Trial Report Exploring the role of galectin-9 and artemin as biomarkers in long COVID with [CFS]: links to inflammation and cognitive function, 2024, Elahi et al

[Dolphin]

See post #5 for published version

https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1443363/abstract

Front. Immunol.
Sec. Viral Immunology
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1443363
This article is part of the Research TopicImmunological consequences of viral infection on brain homeostasis and cognitive impairmentView all articles
Discriminatory biomarkers Galectin-9 and Artemin in Long COVID with chronic fatigue syndrome: Correlation with inflammatory and cognitive markers
Provisionally accepted
Shokrollah Elahi *

Maryam Rezaeifar Mohammed Osman

Shima Shahbaz

• University of Alberta, Edmonton, Canada

This study aimed to assess plasma galectin-9 (Gal-9) and artemin (ARTN) concentrations as potential biomarkers to differentiate individuals with Long COVID (LC) patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) from SARS-CoV-2 recovered (R) and healthy controls (HCs).

Receiver operating characteristic (ROC) curve analysis determined a cutoff value of plasma Gal-9 and ARTN to differentiate LC patients from the R group and HCs in two independent cohorts.

Positive correlations were observed between elevated plasma Gal-9 levels and inflammatory markers (e.g. SAA and IP-10), as well as sCD14 and I-FABP in LC patients.

Gal-9 also exhibited a positive correlation with cognitive failure scores, suggesting its potential role in cognitive impairment in LC patients with ME/CFS.

This study highlights plasma Gal-9 and/or ARTN as sensitive screening biomarkers for discriminating LC patients from controls.

Notably, the elevation of LPS-binding protein in LC patients, as has been observed in HIV infected individuals, suggests microbial translocation.

However, despite elevated Gal-9, we found a significant decline in ARTN levels in the plasma of people living with HIV (PLWH).Our study provides a novel and important role for Gal-9/ARTN in LC pathogenesis.

Keywords: Long Covid, chronic fatigue syndrome, galectin-9, artemin, microbial translocation, HIV

Received: 03 Jun 2024; Accepted: 03 Sep 2024.

https://twitter.com/user/status/1831659088356291063

 

[SNT Gatchaman]

Their previous work at Diverse immunological dysregulation, chronic inflammation, and impaired erythropoiesis in long COVID patients with chronic fatigue syndrome (2024, Journal of Autoimmunity)

 

[Andy]

Full paper available from https://www.sciencedirect.com/science/article/pii/S089684112400101X

"Our ME/CFS patients were selected from a pool of over 2000 patients exhibiting LC symptoms. Through a comprehensive evaluation process that involved clinical assessments, laboratory tests, and the administration of well-defined questionnaires. Specifically, we utilized the de Paul Symptom Questionnaire (PSQ) to identify which patients fulfilled the criteria of ME/CFS; then used the FACIT Fatigue (Version 4) and multidimensional fatigue inventory to identify the severity of fatigue as outlined in the Canadian Consensus criteria (CDC) for ME/CFS and WHO [15,16] as we have previously described [17,18]."

 

[Lindberg]

I find this paper interesting, but wondering if anyone with more knowledge and research experience has any thoughts on it?

 

[SNT Gatchaman]

Now published as —

Exploring the role of galectin-9 and artemin as biomarkers in long COVID with chronic fatigue syndrome: links to inflammation and cognitive function
Elahi, Shokrollah; Rezaeifar, Maryam; Osman, Mohammed; Shahbaz, Shima

This study aimed to assess plasma galectin-9 (Gal-9) and artemin (ARTN) concentrations as potential biomarkers to differentiate individuals with Long COVID (LC) patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) from SARS-CoV-2 recovered (R) and healthy controls (HCs).

Receiver operating characteristic (ROC) curve analysis determined a cut-off value of plasma Gal-9 and ARTN to differentiate LC patients from the R group and HCs in two independent cohorts. Positive correlations were observed between elevated plasma Gal-9 levels and inflammatory markers (e.g. SAA and IP-10), as well as sCD14 and I-FABP in LC patients. Gal-9 also exhibited a positive correlation with cognitive failure scores, suggesting its potential role in cognitive impairment in LC patients with ME/CFS.

This study highlights plasma Gal-9 and/or ARTN as sensitive screening biomarkers for discriminating LC patients from controls. Notably, the elevation of LPS-binding protein in LC patients, as has been observed in HIV infected individuals, suggests microbial translocation. However, despite elevated Gal-9, we found a significant decline in ARTN levels in the plasma of people living with HIV (PLWH). Our study provides a novel and important role for Gal-9/ARTN in LC pathogenesis.


