Trial Report Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition, 2024, Dacosta-Aguayo

[Dolphin]

https://www.ajnr.org/content/early/2024/04/04/ajnr.A8167.abstract

Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition: Insights from a Long-Term Follow-up

Rosalia Dacosta-Aguayo, Josep Puig, Noemi Lamonja-Vicente, Meritxell Carmona-Cervelló, Brenda Biaani León-Gómez, Gemma Monté-Rubio, Victor M. López-Linfante, Valeria Zamora-Putin, Pilar Montero-Alia, Carla Chacon, Jofre Bielsa, Eduard Moreno-Gabriel, Rosa Garcia-Sierra, Alba Pachón, Anna Costa, Maria Mataró, Julia G. Prado, Eva Martinez-Cáceres, Lourdes Mateu, Marta Massanella, Concepción Violán, Pere Torán-Monserrat and for the Aliança ProHEpiC-19 Cognitiu (The APC Collaborative Group)

American Journal of Neuroradiology April 2024, DOI: https://doi.org/10.3174/ajnr.A8167

Abstract
BACKGROUND AND PURPOSE: There is a paucity of data on long-term neuroimaging findings from individuals who have developed the post-coronavirus 2019 (COVID-19) condition. Only 2 studies have investigated the correlations between cognitive assessment results and structural MR imaging in this population. This study aimed to elucidate the long-term cognitive outcomes of participants with the post-COVID-19 condition and to correlate these cognitive findings with structural MR imaging data in the post-COVID-19 condition.

MATERIALS AND METHODS: A cohort of 53 participants with the post-COVID-19 condition underwent 3T brain MR imaging with T1 and FLAIR sequences obtained a median of 1.8 years after Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection. A comprehensive neuropsychological battery was used to assess several cognitive domains in the same individuals. Correlations between cognitive domains and whole-brain voxel-based morphometry were performed. Different ROIs from FreeSurfer were used to perform the same correlations with other neuroimaging features.

RESULTS: According to the Frascati criteria, more than one-half of the participants had deficits in the attentional (55%, n = 29) and executive (59%, n = 31) domains, while 40% (n = 21) had impairment in the memory domain. Only 1 participant (1.89%) showed problems in the visuospatial and visuoconstructive domains. We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain.

CONCLUSIONS: Our findings suggest that cognitive impairment in individuals with the post-COVID-19 condition is associated with long-term alterations in the structure of the brain. These macrostructural changes may provide insight into the nature of cognitive symptoms.

https://twitter.com/user/status/1776769154692862344

 

[Hutan]

There's a paywall.

I'm interested to know something about the characteristics of the participants - were they hospitalised during the acute Covid-19 infection? How old are they?

Interesting that they found cognitive impairment.

Frascati criteria? Seems to be an HIV thing:
HIV-associated neurocognitive disorders: Epidemiology, clinical manifestations, and diagnosis

The presence of neurocognitive deficits in certain individuals with HIV, without alternative explanation other than HIV infection, has long been recognized. However, the terminology to refer to this phenomenon has undergone substantial evolution since its initial characterization. In order to assist in diagnosis and categorization for research and clinical purposes, a working group supported by the United States National Institutes of Health published a classification scheme in 2007 that was initially proposed by the HIV Neurobehavioral Research Center at the University of California, San Diego [3]. This classification, often referred to as the "Frascati criteria," has been widely, but not universally, adopted [4,5]. It includes three levels of impaired neuropsychological test performance and functional impairment within an umbrella term, HIV-associated neurocognitive disorders (HAND):

We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain.

I'm always a bit skeptical about these findings of structural brain differences. The p values for both regions of observed reduced cortical thickness aren't really that flash, especially considering they presumably looked at lots of regions that they haven't reported about. I'm also not sure what data they compared this data to, to come up with the difference.

 

[Hutan]

We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain.

I understood that wrong, but I think it's worse. They don't know if the cortical thickness in the two regions noted are actually any less thick than those of people who don't have post-Covid condition. What they are saying is that there is a significant correlation between thickness of each region and memory performance.

That is rather underwhelming, first because the p-values aren't great, but also because they not only had a range of brain regions to check, but also had three cognitive domains - attentional, executive and memory domains. I'd bet that if they looked at the performance of 48 healthy people in each of those three domains and measured the cortical thickness in a whole lot of brain regions, they would probably find one statistically significant relationship between a domain and a cortical thickness.

 

[SNT Gatchaman]

I'm interested to know something about the characteristics of the participants - were they hospitalised during the acute Covid-19 infection? How old are they?

