Pub Date : 2024-07-27DOI: 10.1101/2024.07.25.24311002
Guoqiao Wang, Yan Li, Chengjie Xiong, Yuchen Cao, Suzanne Schindler, Eric McDade, Kaj Blennow, Oskar Hansson, Jeffrey L. Dage, Clifford R. Jack, Charlotte E. Teunissen, Leslie M Shaw, Henrik Zetterberg, Laura Ibanez, Jigyasha Timsina, Carlos Cruchaga, Randall J Bateman
Introduction: Biomarkers have been essential to understanding Alzheimer's disease (AD) pathogenesis, pathophysiology, progression, and treatment effects. However, each biomarker measure is a representation of the biological target, the assay used to measure it, and the variance of the assay. Thus, biomarker measures are difficult to compare without standardization, and the units and magnitude of effect relative to the disease are difficult to appreciate, even for experts. To facilitate quantitative comparisons of AD biomarkers in the context of biologic and treatment effects, we propose a biomarker standardization approach between normal ranges and maximum abnormal AD ranges, which we refer to as CentiMarker, similar to the Centiloid approach used in PET. Methods: We developed a standardization scale that creates percentile values ranging from 0 for a normal population to 100 for the most abnormal measures across disease stages. We applied this scale to CSF and plasma biomarkers in autosomal dominant AD, assessing the distribution by estimated years from symptom onset, between biomarkers, and across cohorts. We then validated this approach in a large national sporadic AD cohort. Results: We found the CentiMarker scale provided an easily interpretable metric of disease abnormality. The biologic changes, range, and distribution of several AD fluid biomarkers including amyloid-β, phospho-tau and other biomarkers, were comparable across disease stages in both early onset autosomal dominant and sporadic late onset AD. Discussion: The CentiMarker scale offers a robust and versatile framework for the standardized biological comparison of AD biomarkers. Its broader adoption could facilitate biomarker reporting, allowing for more informed cross-study comparisons and contributing to accelerated therapeutic development.
导言：生物标志物对于了解阿尔茨海默病（AD）的发病机制、病理生理学、进展和治疗效果至关重要。然而，每种生物标志物的测量结果都代表了生物靶标、用于测量靶标的检测方法以及检测方法的差异。因此，如果没有标准化，生物标志物的测量很难进行比较，而且即使是专家也很难理解相对于疾病的影响单位和影响程度。为了便于在生物效应和治疗效应的背景下对 AD 生物标志物进行定量比较，我们提出了一种在正常范围和 AD 最大异常范围之间进行生物标志物标准化的方法，我们称之为 CentiMarker，类似于 PET 中使用的 Centiloid 方法：我们开发了一种标准化量表，该量表可创建百分位值，范围从正常人群的 0 到各疾病阶段最异常指标的 100。我们将这一量表应用于常染色体显性 AD 的脑脊液和血浆生物标记物，评估了不同生物标记物之间以及不同队列之间从症状出现起估计年限的分布情况。然后，我们在一个大型全国散发性注意力缺失症队列中验证了这种方法：结果：我们发现 CentiMarker 量表提供了一种易于解释的疾病异常度量标准。包括淀粉样蛋白-β、磷酸化-tau和其他生物标记物在内的几种AD体液生物标记物的生物变化、范围和分布在早发常染色体显性遗传和散发性晚发AD的不同疾病阶段具有可比性：CentiMarker量表为对AD生物标志物进行标准化生物学比较提供了一个稳健且通用的框架。CentiMarker量表为AD生物标记物的标准化生物学比较提供了一个稳健、通用的框架，它的广泛采用将促进生物标记物的报告，使跨研究比较更加有据可依，并有助于加速治疗方法的开发。
{"title":"The CentiMarker Project: Standardizing Quantitative Alzheimer's disease Fluid Biomarkers for Biologic Interpretation","authors":"Guoqiao Wang, Yan Li, Chengjie Xiong, Yuchen Cao, Suzanne Schindler, Eric McDade, Kaj Blennow, Oskar Hansson, Jeffrey L. Dage, Clifford R. Jack, Charlotte E. Teunissen, Leslie M Shaw, Henrik Zetterberg, Laura Ibanez, Jigyasha Timsina, Carlos Cruchaga, Randall J Bateman","doi":"10.1101/2024.07.25.24311002","DOIUrl":"https://doi.org/10.1101/2024.07.25.24311002","url":null,"abstract":"Introduction: Biomarkers have been essential to understanding Alzheimer's disease (AD) pathogenesis, pathophysiology, progression, and treatment effects. However, each biomarker measure is a representation of the biological target, the assay used to measure it, and the variance of the assay. Thus, biomarker measures are difficult to compare without standardization, and the units and magnitude of effect relative to the disease are difficult to appreciate, even for experts. To facilitate quantitative comparisons of AD biomarkers in the context of biologic and treatment effects, we propose a biomarker standardization approach between normal ranges and maximum abnormal AD ranges, which we refer to as CentiMarker, similar to the Centiloid approach used in PET.