 Welcome everyone. I'm Praminder Reina, the lead principal investigator of the Canadian Longitudinal Study on Aging. And thank you for joining us today. I would like to begin today's webinar by acknowledging that as a national study, the CLSA is located on lands that are home to many diverse Indigenous nations. We respect the treaties that were made on these territories and acknowledge the harms and mistakes of the past as we dedicate ourselves to moving forward in partnership with Indigenous peoples and communities in spirit of reconciliation and collaboration. Before we begin our session today, I have few housekeeping things to go through. Today's presentation is being recorded and live streamed on YouTube. Close captions are turned on to change caption settings, select captions at the bottom of the zoom window. If you have questions or comments, you can type them in the question and answer box at the bottom of the zoom window. However, please note that questions submitted in advance will be prioritized. If you have any technical issues, please use the chat box to inform our communication team. And finally, only the presenters, audio and video will be enabled throughout the webinar. Our agenda for today will include an update on the CLSA, followed by three presentations that highlight key CLSA findings and impacts of the study. As much as possible, our speakers have tried to incorporate the question you submitted into their presentations, but we had our work cut out for us. There were more than 500 questions submitted in advance. But our presenters, first presenter will be Dr. Christina Wilson is a professor in the Department of Epidemiology, Biostatistics, Occupational Health and Department of Medicine at McGill University, and a senior scientist at Research Institute of the McGill University Health Center. And Dr. Wilson is also a principal investigator of the CLSA. She leads the Neurological Conditions Initiative and the Veterans Health Initiative. She is also the director of the CLSA Data Curation Center and a site principal investigator of the Montreal CLSA data collection site. Our next speaker who will follow Dr. Wilson is Dr. Vanessa Taller. She is a professor in the School of Psychology at the University of Ottawa and a scientist at Brewer Research Institute where she serves as a site principal investigator for the CLSA. Her current research focuses on the impact of bilingualism on language and cognitive processing, development of neuropsychological testing material for detection of dementia, and changes in brain activity and cognitive impairment and dementia. Next speaker will be Dr. Virena Menek is a professor in the Department of Community Health Sciences in the Max Ready College of Medicine at the University of Manitoba. She is the inaugural site principal investigator of the Winnipeg data collection site for the CLSA. Her main research interests lie in the area of areas of healthy aging, determinants of healthy aging, social isolation and loneliness, and age friendly communities. Our final speaker will be Dr. Brent Richards is a professor, William Dawson Scholar and FRSQ clinician scientist, FRSQ is a Quebec Health Funding Agency at McGill University and a senior lecturer at King's College London, England, trained in genetics, clinical medicine, endocrinology, epidemiology and biostatistics. Dr. Richard focuses on understanding the genetic determinants of common age aging related endocrine diseases such as osteoporosis and diabetes. He's the co-lead of the CLSA biomarker working group. And some of the faces you see on the screen are our lead team that is spread across the country. And what I'm going to do is to take a few minutes to introduce you to some of our other investigators who are not part of the Manitoba, Ontario and Quebec. That's what we are targeting today. And these are the people from our other sites and we will be introducing them in future webinars. And we also have some slides here that introduce many of our coordinators across the country who you probably see all the time whenever you go and visit our sites. And these are the people who actually make this study happen. What I'm going to do is to go to the next slide and talk about a little bit of the history of the CLSA. In 2001, this was a long journey before we even started to engage anyone of you. 2001, there was a meeting that was held in Ottawa to think about designing a study of this nature that was in and we put in a grant application we were fortunate to receive the funding. And then we had our first investment in from the federal government to launch this study in 2009. So you can see here for eight, almost eight, nine years, we were just developing this study to make sure that that we will have a robust study as we get ready to implement. 2010 recruitment began baseline data collection began in 2011. CHR renewed our funding in 2015 so and then we reached our recruitment goal of the initial cohort in 2015 of 50,000 participants. Next slide please. So you can see here 10 years of data collection are happening in 2021 we are a couple of years late acknowledging that because of the pandemic. And our first data set for researchers to use was released in 2015 so over 10 years since the first data release would be in 2025 so as a part of your engagement in the CLSA or the for the past 10 years. I really want to thank you for participating in this study, and without your participation your commitment your dedication. We wouldn't have the data that we have collected to date, and we intend to collect for another 10 years. I'm going to pass on to Dr. Christina Wilson for giving you an update about the CLSA. Thank you. Thank you for parminder for that intro I'm always a little bit shocked when I see that we started working together in 2001. And here we are in 2023 with the success of the study, largely due to our magnificent participants and I'm so glad that that people are having the opportunity to be part of this webinar. So I want to just take a minute I've been tasked with talking a little bit about the nuts and bolts of the study and I hope I can explain a few things if you're if these are things that aren't clear. We did we describe that the study and not, you must be familiar with us calling it the CLSA as both a research study and a platform and some people say well what's the difference. Well I think the difference is that in a research study. There's a very clear plan with specific questions that are targeted and then what we collect should relate to these specific questions so we did that. We did that over those nine years when we were doing the planning, but what's a platform. Well, if you think about a diving platform so you probably all watch the Olympic games and you've seen people on the platform diving. Well the CLSA is a platform in that sense, it's been built, and then people can go up there and dive off using the data that's collected in the CLSA to answer many, many different questions so it's both a study and a platform. We're talking about allowing researchers, according to our very formal process of review to use these data, both in Canada and around the world to answer research questions I wanted to go sort of clarify the difference between a study and a platform and we're both in the CLSA. Next slide. So there are a lot of institutions and you've been introduced to a few people on this call. This is really a national collaboration, the institutions are very supportive of the CLSA. So these are just the logos of the different institutions, both universities and research institutes that are involved. Next slide please. The national and scope and I am always quite intrigued when I see a map of Canada and I see that the cities are all squashed down towards the border but the cities that you see there are where we have the data collection sites across the country. The dots that you see are really meant to refer to the telephone interviews so we're able to do telephone interviews anywhere in the country, obviously, but we can only do the in person assessments from individuals who are living close to our data collection sites, but it's definitely a national study. Next slide please. I wish I don't really have a pointer I don't think at this at this stage so that's a little bit of a challenge but anyway I'll just talk a little bit more about the platform things that you surely know from having read our participant newsletters. We started out with over 50,000 participants at our at recruitment and the individuals were aged between 45 and 85 at recruitment. I have questions that I went through all 500. And one of the things I want to just tell people is that there are no at this point there are no new participants being recruited, our recruitment ended in 2015. And so now this group of individuals are aging, you are aging I am aging as well as a researcher, and I just did a little, a little note on my piece of paper here and I think our participants are now ranging in age from mid 50s to mid 90s, which is really exciting for us that we're able to follow you over this extended period of time and we're looking forward to another 10 years. We have a big COVID virus sitting in the middle we all know that COVID happened and we all know that it did affect the way we were able to collect data in the CLSA, we pivoted very quickly to telephone interviews so that we could not only of you as participants engaged in the study, but I think we're very proud to say that we're able to keep our staff engaged by having them become telephone interviewers even though some of them weren't that before. So I think this is a testament to how we were able to pivot. And I do want to say because I want to also address several comments, several questions that came in. We are contacting participants we are continuing to do in home assessments, but contacting some of you maybe a little bit delayed because of the pandemic but we are looking forward to welcome you all to the data collection site if you're participating in the comprehensive cohort, or as part of the telephone interview if you're in the tracking cohort. So next slide Laura. So, there have been some enhancements to this platform remember my diving platform analogy. And what we've been able to do is we've been able