Pub Date : 2024-04-10DOI: 10.1101/2023.03.12.23287173
Qifang Bi, Barbra A Dickerman, Huong Q Nguyen, Emily T Martin, Manjusha Gaglani, Karen J Wernli, G K Balasubramani, Brendan Flannery, Marc Lipsitch, Sarah Cobey
Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influenced individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.
{"title":"Reduced effectiveness of repeat influenza vaccination: distinguishing among within-season waning, recent clinical infection, and subclinical infection.","authors":"Qifang Bi, Barbra A Dickerman, Huong Q Nguyen, Emily T Martin, Manjusha Gaglani, Karen J Wernli, G K Balasubramani, Brendan Flannery, Marc Lipsitch, Sarah Cobey","doi":"10.1101/2023.03.12.23287173","DOIUrl":"10.1101/2023.03.12.23287173","url":null,"abstract":"<p><p>Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influenced individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/8c/b7/nihpp-2023.03.12.23287173v2.PMC10071822.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9270190","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 : 2024-04-08DOI: 10.1101/2023.09.01.23294920
Markos Tesfaye, Piotr Jaholkowski, Alexey A Shadrin, Dennis van der Meer, Guy F L Hindley, Børge Holen, Nadine Parker, Pravesh Parekh, Viktoria Birkenæs, Zillur Rahman, Shahram Bahrami, Gleda Kutrolli, Oleksandr Frei, Srdjan Djurovic, Anders M Dale, Olav B Smeland, Kevin S O'Connell, Ole A Andreassen
Background: Anxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders.
Methods: We used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively.
Results: Anxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (n = 47), bipolar disorder (n = 33), schizophrenia (n = 71), and ADHD (n = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci.
Conclusions: Anxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.
{"title":"Identification of Novel Genomic Loci for Anxiety and Extensive Genetic Overlap with Psychiatric Disorders.","authors":"Markos Tesfaye, Piotr Jaholkowski, Alexey A Shadrin, Dennis van der Meer, Guy F L Hindley, Børge Holen, Nadine Parker, Pravesh Parekh, Viktoria Birkenæs, Zillur Rahman, Shahram Bahrami, Gleda Kutrolli, Oleksandr Frei, Srdjan Djurovic, Anders M Dale, Olav B Smeland, Kevin S O'Connell, Ole A Andreassen","doi":"10.1101/2023.09.01.23294920","DOIUrl":"10.1101/2023.09.01.23294920","url":null,"abstract":"<p><strong>Background: </strong>Anxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders.</p><p><strong>Methods: </strong>We used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively.</p><p><strong>Results: </strong>Anxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (<i>n</i> = 47), bipolar disorder (<i>n</i> = 33), schizophrenia (<i>n</i> = 71), and ADHD (<i>n</i> = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci.</p><p><strong>Conclusions: </strong>Anxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/eb/16/nihpp-2023.09.01.23294920v1.PMC10491354.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10297933","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 : 2024-04-08DOI: 10.1101/2023.04.06.23288260
Molly F Lazarus, Virginia A Marchman, Edith Brignoni-Pérez, Sarah Dubner, Heidi M Feldman, Melissa Scala, Katherine E Travis
Objective: Limited research links hospital-based experiences of skin-to-skin (STS) care to longer-term neurodevelopmental outcomes in preterm children. The present study examined relations between inpatient STS and neurodevelopmental scores measured at 12 months in a sample of very preterm (VPT) infants.
Study design and methods: From a retrospective study review of medical records of 181 VPT infants (<32 weeks gestational age (GA)) we derived the STS rate, i.e., the total minutes of STS each infant received/day of hospital stay. We used scores on the Capute Scales from routine follow-up care at 12 months as the measure of neurodevelopmental outcome (n=181).
Results: Families averaged approximately 17 minutes/day of STS care (2 days/week, 70 minutes/session), although there was substantial variability. Variation in STS rate was positively associated with outcomes at 12 months corrected age ( r = 0.25, p < .001). STS rate significantly predicted 6.2% unique variance in 12-month neurodevelopmental outcomes, after controlling for GA, socioeconomic status (SES), health acuity, and visitation frequency. A 20-minute increase in STS per day was associated with a 10-point increase (.67 SDs) in neurodevelopmental outcomes at 12 months. SES, GA, and infant health acuity did not moderate these relations.
