Good afternoon. I'm Ashwani Singhal from University of South Dakota Avera Transplant Institute. I'm a transplant hepatologist. I welcome you all here and excited as you all are to be in person after three years or the third meeting after 2019 and we are going to have a unique SIG session which is a combination of alcohol liver disease and non-alcohol fatty liver disease. SIGs together put together this program on similarities differences and learning opportunities and this is the part one and then there is going to be a break of maybe an hour one hour and then we go back here to talk about the second part of the whole SIG session. So without any undue delay I would like to invite Mazen Nooruddin who is one of the co-moderators and chairs with me and JP Arab who is from London Canada. He's a transplant hepatologist and Mazen is from Houston and he's building a new Institute there called Houston Liver Institute and then we'll start the session now. So maybe Mazen you can start with a case presentation and introduction and then we can get the speakers here. Welcome everyone. I think most people are still trying to find their way like I was trying. So actually we united alcoholic liver disease and non-alcoholic fatty liver disease. We want to talk about similarities and differences and new innovations in this field. I just want to mention one quick thing we're probably not going to discuss the terminologies because this is something we're leaving to the leadership and the society leaderships so that's not meant for that rather just to talk about the two diseases. So I want to start with a case and put everything everyone to reality and what actually what we see in our clinic every single day. So this is George. He's a 49 years old Mexican American male. He presents to review lab results from recent physical exam and this is moving on its own and it's not coming back. It went back. So anyways he has a past medical history of type 2 diabetes for 15 days, dyslipidemia for two years, his mother had diabetes, father had hypertension. Social history he does not exercise but walks the dog daily. He works as a malpractice attorney. He drinks three beers a day and two glasses of wine with steak during dinners with clients when he's trying to sue doctors. Prior exam was normal except for central obesity BMI of 333. Symptoms he has right upper quadrant discomfort and his medication he's on metformin 500 milligrams twice daily and fish oil. So I'm sure every single one of you saw this patient or saw a similar George person. Those are his labs his ALT is 69, AST is 76, total is 0.8, albumin 4, platelet is 165 within the normal range, a little bit on the lower side LDL 130, HDL 39, A1C 6.9, triglyceride 240. This is his transient listography CAP 316 and stiffness is 8. So we're gonna ask a few questions again we are gonna keep going there's one hour break so this is the same session. In this first part we're gonna ask questions what is or are the underlying mechanisms? Is there an interaction between ALD and NAFLD and how do you assess these diseases non-invasively? This is the first portion of this meeting and again later we will meet and continue and with that I'll pass it to Dr. Arab to introduce our first excellent speaker. Thanks Dr. Nureddin. So our first speaker is Dr. Stefano Romeo from University of Gothenburg and he's going to talk about mechanisms and pathways of NAFLD. Please go ahead, thank you. All right, thank you very much for having me here today, always a pleasure. I will start directly with the talk. Okay, so I will talk about mechanism and pathways of NAFLD. So going directly into the problem, you see to the left the normal liver and then steatosis, ballooning, inflammation and fibrosis at the biopsy. What you see in all the four stages is just round-shaped circles and these are huge lipid droplets. This is triglycerides accumulating. So steatosis is definitely the hallmark of fatty liver disease. But it's not only the hallmark, so it's not only associated, it's actually the culprit of the disease and here I introduce you to do a triglyceride with the glycerol backbone and fatty acids that are esterified to the carbons of the glycerol. All right, so everything that changes the homeostasis of intracellular hepatocyte fat or triglycerides will just make some change in good or bad for the liver disease. Seems complex, but let's focus on the lipid droplets, the big circle there, yellow. So here you have the triglyceride that I showed you and when you have a negative energy balance, there are lipases there that allow fatty acids to get out of the droplets and then go into beta-oxidation for production of ATP and energy. This can also happen through lipophagy. On the other side, when you have positive energy balance, you have the synthesis of fatty acids and triglycerides. Fatty acids in the seroplants, triglycerides in the ER, and this is like a way for