Biomarkers in Neuropsychiatry最新文献

{"title":"Genetic predictors of attempted suicide among South Indian adolescents and young adults: A case-control study","authors":"Anju Mathew ,&nbsp;Ann Mary Alex ,&nbsp;Chathathayil Mohammedali Shafeeque ,&nbsp;Saboora Beegum Muthubeevi ,&nbsp;Vijayakumar Krishnapillai ,&nbsp;Moinak Banerjee","doi":"10.1016/j.bionps.2025.100126","DOIUrl":"10.1016/j.bionps.2025.100126","url":null,"abstract":"<div><h3>Background</h3><div>Suicide among adolescents and young adults is an alarming public health issue globally. Though studies suggest the link between genetic factors and suicidal behavior, there is a paucity of studies of specific genetic variants in adolescents and young adults. Hence this study explored the genetic predictors for attempted suicide among adolescents and young adults, by studying the genetic basis of serotonin and dopamine synthesis, transport, and degradation machinery.</div></div><div><h3>Methods</h3><div>A Case-control association study was conducted comprising individuals with attempted suicide (cases n = 80), 13–29 years of age, belonging to Malayalam speaking Dravidian population, and attending a tertiary care center in South India. Age, sex, and ethnicity matched controls (n = 267) with no history of attempted suicide were also considered from the same ethnic population. Genotyping was performed for functionally critical SNP in serotonin receptor, Tryptophan hydroxylase, Tyrosine hydroxylase, and Catechol-o-methyl transferase. Statistical significance for allelic and genotypic comparisons and their odds ratios were computed.</div></div><div><h3>Results</h3><div>The Tyrosine Hydroxylase THrs2070762 and Tryptophan Hydroxylase TPH1rs211105 genetic variants showed a statistically significant association with attempted suicide phenotype.</div></div><div><h3>Conclusion</h3><div>The study suggests that the genetic variants in Tyrosine Hydroxylase and Tryptophan Hydroxylase are predictive of attempted suicide among adolescents and young adults. Understanding the genetic variations will help in identifying and managing high-risk individuals.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738876","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":"A systematic review of in vivo brain insulin resistance biomarkers in humans","authors":"Graham Reid ,&nbsp;Brendan Sargent ,&nbsp;Sarah Bauermeister ,&nbsp;Amanda Adler ,&nbsp;Ivan Koychev","doi":"10.1016/j.bionps.2025.100125","DOIUrl":"10.1016/j.bionps.2025.100125","url":null,"abstract":"<div><div>Type 2 diabetes mellitus (T2DM) is associated with an elevated risk of dementia, prompting interest into the concept of brain-specific insulin resistance. However, the brain's reliance on insulin-independent glucose transporters complicates attempts to measure in vivo brain insulin resistance using the definition of system-wide insulin resistance, which is based on glucose-insulin interactions. In this review, we explore three available biomarkers for evaluating in vivo brain-specific insulin resistance in humans: (1) correlating systemic insulin resistance with brain function, (2) examining functional brain changes after the administration of intranasal insulin, and (3) quantifying insulin signalling proteins in neuronally enriched blood-derived extracellular vesicles. Integrating evidence from these three approaches tentatively suggests for the first time that a comprehensive assessment of the brain's default mode network (DMN), combining these methodologies within a single study, may offer a useful biomarker to quantify in vivo brain-specific insulin resistance in humans. Correlating DMN responses to concentrations of pY-IRS-1 in blood-derived extracellular vesicles would corroborate evidence for a brain-specific biomarker and provide a scalable approach to detecting brain-specific insulin resistance in humans. This advancement would enable in vivo evaluations of insulin resistance in the central nervous system, akin to the precise measurements of systemic insulin resistance seen in T2DM. An established and clearly defined biomarker of in vivo brain insulin resistance in humans would permit further investigation into the links between diabetes and dementia, ultimately bolstering support for secondary dementia prevention by identifying those at higher risk for cognitive decline.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100125"},"PeriodicalIF":0.