Conclusion: VPT infants who experienced more STS during hospitalization demonstrated higher scores on 12-month assessments of neurodevelopment. Results provide evidence that STS care may confer extended neuroprotection on VPT infants through the first year of life.
{"title":"Inpatient Skin-to-Skin Care Predicts 12-month Neurodevelopmental Outcomes in Very Preterm Infants.","authors":"Molly F Lazarus, Virginia A Marchman, Edith Brignoni-Pérez, Sarah Dubner, Heidi M Feldman, Melissa Scala, Katherine E Travis","doi":"10.1101/2023.04.06.23288260","DOIUrl":"10.1101/2023.04.06.23288260","url":null,"abstract":"<p><strong>Objective: </strong>Limited research links hospital-based experiences of skin-to-skin (STS) care to longer-term neurodevelopmental outcomes in preterm children. The present study examined relations between inpatient STS and neurodevelopmental scores measured at 12 months in a sample of very preterm (VPT) infants.</p><p><strong>Study design and methods: </strong>From a retrospective study review of medical records of 181 VPT infants (<32 weeks gestational age (GA)) we derived the STS rate, i.e., the total minutes of STS each infant received/day of hospital stay. We used scores on the Capute Scales from routine follow-up care at 12 months as the measure of neurodevelopmental outcome (n=181).</p><p><strong>Results: </strong>Families averaged approximately 17 minutes/day of STS care (2 days/week, 70 minutes/session), although there was substantial variability. Variation in STS rate was positively associated with outcomes at 12 months corrected age ( <i>r</i> = 0.25, <i>p <</i> .001). STS rate significantly predicted 6.2% unique variance in 12-month neurodevelopmental outcomes, after controlling for GA, socioeconomic status (SES), health acuity, and visitation frequency. A 20-minute increase in STS per day was associated with a 10-point increase (.67 SDs) in neurodevelopmental outcomes at 12 months. SES, GA, and infant health acuity did not moderate these relations.</p><p><strong>Conclusion: </strong>VPT infants who experienced more STS during hospitalization demonstrated higher scores on 12-month assessments of neurodevelopment. Results provide evidence that STS care may confer extended neuroprotection on VPT infants through the first year of life.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9303403","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 : 2024-04-08DOI: 10.1101/2023.09.14.23295596
Parikshit Juvekar, Reuben Dorent, Fryderyk Kögl, Erickson Torio, Colton Barr, Laura Rigolo, Colin Galvin, Nick Jowkar, Anees Kazi, Nazim Haouchine, Harneet Cheema, Nassir Navab, Steve Pieper, William M Wells, Wenya Linda Bi, Alexandra Golby, Sarah Frisken, Tina Kapur
The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue. Intraoperative magnetic resonance imaging (iMRI) and ultrasound (iUS) help visualize the tumor and brain shift. iUS is faster and easier to incorporate into surgical workflows but offers a lower contrast between tumorous and healthy tissues than iMRI. With the success of data-hungry Artificial Intelligence algorithms in medical image analysis, the benefits of sharing well-curated data cannot be overstated. To this end, we provide the largest publicly available MRI and iUS database of surgically treated brain tumors, including gliomas (n=92), metastases (n=11), and others (n=11). This collection contains 369 preoperative MRI series, 320 3D iUS series, 301 iMRI series, and 356 segmentations collected from 114 consecutive patients at a single institution. This database is expected to help brain shift and image analysis research and neurosurgical training in interpreting iUS and iMRI.