\u0000Methods: We developed a standardization scale that creates percentile values ranging from 0 for a normal population to 100 for the most abnormal measures across disease stages. We applied this scale to CSF and plasma biomarkers in autosomal dominant AD, assessing the distribution by estimated years from symptom onset, between biomarkers, and across cohorts. We then validated this approach in a large national sporadic AD cohort.\u0000Results: We found the CentiMarker scale provided an easily interpretable metric of disease abnormality. The biologic changes, range, and distribution of several AD fluid biomarkers including amyloid-β, phospho-tau and other biomarkers, were comparable across disease stages in both early onset autosomal dominant and sporadic late onset AD.\u0000Discussion: The CentiMarker scale offers a robust and versatile framework for the standardized biological comparison of AD biomarkers. Its broader adoption could facilitate biomarker reporting, allowing for more informed cross-study comparisons and contributing to accelerated therapeutic development.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-27DOI: 10.1101/2024.07.26.24311084
Mingzhou Fu, Timothy S Chang
Backgrounds: Alzheimer's disease (AD), a leading cause of dementia, poses a growing global public health challenge. While recent studies have identified AD risk factors, they often focus on specific comorbidities, neglecting the complex interrelations and temporal dynamics. Our study addresses this by analyzing AD progression through longitudinal trajectories, utilizing clinical diagnoses over time. Using machine learning and network analysis, we created a computational framework to identify common AD progression patterns. Methods: We analyzed patient diagnoses from UC Health Data Warehouse's Electronic Health Records, coded with the International Classification of Diseases, version 10 (ICD-10). Using the Fine and Gray model to detect significant temporal risk factors between diagnoses, we examined associations between diagnosis pairs and refined the patients' diagnostic trajectories, delineating all possible trajectory combinations. These refined trajectories were compared using Dynamic Time Warping and grouped into clusters with hierarchical clustering. We investigated common AD trajectories through network analysis and compared patient demographics, symptoms, and AD manifestations across clusters. The Greedy Equivalence Search algorithm was used to infer causal relationships within these trajectories. We rigorously evaluated these trajectories through association tests and comparison to controls, Results: Our analysis included 24,473 eligible AD patients, which was filtered to include 5,762 patients with 6,794 unique AD progression trajectories. We identified four trajectory clusters: 1) a mental health cluster (e.g., anxiety disorder → depressive episode) (N_patient = 1,448); 2) an encephalopathy cluster (e.g., hypertension → other disorders of brain) (N_patient = 3,223); 3) a neurodegenerative disease cluster (e.g., transient cerebral ischemic attacks → other degenerative disease of nervous system) (N_patient = 1,502); and 4) a vascular disease cluster (e.g. hypertension → other cerebrovascular diseases) (N_patient = 1,446). Significant differences were observed in demographics, symptoms, and AD features across clusters. Causal analysis indicated that 26.2% of the identified trajectory connections were causal. We also observed patients with risk trajectories faced higher risks of AD compared to those without the trajectory or with only a single risk factor. Conclusion: We uncovered AD diagnosis trajectories, incorporating temporal aspects and causal relationships. These insights improve our understanding of AD development and AD subtypes, and can enhance risk assessment. Our findings can significantly benefit patient care and medical research by moving toward earlier and more accurate diagnoses, along with personalized treatment, such as medical risk factors management and lifestyle modifications.
