Biology subjects

Binder, E. B.

Publications and source records attributed to Binder, E. B..

At least 19 recordsLinked to original sources

bioRxiv2026

Mapping Alzheimer's neuropathology signatures to the whole brain transcriptome using machine learning data fusion

In Alzheimer's disease (AD), misfolded proteins emerge across the entire brain in structured, yet not rigid, spatiotemporal patterns. Yet, a systematic bias of single-cell genomics toward sampling mostly cortical tissue limits our understanding of the whole-brain transcriptomic vulnerability to AD. Here, we develop a machine learning method to extrapolate local AD neuropathology signatures to the whole brain. By analyzing gene expression profiles of over two million cortical cells from 427 humans spanning the AD-pathology spectrum, we derive transcriptomic estimators of AD neuropathology. After extensive validations on datasets with known ground truth, we apply this framework to three million cells from 108 brain regions in the Siletti whole human brain atlas and derive an anticipated brain map of transcriptomic signatures indexing AD neuropathology. This interrogation of regions spanning the cortical, subcortical, and brainstem structures uncovers transcriptomic signatures associated with hyperphosphorylated tau in the medulla oblongata, dorsal raphe nucleus, and the tuberal and mammillary regions of the hypothalamus. At the cellular level, assessments of these signatures across 31 cell populations identify VGLUT1/2 expressing neurons, astrocytes, and microglia as key neuropathology-resembling populations. Within the hippocampus, pathology signatures surface in the rostral cornu ammonis (CA) subfields, particularly in the CA1 pyramidal neurons and dentate granule cells. {beta}-amyloid-like signatures localize to the neocortex with laminar selectivity--most prominently in upper layer somatostatin+ intratelencephalic neurons (L2-L3), but also in deep layer intratelencephalic and corticothalamic neurons (L5-L6). Neocortical astrocytes and microglia exhibiting disease associated signatures similarly demonstrate a unique laminar preference. Together, this study provides the first whole human brain map of AD pathology-associated transcriptomic signals, and exposes cell type, region, and cortex layer specific vulnerabilities.

neuroscience↗

bioRxiv2026

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Understanding how biological age measures perform across development lays the groundwork for investigations into lifespan trajectories of healthy aging. We provide the most comprehensive assessment of epigenetic and brain age models across development (birth to 24 years; [≤]20,917 observations across 15 cohorts), evaluating how these models associate with chronological age and with each other, and how these associations change across development. Chronological age-prediction accuracy of epigenetic and brain age models was modest and varied substantially. Accuracy improved with age and stabilized by middle childhood. Few brain and fewer epigenetic clocks performed stably and well across all developmental stages. Performance was better when age range and tissue corresponded between training and testing data. Associations between epigenetic-brain age residuals were small, and changed little across development, tissues or clock generation. Given this developmentally dynamic system of epigenetic-brain age performances and associations, we give key recommendations to improve developmental research in this field.

neuroscience↗

bioRxiv2026

Developmental Correlates of Epigenetic and Polygenic Indices of Cognition and Educational Attainment from Birth to Young Adulthood

Large-scale genomic studies have identified biomarkers of adult cognitive functioning and educational attainment, yet the developmental pathways connecting these biomarkers to adult outcomes remain unclear. Drawing on four cohorts, we examined the developmental correlates of an epigenetic index of adult cognitive function ( Epigenetic-g) alongside polygenic indices of cognition and education. Epigenetic-g and polygenic indices were uncorrelated and captured distinct variation in childrens cognitive and academic performance. Longitudinal analyses revealed that Epigenetic-g is plastic in early childhood, reaching moderate stability by adolescence, and, unlike polygenic indices, is not related to longitudinal cognitive growth. Twin models indicated that Epigenetic-g captures genetic and unique environmental variation relevant to cognitive and academic achievement that is not identified by current polygenic indices. Epigenetic indices relevant to psychological development can be generated from DNA methylation studies of adults, with most variation in these indices emerging early in life.

genomics↗

bioRxiv2026

(Epi-)Genomic Data in the German TwinLife Study: TwinSNPs and TECS Cohort Profiles

