured by urinary mannitol excretion. The intervention was well tolerated, suggesting Aquamin ® may be a safe, promising adjunct for enhancing gut barrier function in UC management.
{"title":"A Multi-Mineral Intervention Improves Intestinal Permeability in Patients with Ulcerative Colitis: Results from a 90-Day Pilot Trial.","authors":"Muhammad N Aslam, Danielle Kim Turgeon, Shannon McClintock, Ron Allen, Ananda Sen, James Varani","doi":"10.64898/2026.01.28.26345064","DOIUrl":"https://doi.org/10.64898/2026.01.28.26345064","url":null,"abstract":"<p><strong>Introduction: </strong>Previous studies have shown that Aquamin <sup>®</sup> , a multi-mineral extract from red marine algae, enhances barrier integrity proteins in the human colon. These findings prompted further investigation into Aquamin <sup>®</sup> 's effects on gastrointestinal barrier function and permeability.</p><p><strong>Methods: </strong>Subjects with mild or in remission ulcerative colitis (UC) and healthy controls were enrolled in an open-label trial and received Aquamin <sup>®</sup> capsules (800 mg calcium/day) for 90 days. Intestinal permeability was evaluated before and after the 90-day intervention by urinary mannitol excretion after ingestion of a 5 g mannitol solution, with collections across several time intervals (pre-drink, 0-2 h, 2-8 h, and 8-24 h). The primary outcome was the change in mannitol excretion. Serum samples were also collected to assess liver and renal function.</p><p><strong>Results: </strong>In this pilot study ( NCT04855799 ), which included UC patients and healthy controls (n = 8 per group), baseline urine mannitol levels in the 0-2 h sample were 54% higher in UC patients compared to healthy subjects (p = 0.006). Following 90 days of Aquamin <sup>®</sup> supplementation, urinary mannitol levels in UC patients decreased by 28%, 26%, and 41% at the 0-2 h, 2-8 h, and 8-24 h timepoints, respectively; the reduction at the 0-2 h interval reached statistical significance (p = 0.015). Overall, Aquamin <sup>®</sup> supplementation reduced total post-intervention mannitol excretion by 29% (p = 0.024). Aquamin <sup>®</sup> was well tolerated, with no serious adverse events reported. The serum metabolic panel revealed a modest but statistically significant reduction in alkaline phosphatase levels after 90 days of intervention.</p><p><strong>Conclusion: </strong>These results provide preliminary evidence that Aquamin <sup>®</sup> supplementation beneficially modulates gut barrier function and supports epithelial integrity in UC patients. These findings support further investigation of Aquamin <sup>®</sup> as a safe and promising adjunct to current UC management strategies, with potential utility as a barrier therapy in UC.</p><p><strong>Summary: </strong>Aquamin <sup>®</sup> supplementation for 90 days reduced intestinal permeability in ulcerative colitis patients, as measured by urinary mannitol excretion. The intervention was well tolerated, suggesting Aquamin <sup>®</sup> may be a safe, promising adjunct for enhancing gut barrier function in UC management.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12870605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146128248","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}