Link | PDF (Frontiers in Immunology) [Open Access]

 

[Hutan]

Galectin-9 (Gal-9) is a β-galactosidase binding lectin with diverse immunomodulatory properties (19). It is widely abundant in immune and non-immune cells and binds to different receptors, such as TIM-3, PD-1, PDI, IgE, CD44, CD45, and CD3 among others (20–24). The concentration of soluble Gal-9 is reported to be elevated in the plasma, saliva, and synovial fluids in HIV and other inflammatory conditions (25–27). Gal-9, as a DAMP, has been reported to play a predominant role in cytokine release storm in the acute SARS-CoV-2 infection (28). Most recently, we reported elevated levels of Gal-9 in the plasma of LC patients with ME/CFS (29). In particular, our findings supported a positive correlation between the plasma Gal-9 levels with CRP, MIP-1β, IL-10, and VCAM-1 in these patients (29). Of note, persistent gastrointestinal (GI) symptoms are reported in acute phase of COVID-19 disease and LC patients (30, 31). This may, in part, suggest the presence of compromised GI mucosal integrity in LC patients. Thus, plasma soluble CD14 (sCD14) and intestinal fatty acid binding protein (I-FABP) are considered reliable biomarkers for assessing GI permeability and epithelial integrity (32, 33). However, the association of these biomarkers with Gal-9 has not been documented in LC. Moreover, elevated Gal-9 expression across brain tissues is reported to be associated with neuropathology and cognitive impairment in HIV-infected individuals (34).

Additionally, we have reported the elevation of artemin (ARTN), a neurotrophic factor, in the plasma of LC patients with ME/CFS (29). ARTN interacts with its receptor GFRα3 and its co-receptor RET affecting cell growth and differentiation (35). Notably, the role of ARTN in neuropathic pain has been the subject of debate (35, 36). We previously reported that systemic ARTN levels were positively correlated with the cognitive impairment and pain scores in LC patients (29). Therefore, in the current study, we decided to determine whether plasma Gal-9 levels have any association with cognitive impairment scores in LC patients with ME/CFS, as reported in people living with HIV (PLWH) (34, 37). Given that compromised gut integrity and microbial translocation are contributing factors to chronic inflammation commonly observed in PLWH (32, 38), due to this similarity, we decided to examine whether this is the case in LC patients by measuring LPS-binding protein (LPS-BP). Finally, considering the association of plasma ARTN levels with cognitive impairment scores in LC patients with ME/CFS (29) and reported HIV-associated neurocognitive disorder (34), we quantified this neurotrophic factor in the plasma of PLWH and compared them with values of the other groups.

Interesting things to look at

 

[Hutan]

LC cohort
The first cohort (discovery) comprised 44 LC patients (median age 51.5±13.1, 11 males and 33 females) and 24 SARS-CoV-2 infected individuals who had recovered (R) from the disease without any obvious symptoms and complications (median age 50.5 ± 13.3, 6 males and 18 females). All were infected with the original Wuhan SARS-CoV-2 strain. All study subjects were recruited approximately 12 months (371±19 days LC vs. 368±6.2 days R) after the onset of SARS-CoV-2 infection as reported elsewhere (29). We utilized a set of well-defined validated clinical questionnaires developed by CDC and WHO (40, 41) for the diagnostic of LC patients with ME/CFS. To determine the applicability of our findings to another cohort, we established a validating cohort. The validating cohort consisted of 34 LC patients (median age 48 ± 9.8, 9 males and 25 females) and 34 recovered individuals (median age 45 ± 11.39, 10 males and 24 females) from SARS-CoV-2 infection without any symptoms. The infection was confirmed by PCR in both cohorts. This validating cohort was infected mainly with the Delta/or Omicron variants. Similar to the discovery cohort, they were recruited approximately 12 months (435±89 days LC vs. 415±40 days R) after the onset of acute disease, as reported elsewhere (29).

Study participants were age-and sex-matched, and considering that the majority of our patients had a mild acute infection, confounding health conditions were not common. All study subjects (LC and R) in the first cohort were SAS-CoV-2 vaccine-naïve but 67.3% of LC and 73.5% of R were vaccinated in the validating cohort. All of our LC patients in both cohorts met the criteria for categories I, II, III, IV, V, and VI associated with ME/CFS as we previously reported (29). Those LC patients who did not meet the criteria established by CDC and WHO (40, 41) were excluded from the study. Considering that a subset of PLWH presents cognitive impairments, we decided to compare our findings with a cohort of PLWH.