{"title":"Identifying common disease trajectories of Alzheimer's disease with electronic health records","authors":"Mingzhou Fu, Timothy S Chang","doi":"10.1101/2024.07.26.24311084","DOIUrl":"https://doi.org/10.1101/2024.07.26.24311084","url":null,"abstract":"Backgrounds: Alzheimer's disease (AD), a leading cause of dementia, poses a growing global public health challenge. While recent studies have identified AD risk factors, they often focus on specific comorbidities, neglecting the complex interrelations and temporal dynamics. Our study addresses this by analyzing AD progression through longitudinal trajectories, utilizing clinical diagnoses over time. Using machine learning and network analysis, we created a computational framework to identify common AD progression patterns. Methods: We analyzed patient diagnoses from UC Health Data Warehouse's Electronic Health Records, coded with the International Classification of Diseases, version 10 (ICD-10). Using the Fine and Gray model to detect significant temporal risk factors between diagnoses, we examined associations between diagnosis pairs and refined the patients' diagnostic trajectories, delineating all possible trajectory combinations. These refined trajectories were compared using Dynamic Time Warping and grouped into clusters with hierarchical clustering. We investigated common AD trajectories through network analysis and compared patient demographics, symptoms, and AD manifestations across clusters. The Greedy Equivalence Search algorithm was used to infer causal relationships within these trajectories. We rigorously evaluated these trajectories through association tests and comparison to controls, Results: Our analysis included 24,473 eligible AD patients, which was filtered to include 5,762 patients with 6,794 unique AD progression trajectories. We identified four trajectory clusters: 1) a mental health cluster (e.g., anxiety disorder → depressive episode) (N_patient = 1,448); 2) an encephalopathy cluster (e.g., hypertension → other disorders of brain) (N_patient = 3,223); 3) a neurodegenerative disease cluster (e.g., transient cerebral ischemic attacks → other degenerative disease of nervous system) (N_patient = 1,502); and 4) a vascular disease cluster (e.g. hypertension → other cerebrovascular diseases) (N_patient = 1,446). Significant differences were observed in demographics, symptoms, and AD features across clusters. Causal analysis indicated that 26.2% of the identified trajectory connections were causal. We also observed patients with risk trajectories faced higher risks of AD compared to those without the trajectory or with only a single risk factor. Conclusion: We uncovered AD diagnosis trajectories, incorporating temporal aspects and causal relationships. These insights improve our understanding of AD development and AD subtypes, and can enhance risk assessment. Our findings can significantly benefit patient care and medical research by moving toward earlier and more accurate diagnoses, along with personalized treatment, such as medical risk factors management and lifestyle modifications.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-27DOI: 10.1101/2024.07.25.24311036
Pyeong Eun Kim, Sue Young Ha, Myungjae Lee, Nakhoon Kim, Dongmin Kim, Leonard Sunwoo, Wi-Sun Ryu, Beom Joon Kim
Background: The hyperdense artery sign (HAS) in patients with large vessel occlusion (LVO) is associated with outcomes after ischemic stroke. Considering the labor-intensive nature of manual segmentation of HAS, we developed and validated an automated HAS segmentation algorithm on non-contrast brain CT (NCCT) images using a multicenter dataset with independent annotations by two experts. Methods: For the training dataset, we included patients with ischemic stroke undergoing concurrent NCCT and CT angiography between May 2011 and December 2022 from six stroke centers. The model was externally validated using a dataset from one stroke center. For the clinical validation dataset, a consecutive series of patients admitted within 24 hours of symptom onset were included between December 2020 and April 2023 from six stroke centers. The model was trained using a 2D U-Net algorithm with manual segmentation by two experts. We constructed models trained on datasets annotated individually by each expert, and an ensemble model using shuffled annotations from both experts. The performance of the models was compared using area under the receiver operating characteristics curve (AUROC), sensitivity, and specificity. Results: A total of 673, 365, and 774 patients were included in the training, external validation, and clinical validation datasets, respectively, with mean (SD) ages of 68.8 (13.2), 67.6 (13.4), and 68.8 (13.6) years and male frequencies of 55.0%, 59.5%, and 57.6%. The ensemble model achieved higher AUROC and sensitivity compared to the models trained on annotations from a single expert in the external validation dataset. In the clinical validation dataset, the ensemble model exhibited an AUROC of 0.846 (95% CI, 0.819?0.871), sensitivity of 76.8% (65.1?86.1%), and specificity of 88.5% (85.9?90.8%). The predicted volume of the clot was significantly correlated with infarct volume on follow-up diffusion-weighted imaging (r=0.42; p<0.001). Conclusion: Our algorithm promptly and accurately identifies clot signs, facilitating the screening of potential patients who may require intervention.
