The Yale LISTEN Study Town Hall: September 2022

February 27, 2024

Information

Drs. Harlan Krumholz and Akiko Iwasaki discuss preliminary findings and answer questions from LISTEN participants.

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00:04Maybe I'll just start just to stay
00:06for a minute or two and then I'll,
00:08I'm going to hand it to Akiko and
00:11maybe just five us can introduce
00:15ourselves just to say hello.
00:17Leslie, you want to? Sure.
00:19No, I just I'm, I'm here on
00:20behalf of Hugo Health and Kindred.
00:21I just want you to welcome
00:23everybody and appreciate
00:25everybody's engagement here.
00:27For those of you that came to our
00:30cafe last week that it was just an
00:32incredible exchange of ideas and
00:34and conversation and and really
00:36appreciate people that were there.
00:38You know, we, we're here to serve you guys.
00:40We want to have your, we want to be
00:42sure that your voices are heard,
00:43whether it's by participating,
00:45listen or joining some of the
00:46other activities that we're doing
00:48on the Kindred side.
00:49Talia is also here who's
00:51our community manager.
00:52She's been capturing people's
00:54stories and putting, you know,
00:56posting those stories on on the Kindred site.
00:59There's lots of great content
01:00that's showing up there.
01:01There'll be more coming.
01:03So please, please, you know,
01:05reach out to us if you need anything.
01:06And you know,
01:07as Harlan said,
01:08this is the first listen town hall meeting.
01:10I know they have plenty more that
01:11they'd like to do with those of you
01:13that have signed up for the study.
01:15So I'm going to pass it over to them.
01:17And again,
01:17thank you so much and we're really
01:19excited about what's coming forth.
01:21So I'll pass it on tomorrow.
01:22I'll just say just I should
01:24have introduced myself.
01:25So I'm Harlan Krumholz,
01:27I'm a professor of medicine at Yale.
01:29I'm a cardiologist and also Co
01:32founder of Hugo and and Leslie's
01:34husband which is probably one of
01:37the nicest things about me the
01:41and and we're here with Born Alley
01:43and Cesar who are key members of
01:45the Liston team and were part of
01:47the cafe last week and of course
01:49Akiko Iwasaki who is going to be
01:52presenting some information about
01:53a study that we recently completed.
01:55But I I just want to sit there for
01:57a moment that so we're this is all
01:59about trying to think differently
02:00about how the research is done.
02:02And like we said this is all
02:05iterative and maybe and I think
02:06next time it would be better for
02:07everyone to see everyone's face is
02:09to feel better since the community.
02:10But it's unusual for research
02:12study to say like, hey,
02:14let's run some town halls,
02:15let's have some back and forth,
02:16let's have Ask Us Anything sessions
02:18and also share ideas about the study.
02:20And to be able to listen,
02:22the states called listen,
02:23listen to all of our teammates,
02:26all of the people who are participating
02:27so that we can think about how we can
02:30do this better and how we can race
02:32faster towards progress that will
02:34impact positively people's lives.
02:36And so far,
02:37I mean we've enrolled largely
02:40by word of mouth.
02:41I mean, you know,
02:42we've promoted some stuff on social media.
02:44People will join Kindred.
02:45Kindred,
02:45a community where people can
02:46interact and get information,
02:47have the opportunity to link
02:48to their data and join studies.
02:50The promise of Hugo is that people
02:52can gain agency over their data and
02:55that the data won't move without
02:56anyone's permission or be kept safe.
02:57And it's up to people,
02:59as their data assets grow,
03:00whether they want to join studies and
03:02be able to help move things forward.
03:04The profiles within Kindred are
03:06meant to help match with studies
03:08and accelerate that.
03:09When we ask for stories,
03:10it's because we want to know like real life,
03:13like,
03:13how's it affecting you in ways that
03:15questionnaires may not be able to capture?
03:16And then if people connect
03:18to their data sources,
03:19their electronic health record and
03:21wearables and payers and others,
03:23it creates a rich source of data
03:25about them that they have agency over.
03:27And then if they consent to be in
03:29a study and they think that the
03:30study's worthy of them and then
03:32they can agree to have that data
03:34be used in the study.
03:35And it's up to us to try to make sure
03:36data doesn't move without permission.
03:38And in the studies that are offered are
03:40ones that will treat people as partners.
03:43And of course we're starting this first day,
03:44but but we hope that there may be
03:47many opportunities that come down
03:48the Pike that will be part of this.
03:50And again,
03:50part of it is trying to foster a
03:54sense and when I say sense it,
03:56I mean authentically convey
03:57that we're interested in.
03:59In and working directly with people
04:02and again other studies tend to
04:04go through sites and depend on a
04:06physician offering a study to someone
04:08or there there's lots of of people in
04:10the middle between the researchers
04:12and the people participating.
04:14We're trying to say what if
04:15it's a direct to consumer idea,
04:17what if it's decentralized
04:18and anybody can join.
04:20And what if we can talk directly
04:22with the group and and again
04:24listen to to questions,
04:25be able to interact and and then think
04:27about how we can make progress together.
04:31For me, one of the great
04:33privileges of this study.
04:34Now we'll just talk about the listen
04:35study and we're glad to answer a lot of
04:37questions about listen study as we go.
04:38But one of the great privileges
04:40of LISTEN study has been my my
04:43opportunity to work with Akiko,
04:45who is just the most remarkable
04:47scientist and also individual person
04:49who cares deeply about the people that
04:52she's trying to generate knowledge
04:54about to help them do better.
04:56And is also conducting science in
04:58a way with utmost integrity and
05:00leadership and trying to think in
05:02an innovative ways about how we can,
05:04how we can all work together.
05:05So and and the central idea here
05:09is that if we can be able to
05:12collect information about people,
05:13their lives, their journey,
05:14their experience and understand
05:16the diversity of ways in which
05:18they're affected and also include
05:20people who are control populations.
05:22And by the way we're talking about
05:24lists and we're talking about
05:25people who are in with long COVID.
05:26We're also have heard a lot from
05:28people who are reporting vaccine
05:30injury and have symptoms that
05:32often can sound very similar.
05:34And we're very interested in working
05:36with them respecting honoring the
05:37kind of experience that they're
05:39having and seeing whether or not we
05:41can reflect through the through,
05:42you know,
05:43what we're collecting about them
05:44and the biology try to breakthrough
05:46information on that side too.
05:48What we're working with Akiko for me
05:50is the opportunity to both profile
05:52people from their experience and then
05:54combine it with this deep immuno
05:56phenotyping that she's going to talk about.
05:58Really the very best science that
06:00we can imagine.
06:01And being able to generate lots
06:03of data about people,
06:04their experience and how their bodies
06:06are working in order to try to come
06:09up with some insights about what's
06:10causing this and where we can go
06:12for diagnostics and therapeutics.