I think there are questions about the definitions used to identify the LC patients with ME/CFS. For example, reference #40 reported the following and its abstract did not mention PEM

Employing these higher frequency/severity requirements, the CART algorithm identified three symptoms that accurately classified 95.4% of participants as patient or control: fatigue/extreme tiredness, inability to focus on multiple things simultaneously, and experiencing a dead/heavy feeling after starting to exercise.

They report
Discovery cohort was 44 LC patients and 24 Recovered
Validating cohort was 34 LC patients and 34 Recovered

They say the study participants were age and sex matched. They report that all of the LC patients in their study met their ME/CFS requirements; people who did not meet the ME/CFS requirements were not included in the cohorts. So, the 'LC' label here is actually applied to people who have had LC for at least 12 months and who meet their ME/CFS criteria. The 'Recovered' label is applied to people who have been recovered for at least 12 months.

The study size is adequate, especially with the validating cohort. So, some questions around the ME/CFS definition, but it's looking not too bad.

They also had 63 people with HIV on anti-retroviral therapy and 25 healthy controls.

 

[Hutan]

GAL-9 levels


A

The ROC curve point with the best sensitivity/specificity indicated that a plasma Gal-9 level greater that 1725 pg/ml separates LC from HCs with 97% sensitivity and 100% specificity

so, first they identified a value of Gal-9 that separated the LC-ME/CFS Discovery cohort from the healthy controls (1725 pg/ml). The 97% sensitivity means that nearly every individual with their LC-ME/CFS label was identified by this cutoff. The 100% specificity means that every individual with the HC label was identified as negative.

B They then compared the LC-ME/CFS Discovery cohort people's levels of Gal-9 with the Recovered Discovery people. They had to use a higher cutoff point (2779 pg/ml) but the sensitivity was still not bad at 78.4% - most of the people with the LC-ME/CFS label were selected (and so had higher Gal-9 levels), while none of the Recovered people were (100% specificity).

C Encouragingly, things held up fairly well in the Validation cohort. A cut off point similar to the one used in A, identified 82% of the people with LC-ME/CFS and did not identify many of the Recovered people.

These observations suggest that the plasma Gal-9 is a sensitive screening biomarker for discriminating LC patients with ME/CFS from both R and HCs.

I'm not sure that we could expect a better result if Gal-9 actually turns out to be a marker of ME/CFS, given the uncertainty around diagnosis and the possibility that ME/CFS is a spectrum rather than a binary thing. By that last comment, I mean that it is possible that some of the Recovered people may actually have subclinical levels of whatever ME/CFS is - perhaps their lifestyle just accommodates a small amount of impairment.

It is helpful for the story holding together that higher levels of Gal-9 seem to be associated with conditions with perturbed immune systems.

 

[Hutan]

In addition to our previous findings of a positive correlation between plasma Gal-9 and CRP, VCAM-1, MIP-1β, and IL-10 (28, 44), we observed similar correlations between plasma Gal-9 and SAA and IP-10 levels in our discovery (Figures 1D, E) and validating LC cohorts, respectively (Figures 1F, G).

So, top row Discovery cohort; bottom row validating cohort.
SAA is serum amyloid A, charts on the left. IP-10 charts on the right.

R2 aren't amazing, but the relationships look quite convincing. But, look at the scales. What is going on there? In chart D, the LC discovery cohort has levels up to 40 million pg/mL, while all the values in F (the validating cohort) are below 100,000.

A paper on inflammatory rheumatic disease says:

In healthy individuals, SAA is present at the blood concentration below 3 mg/L. During the acute phase of the inflammatory response, SAA increases up to 1,000-fold in 24 h by stimulation of the pro-inflammatory cytokines. This effect is followed by a rapid decline which implies a remarkable feedback regulation (1).

3 mg/L
1 milligram/litre = 1 million picograms/millilitre
So, we would expect healthy people to have blood levels of less than 3 million picograms/millilitre. And so, in D, where the y axis has numbers involving 10's of millions, there does seem to be abnormal levels of SAA, although mostly less than a 10-fold increase. I don't know what is going on with chart F, I assume it's a presentation error.

 

[Hutan]

It's interesting that serum amyloid A was found to be associated with worse fatigue and joint pain in a small study of Gulf War Illness.