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593276","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":"Whole-body hyperthermia as a novel antidepressant therapy","authors":"Kevin D. Gaitonde ,&nbsp;Henry A. Nasrallah","doi":"10.1016/j.bionps.2025.100124","DOIUrl":"10.1016/j.bionps.2025.100124","url":null,"abstract":"<div><div>First-line treatments for major depressive disorder include medication and cognitive behavioral therapy. While effective, pharmacotherapy often takes time to start demonstrating efficacy in symptomatic improvement and may be accompanied by adverse effects, indicating an ongoing need for new therapeutic approaches. A recently emerging somatic antidepressant intervention is whole-body hyperthermia, in which subjects are temporarily exposed to heat and then allowed to cool down. Recent studies employing hyperthermia-based strategies appear to show mood improvements both immediately and several weeks after the conclusion of treatment. However, published studies are often limited by their sample sizes and by their selection criteria. In this article, we review the literature on this novel approach and propose ideas regarding the possible physiological basis of this novel intervention and how it may be used in the future as adjunctive therapy with the current standard of care.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577361","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":"Inducible HSP72 protein as a marker of neuronal vulnerability in brain research: A potential biomarker for clinical psychiatry?","authors":"Ana-Maria Iorgu ,&nbsp;Dragos Inta ,&nbsp;Peter Gass","doi":"10.1016/j.bionps.2025.100123","DOIUrl":"10.1016/j.bionps.2025.100123","url":null,"abstract":"<div><div>The aim of this review is to analyze the potential of the inducible form of 70-kDa heat shock protein (i.e. HSP72) as a biomarker for neuropsychiatric diseases, focusing on both animal and clinical studies. We first discuss findings from animal studies where HSP72 has already revealed its reliability as a sensitive marker of neuronal vulnerability, especially research investigating NMDAR antagonists-induced neurotoxicity, cerebral ischemia, epilepsy, behavioral stress, and effects of psychoactive and/or addictive substances. Next, we summarized human studies providing evidence for the involvement of HSP72 in the pathology of neuropsychiatric disorders like major depression, bipolar disorder, schizophrenia, attention deficit hyperactivity disorder, autism spectrum disorder, and neurodegenerative disorders. Finally, we discuss potential future research approaches needed to further investigate and possibly validate HSP72 as a biomarker in clinical psychiatry.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428838","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":"Is low-grade inflammation related to cognitive performance during a sustained attention task in depression? – A case-control study","authors":"Bruno Pedraz-Petrozzi ,&nbsp;Eva Kathrin Lamadé ,&nbsp;Nils Mischa Hübner ,&nbsp;Jil Zippelius ,&nbsp;Elena Neumann ,&nbsp;Gebhard Sammer","doi":"10.1016/j.bionps.2025.100121","DOIUrl":"10.1016/j.bionps.2025.100121","url":null,"abstract":"<div><div>This study aimed to investigate the associations between inflammatory cytokines and cognitive performance in individuals with depression compared to healthy controls, while accounting for variables, such as perceived fatigue, BMI, and age. Individuals diagnosed with depression (n = 23) and healthy controls (n = 31) were included in the study. A 15-minute sustained attention task (subtest of the Test Battery for Attention, version 2.3.1) was administered with concurrent electroencephalographic recordings to evaluate P300 amplitude and latency. Peripheral inflammation was assessed by measuring IL-6, IL-1β, and TNF-α levels. Perceived fatigue was assessed using the German version of the Fatigue Impact Scale. Generalized linear models (GLM) were used to evaluate the main aims of the study. Results indicated that depression was associated with reduced P300 amplitudes (p = 0.011), and age was significantly associated with P300 amplitude, with older participants showing reductions (p = 0.016). However, no significant effects of inflammatory markers on P300 components were found. While no group differences were observed in the total number of hits, both perceived fatigue (p = 0.033) and TNF-α (p = 0.007) were significantly associated with hit accuracy. A post-hoc mediation analysis explored that perceived fatigue mediates the relationship between depression and number of hits. These findings suggest that low-grade inflammation may not directly influence P300 components, though inflammation and fatigue appear linked to accuracy deficits. Finally, the impact of depression on the number of hits is primarily mediated by perceived fatigue, suggesting that fatigue is a crucial factor in how depression affects cognition.