06:14And most importantly to reflect
06:16back to people that that you know we
06:18believe you like we hear you we we
06:20know that there's there's something
06:22real going on and it's important for
06:24us to work together to demonstrate
06:26what that is and to be able to
06:28provide evidence based guidance
06:29about what people can do to help themselves.
06:31And and anyway So what we'll we're
06:34going by the when people are like
06:35even I know a lot of people have had
06:38very difficult experiences where
06:39either they're being dismissed or or
06:41people doubt them or or wonder if
06:43it's really people doubt themselves even.
06:45And just to say that we're here to
06:47say that let's learn together and
06:49and again you know we're we're we
06:51hope people will consider us allies
06:52in this as we try to make progress
06:54together and help us be better better
06:57partners because we know that that
06:58you know there'll be places where
07:00we could do better maybe we we
07:01haven't been as sensitive as we
07:03could could be or should be
07:04and we're eager to learn about
07:06how we can be better partners.
07:07So with this, I want to turn it over
07:10to Kiko who's who's got a presentation
07:12planned and and I know people are
07:14putting in questions and we can try to,
07:16we got Bernali and Cesar who can either
07:18answer on their own or they can tee
07:20them up for us in the second part of
07:22the presentation where we can answer
07:24them and we're lucky to have them
07:26engaged and also part of the project.
07:28And let me hand this over to my dear friend,
07:31my colleague and partner in this project,
07:35Akiko to welcome you all and
07:36then talk a little bit about a,
07:39a study that we've recently done.
07:40So thank you so much.
07:42All right. Thank you so much Leslie
07:45and Harlan for the introductions.
07:47And you know, I, I feel equally
07:50honored and fortunate to be working
07:53with Harlan and Born Alley and
07:56Cesar and Leslie as a partner.
07:58So just a little bit of background about
08:01myself, I'm an immunologist at Yale.
08:04I've been studying infection with
08:06variety of viruses and immune responses
08:10and seeing how we can use that
08:13knowledge to improve people's health.
08:16And mostly I'm basic immunologist so
08:19I study basic mechanism of diseases
08:22as well as vaccine developments.
08:26We're currently working with the nasal
08:29vaccine booster strategy that will
08:31hopefully prevent any diseases like long
08:33COVID from happening in the future.
08:36So what I'd like to do today is
08:38to first of all welcome everyone.
08:40I see the names of attendees and you
08:43know many of you have reached out
08:45to me and I I I feel like I know
08:47you and it's it's wonderful to see
08:49your names at least on the list.
08:51And some of you are superstars.
08:53You're advocates and I really
08:56appreciate everything you do.
08:58So I'm.
08:58I'm playing a small part in this
09:01whole equation of your lesson study,
09:03but essentially what I want to
09:05do today is to kind of give you
09:07an overview of a prototype study
09:10that we did in collaboration with
09:12Mount Sinai School of Medicine with
09:15David Petrino's group and give you
09:17a sense of what what we can do.
09:19By the way, this is the tip of the iceberg.
09:21We can do a lot more and we
09:23are doing a lot more.
09:24But we wanted to get this information
09:26out to people as soon as possible so that
09:29you can read about it and in fact it this,
09:31the study has already been posted in
09:33mid archive and has been picked up by,
09:36you know I think 80 media outlets already.
09:39So you've probably heard about it.
09:40But I want to tell you what how
09:42we interpret the results.
09:44So I'm going to share the screen.
09:49OK. All right. You can see this. Yes.
09:55OK. So yeah, today I want to talk
09:58about the immunology of long COVID.
10:01The reason we're studying the immune
10:04system in people with long COVID is
10:07because the immune system is it's
10:10it's like an amazing orchestration of
10:14molecules and cells and biological
10:18process that can tell us a lot about
10:20what's happening in in a person's body
10:23even just by collecting blood and
10:25looking at what's in inside of that.
10:27And so today I'm going to focus
10:29mostly on the blood analysis,
10:31but we can do a lot more by collecting
10:34tissues and mucosal surf secretions.
10:36So today's focus will be in the blood.
10:41Before I get into long COVID,
10:43I want to highlight the fact that
10:46there are many other infectious agents,
10:48many viruses as well as non viral
10:52pathogens that can induce long term
10:55symptoms of post acute infection
10:57syndrome of place that that we have
11:00summarized in a recent review with Jan
11:04Chotka that we we published together.
11:08And so Jan himself,
11:10he's suffers from MECFS and he has read
11:14every paper under the sun on this topic.
11:17And he I I kind of helped him with
11:20the strategy for this, this review.
11:22And essentially what you see are a
11:24lot of different viral pathogens,
11:27some of which has really no
11:29name for those diseases.
11:30But it's well known to have a sequela
11:34way after the initial infection process.
11:37Some of these post infection sequela
11:41can take decades to manifest,
11:44whereas others become apparent
11:46within days or weeks.
11:48So stars COVID to the long COVID.
11:50Obviously the CDC definition is
11:54symptoms that last for over 4 weeks
11:57and and that that is certainly
11:59true for stars COVID too.
12:01But other viruses have different
12:03onset of these types of post
12:07infection syndromes and there are
12:09other non viral pathogens,
12:11bacteria and parasites that can also
12:14cause post infectious syndrome at
12:15the the famous ones at the Q fever,
12:18fatigue syndrome and the post Lyme disease.
12:21But there are probably many others
12:23that are under recognized that
12:25many people are suffering from
12:27without really knowing what the
12:29causative agents might be.
12:32Just taking some of the examples of
12:35literature on say Epstein BA virus,
12:38this is a from the same review
12:40what we see it is studies.
12:43So different colors
12:44indicate different studies.
12:46We compile them into one graph and
12:48looking at time since mononucleosis
12:50which is caused by Epstein by virus
12:53infection and then the unrecovered
12:56participants on the Y axis.
12:58You see that there are large
13:00number of unrecovered participants
13:02within about two months post mono.
13:04But this percentage declines over time
13:07and the studies are pretty consistent.
13:11But even after 24 months this
13:13number does not go to zero.
13:15There are about 4% of the individuals
13:18who had mono are two years still
13:21suffering from various symptoms
13:23and many of these have turned
13:25into Chronic fatigue syndrome.
13:29Diagnosis service COVID 2 also
13:33has a similar type of curve.
13:35When you look at people who are
13:39having at least one of 12 common
13:42symptoms or self reported long
13:44COVID in days since COVID-19,
13:46you see that there is there is
13:48definitely decline in these numbers,
13:51but some of these are unfortunately
13:54quite persistent.
13:58And So what might be causing these
14:01long symptom after an acute infection
14:04we we think that there may be many
14:08different causes and it's not that
14:10one of these mechanisms are right,
14:12it's probably many of these
14:14things that are going on.
14:15In some people there might be multiple
14:17of these things going on at once.
14:19But some of the top hypothesis are
14:22viral reservoir or viral pathogen
14:25associated molecular patterns.