to during the pandemic we were able to add a questionnaire study and we were had an amazing response from you with individuals and participants agreeing to participate in that. We were also able to launch a covert antibody study during that time, again taking advantage, not only of you of course but also of this platform to be able to get some real time information about a global pandemic. In very recent years we've added some other enhancements we're doing a memory study. We also have a healthy brains and healthy aging initiative study, and we have seriously implemented our proxy questionnaire for those participants who can no longer participate on their own, but need someone to help them. And there's that we also are had launched in 2021 a covert brain health study and I'm sorry I don't have time to discuss the details of each one of these right now but just to say that we're building upon this platform as we move forward in time. Next slide please. We talk about data collection, we have data collection on all of our participants through questionnaires where individuals, all of you are being asked to answer a large number of questions, and I have a little bit of a personal story to tell you here, hopefully won't take too much time in 2013. I had a phone call from my mom, and she said to me, I had a call from someone in Halifax, and they said they wanted me to be part of a study. And I'm not going to mimic my mother's Yorkshire accent, but she did say to me, is this your study love. So my mother, who's pictured here with my dad was a participant in the tracking cohort so I've seen both sides of the study. She passed away last year. But I also want to say that I was her proxy, so what have been able to complete proxy interviews for her. So the tracking cohort is a very important part of the CLSA. So, has been added new in this new follow up we've added some additional questions, and we were able to release the tracking data a little bit earlier than the data from the comprehensive participants and there's been a large number of publications and I know that our subsequent speakers are going to talk about that shortly. Next slide please Laura. So for the physical assessments for those of you who come into our data collection sites and battle parking and travel time. There are we all know that there are a lot of physical assessments that we're asking you to do and we've added in this wave of data collection wearables, and there are a few subsequent slides about that so that's what's been added new. First we have cognitive assessments as well as the bio specimen collection, blood and urine and this year we've added for a part for a part of the group as stool samples as well. So next slide. So just a minute to talk about the mobility trackers I'm really impressed when I go into our data collection site, and I see all these being set up and plugged in ready to hand off to the participants so we've included tick watch a thigh act to graph. And this is being asked of all comprehensive participants and I really appreciate those of you who've agreed to do this and have agreed to do this data collection at home. In between your in home visit and your data collection site visit. So next slide. So one of the sleep trackers I haven't tried this one out myself, but I know that the staff the Montreal data collection site have. So this is a headband, the muse, and there's also a risk act to graph and what we're doing here is tracking sleep quality and sleep patterns, and there'll be a subgroup of our comprehensive participants who are being asked to participate in this so 2360 out of the total number. Next slide. So briefly speaking about one of the things on the previous slides that the Western healthy brains and healthy aging initiative, we were able to obtain funding from the Western family foundation to add MRI magnetic resonance imaging studies and stool samples for this subgroup of comprehensive participants, and then the stool samples only for 6000 comprehensive participants and again, I want to thank those of you who have agreed or been asked and who have agreed to participate in this. For for for some of the sites I know you have to go somewhere else beyond the data collection site so it's much appreciated that you're given this extra time to the CLSA. This is the response to a number of your questions and I think this is a really excellent question to ask. So what's happened to the 51,338 of you that agree to participate. Well by the end of our second follow up for just seven to little over 7% of you had withdrawn from active data collection, although the vast majority consented to continue through data linkage. This is really quite a small number for such a large study, given what we're asking you to do just a little under 7% of participants have died since their baseline assessment. And this is one of the things that happened to me I completed the decedent interview on for my mother and I, I felt that she really would have wanted me to complete her data collection for the CLSA she was very proud of being a participant when I cleaned out our house I had to remove the, the magnet from her fridge that she got from the CLSA. So we have, we have to think about ways to try and prevent losses. And there were quite a few questions from people about not being contacted and I hope, hopefully it will be contacted soon. We've added some questionnaires that can be done online. For those of you who move outside of the area, if that's needed. And again, introducing the proxy questionnaire for a proxy who can actually answer the questions for a participant who for whatever reason decides that they're not able to answer questions themselves. Next slide please. So, there are a lot of publications, scientific publications and reports that have come out of the CLSA using data researchers who are using these data. And this is just a slide to show you a few of those. There has been publications on depression during the pandemic about informal caregivers. We've had quite a few publications on vaccine willingness just overall not just COVID of course but also influenza. There are researchers who've always also looked at the relationship between mild COVID and mobility problems. So you can see even just with these few examples. The scope of the data allows researchers to come in to use the data in their own area of expertise and answer recent questions that are of interest to them. And we do have a dashboard on the CLSA website that is interactive that you can go and take a look at that provides some of the COVID study results. Next slide please. So these are the some antibody study findings. This has been another question that people ask. More than 18,000 people provided blood samples even during the pandemic. So we're very grateful to that and we know that that was a hardship for many of you. Most of them were able to be tested. And for the presence of antibodies that indicated infection. Many of the samples were collected before vaccines were available. This was one of the main things that we looked at. And clearly the rates of positive findings related to SARS-CoV-2 increased over time in all the provinces. Okay, so younger participants were most likely to test positive, likely due to the fact that the older participants and people in Canada were probably staying away and isolating themselves a little bit more. And there are also results, additional results you can find on our website. Next slide please, Laura. So how are these data being used? Next slide please. So as I alluded before to researchers who are using these data, there are more than 500 research teams that have been approved to use the data since 2014. What's interesting, and I think this speaks well for the future of research and aging in Canada, more than a third are led by trainees. I think that's really important. This is a way that trainees under the supervision of senior researchers can access these data and perhaps even make studies using the CLSA data part of their career when they go into their full jobs. Most of the projects are based in Canada, but we now have research teams from the US, the UK, the Netherlands, Switzerland, and Australia who have learned about the CLSA, appreciate its value, and who are now using and publishing about results related to aging. And there have been over 320 publications. And I should say that the CLSA does review each publication before it's submitted to a journal to ensure that the data have been used for the project that was approved, and also that the description of the study is accurate. Next slide please. So these are just a few examples of the publications. So again, you'll see the variety, publications on nutrition, or in the development of high nutrition risk, publications on age-friendly components of municipalities, successful aging and social participation, genomic studies, genetic studies, season and daylight savings time on sleep symptoms. So it's just a vast number of areas. And then another paper that was recently published, these are all 2023 publications looking at persistent COVID symptoms in community living older adults in the CLSA. And all of these publications are listed on our website and you should be able to access them if you wish. Next slide please. So we've got a lot of media coverage, which is very exciting. We don't do this to get into the media, but we really want our results to be relayed in lay terms to the public, and we've had publications here from Inder New York Times, and also we've had publications in the Globe and Mail. So we've had publications both in the English Press and in the French Press. So that's very exciting because I think the uptake from these kinds, this kind of coverage is often larger, of course, than scientific publications. So next slide please. There have been some impacts on policy. We are connected with the World Health Organization and the CLSA data have been used in a baseline report on the decade of healthy aging. So that was a very exciting initiative that we were contacted, knowing the importance of the study and of your contribution that the World Health Organization was interested in this. And we participated with the COVID-19 immunity task force that was set up during the pandemic in order to do our