medRxiv : the preprint server for health sciences最新文献

{"title":"Clinical, neuropathological, and biochemical characterization of ALS in a large CHCHD10 R15L family.","authors":"Justin Y Kwan, Christian I Lantz, Vlad A Korobeynikov, Allison Snyder, Xiaoping Huang, Taryn Haselhuhn, Katherine N Dore, Angelo Madruga, Laura E Danielian, Alice B Schindler, Ruth Chia, Memoona Rasheed, Jody Crook, Marcell Szabo, Makayla Portley, Carolyn M Sherer, Monique C King, Tzu-Hsiang Huang, Peter Kosa, Bibiana Bielekova, Michael E Ward, Chris Grunseich, Neil A Shneider, Bryan J Traynor, Derek P Narendra","doi":"10.1101/2025.09.22.25335938","DOIUrl":"10.1101/2025.09.22.25335938","url":null,"abstract":"<p><p>Familial forms of ALS are potential candidates for gene-directed therapies, but many recently identified genes remain poorly characterized. Here, we provide a comprehensive clinical, neuropathological, and biochemical description of fALS caused by the heterozygous p.R15L missense mutation in the gene CHCHD10. Using a cross-sectional study design, we evaluate five affected and nine unaffected individuals from a large seven-generation pedigree with at least 68 affected members. The pedigree suggests a high (68 - 81%) but incomplete disease penetrance. Through cloning of the disease-allele from distant members of the family, we establish the disease haplotype in the family. Notably, the haplotype was distinct from that of a previously reported p.R15L mutation carrier with ALS, demonstrating that the variant is in a mutational hotspot. The clinical presentation was notable for being highly stereotyped; all affected individuals presented with the rare ALS variant Flail Arm Syndrome (FAS; also known as, brachial amyotrophic diplegia or Vulpian-Bernhardt Syndrome), suggesting greater involvement of the cervical spinal cord. Consistently, neuropathology from one family member demonstrated substantially increased CHCHD10 protein aggregation and neuronal loss (though absent TDP-43 pathology) in the cervical vs. lumbar spinal cord. This FAS phenotype could be captured by a simple timed finger tapping task, suggesting potential utility for this task as a clinical biomarker. Additionally, through analysis of fibroblast lines from 12 mutation carriers, isogenic iPSC cells, and a knockin mouse model, we determined that CHCHD10 with the R15L variant is stably expressed and retains substantial function both in cultured cells and <i>in vivo</i>, in contrast to prior reports. Conversely, we find loss of function (LoF) variants are more common in the population but are not associated with a highly penetrant form of ALS in the UK Biobank (31 in controls; 0 in cases). Together, this argues against LoF and in favor of toxic gain-of-function as the mechanism of disease pathogenesis, similar to the myopathy-causing variants in CHCHD10 (p.G58R and p.S59L). Finally, through proteomic analysis of CSF of variant carriers, we identify that CHCHD10 protein levels are elevated approximately 2-fold in mutation carriers, and that affected and unaffected individuals are differentiated by elevation of two neurofilaments: neurofilament light chain (NfL) and Peripherin (PRPH). Collectively, our findings help set the stage for gene-directed therapy for a devasting form of fALS, by establishing the likely disease mechanism and identifying clinical and fluid biomarkers for target engagement and treatment response.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214862","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":"Genome-wide association study of adolescent-onset depression.","authors":"Poppy Z Grimes, Brittany L Mitchell, Katherine N Thompson, Qingkun Deng, Xueyi Shen, Jareth C Wolfe, Jodi T Thomas, Robyn E Wootton, Daniel E Adkins, Saranya Arirangan, Elham Assary, Chris Chatzinakos, Charlotte A Dennison, Swathi Hassan Gangaraju, Andreas Jangmo, Yeongmi Jeong, Siim Kurvits, Qingqin S Li, Ehsan Motazedi, Joonas Naamanka, Thuy-Dung Nguyen, Ilja M Nolte, Vanessa K Ota, Joëlle A Pasman, Mina Shahisavandi, Amy Shakeshaft, John R Shorter, Chloe Slaney, Martin Tesli, Carol A Wang, Uxue Zubizarreta-Arruti, Silvia Alemany, Ole A Andreassen, Helga Ask, Sintia I Belangero, Rosa Bosch, Gerome Breen, Rodrigo A Bressan, Alfonso Buil, Enda M Byrne, Miquel Casas, William E Copeland, Thalia C Eley, Laurie J Hannigan, Catharina A Hartman, Alexandra Havdahl, Ian B Hickie, Golam M Khandaker, Kelli Lehto, Hermine Maes, Nicholas G Martin, Alexander Neumann, Albertine J Oldehinkel, Pedro M Pan, Hong Pan, Craig E Pennell, Roseann E Peterson, Alina Rodriguez, Giovanni A Salum, Tanja Gm Vrijkotte, Robbee Wedow, Andrew Jo Whitehouse, Anita Thapar, Henrik Larsson, Christel M Middeldorp, Andrew McIntosh, Mark J Adams, Yi Lu, Heather C Whalley, Alex Sf