The German Twin Family Panel TwinLife is a nationwide longitudinal study of twins and their family members. Primarily focusing on the development of social inequalities over the life course, TwinLife has been collecting data since October 2014 starting with 4,096 twin families (Ntotal = 16,951 individuals). As Germanys largest twin study to date, TwinLife has been surveying four birth cohorts of monozygotic and dizygotic same-sex twin pairs (initially [~]5, 11, 17, and 23 years old) and their families for 11 years. Survey data have been collected through five biennial face-to-face interviews with four computer-assisted telephone interviews in the years between. In addition, saliva samples were collected before the COVID-19 pandemic (2018-2020), during the pandemic (2021), and after (2022-2024). In this Cohort Profile, we describe the curation and initial analyses of molecular genetic and epigenetic data from the two TwinLife satellite projects TwinSNPs and TECS. Together, these projects currently comprise 12,108 processed DNA samples from 6,450 participants, extracted from the first two saliva collections before and during the COVID-19 pandemic. We compared the subsamples with the overall TwinLife sample and provide an overview of derived polygenic scores (PGS), epigenetic clocks and other methylation profile scores (MPS). We found that PGS predicted sample attrition in TwinLife, with small but significant associations between higher PGS for educational attainment and continued participation. Epigenetic clocks derived from saliva were highly correlated with chronological age (r = .71 to r = .94) and were generally more stable over time than other MPS. PGS for epigenetic clocks were associated with the respective clock only during but not before the start of the pandemic. We discuss opportunities of combining prospectively assessed molecular (epi)genetic data in within-family designs such as TwinLife and its implications and avenues for future research.

genetics↗

bioRxiv2026

Multilevel sex-specific neurobiological signatures of early life adversity

Stress exposure early in life is an established risk factor for adult psychiatric illness, yet these disorders - including anxiety disorders and depression - show significant sex-dependence in prevalence, symptomatology, and treatment response. The biology underlying these differences remains largely unexplored and may contribute to the clinical heterogeneity in anxiety and depression. Here, we characterize the lasting impact of developmental stress on adulthood neurobiology and behavior in mice by combining analyses of multiple levels of brain function, including whole-brain c-Fos mapping, manganese-enhanced MRI and transcriptomics with advanced behavioral phenotyping. Across levels of investigation, we find distinct and often opposite effects of developmental stress depending on sex. These results together showcase the strong influence of sex on how early life adversity affects the onset of stress-related disorders. This work emphasizes the necessity of considering sex when investigating developmental and neurobiological underpinnings of stress-related disorders and displays a vast range of lasting effects of developmental stress on the brain, which provides a valuable resource for future studies aiming to improve psychiatric treatments.

neuroscience↗

bioRxiv2025

RAMEN: Dissecting individual, additive and interactive gene-environment contributions to DNA methylome variability in cord blood

DNA methylation (DNAme) is the most commonly studied epigenetic mark in human populations. DNAme has gained attention in the Developmental Origins of Health and Disease field due to its gene expression regulation and potential long-term stability. Genetic variation and environmental exposures are amongst the main factors influencing inter-individual DNAme variability. However, the proportion and genomic distribution of their individual, additive and interactive effects on the DNA methylome remains unclear. Here, we introduce RAMEN, a Findable, Accessible, Interoperable, and Reusable (FAIR) framework tailored for DNAme microarrays. Using machine learning and statistical techniques, RAMEN models and dissects gene-environment contributions to genome-wide Variably Methylated Regions (VMRs), while controlling for spurious associations. To comprehensively test the power of RAMEN, we analyzed and characterized VMRs from cord blood samples from two independent cohorts (CHILD and PREDO; overall n=1,662). We identified genetics as a consistent key contributor to DNAme variability, usually in additive and interactive combinations with the environment, with genetic terms explaining the largest proportion of DNAme variance, compared to environmental and interaction terms. Operationalizing RAMEN as an R package to conduct scalable genome-exposome contribution analyses, our results highlighted the importance of genetic variation in sculpting DNAme patterns in early life.

bioinformatics↗

bioRxiv2025

Integrative Gene and Isoform Co-expression Networks Reveal Regulatory Rewiring in Stress-related Psychiatric Disorders

