Biomarkers in Neuropsychiatry最新文献

{"title":"Diagnostic biomarkers in Alzheimer’s disease","authors":"Emerlee Andersen ,&nbsp;Bryce Casteigne ,&nbsp;William Daniel Chapman ,&nbsp;Andrew Creed ,&nbsp;Forrest Foster ,&nbsp;Allison Lapins ,&nbsp;Rhonna Shatz ,&nbsp;Russell P. Sawyer","doi":"10.1016/j.bionps.2021.100041","DOIUrl":"10.1016/j.bionps.2021.100041","url":null,"abstract":"<div><p>In this review article we examine the various types of diagnostic biomarkers which are used in the early detection of Alzheimer’s disease. This review summerizes the A/T/N classification system for Alzheimer’s biomarkers and its use in the biomarker-based diagnosis of Alzheimer’s disease. Furthermore we review the use of structural MRI, 18F-FDG PET, Amyloid PET, Tau PET, cerebrospinal fluid biomarkers, and the emerging role of plasma biomarkers in the diagnosis of Alzheimer’s disease. In doing so we discuss each biomarkers correlation with pathologic findings, ability to distinguish Alzheimer’s disease from healthy aging, ability to distinguish Alzheimer’s disease from other neurodegenerative diseases, role in A/T/N classification system, and limitations of each biomarker.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2021.100041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"100058129","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 translational research through the interface of digital phenotyping and neuroimaging: A narrative review","authors":"Erica Camacho ,&nbsp;Roscoe O. Brady Jr ,&nbsp;Paulo Lizano ,&nbsp;Matcheri Keshavan ,&nbsp;John Torous","doi":"10.1016/j.bionps.2021.100032","DOIUrl":"10.1016/j.bionps.2021.100032","url":null,"abstract":"<div><p>Instead of matching neuroimaging to static clinical targets, it is currently possible to use dynamic biobehavioral markers of cognition, functioning, behavior, and symptoms captured through a person’s smartphone. This paper reviews the published literature linking neuroimaging and smartphone data to understand the feasibility, methods, and potential of using smartphone sensing (often called digital phenotyping) as a target for neuroimaging. On June 30, 2020, a literature search was conducted on PubMed and PsycINFO for studies utilizing neuroimaging and smartphones tools. We excluded EEG focused studies, conference proceedings and abstracts. A snowball approach was applied to further locate papers. We utilized the NIMH’s Research Domain Criteria (RDoC) framework to organize results. 262 publications uncovered by the search were screened, and 14 papers were included in the final analysis. All studies differed in terms of the type of data collected from smartphones, type of neuroimaging used, areas of the brain measured, and population studied. The average duration before or after neuroimaging and smartphone assessments was 39 days. While it was not possible to directly compare studies, a majority of the included reports were classified under the Negative Valence Systems category in the RDoC framework. All studies reported statistically significant relationships between the information collected via the digital tool and the brain scans, and support feasibility of this method. The current literature connecting smartphone data and neuroimaging is nascent but holds the potential to better understand the ability of digital tools to inform brain structure and/or function. Although the protocols and studies from this search were heterogenous, results suggest feasibility and practicality of this work.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2021.100032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"106330396","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":"Backtracing persistent biomarker shifts to the age of onset: A novel procedure applied to men’s and women’s white blood cell counts in post-traumatic stress disorder","authors":"Vladeta Ajdacic-Gross ,&nbsp;Lena Ajdacic ,&nbsp;Yanhua Xu ,&nbsp;Mario Müller ,&nbsp;Stephanie Rodgers ,&nbsp;Christine Wyss ,&nbsp;Sebastian Olbrich ,&nbsp;Anna Buadze ,&nbsp;Erich Seifritz ,&nbsp;En-Young N. Wagner ,&nbsp;Dragana Radovanovic ,&nbsp;Viktor von Wyl ,&nbsp;Nina Steinemann ,&nbsp;Markus A. Landolt ,&nbsp;Enrique Castelao ,&nbsp;Marie-Pierre F. Strippoli ,&nbsp;Mehdi M. Gholamrezaee ,&nbsp;Jennifer Glaus ,&nbsp;Caroline Vandeleur ,&nbsp;Martin Preisig ,&nbsp;Roland von Känel","doi":"10.1016/j.bionps.2021.100030","DOIUrl":"10.1016/j.bionps.2021.100030","url":null,"abstract":"<div><h3>Background</h3><p>Traumatic experiences tend to be preserved in altered biomarker profiles. These profiles can be traced back from cross-sectional data regarding the age of exposure. Consequently, the change across developmental stages, e.g. from childhood to adulthood, can also be reconstructed. This study introduces a backtrace procedure that is illustrated using white blood cell (WBC) counts in full / partial post-traumatic stress disorder (PTSD). The procedure was applied separately on men's and women's data to provide a replication of the analysis based on different subsamples.</p></div><div><h3>Methods</h3><p>The analysis was carried out with data from the CoLaus|PsyCoLaus study (N = 5111, 2370 men and 2741 women, age range 35–88 years). It was restricted to traumatic experiences that occurred until the age of 35, i.e., the lower age limit of the sample. The WBC counts from up to two assessments were standardized, pooled and assigned to the reported age of trauma exposure. This resulted in age series for each marker, whereas the reference values were based on subjects who did not experience any trauma exposure. The backtrace procedure ascertained the peaks and troughs of the age series and determined the best-fitting critical age range surrounding each peak or trough based on the best p-value from simple t-tests.