{"title":"ReMIND: The Brain Resection Multimodal Imaging Database.","authors":"Parikshit Juvekar, Reuben Dorent, Fryderyk Kögl, Erickson Torio, Colton Barr, Laura Rigolo, Colin Galvin, Nick Jowkar, Anees Kazi, Nazim Haouchine, Harneet Cheema, Nassir Navab, Steve Pieper, William M Wells, Wenya Linda Bi, Alexandra Golby, Sarah Frisken, Tina Kapur","doi":"10.1101/2023.09.14.23295596","DOIUrl":"10.1101/2023.09.14.23295596","url":null,"abstract":"<p><p>The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue. Intraoperative magnetic resonance imaging (iMRI) and ultrasound (iUS) help visualize the tumor and brain shift. iUS is faster and easier to incorporate into surgical workflows but offers a lower contrast between tumorous and healthy tissues than iMRI. With the success of data-hungry Artificial Intelligence algorithms in medical image analysis, the benefits of sharing well-curated data cannot be overstated. To this end, we provide the largest publicly available MRI and iUS database of surgically treated brain tumors, including gliomas (n=92), metastases (n=11), and others (n=11). This collection contains 369 preoperative MRI series, 320 3D iUS series, 301 iMRI series, and 356 segmentations collected from 114 consecutive patients at a single institution. This database is expected to help brain shift and image analysis research and neurosurgical training in interpreting iUS and iMRI.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516086/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41135808","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 : 2024-04-04DOI: 10.1101/2023.09.14.23295576
Zack van Allen, Dan Orsholits, Matthieu P Boisgontier
Objective: In the chronic phase after a stroke, limitations in activities of daily living (ADLs) and instrumental ADL (IADLs) initially plateau before steadily increasing. The benefits of pre-stroke physical activity on these limitations remain unclear. To clarify this relationship, we examined the effect of physical activity on the long-term evolution of functional limitations in a cohort of stroke survivors and compared it to a cohort of matched stroke-free adults.
Methods: Longitudinal data from 2,143 stroke survivors and 10,717 stroke-free adults aged 50 years and older were drawn from a prospective cohort study based on the Survey of Health, Ageing and Retirement in Europe (2004-2022; 8 data collection waves). Physical activity was assessed in the pre-stroke wave. Functional limitations were assessed in the post-stroke waves. Each stroke survivor was matched with 5 stroke-free adults who had similar propensity scores computed on the basis of key covariates, including baseline age, sex, body mass index, limitations in ADL and IADL, chronic conditions and country of residence, before any of the participants from either cohort had experienced a stroke.
Results: Results showed an interaction between stroke status and physical activity on ADL limitations (b = -0.076; 95% CI = -0.142 to -0.011), with the effect of physical activity being stronger in stroke survivors (b = -0.345, 95% CI = -0.438 to -0.252) than in stroke-free adults (b = -0.269, 95% CI = -0.269 to -0.241).
Conclusion: The beneficial effect of pre-stroke physical activity on ADL limitations after stroke is stronger than its effect in matched stroke-free adults followed for a similar number of years.
Impact: Physical activity, an intervention within the physical therapist's scope of practice, is effective in reducing the risk of functional dependence after stroke. Moreover, pre-stroke levels of physical activity can inform the prognosis of functional dependence in stroke survivors.
{"title":"Pre-stroke physical activity matters for functional limitations: A longitudinal case-control study of 12,860 participants.","authors":"Zack van Allen, Dan Orsholits, Matthieu P Boisgontier","doi":"10.1101/2023.09.14.23295576","DOIUrl":"10.1101/2023.09.14.23295576","url":null,"abstract":"<p><strong>Objective: </strong>In the chronic phase after a stroke, limitations in activities of daily living (ADLs) and instrumental ADL (IADLs) initially plateau before steadily increasing. The benefits of pre-stroke physical activity on these limitations remain unclear. To clarify this relationship, we examined the effect of physical activity on the long-term evolution of functional limitations in a cohort of stroke survivors and compared it to a cohort of matched stroke-free adults.</p><p><strong>Methods: </strong>Longitudinal data from 2,143 stroke survivors and 10,717 stroke-free adults aged 50 years and older were drawn from a prospective cohort study based on the Survey of Health, Ageing and Retirement in Europe (2004-2022; 8 data collection waves). Physical activity was assessed in the pre-stroke wave. Functional limitations were assessed in the post-stroke waves. Each stroke survivor was matched with 5 stroke-free adults who had similar propensity scores computed on the basis of key covariates, including baseline age, sex, body mass index, limitations in ADL and IADL, chronic conditions and country of residence, before any of the participants from either cohort had experienced a stroke.