{"title":"Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions.","authors":"Angela Wei, Richard Border, Boyang Fu, Sinead Cullina, Nadav Brandes, Seon-Kyeong Jang, Sriram Sankararaman, Eimear Kenny, Mariam S Udler, Vasilis Ntranos, Noah Zaitlen, Valerie Arboleda","doi":"10.1101/2023.09.14.23295564","DOIUrl":"10.1101/2023.09.14.23295564","url":null,"abstract":"<p><p>Over three percent of people carry a dominant pathogenic variant, yet only a fraction of carriers develop disease. Disease phenotypes from carriers of variants in the same gene range from mild to severe. Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (marginal epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai BioMe Biobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable carrier penetrance and disease severity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain- from loss-of-function variants. We also found that polygenic scores predicted phenotypes amongst pathogenic carriers and that epistatic effects can exceed main carrier effects by an order of magnitude.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41134269","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}
Jonathan Lucas Reddinger, Gary Charness, David Levine
{"title":"Vaccination as personal public good provision.","authors":"Jonathan Lucas Reddinger, Gary Charness, David Levine","doi":"10.1101/2022.04.21.22274110","DOIUrl":"10.1101/2022.04.21.22274110","url":null,"abstract":"<p><p>Vaccination against infectious diseases has both private and public benefits. We study whether social preferences-concerns for the well-being of other people-are associated with one's decision regarding vaccination. We measure these social preferences for 549 online subjects with a public-good game and an altruism game. To the extent that one gets vaccinated out of concern for the health of others, contribution in the public-good game is analogous to an individual's decision to obtain vaccination, while our altruism game provides a different measure of altruism, equity, and efficiency concerns. We proxy vaccine demand with how quickly a representative individual voluntarily took the initial vaccination for COVID-19 (after the vaccine was widely available). We collect COVID-19 vaccination history separately from the games to avoid experimenter-demand effects. We find a strong result: Contribution in the public-good game is associated with greater demand to voluntarily receive a first dose, and thus also to vaccinate earlier. Compared to a subject who contributes nothing, one who contributes the maximum ($4) is 58% more likely to obtain a first dose voluntarily in the four-month period that we study (April through August 2021). In short, people who are more pro-social are more likely to take a voluntary COVID-19 vaccination. Behavior in our altruism game does not predict vaccination. We recommend further research on the use of pro-social preferences to help motivate individuals to vaccinate for other transmissible diseases, such as the flu and HPV.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347278/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40667685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distinct explanations underlie gene-environment interactions in the UK Biobank.","authors":"Arun Durvasula, Alkes L Price","doi":"10.1101/2023.09.22.23295969","DOIUrl":"10.1101/2023.09.22.23295969","url":null,"abstract":"<p><p>The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized, but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for a given trait and E variable. First, we detect locus-specific GxE interaction by testing for genetic correlation <math><mfenced><mrow><msub><mrow><mi>r</mi></mrow><mrow><mi>g</mi></mrow></msub></mrow></mfenced><mo><</mo><mn>1</mn></math> across E bins. Second, we detect genome-wide effects of the E variable on genetic variance by leveraging polygenic risk scores (PRS) to test for significant PRSxE in a regression of phenotypes on PRS, E, and PRSxE, together with differences in SNP-heritability across E bins. Third, we detect genome-wide proportional amplification of genetic and environmental effects as a function of the E variable by testing for significant PRSxE with no differences in SNP-heritability across E bins. Simulations show that these approaches achieve high sensitivity and specificity in distinguishing these three GxE scenarios. We applied our framework to 33 UK Biobank traits (25 quantitative traits and 8 diseases; average <math><mi>N</mi><mo>=</mo><mn>325</mn><mtext>K</mtext></math>) and 10 E variables spanning lifestyle, diet, and other environmental exposures. First, we identified 19 trait-E pairs with <math><msub><mrow><mi>r</mi></mrow><mrow><mi>g</mi></mrow></msub></math> significantly < 1 (FDR<5%) (average <math><msub><mrow><mi>r</mi></mrow><mrow><mi>g</mi></mrow></msub><mo>=</mo><mn>0.95</mn></math>); for example, white blood cell count had <math><msub><mrow><mi>r</mi></mrow><mrow><mi>g</mi></mrow></msub><mo>=</mo><mn>0.95</mn></math> (s.e. 0.01) between smokers and non-smokers. Second, we identified 28 trait-E pairs with significant PRSxE and significant SNP-heritability differences across E bins; for example, BMI had a significant PRSxE for physical activity (P=4.6e-5) with 5% larger SNP-heritability in the largest versus smallest quintiles of physical activity (P=7e-4). Third, we identified 15 trait-E pairs with significant PRSxE with no SNP-heritability differences across E bins; for example, waist-hip ratio adjusted for BMI had a significant PRSxE effect for time spent watching television (P=5e-3) with no SNP-heritability differences. Across the three scenarios, 8 of the trait-E pairs involved disease traits, whose interpretation is complicated by scale effects. Analyses using biological sex as the E variable produced additional significant findings in each of the three scenarios. Overall, we infer a significant contribution of GxE and GxSex effects to complex trait and disease variance.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/81/66/nihpp-2023.09.22.23295969v1.PMC10543037.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41135523","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}