Kwong","doi":"10.1101/2025.09.26.25335972","DOIUrl":"https://doi.org/10.1101/2025.09.26.25335972","url":null,"abstract":"<p><p>Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215150","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":"Hemodynamic Oscillations in Mild TBI During Postural Change: An fNIRS Pilot Study.","authors":"Carsi Kim, Andrea Gomez Carillo, Ulas Sunar","doi":"10.1101/2025.09.25.25336687","DOIUrl":"https://doi.org/10.1101/2025.09.25.25336687","url":null,"abstract":"<p><p>We demonstrate that low-frequency oscillations (LFOs) in cerebral hemodynamics, measured by frequency-domain functional near-infrared spectroscopy (FD-fNIRS), reflect altered cerebral hemodynamic oscillations in mild traumatic brain injury (mTBI). In a pilot study of two mTBI and 13 healthy subjects undergoing head-of-bed positional changes, we analyzed total hemoglobin concentration (THC), oxyhemoglobin (HbO), and deoxyhemoglobin (Hb) dynamics using spectral and time-frequency analyses. mTBI measurements exhibited significantly larger postural changes in THC (ΔTHC = 9.49 µM) compared to controls (ΔTHC = 1.03 µM). LFO power was consistently elevated in mTBI across all slow bands (0.01-0.2 Hz), particularly in the Slow-5 band (0.01-0.027 Hz), suggesting dysregulated cerebral vasomotion. Continuous wavelet transform (CWT) confirmed persistent LFO amplification during and after postural transitions. These findings indicate that THC-based LFO measures may serve as early, non-invasive biomarkers of cerebral autoregulatory impairment in mTBI.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215074","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":"Machine Learning Versus Logistic Regression for Propensity Score Estimation: A Benchmark Trial Emulation Against the PARADIGM-HF Randomized Trial.","authors":"Kaicheng Wang, Lindsey A Rosman, Haidong Lu","doi":"10.1101/2025.06.16.25329708","DOIUrl":"10.1101/2025.06.16.25329708","url":null,"abstract":"<p><p>Machine learning (ML) algorithms are increasingly used to estimate propensity score with expectation of improving causal inference. However, the validity of ML-based approaches for confounder selection and adjustment remains unclear. In this study, we emulated the device-stratified secondary analysis of the PARADIGM-HF trial among U.S. veterans with heart failure and implanted cardiac devices from 2016 to 2020. We benchmarked observational estimates from three propensity score approaches against the trial results: (1) logistic regression with pre-specified confounders, (2) generalized boosted models (GBM) using the same pre-specified confounders, and (3) GBM with expanded covariates and automated feature selection. Logistic regression-based propensity score approach yielded estimates closest to the trial (HR = 0.93, 95% CI 0.61-1.42; 23-month RR = 0.86, 95% CI 0.57-1.24 vs. trial HR = 0.81, 95% CI 0.61-1.06). Despite better predictive performance, GBM with pre-specified confounders showed no improvement over the logistic regression approach (HR = 0.97, 95% CI 0.68-1.37; RR = 0.96, 95% CI 0.89-1.98). Notably, GBM with expanded covariates and data-driven automated feature selection substantially increased bias (HR = 0.61, 95% CI 0.30-1.23; RR = 0.69, 95% CI 0.36-1.04). Our findings suggest that ML-based propensity score methods do not inherently improve causal estimation-possibly due to residual confounding from omitted or partially adjusted variables-and may introduce overadjustment bias when combined with automated feature selection, underscoring the importance of careful confounder specification and causal reasoning over algorithmic complexity in causal inference.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532299","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":"Assessment of a zero-shot large language model in measuring documented goals-of-care discussions.","authors":"Robert Y Lee, Kevin S Li, James Sibley, Trevor Cohen, William B Lober, Danae G Dotolo, Erin K Kross","doi":"10.1101/2025.05.23.25328115","DOIUrl":"10.1101/2025.05.23.25328115","url":null,"abstract":"<p><strong>Context: </strong>Goals-of-care (GOC) discussions and their documentation are important process measures in palliative care. However, existing natural language processing (NLP) models for identifying such documentation require costly task-specific training data. Large language models (LLMs) hold promise for measuring such constructs with fewer or no task-specific training data.</p><p><strong>Objective: </strong>To evaluate the performance of a publicly available LLM with no task-specific training data (zero-shot prompting) for identifying documented GOC discussions.