Publications by authors named "Julia Katharina Pfarr"

Article Synopsis
  • Recent research indicates that impairments in social skills and theory of mind related to autism spectrum disorder (ASD) exist on a continuum among the general population, from typical individuals to those with ASD.
  • This study involved 56 non-clinical participants divided into high and low autistic-like social skill traits, examining amygdala function and structure through various imaging techniques.
  • Results showed that individuals with high social skill traits exhibited increased blood perfusion and different activation patterns in the amygdala when processing fearful faces, suggesting overlapping neurological features between those with typical social functioning and ASD patients.
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Background: Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum.

Methods: In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity.

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Article Synopsis
  • - The study explores the connections between dimensional psychopathological syndromes and brain structure/function in patients with Major Depressive Disorder, Bipolar Disorder, Schizoaffective Disorder, and Schizophrenia, analyzing data from 1,038 individuals.
  • - Researchers identified three main psychopathological factors—paranoid-hallucinatory syndrome, mania, and depression—and found significant brain volume and cortical thickness differences linked to the paranoid-hallucinatory syndrome.
  • - Genome-wide association studies revealed significant genetic associations for mania and depression, suggesting a need for more dimensional perspectives in psychiatric classifications to improve understanding and treatment.
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Background: Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

Methods: In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPI scale; = 208), patients with a DSM-IV-TR diagnosis of BD ( = 87), and healthy controls ( = 115) using voxel-based morphometry in SPM12/CAT12.

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Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients.

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  • This study looks at how stressful life events can lead to depression in people who might already be vulnerable to it.
  • They compared brain changes in people with depression to those without depression over two years.
  • They found that healthy people had some brain changes when stressed, but depressed people only showed changes when they had a history of tough childhood experiences and went through another episode of depression.
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Background: Case-control studies in major depression have established numerous regional grey and white matter effects in fronto-limbic brain regions. Yet, brain structural studies of dimensional depressive psychopathology within the subclinical spectrum are still limited, in particular for multi-modal imaging approaches.

Methods: Using voxel-based and surface-based morphometry (cortical thickness) in combination with diffusion tensor imaging (DTI) in a large non-clinical sample (N = 300), we correlated grey and white matter structural variation with subclinical depressive symptoms assessed with Beck's Depression inventory (BDI).

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Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified.

Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD.

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Background: Controllability is a measure of the brain's ability to orchestrate neural activity which can be quantified in terms of properties of the brain's network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging.

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Psychiatric disorders show high co-morbidity, including co-morbid expressions of subclinical psychopathology across multiple disease spectra. Given the limitations of classical case-control designs in elucidating this overlap, new approaches are needed to identify biological underpinnings of spectra and their interaction. We assessed autistic-like traits (using the Autism Quotient, AQ) and schizotypy - as models of subclinical expressions of disease phenotypes and examined their association with volumes and regional cerebral blood flow (rCBF) of anterior, mid- and posterior hippocampus segments from  structural MRI scans in 318 and arterial spin labelling (ASL) in 346 nonclinical subjects, which overlapped with the structural imaging sample (N = 298).

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Social dominance and subordination have been linked to fronto-limbic and fronto-thalamic networks and are related to phenotypes such as grandiose vs. vulnerable narcissistic traits. The latter have been linked to clinical features such as empathy and emotional regulation.

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Speech is a promising biomarker for schizophrenia spectrum disorder (SSD) and major depressive disorder (MDD). This proof of principle study investigates previously studied speech acoustics in combination with a novel application of voice pathology features as objective and reproducible classifiers for depression, schizophrenia, and healthy controls (HC). Speech and voice features for classification were calculated from recordings of picture descriptions from 240 speech samples (20 participants with SSD, 20 with MDD, and 20 HC each with 4 samples).

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Background: Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking.

Methods: In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories.

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Syntax, the grammatical structure of sentences, is a fundamental aspect of language. It remains debated whether reduced syntactic complexity is unique to schizophrenia spectrum disorder (SSD) or whether it is also present in major depressive disorder (MDD). Furthermore, the association of syntax (including syntactic complexity and diversity) with language-related neuropsychology and psychopathological symptoms across disorders remains unclear.

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Article Synopsis
  • The study investigates the relationship between formal thought disorder (FTD) symptoms and the brain's structural white matter connectivity across three mental health disorders: major depressive disorder, bipolar disorder, and schizophrenia.
  • Researchers analyzed data from 864 patients to identify three main dimensions of FTD: disorganization, emptiness, and incoherence, finding that disorganization and incoherence linked to global brain dysconnectivity.
  • The results highlight specific white matter subnetworks related to FTD, revealing significant overlap with brain regions previously associated with FTD in schizophrenia, indicating that these connection issues may be common across the disorders studied.
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Background: Negative stressful life events and deprivation of social support play critical roles in the development and maintenance of major depressive disorder (MDD). The present study aimed to investigate in a large sample of patients with MDD and healthy control participants (HCs) whether these effects are also reflected in white matter (WM) integrity.

Methods: In this diffusion tensor imaging study, 793 patients with MDD and 793 age- and sex-matched HCs were drawn from the Marburg-Münster Affective Disorders Cohort Study (MACS) and completed the Life Events Questionnaire (LEQ) and Social Support Questionnaire (SSQ).

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Article Synopsis
  • The study looked at how the brain's left and right sides might differ in people with schizophrenia compared to those without it, using brain scans from over 5,000 patients and 6,000 control subjects.
  • Researchers found that people with schizophrenia had slightly thinner areas in the left side of their brains, especially in certain regions, compared to those without the disorder.
  • The differences in brain structure might be linked to how schizophrenia affects brain functions, like language, but more research is needed to understand why they happen.
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Schizotypy has become an increasingly important construct for elaborating psychotic disorders that vary along the schizophrenic spectrum. However, different schizotypy inventories vary in conceptual approach and measurement. In addition, commonly used schizotypy scales have been seen as qualitatively different from screening instruments for prodromal schizophrenia like the Prodromal Questionnaire-16 (PQ-16).

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Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

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Article Synopsis
  • Cognitive dysfunction and changes in brain connectivity are prevalent in major depressive disorder (MDD), but their relationship is not well understood.
  • The study analyzed cognitive performance and brain connections in 805 healthy individuals and 679 MDD patients to explore how cognitive factors relate to brain structural networks.
  • Findings revealed a link between cognitive deficits and reduced connectivity in specific brain subnetworks, which was influenced by the severity of depressive symptoms, highlighting how MDD affects cognitive and brain functioning.
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Background: There is a lack of knowledge regarding the relationship between dimensional psychopathological syndromes and neurocognitive functions, particularly across the major psychiatric disorders (i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), and Schizophrenia (SZ)).

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Retrospective self-reports of childhood maltreatment (CM) are widely used. However, their validity has been questioned due to potential depressive bias. Yet, investigations of this matter are sparse.

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Background: Major depressive disorder (MDD) has been associated with alterations in brain white matter (WM) microstructure. However, diffusion tensor imaging studies in biological relatives have presented contradicting results on WM alterations and their potential as biomarkers for vulnerability or resilience. To shed more light on associations between WM microstructure and resilience to familial risk, analyses including both healthy and depressed relatives of MDD patients are needed.

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