the cell to store calories and then they go in the lipid droplets. Finally, you have a pathway that it's only present in the hepatocytes that is the VLDL secretion. So triglycerides in the ER are packed with apolipoprotein B by MTTP and then they get out. And this VLDL in fasting condition was what the guy before had at 240 milligram per deciliter. So this is triglycerides coming from the liver. All right, you guys probably know I work on genetics. So these are the genes, the genetic variants that I think are the most, you know, accepted or replicated common and rare variants. And I will start, I guess, from what? PMPLA3. So PMPLA3 has a genetic variant that you see carers at the bottom right induce an increase in hepatic triglyceride content. The frequency in Europeans is 5% in homozygosity, but what you see is a tremendous enrichment in the frequency of homozygosity through the, all the way of the fatty liver disease in which nearly one in two of those that have hepatocellular carcinoma are homozygotes for that. And that gives huge other ratio, odds ratio for the disease, 12 for cancer as compared to the general population. All right, what does it do? Mostly it's a lipase and what it does is just esterified any of those three fatty acids from the glacerol, of the backbone of glacerol. And so this is how it works. We have the lipid droplets, we need energy, fatty acids needs to get out, we have PMPLA3, but we also have other lipases like ATGL, also known as PMPLA2. When it's needed, these hydrolyze fatty acids that then get out and then, you know, do what they have to do. But when the protein is mutated, it doesn't work. But it's not only not working, it also sequestrates this CGF58 that is an important enzyme for ATGL to work. So it doesn't work, it doesn't allow other to work. And so this, you know, gets stuck. So with PMPLA3 not working, lipolysis is not working properly. Now we go with TM6SF2. So genome-wide study 2014 from Helen Hobbs group found this gene associated with liver fat. So at that time, we didn't know if the association with liver fat would correspond to an association, a histology with inflammation and fibrosis. So we looked at it. And it does cause this increase in NASH when you have the variant and also advanced fibrosis. What was kind of unexpected was that it actually reduced carotid plaques. And to test this, we also look at a cohort of obese individuals and we look at the follow-up for myocardial infarction. And you see that, again, carriers had lower myocardial infarction. So this is just like completely what you would not expect. So a dissociation between NASH and myocardial infarction. But why is that? Well, we look at liver organoids, spheroids. You see how they grow nice after a week, becoming like a sphere. We use from donors carrying the mutant and the wild type and then expose them to different fatty acids. And these are really nice pictures. You see the orange is the fat. And you see that in low and high fat, carrier of the variant have more intracellular fat. And this recapitulates the human phenotype. So we thought we wanted to look at the VLDL secretion pathway. And so we look at apolipoprotein B in the media. You see that it's very much reduced in the mutant. Then we thought, okay, so does it get stuck in the cells or it's degraded? Well, it seems that it's degraded. So somehow TM6SF2 stabilizes APOB. It also changes the amount of lipids incorporated in the lipoproteins. So this is the model. Fat gets stuck in the liver and it does go into the heart. All right, so here, no VLDL secretion, another pathway causing NASH. All right, MBOT7, this also started with the GWAS on alcoholic liver disease and then found three genes, PMPLA3, TM6SF2, and MBOT7. So we thought, well, you know, these two are factors for NAFLD. Let's see whether they are also increasing the risk of fatty liver disease with MBOT. And so we look at it, biopsies, and it does increase the risk of steatosis, inflammation across the genotypes, and also fibrosis. So this is kind of important. And I also show you other common variants that are shared between NAFLD and alcohol, and this is about NAFLD and alcohol. So this is telling you that there is an overlap between the mechanisms of damage in both diseases. And I would say quite large, but if you think alcohol get, in fact, metabolizes as triglyceride in the liver. All right, we show that this is a transmembrane domain, sits in the ER and other endomembranes. We found that he has a catalytic dyad responsible for the function. And it's a loss of function. The variant was not a non-synonymous mutation. It did affect, it does affect the mRNA expression, so carries a lower of the MBOT7. And what it does, it's involved in the metabolism of arachidonic acid in the phosphatidyl inositol and arachidonic acid. And, you know, I will just go to the model that we built. So this is how it starts, the phosphatidyl