Publications by authors named "Jason D Cooper"
Importance: Bipolar disorder (BD) is frequently misdiagnosed as major depressive disorder (MDD) because of overlapping symptoms and the lack of objective diagnostic tools.
Objective: To identify a reproducible metabolomic biomarker signature in patient dried blood spots (DBSs) that differentiates BD from MDD during depressive episodes and assess its added value when combined with self-reported patient information.
Design, Setting, And Participants: This diagnostic analysis used samples and data from the Delta study, conducted in the UK between April 27, 2018, and February 6, 2020.
Personality, symptom, and demographic correlates of perceived efficacy of selective serotonin reuptake inhibitor monotherapy among current users with low mood: A data-driven approach.
Jiri Benacek
,
Nayra A Martin-Key
,
Giles Barton-Owen
,
Tim Metcalfe
,
Thea S Schei
,
Jason D Cooper
J Affect Disord
December 2021
Article Synopsis
- SSRIs are commonly used to treat depression, but their effectiveness can differ among patients, prompting a study to identify factors that predict how well someone may respond to these medications.
- Using data from an online mental health questionnaire and advanced analysis techniques, researchers found that positive affectivity was the strongest predictor of SSRI response, while chronic pain, sleep problems, and unemployment negatively impacted treatment perception.
- The study highlighted the need for caution in interpreting results due to its exploratory nature, reliance on self-reported data, and the necessity for further research to confirm these findings.
Article Synopsis
- - The Delta Study aimed to enhance the diagnosis of mood disorders in people with low mood, seeking to estimate their prevalence and characteristics, and how these findings can influence clinical practices.
- - Participants were classified into three groups based on their mood disorder history, and comprehensive mental health data was gathered online using standardized assessments to establish accurate diagnoses.
- - Findings revealed significant under- and misdiagnosis rates, with notable percentages of Bipolar Disorder (BD) and Major Depressive Disorder (MDD) among participants; this highlights the necessity for better mental health screening in primary care to prevent worsening symptoms.
Article Synopsis
- Web-based mental health assessments can provide earlier and more cost-effective diagnoses for psychiatric conditions than traditional methods, particularly for those showing symptoms of depression.
- A study with over 2000 participants assessed the impact of a web-based assessment that offered personalized feedback and psychoeducation, leading to positive self-reported outcomes in mental well-being after 6 and 12 months.
- While a majority found the web assessment useful for understanding their mental health, a small percentage actually discussed their results with professionals, resulting in limited new diagnoses despite the assessment's predictive accuracy.
A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data.
Jakub Tomasik
,
Sung Yeon Sarah Han
,
Giles Barton-Owen
,
Dan-Mircea Mirea
,
Nayra A Martin-Key
,
Jason D Cooper
Transl Psychiatry
January 2021
Article Synopsis
- Mood disorders often suffer from under- and misdiagnosis, which leads to ineffective treatment and poor outcomes; this study aimed to create a diagnostic algorithm to differentiate bipolar disorder (BD) from major depressive disorder (MDD).
- Researchers recruited individuals aged 18-45 with depressive symptoms online, using a mental health questionnaire and blood samples for biomarker analysis, alongside established diagnostic interviews.
- The developed algorithm showed a high accuracy in distinguishing BD from MDD with an AUROC of 0.92, and further validation confirmed its effectiveness across different patient groups, potentially improving timely diagnosis and treatment for BD.
Diagnostic prediction model development using data from dried blood spot proteomics and a digital mental health assessment to identify major depressive disorder among individuals presenting with low mood.
Sung Yeon Sarah Han
,
Jakub Tomasik
,
Nitin Rustogi
,
Santiago G Lago
,
Giles Barton-Owen
,
Jason D Cooper
Brain Behav Immun
November 2020
Article Synopsis
- * This study aimed to create diagnostic models using data from blood samples and a digital mental health assessment to distinguish individuals with MDD from those with low mood.
- * The models showed strong predictive performance, identifying key blood proteins and mental health indicators, suggesting they could help with earlier and more accurate MDD diagnoses in clinical practice.
Article Synopsis
- - Mood disorders impact millions globally and current diagnostic methods often lead to delays in accurate diagnosis, highlighting the need for improved approaches that can facilitate early identification of these conditions.
- - The Delta Trial aims to create an algorithm that combines symptom data with proteomic biomarkers to enhance diagnostic accuracy, particularly to differentiate between bipolar disorder and major depressive disorder.
