Jack - amatica health
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This is just one example of research papers we can review to gain insights from in relation to RNA data.
You can test all your RNA (20,000 markers per person) and see how you compare to Herberg et al., findings below:
amaticahealth.com/me-cfs-long-...
You can test all your RNA (20,000 markers per person) and see how you compare to Herberg et al., findings below:
amaticahealth.com/me-cfs-long-...
September 22, 2025 at 4:29 PM
This is just one example of research papers we can review to gain insights from in relation to RNA data.
You can test all your RNA (20,000 markers per person) and see how you compare to Herberg et al., findings below:
amaticahealth.com/me-cfs-long-...
You can test all your RNA (20,000 markers per person) and see how you compare to Herberg et al., findings below:
amaticahealth.com/me-cfs-long-...
Full classification method comes from:
“Diagnostic Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children”
Herberg et al., JAMA, 2016 jamanetwork.com/journals/jam...
“Diagnostic Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children”
Herberg et al., JAMA, 2016 jamanetwork.com/journals/jam...
Distinguishing Bacterial vs Viral Infection in Febrile Children
This study describes the development and diagnostic accuracy of a host-response RNA signature for distinguishing bacterial from viral infection in febrile children younger than 5 years.
jamanetwork.com
September 22, 2025 at 4:29 PM
Full classification method comes from:
“Diagnostic Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children”
Herberg et al., JAMA, 2016 jamanetwork.com/journals/jam...
“Diagnostic Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children”
Herberg et al., JAMA, 2016 jamanetwork.com/journals/jam...
Important note:
These are preliminary. They rely on a simplified 2-gene model and only reference ranges from 3 control. More genes, controls, clinical data, and lab results will strengthen the interpretation.
Study tracked children with active fevers; relevance to adults without fever is unknown
These are preliminary. They rely on a simplified 2-gene model and only reference ranges from 3 control. More genes, controls, clinical data, and lab results will strengthen the interpretation.
Study tracked children with active fevers; relevance to adults without fever is unknown
September 22, 2025 at 4:29 PM
Important note:
These are preliminary. They rely on a simplified 2-gene model and only reference ranges from 3 control. More genes, controls, clinical data, and lab results will strengthen the interpretation.
Study tracked children with active fevers; relevance to adults without fever is unknown
These are preliminary. They rely on a simplified 2-gene model and only reference ranges from 3 control. More genes, controls, clinical data, and lab results will strengthen the interpretation.
Study tracked children with active fevers; relevance to adults without fever is unknown
This method doesn’t require identifying the pathogen itself.
It’s based on how the immune system responds.
It’s based on how the immune system responds.
September 22, 2025 at 4:29 PM
This method doesn’t require identifying the pathogen itself.
It’s based on how the immune system responds.
It’s based on how the immune system responds.
Summary:
C2 & C5 = viral
C3 & C4 = bacterial
C1 = unclear (possibly mild viral)
These groupings are based solely on gene expression patterns of IFI44L and FAM89A discussed in Herberg et al.
C2 & C5 = viral
C3 & C4 = bacterial
C1 = unclear (possibly mild viral)
These groupings are based solely on gene expression patterns of IFI44L and FAM89A discussed in Herberg et al.
September 22, 2025 at 4:29 PM
Summary:
C2 & C5 = viral
C3 & C4 = bacterial
C1 = unclear (possibly mild viral)
These groupings are based solely on gene expression patterns of IFI44L and FAM89A discussed in Herberg et al.
C2 & C5 = viral
C3 & C4 = bacterial
C1 = unclear (possibly mild viral)
These groupings are based solely on gene expression patterns of IFI44L and FAM89A discussed in Herberg et al.
Interestingly, the person in C5 had improvements from COVID Monoclonal Antibodies (mAbs), consistent with persistent viral load.
September 22, 2025 at 4:29 PM
Interestingly, the person in C5 had improvements from COVID Monoclonal Antibodies (mAbs), consistent with persistent viral load.
🟡 C5: Viral
C5 has very high IFI44L and only moderate FAM89A.
This produces a strongly “viral” signal.
The interferon-driven IFI44L is strongly induced here.
→ Fits the viral subset.
C5 has very high IFI44L and only moderate FAM89A.
