Biomarkers in Neuropsychiatry最新文献

{"title":"Cardiovascular risk factors as potential biomarkers of length of hospital stay and rehospitalization in mood disorders – a retrospective study","authors":"Eva Kathrin Lamadé ,&nbsp;Bruno Pedraz-Petrozzi ,&nbsp;Bernhard Schaupp ,&nbsp;Nicole Özer ,&nbsp;Bertram Krumm ,&nbsp;Michaela Coenen ,&nbsp;Sibylle Häfner ,&nbsp;Maria Gilles ,&nbsp;Andreas Meyer-Lindenberg ,&nbsp;Michael Deuschle","doi":"10.1016/j.bionps.2024.100109","DOIUrl":"10.1016/j.bionps.2024.100109","url":null,"abstract":"<div><h3>Objective</h3><div>Cardiovascular diseases are often comorbid with mood disorders, increasing the burden on patients. Few studies explore the role of cardiovascular disease on psychiatric inpatient stays. This retrospective study investigated the association of cardiovascular risk factors during an index stay on psychiatric length of stays and rehospitalization in the subsequent 10 years in patients with mood disorders.</div></div><div><h3>Methods</h3><div>Patients with a first inpatient stay in two German psychiatric hospitals, diagnosed with F31 (bipolar affective disorder), F32 (depressive episode) or F33 (recurrent depressive disorder) were investigated (n=930). The association of hypertension, hypercholesterolemia, and type 2 diabetes mellitus at the index stay with total length of stays, average length of stay and rehospitalization in the next 10 years was investigated in bivariate, and multivariate regression analyses, adjusting for sex, age, BMI, smoking, taking antidepressants and antipsychotics.</div></div><div><h3>Results</h3><div>Patients averaged 99.27 (± 134.94) inpatient days within 10 years, patients with hypertension 138.09 (± 162.85) days. Controlling for confounders, hypertension associated with longer total length of stays (β=0.105, p=0.044), hypertension (β=0.146, p=0.004), hypercholesterolemia (β=0.104, p=0.034) and diabetes (β=0.103, p=0.015) linked to more rehospitalizations and not having hypercholesterolemia (β=0.101, p=0.041) related to longer average stays. Sex mediated the relationship between hypercholesterolemia and both rehospitalization (F=11.60, p&lt;0.001) and total length of stays (F=7.21, p=0.007), with males with hypercholesterolemia showing more rehospitalization and longer total length of stays than females.</div></div><div><h3>Conclusion</h3><div>Cardiovascular risk factors were associated with duration and frequency of psychiatric inpatient stays in patients with mood disorders. Cardiovascular risk factors as potential predictive biomarkers for the course of disease of mood disorders should be monitored and managed.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"11 ","pages":"Article 100109"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534675","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":"An emotional distress biomarker in pregnant women: Ultra-short-term heart rate variability","authors":"Weiyi Xie ,&nbsp;Man Wang ,&nbsp;Hui Yun Li ,&nbsp;Pingqiao Wang ,&nbsp;Clifton Robert Emery ,&nbsp;Siuman Ng","doi":"10.1016/j.bionps.2024.100103","DOIUrl":"10.1016/j.bionps.2024.100103","url":null,"abstract":"<div><p>Prenatal emotional distress is common in pregnant women. Altered emotional distress can occur from the very beginning to the end of pregnancy. Heart rate variability (HRV) has recently become considered to be a potentially reliable psychophysiological stress biomarker in adults. In the current study, we evaluated ultra-short-term HRV (1-minute measurement) as a psychophysiological biomarker by examining the association between HRV parameters and self-reported prenatal emotional distress among pregnant women (<em>N</em> = 230) across three trimesters of pregnancy.</p></div><div><h3>Results</h3><p>Prenatal emotional distress was associated with a lower root mean square of successive differences between normal heartbeats (RMSSD), NN50, and SDNN Index among pregnant women who are in the second trimester. For women in the first and third trimester of pregnancy, prenatal emotional distress was not significantly correlated with any HRV indicators.</p></div><div><h3>Limitations</h3><p>The cross-sectional nature of our results limits the directional expression and assessment of the relationships, and longitudinal studies that target the recruitment of more pregnant women with subtypes of emotional distress issues are also needed.