inositol metabolism. How is it generated? It's generated as a PI with an oleic acid, 18-1. And this needs to get remodeled by phospholipase A2 that gets rid of the oleic acid in position 2. And then you have MBOT7 that remodels that, adding an arachidonic acid. And this end product, PIAA, is actually negative, has a negative feedback in the production of that. When we have the variation, there is less of that, less inhibition. And so there is a futile cycle that basically generates from PIAA triglycerides. So it increases triglyceride synthesis, another mechanism for NAFLD and NASH. All right, so give you just another slide on two variants. This, we found them with a genome-wide study in 21. And there's a GPAM. This is one of the enzymes responsible for triglyceride synthesis. And you see that the variants increase the risk. And also APOE, not any APOE, but APOE4, the one also increases the risk of Alzheimer's, is actually protective against fatty liver disease. Now, we have these eight genetic variations that solidly reduce or increase liver fat content. And if you look at the correlation of the, on how much they increase PDFF, so liver fat content on the x-axis, and how much they increase the risk of hepatocellular carcinoma you see on the top left panel, you see that this is like, you know, a linear relationship. So the more fat, the more risk for HCC. And to the right, you see cirrhosis, very similar. And as a negative control, I put you there colon cancer and all type of cancer. We did also prostate, breast. I mean, it's flat. So this really shows you that liver triglyceride content is deleterious to the liver. And pathways that affect homeostasis of triglyceride and hepatocytes are key for fatty liver disease susceptibility. And also, they cause the progression to cirrhosis and cancer. I wanted to really acknowledge my collaborators, especially Luca Valenti, that I've been working for for many years now, and also my group in Gothenburg, and the funding agents. And thank you. Thank you very much. Thank you very much, Professor Romero. Yes, if you stick around, we will have Q&A session at the end of this first part today. I want to introduce the next speaker, Dr. Pranuki Mandrekar. She's a professor at UMass. She has expertise in alcoholic liver disease. And we're going to switch gears, and she's going to tell us about the mechanisms and pathways for ALD and alcoholic hepatitis. All right, thank you very much. I'd like to thank the organizers for giving me this opportunity to participate in this SIG symposium and really highlight some of the mechanisms and pathways of alcohol-associated liver disease. So, chronic alcohol abuse is a major global health problem. I'm trying to find out how to progress. Okay, thank you. So, we know that chronic alcohol abuse is a major global health problem and has damaging effects on several organs. One of the most significant clinical outcome of prolonged alcohol abuse is alcohol-associated liver disease. ALD is characterized as a spectrum of disorders, including early fatty liver injury due to prolonged alcohol intake, which occurs in almost 90 to 100 percent of alcohol abusers, which then proceeds to alcohol-associated steatohepatitis due to progressive inflammation, and in some cases progresses to fibrosis and hepatocellular carcinoma. Some of the risk factors that are associated with ALD are listed here. Genetics, you just heard some of the similarities in the genes that are involved in ALD and NAFLD. Gender, obesity, and you'll hear more about that through the symposium. Nutritional status, high iron levels, drugs, as well as smoking status. So, just summarizing work over several decades in the ALD research field, pathogenesis of alcohol-associated steatohepatitis is a multiple-hit model. The general working model of alcohol-associated liver disease is that prolonged alcohol use compromises gut integrity, resulting in release of pathogen-associated molecular patterns that can activate the macrophages in the liver. I'm trying to see if there's a pointer. Is there a pointer? All right, that's okay. That activate the macrophages in the liver to produce pro-inflammatory cytokines, as well as chemokines, and these chemokines then result in additional recruitment of immune cells in the liver. The pro-fibrotic cytokines that are produced by some of the macrophages in the liver then activate stellate cells, resulting in fibrosis. In addition, alcohol metabolism also induces oxidative stress and results in hepatocyte injury and death, adding to activation of immune cells in the liver. So, one of the major focus in alcohol-associated liver disease recently has been to really understand this inter-organ cross-talk. I just told you about the direct effect of alcohol on the gut. It compromises the gut integrity, likely through dysbiosis, and through either PAMs, that is pathogen-associated molecular patterns, or microbial