This produces a strongly “viral” signal.
The interferon-driven IFI44L is strongly induced here.
→ Fits the viral subset.
September 22, 2025 at 4:29 PM
🟡 C5: Viral
C5 has very high IFI44L and only moderate FAM89A.
This produces a strongly “viral” signal.
The interferon-driven IFI44L is strongly induced here.
→ Fits the viral subset.
C5 has very high IFI44L and only moderate FAM89A.
This produces a strongly “viral” signal.
The interferon-driven IFI44L is strongly induced here.
→ Fits the viral subset.
🟢 C4: Bacterial
C4 also shows elevated FAM89A and minimal IFI44L.
Though less extreme than C3, the imbalance points toward a bacterial immune signature.
C4 also shows elevated FAM89A and minimal IFI44L.
Though less extreme than C3, the imbalance points toward a bacterial immune signature.
September 22, 2025 at 4:29 PM
🟢 C4: Bacterial
C4 also shows elevated FAM89A and minimal IFI44L.
Though less extreme than C3, the imbalance points toward a bacterial immune signature.
C4 also shows elevated FAM89A and minimal IFI44L.
Though less extreme than C3, the imbalance points toward a bacterial immune signature.
🟢 C3: Bacterial
C3 has high FAM89A and very low IFI44L.
This pattern matches the typical bacterial infection response.
C3 has high FAM89A and very low IFI44L.
This pattern matches the typical bacterial infection response.
September 22, 2025 at 4:29 PM
🟢 C3: Bacterial
C3 has high FAM89A and very low IFI44L.
This pattern matches the typical bacterial infection response.
C3 has high FAM89A and very low IFI44L.
This pattern matches the typical bacterial infection response.
🔵 C2: Viral
C2 shows elevated IFI44L with low FAM89A.
This matches the viral infection pattern seen in Herberg et al.’s work.
Fits into the viral infection group.
C2 shows elevated IFI44L with low FAM89A.
This matches the viral infection pattern seen in Herberg et al.’s work.
Fits into the viral infection group.
September 22, 2025 at 4:29 PM
🔵 C2: Viral
C2 shows elevated IFI44L with low FAM89A.
This matches the viral infection pattern seen in Herberg et al.’s work.
Fits into the viral infection group.
C2 shows elevated IFI44L with low FAM89A.
This matches the viral infection pattern seen in Herberg et al.’s work.
Fits into the viral infection group.
🟣 C1: Unclear (borderline viral)
C1 has modest expression of both genes. IFI44L is slightly higher than FAM89A.
→ Slight viral tilt, but not enough to say confidently.
Possibly an indeterminate or mild infection.
C1 has modest expression of both genes. IFI44L is slightly higher than FAM89A.
→ Slight viral tilt, but not enough to say confidently.
Possibly an indeterminate or mild infection.
September 22, 2025 at 4:29 PM
🟣 C1: Unclear (borderline viral)
C1 has modest expression of both genes. IFI44L is slightly higher than FAM89A.
→ Slight viral tilt, but not enough to say confidently.
Possibly an indeterminate or mild infection.
C1 has modest expression of both genes. IFI44L is slightly higher than FAM89A.
→ Slight viral tilt, but not enough to say confidently.
Possibly an indeterminate or mild infection.
The key idea is this:
- High IFI44L, low FAM89A → viral infection
- High FAM89A, low IFI44L → bacterial infection
We applied this rule to each preliminary cluster to infer possible infection type.
- High IFI44L, low FAM89A → viral infection
- High FAM89A, low IFI44L → bacterial infection
We applied this rule to each preliminary cluster to infer possible infection type.
September 22, 2025 at 4:29 PM
The key idea is this:
- High IFI44L, low FAM89A → viral infection
- High FAM89A, low IFI44L → bacterial infection
We applied this rule to each preliminary cluster to infer possible infection type.
- High IFI44L, low FAM89A → viral infection
- High FAM89A, low IFI44L → bacterial infection
We applied this rule to each preliminary cluster to infer possible infection type.
This classification uses a method from Herberg et al. (JAMA, 2016). They showed that expression levels of just two genes (RNA) can help separate viral from bacterial infections in children with fever.
The RNA are available to be tested here:
amaticahealth.com/me-cfs-long-...