</p><p><strong>Methods: </strong>We compared performance of two NLP models in identifying documented GOC discussions: Llama 3.3 using zero-shot prompting; and, a task-specific BERT (Bidirectional Encoder Representations from Transformers)-based model trained on 4,642 manually annotated notes. We tested both models on records from a series of clinical trials enrolling adult patients with chronic life-limiting illness hospitalized over 2018-2023. We evaluated the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), and maximal F ₁ score, for both note-level and patient-level classification over a 30-day period.</p><p><strong>Results: </strong>In our text corpora, GOC documentation represented <1% of text and was found in 7.3-9.9% of notes for 23-37% of patients. In a 617-patient held-out test set, Llama 3.3 (zero-shot) and BERT (task-specific, trained) exhibited comparable performance in identifying GOC documentation (Llama 3.3: AUC 0.979, AUPRC 0.873, and F ₁ 0.83; BERT: AUC 0.981, AUPRC 0.874, and F ₁ 0.83).</p><p><strong>Conclusion: </strong>A zero-shot large language model with no task-specific training performed similarly to a task-specific trained BERT model in identifying documented goals-of-care discussions. This demonstrates the promise of LLMs in measuring novel clinical research outcomes.</p><p><strong>Key message: </strong>This article reports the performance of a publicly available large language model with no task-specific training data in measuring the occurrence of documented goals-of-care discussions from electronic health records. The study demonstrates that newer large language AI models may allow investigators to measure novel outcomes without requiring costly training data.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12140542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144236315","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":"Inflammatory arthritis immune related adverse events represent a unique autoimmune disease entity primarily driven by T cells, but likely not autoantibodies.","authors":"Xingxing Zhu, Yue Yu, Yanfeng Li, Panwen Wang, Ying Li, Chantal McCabe, Shiju Chen, Hannah E Langenfeld, Andrew C Hanson, Brenna E Sharp, Amber Woltzen, Cynthia S Crowson, Svetomir N Markovic, John M Davis, Haidong Dong, Uma Thanarajasingam, Hu Zeng","doi":"10.1101/2025.06.06.25328991","DOIUrl":"10.1101/2025.06.06.25328991","url":null,"abstract":"<p><p>Immune checkpoint inhibitor (ICI)-induced inflammatory arthritis (IA) is an increasingly recognized immune-related adverse event (irAE), yet its underlying immunopathogenesis remains poorly understood. Unlike rheumatoid arthritis (RA), where autoantibodies and B cell dysfunction are central features, the contribution of humoral immunity to IA irAE is unclear. Here, we performed in-depth immunophenotyping of peripheral blood from patients with IA irAE, and compared them with seronegative RA patients, ICI-treated patients without irAE, and healthy controls. IA irAE was marked by a distinct T cell-dominated profile, with CD4⁺ T cells exhibiting reduced CXCR3 and CCR6 expression, and both CD4⁺ and CD8⁺ T cells showing increased cytotoxic molecule expression and metabolic activation. In contrast to seronegative RA, IA irAE patients displayed no significant elevation in autoantibody levels or atypical CD11c⁺CD21^- B cells. IA irAE was further characterized by a proinflammatory cytokine milieu, with elevated levels of IL-6, IL-12, and type I IFN, which correlated with the observed T cell activation phenotypes. Altogether, our findings define IA irAE as an immunologically distinct entity from RA, representing a naturally occurring model of antibody-independent systemic autoimmunity in humans. These results suggest that pathogenic T cell responses, potentiated by specific inflammatory cytokines, may be sufficient to drive arthritis in the absence of humoral autoimmunity, offering new insights into immune tolerance breakdown and therapeutic targeting in irAEs.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12154995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277152","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":"Partner Military Deployment During Wartime Is Associated with Maternal Depression and Impaired Bonding: A Matched-Control Study from the Israel-Hamas War.","authors":"Hadas Allouche-Kam, Sabrina J Chan, Isha H Arora, Christina T Pham, Inbal Reuveni, Eyal Sheiner, Sharon Dekel","doi":"10.1101/2025.01.20.25320861","DOIUrl":"10.1101/2025.01.20.25320861","url":null,"abstract":"<p><p>Purpose. The pregnancy and postpartum periods represent a time of heightened psychological vulnerability with implications for the offspring. Knowledge of the mental health of perinatal women exposed to armed conflict when their partner is in military deployment is scarce. Methods. This matched-control, survey-based study included a sample of 429 women recruited during the first months of the Israel-Hamas War who were pregnant or within six months postpartum. Women who had a partner in military