The study includes participants who have persistent symptoms after recovering from COVID-19 with and without cognitive symptoms, as well as participants who were infected but did not develop the PCC and uninfected paricipants. In this report, we present the structural MR imaging data of a subsample that underwent brain imaging and cognitive assessment as part of the study.

This cross-sectional study involved 53 participants who had the PCC with cognitive symptoms after recovering from COVID-19. They were recruited from primary health centers and hospitals in Northern Barcelona (Spain) between August 1, 2020, and March 2023. The study followed the WHO criteria for confirming the PCC diagnosis. 4 The participants also had to be at least 12 weeks postinfection and between 20 and 70 years of age. The study excluded those with pre-existing psychiatric, neurologic, or neurodevelopmental disorders that could cause cognitive deficits, those with a history of drug or alcohol abuse or a life expectancy of ,6 months, and those who could not undergo MR imaging due to medical contraindication or claustrophobia.

The results of the demographic and clinical characteristics are summarized in the Online Supplemental Data. The sample consisted of 53 individuals mainly with a history of mild COVID-19 infection, with a mean age of 48.23 (SD, 9.2) years and a mean education level of 14.04 (SD, 2.6) years. Most participants were women (88.7%) and had a mild-moderate clinical spectrum of COVID-19 (81.1%). Only 17% of the participants required hospitalization in the acute phase due to COVID-19. The most common vascular risk factors of the sample were smoking (current or former, 44.2%) and alcohol consumption (40.4%). According to the WHO standards, 34% of the participants were overweight (BMI ¼ 25–29.9), 13.2% were obese (BMI 30–34.9), and 13.2% were extremely obese (BMI $35). The mean time since the diagnosis of COVID-19 was 1.8 years.

 

[SNT Gatchaman]

We think that the gray and white matter voxel-based morphometry is hampered by the lack of an uninfected SARS-COV-2 or recovered COVID-19 matched control group, as well as the small sample size.

In addition, we are confident that there must be functional alterations in the brain, because these usually occur before a structural region is affected and account for structural changes. 59

(59) is Brain structural alterations are distributed following functional, anatomic and genetic connectivity (2018, Brain, open-access).

That seemed like an odd sentence and initially I wondered if they meant "we are confident that there must be functional alterations in the brain, because these usually occur before a structural region is [visibly] affected and account for [those functional] changes". But no. While this is not discussing FND as far as I can see (although who knows how FND mechanisms will ultimately turn out), the idea is that structural changes occur along/within functionally connected brain regions.

Thus far, at least four important mechanisms (not necessarily mutually exclusive) have been invoked to explain the spread of brain alterations: transneuronal spread, nodal stress, shared vulnerability, and trophic failure

The first mechanism is based on the involvement of certain toxic agents that propagate along neuronal connections. A growing body of evidence indicates that misfolded proteins may spread in a prion-like way along brain axonal fibres throughout a corruptive templating as a cascade phenomenon of misfolded protein propagation. Borrowed from prion diseases, this mechanism has been subsequently explored in neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis and tauopathies, and more recently has been tentatively generalized to other brain disorders. However, the application of the prion-like mechanism to neurodegenerative diseases is still an open field of research.

The second mechanism is based on the hypothesis that the most active brain regions (i.e. network hubs) may also be the most functionally stressed and, as a result, susceptible to be structurally altered. This phenomenon has been confirmed in humans by using in vivo neuroimaging techniques and voxel-based meta-analyses.

The third mechanism relies on the hypothesis that certain areas with shared gene or protein expressions may exhibit common vulnerability to neuropathology. This phenomenon could be partially mediated by the relationship between expression of genes and patterns of brain connectivity.

The fourth mechanism invokes a failure in the process of trophic factors production, which can lead to the pathological deterioration of neural wiring.

Our analysis points out that three (i.e. nodal stress, shared vulnerability, and transneuronal spread) of the four mechanisms put forward so far are likely to play a role with different temporal progressions in the formation and development of structural co-alterations. In particular, we found that functional connectivity offers the better account of the structural co-alteration patterns, followed by anatomic and genetic connectivity. Although one type of connectivity can be prevalent in the co-alteration patterns, it must be noted that all these three types are significantly involved in the progression of brain alterations. This is consistent with the cross-diagnostic nature of data used in this study.

 

[Jonathan Edwards]

What they are saying is that there is a significant correlation between thickness of each region and memory performance.

And we know that is true of any population!!
It would be weird if they hadn't found that.