</p></div><div><h3>Conclusions</h3><p>Time-domain parameters of low HRV (associated with reduced parasympathetic activity) can potentially serve as an efficient psychophysiological biomarker for prenatal emotional distress in the second trimester of pregnancy. However, the time-domain HRV indicators in pregnant women in the first and third trimesters may be affected by other physiological and psychological fluctuations, thus decreasing the HRV biomarker’s efficiency in predicting their prenatal emotional distress.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"11 ","pages":"Article 100103"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000212/pdfft?md5=e9c0abe06f20dd4d7947b7af16759112&pid=1-s2.0-S2666144624000212-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141850955","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":"Biomarker discovery using machine learning in the psychosis spectrum","authors":"Walid Yassin ,&nbsp;Kendra M. Loedige ,&nbsp;Cassandra M.J. Wannan ,&nbsp;Kristina M. Holton ,&nbsp;Jonathan Chevinsky ,&nbsp;John Torous ,&nbsp;Mei-Hua Hall ,&nbsp;Rochelle Ruby Ye ,&nbsp;Poornima Kumar ,&nbsp;Sidhant Chopra ,&nbsp;Kshitij Kumar ,&nbsp;Jibran Y. Khokhar ,&nbsp;Eric Margolis ,&nbsp;Alessandro S. De Nadai","doi":"10.1016/j.bionps.2024.100107","DOIUrl":"10.1016/j.bionps.2024.100107","url":null,"abstract":"<div><p>The past decade witnessed substantial discoveries related to the psychosis spectrum. Many of these discoveries resulted from pursuits of objective and quantifiable biomarkers in tandem with the application of analytical tools such as machine learning. These approaches provided exciting new insights that significantly helped improve precision in diagnosis, prognosis, and treatment. This article provides an overview of how machine learning has been employed in recent biomarker discovery research in the psychosis spectrum, which includes schizophrenia, schizoaffective disorders, bipolar disorder with psychosis, first episode psychosis, and clinical high risk for psychosis. It highlights both human and animal model studies and explores a varying range of the most impactful biomarkers including cognition, neuroimaging, electrophysiology, and digital markers. We specifically highlight new applications and opportunities for machine learning to impact noninvasive symptom monitoring, prediction of future diagnosis and treatment outcomes, integration of new methods with traditional clinical research and practice, and personalized medicine approaches.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"11 ","pages":"Article 100107"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266614462400025X/pdfft?md5=7101ef10363447bdeb9452c0a8f96944&pid=1-s2.0-S266614462400025X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142087406","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":"Salivary cortisol in Schizophrenia: a selective review and meta-analysis of controlled studies of the past decade","authors":"Walter Paganin ,&nbsp;Sabrina Signorini","doi":"10.1016/j.bionps.2024.100098","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100098","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;p&gt;Stress and trauma significantly contribute to various psychiatric disorders, including schizophrenia. Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, particularly abnormal cortisol secretion, is implicated in schizophrenia's pathophysiology. Salivary cortisol, a convenient measure, provides insights into HPA axis activity. This systematic review and meta-analysis assess salivary cortisol levels in individuals with schizophrenia compared to healthy controls, evaluating its potential as a biomarker for schizophrenia.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Aim&lt;/h3&gt;&lt;p&gt;To assess the differences in salivary cortisol levels at baseline and in response to stress between patients with schizophrenia and healthy controls, determining the reliability of salivary cortisol as a biomarker for schizophrenia.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;p&gt;A systematic review and meta-analysis were conducted following PRISMA guidelines. We searched MEDLINE/PubMed, Cochrane Central, and EMBASE for human studies on schizophrenia and controls published from January 1, 2013, to July 1, 2023, reporting baseline or post-stress salivary cortisol levels. Exclusions were non-human studies, non-specific schizophrenia diagnoses, or missing cortisol data. Two reviewers independently extracted data and appraised quality, resolving discrepancies by consensus. Due to significant heterogeneity (I² = 94 % for baseline, 75 % for stress response), a random effects model was used.