</p></div><div><h3>Results</h3><p>In CoLaus|PsyCoLaus, 750 participants reported trauma exposure until the age of 35, and 86 (out of 329) men and 187 (out of 421) women thereof were coded with a full or partial PTSD. Full / partial PTSD after trauma exposure in childhood was characterized by increased WBC counts (lymphocytes, eosinophils – in women also neutrophils). This pattern was partly retained during adolescence, in men due to eosinophils counts and in women due to lymphocyte counts. For exposure in young adulthood, the deviations were in the negative direction – in men with decreased basophils, in women with decreased lymphocytes and monocytes.</p></div><div><h3>Conclusions</h3><p>Summarizing, the backtrace approach revealed WBC profiles in PTSD that were specific to particular developmental age stages. The strongest persistent upregulation of the immune system related to trauma exposure was traceable to childhood / early adolescence both in men and in women. Further research will show which biomarkers are similarly suitable for backtracing as WBC counts. As in PTSD, the backtrace approach could also be applied to identifying persistent biomarker profiles in other mental disorders, as well as autoimmune and other chronic diseases.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2021.100030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42138733","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 a paired-stimuli configuration necessary to obtain typical evoked response differences in studies of psychosis? An MEG study","authors":"William Oliver ,&nbsp;David Parker ,&nbsp;William Hetrick ,&nbsp;Brett A. Clementz","doi":"10.1016/j.bionps.2021.100033","DOIUrl":"10.1016/j.bionps.2021.100033","url":null,"abstract":"<div><p>Paired-stimuli (S1-S2) procedures have long been used to assess auditory processing in psychosis. Such studies have shown aberrant evoked responses (ERPs) following long (S1 response) and/or short (S2 response) inter-stimulus intervals. The historical tendency from paired stimuli outcomes in the schizophrenia (SZ) literature is for (i) response to the first stimulus (S1) to be smaller among SZ, and (ii) response to the second stimulus (S2) to be larger among SZ in relation to the size of their S1. An interpretation of these two findings is that SZ have poor auditory response suppression to redundant stimuli (“poor gating”). The present study sought to determine if the reported S1 and S2 effects in SZ (smaller S1 and larger S2 in relation to S1 magnitude) require the paired-stimuli presentation format. Participants (18 schizophrenia and 17 healthy persons) were administered the equivalent of S1 (after a 4.5-sec ISI – “long ISI”) and S2 (after a 500-ms ISI – “short ISI”) stimuli under four conditions (traditional paired long and short, randomly interleaved long and short, block of long, block of short). Neural activity differences were consistent between-groups independent of condition: (i) schizophrenia cases had greater activity in the pre-stimulus to very early post-stimulus period, (ii) healthy persons had greater M100 activity to long ISI stimuli, and (iii) healthy persons had greater activity after the M50/M100 evoked fields (recovery phase) following short ISI stimuli. Simple early auditory processing in psychosis may be largely independent of stimulus presentation condition, an outcome that may help re-frame future translational studies. Traditional paired-stimuli auditory neural response effects may not require the paired-stimuli format.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2021.100033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40705822","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 and neurobehavioral diagnosis","authors":"Joshua B. Ewen ,&nbsp;William Z. Potter ,&nbsp;John A. Sweeney","doi":"10.1016/j.bionps.2020.100029","DOIUrl":"10.1016/j.bionps.2020.100029","url":null,"abstract":"<div><p>Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2020.100029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39344103","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":"How not to think about biomarkers in psychiatry: Challenges and conceptual pitfalls","authors":"Awais Aftab ,&nbsp;Manu Sharma","doi":"10.1016/j.bionps.2021.100031","DOIUrl":"https://doi.org/10.1016/j.bionps.2021.100031","url":null,"abstract":"","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2021.100031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91686551","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":"Treatment response biomarkers in anxiety disorders: From neuroimaging to neuronally-derived extracellular vesicles and beyond","authors":"Jeffrey R. Strawn ,&nbsp;Amir Levine","doi":"10.1016/j.bionps.2020.100024","DOIUrl":"10.1016/j.bionps.2020.100024","url":null,"abstract":"<div><p>Multiple and diverse psychotherapeutic or psychopharmacologic treatments effectively reduce symptoms for many patients with anxiety disorders, but the trajectory and magnitude of response vary considerably. This heterogeneity of treatment response has invigorated the search for biomarkers of treatment response in anxiety disorders, across the lifespan. In this review, we summarize evidence for biomarkers of treatment response in children, adolescents and adults with generalized, separation and social anxiety disorders as well as panic disorder. We then discuss the relationship between these biomarkers of treatment response and the pathophysiology of anxiety disorders. Finally, we provide context for treatment response biomarkers of the future, including neuronally-derived extracellular vesicles in anxiety disorders and discuss challenges that must be overcome prior to the debut of treatment response biomarkers in the clinic. A number of promising treatment response biomarkers have been identified, although there is an urgent need to replicate findings and to identify which biomarkers might guide clinicians in selecting from available treatments rather than just simply identifying patients who may be less likely to respond to a given intervention.