Isoform-specific expression patterns have been implicated in stress-related psychiatric disorders like major depressive disorder (MDD), yet the extent of their involvement and their interrelationships remain unclear. We constructed co-expression networks for individuals affected (n=210, 81% with depressive symptoms) and unaffected (n=95) by stress-related psychiatric disorders. We incorporated total gene expression (TE) and isoform ratio (IR) data and validated the inferred networks using advanced graph generation techniques. Our analysis revealed distinct network topology and structure between the two groups. Investigation of the 127 shared hubs (degree >= 10) found that these hubs exhibit co-regulatory patterns unique to each network. The affected individuals network also contained 61 hub nodes with a minimum absolute fold increase of two in connectivity compared to the unaffected individuals network. Notably, 49% of these hubs showed evidence for association with psychiatric disorders. Gene Ontology enrichment analysis revealed distinct biological processes associated with hubs, such as mRNA processing for affected and immune response and cell adhesion for unaffected individuals. Enrichment analysis of GWAS loci further supported network-specific findings. Analysis of the isoform-specific nodes showed distinct protein-protein interactions compared to gene-level analysis. This is the first study to demonstrate network-level differences in gene and isoform co-expression patterns between individuals with and without stress-related psychiatric disorders, with a particular focus on depressive symptoms. Our findings provide evidence for substantial rewiring of gene regulatory networks in affected individuals. Incorporating isoform-level data revealed a deeper level of complexity, highlighting the importance of considering isoform variations in understanding the molecular basis of these conditions.

systems biology↗

bioRxiv2025

Lower cortical FKBP5 DNA methylation at key enhancer sites is associated with older age and higher gene expression in schizophrenia

An increasingly compelling body of literature indicates the glucocorticoid receptor cochaperone FK506-binding protein 51 (FKBP51) is a promising target for novel psychiatric therapeutics. However, the mechanisms regulating the corresponding FKBP5 gene directly in the human brain remain largely unknown yet are needed to facilitate the development of precise mechanism-based treatment approaches. Here, we examined FKBP5 DNA methylation patterns in postmortem human brain samples from the dorsolateral prefrontal cortex of individuals who lived with a major psychiatric disorder (schizophrenia, major depression, or bipolar disorder; n=329) and controls n=231. We identified that cytosine-phosphate-guanine-dinucleotide (CpG) specific FKBP5 DNA methylation is altered in psychiatric disorders across the FKBP5 locus, and that these changes are differentially associated with age and genotype (rs1360780 CC vs CT/TT). Individuals with schizophrenia had significantly lower levels of DNA methylation in the proximal enhancer of FKBP5, which also negatively correlated with FKBP5 gene expression. These changes were also associated with predicted glucocorticoid response elements (GREs) in the proximal enhancer, but not other transcription factor binding sites. This evidence supports that in the human cortex, FKBP5 DNA methylation is associated with both genetic and ageing effects, and that the associations between these factors vary at a diagnosis-specific level in psychopathology. This may have implications for developing FKBP5-targeted therapeutics and defining a subgroup of patients who will benefit from such treatments.

neuroscience↗

bioRxiv2024

Astrocytic glutamate regulation is implicated in the development of stress-related psychiatric disorders

Astrocytes are a brain cell type vulnerable to the effects of stress and the development of psychiatric-like phenotypes in animals, yet how this translates to humans is unclear. Here, we probed the diversity of [~]145,000 total human cortical astrocytes with single nucleus and spatial transcriptomics, showing that human astrocytes comprise a molecularly and anatomically diverse cell population. In individuals with psychiatric disorders and high adversity exposure, we identified distinct alterations to glutamate-related synaptic functions, supported by histological quantification of >20,000 astrocytes. Early-life adversity exposure produced more pronounced cellular changes than adversity experienced later in life, and female cases displayed stronger transcriptomic associations than males with adversity exposure. Human pluripotent stem cell-derived astrocytes from both two- and three-dimensional models confirmed that glutamate signalling is directly impacted by glucocorticoid activation. Our findings highlight astrocytes as crucial players in how exposure to severe adversity raises risk to psychopathology and position them as strategic pharmacological targets for future intervention strategies.

neuroscience↗

bioRxiv2024

Age-Associated Genetic and Environmental Contributions to Epigenetic Aging Across Adolescence and Emerging Adulthood