{"title":"Detection and segmentation of hyperdense middle cerebral artery sign on non-contrast CT using artificial intelligence","authors":"Pyeong Eun Kim, Sue Young Ha, Myungjae Lee, Nakhoon Kim, Dongmin Kim, Leonard Sunwoo, Wi-Sun Ryu, Beom Joon Kim","doi":"10.1101/2024.07.25.24311036","DOIUrl":"https://doi.org/10.1101/2024.07.25.24311036","url":null,"abstract":"Background: The hyperdense artery sign (HAS) in patients with large vessel occlusion (LVO) is associated with outcomes after ischemic stroke. Considering the labor-intensive nature of manual segmentation of HAS, we developed and validated an automated HAS segmentation algorithm on non-contrast brain CT (NCCT) images using a multicenter dataset with independent annotations by two experts.\u0000Methods: For the training dataset, we included patients with ischemic stroke undergoing concurrent NCCT and CT angiography between May 2011 and December 2022 from six stroke centers. The model was externally validated using a dataset from one stroke center. For the clinical validation dataset, a consecutive series of patients admitted within 24 hours of symptom onset were included between December 2020 and April 2023 from six stroke centers. The model was trained using a 2D U-Net algorithm with manual segmentation by two experts. We constructed models trained on datasets annotated individually by each expert, and an ensemble model using shuffled annotations from both experts. The performance of the models was compared using area under the receiver operating characteristics curve (AUROC), sensitivity, and specificity.\u0000Results: A total of 673, 365, and 774 patients were included in the training, external validation, and clinical validation datasets, respectively, with mean (SD) ages of 68.8 (13.2), 67.6 (13.4), and 68.8 (13.6) years and male frequencies of 55.0%, 59.5%, and 57.6%. The ensemble model achieved higher AUROC and sensitivity compared to the models trained on annotations from a single expert in the external validation dataset. In the clinical validation dataset, the ensemble model exhibited an AUROC of 0.846 (95% CI, 0.819?0.871), sensitivity of 76.8% (65.1?86.1%), and specificity of 88.5% (85.9?90.8%). The predicted volume of the clot was significantly correlated with infarct volume on follow-up diffusion-weighted imaging (r=0.42; p<0.001).\u0000Conclusion: Our algorithm promptly and accurately identifies clot signs, facilitating the screening of potential patients who may require intervention.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-27DOI: 10.1101/2024.07.25.24310988
Thomas P Spargo, Chloe F Sands, Isabella R Juan, Jonathan Mitchell, Vida Ravanmehr, Jessica C Butts, Ruth B De-Paula, Youngdoo Kim, Fengyuan Hu, Quanli Wang, Dimitrios Vitsios, Manik Garg, Mirko Messa, Guillermo del Angel, Daniel G Calame, Hiba Saade, Laurie Robak, Ben Hollis, Huda Y Zoghbi, Joshua Shulman, Slavé Petrovski, Ismael Al-Ramahi, Ioanna Tachmazidou, Ryan S Dhindsa
Background Despite its significant heritability, the genetic underpinnings of Parkinson disease (PD) remain incompletely understood, particularly the role of rare variants. Advances in population-scale sequencing now provide an unprecedented opportunity to uncover additional large-effect rare genetic risk factors and expand our understanding of disease mechanisms. Methods We leveraged whole-genome sequence data with linked electronic health records from 490,560 UK Biobank participants, identifying 3,809 PD cases and 247,101 controls without a neurological disorder. We performed both variant- and gene-level association analyses to identify novel genetic associations with PD. We analyzed two additional independent case-control cohorts for replication (totaling 3,739 cases and 58,156 controls). Additionally, we performed functional validation of a novel PD association in a human synuclein-expressing Drosophila model. Findings In the UK Biobank, we replicated associations in well-established loci including GBA1 and LRRK2. We also identified a novel association between protein-truncating variants (PTVs) in ITSN1 and an increased risk of PD, with an effect size exceeding those of established loci (Fisher's Exact Test: p=6.1x10-7; Odds ratio [95% confidence interval] = 10.53 [5.20, 21.34]). We replicated the ITSN1 risk signal in a meta-analysis across all cohorts (Cochran-Mantel-Haenszel test p=5.7x10-9; Odds ratio [95% confidence interval] = 9.20 [4.66, 16.70]). In Drosophila, haploinsufficiency of the ITSN1 ortholog (Dap160) exacerbated α-synuclein-induced compound eye degeneration and motor deficits. Interpretation We establish ITSN1 as a novel risk gene for PD, with PTVs substantially increasing disease risk. ITSN1 encodes a scaffold protein involved in synaptic vesicle endocytosis, a critical pathway increasingly recognized in PD pathogenesis. Our findings highlight the power of large-scale sequencing coupled with preclinical functional modeling to identify rare variant associations and elucidate disease mechanisms.
{"title":"Haploinsufficiency of ITSN1 is associated with Parkinson's disease","authors":"Thomas P Spargo, Chloe F Sands, Isabella R Juan, Jonathan Mitchell, Vida Ravanmehr, Jessica C Butts, Ruth B De-Paula, Youngdoo Kim, Fengyuan Hu, Quanli Wang, Dimitrios Vitsios, Manik Garg, Mirko Messa, Guillermo del Angel, Daniel G Calame, Hiba Saade, Laurie Robak, Ben Hollis, Huda Y Zoghbi, Joshua Shulman, Slavé Petrovski, Ismael Al-Ramahi, Ioanna Tachmazidou, Ryan S Dhindsa","doi":"10.1101/2024.07.25.24310988","DOIUrl":"https://doi.org/10.1101/2024.07.25.24310988","url":null,"abstract":"Background\u0000Despite its significant heritability, the genetic underpinnings of Parkinson disease (PD) remain incompletely understood, particularly the role of rare variants. Advances in population-scale sequencing now provide an unprecedented opportunity to uncover additional large-effect rare genetic risk factors and expand our understanding of disease mechanisms. Methods\u0000We leveraged whole-genome sequence data with linked electronic health records from 490,560 UK Biobank participants, identifying 3,809 PD cases and 247,101 controls without a neurological disorder. We performed both variant- and gene-level association analyses