</p><p><strong>Results: </strong>Results showed an interaction between stroke status and physical activity on ADL limitations (b = -0.076; 95% CI = -0.142 to -0.011), with the effect of physical activity being stronger in stroke survivors (b = -0.345, 95% CI = -0.438 to -0.252) than in stroke-free adults (b = -0.269, 95% CI = -0.269 to -0.241).</p><p><strong>Conclusion: </strong>The beneficial effect of pre-stroke physical activity on ADL limitations after stroke is stronger than its effect in matched stroke-free adults followed for a similar number of years.</p><p><strong>Impact: </strong>Physical activity, an intervention within the physical therapist's scope of practice, is effective in reducing the risk of functional dependence after stroke. Moreover, pre-stroke levels of physical activity can inform the prognosis of functional dependence in stroke survivors.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41140847","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 : 2024-03-27DOI: 10.1101/2022.09.13.22279673
James T Anibal, Adam J Landa, Nguyen T T Hang, Miranda J Song, Alec K Peltekian, Ashley Shin, Hannah B Huth, Lindsey A Hazen, Anna S Christou, Jocelyne Rivera, Robert A Morhard, Ulas Bagci, Ming Li, Yael Bensoussan, David A Clifton, Bradford J Wood
Publicly available audio data presents a unique opportunity for the development of digital health technologies with large language models (LLMs). In this study, YouTube was mined to collect audio data from individuals with self-declared positive COVID-19 tests as well as those with other upper respiratory infections (URI) and healthy subjects discussing a diverse range of topics. The resulting dataset was transcribed with the Whisper model and used to assess the capacity of LLMs for detecting self-reported COVID-19 cases and performing variant classification. Following prompt optimization, LLMs achieved accuracies of 0.89, 0.97, respectively, in the tasks of identifying self-reported COVID-19 cases and other respiratory illnesses. The model also obtained a mean accuracy of 0.77 at identifying the variant of self-reported COVID-19 cases using only symptoms and other health-related factors described in the YouTube videos. In comparison with past studies, which used scripted, standardized voice samples to capture biomarkers, this study focused on extracting meaningful information from public online audio data. This work introduced novel design paradigms for pandemic management tools, showing the potential of audio data in clinical and public health applications.
{"title":"Omicron detection with large language models and YouTube audio data.","authors":"James T Anibal, Adam J Landa, Nguyen T T Hang, Miranda J Song, Alec K Peltekian, Ashley Shin, Hannah B Huth, Lindsey A Hazen, Anna S Christou, Jocelyne Rivera, Robert A Morhard, Ulas Bagci, Ming Li, Yael Bensoussan, David A Clifton, Bradford J Wood","doi":"10.1101/2022.09.13.22279673","DOIUrl":"10.1101/2022.09.13.22279673","url":null,"abstract":"<p><p>Publicly available audio data presents a unique opportunity for the development of digital health technologies with large language models (LLMs). In this study, YouTube was mined to collect audio data from individuals with self-declared positive COVID-19 tests as well as those with other upper respiratory infections (URI) and healthy subjects discussing a diverse range of topics. The resulting dataset was transcribed with the Whisper model and used to assess the capacity of LLMs for detecting self-reported COVID-19 cases and performing variant classification. Following prompt optimization, LLMs achieved accuracies of 0.89, 0.97, respectively, in the tasks of identifying self-reported COVID-19 cases and other respiratory illnesses. The model also obtained a mean accuracy of 0.77 at identifying the variant of self-reported COVID-19 cases using only symptoms and other health-related factors described in the YouTube videos. In comparison with past studies, which used scripted, standardized voice samples to capture biomarkers, this study focused on extracting meaningful information from public online audio data. This work introduced novel design paradigms for pandemic management tools, showing the potential of audio data in clinical and public health applications.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10469112","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 : 2024-03-26DOI: 10.1101/2023.06.24.23291169
Alejandro Arbona-Lampaya, Heejong Sung, Alexander D'Amico, Emma E M Knowles, Emily K Besançon, Ally Freifeld, Ley Lacbawan, Fabiana Lopes, Layla Kassem, Antonio E Nardi, Francis J McMahon
Background: Bipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainly, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.