COVID studies, at least one of our COVID studies, and we work very closely with the Public Health Agency of Canada, providing them with information. And sometimes they apply for data to do analyses of the data for policy reasons. Next slide please. Okay, so I think if I'm not mistaken that this is probably my last slide. We have to acknowledge the funding that has been received for this study. It is an ongoing activity to ensure that we have adequate funding to be able to collect these data and to prepare these data for research and also to be able to find the time and resources to reach out to participants through development of our newsletters and the dashboards on the CLSA. So it's very important to acknowledge the funding. We're largely funded by the Government of Canada through the Canadian Institutes of Health Research through the Canada Foundation for Innovation and also provincial governments and the universities. The Western Family Foundation, as I said before, has provided funding, COVID-19 immunity task force, the Jerebensky Research Institute of McMaster University, and also the Nova Scotia Health Research Coalition and the Public Health Agency of Canada. So I think if I'm not mistaken, Laura, who's leading us, this is my last slide, just saying thank you to all of you for participating and if there are family members and friends on this call, thank you for supporting the CLSA participants and thank you for being here. So I think I'm now charged with passing on the baton. I'm going to look in the chat now to see if I can answer some of the questions directly to you, but I'm going to pass you on to Vanessa Tallah, Dr. Vanessa Tallah, who's going to talk to you about cognition in the CLSA. So over to you, Vanessa. Thank you very much, Tina. So I'm going to share my slides. Can everybody see that I'm screen sharing. Thank you very much for being here to listen to all this information about the CLSA. My role in the CLSA, as Praminder mentioned, is that I'm the site principal investigator at the Ottawa site, and I'm also the lead for the psychological health working group, which includes the cognitive data. So that is what I will be talking to you about here today. I'll talk to you a bit about what the cognitive data even are, and give you a couple of examples of some of the work that's been published using cognitive data, and then go on to talk to you a little bit about the follow-up studies, the current research that we're engaging in, or analyses of the data. So I'd like to thank everyone for their, we received, I received many questions about the cognitive data. The majority of the questions relating to people had a lot of questions about cognitive impairment and dementia, and concerns about their memory and cognitive functions. So I will do my best to answer those questions for you as I go through the presentation. So let's start, let me just, let's start by just telling you what I mean by the cognitive data. So I'm sure that those of you who are participants are very familiar with the, with these tests that I'm going to talk to you about quickly. So everyone, there's a subset of tests that everybody in the CLSA does, irrespective of whether you're in the tracking or the comprehensive cohort. And then we have some tests that we do only with the comprehensive cohort, just because we need people to be present. And there are some that have materials that we need to do in person and do over the telephone. So everybody does the animal fluency test. You'll remember this one where you are asked to name all the animals that you can think of in one minute. And in the comprehensive cohort, we also do that test but using letters. So to name all the items that you can think of in one minute with starting with a given letter. So everyone does the mental alternation test so that's the one where you're switching between numbers and letters one a to be etc. And those tests are assessing what we call your executive function so these, this is sort of like your, your brains control center that you are managing your resources and your intention and so on. So, also for executive function people in the comprehensive cohort do a task called the stroke task. So that is the one where you're asked to name. You see colors and you see color words and then you see color words printed in a different color ink and you have to name the color of the ink so this is testing the ability to inhibit irrelevant information and name the color of the ink rather than reading the word. And also so that's executive function we also have some tasks looking at memory function. So in both both cohorts people do the auditory verbal learning test where you're given a word list you're asked to remember it immediately and then at a five minute delay, and also the prospect of memory test so this is testing your ability to remember to remember. So, in real life that looks something like, oh I need to remember that I have to buy some milk on my way home from work or something along those lines so in the way that we tested in the CLSA is by looking at whether so that's the test where you have to remember at some point during the testing session to take the money out of the envelope and give it to the examiner. And you, you are either asked to do it at a certain time or with the queue. And then finally we measure processing speed so that's the one with the computer screen where you're pressing your responding to items and we're looking at how quickly you're able to do that. So, these are the cognitive data that we collect and we also ask people so since follow up one we started asking people questions about their self perceived memory function. So those are questions like, Have you noticed any changes in your memory. Are you worried about those changes. And I'll talk a little bit about about that some work we've done using those data in a few slides. I'm going to use some examples now I'll first I'd like to say why we collect these data so I know people don't I hear that people don't like cognitive testing I've done lots of cognitive testing myself and I also don't like it so I certainly understand that and very much appreciate the willingness to do these tasks that they do not do not enjoy doing so why do we do this well first that allows us to track changes in people's cognitive function over time. And we can look at the, the effects of different events or different health conditions on cognitive performance. So I'll give you an example of that in a moment. We can identify factors that might help people maintain cognitive function. And we can also track the progress of people who are worried if they're losing memory function, even if their memory testing is normal so there's, there are people who will report yes and I feel like my memory is declining. And then when we look at their memory performance, actually, they are, they look fine so this is a really interesting question of what does that mean for somebody to have the self reported concern about their memory or cognitive function in the in the context of normal cognitive performance. I'm going to highlight now a couple of there's many studies using the cognitive data I certainly don't have time to talk about all of them, but I wanted to highlight a couple of studies that have been done using these data so this one that I'm going to talk about now about traumatic brain injury is some work done by my former PhD student Mark Bedard so he based his PhD work on CLSA data, and he was interested in traumatic brain injury and cognition. So traumatic brain injury is when somebody suffers a head injury that result in injury to the brain and often people will refer to a concussion which is a TBI. And so in CLSA we asked people if they have experienced TBI's in the past, and what he wanted to do was look at performance and cognitive testing and people who've had a head injury, both initially and then after three years so in his thesis he looked at the data from the, from baseline and from follow up one. And so, some people who experienced a TBI experience also loss of consciousness, some do not so he was also looking at that as a factor to assess the severity of the TBI. So he wanted to look at their cognitive performance and he was also interested in the role of social support as a predictor of preserve cognitive function so there have been some studies suggesting that social support is very valuable in terms of preserving cognitive function. It's quite unique to be able to do this kind of study with such a large group of participants and see if social support can help people maintain their cognitive function in the face of a challenge like a TBI. So, what he found was that people with a previous TBI at some point in the past, who had experienced a loss of consciousness with that TBI had lower cognitive performance and greater cognitive decline, and this is even years after the TBI so within CLSA we ask about lifetime traumatic brain injury, it doesn't have to be recent. So, this is as expected the brain injury will have impacts on people's cognitive function. But what was really exciting about this, his findings was that when he asked people about their perceived social support, that it suggests that he found that perceived social support can help buffer against this cognitive decline. One of the things is, if somebody reports that they have high levels of social support, they show less decline over the course of these three years, compared to people reporting lower levels of social support and this is there's different types of social support so CLSA asks about different, different subsets of social support, and what he found was that specifically or particularly emotional support seemed to help buffer against cognitive decline. This is really exciting because it suggests avenues for helping people preserve their cognitive function, even in the face of challenges like a traumatic brain injury. So, and I mentioned previously, subjective cognitive status so we know that there are some people that report that they're worried about changes in their memory or cognition, even though their performance on cognitive tasks is normal. You'll notice and we ask if you've noticed changes, and we also ask if you're worried about them so a lot of people