metabolites, as well as extracellular vesicles, can activate some of the immune cells in the liver. In addition to the gut, the brain is also an important organ that may contribute to ALD, likely through cytokines. Our group, as well as others, have shown that alcohol consumption induces neuroinflammation. There's also a sort of an understanding that there is a interrelationship between the gut and the brain that may contribute to ALD. In addition, adipose tissue, as well, contributes to alcohol-associated steatohepatitis, steatosis. So, just summarizing some of the mechanisms related to alcohol-associated fatty liver, you heard some of the mechanisms related to lipogenesis. Alcohol can affect SRA-BP1, as well as elevate acetyl-CoA carboxylase, inhibit some of the enzymes, such as the AMPK, the SIRTUIN-1, all leading to increased triglyceride accumulation. In addition, alcohol can also inactivate some of the key molecules important in fatty acid oxidation, as well as due to the changes in adipose tissue resulting in fatty acid release, there can also be a fatty acid uptake occurring at the level of the liver. In addition, dysfunctional autophagy has also been suggested to contribute to alcohol-associated steatosis. So, looking at some of the most important mechanisms related to inflammation, we know that progressive inflammation is associated with ALD pathogenesis. So, the initiation phase of these inflammation or inflammatory responses really is about the activation of the liver resident macrophage or the Kupfer cell that is activated through the toll-like receptors and results in induction of pro-inflammatory cytokines. It sort of acquires this classically activated M1 macrophage state. In addition, you will also find alternatively activated M2 macrophages that can produce anti-inflammatory cytokines and somewhat balance off the pro-inflammatory cytokines, but can actually contribute towards liver fibrosis. TGF-beta in particular, we know can activate stellate cells. In addition to the pro-inflammatory cytokines, chemokines such as CCL-2 can promote recruitment of monocytes from, or pro-inflammatory monocytes from circulation that can add to this entire inflammatory response and contribute to the progression of liver disease. More recently, there has been much work trying to understand the resolution phase in the liver and particularly in context with the role of the Lysicc-C-high or the pro-inflammatory monocyte-derived macrophages that can be converted to the Lysicc-C-low or restorative macrophages that produce anti-inflammatory cytokines, as well as collagen degradation molecules such as the MMPs, as well as regenerative growth factors. And this is some of the research that might lead more to our understanding of how we can reprogram these macrophages in alcohol-associated liver disease. In addition, neutrophils that typically are antibacterial, as well as protect in terms of and contribute to sort of liver repair, remove dead cells, or contribute to hepatocyte generation, in fact has been shown to contribute to liver injury in context with alcoholic liver disease by increasing or adding to the production of pro-inflammatory cytokines, ROS production, as well as formation of extracellular traps, the neutrophil extracellular traps. Another immune cell, the NK cell, which in terms of alcohol-associated fibrosis, has been shown to confer protection. More recently, there have been studies showing that there's an increased number of NK cells in compensated cirrhosis, and this may have to be further investigated in terms of the role of NK cells in progression of ALG pathogenesis. So here's showing you a snap cap of a number of different stress-associated pathways that can actually almost enter a crosstalk with either fatty liver pathways related to fatty liver induction, as well as inflammatory pathways that are induced by alcohol. Some of the pathways we know related to oxidative stress, ROS, can promote total active receptor 4 downstream, its activation. Some of the molecules related to proteostasis network, the heat shock factors, autophagy, as well, has been shown to be activated by chronic alcohol consumption. DNA damage response, as well, contributes to ALD and ER stress pathways and some of the molecules that are important in ER stress. So here is just showing you a stress-mediated, sort of, this crosstalk between stress-mediated proteostasis chaperones in context with alcohol-associated immune signaling. If you can see, some of the chaperone, Hsp90, is extremely important and is a chaperone in maintaining the function of some of the key molecules downstream of TLR4 to produce pro-inflammatory cytokines. And my group has actually shown that using inhibitors that have been tested in clinical trials for cancer are capable of reducing alcohol-associated liver disease by reducing some of the pro-inflammatory cytokines. Another important mechanism