deployment were matched primarily on demographics, prior mental health, and trauma exposure to women whose partner was no longer deployed. Results. We found that nearly 44% of pregnant women with a partner deployed endorsed probable depression. This group was more than twice as likely to endorse probable depression than matched pregnant controls. Likewise, postpartum women with a partner deployed reported significantly more maternal-infant attachment problems than the matched postpartum group of partners not deployed. Importantly, analysis showed that partner's active deployment was related to maternal depression and attachment problems via reduced perceived social support. Conclusions. Partner military deployment during conditions of war can serve as a major psychological stressor for pregnant and postpartum women. It can heighten psychiatric morbidity and interfere with attachment to the infant in part by diminished social support. Implementation of community-based services for the peripartum population is crucial during times of war and other large-scale traumas.</p><p><strong>Article highlights: </strong>Partner military deployment increases risk for antepartum depression and maternal-infant bonding problems.Reduced social support explains these maternal outcomes.Clinical attention to the wellbeing of the peripartum population is warranted during times of collective trauma.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838974/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143461320","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":"Mapping genetic effects on splicing in ten thousand post-mortem brain samples reveals novel mediators of neurological disease risk.","authors":"Aline Réal, B P Kailash, Winston H Cuddleston, Benjamin Z Muller, Beomjin Jang, Alex Tokolyi, Hong-Hee Won, Jack Humphrey, Towfique Raj, David A Knowles","doi":"10.1101/2025.09.25.25336663","DOIUrl":"https://doi.org/10.1101/2025.09.25.25336663","url":null,"abstract":"<p><p>Alternative splicing shapes isoform diversity and gene dosage, but how genetic variation impacts splicing in brain disease is still not fully characterized. We assembled BigBrain, a multi-ancestry resource of 10,725 bulk RNA-seq profiles with matched genotypes from 4,656 individuals across 43 tissue-cohort pairs and mapped 68,358 <i>cis</i> -sQTLs affecting 10,966 genes using mixed-model meta-analysis. Using SuSiE, we were able to finemap over half of these sQTLs into 95% credible sets, frequently to a single variant near splice sites. We further annotated variants predicted to alter dosage through frameshifts or nonsense-mediated decay or disrupt protein domains. Colocalization with seven neurodegenerative and psychiatric GWAS highlighted 97 loci where alternative splicing appears to mediate genetic risk. Among sQTL-eQTL pairs with colocalization probability ≥ 0.8 (posterior probability of a shared causal variant), half shared credible-set variants, showing that splicing can complement or act independently of expression. Mechanistic examples include <i>CAMLG</i> , <i>ZDHHC2</i> , and <i>CLU</i> .</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214827","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":"Genome-wide association meta-regression identifies stem cell lineage orchestration as a key driver of acne risk.","authors":"Jessye Maxwell, Brittany L Mitchell, Xinyi Du-Harpur, Luba M Pardo, Willemijn C A M Witkam, Nick Dand, Meike Bartels, Michael J Betti, Dorret I Boomsma, Xianjun Dong, Zachary Gerring, Sarah Finer, Fiona A Hagenbeek, Jouke Jan Hottenga, George Hripcsak, Laura Huilaja, Kristian Hveem, Benjamin M Jacobs, Mart Kals, James Kaufman-Cook, Johannes Kettunen, Atlas Khan, Külli Kingo, Krzysztof Kiryluk, Mari Løset, Gerton Lunter, Michelle K Lupton, Josine L Min, Nicholas G Martin, Sarah E Medland, Andres Metspalu, Dorien Neijzen, Tamar E C Nijsten, Tiit Nikopensius, Catherine M Olsen, Lynn Petukhova, Anu Reigo, Miguel E Rentería, Rossella Rispoli, Jake Saklatvala, Eeva Sliz, Kaisa Tasanen-Määttä, Maris Teder-Laving, Laurent Thomas, Richard C Trembath, Mariliis Vaht, David A van Heel, Chunhua Weng, David C Whiteman, Jonathan N Barker, Catherine Smith, Michael A Simpson","doi":"10.1101/2025.06.27.25330406","DOIUrl":"10.1101/2025.06.27.25330406","url":null,"abstract":"<p><p>Over 85% of the population experience acne at some point in their lives, with its severity spanning a quantitative spectrum, from mild, transient outbreaks to more persistent, severe forms of the condition. Moderate to severe disease poses a substantial global burden arising from both the physical and psychological impacts of this highly visible condition. The analytical approach taken in this study aimed to address the impact of variation in the dichotomisation of acne case control status, driven by