14:27These are sort of the RNA or
14:29the DNA of the viral genome that
14:32triggers innate immune responses.
14:34And also this persistent antigen can
14:37drive T cells and B cells to act
14:40for chronic in a chronic manner,
14:43stimulating chronic inflammation.
14:46Second hypothesis is autoimmunity.
14:49It's possible that you generate
14:51autoreactive antibody after
14:53an acute infection.
14:54This is a a well known thing
14:56that happens after an infection.
14:58You generate these bystander
15:00activation of T cells and B cells,
15:02but if they persist that could
15:05also trigger long term symptoms.
15:07Now C is this dysbiosis of the microbiome,
15:11the commensal bacteria that live in the gut.
15:15Their composition changes over time
15:17and it's possible that the the bad type
15:19of bacteria may be replicating in in
15:22the gut to cause some of the symptoms.
15:24It's also possible that there is
15:27reactivation of latent viruses like
15:30the Epstein virus or other herpes
15:32virus family members that could become
15:35reactivated and cause some symptoms.
15:38And then it's also possible that there's
15:40tissue damage in various different
15:42organs that might contribute to inflammation.
15:46There are many, many studies that
15:48have been done and these are
15:50just handful of the examples that
15:52indicate possible viral reservoir.
15:55There is antigen, there is RNA,
15:57there's combination of these, sorry
16:03of these viral features that are found in
16:08people with COVID months after an infection.
16:13There's also EBV reactivation,
16:15the Epstein biovirus that I talked about just
16:18now that that was identified to be one of
16:21the four predictive factors for long COVID.
16:24There are also papers showing autoreactive
16:27antibodies against G protein couple receptors
16:30as well as Lupus related auto antibodies.
16:35And then we also published the mouse
16:38model in which central nervous system
16:41damage can be caused by an acute
16:44respiratory infection with SARS COV two.
16:47So there's evidence of all these
16:49things and and like I said long COVID,
16:52it it is definitely heterogeneous
16:55disease that encompasses probably many of
16:59these in combination of these features.
17:04Well this is one of my favorite studies
17:07where people have found that dogs that
17:10are trained to detect SARS COV to infected
17:14supernatant identified about half of the
17:17people with long COVID where 0% of the
17:21controls were identified by these dogs.
17:24This is a very unbiased way of
17:27detecting viral persistence I think in
17:30in people and it's it's a interesting
17:33indication of possible viral reservoir.
17:38So the study that came out earlier this
17:41year by Jim Heath's group demonstrated by
17:45studying people who had acquired COVID and
17:49following them for two to three months.
17:51They identify 4 anticipating risk
17:53factors at the time of initial diagnosis
17:57that predisposed people to long COVID.
18:00One is type 2 diabetes,
18:03second is SARS Co V2 RNA aemia,
18:06this is viral RNA found in the blood,
18:09Epstein biovirus,
18:10Viremia again ABBDNA found in the
18:14blood and then auto antibodies
18:17against lupus related antigens.
18:19These four factors could explain
18:21a lot of the risk associated
18:23with development of long COVID.
18:28So then talking, this is the background,
18:32just kind of give a sense of what's known,
18:34what's not known and what we've done.
18:37So we have carried out our first human
18:41long COVID studies and as I said,
18:44this is a prototype.
18:46We plan to do this hopefully with the
18:50real lesson cohort and asking distinct
18:52questions about the immune phenotypes and
18:55what's driving some of these symptoms.
18:58And I just wanted to introduce
19:01the team that we worked with,
19:03which is, as I mentioned earlier,
19:05David Petrino at Mount Sinai
19:08School of Medicine.
19:09He sees thousands of long haulers.
19:13He's an amazing human being as well and
19:17I have the fortune of collaborating
19:19with him and his team Jamie Wood,
19:22Laura Tabakov and Dana McCarthy and
19:25and others from his team who have been
19:29working for over 2 years together.
19:32I actually reached out to David when I
19:35first heard about long COVID during an
19:39interview with Ed Young from the Atlantic.
19:42He was asking me about what are what
19:44are your hypothesis about these long
19:46COVID And that was like really the
19:48first time I heard about these post
19:50acute sequela of COVID because it was
19:54summer of 2020, so pretty early on.
19:57But then in the same articles David
20:00Petrino was quoted and I realized that
20:03he he really cares about patients and
20:06he's very knowledgeable about the
20:08clinical features associated with long COVID.
20:10So I'm very happy that he responded to
20:13my e-mail and we started a collaboration.
20:15And so that's the,
20:16the work that I'm going to tell
20:19you about today.
20:20And of course I'm just a conduit of what?
20:23My team and others have done together,
20:26so these are really the heroes who carried
20:30out the studies and students and postdocs.
20:33And so John Klein is the first
20:36of the Co first authors.
20:39He's an MD PhD student in the lab.
20:43Jill J Cox is a MDPHD student in Aaron
20:46Rings Laboratory who is also a key
20:49collaborator in this home endeavor.
20:52Rahul is a postdoctoral fellow in David
20:57van Dyke's lab who is does the machine
21:01learning algorithm for the study.
21:03Jeff Sasha pay When are three other
21:06members of the laboratory who really
21:09work tirelessly to analyze the samples?
21:12And so this is I'm just presenting
21:15their work.
21:17So the Mount Sinai Yale my long COVID
21:22study was to really try to collect
21:25as many information as possible from
21:28people who have had long COVID it.
21:31So this is from Mount Sinai.
21:33So New York got its first wave
21:35pretty early during the pandemic.
21:37When we collected the sample samples,
21:40they were about at least a year out
21:43from their original infection and we
21:46we included people who are older than
21:4818 years of age and who fit The Who
21:52guideline criteria for COVID infection.
21:55And we excluded certain types
21:57of individuals because we didn't
22:00have a large number.
22:01As you can see,
22:03we have 99 long COVID in purple
22:06at the convalescent control.
22:08These are the people who got infected
22:10around the same time but completely
22:13recovered 39 people and healthy Control,
22:16these are 39 people who never had COVID.
22:19And then we also had a healthcare
22:21workers who provided samples for the
22:24antibody analysis and we conducted
22:26multiple immune phenotyping.
22:28One is a flow cytometry to look
22:31at cell cellular factors and
22:33composition and activation phenotype.
22:36We also did human exoprotium
22:39antibody analysis.
22:40This is also known as a rapid
22:44extracellular antigen profiling or
22:46REAP technology developed by Doctor
22:49Ring and SARS COV 2 antibody profiling.
22:53This is looking at virus specific antibodies.
22:57We also did a peptide display library.
23:00This is really looking at antibodies
23:03against virtually any epitope that we we
23:06were interested in plasma proteomics,
23:08so we'll get cytokines and hormones and
23:10then of course EMR and symptoms survey,
23:13we wanted to correlate people's symptoms
23:16to different immune features and
23:19that's how we did the study and this
23:22is in met archive, not by archive, OK.