associated with alcohol liver disease is epigenetic mechanisms through either acetylation or methylation of histones, as well as methylation of DNA and RNA. And a number of microRNAs, as well as link RNAs, have been identified as critical mechanisms related to alcohol-mediated fatty liver injury, as well as inflammation. And here's a really nice table from a recent review article by Dr. Vijay Shah and Kao's group that really lists many of these microRNAs. So with all of this research that is ongoing in the field of ALD, all the mechanisms and all the pathways, there have been ongoing clinical trials that are focused on really three main areas. One is the anti-inflammatory sort of targets, knowing that alcohol-associated liver disease is really about progressive inflammation. In addition, regenerative agents are being tested, as well as really drugs trying to act on the gut-liver axis. Recent studies have also shown that fecal microbial transplantation cannot only reduce ALD, but also alleviate, have some beneficial effects in terms of alcohol use disorder. So despite all of this ongoing work, significant gaps still remain, and we hope to understand through this symposium how we can sort of try to identify new targets for this devastating disease. So here are some of the key takeaways that ALD is a multifactorial disease that involves complex cell-cell as well as organ-organ interactions. You have metabolic and stress pathways as well as inflammatory responses and epigenetic mechanisms are really central to pathophysiology of ALD, and that preclinical translational studies and some ongoing clinical trials are targeting some of these pathways. So with that, I'd like to thank everyone in my group and all my collaborators and my funding agencies. Thank you. Thank you, Dr. Manrekar. So now with the two elegant talks on pathophysiology and understanding the mechanisms of each disease separately, we move on to where the case Dr. Nooradin described or presented, where it makes relevant clinically. And to move into that section, the first talk will be how these two risk factors in George, the case was presented, interact in causing the liver disease, obesity on alcohol and alcohol on obesity. So to make that presentation, I would invite Dr. Gowre from IU, Indiana, to present on this topic. Sameer. Thank you, Dr. Singhal. Thank you, Dr. Nooradin for the kind invitation. I want to thank Dean Ashzyg also for having me. So these are my disclosures. We're going to start off by discussing the impact of NAFLD risk factors on ALD. Data suggests that obesity synergy with alcohol consumption does increase the risk of fatty liver. In these data from the Dionysus study, you could see on the far right hand that heavy drinkers who also had obesity had double the prevalence of fatty liver than heavy drinkers who were not obese. This point has been shown in many other studies, and when you stratify this synergy by sex, you see that the interaction holds both in men and women. An important note is that women are more susceptible to the effects of this synergy as lower levels of alcohol consumption. The incident of severe liver disease is also increased as a result of the synergy between the metabolic syndrome component and alcohol use at any level. If you look at alcohol consumption as a categorical variable, and here you see non-excessive alcohol use in the gray bars and excessive alcohol use in the black bars, you would see even moderate alcohol consumption in the setting of underlying obesity, in the setting of central obesity with increased waist circumference or diastolic obesity. With increased waist circumference or diabetes, the risk of incident liver disease goes significantly up when you have these components of metabolic syndrome. Now, the relationship becomes far more clearer when you look at alcohol consumption as a continuous variable. Here, too, you see that when the components of metabolic syndrome, whether it be a different BMI strata, including overweight and obesity, as well as central obesity and diabetes, you see there is exponential increase in the risk of severe incident liver disease even at low levels of alcohol consumption when these factors are present. Now, PMPLA3 and CAFI are well-established modifiers of the severity of NAFL. They also appear to modulate the risk of alcohol-associated hepatitis as well as its severity. We have previously observed that the frequency of the risk G allele for the PMPLA3 was more frequent in participants who had alcoholic hepatitis compared to the healthy controls. The other risk variants of established genes that Stefano just discussed, we saw some signal, but that did not reach statistical significance. Moving on to assess the severity of PMPLA3 in severe alcoholic hepatitis, you would notice that carriers of the PMPLA3 low-risk genotype, the CC, have lower frequency of severe alcoholic hepatitis compared to the patients