Fen Bao

Ms. Fen Bao

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 August 2017 in Brain Sciences
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Evanthia BernitsasEvanthia Bernitsas
Evanthia Bernitsas
KYKalyan Yarraguntla
Kalyan Yarraguntla
FBFen Bao
Fen Bao
RSRishi Sood
Rishi Sood
CSCarla Santiago-Martinez
Carla Santiago-Martinez
NSNavid Seraji
Navid Seraji
Fatigue is a common and disabling symptom in Multiple Sclerosis (MS). However, consistent neuroimaging correlates of its severity are not fully elucidated. In this article, we study the neuronal correlates of fatigue severity in MS. Forty-three Relapsing Remitting MS (RRMS) patients with MS-related fatigue (Fatigue Severity Scale (FSS) range: 1–7) and Expanded Disability Status Scale (EDSS) ≤ 4, were divided into high fatigue (HF, FSS ≥ 5.1) and low fatigue groups (LF, FSS ≤ 3). We measured T2 lesion load using a semi-automated technique. Cortical thickness, volume of sub-cortical nuclei, and brainstem structures were measured using Freesurfer. Cortical Diffusion Tensor Imaging (DTI) parameters were extracted using a cross modality technique. A correlation analysis was performed between FSS, volumetric, and DTI indices across all patients. HF patients showed significantly lower volume of thalamus, (p = 0.02), pallidum (p = 0.01), and superior cerebellar peduncle ((SCP), p = 0.002). The inverse correlation between the FSS score and the above volumes was significant in the total study population. In the right temporal cortex (RTC), the Radial Diffusivity ((RD), p = 0.01) and Fractional Anisotropy ((FA), p = 0.01) was significantly higher and lower, respectively, in the HF group. After Bonferroni correction, thalamic volume, FA-RTC, and RD-RTC remained statistically significant. Multivariate regression analysis identified FA-RTC as the best predictor of fatigue severity. Our data suggest an association between fatigue severity and volumetric changes of thalamus, pallidum, and SCP. Early neuronal injury in the RTC is implicated in the pathogenesis of MS-related fatigue.

27 May 2019 in Brain Sciences
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KYKalyan Yarraguntla
Kalyan Yarraguntla
FBFen Bao
Fen Bao
SLSamuel Lichtman-Mikol
Samuel Lichtman-Mikol
SRSara Razmjou
Sara Razmjou
CSCarla Santiago-Martinez
Carla Santiago-Martinez
Evanthia BernitsasEvanthia Bernitsas
Evanthia Bernitsas
Few cross-sectional studies have investigated the correlation between neurochemical changes and multiple sclerosis (MS) fatigue, but little is known on the fatigue-related white matter differences between time points. We aim to investigate the longitudinal neurometabolite profile of white matter in MS fatigue. Forty-eight relapsing remitting multiple sclerosis (RRMS) patients with an expanded disability status scale (EDSS) ≤ 4 underwent high field 1H-multivoxel magnetic resonance spectroscopy (MRS) at baseline and year 1. Fatigue severity was evaluated by the fatigue severity scale (FSS). Patients were divided into low (LF, FSS ≤ 3), moderate (MF, FSS = 3.1–5), and high fatigue (HF, FSS ≥ 5.1) groups. In a two-way analysis of variance (ANOVA), we observed a decline in the ratio of the sum of N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) to the sum of creatine (Cr) and phosphocreatine (PCr) in the right anterior quadrant (RAQ) and left anterior quadrant (LAQ) of the MRS grid in the HF group at baseline and year 1. This decline was significant when compared with the LF group (p = 0.018 and 0.020). In a one-way ANOVA, the fatigue group effect was significant and the ratio difference in the right posterior quadrant (RPQ) and left posterior quadrant (LPQ) of the HF group was also significant (p = 0.012 and 0.04). Neurochemical changes in the bilateral frontal white matter and possibly parietooccipital areas were noted in the HF group at two different time points. Our findings may shed some light on the pathology of MS fatigue.

20 December 2023 in Brain Sciences
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MEMahmoud Elkhooly
Mahmoud Elkhooly
FBFen Bao
Fen Bao
Evanthia BernitsasEvanthia Bernitsas
Evanthia Bernitsas
Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system by causing inflammation, demyelination and neurodegeneration. Fatigue is the most prevalent and one of the most disabling symptoms among people with MS (pwMS). Due to its complexity and subjective character, fatigue is still little understood despite its frequent occurrence and severe impact. The potential causes, effects, and treatments of fatigue associated with MS have been extensively studied in recent years. Though the benefits of such a variety of contributions are obvious, there have not been many attempts to evaluate the effect of disease modifying therapies (DMTs) on MS-related fatigue. In this review, we summarize clinical trials and research studies, and we discuss the effect of different DMTs on MS-related fatigue.

29 June 2026 in Neurology International
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ANAnas Nourelden
Anas Nourelden
FBFen Bao
Fen Bao
ABAbigail Biddix
Abigail Biddix
NPNidhi M. Patel
Nidhi M. Patel
MAMawadda Abdelhai
Mawadda Abdelhai
AMAnza B. Memon
Anza B. Memon
Background/Objectives: Multiple sclerosis (MS) can cause neurodegeneration leading to accelerated brain atrophy. Brain-predicted age (BA) is an emerging neuroimaging biomarker for neurodegeneration but remains underexplored in MS. This study examines the pathophysiological substrates associated with the brain age gap in MS compared with healthy controls (HCs) through a combination of volumetric, spectroscopic, and diffusion imaging. Methods: This retrospective cross-sectional study included 33 HCs and 124 MS patients. Participants underwent 3T MRI including 3D-T1, MR spectroscopy, magnetization transfer, and diffusion imaging. BA and volumes were estimated from T1-weighted scans using brainageR. Metabolic integrity (total N-acetylaspartate to total creatine ratio, tNAA/tCr) and microstructural damage (magnetization transfer ratio [MTR], fractional anisotropy [FA]) were evaluated independently in normal-appearing tissues. Multivariate linear regression assessed MS diagnosis as an independent predictor of BA metrics, controlling for age, sex, and race. Results: MS patients showed significantly higher predicted brain age (53.3 vs. 31.8 years) and a markedly larger age gap (10.2 vs. −0.1 years) compared to HCs. Beyond macroscopic volume loss, accelerated aging paralleled profound subclinical degradation, including lower neuronal integrity (tNAA/tCr: 2.0 vs. 2.4) and widespread microstructural damage, evidenced by reduced MTR and FA across both normal-appearing gray and white matter. Linear regression confirmed MS diagnosis as an independent predictor of both BA and Age Gap (15.09 and 13.50 years) after adjusting for confounders. Conclusions: MS patients exhibit accelerated biological brain aging, characterized by a significant age gap and concurrent tissue volume loss. The brain age gap in MS extends beyond macroscopic atrophy, capturing underlying subclinical metabolic failure and widespread microstructural degradation in normal-appearing tissues. This positions BA as a robust, multi-dimensional proxy for neuroaxonal pathology.

5 August 2026 in Neuro-Ophthalmology
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Journal Article
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ANAnas Nourelden
Anas Nourelden
FBFen Bao
Fen Bao
PBPoonam Bansal
Poonam Bansal
AMAnza Memon
Anza Memon
Multiple sclerosis (MS) is a chronic immune-mediated demyelinating disease of the central nervous system characterized by acute and chronic inflammation and progressive neurodegeneration which toge...