the over 50% of people report that they have noticed changes which is understandable I would say that I feel like I've noticed changes in my cognitive function in the past few years my memory is not as high as it was when I was 25, but critically we also ask people if they are concerned about, about those changes so when we're talking about people who have what we call subjective cognitive decline, what we mean is people who say they are concerned they say their memory has changed they say that they're concerned about it. And then when we test them their performance on cognitive tasks is normal. So of course people whose cognition is declining or who have cognitive impairment. Also often report that they're concerned about about their cognitive about their memory performance but here we're focusing on the people who don't show any signs of cognitive impairment. So a critical question in research is what does this mean is it that the person is starting to decline, but the changes are too subtle and are not detectable yet with with neuro psychological testing, or it could be that the person is fine and they're just experiencing anxiety or concerns, but so this we would call the worried well. And so, typically when you look at people with subjective cognitive decline. There's a subset who are the worried well, and there's a subset who are what we would say in a stage where the patient knows but the doctor doesn't know yet that there's something wrong. So, we, one of the major goals and research is to figure out who of those people are on a trajectory to start experiencing cognitive impairment and who are not. We've, we've started asking people, as I said, in the second wave of data collection about their self perceived cognitive function so we can start to answer these questions. So, this is another more work done by a PhD student here at who was here at University of Ottawa at the time she was doing this work. The question was that she was trying to identify the bio cycle social factors that predict these concerns about cognition. So, why do we want to do this, well understanding the factors that predict concerns about cognition could help us design these things to assist people with these with these concerns. So, what she found was that physical factors surprisingly physical factors such as low levels of physical activity, hypertension problems with vision did not predict concerns about cognition, but really these effects were as cycle, psychosocial variables. So depression, perceived perceived support and personality traits so for example people who are more extroverted are less likely to have concerns people who are more emotionally stable or less likely to have concerns, people who are very conscientious this is again, reducing the risk of concerns. So, why, why is this important well when we when you're thinking about conceptualizing subjective cognitive concerns. It is really important to consider psychological and social factors so this can be relevant both in terms of building about what it means to have a CD or subjective cognitive decline, and also from a kind of clinical perspective when you're assessing someone determining how to how to think about their self reported memory concerns. So, what we're doing now is I we're trying to identify factors that influence the risk of subsequent decline and people with the subjective cognitive concerns, and also examining factors like perhaps social support that might protect against cognitive impairment. So this really actually addresses a lot of the questions that I received about what is it that we can do to help us I'm concerned people say I'm concerned about my memory. Is there anything I can do to prevent myself from, or reduce my risk of developing cognitive impairment so these are some of the questions that we're trying to answer now. There were, we were limited in our ability to really study dimension the early years of CLSA because people at baseline when they entered the study everybody was cognitively in fact so what that means is that, as the study progresses, we are going to see some of our participants developing cognitive impairment and dementia, and now really is when we're starting to be able to do more research looking at that population. There's just a couple a little flavor of some of the work that's being done so far with the the cognitive measures. And we have lots of other at ongoing work so in collaboration with my colleague Megan O'Connell at the University of Saskatoon. She's developed a method to detect changes in cognition using the CLSA battery so she's developed something that we refer to as the cognitive impairment indicator, which uses the scores that we have available from the cognitive testing to identify people who might be at risk of having cognitive impairment. So this is important because you know, sometimes somebody will get a low score you can start a single low score as indicating cognitive impairment so I'm sure you all know this from having done lots of, lots of cognitive testing sometimes you just, there's a test that you don't do well on for, for whatever reason maybe you're distracted or your brain kind of freezes don't for example produce very many items when you're asked to name all the animals that you can, but actually all the other neuropsych scores or the cognitive scores look fine so this is what we would call a spurious low score. So using this cognitive impairment indicator allows allows us not only to identify cognitive impairment within CLSA but also identify baseline like how many people show these types of spurious scores which can be very helpful for clinicians when they're, when they're working with clients in the clinic. So, and we can also use so a recent study that was just published, what was looking at shift work as so this is using this cognitive impairment indicator, and identified that shift work is a risk factor for exhibiting or being at risk for cognitive impairment so this is, there's a lot of huge possibilities of all of the factors that we can consider as potential risks for cognitive impairment and this work is, is just beginning so this is a paper that came out in just in 1923 showing risks of shift work which of course disrupts sleep and circadian rhythm so it's not good for cognition. Another really important piece of work that we've done as part of the cognitive group with Megan and others is developing norms based on this very large sample so what do I mean by norms well this is where. When you are seeing a clinician and they do cognitive testing on you they need to know what a normal score would look like or what they would expect your score to look like based on factors like age, education level, sex, and so on so we they will use norms to do that to determine if somebody looks like they're outside of normal limits on performance on a cognitive test, but oftentimes that the number of participants used to develop these norms is a little bit low so this the CLSA provides a really exciting opportunity to develop very robust norms based on this very large sample and so this is because we know that cognition is expected to change as we age there are some areas of cognition where you'll see changes we call this normal aging. So we're trying to determine when people's cognitive performance changes. If this is normal aging or if there's cause for concern and excitingly the norms are available in both English and French because many people complete their, their CLSA visits in French so this is really useful for clinicians across Canada. We are also looking to identify markers of cognitive decline and this will in the future will allow us to identify risk and protective factors for dementia. And we're also doing work so Tina mentioned the international nature of work with CLSA so a study we recently published harmonizing so there are lots of studies in other countries with large scale studies with older adults and we harmonized across those studies to determine the optimal way to ask people so this was related to the questions on subjective cognitive status to identify the optimal way to ask people about their cognitive function so because there's lots of different ways that you can do this and let you house your function compared to other people your age compared to yourself 10 years ago. Are you concerned about it etc so we've been able to use all of these data sets to to combine and figure out how those questions should best be posed. So, in conclusion, the cognitive data crucial component of the CLSA we're so grateful that you complete these tests. They allow us to understand the factors, driving cognitive health throughout the lifespan. This can help us assist people and maintaining cognitive health and also identify people who are at risk of cognitive decline. And our ultimate goal is to lead to better quality of life for Canadians and others as well, of course. So, that's my, my final slides. Thank you very much for your participation and also for coming here today to listen to us and I'm now going to pass off to Verena Menek who'll be talking to you about social isolation. Thanks Vanessa. Hello everybody. I'm assuming if people can't hear me they will let me know. I'll share my slides here. Let me go back. Yes, I am really pleased that I am able to share some of the work I've been doing on social isolation and loneliness. And let me introduce first of all my colleague here Nancy Newell. I'm an associate professor in the Department of Psychology at Branton University. So the two of us have been working on this topic who for quite a few years now probably well over 10 years in some form or the other. And we'll keep going with it. Moving off with some definitions, just so we're all on the same page. What do I mean by social isolation and loneliness. Imagine we have two people and I call them here, Lizzie and Tom. And the circles around those two people reflect their social networks. So the squares within the circles are the people in the social network. The people within the small circle are the people that are really the person feels sees a lot is close to the outer circle are also important people in the person's life and the different colors reflect different people. For example, red is for the partner spouse and the