23:27So the demographic of the population
23:30were similar between the long COVID
23:33and the convalescent controls.
23:35Median age was 45.8 versus 41.4
23:40female dominant.
23:42This is typical of long COVID,
23:44there are a lot more female
23:46patients than male patients.
23:48And then we have also most of the
23:51people were not hospitalized and then
23:53there were some that were hospitalized.
23:55But there was no significant difference
23:58between these groups and days from
24:00acute COVID as I mentioned the
24:04they're about at least a year out
24:07from their infection around the year
24:10to 18 months or so mean both the
24:13convalescent and long COVID groups,
24:17so long COVID patients.
24:19So we did all these different analysis.
24:21I'm just going to highlight some
24:23of the key things that we found.
24:25So again, just to Orient you,
24:27the healthy controls are
24:29already always in orange,
24:31the convalescent controls are in yellow and
24:34long long COVID participants are in purple.
24:38So of all the features that we
24:40looked at by flow cytometry,
24:42what we see is an elevated level
24:45of non conventional monocytes.
24:48These are.
24:49So I don't want to get into the
24:51details about these cell types,
24:53but essentially these are the cells that you,
24:55you know often find during a chronic viral
24:58infection and they seem to be activated.
25:01We also see reduction in these
25:04conventional dendritic cell type one,
25:06these are the cells that are known
25:08to stimulate antiviral T cells and
25:11they're kind of reducing the blood.
25:14We also see activated B cells,
25:17B cells are the cells that make
25:20antibodies and they they have this
25:23interesting activation phenotype
25:24in the long COVID patients and we
25:28also see double negative B cells.
25:30These are B cells that are thought to be
25:33involved in extra follicular activation.
25:35It's just too technical to
25:37get into what what they are.
25:39But essentially this was what we saw,
25:42what was these cells were also elevated
25:45and then when we looked at the T cells,
25:48so T cells are the ones that's that
25:51can detect virus infected cells and
25:53kill them and some of the other
25:55T cells are known as helper cells
25:57of CD4T cells or the helper cells
26:00that kind of remember different
26:02viruses and and stimulate it.
26:04They're like the the central control
26:06commander of the immune system and
26:09they play very important role in
26:11every aspect of the immune system.
26:13What we saw was that in a long
26:16COVID patients,
26:16what we call the the central memory
26:19cell population of T cells were
26:22reduced in circulation whereas the
26:25exhausted T cells were elevated both
26:27the CD four and the CD eight types.
26:30So exhausted T cells are interesting
26:33because they are only present when T
26:37cells detect the antigen over and over.
26:40So for instance,
26:41you find these cells during a
26:43chronic viral infection.
26:44You find these cells in a,
26:46in a tumor setting,
26:48people who have tumors that can't be removed.
26:51So the T cells that are specific to
26:53that specific antigen become exhausted
26:55because they've been stimulated too long.
26:58So that's elevated.
27:00That's interesting.
27:01We don't know what these T
27:03cells are actually detecting,
27:04but it means there's some kind of chronic
27:07antigen that's stimulating this response.
27:10We also found that cytokines
27:13that are secreted by these
27:15helper T cells are elevated.
27:18So cytokines are like the languages
27:20that the T cells speak to communicate,
27:23you know,
27:24different signals to other other leukocytes
27:27or other cell types in the body.
27:30They're very important.
27:31But what we're seeing here is that
27:33these types of cytokines Interleukin 2,
27:36four and six are elevated in the
27:40CD 4T cells of people,
27:42long COVID patients but not the others.
27:45So the convalescent controls,
27:46they were infected but recover,
27:48they don't have these features.
27:51And if you look at there are
27:53some T cells that secrete both
27:54Illinois four and Illinois 6.
27:56These double positive cells are pretty
27:59much only found in people with long COVID.
28:03So that's very interesting.
28:04We don't know what they're doing but
28:06they do correlate with something.
28:08I'm going to tell you what that is soon.
28:13The other features we looked at are
28:16antibodies against the virus and what we saw
28:19was that the long COVID patients have so,
28:22so we controlled for the number of
28:25vaccinations because of course the the more
28:27vaccines you receive the more antibody
28:29you generate against the spike protein.
28:32So we only took people who had two doses
28:34of vaccines and then asked what is
28:37their antibody level against the spike
28:39or the S1 region of the spike or the
28:41receptor binding domain of the spike.
28:43So the purple again the long COVID
28:47patients with two doses of vaccines,
28:49they had higher levels of antibodies and
28:52that that was really consistent among
28:55these participants against SS1 and RBD.
29:00And so this is interesting again it
29:04suggests that these B cells may be
29:07undergoing maturation process because
29:09they're seeing the antigen over and over.
29:12That's just a speculation.
29:14We don't know why they have higher
29:16levels but that could be one reason.
29:20The other thing that we looked at,
29:22I mean we we looked at actually
29:24thousands of factors from the
29:26blood of these participants and we
29:29asked what are the features that
29:31are most significantly different
29:33between people with long COVID
29:35and people without long COVID.
29:37And the number one factor,
29:39the most significant was the cortisol,
29:42plasma cortisol level.
29:44Now we didn't do a cortisol
29:46measurement throughout the day,
29:48which is what we're planning to
29:50do to find out if their pattern of
29:53cortisol secretion is different.
29:55But at the time when we collected the
29:58data most participants were collected,
30:01their blood was collected a
30:03similar time during the day.
30:05So let me go to that So the
30:07collection time for healthy Control,
30:09the Calm Blessing control or the long
30:12haulers were about similar time from the.
30:15So Kiko,
30:17let me let me ask you this just because
30:19you've got a lot of good amazing stuff here.
30:22So just because I'm thinking you
30:25know you've got it's such good detail
30:28but a lot of people will like I I
30:31think what we want them to take home
30:33from this is that you've got it what
30:35you your approach is let's measure
30:37thousands of different things,
30:39multiple different domains.
30:41I mean it's just for people listening.
30:43I mean look Akiko as you can tell
30:44is like at the top of the field and
30:47and you know and there are others of
30:49course who are thinking hard about
30:51this stuff but one of the central
30:53messages from the study was that
30:55that there was something there.
30:57So all these people generally had
30:59you know lots of other tests and I'm
31:01seeing in the and I I'm just going
31:03saying this because we're also getting
31:05questions that I want to be able to
31:07to get to but people are getting
31:08lots of tests we're all come back
31:10to normal And then with this vast
31:13array of testing many of it and very
31:16different you know kinds of things.
31:18Some looking for substances produced
31:19by the immune system.
31:20Some persons by antibody proteins
31:23something looking at evidence
31:25reactivation all this kind of stuff
31:27that that people who and this is just
31:29a long COVID we didn't have a vaccine
31:32injured that we're going to we're
31:33hopefully develop cohorts like that
31:35but people are different we're different.
