Biomarker-based subtyping of depression and anxiety disorders using Latent Class Analysis. A NESDA study

Beijers, Lian; Wardenaar, Klaas J.; Bosker, Fokko J.; Lamers, Femke; Grootheest, Gerard van; Boer, Marrit K. de; Penninx, Brenda W.J.H.; Schoevers, Robert A.

doi:10.1017/s0033291718001307

Cited by 30 publications

(30 citation statements)

References 77 publications

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“…Making generalized statements about depression is difficult when one considers the plethora of different depressive subtypes described in the literature which are characterized by distinct symptomatologies. It might be worthwhile to use biological differences as a springboard for defining depression subtypes based on biomarker profile analysis utilizing latent class analysis [445]. [47,53,93,446], the peripheral cytokine profile should not be considered a simple reflection of what is happening in the brain since peripheral cytokines are strongly influenced by several extra-central nervous system (CNS) variables.…”

Section: Heterogeneitymentioning

confidence: 99%

Peripheral Markers of Depression

Nobis

Zalewski

Waszkiewicz

2020

JCM

126

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Major Depressive Disorder (MDD) is a leading cause of disability worldwide, creating a high medical and socioeconomic burden. There is a growing interest in the biological underpinnings of depression, which are reflected by altered levels of biological markers. Among others, enhanced inflammation has been reported in MDD, as reflected by increased concentrations of inflammatory markers—C-reactive protein, interleukin-6, tumor necrosis factor-α and soluble interleukin-2 receptor. Oxidative and nitrosative stress also plays a role in the pathophysiology of MDD. Notably, increased levels of lipid peroxidation markers are characteristic of MDD. Dysregulation of the stress axis, along with increased cortisol levels, have also been reported in MDD. Alterations in growth factors, with a significant decrease in brain-derived neurotrophic factor and an increase in fibroblast growth factor-2 and insulin-like growth factor-1 concentrations have also been found in MDD. Finally, kynurenine metabolites, increased glutamate and decreased total cholesterol also hold promise as reliable biomarkers for MDD. Research in the field of MDD biomarkers is hindered by insufficient understanding of MDD etiopathogenesis, substantial heterogeneity of the disorder, common co-morbidities and low specificity of biomarkers. The construction of biomarker panels and their evaluation with use of new technologies may have the potential to overcome the above mentioned obstacles.

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Section: Heterogeneitymentioning

confidence: 99%

Peripheral Markers of Depression

Nobis

Zalewski

Waszkiewicz

2020

JCM

126

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“…This is however mostly informed by knowledge of reference values in patients suspected of, or known to have, these disorders (16)(17)(18). For psychiatric disorders such as major depressive disorder, biomarker research has mostly involved plasma rather than CSF analysis (8,19,20) and the few studies investigating CSF biochemistry have frequently produced inconsistent results (21,22).…”

Section: Introductionmentioning

confidence: 99%

The Anaesthetic Biobank of Cerebrospinal fluid: a unique repository for neuroscientific biomarker research

Tigchelaar¹,

Atmosoerodjo²,

Faassen³

et al. 2021

Ann Transl Med

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Background:The pathophysiology of numerous central nervous system disorders remains poorly understood. Biomarker research using cerebrospinal fluid (CSF) is a promising way to illuminate the neurobiology of neuropsychiatric disorders. CSF biomarker studies performed so far generally included patients with neurodegenerative diseases without an adequate control group. The Anaesthetic Biobank of Cerebrospinal fluid (ABC) was established to address this. The aims are to (I) provide healthy-control reference values for CSF-based biomarkers, and (II) to investigate associations between CSF-based candidate biomarkers and neuropsychiatric symptoms.Methods: In this cross-sectional study, we collect and store CSF and blood from adult patients undergoing spinal anaesthesia for elective surgery. Blood (20.5 mL) is collected during intravenous cannulation and CSF (10 mL) is aspirated prior to intrathecal local anaesthetic injection. A portion of the blood and CSF is sent for routine laboratory analyses, the remaining material is stored at −80 ℃. Relevant clinical, surgical and anaesthetic data are registered. A neurological examination and Montreal Cognitive Assessment (MoCA) are performed pre-operatively and a subset of patients fill in questionnaires on somatic and mental health (depression, anxiety and stress).Results: Four-hundred-fifty patients (58% male; median age: 56 years) have been enrolled in the ABC.The planned spinal anaesthetic procedure was not attempted for various reasons in eleven patients, in fourteen patients the spinal puncture failed and in twelve patients CSF aspiration was unsuccessful. A mean of 9.3 mL CSF was obtained in the remaining 413 of patients. Most patients had a minor medical history and 60% scored in the normal range on the MoCA (median score: 26). Conclusions:The ABC is an ongoing biobanking project that can contribute to CSF-based biomarker research. The large sample size with constant sampling methods and extensive patient phenotyping provide excellent conditions for future neuroscientific research.

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“…In our study, the routinely measured laboratory variables and vital signs were used to identify subphenotypes, making our results generalizable to other institutions. Subphenotypes of a disease are usually explored by using genomic information or biomarkers that were not routinely obtained in clinical practice [ 32 , 33 ]. Although these studies provide more in-depth insights into the underlying pathophysiology of each distinct subphenotype, their clinical utility is limited due to unavailability of these novel biomarkers or transcriptomics.…”

Section: Discussionmentioning

confidence: 99%

Latent transition analysis of cardiac arrest patients treated in the intensive care unit

et al. 2021

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Background and objective Post-cardiac arrest (CA) syndrome is heterogenous in their clinical presentations and outcomes. This study aimed to explore the transition and stability of subphenotypes (profiles) of CA treated in the intensive care unit (ICU). Patients and methods Clinical features of CA patients on day 1 and 3 after ICU admission were modeled by latent transition analysis (LTA) to explore the transition between subphenotypes over time. The association between different transition patterns and mortality outcome was explored using multivariable logistic regression. Results We identified 848 eligible patients from the database. The LPA identified three distinct subphenotypes: Profile 1 accounted for the largest proportion (73%) and was considered as the baseline subphenotype. Profile 2 (13%) was characterized by brain injury and profile 3 (14%) was characterized by multiple organ dysfunctions. The same three subphenotypes were identified on day 3. The LTA showed consistent subphenotypes. A majority of patients in profile 2 (72%) and 3 (82%) on day 1 switched to profile 1 on day 3. In the logistic regression model, patients in profile 1 on day 1 transitioned to profile 3 had worse survival outcome than those continue to remain in profile 1 (OR: 20.64; 95% CI: 6.01 to 70.94; p < 0.001) and transitioned to profile 2 (OR: 8.42; 95% CI: 2.22 to 31.97; p = 0.002) on day 3. Conclusion The study identified three subphenotypes of CA, which was consistent on day 1 and 3 after ICU admission. Patients who transitioned to profile 3 on day 3 had significantly worse survival outcome than those remained in profile 1 or 2.

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Biomarker-based subtyping of depression and anxiety disorders using Latent Class Analysis. A NESDA study

Cited by 30 publications

References 77 publications

Peripheral Markers of Depression

Peripheral Markers of Depression

The Anaesthetic Biobank of Cerebrospinal fluid: a unique repository for neuroscientific biomarker research

Latent transition analysis of cardiac arrest patients treated in the intensive care unit

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