blue is for children grandchildren. And so we carry these networks through life with us. Now, when you look at the two networks that really very different so Lizzie has a lot of people in her social network. Tom has very few so probably we could argue. You might agree with me that Lizzie might not be socially isolated because she does have a lot of people around her that she let's say we've asked her that she sees a lot she has a lot of contact with but she does not. So social isolation then is an objective state of a lack of social contact it's something we can count we can count the number of people in the network. We can ask about frequency of contact and we can say that Lizzie let's say it's not socially isolated where this Tom is loneliness on the other hand, is a feeling it is an unpleasant feeling of being disconnected and feeling that enough contact not the type of contact that one would like. So looking at Tom, not a lot of people in the social network. Really we could say socially isolated. We don't know whether he's lonely, maybe he's actually not lonely at all maybe he's just happy with having very few people in the network. Even though she has a lot of people in her social network might actually be lonely, we would have to ask her the saying as the saying goes, we can be lonely in a crowd. Now, we know from a lot of research for many decades over many decades that social isolation and loneliness, both of them are health risks. Such as the few examples, they're associated with the decreased immune system increased risk of heart disease and stroke increased risk of dementia increased risk of depression loneliness in particular is very strongly related to depression and lower quality of life. We also know that social isolation is related to mortality so it increases the risk of mortality as much as smoking 15 cigarettes a day. Now that statistic that piece of information has been quite a bit in the media during the pandemic especially, even though we have known this for over 40 years since the early 80s so it's not a new finding at all. So we know social isolation and loneliness are bad, we've known that for a very long time the real challenge though is how do we connect people, what do we do about it. And that is where our work Nancy and my work has focused on so how can we get that socially isolated socially or lonely person socially engaged. And connected to the very many programs that are actually available out there that are that could provide some social contact. So, our project which we're calling targeting isolation has two main objectives one is to provide evidence based information about social isolation loneliness, but also about other aspects of aging about older adults and then train other connectors to identify and refer at risk older adults to resources in the community now. What do I mean by community connectors, a community connector is a person in the community who was part of their everyday work is in contact with older adults who might be socially isolated or lonely so think about a pharmacist pharmacists have a lot of contact with a lot of people. And they might actually be an older person's only contact as they pick up medication so that might be a person who could say well wait a minute there seems to be something wrong here. This person maybe is chatting a little bit too much what's going on. I'm not sure. So that person then that pharmacist that community connector could say, again, there's warning signs here. I'm not sure what to do this is not really my job right and I'm, you know, I'm a pharmacist I'm not a counselor. And then they would refer that person over to a community organization who could assess needs, and then connect the person with the appropriate resources. So we can do this project alone. So we are partnering with community organizations. That is forming what we call the aging well together coalition. And let me just briefly introduce the organizations activating active aging in Manitoba is an organization that focuses on active living healthy aging. The Manitoba Association of senior communities focuses also on social engagement that's an umbrella organization that helps active living centers and seniors groups with their programming. The transportation option network for seniors. Tons that focuses as the name suggests on transportation. Transportation is a really important piece of this whole puzzle because what if their programs out there in the community but the person can't get to them. It's a stock so we need to also work on transportation and then we have a no support services for older adults, and they provide specialized support services for all the people. So just to give a couple of examples they have a really interesting program called senior centers without walls it is programming for site socially isolated older adults over the phone. So all kinds of things that people can call in and have programming over the phone. We also have a befriending programs also a volunteer will will go into a person's home to chat with them and just for some friendly visiting. And overall we also try to raise awareness of the issue of social engagement importance of social engagement and as well as programs and so on. So that's us. Targeting isolation. So that's the work that Nancy and I do is very much based on CLSA. So CLSA provides a foundation for our work and why is CLSA so important for us well first of all it's Canadian data, and that's super important. But in some cases, given what we're interested in some of the basic statistics that we're interested in we can also have Manitoba specific data for our partner that's partners that's really important because they know what's going on right here in Manitoba and some of it we can even look at Winnipeg you know what's happening here. What is the picture of social isolation loneliness look like right here. CLSA also has a lot of questions on it and and and thanks so much for responding to all of the questions that we ask you, but there are questions around social networks, social support social participation. All of those are really important for us and loneliness of course. In terms of our work, those are really, really important. I think if you just the flavor of some of the things that is important for our partners. So, just to know how common our social isolation and loneliness in Manitoba. Okay, these numbers will not be that different in other localities in other provinces but again for our partners it's particularly important to know have been Manitoba figures. So, about 20% of Manitobans age 65 plus are socially isolated about 25% say they are lonely and this is pre COVID, and about one in three so about 30% something like that want to participate in more social that last piece of information is important again for our partners because it suggests that people actually do want to be more socially engaged. There's an opportunity there. If we only could get them hooked up. Now, we know life changed during COVID, we all know that we have gone through it and I think all of us have to some extent did to some extent become socially isolated. And many of us became lonely and CLSA has been, as was pointed out by Tina has been incredibly useful to show what just the magnitude of that impact was and so when we look at Manitoba figures. In pre COVID we have about 20% socially isolated people and then it goes to about a third 30% plus during COVID. Now, in and of itself, that doesn't surprise us because we all know that it was a real challenge to live through COVID. What is interesting though is how this will change over time as we get new data in so as we as you are willing to participate again in being interviewed. How do the numbers change are people recovering from COVID. And perhaps even more importantly, are there certain groups of people who do not go back to normal. And that we need to know about, and that the organizations that we're working with need to know about where the gaps where the challenges. We've also done research on risk factors so both our research and other people's research shows that social isolation loneliness is more common among people living with low income those with health problems, those experiencing life transition and losing a spouse or partner is a very major impact for example. So, in order to to group the these these risk factors we've come up with the acronym helps so knowing the risk factors helps. And we've came up we've come up with that just as a way of helping those community connectors. Remember some of these risk factors. And so again briefly they are health problems environmental factors would include things like having access to transportation, living in a safe neighborhood. Life transitions. Again, I mentioned loss of a spouse but there are other life transitions to the really important, like becoming a caregiver can be very isolating losing a driver's license can make a big difference. There are psychological risk factors for example what was self esteem and some people have certain negative ways about thinking about their relationships even if they have relationships and that can be detrimental. We have certain social groups like, for example, people on low income who are more likely to be socially isolated when lonely. Another thing we have been working on a great deal is to say, how can we. How can we tell our community connectors who they should refer to a community organization. Yes risk factors are important to know about, but not everybody who has a risk factor will be socially isolated and lonely so can we be more specific. And we have done Nancy and I quite a lot of research using CLSA on that but also combined with other people's research we have once again come up with a an acronym show somebody you cared. Let's say you see somebody that you think has some of those risk factors maybe there's some some warning signs there's some signal something is not right here. What is it that you should look out for the C stands for connections that relates to the loneliness. Does the person want more social contact. Are they lonely. They don't want to directly ask them if they're lonely, but you could ask, would you like to be around more people activities does the person lack meaningful activities. And the