31:37I mean and and I think that one of
31:39the central things I've been telling
31:41people is you know this is evidence
31:43that what people are saying I don't
31:45feel right and then people are doing
31:46a bunch of tests and they're saying I
31:49can't find anything wrong with you.
31:51Well, maybe that's not me,
31:53the person who's telling you
31:55something's wrong.
31:55Maybe it's the tests that you know,
31:57and we don't yet have the right tests that
32:00are detecting what it is in your body.
32:03That's not going right.
32:04At least it's different than it was before.
32:08That's causing you to feel a whole
32:09bunch of symptoms.
32:09And one of the things that you
32:11think about listen is, you know,
32:12with more than 600 people in listen
32:14and people haven't filled out,
32:16a lot of these profiles is that
32:18people are are severely affected.
32:20So you know,
32:21that remember that scale that
32:22was like was zero to 100.
32:23Like if you go out to the, you know,
32:25the United States general population
32:27for the age group that we've got,
32:29you know,
32:29people aren't perfect health or their,
32:31their numbers are something like 84 or 85.
32:33Something like that is a that's the
32:35average score that people will say
32:36when you say how's your health.
32:37And in this group it's 5050 and
32:41and many people were down.
32:43And I'm just telling you what you
32:44already know, 'cause you filled it out.
32:46Some people are down 30 and and
32:48and even lower
32:49and showing that,
32:50you know people are severely affected
32:52and lots of people are representing
32:54their previous lives as very healthy.
32:57I mean, and many people,
32:58marathon runners doing all sorts of things.
33:00So what the most important thing
33:02I think what what what Akiko is
33:04showing is that we actually she in
33:07her lab and all the people working
33:08with her I'll say I like to say we
33:11but really it's it's her and her
33:12lab you know are detecting very
33:15important changes that have occurred.
33:18We believe changes is cross-sectional
33:19but that you know that that that
33:22differentiate people who are reporting
33:23all these symptoms from people who
33:25aren't reporting all these symptoms.
33:27And it again, we think it's the
33:28first half of the first inning,
33:29it's just the beginning of
33:31unpacking all of this.
33:32But but like when you're seeing all this,
33:35these you know,
33:36numbers I know can be overwhelming
33:38amount of information.
33:39But I think we wanted to give you a sense of
33:42the substance of the work that's going on.
33:44But maybe I'm just thinking,
33:47Kiko, it's, you know,
33:48we got 20 minutes,
33:49maybe we can just start taking
33:50some questions.
33:51And a lot of these questions by the way,
33:53I I I think I'm interested in hearing
33:54what you have to say about them
33:56because a lot of them are really
33:57tuned towards people having already
33:59had other tests and stuff like that.
34:01And and I'm just thinking you know
34:04for some people this might be it's
34:06it's great to get the high level but
34:07but let's maybe just get into some of
34:10the questions that'd be all right.
34:12Of course, it's fine.
34:13I'm sorry if I went on and on but I
34:16can listen to you forever.
34:17But also I got a lot to learn
34:18even when I'm listening to you.
34:20I'm thinking you know I need there's
34:21more I would need to learn to get up
34:24to because it's so deep and broad.
34:27But. But it should give everyone
34:29a sense of of the depth here.
34:31You know that this isn't just like
34:32one test or another test but it's
34:34like it's a depth of information
34:35which she was sort of showing you
34:37that we're looking in this way.
34:38That way.
34:38I mean, the immune system is amazing.
34:40I mean it's and the body's amazing
34:42and there's so many different
34:43ways that we can look at this
34:44that are far beyond what our
34:45traditional tests people have done.
34:47So maybe we can just go on one does
34:52vascular endothelial inflammation fit
34:53with hypothesis be of autoimmunity?
34:55I don't know.
34:56If you want to Give your opinion about that,
34:59yeah. It could be autoimmunity.
35:01You can imagine antibodies that are
35:04binding to the vascular endothelial
35:06cells causing some inflammation.
35:09It could be complement deposition.
35:11It could be inflammation itself
35:14that's causing vascular damage. Yeah.
35:17So there are a lot of possibilities
35:18of how vascular damage could happen,
35:21but autoimmunity is one of them.
35:23And I'm going to just pepper you with
35:24these like, I'm just going to go fast.
35:25So if you don't mind put you on the hot seat.
35:29OK If you think I'm missing anything or
35:31you think there's something else but this
35:33regarding the theory viral reservoir.
35:34I'm vaccine injured and have had my COVID
35:37antibodies checked eight weeks from injury
35:38and had never had had the infection.
35:40The nucleic capsid antibodies were found
35:42so it's the an autoimmunity for us.
35:44I had immediate reaction dizziness
35:46within minutes of the shot and then
35:49someone else that you know they were
35:51sorry to hear that and that they had
35:52both post booster and post infection.
35:54long COVID after Pfizer booster.
35:56I could barely stay in the next
35:575 days and barely walk straight
35:58for the following two weeks.
36:00Even now almost a year later I can't
36:02stand with eyes closed might bounce off.
36:03Let me just say what I'm saying
36:05these when we're talking about these
36:06things that people are suffering,
36:07I mean, my heart hurts to hear them,
36:09but let's we'll try to go through
36:11these quickly.
36:11But I want to say to each and
36:13everyone of you that I'm sorry
36:14for what you're experiencing.
36:15We're trying to move forward.
36:16But I think this was just a question
36:18of whether or not your thoughts about
36:20vaccine injury and are we going to
36:22take the same approach to look at it
36:23or are there special features to it?
36:26Yeah, great question.
36:27So I'm sorry I didn't get into the
36:31vaccine injured injury hypothesis,
36:33but other than the viral reservoir,
36:36which obviously isn't part of the vaccine,
36:40I think all of these hypothesis
36:42can still hold true.
36:44And that's why we're very excited to
36:47compare vaccine injury versus long COVID.
36:49We now have really a lot of insights
36:53which I was sharing with you about
36:55long COVID and immune phenotype.
36:57But for post vaccine and it it's
37:01possible that these four hypothesis
37:03except for the viral reservoir,
37:05I would replace that by
37:07potentially the antigen reservoir.
37:09But we don't know,
37:11we don't know whether the spike itself
37:14can be triggering the chronic sort
37:16of activation of T cells and B cells.
37:19And that we can tell by looking
37:21at the flow cytometry data.
37:23You know,
37:24I was showing you the activated
37:25B cells and T cells.
37:27This is a feature that we can
37:29immediately sort of decipher by doing
37:32a similar study on vaccine injury.
37:34So if the injury happens within
37:37minutes of the first vaccine,
37:39though it's unlikely to be driven
37:43by adaptive immune response
37:45because adaptive immunity takes
37:48couple weeks to develop.
