Brenda W. J. H. Penninx’s research while affiliated with Gezond Amsterdam and other places

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Publications (355)


Biological pathways underlying the relationship between childhood maltreatment and Multimorbidity: A Two-Step, multivariable Mendelian randomisation study
  • Article

February 2025

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8 Reads

Brain Behavior and Immunity

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Ville Karhunen

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Janine F. Felix

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[...]

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Yuri Milaneschi


Participant retention flowchart
Probabilities of endorsing depressive symptoms derived from baseline 4-class latent class analysis (N = 619)
Transition probabilities and class sizes for three-step LTA model (N = 432)
Probabilities <10% are not shown.
Model fit and class prevalence for baseline LCA models with varying numbers of classes and residual associations (N = 619)
Adjusted multinomial logistic regression models of class membership at baseline in relation to participant characteristics (N = 432)
Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis
  • Article
  • Full-text available

January 2025

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38 Reads

Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR). A secondary analysis of a two-year cohort study called Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD), which collected data every three months from patients with a history of recurrent MDD in the United Kingdom, the Netherlands, and Spain (N = 619). We used latent class and latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined transitions over time. We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. These same classes were identified at 6- and 12-month follow-ups, and participants tended to remain in the same class over time. We found no statistically significant differences between the two severe subtypes regarding baseline clinical and sociodemographic characteristics. Our findings emphasize severity differences over symptom types, suggesting that current subtyping methods provide insights akin to existing severity measures. When examining transitions, participants were most likely to remain in their respective classes over 1-year, indicating chronicity rather than oscillations in depression severity. Future work recommendations are made.

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Figure 1. Time course of stimulus presentation for the implicit facial emotional processing task
Figure 4. Axial view of the Default Mode Network constellation across the PRISM1 and PRISM2
Figure 5. Social dysfunction and functional connectivity of the Default Mode Network. A): Significant
Figure 6. Social dysfunction and functional connectivity of the Default Mode Network in the mega-
Social dysfunction relates to altered default mode network functional integrity across neuropsychiatric disorders: A replication and generalization study

January 2025

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31 Reads

Background Social dysfunction is an early manifestation of neuropsychiatric disorders that may relate to altered Default Mode Network (DMN) integrity. This study aimed to replicate previous findings linking social dysfunction with diminished resting-state DMN functional connectivity and altered task-based DMN functional activation in response to emotional faces across schizophrenia (SZ), Alzheimer’s disease (AD), and healthy controls (HC), and to extend these findings to major depressive disorder (MDD). Methods Resting-state fMRI and task-based fMRI data on implicit facial emotional processing were acquired in an overlapping cohort (resting-state fMRI: N=167; SZ=32, MDD=44, AD=29, HC=62. Task-based fMRI: N=152; SZ=30, MDD=42, AD=26, HC=54). Additionally, mega-analyses (N=317 for resting-state fMRI; N=291 for task-based fMRI) of the current and a prior independent sample were conducted. Social dysfunction was indexed with the Social Functioning Scale (SFS) and the De Jong-Gierveld Loneliness (LON) scale. Results The association between higher mean SFS+LON social dysfunction scores and diminished DMN connectivity within the dorsomedial prefrontal cortex across SZ/AD/HC participants was replicated, and extended to MDD patients. Similar observations within the dorsomedial and rostromedial prefrontal cortex were found in the mega-analysis. Associations between social dysfunction and DMN activation in response to sad and happy faces were not replicated or found in the mega-analysis. Conclusions Diminished dorsomedial prefrontal cortex DMN connectivity emerged as a transdiagnostic neurobiological marker for social dysfunction, suggesting a potential treatment target for precision medicine approaches. DMN functional responses to emotional faces may not be a sensitive biomarker for social dysfunction.



Fig. 1: Overview of the three key components of Immuno-Metabolic Depression (IMD).
Fig. 2: A visual, simplified overview of risk and neurobiological mechanisms involved in the development of immuno-metabolic depression. Note: Information on increased imbalance in energy supply/demand (immuno-metabolic stress) is conveyed through interoceptive signals to the brain, which orchestrates congruent physiological and behavioural energy-saving/intake responses. Various factors, such as genetic predisposition or environmental challenges (e.g., overnutrition, stress/trauma) can disrupt this homeostatic system. For instance, elevated inflammatory signalling may lead to central insulin or leptin resistance and overall disconnection in homeostatic brain hubs. As a result, the interoceptive signals regarding body energy status are misread, pushing the system towards excessive energy-saving/intake responses (e.g., increased appetite, reduced activity). These outputs may, in turn, further amplify the system's dysregulation (e.g., increasing inflammatory signalling) setting up a self-sustaining detrimental cycle.
Fig. 3: Six key facts of the impact, burden, future research needs, and potential personalized treatment options for immuno-metabolic depression (IMD).
Immuno-metabolic depression: from concept to implementation