BackgroundEpigenetic aging estimators commonly track chronological and biological aging, quantifying its accumulation (i.e., epigenetic age acceleration) or speed (i.e., epigenetic aging pace). Their scores reflect a combination of inherent biological programming and the impact of environmental factors, which are suggested to vary at different life stages. The transition from adolescence to adulthood is an important period in this regard, marked by an increasing and, then, stabilizing epigenetic aging variance. Whether this pattern arises from environmental influences or genetic factors is still uncertain. This study delves into understanding the genetic and environmental contributions to variance in epigenetic aging across these developmental stages. Using twin modeling, we analyzed four estimators of epigenetic aging, namely Horvath Acceleration, PedBE Acceleration, GrimAge Acceleration, and DunedinPACE, based on saliva samples collected at two timepoints approximately 2.5 years apart from 976 twins of four birth cohorts (aged about 9.5, 15.5, 21.5, and 27.5 years at first and 12, 18, 24, and 30 years at second measurement occasion). ResultsHalf to two-thirds (50-68%) of the differences in epigenetic aging were due to unique environmental factors, indicating the role of life experiences and epigenetic drift, besides measurement error. The remaining variance was explained by genetic (Horvath Acceleration: 24%; GrimAge Acceleration: 32%; DunedinPACE: 47%) and shared environmental factors (Horvath Acceleration: 26%; PedBE Acceleration: 47%). The genetic and shared environmental factors represented the primary sources of stable differences in corresponding epigenetic aging estimators over 2.5 years. Age moderation analyses revealed that the variance due to individually-unique environmental sources was smaller in younger than in older cohorts in epigenetic aging estimators trained on chronological age (Horvath Acceleration: 47% to 49%; PedBE Acceleration: 33% to 68%). The variance due to genetic contributions, in turn, potentially increased across age groups for epigenetic aging estimators trained in adult samples (Horvath Acceleration: 18% to 39%; GrimAge Acceleration: 24% to 43%; DunedinPACE: 42% to 57%). ConclusionsTransition to adulthood is a period of the increasing variance in epigenetic aging. Both environmental and genetic factors contribute to this trend. The degree of environmental and genetic contributions can be partially explained by the design of epigenetic aging estimators.

genomics↗

bioRxiv2024

Huntingtin CAG repeat size variations outside the Huntington's disease complex: associations with depression and anxiety phenotypes and basal ganglia structure

Huntingtons Disease (HD) is strongly associated with psychiatric symptoms, yet, associations between Huntingtin gene (HTT) CAG repeat size variations and psychiatric phenotypes outside the HD complex are still under-investigated. In this genetic case-control study we compared the distribution of HTT CAG repeat sizes in predefined ranges between patients with major depressive disorder (MDD) (n=2136) and anxiety disorders (ANX) (n=493), and healthy controls (CON) (n=1566). We used regression models to study interactions between the alleles and associations with fine-granular clinical phenotypes and basal ganglia structure. HD mutations in the range of incomplete penetrance (36-39 repeats) were not overrepresented in patients. In participants older than 48 years, 13-20 repeats on both HTT alleles were associated with a reduced ANX risk whereas a 13-20|21-26 combination was associated with an increased ANX risk. Post-hoc analyses confirmed a turning point around 21 repeats and trends in the same direction were detected for MDD. The joint patient|CON analysis of the full spectrum of allele combinations confirmed interaction effects and age-dependent allele|risk profiles. A short-by-long interaction effect and an age-dependent negative correlation of the short allele on the nucleus accumbens volume was detected, independently of the diagnostic group. In conclusion, we revealed that HTT CAG repeat sizes of both alleles in the non-HD range modulate the susceptibility for common psychiatric disorders and basal ganglia structure in an age-dependent way, displaying that normal variation of the functionally diverse wildtype huntingtin protein may already impact brain function.

genetics↗

bioRxiv2024

Chronic exposure to glucocorticoids amplifies inhibitory neuron cell fate during human neurodevelopment in organoids

Disruptions in the tightly regulated process of human brain development have been linked to increased risk for brain and mental illnesses. While the genetic contribution to these diseases is well established, important environmental factors have been less studied at molecular and cellular levels. In this study, we used single-cell and cell-type-specific techniques to investigate the effect of glucocorticoid (GC) exposure, a mediator of antenatal environmental risk, on gene regulation and lineage specification in unguided human neural organoids. We characterized the transcriptional response to chronic GC exposure during neural differentiation and studied the underlying gene regulatory networks by integrating single-cell transcriptomics-with chromatin accessibility data. We found lasting cell type-specific changes that included autism risk genes and several transcription factors associated with neurodevelopment. Chronic GCs influenced lineage specification primarily by priming the inhibitory neuron lineage through key transcription factors like PBX3. We provide evidence for convergence of genetic and environmental risk factors through a common mechanism of altering lineage specification.