ascertainment and study design, on effect size estimates across independent genetic association studies of acne. Through a fixed intercept meta-regression framework, we combined evidence genome-wide for association with acne across studies in which case-control status had been ascertained in different settings, allowing for different severity threshold definitions. Across a combined sample of 73,997 cases and 1,103,940 controls of European, South Asian and African American ancestry we identify genetic variation at 165 genomic loci that influence acne risk. There is evidence for both shared and ancestry specific components to the genetic susceptibility to acne and for sex differences in the magnitude of effect of risk alleles at three loci. We observe that common genetic variation explains 13.4% of acne heritability on the liability scale. Consistent with the hypothesis that genetic risk primarily operates at the level of individual pilosebaceous units, a polygenic score derived from this case-control study of acne susceptibility is associated with both self-reported and clinically assessed acne severity in adolescence, further strengthening the link between genetic risk and disease severity. Prioritisation of causal genes at the identified acne risk loci, provides genetic validation of the targets of established and emerging acne therapies, including retinoid treatments. The identified acne risk loci are enriched for genes encoding downstream effectors of <i>RXRA</i> signalling, including <i>SOX9</i> and components of the <i>WNT</i> and p53 pathways. Illustrating that the control of stem cell lineage plasticity and cellular fate are important mechanisms through which genetic variation influences acne susceptibility within the pilosebaceous unit.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12262744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144644552","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":"State Guided ICA of Functional Network Connectivity Reveals Temporal Signatures of Alzheimer's Disease.","authors":"Elaheh Zendehrouh, Mohammad Se Sendi, Anees Abrol, Armin Iraji, Vince Calhoun","doi":"10.1101/2025.09.23.25336175","DOIUrl":"https://doi.org/10.1101/2025.09.23.25336175","url":null,"abstract":"<p><p>Identifying robust neuroimaging biomarkers for Alzheimer's disease (AD) and mild cognitive impairment (MCI) is essential for early diagnosis and intervention. In this study, we introduce a novel, fully automated, guided dynamic functional connectivity (dFNC) framework to extract multiple dynamic measures for distinguishing MCI/AD from cognitively normal (CN) individuals. Resting-state fMRI data were used to extract subject-specific brain networks via spatially constrained independent component analysis (scICA), using a multi-objective optimization framework to ensure alignment with known functional networks while preserving individual variability. Using these components, dFNC was computed through a sliding-window approach. ICA was then applied to the concatenated dFNC matrices from the UK Biobank (UKBB) dataset to identify five canonical brain states, each representing a replicable, independent pattern of connectivity. These states served as biologically informed priors in a state-constrained ICA (St-cICA), which was applied to each subject in the combined OASIS-3 and ADNI datasets to guide individual-level decomposition and ensure interpretable connectivity states guided by state priors derived from the normative UKBB sample. St-cICA extracted subject-specific dFNC features and associated weighted timecourses. To characterize dFNC patterns, we computed metrics from the most strongly expressed (primary) state and introduce estimation of the second-most expressed (secondary) state at each timepoint, including dwell time, occupancy rate, and transition probabilities. Group comparisons using two-sample t-tests revealed widespread and significant alterations in AD/MCI compared to CN individuals. AD/MCI participants exhibited higher dwell times and increased self-transitions, indicating reduced neural flexibility and a tendency to remain in specific connectivity states. In contrast, CN individuals showed more diverse and recurrent transitions, reflecting greater adaptability. Secondary transitions revealed widespread selective switching in CN, whereas AD/MCI showed reduced cross-state engagement. A classification model trained on 6,960 dynamic features achieved strong performance in distinguishing AD/MCI from CN (mean AUC ≈ 0.85). These findings highlight the potential of guided dFNC as a biomarker framework for early-stage AD detection using resting-state fMRI.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485992/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214619","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}