Analyses included 277 days with both blood draws and self-reports. Days with worse fatigue severity were associated with higher C-reactive protein and serum amyloid A, and lower eotaxin 1. Muscle pain and joint pain were associated with leptin, monocyte chemoattractant protein 1, and interferon γ–induced protein. Joint pain was further associated with serum amyloid A and eotaxin 3.

And it has been mentioned in relation to the microclots, I think the proponents of the microclot theory have found increased SAA in Long Covid.

 

[forestglip]

I think there are questions about the definitions used to identify the LC patients with ME/CFS. For example, reference #40 reported the following and its abstract did not mention PEM

All of our LC patients in both cohorts met the criteria for categories I, II, III, IV, V, and VI associated with ME/CFS as we previously reported (29)

I looked at their previous paper, 29.

All participants were evaluated for the presence of criteria related to ME/CFS based on the DSQ; namely: fatigue (I), post-exertional malaise (II), sleep difficulties (III), pain (IV), neurological/cognitive manifestations (V), and other (VI) which included autonomic, neuroendocrine, and immune manifestations using a 5-point Likert scale [...] Each patient was considered positive if they scored a high frequency of symptoms over the past 6 months and severity (based on the impact of the symptom on their quality of life) of ≥2 in each of the 6 categories. [...] All of our LC patients in both cohorts met the criteria for categories I, II, III, IV, and/or V, and VI [[19], [20], [21]]. Those LC patients who did not meet these criteria were excluded from the study.

So it seems every ME/CFS participant met category II, PEM, in both papers.

 

[Hutan]

So it seems every ME/CFS participant met category II, PEM, in both papers.

Super, thank you forestglip

 

[forestglip]

I love correlations with actual symptom metrics:

Our analyzes showed a positive correlation between Gal-9 levels and impaired cognitive function scores in both LC cohorts with ME/CFS (Figures 2F, G). However, we did not find any association between Gal-9 levels and other symptoms such as pain severity or widespread pain scores in LC patients (data not shown).

It's strange that they don't explain what exactly they mean by cognitive failure in this paper, but they do mention it in the context of their previous paper:

Furthermore, the positive correlation between Gal-9 with ARTN concentrations, previously associated with cognitive failure and pain symptoms (29),

Cognitive Failure Questionnaire (CFQ)

The CFQ contains 25 items and uses a 5-Likert scale (0 = never; 1 = very rarely; 2 = occasionally; 3 = quite often; 4 = very often) to evaluate the frequency with which people experience failures in different areas of cognition such as perception, memory, and motor function. Scores are from (the range 0–100) with a score ≥43 indicating cognitive failure.

The Cognitive Failures Questionnaire (CFQ) and its correlates, 1982, Broadbent et al.

This paper describes a questionnaire measure of self-reported failures in perception, memory, and motor function. Responses to all questions tend to be positively correlated, and the whole questionnaire correlates with other recent measures of self-reported deficit in memory, absent-mindedness, or slips of action. The questionnaire is however only weakly correlated with indices of social desirability set or of neuroticism. It is significantly correlated with ratings of the respondent by his or her spouse, and accordingly does have some external significance rather than purely private opinion of the self. The score is reasonably stable over long periods, to about the same extent as traditional measures of trait rather than state. Furthermore, it has not thus far been found to change in persons exposed to life-stresses. However, it does frequently correlate with the number of current psychiatric symptoms reported by the same person on the MHQ; and in one study it has been found that CFQ predicts subsequent MHQ in persons who work at a stressful job in the interval. It does not do so in those who work in a less stressful environment. The most plausible view is that cognitive failure makes a person vulnerable to showing bad effects of stress, rather than itself resulting from stress.

 

[forestglip]

I asked Claude to come up with all the reasons it could think of that could explain the correlation between Gal-9 and cognitive failure:

Certainly. There are several potential explanations for the observed correlation between cognitive failure scores and galectin-9 (Gal-9) levels in Long COVID patients with ME/CFS. Let's explore various possibilities, including biological, psychological, and social factors:

1. Direct neuroinflammatory effect: The primary explanation suggested by the authors is that elevated Gal-9 contributes to neuroinflammation, either directly or indirectly, leading to cognitive impairment. This could be due to Gal-9's role in activating microglia and astrocytes, promoting cytokine production in the central nervous system.

2. Blood-brain barrier disruption: Elevated Gal-9 might contribute to increased blood-brain barrier permeability, allowing inflammatory mediators to enter the CNS and cause cognitive disturbances.