neuroscience↗

bioRxiv2023

Gene Set-Based Analysis of the Endosomal Sorting Processes Cargo Selection and Membrane Tubulation with Human Reward System Reactivity

Dysfunction of the dopaminergic reward system has been implicated in the pathophysiology of several neuropsychiatric disorders. The endosomal network encompasses important processes related to neurotransmission in dopamine neurons, e.g, endocytosis, sorting, recycling and degradation of receptors. In the present study, we investigated whether genetic variation influencing the endosomal sorting machinery, in particular cargo selection and membrane tubulation, may impact on the activation strength in key regions of the mesolimbic reward system, i.e. the ventral tegmental area (VTA) and the nucleus accumbens (NAc). To test our hypothesis, the VTA and NAc responses to conditioned reward stimuli were investigated using the desire-reason dilemma (DRD) paradigm during functional magnetic resonance imaging (fMRI). Association of these neural responses with a set of genetic variants related to endosomal sorting processes were tested in two independent samples (N = 182; N = 214). In the first sample, the gene set was associated with both VTA and NAc responses to conditioned reward stimuli [empirical P -values: R-VTA 0.0036; R-NAc 0.0016; L-NAc 0.0094], while the effect in the R-VTA could be replicated in the second sample [empirical P -value: R-VTA 0.0443] at the level of the gene set. For the NAc, an additional exploratory analysis of a patient-only subsample of the first sample (N = 64) suggested that the gene set may express its effect in this brain region predominantly in patients. These findings provide first evidence that the endosomal sorting processes cargo selection and membrane tubulation influence neural responses of the reward system to conditioned stimuli. Further studies are required to clarify the role of endosomal sorting processes in the pathophysiology of neuropsychiatric disorders.

genetics↗

bioRxiv2023

Stress-induced brain responses are associated with BMI in women

BackgroundStress is associated with elevated risk for overweight and obesity, especially in women. Since body mass index (BMI) is correlated with increased inflammation and reduced baseline cortisol, obesity may lead to altered stress responses. However, it is not well understood whether stress-induced changes in brain function scale with BMI and if peripheral inflammation contributes to this. MethodsWe investigated the subjective, autonomous, endocrine, and neural stress response in a transdiagnostic sample (N=192, 120 women, MBMI=23.7{+/-}4.0 kg/m2; N=148, 89 women, with cytokines). First, we used regression models to examine effects of BMI on stress reactivity. Second, we predicted BMI based on stress-induced changes in activation and connectivity using cross-validated elastic-nets. Third, to link stress responses with inflammation, we quantified the association of BMI-related cytokines with model predictions. ResultsBMI was associated with higher negative affect after stress and an increased response to stress in the substantia nigra and the bilateral posterior insula (pFWE<.05). Moreover, stress-induced changes in activation of the hippocampus, dACC, and posterior insula predicted BMI in women (pperm<.001), but not in men. BMI was associated with higher baseline cortisol while cytokines were not associated with predicted BMI scores. ConclusionsStress-induced changes in the hippocampus and posterior insula predicted BMI in women, indicating that acute brain responses to stress might be more strongly related to a higher BMI in women compared to men. Altered stress-induced changes were associated with baseline cortisol but independent of cytokines, suggesting that the endocrine system and not inflammation contributes to stress-related changes in BMI.

neuroscience↗

bioRxiv2022

Temporal regulation of ZBTB16 expression by glucocorticoids alters human cortical neurogenesis

Glucocorticoids are important for proper organ maturation and their levels are tightly regulated during development. Here we use human cerebral organoids and mice to study cell-type specific effects of glucocorticoids on neurogenesis. We show that glucocorticoids increase a specific type of basal progenitors (co-expressing PAX6 and EOMES) that has been shown to drive cortical expansion in gyrified species. This effect is mediated via the transcription factor ZBTB16 and leads to increased production of neurons. A phenome-wide mendelian randomization analysis of an enhancer variant that moderates glucocorticoid-induced ZBTB16 levels, reveals causal relationships with higher educational attainment and altered brain structure. The relationship with postnatal cognition is supported by data from a prospective pregnancy cohort. This study provides a novel cellular and molecular pathway for the effects of glucocorticoids on human neurogenesis that relates to lasting postnatal phenotypes.