- - Over 3200 people participated in the Delta Trial, with hundreds providing necessary blood samples and completing follow-up questionnaires, which supports the trial's potential in developing more effective diagnostic methods.
Article Synopsis
- Individuals with subthreshold depression are at higher risk for developing major depressive disorder (MDD), prompting researchers to create a prediction model based on various data types.
- The model analyzed 198 characteristics from different groups, including first-episode MDD patients and subthreshold individuals, using advanced statistical techniques to ensure reliability.
- Results revealed a 12-feature model that could fairly predict MDD onset in subthreshold individuals up to four years in advance, highlighting its potential for early identification and treatment in clinical settings.
Article Synopsis
- Obsessive-compulsive disorder (OCD) is a childhood-onset neuropsychiatric disorder marked by intrusive thoughts (obsessions) and repetitive behaviors (compulsions), potentially linked to insulin signaling.
- In a study using TALLYHO/JngJ (TH) mice, researchers assessed compulsive behaviors, anxiety levels, brain structure, and specific neuro-metabolite and protein levels associated with OCD.
- The TH mice displayed increased compulsivity and anxiety, along with distinct differences in brain microstructure and neurochemical levels, suggesting that abnormal insulin signaling may contribute to compulsivity-like behaviors.
Multimodel inference for biomarker development: an application to schizophrenia.
Transl Psychiatry
February 2019
In the present study, to improve the predictive performance of a model and its reproducibility when applied to an independent data set, we investigated the use of multimodel inference to predict the probability of having a complex psychiatric disorder. We formed training and test sets using proteomic data (147 peptides from 77 proteins) from two-independent collections of first-onset drug-naive schizophrenia patients and controls. A set of prediction models was produced by applying lasso regression with repeated tenfold cross-validation to the training set.
View Article and Find Full Text PDFArticle Synopsis
- * Utilizing advanced techniques, researchers examined immune cell signaling in patients with four major disorders (autism, bipolar disorder, major depression, schizophrenia) and identified 25 significant alterations compared to healthy controls.
- * Findings suggest a continuum of neuropsychiatric conditions rather than distinct categories, revealing specific network changes in immune cell pathways that could lead to new treatment targets.
Article Synopsis
- The study aims to investigate how the immune response to dendritic cell-based immunotherapy interacts with combined antiretroviral therapy (cART) interruption in individuals infected with HIV-1, focusing on plasma protein levels.
- Researchers administered a dendritic cell vaccine to HIV-infected participants and measured various plasma analytes, including cytokines and hormones, before and after cART interruption, comparing results with healthy control groups.
- Findings indicate significant differences in plasma analyte levels between HIV-infected individuals and healthy controls, with certain analytes and neutrophil counts correlating with vaccine response and cART interruption, highlighting the complex immune changes associated with chronic HIV infection.
Schizophrenia-risk and urban birth are associated with proteomic changes in neonatal dried blood spots.
Transl Psychiatry
December 2017
Article Synopsis
- The study examined protein differences in blood between individuals with first-onset schizophrenia and healthy controls, and also looked at newborn blood samples to identify early markers associated with later schizophrenia development.
- Researchers used advanced mass spectrometry techniques to analyze proteins, finding significant alterations in levels of specific proteins like Haptoglobin and Antithrombin-III in both the schizophrenia patients and neonates who later developed the disorder.
- The research indicated environmental factors, such as urban living during pregnancy, influenced protein abundance at birth, and hopes to lead to better predictive models and prevention strategies for neurodevelopmental disorders.
Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls.
View Article and Find Full Text PDFThere is an increasing interest in the use of dried blood spot (DBS) sampling and multiple reaction monitoring in proteomics. Although several groups have explored the utility of DBS by focusing on protein detection, the reproducibility of the approach and whether it can be used for biomarker discovery in high throughput studies is yet to be determined. We assessed the reproducibility of multiplexed targeted protein measurements in DBS compared to serum.
View Article and Find Full Text PDFEvaluation of molecular brain changes associated with environmental stress in rodent models compared to human major depressive disorder: A proteomic systems approach.
David Alan Cox
,
Michael Gerd Gottschalk
,
Viktoria Stelzhammer
,
Hendrik Wesseling
,
Jason David Cooper
World J Biol Psychiatry
June 2019
Article Synopsis
- This study investigates the relevance of rodent models for major depressive disorder (MDD) by comparing proteomics data from human brain tissue to three common stress-induced animal models.
- Using protein interaction networks, researchers identified seven functional domains linked to MDD that are represented in multiple models.