The Lancet Regional Health - Europe

Major depressive disorder is a common, disabling mental disorder characterized by extensive etiological and phenotypic heterogeneity. This heterogeneity makes treatment approaches imprecise and often ineffective. Insight into the underlying biological mechanisms underpinning depression and its subtypes may enable more personalized treatments. In this review, we provide an overview of immuno-metabolic depression and illustrate that significant immuno-metabolic dysregulations are present in about 20–30% of people with depression. Such immuno-metabolic depression is characterized by the clustering of 1) atypical, energy-related depressive symptoms such as hypersomnia, fatigue, hyperphagia, and possibly anhedonia, 2) systemic low-grade inflammation with elevated levels of e.g., C-reactive protein, cytokines and glycoprotein acetyls, and 3) metabolic abnormalities involving e.g., obesity, dyslipidaemia, insulin and leptin resistance. Persons with immuno-metabolic depression are at a higher risk for cardiometabolic diseases and seem to respond less well to standard antidepressant treatment. Interventions targeting inflammation, metabolism or lifestyle may be more effective treatment options for individuals with immuno-metabolic depression, in line with principles of precision psychiatry.


Demographic and clinical information of the participants for each dataset
Comparative analysis of model performance on age and gender MDD balanced data using different LLMs
Exploring Biases Related to the Use of Large Language Models in a Multilingual Depression Corpus

December 2024

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32 Reads

Recent advancements in Large Language Models (LLMs) present promising opportunities for applying these technologies to aid the detection and monitoring of Major Depression Disorder (MDD). However, demographic biases in LLMs may present challenges in the extraction of key information. This study evaluates commonly used LLMs in the speech health literature, across a cohort comprised of English, Spanish, and Dutch speakers with recurrent MDD to observe the effects of different demographic imbalances. Results indicate demographics indeed influence model performance. Gender showed variable impacts across models, with age presenting more pronounced differences. Model performance also varied across language. This study emphasizes the necessity of incorporating demographic-aware models in health-related analyses. It raises awareness of the biases that may affect their application in mental health and suggests further research on methods to mitigate these biases and enhance model generalization.


Glucocorticoids and HPA axis regulation in the stress-obesity connection: A comprehensive overview of biological, physiological and behavioural dimensions

December 2024

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9 Reads

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1 Citation

Clinical Obesity

Chronic stress, characterized by increased long‐term exposure to the glucocorticoid hormone cortisol, is increasingly linked to obesity development. Still, various knowledge gaps persist, including on underlying pathophysiological mechanisms. The aim of the current review is to provide the latest insights on the connection between stress and obesity. We discuss three biological stress systems—the autonomic nervous system, the hypothalamus–pituitary–adrenal (HPA) axis and the immune system—and their link with obesity, with a particular focus on the HPA axis. The role of cortisol and its regulatory variations (including glucocorticoid rhythmicity and altered sensitivity) in adipose tissue biology and obesity development is discussed. Moreover, we highlight the physiological, affective, cognitive and behavioural dimensions of the stress response offering a deeper understanding of how stress contributes to obesity development and vice versa. Finally, stress as a treatment target for obesity is discussed. We conclude that the link between stress and obesity is complex and multifaceted, influenced by physiological, affective, cognitive and behavioural stress response mechanisms, which especially when chronically present, play a key role in the development of obesity and associated cardiometabolic diseases. This necessitates integrated approaches tailored to individual needs, including lifestyle modifications, behavioural interventions, psychosocial support and possible additional pharmacological interventions.



Citations (51)


... As adipose tissue enlarges, it secretes adipokines and pro-inflammatory cytokines in a dysfunctional manner, coupled with an increased release of free fatty acids that contributes to chronic low-grade inflammation and the onset of insulin resistance, dyslipidemia, and other obesity-related metabolic disorders. Obesity also involves a disrupted HPA axis, altered cortisol secretion profiles, and diurnal salivary cortisol rhythms [24]. GCs participate in several processes within adipose tissue, including adipogenesis, metabolism, inflammation, and adipokine production. ...