question here might be, what do you do for fun, would you like to do other things, other than what you're currently doing relationships. How do you get at social isolation. How much contact is the person have with friends family so how often do you see your family or friends might the family members might be a question here. Does the person have an emergency contact so are there social supports there if they're needed. And dwelling is, are they living alone, are they living in a safe neighborhood. So we just address a question that somebody sent our way. And that has to do with living alone and the question was is living alone, different from being living with a spouse. And my answer would be it depends, we have it here as one of the questions to explore, but in and of itself living alone does not need to be a problem, depending on the social network that the person has around them. A person can live alone but be very strongly socially connected and have social supports right now might have people to check in every day on them. They might go out a lot they had so there's a very strong social network where there is a problem is when a person lives alone and has no good social network and social support system. So, think about what would happen if the person falls, would somebody notice. Oh, as we've seen some in some recent disasters natural disasters like heat waves. They were all the people living alone and nobody knew. Nobody realized that they were in danger and some of people died. So, living alone is not the only thing. Of course, it depends really on other factors to social support and social network around them. So, what we tell our community connectors then if if you see some of these signs, the person seems to be lacking the connections, if three or more questions are causing you concern, refer the person over to a community organization. We have and targeting isolation then we have prepared fact sheets so everything I talked about is on our website you can access it there it has more information that I could go through we have reports. We have resources, various resources we also have videos we you can meet team up targeting isolation Manitoba who will talk you through some of the things I've talked about like risk factors on so on. So on, just to note that because we're working in Manitoba, our, some of the stats, the facts are Manitoba specific. So, just be aware of that if you're accessing the website from outside some of it is general but some of it will be Manitoba specific. Now to train community connectors we've also developed workshops so Nancy and I have given workshops we've given them for for example pharmacists occupational therapists physiotherapists and so on. But we've also developed e learning modules again they're accessible if you're interested in looking that you can look at them one is for health care professionals like pharmacists. And one is for community volunteers and again goes through what is social isolation. What are some of the risk factors what are some of those signs and then there's the referral information now. The caveat with this is that it is Manitoba focused, we are telling community connectors in Manitoba to refer over to a no support services for all their adults the organization that we're partnering. Why a no well because they're a partner of ours, but also because they have the capacity to call back the person when they're getting a referral, a referral. So when they get a referral they can call the person, they have the capacity to assess needs and they can then get the person in touch with whatever resources the person actually needs. So if you're looking at it from outside I would encourage it outside Manitoba I would encourage you to think about which organization would you refer somebody to is there an organization in your community that might make a lot of sense. So, that's it for me. Thank you so much for participating in CLSA, our work would not be possible without you. And for any of the information I talked about or other information go to targeting isolation.com, or you can contact me directly. And I will turn it over to Brent. You can share with you biological samples information. Hello everybody. Very nice to be able to present to the CLSA participants. I want to start off by expressing my gratitude for all of the work that has been done by CLSA participants to participate in this cohort. One of the things I have been working as a researcher interested in the genetic determinants of disease, and have been working with CLSA data for at least about the last eight years and I'm just going to share with you some of the insights that we've been able to make and try to provide this into a context which may be relevant to most of the participants on this call. I want to start off by maybe bringing some of you back to 1978, when in June, 30 boys went on a canoe trip and Lake Temiskaming, and 12 of them died. And one of the adults on the trip also died. And this was a tragedy at the time in Canada, and in fact was brought to a provincial commission. In this context, a thorough examination as to the causes of this tragedy was brought to four. And when people think about tragedies they often think well this person served served left into my lane in front of me or this critical decision was made that led to the death of these 12 boys. But what the commission actually found when they examined the causes of this tragedy is that there was no actual single cause of this tragedy. Rather, it was a confluence of respectors. And that was that these were inexperienced paddlers, they were in a moderate wind. There are moderate waves. Notice that these were not severe waves. These were moderate waves. They were paddling for four hours. So not a long period of time. They didn't sleep very well. There was cold water. There was no swim test. And there was only one adult. And this confluence of risk factors led to a tragedy, which actually changed the shape of outdoor education in Ontario and across Canada, and changed how people think about participating in outdoor activities. Because it became apparent that this was not just unique to this tragedy but actually was a common theme in many tragedies across Canada. And I'm going to share with you how a similar analogy can be made to actually risk of disease. I'm going to start off by talking about breast cancer. I'm going to talk about it because it's common. Almost everybody on the call will have known somebody in their life who has been impacted by breast cancer or maybe been a breast cancer survivor themselves. And when we think about what causes breast cancer, a lot of people tend to think about a specific cause. In fact, there's a very well-known example of a woman who had a single genetic cause, which led to her having a double mastectomy to prevent occurrence of breast cancer. When we think about most people who have breast cancer, we find that they actually do not have a single genetic cause, but actually they have a confluence of many causes. And so I'm going to take you through a little bit of a story today to tell you a little bit about how we have begun to think more and more about the major causes of diseases in our population and how these are actually confluence and mix of causes because most aging-related diseases caused by hundreds of little nudges. And some of those little nudges are the things that we eat, the number of times we go for a run, the number of cigarettes that we smoke. But a lot of that risk, and this varies by disease, but a lot of that risk is actually inherited as little tiny nudges from our parents in the form of our genome. So what I'm going to do is take you through a graphical demonstration of how we've been able to try to discern these little nudges over time and how we peer into the genome to be able to do so and what this means to you and your families. This is a map of the human genome. Each of these vertical lines is actually a chromosome. And this is the state of knowledge in 2005 where each one of these little pins represents a region of the human genome that was reproducibly associated with the risk of disease. And you can see that back in 2005, which was around the time CLSA was getting started, we knew very, very little. And then if we fast forward to 2020, excuse me, 2010, this map becomes much more dense. We start to see many more pins show up where we're reproducibly associating different regions of the genome with risk of common diseases. And if we move to 2020, this becomes very, very, very full. And in fact, I'm actually only able to show you some of the chromosomes because if I had to show you all of them, they wouldn't fit into one slide. And so how has this happened? Well, it's happened via the work that people like you have done, which is sharing your DNA as well as medical information so that we can map the regions of the genome that cause common diseases. And we have been able to understand that just like in the case of the Lake Tomiskaming tragedy, as well as most causes of breast cancer, that our risk of disease is predominantly conferred from a genetic perspective by tiny little nudges from many thousands of genetic variants that impact our risk. Now with that as an understanding, I'm going to move forward to try to explain to you how we can use this information to help our patients. And I'm going to frame this in three different categories. The first is how we can use this information for disease prediction, how we can use it for improving diagnosis. And the third how we can use this information to identify causes of disease. So let's get started and talk about disease prediction. So we'll focus on breast cancer. And this is very interesting slide. I was published a few years ago now and things have actually improved since then in our ability to be able to discern those that risk of breast cancer. And what the horizontal axis shows here is the age of a woman and what on the y axis shows here is their absolute risk of getting breast cancer. Most people do not contract breast cancer over their lifetime. But what these different colored lines do is they summarize the information across the genome, and what's called a polygenic risk score to be able to put people on different tracks for different