Methods: Participants in the Amish-Mennonite Bipolar Genetics (AMBiGen) study were assigned categorical mood disorder diagnoses by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment. Major MDQ dimensions were analyzed by Principal Component Analysis (PCA) in 726 participants. Heritability and genetic overlaps between categorical diagnoses and MDQ-derived dimensions were estimated with SOLAR-ECLIPSE within 432 genotyped participants.
Results: MDQ scores were significantly higher among individuals diagnosed with BD and related disorders, as expected, but varied widely among relatives. PCA suggested a three-component model for the MDQ. Heritability of the MDQ score was 30% (p<0.001), evenly distributed across its three principal components. Strong and significant genetic correlations were found between categorical diagnoses and most MDQ measures.
Limitations: Recruitment through probands with BD resulted in increased prevalence of BD in this sample, limiting generalizability. Unavailable genetic data reduced sample size for some analyses.
Conclusion: heritability and high genetic correlations between categorical diagnoses and MDQ measures support a genetic continuity between dimensional and categorical models of BD.
{"title":"Strong Genetic Overlaps Between Dimensional and Categorical Models of Bipolar Disorders in a Family Sample.","authors":"Alejandro Arbona-Lampaya, Heejong Sung, Alexander D'Amico, Emma E M Knowles, Emily K Besançon, Ally Freifeld, Ley Lacbawan, Fabiana Lopes, Layla Kassem, Antonio E Nardi, Francis J McMahon","doi":"10.1101/2023.06.24.23291169","DOIUrl":"10.1101/2023.06.24.23291169","url":null,"abstract":"<p><strong>Background: </strong>Bipolar disorder (BD) presents with a wide range of symptoms that vary among relatives, casting doubt on categorical illness models. To address this uncertainly, we investigated the heritability and genetic relationships between categorical and dimensional models of BD in a family sample.</p><p><strong>Methods: </strong>Participants in the Amish-Mennonite Bipolar Genetics (AMBiGen) study were assigned categorical mood disorder diagnoses by structured psychiatric interview and completed the Mood Disorder Questionnaire (MDQ), which assesses lifetime history of manic symptoms and associated impairment. Major MDQ dimensions were analyzed by Principal Component Analysis (PCA) in 726 participants. Heritability and genetic overlaps between categorical diagnoses and MDQ-derived dimensions were estimated with SOLAR-ECLIPSE within 432 genotyped participants.</p><p><strong>Results: </strong>MDQ scores were significantly higher among individuals diagnosed with BD and related disorders, as expected, but varied widely among relatives. PCA suggested a three-component model for the MDQ. Heritability of the MDQ score was 30% (p<0.001), evenly distributed across its three principal components. Strong and significant genetic correlations were found between categorical diagnoses and most MDQ measures.</p><p><strong>Limitations: </strong>Recruitment through probands with BD resulted in increased prevalence of BD in this sample, limiting generalizability. Unavailable genetic data reduced sample size for some analyses.</p><p><strong>Conclusion: </strong>heritability and high genetic correlations between categorical diagnoses and MDQ measures support a genetic continuity between dimensional and categorical models of BD.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9899210","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 : 2024-03-26DOI: 10.1101/2023.05.19.23290190
Argita D Salindri, Maia Kipiani, Nino Lomtadze, Nestani Tukvadze, Zaza Avaliani, Henry M Blumberg, Katherine E Masyn, Richard B Rothenberg, Russell R Kempker, Matthew J Magee
Little is known regarding the relationship between common comorbidities in persons with tuberculosis (TB) (including human immunodeficiency virus [HIV], diabetes, and hepatitis C virus [HCV]) with post-TB mortality. We conducted a retrospective cohort study among persons who initiated treatment for rifampicin-resistant and multi/extensively drug-resistant (RR and M/XDR) TB reported to the country of Georgia's TB surveillance during 2009-2017. Exposures included HIV serologic status, diabetes, and HCV status. Our outcome was all-cause post-TB mortality determined by cross-validating vital status with Georgia's death registry through November 2019. We estimated adjusted hazard rate ratios (aHR) and 95% confidence intervals (CI) of post-TB mortality among participants with and without comorbidities using cause-specific hazard regressions. Among 1032 eligible participants, 34 (3.3%) died during treatment and 87 (8.7%) died post-TB treatment. Among those who died post-TB treatment, the median time to death was 21 months (interquartile range 7-39) post-TB treatment. After adjusting for confounders, the hazard rates of post-TB mortality were higher among participants with HIV co-infection (aHR=3.74, 95%CI 1.77-7.91) compared to those without HIV co-infection. In our cohort, post-TB mortality occurred most commonly in the first three years post-TB treatment. Linkage to care for common TB comorbidities post-treatment may reduce post-TB mortality rates.