37:50So if it's within minutes,
37:52you know you may be reacting
37:55to components of the vaccine in
37:58either sort of an allergic manner
38:00or it's possible that you may be
38:03reacting to the 3D native immune
38:06response to the to the vaccine that
38:09somehow cannot be repressed later.
38:12So but if it's happening after
38:15the booster dose,
38:16it may be driven by adaptive immune
38:19responses that you generate with the
38:22first primary series of the the vaccine.
38:25So I I think we have to be open minded
38:27about what might be causing those and
38:30and that's what we're trying to give
38:32as many people we're we're going
38:34to start implementing this part
38:35of selecting certain people to see
38:37whether they'd be willing to provide
38:38blood and and saliva so that we
38:40can run some of these same tests.
38:41So here's another one.
38:42Do you think it's possible for dogs
38:44to recognize injured vaccine vaccine
38:45injury and are they recognizing virus
38:47or the combination of the immune
38:49response present with the virus?
38:52Yeah. First of all,
38:53we don't know what the dogs are detecting,
38:56the volatile organic compounds
38:57that the the dogs are sensing.
39:00We we no one has identified what that is.
39:03So we don't know.
39:04It would be pretty amazing if the
39:07dogs can recognize the vaccine
39:09injury because that would very
39:13much suggest the spike, you know,
39:16because that's sort of the common
39:18thing that they've been trained with
39:21the viral infected supernatant.
39:22Unless it's something that's induced by the
39:25infection that's also induced by the vaccine,
39:27that has nothing to do with the spike.
39:29It's possible, right?
39:30But like logically spike would
39:32be the common feature there.
39:34So yeah,
39:35it would be great to see if the
39:37dogs can recognize vaccine injury.
39:41I thought there was another one that
39:43just disappeared, but I'll go this one.
39:45I was told by the Long Hawk COVID
39:46clinic at Johns Hopkins that
39:48Professor Pretorius is currently
39:49affiliating her research with Yale.
39:51Is this correct? And if so,
39:52we'd be following up with a micro
39:55clotting studies in potential testing.
39:58Yeah, definitely we.
39:59We've been in touch with Doctor Pretorius
40:03Group and we are learning how to do
40:07the micro clot analysis in the lab.
40:10You know we we have very limited
40:12number of people in the lab so
40:14we can't do everything but micro
40:16clot is certainly on the radar.
40:19It's not like the central focus right now,
40:21but it's something we'd like
40:23to do in the future.
40:25Great. I I think maybe that's just
40:27about the theories about vaccine,
40:29but I think that you you covered
40:31your thoughts about the the
40:33vaccine injured hypothesis there.
40:35There would be maybe even more
40:37that you thought but let me go.
40:39Will you be testing or looking
40:40at immune mediated small fiber
40:42neuropathy related antibodies,
40:46TSHDSFG, FR3, MAG, many of us with
40:48chronic neurologic vaccine reactions
40:50test positive for small fiber neuropathy
40:52via skin biopsies are sometimes
40:53positive for these antibodies,
40:57absolutely. So there are two technologies
41:00that that would cover those the REAP
41:04that I was telling you about which is
41:07an human exoprotium antibody analysis
41:09that Doctor Ringslam has developed
41:12it it covers over 6000 proteins.
41:15So many of these are in that at
41:18least fragments are in there.
41:20So if you are developing auto antibodies,
41:22we would be picking them up.
41:25The other strategy that I mentioned is
41:28the phase display library that one can
41:30also pick up antibody against any episode.
41:33So we should be able to pick those up.
41:36So yeah, I mean whatever it is,
41:38we are going to find it.
41:42Someone asked why was it that injured
41:44folks like me who clearly have SFN
41:46are showing negative test results.
41:48I think that's that's a question, Yeah.
41:52So you know if we only did 10 tests,
41:55we would also not find much in long COVID.
41:58We did thousands of,
42:00we we tested thousands of parameters and
42:03and that's why we were able to identify
42:06distinguishing features for long COVID.
42:09I I think this wide net sort of approach
42:13that we're doing will reveal something
42:16common in a post vaccine injury.
42:19So I'm hopeful that we're going to
42:22find something but you know standard
42:25lab testing and will maybe not
42:27pick up the the the key features
42:28that we are able to pick
42:31up and Michelle Ash is there
42:33specific anti star COV 2 IgG test
42:35that we can take that will allow
42:37you to capture the same kinds of
42:38readings many of us have had antibody
42:40tests but different types Quest,
42:41LabCorp, Academic Centers, Radiance.
42:45So it's harder to compare,
42:49yeah. So in in our preprint we also
42:54found that people with long COVID
42:57make antibodies to specific epitope
43:00within the spike that that is not
43:03found in the convalescent controls.
43:05So it's something that's induced
43:08by the features, viral features
43:11associated with long COVID and it's
43:14not related to vaccine status because
43:17we compared people who are vaccinated.
43:20And so it's, it's possible that the
43:22molecular kind of analysis that
43:25we're doing will pick up unique
43:27features of your antibodies.
43:29Yeah. It's not a standard sort
43:31of quest type of testing.
43:33So, yeah, I'm not sure whether they're
43:35going to pick up any difference.
43:38Yeah. And I think you really
43:39have to have the laboratory
43:40research test to get the kind of
43:42things that you're you're doing,
43:43which again the reason for the study,
43:45the those antibody tests may
43:47give you some information,
43:48but not exactly what you're been looking at.
43:50Someone's asking based on your test,
43:51So the people should be going
43:53out and getting cortisol tests.
43:55Yeah. So that's the other thing.
43:57I don't want to, you know,
44:00first we need to do more research.
44:03You know, it's a limited number of
44:04people and it's, it's one site.
44:05And that's why this,
44:06listen study is great,
44:07'cause we can this, you know,
44:09in a decentralized manner,
44:10we can collect samples from many of
44:13you and test it, the standard sort of,
44:17you know, clinical cortisol test.
44:19We don't know whether they're going
44:21to pick up the difference if you're
44:24doing it for some reason anyway,
44:25yeah, why not?
44:26But I I cannot promise you that
44:28that's going to be a sensitive
44:30way of detecting the differences.
44:32So again,
44:32we do have to do some head
44:33to head comparison.
44:35Yeah
44:35Karen. So if you consider running the
44:37same tests as a group of vaccine injured
44:39that have long COVID type of symptoms,
44:41I'd just say I can just pick that up
44:42say like that's on that's in the plan.
44:44Actually we're starting that now.
44:46We're already contacting a few
44:47people to get started on that.
44:48But that's exactly what we want to do.
44:50We want to demonstrate you know what
44:52what does what do People's Kiko Star
44:55calling these immune signatures you
44:56know what is it that looks like that's
44:58going on in their bodies and and can
45:00we learn from that so that that's
45:02that's definitely in the plan soon to
45:05be launched will there be translation
45:08these findings into clinical trials.