to identify novel genetic associations with PD. We analyzed two additional independent case-control cohorts for replication (totaling 3,739 cases and 58,156 controls). Additionally, we performed functional validation of a novel PD association in a human synuclein-expressing Drosophila model. Findings\u0000In the UK Biobank, we replicated associations in well-established loci including GBA1 and LRRK2. We also identified a novel association between protein-truncating variants (PTVs) in ITSN1 and an increased risk of PD, with an effect size exceeding those of established loci (Fisher's Exact Test: p=6.1x10-7; Odds ratio [95% confidence interval] = 10.53 [5.20, 21.34]). We replicated the ITSN1 risk signal in a meta-analysis across all cohorts (Cochran-Mantel-Haenszel test p=5.7x10-9; Odds ratio [95% confidence interval] = 9.20 [4.66, 16.70]). In Drosophila, haploinsufficiency of the ITSN1 ortholog (Dap160) exacerbated α-synuclein-induced compound eye degeneration and motor deficits. Interpretation\u0000We establish ITSN1 as a novel risk gene for PD, with PTVs substantially increasing disease risk. ITSN1 encodes a scaffold protein involved in synaptic vesicle endocytosis, a critical pathway increasingly recognized in PD pathogenesis. Our findings highlight the power of large-scale sequencing coupled with preclinical functional modeling to identify rare variant associations and elucidate disease mechanisms.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.1101/2024.07.24.24310956
Tiffany Li, Hannah C Timmins, Lisa G Horvath, Michelle Harrison, Peter Grimison, Michael Friedlander, Gavin Marx, Frances Boyle, David Wyld, Robert Henderson, Tracy King, Sally Baron-Hay, Matthew C Kiernan, Elizabeth H Barnes, David Goldstein, Susanna B Park
Background and Objective Chemotherapy-induced peripheral neuropathy (CIPN) is a complex and dose-limiting toxicity of anticancer treatments with chronic symptoms leading to increased disability and reduced quality of life. The present study evaluated clinical risk factors associated with development of chronic, severe and dose-limiting CIPN, utilising a comprehensive multi-modal battery of neuropathy assessment. Methods Baseline clinical risk factors were investigated in patients who had completed neurotoxic chemotherapy (including taxanes, platinums and haematological cancer therapies). CIPN was assessed using neurological evaluation (Total Neuropathy Score, sural nerve conduction studies), patient reported outcome measure (EORTC QLQ-CIPN20), and clinically graded neuropathy (NCI-CTCAE). Multivariate models of risk factors associated with development of chronic, severe and dose-limiting CIPN were evaluated using backwards stepwise regression model building. Results The study recruited 903 patients (age 61 (IQR 50-69) years) who were assessed 12 (IQR 6-24) months post neurotoxic treatment. 73% of patients presented with CIPN at time of assessment, with 37% having moderate to severe symptoms. 32% of patients experienced neurotoxic treatment dose modification due to CIPN. Across the various CIPN assessment approaches, risk factors for chronic CIPN included older age, diabetes diagnosis, higher BMI and prior exposure to neurotoxic treatment (all P<0.05). Risk factors for severe CIPN included older age, higher BMI, prior neurotoxic treatment and female sex (all P<0.05), whereas risk factors for dose-limiting CIPN included older age and female sex (all P<0.05). Discussion This study identified baseline clinical risk factors associated chronic, severe and dose-limiting CIPN. Closer monitoring of these vulnerable cohorts will allow for timely CIPN management, including referral pathways to intervention and rehabilitation therapies which will ultimately lead to improved CIPN morbidity.
{"title":"Peripheral Neuropathy in Cancer Patients- Multifactorial Contributors to Dose Limiting and Chronic Toxicity","authors":"Tiffany Li, Hannah C Timmins, Lisa G Horvath, Michelle Harrison, Peter Grimison, Michael Friedlander, Gavin Marx, Frances Boyle, David Wyld, Robert Henderson, Tracy King, Sally Baron-Hay, Matthew C Kiernan, Elizabeth H Barnes, David Goldstein, Susanna B Park","doi":"10.1101/2024.07.24.24310956","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310956","url":null,"abstract":"Background and Objective\u0000Chemotherapy-induced peripheral neuropathy (CIPN) is a complex and dose-limiting toxicity of anticancer treatments with chronic symptoms leading to increased disability and reduced quality of life. The present study evaluated clinical risk factors associated with development of chronic, severe and dose-limiting CIPN, utilising a comprehensive multi-modal battery of neuropathy assessment.\u0000Methods\u0000Baseline clinical risk factors were investigated in patients who had completed neurotoxic chemotherapy (including taxanes, platinums and haematological cancer therapies). CIPN was assessed using neurological evaluation (Total Neuropathy Score, sural nerve conduction studies), patient reported outcome measure (EORTC QLQ-CIPN20), and clinically graded neuropathy (NCI-CTCAE). Multivariate models of risk factors associated with development of chronic, severe and dose-limiting CIPN were evaluated using backwards stepwise regression model building.\u0000Results\u0000The study recruited 903 patients (age 61 (IQR 50-69) years) who were assessed 12 (IQR 6-24) months post neurotoxic treatment. 73% of patients presented with CIPN at time of assessment, with 37% having moderate to severe symptoms. 32% of patients experienced neurotoxic treatment dose modification due to CIPN. Across the various CIPN assessment approaches, risk factors for chronic CIPN included older age, diabetes diagnosis, higher BMI and prior exposure to neurotoxic treatment (all P<0.05). Risk factors for severe CIPN included older age, higher BMI, prior neurotoxic treatment and female sex (all P<0.05), whereas risk factors for dose-limiting CIPN included older age and female sex (all P<0.05).\u0000Discussion\u0000This study identified baseline clinical risk factors associated chronic, severe and dose-limiting CIPN. Closer monitoring of these vulnerable cohorts will allow for timely CIPN management, including referral pathways to intervention and rehabilitation therapies which will ultimately lead to improved CIPN morbidity.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1101/2024.07.24.24310951