The RNA are available to be tested here:
amaticahealth.com/me-cfs-long-...
amatica
20,000 results in one test - understand your disease while helping advance research
amaticahealth.com
September 22, 2025 at 4:29 PM
This classification uses a method from Herberg et al. (JAMA, 2016). They showed that expression levels of just two genes (RNA) can help separate viral from bacterial infections in children with fever.
The RNA are available to be tested here:
amaticahealth.com/me-cfs-long-...
The RNA are available to be tested here:
amaticahealth.com/me-cfs-long-...
All markers above can be tested through our full RNA seq panel - 20,000 results per participant:
amaticahealth.com/me-cfs-long-...
For Research Use Only - not for use in diagnostic procedures. Results are educational, not medical advice, and not validated to assess BBB function.
amaticahealth.com/me-cfs-long-...
For Research Use Only - not for use in diagnostic procedures. Results are educational, not medical advice, and not validated to assess BBB function.
September 20, 2025 at 2:11 PM
All markers above can be tested through our full RNA seq panel - 20,000 results per participant:
amaticahealth.com/me-cfs-long-...
For Research Use Only - not for use in diagnostic procedures. Results are educational, not medical advice, and not validated to assess BBB function.
amaticahealth.com/me-cfs-long-...
For Research Use Only - not for use in diagnostic procedures. Results are educational, not medical advice, and not validated to assess BBB function.
Here’s the key study on Long COVID, brain fog, and blood–brain barrier disruption using blood RNA profiling:
www.nature.com/articles/s41...
www.nature.com/articles/s41...
September 20, 2025 at 2:11 PM
Here’s the key study on Long COVID, brain fog, and blood–brain barrier disruption using blood RNA profiling:
www.nature.com/articles/s41...
www.nature.com/articles/s41...
A carefully chosen gene panel (like the one above) helps researchers focus on meaningful BBB signals - even when they’re low in abundance.
As more studies are done, this approach may help monitor or predict brain conditions from a simple blood test.
As more studies are done, this approach may help monitor or predict brain conditions from a simple blood test.
September 20, 2025 at 2:11 PM
A carefully chosen gene panel (like the one above) helps researchers focus on meaningful BBB signals - even when they’re low in abundance.
As more studies are done, this approach may help monitor or predict brain conditions from a simple blood test.
As more studies are done, this approach may help monitor or predict brain conditions from a simple blood test.
This suggests a systemic response - possibly due to vascular stress or early BBB damage in Alzheimer’s.
Even in chronic diseases, blood gene expression can reflect changes in brain vascular health and BBB stability.
Even in chronic diseases, blood gene expression can reflect changes in brain vascular health and BBB stability.
September 20, 2025 at 2:11 PM
This suggests a systemic response - possibly due to vascular stress or early BBB damage in Alzheimer’s.
Even in chronic diseases, blood gene expression can reflect changes in brain vascular health and BBB stability.
Even in chronic diseases, blood gene expression can reflect changes in brain vascular health and BBB stability.
Study 4: Alzheimer’s & Vascular Genes
Researchers looked at VEGF-related gene expression in blood and brain. They found:
- Higher PGF and VEGFB in blood
- Lower expression in brain
This imbalance was linked to faster cognitive decline.
Researchers looked at VEGF-related gene expression in blood and brain. They found:
- Higher PGF and VEGFB in blood
- Lower expression in brain
This imbalance was linked to faster cognitive decline.
September 20, 2025 at 2:11 PM
Study 4: Alzheimer’s & Vascular Genes
Researchers looked at VEGF-related gene expression in blood and brain. They found:
- Higher PGF and VEGFB in blood
- Lower expression in brain
This imbalance was linked to faster cognitive decline.
Researchers looked at VEGF-related gene expression in blood and brain. They found:
- Higher PGF and VEGFB in blood
- Lower expression in brain
This imbalance was linked to faster cognitive decline.
This study shows that blood RNA changes reflect the inflammatory response after stroke - especially the response that damages the BBB and allows immune cells into the brain.
The method used is directly applicable to tracking BBB injury over time.
The method used is directly applicable to tracking BBB injury over time.