45:10So what's timeline been I I'll just
45:12say quickly that you know Kiko and I
45:14recognize that people are suffering and
45:16we can't wait for a full understanding of
45:18this condition in order to move forward.
45:20And and I'll give you,
45:21you know there are lots of situations
45:23in medicine where you may not
45:24fully understand some,
45:25but you have some hints that things that
45:27are worth trying and they actually can
45:29give insight into the underlying cause too.
45:31At the same time.
45:32So we we are eagerly moving forward to
45:35try to figure out how we can use this
45:37platform to to to run trials and to get
45:40candidates based on what we know already.
45:43We're in discussions actually
45:45there's a potential trial that could
45:47run as as soon as in a few months.
45:49And we're hoping that we'll have a bunch
45:51of people from this community ready,
45:53eager to go and we can enroll it
45:56within weeks, run it, you know,
45:58within a month and figure out
45:59the answer and then keep going.
46:01And then we're trying to,
46:02we're all the time talking to people
46:04who may have therapies that we can try.
46:06And if this group is up for it,
46:08then, you know,
46:09we'll be able to learn stuff rapidly.
46:10But I think it's essential that
46:12we do this in rigorous ways with
46:15trials just to bring in a few other
46:18people who haven't asked.
46:19Some of us not all,
46:21seem to get significantly worse
46:22immediately after steroids like Prednisone.
46:24Maybe it's because Prednisone also lowers
46:26cortisol for an already low cortisol subject.
46:29I I'll just say I think it's
46:31important for this group to share
46:32experience about what triggers them,
46:34what makes things better,
46:34what makes things worse.
46:35We can continue to ask those kind
46:37of questions and collect that,
46:38share that information and figure
46:40out other clusters and people
46:41have the same kind of triggers.
46:42I don't think we know yet.
46:45You know have a strong enough
46:47evidence base to be able to say
46:49that reproducibly you know because
46:51some people are you know have even
46:53reported steroids helped them.
46:54Some people reported it's made them worse.
46:57It's it's hard to know but we need
46:58to like if we can get a bunch
47:00of people who are
47:00having different reactions then be
47:02able to compare them with many of
47:04the tests that that Kiko's running
47:06maybe that'll provide some insight.
47:08Can you talk about TNF?
47:09Mine was very high.
47:11Also there's overlap with
47:12reactivated viruses.
47:13Chronic Lyme.
47:14What's the spike protein and
47:16what have you attributed to
47:17other diseases and have you seen
47:19anemia in the long haul vaccine
47:21injured and positive Lyme IGN
47:23is has not converted to IG G
47:26you have any comments on that?
47:29Yeah. So we did measure TNF,
47:31it's one of our cytokine
47:34that we measured the and just
47:37to say to people just some people may
47:38not know a cytokine is a substance
47:40that's released in the course of
47:41a response for the immune system.
47:43I mean you can do better job definition,
47:45but it's just, I'm just assuming
47:46people like even that word might
47:48not be familiar to many people.
47:50Sorry. Yeah. Cytokines are,
47:51yeah, like I said, like you know
47:54language that does immune cells
47:55use to communicate with each other.
47:57TNF is one of the like loudest
47:59alarms you can imagine.
48:01TNF, Illinois 6, Illinois one,
48:03these are cytokines that is
48:05released during an acute infection,
48:07bacterial or viral.
48:09And if you have high levels of TNF,
48:12you're not going to feel well
48:14because it has many pleotropic
48:16impact throughout the body anyway.
48:19We did measure TNF and it's elevated
48:21in some people but not others.
48:22It wasn't one of the significantly
48:25different factors,
48:25but I wouldn't discount that
48:27as a part of the, you know,
48:29pathological process.
48:30And you know we did also
48:33look at antibody to many,
48:36many pathogens including Lyme
48:39antigens and we did not see any
48:42significant difference between the
48:44long haulers and non long haulers.
48:47But what I didn't get to my
48:50presentation is that we did see
48:52the Epstein biovirus reactivate
48:55reactivation feature in our antibody.
48:57So that that's one of the the highest
48:59feature after cortisol that is
49:02different in the long COVID patients.
49:08And and that's that was a great question
49:10a great answer just to confirm study
49:12found higher levels of cortisol long
49:14COVID actually it's a lower levels of
49:18cortisol in in the long COVID patients.
49:23This was nice professor sake even
49:24though I don't understand all the
49:25cell biology I find the president
49:26very engaging hope to hear from you
49:28more in the future that was just a
49:29a lovely and we recognized we need
49:31to work you know this is our first
49:33one and and we've got to figure out
49:34how to calibrate the communication.
49:36Just, you know,
49:37forgive us if we're still learning.
49:39This is about trying to figure out
49:41how we share information and we
49:42need to again continue to do better
49:44about how we how we communicate.
49:46Recognizing the people with very
49:48different levels of backgrounds and also
49:50many people still suffering brain fog
49:52and heart difficulty concentrating and
49:54it may be an hour presentation like this.
49:56You know we should just only be
49:58doing questions if people have can
49:59even put them up in in advance.
50:01We we want to be as helpful as possible.
50:03Realize that every time I get vaccinated
50:05I suffer many side effects for months.
50:06It's still ongoing.
50:07Nervous about getting the latest by Valent.
50:09I was told it's safer than
50:11actually getting COVID.
50:12What do you think?
50:16I'll take that as a clinician.
50:17I don't know if you have an idea,
50:17but I'm just saying like,
50:18I I don't know what to say in this case.
50:21I mean, I hear from a lot of people,
50:23they're, they're concerned about
50:24getting the vaccine because they've not
50:26had a great experience with the past.
50:28They're even more concerned
50:29about getting COVID.
50:30The vaccine, by the way,
50:31doesn't fully prevent COVID,
50:32as many of you know.
50:34It does mitigate the consequences
50:36of the COVID infection and it may
50:38decrease the infection rate by some
50:40percentage in in the same way,
50:41flu vaccine, you know,
50:42it doesn't keep everyone from getting flu,
50:44but it reduces the risk and
50:47reduces the consequence.
50:48This is just a really hard one.
50:50I don't think we want to be
50:51giving medical advice here,
50:53but just to acknowledge that that's a tough,
50:56tough one.
50:57There are a few questions
51:00regarding medical records.
51:01People are asking how like what is
51:03the timeline for them to connect
51:05medical records and what records do
51:07we like are we expecting from them.
51:09So the I think I'll just take this one.
51:11So the idea about for example the
51:121st I'll just take the survey.
51:14So you've been asked to fill
51:16out surveys in Kindred and then
51:17come into into this.
51:19And though all those service help
51:21provide profiling information and
51:24we're likely to then augment that
51:25information with more information
51:27as we learn more about people in
51:29the study and figure out what we
51:31need to dig into more detail on.