who carry the GC and GG genotype. Interestingly, CAFI consumption actually reduces the risk of severe alcoholic hepatitis in both the groups. Now, the histological severity of alcoholic liver disease is influenced by an interaction of metabolic and genetic factors. This has been the theme, as you've noticed. In this study from Denmark with biopsy-proven ALD, independent variables that were associated with severity of histological steatosis were, in addition to active drinking, were metabolic and genetic, as you see, obesity, hypertriglyceridemia, the PMPLA3 genotype. In terms of factors independently associated with severity of fibrosis, the strongest predictor was actually insulin resistance, as measured by HOMA-IR. Other factors associated with severity of fibrosis and ALD were low LDL, DTM6SF2, age, as well as PMPLA3. So, building on these observations, it's actually possible to risk stratify heavy drinkers for the risk of developing alcohol-associated liver cirrhosis using a 3-SNP genetic risk score combined with diabetes. Here, in this study, as you see, 3-SNP genetic risk score combined with diabetes. Here, in this study, as you see, 3 large cohorts of heavy drinkers were used to develop and validate this 3-SNP genetic score. And as you see on the left-hand side of the panel, in the 3 cohorts, the initial area under the receiver-operator curve for this 3-SNP model were only modest. And when they looked at in the UK Biobank cohort on the right-hand side, you would see that it didn't, when they added BMI and coffee to the model, the performance did not improve significantly. But when they added diabetes to the model, there is significant discriminatory ability for this model for separating those at risk. If you look at the far right-hand side, you will see that patients who have high risk on the genetic risk score of over 0.7, who are diabetics, have over tenfold increase in the risk for developing alcohol-associated cirrhosis compared to those who are non-diabetic and have low genetic risk score. Moving on to discuss the impact of alcohol on NAFLD, several observational studies have evaluated the effects on NAFLD risk using ALT or ultrasound-diagnosed steatosis. As you could see, the signal is mixed. Some studies, notably, as you see on the first row, observed significant increase in the risk of NAFLD with even consumption of less than one drink a day in the setting of obesity. In the second row, you see that consumption of less than one drink a day with non-wine beverage increased the risk. Importantly, a study from Korea in the bottom row showed that there is increased risk of hepatic fibrosis with modest drinking as reflected by worsening FIF-4 and Nafl fibrosis score. Now, studies that evaluated the effects of moderate alcohol consumption on Nafl histology showed, in general, neutral or beneficial effects of MAC on Nafl histology, with two notable exemptions. One study used Mendelian randomization based on ADH1B GG genotype, which is associated with modest drinking, and showed increased risk for NASH and histological severity of Nafl. Another study looked at using longitudinal paired biopsies, demonstrated that while the risk for NASH is reduced with modest alcohol consumption, these patients who consumed alcohol modestly were less likely to resolve steatosis or NASH on follow-up. We recently looked at this in the NASH CRN database study, and we observed that modest alcohol consumption significantly reduces the severity of NASH in a dose-dependent manner. As you see, up to 28 grams of alcohol a day, there is dose-dependent decrease in ballooning, severity or frequency of ballooning, portal inflammation, advanced fibrosis, and definite steatohepatitis. We also examined the interaction of moderate alcohol consumption with the STAR2 allele of the ADH1B variant, which is associated with faster alcohol metabolism, and we noted that the patients who consumed alcohol modestly, who also had the STAR2 allele variance, experienced the highest risk reduction for NASH compared to those who consumed alcohol and had the STAR1 allele. The mortality in patients with Nafl is also increased with modest alcohol consumption, as shown in this study based on the NHANES database. As you see here, those highlighted in the orange line who consumed half to 1.4 drinks a day had better survival, both in men and women, than those who consumed less or more alcohol. Now, the problem is that those who consumed one and a half drinks or more a day had increased mortality, so very narrow therapeutic window. This study also highlighted the importance of other covariates that influenced the survival in patients with Nafl, including age, male sex, current smoking, physical activity, fiber consumption, as well as diabetes. Now, in the multi-ethnic international cohort of Nafl with biopsy-proven Nafl and advanced fibrosis, when they looked at the subset with Nafl cirrhosis, actually, moderate