absolute risks of having breast cancer. And you can see that if you're in the 99th percentile of risk, so it'd be a very, very high risk and your risk would be higher than 99% of the population that your risk of breast cancer starts to become appreciably high, even in your late 30s and becomes very high by the age of 80. Whereas if you're in the bottom one percentile of risk, this actually your risk actually never becomes appreciably high, where in most jurisdictions would suggest a mammogram until quite later in your life. And most people of course are bended to different groups, depending upon their, their risk. But what we can actually now do is quantify this risk through something called a polygenic risk score, which is just a fancy way of saying of counting all of those little nudges that we have in their genome and seeing who is lucky enough to have very few and who is unlucky enough to have many. And so you can easily think about this as a shared cumulative risk that that person has, just by collecting all of those little nudges that moves them along this risk distribution. What we can start to think about doing for these people is instead of just identifying people like Angelina Jolie, who are at risk for a single mutation, which increases importantly the risk of breast cancer, but identifying the very, very large proportion of the population, compared to those with a single gene mutation, who actually have a similar or higher risk of disease, but is much more common in the population because they're, they happen to be in the top 5% or the top 1% of the risk accumulation. And so I'll next talk about how we can use this information to try to improve diagnoses, and I'm going to shift to using genetic insights in the case of diabetes. I'm going to show you an example of how we can actually use the same type of polygenic risk score to differentiate between type one and type two diabetes. Why is this a problem? Well, many of you may know someone who has diabetes and you probably know more people who have type two diabetes. Type two diabetes is a disease that is often later on set in age and is often more driven by obesity. But about half of the people who develop type one diabetes actually develop it after the age of 18. I'm an endocrinologist, I treat people with diabetes all the time, and very early in their disease, it's very difficult to try to understand which type of diabetes they have. But interestingly, these two different diseases, type one and type two diabetes, have very different genetic risk factors. So we can actually quantify a person's risk of the disease, both type one and type two diabetes, and see if they are someone who more clearly has genetic predisposition to one type of diabetes over the other. And doing so can really help us to rationalize when the patient should begin on insulin therapy. So here is a slide where researchers have done this. They have done this by looking at two genetic risk profiles, one for people with type one diabetes, and the other for type two diabetes. And you can see that you can spread out these two populations quite nicely where some people overlap, but the majority you can actually paint them into more probably a diagnosis of type one diabetes, and this information I'm actually rolling out into our clinic right now at McGill University in Montreal to help clinicians and their patients decide which type of diabetes they have so that they can receive the appropriate therapies faster. The third thing that I promised to tell you about was identifying causes of disease, and this is a way that we can use human genetic information to be able to disentangle a lot of the causes and consequences of disease using some simple concepts that I'll describe to you right now. So oftentimes we're trying to understand whether or not a risk factor causes a disease, and here I'm going to switch gears to talk about osteoporosis. I'm actually going to use data from you to be able to show you these insights. We can measure a risk factor for a disease and we can measure these in the bloods and one thing that we have recently measured in approximately 10,000 people in CLSA is 1000 different metabolites and so some people on this call, your blood has been surveyed for 1000 circulating metabolites. And we're interested if any of these cause aging related diseases and I'm just going to show you the example of osteoporosis. So when we do that when we measure these metabolites and test if they're associated with osteoporosis, we should be really worried about confounders and confounders could be things like body mass index so having a high body mass index could influence in the body and could increase or decrease your risk of osteoporosis. And if we don't understand this relationship and this potential confounding factor, then we can draw spurious conclusions and doing so actually plagues a lot of our understanding of cause and consequences of disease. And so using the human genetic data that we've generated from your DNA, we can actually disentangle this problem by identifying genetic variation. So, some people have one flavor of a piece of DNA and other people have a different flavor of a piece of DNA that strongly associates with metabolites. And what we can then do is using the biological fact that these genetic variants are randomized in the population at conception. So whether or not you got a specific genetic variant or your brother or sister got a specific genetic variant is essentially a random process. And that random process breaks association with confounding factors. And doing so allows us to be able to test via these genetic variants their effect upon disease freeing ourselves of these confounding factors. And so we have done this recently using data generously contributed by participants on this call, and we were able to estimate the causal effects of 1000 metabolites on bone density, which many of you will know is the most important risk factor for osteoporosis. And we found that some of the metabolites had clear effects upon bone marrow density, such as all this metabolite here which I'll name which is called orate, which is found that individuals who had higher levels of orate had much lower bone marrow density. And, importantly, we can make a statement that orate influences bone marrow density causally, and is unlikely to be biased by confounding. And this information can be very, very helpful for therapeutic development, because we can actually identify targets that are causal in humans which is a difficult thing to do across the entire biomedical enterprise of information. Because it's very rare that we can actually make causal insights in humans. And therefore, being able to target something that actually causes the disease is much more effective than something that is actually just associated with the disease, or something that is actually caused by the disease. And so this is an example of how we've used your data to be able to gain causal insights in disease, providing us a platform for being able to undertake therapeutic interventions that intervene upon these metabolites and decrease risk of disease or its consequences. So I'll just summarize here. The first point that I'd like to make is that rapid advances in measuring millions of small influence on disease risk has allowed us to better identify individuals at risk of disease, clarify diagnoses, and help to identify causes of disease which can be used as targets for therapeutic interventions. This is only possible through large scale collections of data from humans such as you, the participants of CLSA and for which we are very grateful. I'll close by just reminding you that, in fact, most tragedies that affect our lives are due to a confluence of causes. And this is something that we're beginning to be able to quantify quite clearly using large scale human collections such as those afforded by DNA. And I, by the DNA in CLSA, and I look forward to answering any questions that you have in discussing in the Q&A session. So thank you for your time. Thank you very much, Brent, and thanks to all our presenters and attendees for joining us today. Before we close, I just wanted to share a few reminders. If you have questions about your participation or wish to update your contact information, please get in touch with us by phone, email, or through our website. You can always visit the CLSA website for the latest news about updates about the study and all the new publications that are coming out and you saw some of the highlights today. And we'll also appreciate you completing the feedback survey because this is important because we want to engage with you, but we want to make sure that we are giving you information that is of interest to you and you see the value of participating in a study like CLSA. All registered attendees will be emailed a link to the survey in the next 24 hours, so please fill it out. And finally, I thank you again for participating in the CLSA, your contribution and something Dr. Wilson mentioned at the beginning of the study, which is really important for a study like CLSA, that we have as high a retention as possible, because that's what makes these findings applicable to a general population. In relation to that, there were some questions posted on the on the chat and on the question answer how representative this study is. And the question was, because we only focused on 10 provinces and we didn't go into the territories. And I think Dr. Wilson did answer that question. And, but we use the Statistics Canada sampling technique, that's how we identify people. And the challenge is that, and other factors that we did not go on to the reserves to recruit people into the study because it requires a very different type of study. We work with the communities, and we are early on determined that if that type of a study was going to happen, it will have to be led by people who are from those communities. And, and the challenges of other parts of the remote areas in Canada was that there was hardly any infrastructure available to carry out the study like this so it was a logistical decision rather than a scientific decision. However, what we say is that our study results are applicable to the people, the regions from which we have selected