neuroscience↗

bioRxiv2022

DiffBrainNet: differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions

Genome-wide gene expression analyses are invaluable tools for increasing our knowledge of biological and disease processes, allowing a hypothesis-free comparison of gene expression profiles across experimental groups, tissues and cell types. Traditionally, transcriptomic data analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders and their risk factors, including stress. In this manuscript, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress hormone receptor agonist dexamethasone in C57Bl/6 mice, in 8 brain regions important for stress processing: the prefrontal cortex, the amygdala, the paraventricular nucleus of the hypothalamus, the cerebellar cortex, and sub regions of the hippocampus: the dorsal and ventral Cornu Ammonis 1, the dorsal and ventral dentate gyrus. By applying a combination of differential network- and differential expression-analyses, we find that these explain distinct but complementary aspects and biological mechanisms of the responses to the stimulus. In addition, network analysis identifies new differentially connected partners of important genes and can be used to generate hypotheses on specific molecular pathways affected. With this work, we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain: DiffBrainNet (http://diffbrainnet.psych.mpg.de), which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

genomics↗

bioRxiv2021

Spatio-temporal dynamics of stress-induced network reconfigurations reflect negative affectivity

BackgroundChronic stress is an important risk factor in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk. MethodsUsing an established psycho-social stress task flanked by two resting-state scans, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 unmedicated participants with and without mood and anxiety disorders. To estimate block-wise changes in stress-induced brain activation and FC, we used hierarchical mixed-effects models based on denoised timeseries within a predefined stress network. We predicted inter- and intra-individual differences in stress phases (anticipation vs. acute stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines. ResultsWe identified four subnetworks showing distinct changes in FC over time. Subnetwork trajectories predicted the stress phase (accuracy: 71%, pperm<.001) and increases in pulse rate (R2=.10, pperm<.001). Critically, individual spatio-temporal trajectories of changes across networks also predicted negative affectivity ({Delta}R2=.08, pperm=.009), but not the presence or absence of a mood and anxiety disorder. ConclusionsSpatio-temporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.

neuroscience↗

bioRxiv2020

Threat-induced hippocampal connectivity fingerprints do not generalize to psychosocial stress

Stress is an everyday experience and maladaptive responses play a crucial role in the etiology of affective disorders. Despite its ubiquity, the neural underpinnings of subjective stress experiences have not yet been elucidated, particularly at an individual level. In an important advance, Goldfarb et al.1 showed recently that subjective stress and arousal levels in response to threatening stimuli were successfully predicted based on changes in hippocampal connectivity during the task using a machine learning approach. Crucially, stress responses were predicted by interpretable hippocampal connectivity networks, shedding new light on the role of the hippocampus in regulating stress reactivity2. However, the authors induced stress by displaying aversive pictures, while stress research often relies on the extensively validated Trier social stress task (TSST)3. The TSST incorporates crucial factors such as unpredictability of success and the social-evaluative threat of the stressor thereby eliciting cortisol responses more robustly compared to threatening images4. Towards generalization, cross validation within a sample as conducted by Goldfarb et al.1 or independent replications are important steps, but the generalizability to different stressors allows to draw broader conclusions about the potential use of hippocampal connectivity to predict subjective stress5. Arguably, translating these findings to clinical applications would require a broad generalization of the results or the prediction algorithm to psychosocial stress. Here, we assessed the predictive performance of Goldfarb et als1 algorithm for subjective stress in an independent sample using an MR adaption of the TSST6,7. In line with Goldfarb et al.1, we observed robust stress-induced changes in hippocampal connectivity. However, the spatial correlation of the changes in connectivity was low indicating little convergence across alleged stress paradigms. Critically, stress-induced changes of hippocampal connectivity were not robustly predictive of subjective stress across a multiverse of analyses based on connectivity changes. Collectively, this indicates that the generalizability of the reported stress connectivity fingerprint to other stressors is limited at best, suggesting that specific tasks might require tailored algorithms to robustly predict stress above chance levels.

neuroscience↗