- The social defeat model showed the closest alignment with human MDD pathology for four of these domains, highlighting a new approach for enhancing the translation of preclinical research to human conditions.
Blood-based immune-endocrine biomarkers of treatment response in depression.
J Psychiatr Res
December 2016
Article Synopsis
- Antidepressant treatment for major depressive disorder typically has low success rates, with over 50% of patients not responding well, leading to a trial-and-error approach to finding effective medication.
- A comprehensive study analyzed 258 serum markers in 332 patients to identify potential biomarkers for treatment response, revealing specific proteins linked to how well individuals respond to different antidepressants.
- Although some commonly cited markers were not confirmed, the study suggests that an individual's immune-endocrine profile could guide more personalized treatment strategies in the future.
Altered apolipoprotein C expression in association with cognition impairments and hippocampus volume in schizophrenia and bipolar disorder.
Eur Arch Psychiatry Clin Neurosci
April 2017
Article Synopsis
- Proteomic analyses were used to investigate plasma protein differences between schizophrenia (SZ), bipolar disorder (BD), and non-clinical controls, focusing on their relation to cognitive deficits and brain structures.
- The study quantified 42 plasma proteins in SZ patients, BD patients, and controls and found that apolipoprotein levels varied significantly between groups, linking these changes to cognitive impairments and hippocampal volume, although they did not correlate with clinical symptom severity.
- The findings highlight the importance of identifying molecular patterns associated with cognitive performance and brain morphology in SZ and BD, which may aid in understanding their underlying mechanisms and improving diagnosis and treatment.
Article Synopsis
- A new systems biology approach was created to compare brain tissue from both rodent models of schizophrenia and human patients to identify which model best reflects the human disease.
- Researchers used LC-MS proteomic profiling to analyze differences in protein abundance in brain tissues, finding significant changes that relate to five functional domains of schizophrenia across all rodent models studied.
- The study determined that the chronic PCP rodent model most closely matches human schizophrenia brain changes, potentially helping improve drug discovery and understanding of the disease's biology.
Article Synopsis
- * Researchers analyzed serum from 65 MDD patients and found significant differences in proteins related to immune response and apolipoproteins across different staging models for TRD.
- * The findings suggest that certain proteins could help identify high-risk patients, but the subtle molecular changes need careful interpretation before clinical application.
Article Synopsis
- Recent studies show that only a few serum biomarker tests are used in clinical settings, and concerns arise regarding their reproducibility.
- The research analyzed 171 serum proteins and small molecules in 1,676 participants to determine how sex and female hormonal status affect biomarker variation.
- Findings revealed that significant differences exist in biomarker levels based on sex and hormonal status, highlighting the importance of matching these factors in studies to reduce false discovery rates.
Article Synopsis
- * A study examined serum samples from 231 MDD patients and 365 controls, identifying 28 markers of MDD that are influenced by sex, particularly finding male-specific immune response proteins associated with depression.
- * The research suggests that male MDD might be more accurately identified through certain serum analytes, highlighting potential limitations in applying inflammatory theories of depression across genders and emphasizing the need for further studies to enhance understanding and diagnostic methods.
Article Synopsis
- Less than half of depression patients get accurate diagnoses in primary care, prompting the need for better diagnostic tools using biological markers.
- A study analyzed data from 1,007 patients to develop a serum biomarker panel, identifying 33 key immune-neuroendocrine markers for distinguishing depression.
- The new biomarker panel showed moderate to good accuracy in differentiating between depressed patients and controls, suggesting it could improve diagnosis in healthcare settings with further validation.
Commercialisation of Biomarker Tests for Mental Illnesses: Advances and Obstacles.
Trends Biotechnol
December 2015
Article Synopsis
- Significant progress has been made in biomarker research for mental illnesses, but no FDA-approved blood tests have been integrated into clinical practice yet.
- Key challenges to commercializing these findings include inadequate research funding and issues with reproducibility, which undermine scientific credibility.
- Efforts are underway to address problems like research fraud and statistical errors, which raises optimism for the future development of reliable biomarker tests.
Article Synopsis
- Bipolar disorder (BD) is often misdiagnosed, leading to ineffective treatments, which prompted the investigation of a biomarker panel for accurate diagnosis.
- A meta-analysis of eight studies identified a panel with 20 protein biomarkers that showed strong predictive capabilities in distinguishing BD from other mental health disorders.
- The findings suggest that using this biomarker panel can significantly improve early and accurate diagnosis, potentially delaying or preventing the onset of bipolar disorder.