Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders

Stein, Frederike; Schmitt, Simon; Pfarr, Julia‐Katharina; Ringwald, Kai G.; Thomas-Odenthal, Florian; Meller, Tina; Steinsträter, Olaf; Waltemate, Lena; Lemke, Hannah; Meinert, Susanne; Winter, Alexandra; Breuer, Fabian; Thiel, Katharina; Grotegerd, Dominik; Hahn, Tim; Jansen, Andreas; Lemke, Hannah; Krug, Axel; Nenadić, Igor; Kircher, Tilo

doi:10.1038/s41380-022-01687-4

Cited by 43 publications

(26 citation statements)

References 84 publications

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“…Even in disorders with significant phenotypic heterogeneity (e.g., SZ) we were able to identify consistent alterations within the rectus, which has previously been associated with a genetic risk for SZ, BP, and psychosis (Luna et al, 2022), and the cerebellum, with varying regions associated with cognitive losses (e.g., long-term and working memory) and psychosis (Clark et al, 2020; Moberget et al, 2018; Moberget & Ivry, 2019). Our findings within the hippocampus are also aligned with previous literature (Brosch et al, 2022; Lorenzetti et al, 2009; McCutcheon et al, 2023; Torres et al, 2016) that found reductions within MDD, BP, and SZ. Other cross-disorder studies found similar shared and disease-specific alterations in the hippocampus, amygdala, thalamus, accumbens of individuals with SZ, BP, and MDD (Okada et al, 2023).…”

Section: Discussionsupporting

confidence: 92%

Cortical Similarities in Psychiatric and Mood Disorders Identified in Federated VBM Analysis via COINSTAC

Rootes-Murdy,

Panta,

Kelly

et al. 2023

Preprint

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Psychiatric disorders such as schizophrenia, major depressive disorder, and bipolar disorder have areas of significant overlap across multiple domains including genetics, neurochemistry, symptom profiles, and regional gray matter alterations. Various structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across these different disorders, though few direct comparisons have been conducted. Given the overlap in symptom presentations and GM alterations, these disorders may have a common etiology or neuroanatomical basis that may relate to a certain vulnerability for mental illness. Pooling large data or heterogeneous data can ensure representation of several participant factors, providing more accurate results. However, ensuring large enough datasets at any one site can be cumbersome, costly, and may take many years of data collection. Large scale collaborative research is already facilitated by current data repositories and neuroinformatics consortia such as the Enhacing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium, institutionally supported databases, and data archives. However, these data sharing methodologies can still suffer from significant barriers. Federated approaches can augment these approaches and mitigate some of these barriers by enabling access or more sophisticated, shareable and scaled up analyses of large-scale data which may not be shareable and can easily be scaled up with the number of sites. In the current study, we examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). Briefly, COINSTAC (https://coinstac.trendscenter.org) is an open-source decentralized analysis application that provides a venue for analyses of neuroimaging datasets without sharing individual level data, while maintaining granular control of privacy. Through federated analysis, we examined T1-weighted images (N = 3,287) from eight psychiatric diagnostic groups across seven sites. We identified significant overlap in the GM patterns of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions, specifically the bilateral insula, that may indicate a possible shared vulnerability to psychiatric disorders.

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Section: Discussionsupporting

confidence: 92%

Cortical Similarities in Psychiatric and Mood Disorders Identified in Federated VBM Analysis via COINSTAC

Rootes-Murdy,

Panta,

Kelly

et al. 2023

Preprint

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“…These findings are consistent with the literature in patients with schizophrenia (Kong et al, 2014), specifically the decreased GMD in the left middle temporal cortex (Brosch et al, 2022;Kong et al, 2014). The anterior cingulate finding is of particular interest.…”

Section: Structural Findingssupporting

confidence: 92%

Sex differences and symptom based gray and white matter densities in schizophrenia