{"title":"HIV co-infection increases the risk of post-tuberculosis mortality among persons who initiated treatment for drug-resistant tuberculosis.","authors":"Argita D Salindri, Maia Kipiani, Nino Lomtadze, Nestani Tukvadze, Zaza Avaliani, Henry M Blumberg, Katherine E Masyn, Richard B Rothenberg, Russell R Kempker, Matthew J Magee","doi":"10.1101/2023.05.19.23290190","DOIUrl":"10.1101/2023.05.19.23290190","url":null,"abstract":"<p><p>Little is known regarding the relationship between common comorbidities in persons with tuberculosis (TB) (including human immunodeficiency virus [HIV], diabetes, and hepatitis C virus [HCV]) with post-TB mortality. We conducted a retrospective cohort study among persons who initiated treatment for rifampicin-resistant and multi/extensively drug-resistant (RR and M/XDR) TB reported to the country of Georgia's TB surveillance during 2009-2017. Exposures included HIV serologic status, diabetes, and HCV status. Our outcome was all-cause post-TB mortality determined by cross-validating vital status with Georgia's death registry through November 2019. We estimated adjusted hazard rate ratios (aHR) and 95% confidence intervals (CI) of post-TB mortality among participants with and without comorbidities using cause-specific hazard regressions. Among 1032 eligible participants, 34 (3.3%) died during treatment and 87 (8.7%) died post-TB treatment. Among those who died post-TB treatment, the median time to death was 21 months (interquartile range 7-39) post-TB treatment. After adjusting for confounders, the hazard rates of post-TB mortality were higher among participants with HIV co-infection (aHR=3.74, 95%CI 1.77-7.91) compared to those without HIV co-infection. In our cohort, post-TB mortality occurred most commonly in the first three years post-TB treatment. Linkage to care for common TB comorbidities post-treatment may reduce post-TB mortality rates.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/41/78/nihpp-2023.05.19.23290190v1.PMC10246159.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9994502","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 : 2024-03-20DOI: 10.1101/2020.11.23.20235945
Daniel M Low, Vishwanatha Rao, Gregory Randolph, Phillip C Song, Satrajit S Ghosh
Introduction: Detecting voice disorders from voice recordings could allow for frequent, remote, and low-cost screening before costly clinical visits and a more invasive laryngoscopy examination. Our goals were to detect unilateral vocal fold paralysis (UVFP) from voice recordings using machine learning, to identify which acoustic variables were important for prediction to increase trust, and to determine model performance relative to clinician performance.
Methods: Patients with confirmed UVFP through endoscopic examination (N=77) and controls with normal voices matched for age and sex (N=77) were included. Voice samples were elicited by reading the Rainbow Passage and sustaining phonation of the vowel "a". Four machine learning models of differing complexity were used. SHapley Additive explanations (SHAP) was used to identify important features.
Results: The highest median bootstrapped ROC AUC score was 0.87 and beat clinician's performance (range: 0.74 - 0.81) based on the recordings. Recording durations were different between UVFP recordings and controls due to how that data was originally processed when storing, which we can show can classify both groups. And counterintuitively, many UVFP recordings had higher intensity than controls, when UVFP patients tend to have weaker voices, revealing a dataset-specific bias which we mitigate in an additional analysis.
Conclusion: We demonstrate that recording biases in audio duration and intensity created dataset-specific differences between patients and controls, which models used to improve classification. Furthermore, clinician's ratings provide further evidence that patients were over-projecting their voices and being recorded at a higher amplitude signal than controls. Interestingly, after matching audio duration and removing variables associated with intensity in order to mitigate the biases, the models were able to achieve a similar high performance. We provide a set of recommendations to avoid bias when building and evaluating machine learning models for screening in laryngology.