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100121"},"PeriodicalIF":0.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387470","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":"Advancing transdiagnostic data analytics using knowledge graphs","authors":"Fiona Klaassen ,&nbsp;Emanuel Schwarz","doi":"10.1016/j.bionps.2025.100122","DOIUrl":"10.1016/j.bionps.2025.100122","url":null,"abstract":"<div><div>Artificial intelligence approaches have tremendous potential to advance our understanding of biological and other processes contributing to mental illness risk. An important question is how such approaches can be tailored to support transdiagnostic investigations that are considered central for gaining deeper insight into etiological processes and psychopathology that may not align well with categorical illness delineations. Here, we present the so-called “knowledge graphs” that could be leveraged in analytic approaches to synthesize multimodal data of transdiagnostic relevance, identify important latent structures and biomarkers, and support the evaluation of existing transdiagnostic frameworks.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100122"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143288352","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 in alcohol use disorder - The promise and pitfalls of neuroimaging drug cue reactivity","authors":"Marlen Pfisterer ,&nbsp;Sina Zimmermann ,&nbsp;Judith Zaiser ,&nbsp;Sarah Gerhardt ,&nbsp;Sabine Vollstädt-Klein ,&nbsp;Falk Kiefer ,&nbsp;Patrick Bach","doi":"10.1016/j.bionps.2025.100119","DOIUrl":"10.1016/j.bionps.2025.100119","url":null,"abstract":"","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100119"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181182","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":"Developing non-invasive molecular markers for early risk assessment of Alzheimer's disease","authors":"Tapas K. Sur ,&nbsp;Tanmoy Mondal ,&nbsp;Zarish Noreen ,&nbsp;Jheannelle Johnson ,&nbsp;Gail Nunlee-Bland ,&nbsp;Christopher A. Loffredo ,&nbsp;Brent E. Korba ,&nbsp;Vijay Chandra ,&nbsp;Siddhartha S. Jana ,&nbsp;Bernard Kwabi-Addo ,&nbsp;Sumit Sarkar ,&nbsp;Somiranjan Ghosh","doi":"10.1016/j.bionps.2025.100120","DOIUrl":"10.1016/j.bionps.2025.100120","url":null,"abstract":"<div><div>Alzheimer's disease (AD) is a heterogeneous neurodegenerative disease, with no standard biomarker(s) to detect or confirm its risk at an early stage. The prevalence of AD increases exponentially worldwide in people of ages over 65 and older. Current improvements have unveiled the disease's pathophysiology and clinical diagnostic tests, targeting the neurological changes (neurodegeneration, amyloid precursor protein metabolism and tangle pathology) with precise PET/MRI imaging and xMAP/SIMOA (Multiplex simultaneous detection/single molecule array) to identify and quantify β-amyloids (Aβ40, Aβ42), total tau (T-tau) and phosphorylated tau (P-tau) proteins in the brain and cerebrospinal fluid (CSF) of patients. However, their utility for diagnosis in routine clinical practice is still challenging because of cost, accessibility, standardization, procedural limitation, and regulatory approval. Further research is needed to establish affordable, patient-friendly, easy, quick, and robust biomarkers for early AD detection, progression, and therapeutic management. Research on blood-based preclinical diagnosis and clinical practice for AD has advanced significantly in the last decade. Emerging literature supports the importance of new molecular biomarkers and signature genes from blood to detect and predict AD in advance. This review examines the potential applications of these blood-based target biomarkers for early disease detection, co-morbid condition risk prediction, and treatment management of AD.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100120"},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143352413","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":"Cognitive performance and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT) - 2","authors":"Brett A. Clementz ,&nbsp;Ishanu Chattopadhyay ,&nbsp;S. Kristian Hill ,&nbsp;Jennifer E. McDowell ,&nbsp;Sarah K. Keedy ,&nbsp;David A. Parker ,&nbsp;Rebekah L. Trotti ,&nbsp;Elena I. Ivleva ,&nbsp;Matcheri S. Keshavan ,&nbsp;Elliot S. Gershon ,&nbsp;Godfrey D. Pearlson ,&nbsp;Carol A. Tamminga ,&nbsp;Robert D. Gibbons","doi":"10.1016/j.bionps.2024.100117","DOIUrl":"10.1016/j.bionps.2024.100117","url":null,"abstract":"<div><h3>Objective</h3><div>The B-SNIP consortium validated neurobiologically defined psychosis Biotypes (BT1, BT2, BT3) using cognitive and psychophysiological measures. B-SNIP’s biomarker panel is not practical for most settings. Previously, B-SNIP developed an efficient classifier of Biotypes using only clinical assessments (called ADEPT-CLIN) with acceptable accuracy (∼.81). Adding cognitive performance may improve ADEPT’s performance.