alcohol consumption was associated with poor outcomes, including worse transplant-free survival, increased risk of hepatic decompensation, and development of hepatocellular carcinoma. Now, the outcomes in patients with fatty liver that are affected by alcohol consumption are not only hepatic. There are also extra-hepatic consequences for that. As you see here in this elegant study from Finland, alcohol consumption significantly increases the risk of advanced liver disease, even at low levels of consumption in both men and women. It also increases the risk of cancer at very low levels of consumption, and it comes also with the benefit of reducing cardiovascular disease steadily, and in a J-shaped curve, it reduces all-cause mortality. The nadir for that J-shaped curve is between zero and nine grams of alcohol consumption a day. Now, when you do a subgroup analysis, it is important to note that these benefits on cardiovascular disease risk and all-cause mortality benefits were restricted only to never smokers. They were not observed in current or former smokers. So, to summarize, the risk, severity, and outcomes of ALD and NAFLD are modulated by the interaction of multiple factors, including metabolics, genetic, environmental, and behavioral factors. ALD and NAFLD patients are enriched with metabolic traits, and alcohol synergy with these traits results in poor outcomes. Data suggesting that MAC benefits on NAFLD come from observational study with narrow therapeutic windows. And finally, alcohol, coffee, body weight, and physical activities are modifiable factors that affect the risk and severity of ALD and NAFLD. Thank you for your attention. Thank you. Thank you very much. Thank you very much. Now, it's for me an honor to introduce Dr. Mason Redding, who is going to talk about noninvasive markers for diagnosis and prognosis of NAFLD. Again, it's great to be here. It's good to be in person. All right, so I'm gonna talk about the noninvasive markers for diagnosis and prognosis of NAFLD. This is an evolving field with many data since COVID, so buckle up, it's gonna be a lot of slides. Those are my disclosures. So the objective of my talk is to discuss noninvasive biomarkers in NAFLD and NASH patients addressing the following areas. Fibrosis biomarkers, we have evolving area that look for NASH and F2 and higher. And the reason why we look for these patients because those are the patients that they go into phase three registry trials and we wanna diagnose them noninvasively. The reason why NASH and F2 also because F2 and higher patients, they have increased morbidity and mortality in nonalcoholic steatohepatitis. So this is a large area right now with many research in it. And then I'm gonna move on and talk about monitoring response to therapy and how we can do that with noninvasive testing or NITs. And finally, I'm gonna talk about noninvasive testing and their correlation with clinical liver events on what's called now major clinical liver events or MALO. Let's talk about fibrosis biomarkers. And I just told you why fibrosis is important. There are multiple papers now showing F2 and higher correlates with morbidity and mortality. The New England Journal paper from the NASH CRN also testified to the previous data in a prospective manner and showed F3 and F4 patients are at the highest risk of clinical liver events. But since COVID, we had a good year in terms of some clinical pathways and guidance from our societies. For instance, the AGA recommended that high-risk populations such as those with type 2 diabetes and two metabolic risk factors to be screened for NAFLD, a step that we have not seen before in the US. And they recommend starting with simple screening with FIB4, we'll talk about in a second. Many of you know what's FIB4. And if the FIB4 fall in the indeterminate zone, patients should be referred for another test such as transient allostrography or blood tests such as TEST. And you can keep doing testing until you pin it down and you find what's the stage of fibrosis. If the score is low, the patients stay in the primary care and if it's high, they come to a hepatologist and the hepatologist usually doing more testing, we'll talk about them. Eazl also confirmed such guidelines and they're very similar to the AGA, starting with FIB4, which as you know, FIB4 is a simple test that you can get it on a CBC and a CMP, which is HAST, ALT and platelet. And there are two cutoffs, 1.3 less than that patient likely doesn't have advanced fibrosis and more than 2.67 patients likely has advanced fibrosis. And in between, it's a very important concept, we call it the indeterminate zone that we're not so sure and we need to do another testing. I crossed NAFLD fibrosis score not because it's not a good test, it's just because more societies guidelines are trying to simplify it and narrow it down to one test and currently that is FIB4. Caveat about