the people from. And I think we still have few minutes left so I would like to open it up for questions just to remind me muting will remain on, but you can enter your questions into in the question and answer box, and one of us will try to answer those questions and I. And one of us answered some of your questions already as we were seeing, and hopefully, we haven't missed many, but if you have any questions, please type it in, and verena myself brand door Vanessa and Tina could take on any one of those questions. I'm trying to see. Sorry. Sorry, permission Jennifer, if no questions come up, you could talk about anything about impact, because there were a few questions about like impact in the community on the results of the study, but I see some coming in now. First of all, there was a question about the blood samples that you send during the co with the drop of the blood. We are not using that blood to do the studies that Brent was talking the blood collection that we collected from our participants then they come to our data and we need a large amount of blood to be able to do these studies, and that's the blood that was used that the blood that we received through. During the four which was a drop of blood that was only used to do the antibody studies. And some of the questions are related to scientific publications you can go to our website and many of those are listed there. I'm not sure I'm going to be. I'm following all the questions, but if anybody has seen other questions. I have a question about if I see a day we free see somebody with that risk are those that is that information passed on to my family doctor we don't do that because we don't have the consent to contact your family doctors. So in some cases, if there is a clinically relevant thing we see, and with the consultation with our study physicians we will contact you, and you can provide that information to your doctor, or you can give us the permission to contact them at that time Tina you have your Yes, I just wanted to respond to a question in the question and answer about the study is going for 10 years and is there a plan for it to go longer. I think I'll give the prestigious answer we hope so. But I have to tell you that there's a lot of discussion going on now. How can we continue this study to go on for longer than 10 years so I think in our most recent writings we say that it's at least 20 years. The other challenge we have is if the study does end in 2033, we have to figure out a way to securely store and manage the information that's been collected from all of you so this is a topic of conversations. And I do want to add something to that but we're seriously thinking about this. And there was a question from Mike about how does the CLSA population compared to the Canadian population in terms of education, a very good question. Even when we were selecting people we knew that we were getting people fewer people in the low education groups and as part of the design of the CLSA. We went to some of the dissemination area based on statistics Canada data and over sample people from the low education areas. And we're sure that we have a large enough number so we can do meaningful analysis that are applicable to to those groups of people. And we have compared our data with the census data, generally we and with some of the statistics Canada service that our population based representative some service. But we do have my few percentages lower people in our low education and low income groups and that is the nature of many of these studies because people from low income, low education groups generally less likely to participate. However, we have worked with statistics Canada to develop these statistical strategies to make our data more generalizable to the population by creating some weights that that one person from that low income group can represent 20 people. So we are using those strategies to see how we can make our data generalizable to the target population from which we selected our individuals. Is there anything else Tina you want to take on or others from the group. Okay, unmute. Someone asked if there are similar studies conducted in other countries and the answer to that is yes, and we are and from the, from the very beginning of planning the study we've been in communication with most of them to try and ensure that the what we're collecting is comparable with what they're collecting. So just to say yes we're completely aware of the other studies. But we are very proud of the fact that our study is one of the largest and most comprehensive of all the ages studies around the world. So Brent, there was a question I'm interested in metabolites and how they may bring about high blood pressure increase in cholesterol, and so and so forth you want to tackle that question. Yes, for sure. Yes, so metabolites absolutely can influence risk of high blood pressure they can also influence risk of type two diabetes and obesity. We have published on this and we have identified some metabolites that we believe are causal for cardiometric disease outcomes. The publication I believe is on the CLSA website. The last author's name is Chen and it's published in nature genetics and but that outlines some of those metabolite risk factors for cardiometabolic diseases. If you send out the email to us we can send you that publication that Brent was mentioning on that particular topic. There was a question about I'm thinking of diseases like schizophrenia rather than mental health. I think some of the diseases that are very rare, you probably need way more than 50,000 people to be able to look at them. Schizophrenia would be one of those diseases that CLSA might not have enough numbers. Secondly, people might likely to not participate in studies such as CLSA or stay in the studies such as CLSA so those studies have to be designed very differently to capture people with those neurological conditions such as schizophrenia. There was a question I'm interested in the fact that partners are not interviewed data is being collected on what you are being told by the participant without cross reference. That's a good question we debated quite a bit at the outset. Whether we can, we should have both partners collect data for multiple reasons some of them are scientific and some of them were logistic reasons that we decided that we were going to one person from a household. I don't know of any study that verifies questions across partners in relation to what is being answered and we are many times interested in your perception of your health, rather than by someone else. But as you know, many of you have given your health care numbers to us with your consent, and we use those numbers to with your permission link it with the health care registries data. So we can actually cross reference with your medical data to see what actually is going on in relation to health related factors at least. Tina, do you want to add anything to that. I don't think so. I think I mean I just want to say that how humbling it is to have so many of you coming to this webinar and asking your questions which were scrambling to try and answer and we will be repeat we've got all of these recorded so we hope that we can bundle some of the answers to these questions and circulate them to you but I'm just blown away this has been a wonderful experience I've learned a lot too. And this is a one quick question was there an outcome that was surprising to the research team. To me at least we did a baseline report for the CLSA. It was, it was widely publicized and we did it for the public health agency again and that goes back to the question that we're in I was talking about. You lonely when if you're married versus when you're living alone, and the question that surprised me and we I'm not sure how much that question has been dealt into was that run 20 or 18% of the married women reported being lonely. And, and that was an interesting finding and and I think it needs further exploration that you could be in a marital relationship and still feel lonely. So loneliness is not just because you live alone, it could happen in for multiple other reasons as well. But I know you want to tackle that one and further on that one or no. That is a really good example of exactly the difference between social isolation and loneliness. So you can be lonely in a crowd you can be lonely in a spousal relationship it depends on the quality of the relationship and there was a question from Philip Bartlett that I briefly addressed about spousal relationships we do not have questions around that oh I wish we did I really wish we have more questions but as you all know you're answering already so many questions and thanks so much for doing that. And we all would like to add more questions but there's only so much time you can give us. Another question I think we had around 1800 people registered for the webinar, and I saw around 500 people who are active on the webinar today. And, and this was only targeted for our participants in Manitoba, Ontario and Quebec. And so I don't know what percentage of the participants that would be who attended today we'll have to do those calculations later. But, but we are very encouraged to see this much interest in the middle of the day from many of you in relation to the CMSA. Any of these presentation will be available online. Yes, we usually have our web seminars posted on our websites. I think I think we have to we have come to the end of our webinar we have gotten a little longer than planned. So again, I want to thank you all of you for attending today and asking really insightful questions. And, and we hope you will continue to participate in the CLSA and, and participate in many of the sub studies that we are including to enrich our data to answer very important questions and somebody asked this question earlier on the what is the goal is to extend the life actually that's not the goal of the CLSA CLSA's goal is to keep people healthy as long as possible rather than just extending life so it is about health span. And, and if, and that's what most of our research is trying to achieve. So thank you again, thank you to the all the speakers, they did a wonderful job. And I learned a lot as well from each one of you.