</div></div><div><h3>Method</h3><div>Clinical assessments from ADEPT-CLIN plus 18 cognitive measures from 1907 individuals with a B-SNIP psychosis Biotype were used to create an additional diagnostic algorithm called ADEPT-COG. Extremely randomized trees were used to create this low burden classifier.</div></div><div><h3>Results</h3><div>Total Biotype classification accuracy peaked at 94.6 % with 65 items. A reduced set of 18 items showed 90.5 % accuracy. Only 9–10 items achieved a one-vs-all (e.g., BT1 or not) accuracy of ∼.95, considerably better than using clinical assessments alone. The top discriminators of psychosis Biotypes were antisaccade proportion correct, BACS total, symbol coding, antisaccade correct response latency, verbal memory, digit sequencing, stop signal reaction times, stop signal proportion correct, Tower of London, and WRAT Reading. Except for antisaccade proportion correct and Tower of London, there was no overlap of the top discriminating items for B-SNIP Biotypes and DSM psychosis categories.</div></div><div><h3>Conclusions</h3><div>This low-burden algorithm using clinical and cognitive measures achieved high classification accuracy and can support Biotype-specific etiological and treatment investigations in clinical and research environments. It may be especially useful for clinical trials.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100117"},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181181","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":"A systematic review of neurobiological aspects of borderline personality disorder among adolescent patients","authors":"Liliana Cruz-Ausejo ,&nbsp;Alex Rojas-Ortega ,&nbsp;Glauco Valdivieso-Jiménez ,&nbsp;Anthony Copez-Lonzoy ,&nbsp;Andrea Matayoshi ,&nbsp;Josmel Pacheco-Mendoza ,&nbsp;Vicente A. Benites-Zapata","doi":"10.1016/j.bionps.2024.100114","DOIUrl":"10.1016/j.bionps.2024.100114","url":null,"abstract":"<div><h3>Background</h3><div>Borderline personality Disorder is a complex mental health condition with disturbances in emotions, self-perception, and relationships. Emerging in adolescence, it reaches its peak in early adulthood, impacting 1 %-3 % of individuals.</div></div><div><h3>Methods</h3><div>We documented this review in PROSPERO with the registration code CRD4202126220. Subsequently, we conducted a comprehensive search across Pubmed, PsycINFO, Medline, Embase, Web of Science and Scopus databases. A systematic synthesis focusing on the neurobiological foundations of borderline personality disorder is presented.</div></div><div><h3>Results</h3><div>A total of 22 studies and 1400 participants were included. Most of the studies 10/22 and 4/22 were from Australia and Germany, respectively. Genetic findings linked the short allele of 5-HTTLPR to the elevated borderline personality disorder traits and revealed neuroendocrine alterations. While imaging studies documented structural brain changes in areas such as the dorsolateral frontal gyrus and hippocampus, and reduced volumes in the anterior cingulate cortex and corpus callosum. Electrophysiological studies indicated abnormal cerebral maturation with diminished P300 amplitudes and increased alpha phase synchrony in borderline personality disorder adolescents, particularly during emotional tests.</div></div><div><h3>Conclusion</h3><div>We concluded that while borderline personality disorder symptoms may endure from adolescence into adulthood, existing evidence lacks consistency in neurobiological findings. Differences in the prefrontal cortex, orbitofrontal cortex, amygdala and hippocampus showed potential significance, however, electrophysiological, biochemical and genetic presented insufficient generalizable evidence for adolescents. Longitudinal studies and further investigation are needed.</div></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":"12 ","pages":"Article 100114"},"PeriodicalIF":0.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181180","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}