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;p&gt;Nineteen studies were initially selected, with twelve excluded due to non-specific schizophrenia diagnoses and missing cortisol data. The final meta-analysis included seven studies with 507 schizophrenia patients and 175 healthy controls. Key findings include:&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Baseline cortisol levels&lt;/h3&gt;&lt;p&gt;No significant difference in baseline salivary cortisol levels between schizophrenia patients and healthy controls (pooled estimate: −0.02, 95 % CI: −0.47–0.42).&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Cortisol response to stress&lt;/h3&gt;&lt;p&gt;No significant difference in post-stress cortisol levels between the two groups (pooled estimate: 0.03, 95 % CI: −1.84–1.79).&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study variability&lt;/h3&gt;&lt;p&gt;High variability across studies due to differences in design, patient characteristics, and cortisol measurement techniques. Despite some evidence of altered cortisol dynamics in schizophrenia, high variability in methodologies and confounding factors like medication use and psychosocial stressors complicate definitive conclusions.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;p&gt;The review underscores the potential of cortisol as a biomarker for stress response; however, its use in diagnosing schizophrenia remains inconclusive. Individual variability and methodological differences limit the diagnostic accuracy of salivary cortisol. Future research with larger sample sizes, uniform methodologies, and comprehensive control for confounding variables is essential to elucidate the role of salivary corti","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"11 ","pages":"Article 100098"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000169/pdfft?md5=f058592a4a65c1f2622d205f6da551b1&pid=1-s2.0-S2666144624000169-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434990","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":"Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis","authors":"Jonatan M. Panula ,&nbsp;Athanasios Gotsopoulos ,&nbsp;Jussi Alho ,&nbsp;Jaana Suvisaari ,&nbsp;Maija Lindgren ,&nbsp;Tuula Kieseppä ,&nbsp;Tuukka T. Raij","doi":"10.1016/j.bionps.2024.100102","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100102","url":null,"abstract":"<div><p>As many as one third of the patients diagnosed with schizophrenia do not respond to first-line antipsychotic medication. This group may benefit from the atypical antipsychotic medication clozapine, but initiation of treatment is often delayed, which may worsen prognosis. Predicting which patients do not respond to traditional antipsychotic medication at the onset of symptoms would provide fast-tracked treatment for this group of patients. We collected data from patient records of 38 first-episode psychosis patients, of whom seven did not respond to traditional antipsychotic medications. We used clinical data including medical records, voxel-based morphometry MRI data and inter-subject correlation fMRI data, obtained during movie viewing, to predict future treatment resistance. Using a neural network model, we correctly predicted future treatment resistance in six of the seven treatment resistance patients and 25 of 31 patients who did not require clozapine treatment. Prediction improved significantly when using imaging data in tandem with clinical data. The accuracy of the neural network model was significantly higher than the accuracy of a support vector machine algorithm. These results support the notion that treatment resistant schizophrenia could represent a separate entity of psychotic disorders, characterized by morphological and functional changes in the brain which could represent biomarkers detectable at early onset of symptoms.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"11 ","pages":"Article 100102"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000200/pdfft?md5=1537d8d8bee9b33c989ae141572cc29c&pid=1-s2.0-S2666144624000200-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605922","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":"Biomarkers of neurocognitive disorders: A ray of hope on the horizon?","authors":"Rita Khoury,&nbsp;George Grossberg","doi":"10.1016/j.bionps.2024.100083","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100083","url":null,"abstract":"","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"10 ","pages":"Article 100083"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000017/pdfft?md5=3cf44bb55ff2b20223fe6b874e9a7eb2&pid=1-s2.0-S2666144624000017-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141328521","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":"Prediction of psychotic disorder in individuals with clinical high-risk