Nicholas Demetriou, Alexandra S. Jensen, Ellen Farr, Shreya Khanna, John M. Coleman, Senda Ajroud-Driss, Adenike A. Adewuyi, Lisa F. Wolfe, Colin K. Franz
Introduction/Aims: Phrenic Neuropathy (PhN) impairs diaphragm muscle function, causing a spectrum of breathing disability. PhN etiologies and their natural history are ill defined. This knowledge gap hinders informed prognosis and management decisions. This study aims to help fill this knowledge gap on PhN etiologies, outcomes, and recovery patterns, especially in the context of non-surgical clinical practice. Methods: This is a retrospective study from two interdisciplinary clinics, physiatry and neurology based. Patients were included if PhN was identified, and other causes of hemi-diaphragm muscle dysfunction excluded. Patients were followed serially per the discretion of the neuromuscular trained neurologist or physiatrist. Recovery was assessed using pulmonary function tests (PFTs), diaphragm muscle US thickening ratio, and patient-reported outcomes in patients presenting within two years of PhN onset. Results: We identified 151 patients with PhN. The most common etiologies included idiopathic (27%), associated with cardiothoracic procedure (24%), and intensive care unit (17%). Of these patients, 117 (77%) were evaluated within two years of PhN onset. Of patients included in outcome analyses, 69% saw improvement on serial US, 50% on serial PFTs and 79% reported symptomatic improvement at an average of 13, 16, and 17 months respectively. Conclusion: This study maps PhN etiologies and recovery. A clear majority of PhN patients show improvement in diaphragm muscle function, but on average improvements took 13-17 months depending on the assessment type. These insights are vital for developing tailored treatments and can guide physicians in prognosis and decision-making, especially if more invasive interventions are being considered.
{"title":"Phrenic Neuropathy Etiologies and Recovery Trajectories in Outpatient Rehabilitation and Neuromuscular Medicine Clinics: A Retrospective Analysis","authors":"Nicholas Demetriou, Alexandra S. Jensen, Ellen Farr, Shreya Khanna, John M. Coleman, Senda Ajroud-Driss, Adenike A. Adewuyi, Lisa F. Wolfe, Colin K. Franz","doi":"10.1101/2024.07.24.24310951","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310951","url":null,"abstract":"Introduction/Aims: Phrenic Neuropathy (PhN) impairs diaphragm muscle function, causing a spectrum of breathing disability. PhN etiologies and their natural history are ill defined. This knowledge gap hinders informed prognosis and management decisions. This study aims to help fill this knowledge gap on PhN etiologies, outcomes, and recovery patterns, especially in the context of non-surgical clinical practice. Methods: This is a retrospective study from two interdisciplinary clinics, physiatry and neurology based. Patients were included if PhN was identified, and other causes of hemi-diaphragm muscle dysfunction excluded. Patients were followed serially per the discretion of the neuromuscular trained neurologist or physiatrist. Recovery was assessed using pulmonary function tests (PFTs), diaphragm muscle US thickening ratio, and patient-reported outcomes in patients presenting within two years of PhN onset. Results: We identified 151 patients with PhN. The most common etiologies included idiopathic (27%), associated with cardiothoracic procedure (24%), and intensive care unit (17%). Of these patients, 117 (77%) were evaluated within two years of PhN onset. Of patients included in outcome analyses, 69% saw improvement on serial US, 50% on serial PFTs and 79% reported symptomatic improvement at an average of 13, 16, and 17 months respectively. Conclusion: This study maps PhN etiologies and recovery. A clear majority of PhN patients show improvement in diaphragm muscle function, but on average improvements took 13-17 months depending on the assessment type. These insights are vital for developing tailored treatments and can guide physicians in prognosis and decision-making, especially if more invasive interventions are being considered.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.23.24310859
Marcelo Mendonça, Pedro Ferreira, Raquel Barbosa, Joaquim Alves Da Silva
Motor subtypes in Parkinson′s Disease (PD) are unstable over time, limiting mechanistic insights and biomarker discovery. We focused on Rest Tremor (RT) as a symptom to test for phenotype stability and link them to specific circuits and disease mechanisms. Using the PPMI cohort data over 5 years we found that RT we found that RT is more stable than common Tremor- Dominant definitions, a stability also seen for therapy response. At time of diagnosis, the population of therapy-resistant RT patients was enriched with a brain-first PD profile as predicted by a-Synuclein origin site and connectome (SOC) model. Resistant-RT patients have lower gastrointestinal and cardiovascular symptoms, lower prevalence of probable REM-Sleep behavior disorder, and higher dopaminergic asymmetry compared to therapy-responsive or no tremor patients. Treating RT as a distinct phenomenon revealed a relative phenotypic stability with treatment response being linked to different patterns of disease progression.