Soroosh Solhjoo, Mark C Haigney, Trishul Siddharthan, Abigail Koch, Naresh M Punjabi
{"title":"Sleep-Disordered Breathing Destabilizes Ventricular Repolarization.","authors":"Soroosh Solhjoo, Mark C Haigney, Trishul Siddharthan, Abigail Koch, Naresh M Punjabi","doi":"10.1101/2023.02.10.23285789","DOIUrl":"10.1101/2023.02.10.23285789","url":null,"abstract":"<p><strong>Rationale: </strong>Sleep-disordered breathing (SDB) increases the risk of cardiac arrhythmias and sudden cardiac death.</p><p><strong>Objectives: </strong>To characterize the associations between SDB, intermittent hypoxemia, and the beat-to-beat QT variability index (QTVI), a measure of ventricular repolarization lability associated with a higher risk for cardiac arrhythmias, sudden cardiac death, and mortality.</p><p><strong>Methods: </strong>Three distinct cohorts were used for the current study. The first cohort, used for cross-sectional analysis, was a matched sample of 122 participants with and without severe SDB. The second cohort, used for longitudinal analysis, consisted of a matched sample of 52 participants with and without incident SDB. The cross-sectional and longitudinal cohorts were selected from the Sleep Heart Health Study participants. The third cohort comprised 19 healthy adults exposed to acute intermittent hypoxia and ambient air on two separate days. Electrocardiographic measures were calculated from one-lead electrocardiograms.</p><p><strong>Results: </strong>Compared to those without SDB, participants with severe SDB had greater QTVI (-1.19 in participants with severe SDB vs. -1.43 in participants without SDB, <i>P</i> = 0.027), heart rate (68.34 vs. 64.92 beats/minute; <i>P</i> = 0.028), and hypoxemia burden during sleep as assessed by the total sleep time with oxygen saturation less than 90% (TST<sub>90</sub>; 11.39% vs. 1.32%, <i>P</i> < 0.001). TST<sub>90</sub>, but not the frequency of arousals, was a predictor of QTVI. QTVI during sleep was predictive of all-cause mortality. With incident SDB, mean QTVI increased from -1.23 to -0.86 over 5 years (<i>P</i> = 0.017). Finally, exposing healthy adults to acute intermittent hypoxia for four hours progressively increased QTVI (from -1.85 at baseline to -1.64 after four hours of intermittent hypoxia; <i>P</i> = 0.016).</p><p><strong>Conclusions: </strong>Prevalent and incident SDB are associated with ventricular repolarization instability, which predisposes to ventricular arrhythmias and sudden cardiac death. Intermittent hypoxemia destabilizes ventricular repolarization and may contribute to increased mortality in SDB.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d2/ed/nihpp-2023.02.10.23285789v2.PMC9949208.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9523826","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}
Perline A Demange, Dorret I Boomsma, Elsje van Bergen, Michel G Nivard
{"title":"Evaluating the causal relationship between educational attainment and mental health.","authors":"Perline A Demange, Dorret I Boomsma, Elsje van Bergen, Michel G Nivard","doi":"10.1101/2023.01.26.23285029","DOIUrl":"10.1101/2023.01.26.23285029","url":null,"abstract":"<p><p>We investigate the causal relationship between educational attainment (EA) and mental health using two research designs. First, we compare the relationship between EA and 18 psychiatric diagnoses within sibship in Dutch national registry data (N=1.7 million), thereby controlling for unmeasured familial factors. Second, we apply two-sample Mendelian Randomization, which uses genetic variants related to EA or psychiatric diagnosis as instrumental variables, to test whether there is a causal relation in either direction. Our results suggest that lower levels of EA causally increase the risk of MDD, ADHD, alcohol dependence, GAD and PTSD diagnoses. We also find evidence of a causal effect of ADHD on EA. For schizophrenia, anorexia nervosa, OCD, and bipolar disorder, results were inconsistent across the different approaches, highlighting the importance of using multiple research designs to understand complex relationships such as between EA and mental health.</p>","PeriodicalId":18659,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/cf/53/nihpp-2023.01.26.23285029v1.PMC9901051.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9295178","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}
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
{"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}
Molly F Lazarus, Virginia A Marchman, Edith Brignoni-Pérez, Sarah Dubner, Heidi M Feldman, Melissa Scala, Katherine E Travis
{"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}
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
{"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}
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
{"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}
Zack van Allen, Dan Orsholits, Matthieu P Boisgontier
{"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}