state by multimodal machine-learning: A preliminary study","authors":"Yoichiro Takayanagi ,&nbsp;Daiki Sasabayashi ,&nbsp;Tsutomu Takahashi ,&nbsp;Yuko Higuchi ,&nbsp;Shimako Nishiyama ,&nbsp;Takahiro Tateno ,&nbsp;Yuko Mizukami ,&nbsp;Yukiko Akasaki ,&nbsp;Atsushi Furuichi ,&nbsp;Haruko Kobayashi ,&nbsp;Mizuho Takayanagi ,&nbsp;Kyo Noguchi ,&nbsp;Noa Tsujii ,&nbsp;Michio Suzuki","doi":"10.1016/j.bionps.2024.100089","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100089","url":null,"abstract":"<div><p>Objective markers which can reliably predict psychosis transition among individuals with at-risk mental state (ARMS) are warranted. In this study, sixty-five ARMS subjects [of whom 17 (26.2%) later developed psychosis] were recruited, and we performed supervised linear support vector machine (SVM) with a variety of combinations of.modalities (clinical features, cognition, structural magnetic resonance imaging, eventrelated.potentials, and polyunsaturated fatty acids) to predict future psychosis onset. While single-modality SVMs showed a poor to fair accuracy, multi-modal SVMs revealed better predictions, up to 0.88 of the balanced accuracy, suggesting the advantage of multi-modal machine-learning methods for forecasting psychosis onset in ARMS.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"10 ","pages":"Article 100089"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000078/pdfft?md5=2493a84bb92816fb52e5be58d85cd229&pid=1-s2.0-S2666144624000078-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140320430","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":"Exploring the neural effects of adverse childhood experiences through the retina","authors":"Brittany A. Blose","doi":"10.1016/j.bionps.2024.100093","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100093","url":null,"abstract":"<div><p>Adverse childhood experiences (ACEs) are associated with developing systemic diseases and mental illnesses, affecting multiple body systems, including those that affect allostasis, such as the immune, endocrine, and nervous systems. Numerous different biomarkers reflect the biological manifestations of ACEs across these systems and point to possible mechanisms of pathology following early adversity. Retinal layer thickness values and retinal microvasculature parameters, which may reflect central nervous system structure and function, have scarcely been explored in relation to early life stress in humans but could potentially be valuable indicators of early life adversity sequelae. Animal models of early life stress using rodents demonstrate that early adversity is associated with structural and functional alterations of the retina. Thus, given the widespread impact of ACEs across several different allostatic systems in the body, including the central nervous system of which the retina is a part, and evidence in animal models suggesting a relationship between early life stress and retinal alterations, the retina is likely to be affected by ACEs in humans. Retinal biomarkers may also represent especially feasible methods for exploring the effects of early adversity on the body, as they can be examined in vivo using optical coherence tomography (OCT), OCT angiography (OCTA), and electroretinography (ERG), which are quick and noninvasive retinal imaging and electrophysiological techniques. Therefore, future research should focus on the impact of ACEs on the retina in humans and what retinal changes predict in terms of symptoms, course, and functional impairment associated with negative physical and mental health outcomes. This can further our understanding of the pathological mechanisms of diseases and disorders that individuals with ACEs are at risk of developing.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"10 ","pages":"Article 100093"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266614462400011X/pdfft?md5=5730d06ea55531c3e5783f8021e5ef57&pid=1-s2.0-S266614462400011X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140548501","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":"Electroretinographic dysfunction, insulin resistance, and childhood trauma in early-course psychosis: A case-control exploratory study","authors":"Erik Velez-Perez ,&nbsp;Nicolas Raymond ,&nbsp;Chelsea Kiely ,&nbsp;Willa Molho ,&nbsp;Rebekah Trotti ,&nbsp;Caroline Harris ,&nbsp;Deepthi Bannai ,&nbsp;Rachal Hegde ,&nbsp;Sarah Herold ,&nbsp;Matcheri Keshavan ,&nbsp;Steven Silverstein ,&nbsp;Paulo Lizano","doi":"10.1016/j.bionps.2024.100088","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100088","url":null,"abstract":"<div><h3>Background</h3><p>Electroretinographic dysfunction is observed in psychosis, with a-wave and b-wave amplitudes potentially serving as biomarkers. Insulin resistance (IR) and childhood trauma (CT) have also been associated with psychosis-spectrum disorders, particularly schizophrenia. Electroretinographic dysfunction in early-course psychosis (EP) lacks exploration. This case-control exploratory study aimed to understand electroretinographic dysfunction in EP and its relationship with IR and CT.