{"title":"Brain-first forms of Parkinson′s Disease are over-represented in patients with non-responsive resting tremor","authors":"Marcelo Mendonça, Pedro Ferreira, Raquel Barbosa, Joaquim Alves Da Silva","doi":"10.1101/2024.07.23.24310859","DOIUrl":"https://doi.org/10.1101/2024.07.23.24310859","url":null,"abstract":"Motor subtypes in Parkinson′s Disease (PD) are unstable over time, limiting mechanistic\u0000insights and biomarker discovery. We focused on Rest Tremor (RT) as a symptom to test for\u0000phenotype stability and link them to specific circuits and disease mechanisms. Using the PPMI\u0000cohort data over 5 years we found that RT we found that RT is more stable than common Tremor-\u0000Dominant definitions, a stability also seen for therapy response. At time of diagnosis, the\u0000population of therapy-resistant RT patients was enriched with a brain-first PD profile as predicted\u0000by a-Synuclein origin site and connectome (SOC) model. Resistant-RT patients have lower\u0000gastrointestinal and cardiovascular symptoms, lower prevalence of probable REM-Sleep behavior\u0000disorder, and higher dopaminergic asymmetry compared to therapy-responsive or no tremor\u0000patients. Treating RT as a distinct phenomenon revealed a relative phenotypic stability with\u0000treatment response being linked to different patterns of disease progression.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.24.24310926
Marvin Petersen, Moritz Link, Carola Mayer, Felix Naegele, Maximilian Schell, Jens Fiehler, Juergen Link, Simone Kuehn, Raphael Twerenbold, Amir Omidvarnia, Felix Hoffstaedter, Kaustubh R. Patil, Simon B. Eickhoff, Goetz Thomalla, Bastian Cheng
The increasing global life expectancy brings forth challenges associated with age-related cognitive and motor declines. To better understand underlying mechanisms, we investigated the connection between markers of biological brain aging based on magnetic resonance imaging (MRI), cognitive and motor performance, as well as modifiable vascular risk factors, using a large-scale neuroimaging analysis in 40,579 individuals of the population-based UK Biobank and Hamburg City Health Study. Employing partial least squares correlation analysis (PLS), we investigated multivariate associative effects between three imaging markers of biological brain aging - relative brain age, white matter hyperintensities of presumed vascular origin, and peak-width of skeletonized mean diffusivity - and multi-domain cognitive test performances and motor test results. The PLS identified a latent dimension linking higher markers of biological brain aging to poorer cognitive and motor performances, accounting for 94.7% of shared variance. Furthermore, a mediation analysis revealed that biological brain aging mediated the relationship of vascular risk factors - including hypertension, glucose, obesity, and smoking - to cognitive and motor function. These results were replicable in both cohorts. By integrating multi-domain data with a comprehensive methodological approach, our study contributes evidence of a direct association between vascular health, biological brain aging, and functional cognitive as well as motor performance, emphasizing the need for early and targeted preventive strategies to maintain cognitive and motor independence in aging populations.