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2020.100024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38417472","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":"High delta and gamma EEG power in resting state characterise dementia in Parkinson’s patients","authors":"Anita Pal ,&nbsp;Nishi Pegwal ,&nbsp;Madhuri Behari ,&nbsp;Ratna Sharma","doi":"10.1016/j.bionps.2020.100027","DOIUrl":"10.1016/j.bionps.2020.100027","url":null,"abstract":"<div><h3>Background</h3><p>Parkinson’s disease (PD) is a chronic neurodegenerative disease with appearance of dementia as the disease progresses. Dementia in PD worsens the quality of life and poses a burden on caregivers. Objective markers of the presence and as well as onset of dementia needs to be explored to improve the quality of life.</p><p>We attempted to identify EEG abnormalities that differentiate PD patients with or without dementia using high density EEG. The differential changes in the EEG spectral activity could mark the early stage as well as onset of dementia in Parkinson’s disease (PD).</p></div><div><h3>Methods</h3><p>The present study was designed to find out the resting eyes-closed (EC) EEG characteristics in PD with dementia (PDD) and without dementia (PDND) compared to healthy controls (CON) of both gender using high density EEG. Absolute power of seven frequency bands based on individual alpha frequency was estimated by Fast Fourier transform algorithm in 58 PD patients (30 PDND and 28 PDD) and 26 CON.</p></div><div><h3>Results</h3><p>Compared to CON, PDND had higher power in theta and lower alpha1 bands while PDD had higher power in delta, theta, lower alpha1 and beta bands. Higher delta and gamma power with no difference in theta and lower alpha 1 power was the characteristic feature of PD patients with dementia compared to non-dementia.</p></div><div><h3>Conclusions</h3><p>This cross-sectional study proposes to use these differential changes in power as EEG signatures of appearance of dementia in PD. Absence of high delta power, but presence of high theta and lower alpha 1 power defined PDND group compared to CON.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2020.100027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"97258816","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":"Neurocognitive and neurophysiological endophenotypes in schizophrenia: An overview","authors":"Francesco Luciano Donati ,&nbsp;Armando D’Agostino ,&nbsp;Fabio Ferrarelli","doi":"10.1016/j.bionps.2020.100017","DOIUrl":"10.1016/j.bionps.2020.100017","url":null,"abstract":"<div><p>Schizophrenia (SCZ) is a severe psychotic disorder that affects up to 1% of the US population and it is associated with progressive impairment in social functioning and cognition. Nonetheless, despite its high burden, the pathophysiology of SCZ, including the genetic and biological mechanisms underlying the development and manifestation of the disorder, remains largely elusive. Endophenotypes are subtypes of biological markers that are more closely related to the genetic vulnerability for a disorder (e.g., SCZ). Recently, research on endophenotypes has identified several parameters that may prove useful in shedding light over the underlying neurobiology of SCZ. In this article, we provide an overview of the most established SCZ endophenotypes in the domains of neurocognition (attention deficits, working and verbal declarative memory dysfunctions) and neurophysiology (pre-pulse inhibition, anti-saccade impairment, event-related potential deficits) along with some novel, sleep-based measures (reduced sleep spindles and sleep slow waves). We also discuss recent conceptual advances in the field that may lead to novel, personalized treatment interventions for patients affected by this devastating mental illness.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2020.100017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9610682","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":"Change point analyses in prodromal Alzheimer’s disease","authors":"Alvin H. Bachman ,&nbsp;Babak A. Ardekani ,&nbsp;for the Alzheimer’s Disease Neuroimaging Initiative","doi":"10.1016/j.bionps.2020.100028","DOIUrl":"10.1016/j.bionps.2020.100028","url":null,"abstract":"<div><p>Change point analysis can reveal when a biomarker starts to diverge from the pattern of normal aging. This paper analyzes several biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to estimate the sequence and timing of their change points relative to a subsequent clinical diagnosis of mild cognitive impairment (MCI) in subjects initially considered cognitively normal (CN). Data on 379 stable CN (sCN) and 98 progressive CN (pCN) subjects who progressed to an MCI diagnosis were used. Linear mixed-effects change point models were used to estimate when various biomarkers in pCN started to diverge from rates expected in normal aging. Our results indicate that in pCN, hippocampal atrophy rate diverges from normal aging 12.4 (±2.8) years before MCI diagnosis, followed by ventricular volume expansion and decrease in Rey Auditory Verbal Learning Test of immediate recall scores about 5 years later. Glucose metabolism decrease begins about 5 (±1.3) years before diagnosis, followed by deterioration in other cognitive test scores. Planned AD interventions should note that irreversible changes such as atrophy may occur a decade before possible diagnosis of MCI.</p></div>","PeriodicalId":52767,"journal":{"name":"Biomarkers in Neuropsychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bionps.2020.100028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"111421530","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}