3. Reverse causality: It's possible that cognitive impairment leads to increased stress and inflammation, which in turn elevates Gal-9 levels. The correlation might be present, but the causality could be reversed.

4. Common underlying factor: Both cognitive impairment and elevated Gal-9 could be consequences of a shared underlying pathology, such as persistent viral presence or autoimmune processes, without a direct causal relationship between them.

5. Metabolic dysregulation: Gal-9 elevation might be a marker of broader metabolic disturbances that affect both peripheral inflammation and cognitive function, rather than a direct cause of cognitive issues.

6. Psychological stress and inflammation: Cognitive difficulties could lead to increased psychological stress, which in turn promotes inflammation and elevates Gal-9. This would fit into a biopsychosocial model where cognitive symptoms, stress, and inflammation form a self-reinforcing cycle.

7. Sleep disturbances: Poor sleep quality, common in Long COVID and ME/CFS, could contribute to both cognitive impairment and elevated inflammatory markers like Gal-9. The correlation might reflect this shared relationship with sleep disruption.

8. Gut-brain axis dysfunction: Elevated Gal-9 might be a marker of intestinal permeability and microbial translocation, which could affect cognitive function through the gut-brain axis, rather than through direct effects of Gal-9 on the brain.

9. Hormonal influences: Endocrine disruptions in Long COVID could potentially influence both cognitive function and Gal-9 levels, creating an apparent correlation without direct causation.

10. Medication effects: If patients with more severe cognitive symptoms are more likely to be on certain medications, these drugs could potentially influence Gal-9 levels, creating a spurious correlation.

11. Reporting bias: Patients with higher levels of inflammation might be more likely to report cognitive symptoms due to heightened body awareness or expectation of symptoms, rather than objective cognitive decline.

12. Social factors: Socioeconomic status or education level might influence both cognitive reserve (affecting cognitive failure scores) and overall health status (influencing inflammatory markers like Gal-9), creating an apparent correlation.

13. Viral persistence: If SARS-CoV-2 persists in certain tissues, it could potentially cause both elevated Gal-9 (as part of the immune response) and cognitive symptoms through direct or indirect effects on the nervous system.

14. Autoantibodies: The correlation could reflect the presence of autoantibodies that affect both cognitive function and trigger inflammatory responses involving Gal-9.

15. Vascular dysfunction: Gal-9 might be a marker of endothelial dysfunction, which could independently contribute to both systemic inflammation and cognitive impairment through effects on cerebral blood flow.

These explanations are not mutually exclusive, and the observed correlation likely results from a complex interplay of multiple factors. Further research would be needed to elucidate the precise mechanisms underlying this relationship.

The authors' suggested explanation:

The positive correlation with cognitive failure scores suggests that Gal-9 may contribute to cognitive impairment in individuals with LC. Whether this effect is indirect through the elevation of pro-inflammatory cytokines/chemokines or direct needs to be determined. It has been reported that Gal-9 acts as an astrocyte-microglia signaling molecule, enhancing cytokine production (e.g. IL-6 and TNF-α) (63). Moreover, elevated levels of plasma and cerebrospinal fluids (CSF) Gal-9 are correlated with cognitive impairments in PLWH [people living with HIV] (64), further supporting its potential role in cognitive deficits in other viral infections, such as LC.

64 doesn't seem like the right citation for the HIV claim. I think it's 37:

Irrespective of HIV status, higher Gal-9 levels correlated with lower cognitive test scores in multiple domains [verbal learning, visuospatial learning, memory, motor skills (all P < 0.05)]. [...]

Plasma Gal-9 levels exhibited modest inverse correlations with performances in the domains of learning (HVLT-R learning total, r = −0.31; P = 0.0163; BVMT-R total, r = −0.26; P = 0.0439), psychomotor speed (Digit Symbol, r = −0.31; P = 0.0176) and visuospatial (Block Design, r = −0.30; P = 0.0225) (Fig. 2a). These associations were not significant when Gal-9 levels and cognitive performances were examined among AWH [adolescents with perinatally acquired HIV] (data not shown).

And 34, but I can't access the full text:

Here, we quantified Galectin-9 (Gal-9), a pleiotropic immunomodulatory protein, in post-mortem brain tissue across multiple regions from HIV-infected and HIV-uninfected donors to determine causal associations with HIV brain injury. We demonstrate that the staining intensity, total staining area, and cell-associated frequency of Gal-9 were elevated, principally in the frontal lobe and basal ganglia. Higher frontal lobe Gal-9 levels correlated with lower pre-mortem neuropsychological performance test scores in areas of attention and motor skills. Our results suggest that Gal-9 activity across the brain plays a role in neuroHIV pathogenesis and constitutes a promising disease-modifying target.

