Aaron Abend
Senior Researcher, Autoimmune Registry
11 active projects
V7 ARI Genomics Workspace - 4-21-23
Scientific Questions Being Studied
We now have 4 goals in our research - this workspace has been created specifically for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
4. We will develop statistics analyzing the association of variants known to affect autoimmune diseases for specific diseases to see if those variants corelate with other autoimmune diseases.
Anticipated Findings
There are recognized associations between specific gene variants and some autoimmune diseases. We are going to explore whether those associations can be found in other autoimmune and autoinflammatory diseases. We hope this work can uncover the common mechanisms that underlie autoimmune conditions that appear to be unconnected but which are comorbid.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled Tier
V7 ARI Workspace - 4-21-23
Scientific Questions Being Studied
We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Francis Ratsimbazafy - Other, All of Us Program Operational Use
- Jun Qian - Other, All of Us Program Operational Use
- Jeremy Harper - Senior Researcher, Autoimmune Registry
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Ingrid He - Project Personnel, Autoimmune Registry
- Emily Holladay - Project Personnel, Autoimmune Registry
- Chenchal Subraveti - Project Personnel, All of Us Program Operational Use
- Adnaan Jhetam - Project Personnel, Autoimmune Registry
- Alexander Burrows - Research Assistant, Autoimmune Registry
- Jagannadha Avasarala - Other, University of Kentucky
ARI Workspace V5 2022
Scientific Questions Being Studied
We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Francis Ratsimbazafy - Other, All of Us Program Operational Use
- Jun Qian - Other, All of Us Program Operational Use
- Jeremy Harper - Senior Researcher, Autoimmune Registry
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Ingrid He - Project Personnel, Autoimmune Registry
- Emily Holladay - Project Personnel, Autoimmune Registry
- Chenchal Subraveti - Project Personnel, All of Us Program Operational Use
- Adnaan Jhetam - Project Personnel, Autoimmune Registry
- Alexander Burrows - Research Assistant, Autoimmune Registry
- Jagannadha Avasarala - Other, University of Kentucky
Duplicate of ARI Genomics Workspace
Scientific Questions Being Studied
We now have 4 goals in our research - this workspace has been created specifically for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
4. We will develop statistics analyzing the association of variants known to affect autoimmune diseases for specific diseases to see if those variants corelate with other autoimmune diseases.
Anticipated Findings
There are recognized associations between specific gene variants and some autoimmune diseases. We are going to explore whether those associations can be found in other autoimmune and autoinflammatory diseases. We hope this work can uncover the common mechanisms that underlie autoimmune conditions that appear to be unconnected but which are comorbid.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierARI Workspace V5
Scientific Questions Being Studied
We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Francis Ratsimbazafy - Other, All of Us Program Operational Use
- Jun Qian - Other, All of Us Program Operational Use
- Jeremy Harper - Senior Researcher, Autoimmune Registry
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Ingrid He - Project Personnel, Autoimmune Registry
- Emily Holladay - Project Personnel, Autoimmune Registry
- Chenchal Subraveti - Project Personnel, All of Us Program Operational Use
- Adnaan Jhetam - Project Personnel, Autoimmune Registry
- Alexander Burrows - Research Assistant, Autoimmune Registry
- Jagannadha Avasarala - Other, University of Kentucky
ARI Workspace V4
Scientific Questions Being Studied
The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Jeremy Harper - Senior Researcher, Autoimmune Registry
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Alexander Burrows - Research Assistant, Autoimmune Registry
- Adnaan Jhetam - Project Personnel, Autoimmune Registry
ARI Genomics Workspace
Scientific Questions Being Studied
We now have 4 goals in our research - this workspace has been created specifically for Goal #4.
1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.
2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.
3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.
4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
- Ancestry
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
4. We will develop statistics analyzing the association of variants known to affect autoimmune diseases for specific diseases to see if those variants corelate with other autoimmune diseases.
Anticipated Findings
There are recognized associations between specific gene variants and some autoimmune diseases. We are going to explore whether those associations can be found in other autoimmune and autoinflammatory diseases. We hope this work can uncover the common mechanisms that underlie autoimmune conditions that appear to be unconnected but which are comorbid.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierOriginal ARI Workspace
Scientific Questions Being Studied
The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Priya Padathula - Project Personnel, Autoimmune Registry
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Darrison Haftarczyk - Research Assistant, Autoimmune Registry
Duplicate of ARI Workspace -7-29-20 #1
Scientific Questions Being Studied
The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierARI Disease Sets
Scientific Questions Being Studied
The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Aaron Abend - Senior Researcher, Autoimmune Registry
ARI Workspace
Scientific Questions Being Studied
The goal of our research is to determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. This work will help understand the likelihood of having autoimmune disease and we hope it will improve the ability of doctors to diagnose patients as it will establish the prior probability of having one of these many diseases.
Project Purpose(s)
- Disease Focused Research (Autoimmune diseases)
Scientific Approaches
We will create three data sets for analysis:
1. A list of diseases rated in the following ways:
a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism
b. Autoinflammatory versus autoimmune flag
c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause
2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
Anticipated Findings
The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.
Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Jeffrey Green - Project Personnel, Autoimmune Registry
- Eric Chen - Project Personnel, Autoimmune Registry
- Aaron Abend - Senior Researcher, Autoimmune Registry
Collaborators:
- Priya Padathula - Project Personnel, Autoimmune Registry
- Darrison Haftarczyk - Research Assistant, Autoimmune Registry
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