全球预期寿命的延长带来了与年龄相关的认知和运动能力下降的挑战。为了更好地了解潜在的机制，我们对英国生物库（UK Biobank）和汉堡市健康研究（Hamburg City Health Study）中的 40,579 人进行了大规模神经成像分析，研究了基于磁共振成像（MRI）的大脑生物衰老标志物、认知和运动能力以及可改变的血管风险因素之间的联系。通过偏最小二乘法相关性分析（PLS），我们研究了大脑生物衰老的三个成像标志物--相对脑龄、假定血管源性白质高密度和骨架化平均扩散峰值宽度--与多领域认知测试表现和运动测试结果之间的多变量关联效应。PLS 发现了一个潜在维度，将较高的大脑生物老化标记与较差的认知和运动表现联系起来，占共享方差的 94.7%。此外，中介分析显示，大脑生物老化中介了血管风险因素（包括高血压、血糖、肥胖和吸烟）与认知和运动功能的关系。这些结果在两个队列中均可复制。通过将多领域数据与综合方法相结合，我们的研究为血管健康、大脑生物老化、认知功能和运动表现之间的直接联系提供了证据，强调了在老龄人口中尽早采取有针对性的预防策略以保持认知和运动独立性的必要性。
{"title":"Markers of Biological Brain Aging Mediate Effects of Vascular Risk Factors on Cognitive and Motor Functions: A Multivariate Imaging Analysis of 40,579 Individuals","authors":"Marvin Petersen, Moritz Link, Carola Mayer, Felix Naegele, Maximilian Schell, Jens Fiehler, Juergen Link, Simone Kuehn, Raphael Twerenbold, Amir Omidvarnia, Felix Hoffstaedter, Kaustubh R. Patil, Simon B. Eickhoff, Goetz Thomalla, Bastian Cheng","doi":"10.1101/2024.07.24.24310926","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310926","url":null,"abstract":"The increasing global life expectancy brings forth challenges associated with age-related cognitive and motor declines. To better understand underlying mechanisms, we investigated the connection between markers of biological brain aging based on magnetic resonance imaging (MRI), cognitive and motor performance, as well as modifiable vascular risk factors, using a large-scale neuroimaging analysis in 40,579 individuals of the population-based UK Biobank and Hamburg City Health Study. Employing partial least squares correlation analysis (PLS), we investigated multivariate associative effects between three imaging markers of biological brain aging - relative brain age, white matter hyperintensities of presumed vascular origin, and peak-width of skeletonized mean diffusivity - and multi-domain cognitive test performances and motor test results. The PLS identified a latent dimension linking higher markers of biological brain aging to poorer cognitive and motor performances, accounting for 94.7% of shared variance. Furthermore, a mediation analysis revealed that biological brain aging mediated the relationship of vascular risk factors - including hypertension, glucose, obesity, and smoking - to cognitive and motor function. These results were replicable in both cohorts. By integrating multi-domain data with a comprehensive methodological approach, our study contributes evidence of a direct association between vascular health, biological brain aging, and functional cognitive as well as motor performance, emphasizing the need for early and targeted preventive strategies to maintain cognitive and motor independence in aging populations.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"245 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.24.24310884
Kevin Bonham, Guilherme Fahur Bottino, Emma T Margolis, Fadheela Patel, Michal Zieff, Shelley H McCann, Kirsten A Donald, Laurel J Gabard-Durnam, Vanja Klepac-Ceraj
Infancy is a time of rapid brain development supporting foundational sensory learning. The gut microbiome, also undergoing extensive developmental changes in early life, may influence brain development through metabolism of neuroactive compounds. Here, we show across the first 18 months of life that microbial genes encoding enzymes that produce and degrade neuroactive compounds, including neurotransmitters GABA and glutamate, the amino acid tryptophan, and short-chain fatty acids including acetate and butyrate, are associated with visual neurodevelopmental learning, measured by the visual-evoked potential (VEP). Microbial gene sets from stool collected around 4 months of age were strongly associated with VEP features measured from 9 to 14 months of age and showed more associations than concurrently measured gene sets, suggesting microbial metabolism in early life may have long term effects on neural plasticity and development.
{"title":"Co-development of gut microbial metabolism and visual neural circuitry in human infants","authors":"Kevin Bonham, Guilherme Fahur Bottino, Emma T Margolis, Fadheela Patel, Michal Zieff, Shelley H McCann, Kirsten A Donald, Laurel J Gabard-Durnam, Vanja Klepac-Ceraj","doi":"10.1101/2024.07.24.24310884","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310884","url":null,"abstract":"Infancy is a time of rapid brain development supporting foundational sensory learning. The gut microbiome, also undergoing extensive developmental changes in early life, may influence brain development through metabolism of neuroactive compounds. Here, we show across the first 18 months of life that microbial genes encoding enzymes that produce and degrade neuroactive compounds, including neurotransmitters GABA and glutamate, the amino acid tryptophan, and short-chain fatty acids including acetate and butyrate, are associated with visual neurodevelopmental learning, measured by the visual-evoked potential (VEP). Microbial gene sets from stool collected around 4 months of age were strongly associated with VEP features measured from 9 to 14 months of age and showed more associations than concurrently measured gene sets, suggesting microbial metabolism in early life may have long term effects on neural plasticity and development.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.24.24310932
Joao Manuel Ferreira
Objective This systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy. Methods: A systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria included peer-reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed. Results: From 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods employed for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception. Significance User involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy.
{"title":"User involvement in the design and development of medical devices in Epilepsy: a systematic review","authors":"Joao Manuel Ferreira","doi":"10.1101/2024.07.24.24310932","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310932","url":null,"abstract":"Objective This systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy.\u0000Methods: A systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria included peer-reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed.\u0000Results: From 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods employed for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception. Significance User involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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