51:32And one of the innovations of
51:34the study is that rather than
51:36having you give us permission and
51:38then going to every healthcare
51:40system and then believe it or not,
51:42faxing them consents and then get
51:44then you know waiting weeks before
51:46they give us like paper copies of
51:48the records and then having to go
51:50through them and abstract them.
51:51You know we're using this digital way
51:53and the way the digital way was work,
51:54you connect to your records
51:56or wearables or everywhere.
51:57You've got your data assets,
51:59your personal data assets grow comes
52:01into your own cloud based account.
52:04One day sometime in the future we'll
52:05be able to actually show a viewer
52:07where you can see what you've got.
52:08You don't have that yet and Hugo but
52:10it comes to your cloud based account.
52:11Then you with your permission,
52:12it's going into the study and
52:14the way it works is once you've
52:16connected to your records that way,
52:18it's being refreshed all the time
52:19in your secure cloud based account.
52:21And if you've given permission
52:22for it to go into the study,
52:24it moves into the study and and kind
52:26of keeps the study all updated.
52:28If you ever decide you want to stop,
52:30you can just stop it. It just stops.
52:32If you ever decide you want to delete
52:34your records, you can delete records.
52:35But meanwhile your data assets
52:37are growing and all we're
52:38encouraging is the more places you connect
52:40to do you connect to your health systems,
52:42the health systems where you've gotten
52:44who have who have electronic records
52:46where we can make this connection
52:48pharmacies like like you know Walmart,
52:51Walgreens, Kroger's,
52:52anywhere you've got large major
52:55pharmacies or labs or wearables.
52:57The more data assets are growing that can
53:00help the study to have more insight into
53:02your journey in what's going on with you.
53:05So we're just you know and part of
53:06this we're trying to learn together.
53:08You could come and tell us it's
53:09too burdensome, it's hard,
53:10or what you're encountering is challenges.
53:12And we want to be able to hear
53:14that and figure out how we
53:15can make it better and easier.
53:16But the alternative is a
53:18really labor intensive,
53:20difficult and delayed process where
53:21everybody goes out and tries to get records.
53:24Then I can go out and get your records,
53:25but then more things happen
53:26and we got to go out again.
53:28But with this digital process,
53:30we protect your privacy.
53:32We protect your records only.
53:33Everything moves with your permission
53:35and then but stuff is constantly
53:37being refreshed and the study can
53:39continue to follow people over time.
53:41Once you are connected,
53:43it's automated.
53:44But that's the way we're trying to
53:46to to do this as a new approach.
53:48You look like and I just want to add too,
53:49because
53:50I think people are concerned
53:51about the Kindred side of it and
53:52that is how Kindred is built.
53:53So there's nothing that will
53:54happen to your records in Kindred.
53:56We we assure you that nothing
53:58moves without your permission.
53:59The only place we're sharing it
54:00is with listen if that's what
54:02you've given us permission to do.
54:03But that that is,
54:05you know foundational
54:07to what we are doing on Kindred. You it's
54:09they're your records and
54:12and that's the other things like
54:13Kinder doesn't own your data.
54:14Hugo doesn't own your data you own your
54:16data and and everything is permission
54:18based there's no back end selling nothing.
54:20It's it's it's a matter of trying to put
54:23people in a position where they gain
54:25agency over the data and then can be
54:27parts of studies where they're allowing
54:28that data to come into the study.
54:30But but that's the the way we're doing this.
54:33I I know we're we're we're at time and
54:34I know we could have probably done a
54:36lot of things better than what we did
54:38and there's lots of questions here.
54:40So I I think that we can be looking
54:41at these questions and kind of bring
54:43some of them together and then share
54:45them back through you know an e-mail or
54:49something to all the listen participants
54:51and they'll learn from these important
54:54questions that people have raised.
54:57I see lots of people here as I look down
54:59here that we have just so appreciative
55:01of all of you and that you're being
55:03part of this and helping us do better.
55:06And we can definitely answer these questions
55:09and and when we don't have answers,
55:10we can just be honest with you
55:11and say we don't know,
55:12you know and that we hope we will know soon.
55:14But I don't know, Kiko,
55:16if you I'm trying to just be respectful
55:18of your time and everyone's time.
55:20We have a lot more questions.
55:21Let me just say we're committed to getting
55:23information back to you with these questions.
55:25So don't think that we're
55:26going to ignore them.
55:28But Kiko,
55:28do you have anything you want
55:30to say at the end?
55:31Oh, yeah, absolutely.
55:32So I yeah, maybe I can do another
55:35one just to complete my presentation.
55:37If anyone's interested,
55:38I'm happy to come back and do it.
55:41The other thing is that, you know,
55:43we really don't know much about
55:45the vaccine injury and we're very
55:46eager to find out what's going on.
55:48So it's just a matter of starting
55:51the study and with your help
55:53understanding what's going on.
55:55And the idea generally is like we
55:57should have regular town halls.
55:59We should continue to you know interact with
56:03people who are you know you all of you.
56:05And and by the way you can reach out to
56:07us other times too like it's not just
56:09constrained by this what does it say?
56:10So listen study at yale.edu.
56:12Anybody can send us an e-mail at
56:14any time and you know the notion
56:16should be that we're we want to
56:18it's not like we're the researchers
56:19we don't want to hear from you.
56:21It's just exactly the opposite and
56:23we but we need to learn like how do
56:25we do this how do we make it better.
56:26How do we interact appropriately.
56:28How do we communicate clearly?
56:30And yeah, and Kiko,
56:31it's not like we've just regularly
56:33come back to this group.
56:34And if it's a ton of questions,
56:36then we can just spend the
56:38time answering questions.
56:39And I think also if we can figure
56:41this out where it looks more like a
56:42meeting where everyone's together,
56:43I think that'll make us all feel good too.
56:45That there's a a large group of people
56:47who are all part of this together.
56:50But just again, you know,
56:52I've said this to everyone and
56:53listened before, deep gratitude less.
56:55He's telling me there's 656 people.
56:57And listen now that's pretty good as a
57:00number of people growing by word of mouth,
57:04we've had you know I think
57:0680 some people on this call.
57:08That's pretty good percentage
57:09of people who are listening and
57:10we're we we're just open to ideas.
57:13What we really want to do is
57:14grow this community.
57:14We want to make it as big as possible
57:16bring in and more people get,
57:17the more we can learn from each other
57:20and also start really revving up this
57:22immuno phenotyping part for listen
57:24so that we can start to to have very
57:27detailed information that we can
57:29leverage to to bring some answers.
57:33So with that I I just like this isn't like,
57:36OK, we're over this is
57:38just like this hour's over.
57:39But we're going to continue to be
57:42involved in and and communicate
57:44and yeah thanks. Thanks Akiko.
57:46Great job and say something
57:48Bernali and and for everyone who's
57:50got questions and I'm looking
57:51at these questions is terrific.
57:52So this would be great for us
57:54to to get back to Bob.
57:55Thank you.
57:57Thank you everyone.