</p></div><div><h3>Methods</h3><p>The study involved healthy controls (<em>n</em>=13) and EP individuals (<em>n</em>=14) and included photopic and scotopic flash-electroretinography (fERG), blood collection for IR assessment, and the Childhood Trauma Questionnaire (CTQ). Data were analyzed using SPSS v.29.0. Case-control differences across fERG conditions were explored using repeated-measures ANCOVA (3 flash conditions X 2 groups) adjusted for gender and age. Sub-analyses included Fisher’s, Mann-Whitney, partial correlations, and logistic and linear regressions.</p></div><div><h3>Results</h3><p>Compared to controls, EP participants showed (1) lower photopic a-wave and b-wave amplitudes, specifically in the left eye and under the P₁ condition, (2) greater odds for IR, and (3) higher CTQ scores. IR was associated with a higher CTQ score and a lower P_2b amplitude. A higher CTQ score was associated with lower P_2b amplitude in the left eye when adjusting for its interacting effect with IR.</p></div><div><h3>Conclusion</h3><p>These findings suggest lower photopic a-wave and b-wave amplitudes, IR, and CT are explanatory markers in EP. CT may dysregulate the hypothalamic-pituitary-adrenal axis, increasing the risk of experiencing later-life psychosis. IR might be a biomarker in psychosis, contributing to electroretinographic dysfunction and neurodegeneration of cone post-synaptic cells. Further investigations are needed.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"10 ","pages":"Article 100088"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000066/pdfft?md5=d5f15b7d1cae44d215c30cb7eef40f47&pid=1-s2.0-S2666144624000066-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160587","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":"Football-related concussions and head impacts are associated with changes in retinal structure and signaling","authors":"Steven M. Silverstein ,&nbsp;Jason Atlas ,&nbsp;Mia Young ,&nbsp;Lyvia Bertolace ,&nbsp;Iwona Juskiewicz ,&nbsp;Kian Merchant-Borna ,&nbsp;Sarah Dermady ,&nbsp;Yonatan Abrham ,&nbsp;Kyle Green ,&nbsp;Jeff Bazarian ,&nbsp;Rajeev S. Ramchandran ,&nbsp;Brian P. Keane","doi":"10.1016/j.bionps.2024.100091","DOIUrl":"https://doi.org/10.1016/j.bionps.2024.100091","url":null,"abstract":"<div><p>Subconcussive head hits (SHH) are common in contact sport athletes and are predictive of the later development of cognitive and brain changes, including chronic traumatic encephalopathy. In this pilot study we determined whether a history of concussion, and SHH acquired during a single season of college football, were associated with changes on retinal biomarkers of central nervous system (CNS) structure and function. College football players with a history of concussion (FB+C; n=9) or without a concussion history (FB-C; n=11), and non-contact sport collegiate athletes (Track/Swim; n=12) underwent visual and cognitive testing, retinal imaging (optical coherence tomography (OCT) and OCT angiography (OCTA)), and electroretinography (ERG) at three time points: pre-season, post-season and 4-month follow-up. The FB+C group demonstrated thicker maculae and exaggerated ERG waveforms (from all retinal neural cell types) compared to the other groups. These changes were generally observed at all timepoints, suggesting long-term changes associated with concussions, rather than effects of recent football activity. However, we also observed significant relationships between the number of head impacts during the season and stronger ERG responses, degree of macula thickening, enlargement of optic disc parameters, and increases in the density of retinal microvasculature relative to controls. These data suggest that retinal biomarkers are sensitive to both long- and short-term CNS changes related to participation in football, even in young athletes.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"10 ","pages":"Article 100091"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666144624000091/pdfft?md5=b75c50e6a5c23938220b1844ba9869e4&pid=1-s2.0-S2666144624000091-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140351148","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}