September 20, 2025 at 2:11 PM
This study shows that blood RNA changes reflect the inflammatory response after stroke - especially the response that damages the BBB and allows immune cells into the brain.
The method used is directly applicable to tracking BBB injury over time.
The method used is directly applicable to tracking BBB injury over time.
Study 3: Intracerebral Hemorrhage (Stroke)
Researchers sequenced blood RNA at 24h and 72h after stroke.
At 72h, they found:
- Increased IL8, MMP9, NF-κB, ICAM1
All tied to immune-driven BBB damage.
Researchers sequenced blood RNA at 24h and 72h after stroke.
At 72h, they found:
- Increased IL8, MMP9, NF-κB, ICAM1
All tied to immune-driven BBB damage.
September 20, 2025 at 2:11 PM
Study 3: Intracerebral Hemorrhage (Stroke)
Researchers sequenced blood RNA at 24h and 72h after stroke.
At 72h, they found:
- Increased IL8, MMP9, NF-κB, ICAM1
All tied to immune-driven BBB damage.
Researchers sequenced blood RNA at 24h and 72h after stroke.
At 72h, they found:
- Increased IL8, MMP9, NF-κB, ICAM1
All tied to immune-driven BBB damage.
Study 2: Repeated Blast Exposure
Military breachers (who experience repeated low-level blasts) showed changes in blood RNA:
- Immune genes like LILRB5, CD200
- A brain-specific gene CNTNAP2
This suggests chronic stress or damage to brain barriers.
Military breachers (who experience repeated low-level blasts) showed changes in blood RNA:
- Immune genes like LILRB5, CD200
- A brain-specific gene CNTNAP2
This suggests chronic stress or damage to brain barriers.
September 20, 2025 at 2:11 PM
Study 2: Repeated Blast Exposure
Military breachers (who experience repeated low-level blasts) showed changes in blood RNA:
- Immune genes like LILRB5, CD200
- A brain-specific gene CNTNAP2
This suggests chronic stress or damage to brain barriers.
Military breachers (who experience repeated low-level blasts) showed changes in blood RNA:
- Immune genes like LILRB5, CD200
- A brain-specific gene CNTNAP2
This suggests chronic stress or damage to brain barriers.
They also showed that these patients’ blood cells stuck more strongly to lab-grown brain endothelial cells, and their serum caused inflammation in those cells.
The changes in blood RNA reflected inflammation and damage at the BBB.
The changes in blood RNA reflected inflammation and damage at the BBB.
September 20, 2025 at 2:11 PM
They also showed that these patients’ blood cells stuck more strongly to lab-grown brain endothelial cells, and their serum caused inflammation in those cells.
The changes in blood RNA reflected inflammation and damage at the BBB.
The changes in blood RNA reflected inflammation and damage at the BBB.
Study 1: Long COVID + Brain Fog
Researchers sequenced immune cells from Long COVID patients with brain fog. They found:
Increased clotting and complement genes
Decreased adaptive immune genes
This matched signs of a leaky BBB on MRI.
Researchers sequenced immune cells from Long COVID patients with brain fog. They found:
Increased clotting and complement genes
Decreased adaptive immune genes
This matched signs of a leaky BBB on MRI.
September 20, 2025 at 2:11 PM
Study 1: Long COVID + Brain Fog
Researchers sequenced immune cells from Long COVID patients with brain fog. They found:
Increased clotting and complement genes
Decreased adaptive immune genes
This matched signs of a leaky BBB on MRI.
Researchers sequenced immune cells from Long COVID patients with brain fog. They found:
Increased clotting and complement genes
Decreased adaptive immune genes
This matched signs of a leaky BBB on MRI.
Now let’s look at how this has been used in real research.
Studies have used blood RNA sequencing to detect changes in BBB-related genes in humans - both in acute injuries and chronic brain conditions.
Studies have used blood RNA sequencing to detect changes in BBB-related genes in humans - both in acute injuries and chronic brain conditions.
September 20, 2025 at 2:11 PM
Now let’s look at how this has been used in real research.
Studies have used blood RNA sequencing to detect changes in BBB-related genes in humans - both in acute injuries and chronic brain conditions.
Studies have used blood RNA sequencing to detect changes in BBB-related genes in humans - both in acute injuries and chronic brain conditions.