Reference:

The Role of Cortisol and Dehydroepiandrosterone in Obesity, Pain, and Aging
Glucocorticoids and HPA axis regulation in the stress-obesity connection: A comprehensive overview of biological, physiological and behavioural dimensions
  • Citing Article
  • December 2024

Clinical Obesity

... 93 Moreover, while having comparable effects on mental health, running therapy seems more beneficial than SSRI treatment when examining physical health outcomes such as weight, waist circumference, inflammation, metabolic markers, blood pressure and heart rate. 94,95 Exercise interventions thus seem a viable addition in the treatment of immuno-metabolic depression. ...

Running therapy or antidepressants as treatments for immunometabolic depression in patients with depressive and anxiety Disorders: A secondary analysis of the MOTAR study
  • Citing Article
  • October 2024

Brain Behavior and Immunity

... To account for multiple testing in GWAS, a fixed P-value threshold of 5 × 10 −8 is widely used to identify association between a common genetic variant and a trait of interest [47][48][49][50]. Chen et al. [47] demonstrate that the standard 5 × 10 −8 P-value threshold is the best multiple testing procedure for limiting false positives and is appropriate for both large and modest-sized studies to generate a highly accurate list of associated loci. ...

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries

Nature Genetics

... It may have been preferable to employ a continuous measure of MDD symptomology, rather than neuroticism. However, we are unaware of any large-scale symptom level data for MDD in a general population sample (e.g. in UK biobank, many depression symptoms are only queried if gating symptoms are endorsed) 23 , and it is possible that if clinical symptom . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. ...

Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts

Psychological Medicine

... European epidemiological studies with up to 50,000 participants 21-23 examined a lipid-targeted metabolomic platform and identified a biological signature for depression characterized by higher levels of glycoprotein acetyls (indexing systemic chronic inflammation), isoleucine (implicated in insulin resistance), triglycerides, very-low-density lipoproteins and lower levels of highdensity lipoproteins, and altered levels of metabolites involved in mitochondrial energetics such as fatty acids. Other European cohorts with up to 14,000 participants 24,25 applied even larger-scaled untargeted metabolomic platforms and confirmed the association of depression with reduced fatty acids and increased lysophospholipids involved in energy homeostasis and immunity. ...

The metabolome-wide signature of major depressive disorder

Molecular Psychiatry

... pathways. In particular, gene set enrichment analysis of the head circumference variants found several enriched gene sets in various cancers and the p53, Wnt, and ErbB signaling pathways (Supplementary Table S1) [4]. In addition, a few studies have previously reported an association between head size at birth and the risk of developing certain types of cancer later in life [5][6][7]. ...

Genetic variants for head size share genes and pathways with cancer

Cell Reports Medicine

... In our individual participant data metaanalyses, we found little evidence of a relation between psychosocial stress and cancer incidence, with the exception of lung cancer, where smoking played a mediating role. [2][3][4] We fully agree with Dr. Jerjes on the importance of distinguishing between acute and chronic stress in their potential effects on biological mechanisms and subsequent cancer risk. In PSY-CA we examined psychosocial factors which were assessed at only one point in time as only few cohorts had repeated measurements of psychosocial factors available. ...

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis

Psychological Medicine

... Most trained LLMs, developed from extensive text datasets, often inherit biases ranging from gender to cultural insensitivities, which can negatively impact their application in mental health settings; e.g., when aiding the monitoring of MDD symptoms [16][17][18] . Addressing such biases is critical to minimizing the risk of discrimination and ensuring that LLMs produce fairer/equitable outcomes for diverse populations. ...

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model
  • Citing Article
  • March 2024

Journal of Affective Disorders

... Thus, ECP may go hand-in-hand with reducing irrational medication use, resulting in co-benefits for patients and the planet. While discontinuation of antidepressants, antipsychotics and mood stabilizers may not be an option for all patients as they are all associated with increased relapse risks, considerations of specific risk factors and a discontinuation (crisis) plan may help accommodate patients' preferences and ensure discontinuation practices have a strong evidence basis (Vinkers et al., 2024). In considering both the burden of relapse on quality of life of patients and the environmental footprint resulting from relapse (Prasad et al., 2022), ECP practices balance discontinuation risks and evidence on treatment outcomes with patient preferences. ...

Discontinuation of psychotropic medication: a synthesis of evidence across medication classes

Molecular Psychiatry

... Moreover, empirical research, including Liu J. et al. (2024), and Gathier et al. (2024), confirms a strong link between depression and mobile phone dependency. Depressed individuals often turn to mobile phones for comfort, increasing their dependency. ...

The role of explicit and implicit self-esteem in the relationship between childhood trauma and adult depression and anxiety
  • Citing Article
  • March 2024

Journal of Affective Disorders