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3 Two Dominant Post-COVID Subtypes in Patients Seeking Treatment for “Brain Fog” Through a Post-COVID Treatment Clinic
- Kristine Lokken, Jamie Hansel Robinson, Richard Kennedy, David E Vance, Ronald M Lazar, Roy C Martin, Melissa J Greenfield, Pariya F Wheeler, Adam Gerstenecker
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 876-877
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Objective:
To examine patterns of cognitive function among a clinical sample of patients seeking treatment for Post-Acute Sequelae of COVID-19 (PASC).
Participants and Methods:One hundred nineteen patients each completed a baseline neuropsychological evaluation, including clinical diagnostic interview, cognitive assessments, and a comprehensive battery of self-report questionnaires. Patients had a mean age of 50 years (range:18 to 74, SD=10.1) and a mean of 15.5 years (SD=2.54) of formal education. Patients were primarily female (74%) and of White/Caucasian race (75%). Hierarchical agglomerative clustering was used to partition the data into groups based on cognitive performance. Euclidean distance was used as the similarity measure for the continuous variables and within-cluster variance was minimized using Ward’s method. The optimal number of clusters was determined empirically by fitting models with 1 to 15 clusters, with the best number of clusters selected using the silhouette index. All analyses were conducted using the NbClust package, an R package for determining the relevant number of clusters in a data set.
Results:Clustering yielded two distinct clusters of cognitive performance. Group 1 (n=57) performed worse than Group 2 (n=62) on most cognitive variables (including a brief cognitive screener and tests of attention/working memory, executive function, processing speed, learning and delayed recall). Of note, there were no significant differences between groups on an infection severity scale, hospitalizations/ICU admissions, initial or current COVID-19 symptoms, or prior comorbidities. Groups did not differ in age or gender, but Group 1 had a lower education level than Group 2 (M=14.7, SD=2.45 vs. M=16.2, SD=2.42; p=.001). Group 1 also had significantly more minorities than Group 2 (40% vs. 8%; p<.001). No other demographic differences (income, living arrangement, or marital status) were observed. In comparison to Group 2 patients, Group 1 patients self-reported significantly higher levels of anxiety and depression and functional impairment (Functional Activities Questionnaire: M=11.3, SD=8.33 vs. M=7.65, SD=7.97), perceived stress (Perceived Stress Scale: M=24.7, SD=7.90 vs. M=20.3, SD=7.89), insomnia (Insomnia Severity Index: M=16.0, SD=6.50 vs. M=13.1, SD=6.76), and subjective cognitive functioning (Cognitive Failures Questionnaire: M=58.8, SD=16.9 vs. M=50.3, SD=18.6; p’s<.05).
Conclusions:Findings indicate two predominant subtypes of patients seeking treatment for PASC, with one group presenting as more cognitively impaired and reporting greater levels of anxiety, depression, insomnia, perceived stress, functional limitations, and subjective cognitive impairment. Future directions include follow-up assessments with these patients to determine cognitive trajectories over time and tailoring treatment adjuncts to address mood symptoms, insomnia, functional ability, and lifestyle variables. Understanding mechanisms of differences in cognitive and affective symptoms is needed in future work. Limitations to the study were that patients were referred for evaluation based on the complaint of “brain fog” and the sample was a homogenous, highly educated, younger group of individuals who experienced generally mild COVID-19 course.
30 Hippocampal Internal Architecture Subfield Volumes Associated with Systematic Inflammatory Biomarkers in Multiple Sclerosis
- Christopher Collette, Amani M. Norling, Randall A. Walden, Hyun Freeman, Terina Myers, Lawrence Ver Hoef, Khurram Bashir, Ronald M. Lazar, Adam Gerstencker
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 546-547
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Objective:
Multiple Sclerosis (MS) affects up to 500,000 adults in the United States, with cognitive impairment present in 45%-65% of people. Studies showed hippocampal atrophy in MS, but the underlying mechanisms remain unknown. Inflammation has been proposed to play a significant role, and associations between systemic inflammatory biomarkers and hippocampal atrophy have been shown in other neurological conditions. However, research exploring serum biomarker and volumetric associations in MS are lacking. Given that conventional imaging methods lack resolution for hippocampal internal architecture (HIA), new protocols were developed. We used the High-Resolution Multiple Image Co-Registration and Averaging (HR-MICRA) method to visualize the HIA subfields. We investigated the relationship between subfield volumes generated from HR-MICRA scans and systemic serum biomarkers in MS.