 

[Hutan]

This is from a Canadian team, specifically from Edmonton.
I've sent them an invitation to join us here, and a query about the y axis scale in Figure 1F.

 

[forestglip]

In reference 34, the two largest Gal-9 - cognitive correlations in HIV were with HVLT-R and digit symbol tests.

HVLT-R

The Hopkins Verbal Learning Test – Revised (HVLT-R) is the most recent (2001) version of the verbal learning and memory test. The current HVLT-R offers six alternate forms. Each form contains 12 nouns, four words each from one of three semantic categories (e.g., precious gems, articles of clothing, vegetables, etc.), to be learned over the course of three learning trials. Approximately 20–25 min later, a delayed recall trial and a recognition trial are completed. The delayed recall requires free recall of any words remembered. The recognition trial is composed of 24 words, including the 12 target words and 12 false-positives, 6 semantically related, and 6 semantically unrelated.

Digit symbol

Digit symbol substitution test (DSST) is a neuropsychological test sensitive to brain damage, dementia, age and depression. The test is not sensitive to the location of brain-damage (except for damage comprising part of the visual field).[1] It consists of (e.g. nine) digit-symbol pairs (e.g. 1/-, 2/┴, ... 7/Λ, 8/X, 9/=) followed by a list of digits.[2][3][4] Under each digit the subject should write down the corresponding symbol as fast as possible. The number of correct symbols within the allowed time (e.g. 90 or 120 sec) is measured.

 

[Lindberg]

I tried to take the DSST test that @forestglip posted above. During the course of the test it took a longer time to react and draw the symbols, but certain symbols were more difficult than others. For instance number six. It’s like my mind freezes. It knows what to do, but it can’t decide on which way to go so it just freezes. I get trouble moving my eyes and my hand and it takes an unusually high amount of effort to get them moving again. All in all these two rows of numbers and symbols took me three minutes to complete. Anyone else having the same kind of trouble?

 

[Peter T]

I tried to take the DSST test that @forestglip posted above. During the course of the test it took a longer time to react and draw the symbols, but certain symbols were more difficult than others. For instance number six. It’s like my mind freezes. It knows what to do, but it can’t decide on which way to go so it just freezes. I get trouble moving my eyes and my hand and it takes an unusually high amount of effort to get them moving again. All in all these two rows of numbers and symbols took me three minutes to complete. Anyone else having the same kind of trouble?

I just tried it using my finger to out line the shapes. For about five I thought this is easy, then froze having forgotten what I was meant to do. Mentally stopping and starting again worked until after the next five when I froze again.

This is interesting and I wonder if it might be happening in other cognitive tasks. For example writing comments here I regularly have to stop recollect what I am trying to say and start again, which could be why my grammar falls apart when after a stop I recollect the intent of my post but not the specific language I had planned.

 

[Lindberg]

For about five I thought this is easy, then froze having forgotten what I was meant to do. Mentally stopping and starting again worked until after the next five when I froze again.

Interesting! I found the symbols number 5 and 6 to be the most difficult ones, that’s when my mind froze. But you are right in that it might be the repetition in itself (after approximately five tasks) that the mind freezes. Perhaps also a combination of repetition “tiredness” and the type of symbol (cognitive task). I’ve noticed before that I can do certain types of cognitive tasks easily, like finding a linear pattern. But, whenever I have to choose between two directions my mind freezes and it’s very difficult to force it to act.

 

[Peter T]

Interesting! I found the symbols number 5 and 6 to be the most difficult ones, that’s when my mind froze. But you are right in that it might be the repetition in itself (after approximately five tasks that the mind freezes). Perhaps also a combination of repetition “tiredness” and the type of symbol (cognitive task). I’ve noticed before that I can do certain types of cognitive tasks easily, like finding a linear pattern. But, whenever I have to choose between two directions my mind freezes and it’s very difficult to force it to act.

This is probably a tenuous link, but I can experience what I term ‘jamais vu’ particularly when in PEM. It used to happen more frequently when I was still working and had a daily commute, when I would suddenly have no idea where I was on a road I knew well and would have to wait until cognitive mapping kicked back in. When my ME is at its worst it can even happen in the house, but as there are only a few doors on the landing I can bypass the problem by looking through each til I find the bathroom or my bedroom.