{"title":"Identifying bias in models that detect vocal fold paralysis from audio recordings using explainable machine learning and clinician ratings.","authors":"Daniel M Low, Vishwanatha Rao, Gregory Randolph, Phillip C Song, Satrajit S Ghosh","doi":"10.1101/2020.11.23.20235945","DOIUrl":"10.1101/2020.11.23.20235945","url":null,"abstract":"<p><strong>Introduction: </strong>Detecting voice disorders from voice recordings could allow for frequent, remote, and low-cost screening before costly clinical visits and a more invasive laryngoscopy examination. Our goals were to detect unilateral vocal fold paralysis (UVFP) from voice recordings using machine learning, to identify which acoustic variables were important for prediction to increase trust, and to determine model performance relative to clinician performance.</p><p><strong>Methods: </strong>Patients with confirmed UVFP through endoscopic examination (N=77) and controls with normal voices matched for age and sex (N=77) were included. Voice samples were elicited by reading the Rainbow Passage and sustaining phonation of the vowel \"a\". Four machine learning models of differing complexity were used. SHapley Additive explanations (SHAP) was used to identify important features.</p><p><strong>Results: </strong>The highest median bootstrapped ROC AUC score was 0.87 and beat clinician's performance (range: 0.74 - 0.81) based on the recordings. Recording durations were different between UVFP recordings and controls due to how that data was originally processed when storing, which we can show can classify both groups. And counterintuitively, many UVFP recordings had higher intensity than controls, when UVFP patients tend to have weaker voices, revealing a dataset-specific bias which we mitigate in an additional analysis.</p><p><strong>Conclusion: </strong>We demonstrate that recording biases in audio duration and intensity created dataset-specific differences between patients and controls, which models used to improve classification. Furthermore, clinician's ratings provide further evidence that patients were over-projecting their voices and being recorded at a higher amplitude signal than controls. Interestingly, after matching audio duration and removing variables associated with intensity in order to mitigate the biases, the models were able to achieve a similar high performance. We provide a set of recommendations to avoid bias when building and evaluating machine learning models for screening in laryngology.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9e/ea/nihpp-2020.11.23.20235945v6.PMC7836138.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9901589","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 : 2024-03-08DOI: 10.1101/2023.04.24.23289028
P Aranega-Bou, C Cornbill, G Rodger, M Bird, G Moore, A Roohi, K L Hopkins, S Hopkins, P Ribeca, N Stoesser, S I Lipworth
The authors have withdrawn their manuscript due to becoming aware of methodology issues related to the curation of the training set used to determine cut-off values for Biotyper cluster assignation and lack of replicate measurements on different days for the isolates analysed. It is therefore unclear whether the conclusions of the manuscript are founded and no further work is possible to correct these issues as the instrument is no longer available to the authors. If you have any questions, please contact the corresponding author.
{"title":"WITHDRAWN: Evaluation of Fourier Transform Infrared spectroscopy (IR Biotyper) as a complement to Whole genome sequencing (WGS) to characterise <i>Enterobacter cloacae</i> , <i>Citrobacter freundii</i> and <i>Klebsiella pneumoniae</i> isolates recovered from hospital sinks.","authors":"P Aranega-Bou, C Cornbill, G Rodger, M Bird, G Moore, A Roohi, K L Hopkins, S Hopkins, P Ribeca, N Stoesser, S I Lipworth","doi":"10.1101/2023.04.24.23289028","DOIUrl":"10.1101/2023.04.24.23289028","url":null,"abstract":"<p><p>The authors have withdrawn their manuscript due to becoming aware of methodology issues related to the curation of the training set used to determine cut-off values for Biotyper cluster assignation and lack of replicate measurements on different days for the isolates analysed. It is therefore unclear whether the conclusions of the manuscript are founded and no further work is possible to correct these issues as the instrument is no longer available to the authors. If you have any questions, please contact the corresponding author.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a2/cc/nihpp-2023.04.24.23289028v1.PMC10193520.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9506083","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}