Marïë¹

2022

Cortica

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We investigated the association between densities in gray matter (GMD) and white matter (WMD) phenotypes and positive (PS) and negative (NS) symptoms in 40 schizophrenia patients (SZ). Cerebral densities were compared with 41 normal controls (NC) matched for age and sex using voxel-based morphometry on T1-3T-MRI. We found decreased GMD in the anterior cingulate-temporal gyri and increased GMD in the posterior cingulate gyrus in SZ relative to NC. WMD reduction was found in the inferior frontal and posterior parietal regions in SZ relative to NC. GMD in the insula/caudate correlated with PS, while GMD in the middle frontal gyrus and cerebellum correlated with NS. WMD in the middle frontal and superior frontal regions correlated with PS and NS respectively. Invers correlations were found between GMD in the parietal lobe and the uvula with PS. An inverse correlation was found between GMD in the cerebellum and NS. Inverse correlation was also found in the WMD of the occipital region and superior frontal regions with PS and NS respectively. Comparison between male groups revealed decreased total GMD in male patients, while no differences were observed between female groups. These correlational findings suggest that symptom profiles in schizophrenia show unique GM/WM phenotypes.

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“…Insulin resistance is a risk factor for dementia [ 7 ], cognitive deterioration later in life in those with type 2 diabetes mellitus (T2DM), and mood disorder, such as depression [ 8 , 9 ] as well as cognitive dysfunction in youth [ 10 ]. Reductions in left hippocampal grey matter volume have also been found to be common to MDD, BD, and SZ [ 11 ], showcasing the close neural interaction shared by these conditions. Therefore, new interventional approaches of metabolic psychiatry prevention and treatment targets must be further studied and may have the potential to yield universal improvements in psychiatric conditions through neuronal access to metabolic changes with nutritional ketones [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Reductions in left hippocampal grey matter volume have also been found to be common to MDD, BD, and SZ [ 11 ], showcasing the close neural interaction shared by these conditions. Therefore, new interventional approaches of metabolic psychiatry prevention and treatment targets must be further studied and may have the potential to yield universal improvements in psychiatric conditions through neuronal access to metabolic changes with nutritional ketones [ 11 ]. We review the current body of evidence for the effects of Ketogenic Diets (KD) on neuronal networks.…”

Section: Introductionmentioning

confidence: 99%

The Role of Ketogenic Metabolic Therapy on the Brain in Serious Mental Illness: A Review

Dalai

Ford

2022

J Psychiatry Brain Sci

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In search of interventions targeting brain dysfunction and underlying cognitive impairment in schizophrenia, we look at the brain and beyond to the potential role of dysfunctional systemic metabolism on neural network instability and insulin resistance in serious mental illness. We note that disrupted insulin and cerebral glucose metabolism are seen even in medication-naïve first-episode schizophrenia, suggesting that people with schizophrenia are at risk for Type 2 diabetes and cardiovascular disease, resulting in a shortened life span. Although glucose is the brain’s default fuel, ketones are a more efficient fuel for the brain. We highlight evidence that a ketogenic diet can improve both the metabolic and neural stability profiles. Specifically, a ketogenic diet improves mitochondrial metabolism, neurotransmitter function, oxidative stress/inflammation, while also increasing neural network stability and cognitive function. To reverse the neurodegenerative process, increasing the brain’s access to ketone bodies may be needed. We describe evidence that metabolic, neuroprotective, and neurochemical benefits of a ketogenic diet potentially provide symptomatic relief to people with schizophrenia while also improving their cardiovascular or metabolic health. We review evidence for KD side effects and note that although high in fat it improves various cardiovascular and metabolic risk markers in overweight/obese individuals. We conclude by calling for controlled clinical trials to confirm or refute the findings from anecdotal and case reports to address the potential beneficial effects of the ketogenic diet in people with serious mental illness.

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Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders

Cited by 43 publications

References 84 publications

Cortical Similarities in Psychiatric and Mood Disorders Identified in Federated VBM Analysis via COINSTAC

Cortical Similarities in Psychiatric and Mood Disorders Identified in Federated VBM Analysis via COINSTAC

Sex differences and symptom based gray and white matter densities in schizophrenia

The Role of Ketogenic Metabolic Therapy on the Brain in Serious Mental Illness: A Review

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