Participants and Methods:Patients with MS were recruited (N= 34, mean age= 54.6, 35.3% Black) underwent Magnetic Resonance Imaging (MRI), and serum biomarkers were obtained, specifically chosen for their potential role in MS. Inflammatory biomarkers included; granulocyte colony stimulating factor (G-CSF), interleukin-10 (IL-10), matrix metalloproteinase-9 (MMP-9), tumor necrosis factor- a (TNF- a), and growth factors; vascular endothelial growth factor (VEGF); insulin-like growth factor-1 (IGF-1), and brain derived growth factor (BDNF). Imaging was performed in a Siemens Prisma 3T scanner with a 64-channel head coil using the HR-MICRA method. Hippocampal subfields were calculated using the Automated Segmentation of Hippocampal Subfields (ASHS) package. We used the Magdeburg Young Adult 7T Atlas for sub-hippocampal structures and Penn Temporal Lobe Epilepsy T1-MRI Whole Hippocampus ASHS Atlas for general hippocampal structure and segmentation. Pearson's product-moment analyses provided correlations between biomarkers and hippocampal subfield volumes for each cerebral hemisphere. A statistical significance level of p < 0.05 was used for all analyses.
Results:Correlations emerged between left hemisphere Cornu Ammonis (CA) 2 and G-CSF (r = -.384; p = .025); IL-10 (r = -.342; p = .048); VEGF (r = -.371; p= .031); and CA3 with IL-10 (r = -.488, p = .003); G-CSF (r = -.386; p= .024); VEGF (r = -.352; p= .041). Dentate gyrus correlated with MMP-9 (r =.416; p=.014); IL-10 (r = -.365; p =.034). BDNF was correlated with right hemisphere CA1 (r = -.417, p = .014), CA2 (r = -.497; p= .003) and CA3 (r = -.451; p=.007).
Conclusions:In our sample of persons with MS, left hemisphere hippocampal subfield volumes were negatively correlated with inflammatory biomarkers, supporting previous reports linking inflammation to reduced brain volumes in other neurological conditions. In the right hemisphere, we found negative correlations between HIA and BDNF, suggesting a neuroprotective function for BDNF in this neurodegenerative disease. These findings in a representative sample of patients with MS highlight the need for further research exploring the relationship between HIA and systemic serum biomarkers in MS.
31 Finding the Link Between Inflammatory Biomarkers and Cognitive Functioning in People with Multiple Sclerosis
- Katherine Ward, Christopher Collette, Amani M. Norling, Hyun Freeman, Terina Myers, Khurram Bashir, Ronald M. Lazar, Ronald M. Lazar, Adam Gerstenecker
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 547
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Objective:
To investigate the relationship between systematic inflammatory biomarkers and cognition in patients with Multiple Sclerosis (MS).
Participants and Methods:We recruited 36 patients diagnosed with MS (31 with relapsing-remitting and 5 with progressive) who presented for treatment at the University of Alabama at Birmingham (UAB). Patients underwent a comprehensive neuropsychological battery, and serum blood samples were collected. Cognitive data was divided into an overall Cognitive Composite score and seven cognitive domains (i.e., Attention, Verbal Memory, Visual Memory, Visuospatial Ability, Language, Processing Speed, and Executive Function) using z-score averages. Pearson's product-moment correlations were conducted to determine the relationship between cognitive performance and 14 inflammatory biomarkers specifically chosen for their potential role in MS.
Results:Granulocyte Colony Stimulating Factor (G-CSF) was significantly correlated with Executive Function (r= -.355; p=.039) and Processing Speed (r= -.528; p= .001) scores. Additionally, Interleukin-10 (IL-10) was significantly correlated with Visual Memory (r= -.346; p= .041) scores. Finally, Tumor Necrosis Factor (TNF-a) was significantly correlated with Visual Memory (r= -.347; p= .041).
Conclusions:Studies investigating associations between inflammation and cognition in MS are lacking. In our sample of persons with Multiple Sclerosis, G-CSF biomarkers were negatively correlated with Executive Function as well as Processing Speed. In addition, IL-10 and TNF-a biomarkers were negatively correlated with Visual Memory scores. These findings in a representative sample of patients with MS highlight the need for further research exploring the relationship between systematic inflammatory biomarkers and cognition in MS.