FIB4, there's data showing that maybe in 65, we have to age 65 and higher, maybe we have to adjust the cutoffs and its performance in type two diabetes is being still studies as not as accurate. Now, people said, well, FIB4 is out there, we don't need further testings, that's not true. We probably need still research to get more accurate testing, but now we have the simple test that we can start with and it's cost effective. So this is the concept I told you about, you start with first NIT and NASH, now we know you need to nail it down and we get to the second test to narrow at least this indeterminate zone or to confirm even the high test results. And with two to three tests, you can pin it down. So don't be surprised we're presenting many tests to you because you need to use more than one. So we have a toolbox. ELF is a fibrosis test, is heuric acid, P3MP and TMP1, has been approved by the FDA and was approved for diagnostic purposes. Values more than 9.8 predict progression to cirrhosis and 11.3-ish predict progression to clinical outcomes. But it's also safe to assume levels less than 7.7 that is a patient that doesn't have advanced fibrosis and more than 9.8 this patient who has advanced fibrosis. Another promising test that is still not available commercially Pro-C3, which is type 3 collagen biomarker, fibrosis biomarker and has been combined with other parameters to increase its accuracy. I wanna tell you that machine learning is coming, it's evolving field. So this is a study we did as an example, there are many examples, but this is an example from our group where we had 1,300 patients with paired biopsy, transient osteography, as well as blood test. And we split them into validation and testing cohort, validation cohort and we did multiple machine learning test. And what we did, we looked for F2, F3, F4 and Nash and F2. So it's a granular little bit further than the FIB4. Now this is a caveat that those were 17 variables. So people said this is too many and FIB4 is much simpler. Again, this is more granular and machine learning is not supposed that you sit down and enter 17 tests. Rather, a machine should spit that out for you. Your Epic system, your EHR should spit that out for you and tell you what's the patient is. And the variables are all labs and demographics. There's no imaging in those, there's no histology. Indeed, let me show you the area under the curve. So for F2, F3 and F4, the random first model achieved area under the curve of 0.86, 0.89. For F3 and 0.89 for cirrhosis, if you compare it to imaging studies such as transient colostography, it did as well, if not better. Of course, AUC is not the only test we look for. It had very good PPVs, NPVs, specificity and sensitivity. Moving on to imaging, we know that imagings are very accurate here, like the clinical pathways are suggesting as a second test. But transient colostography, vibration transient colostography and MR listography have been shown to be very accurate. MRE is slightly more accurate. But also, there is an advantage that you can couple them with another test in the same machine. For instance, the CAP, you get the steatosis and the same MRI machine, you can get MRI PDFF reflecting steatosis and MRE will frict fibrosis. Let me move on to the NASH and F2 because this is a very important area. Patients in phase three trials now are getting biopsies. Can we identify these patients without a liver biopsy? And there are multiple studies. This is the NIS4 test that is a blood test that consists of micro RNAs in addition to other fibrosis markers and hemoglobin A1C. And a paper came out in the Lancet gastroenterology hepatology and it performed very well. But in this meeting, I see modification of the test so look for that test and its new versions. Also importantly, the Nimble Consortium published encouraging data on that NIS4. We published data on a metabolic test that we used 12 lipids in addition to BMI and AST and ALT. Actually, we present it in an abstract format and it's a revision now. And these 12 lipids added value to the BMI, AST and ALT and drove the AUC up to almost 0.8. And it did a little bit better than the FAST score by transient listography that I'm coming to in a second. Kathleen Corey from MGH did a very nice study on proteomics looking at NASH-NF2 in higher patients using eight proteins and had very good area under the curve. Indeed, she used that one protein that also had an excellent area under the curve. So proteomic is also an evolving field there. I wanna go back to the machine learning model that I showed you earlier and this is the AUC for NASH-NF2 and higher and the random forest and it was better than the FAST and had very good MPV and specificity. The FAST score, many of you know what it is now, it's by vibration control transient listography and SCAP as well as stiffness and AST. It has two cutoff values to rule in or rule out NASH-NF2 and higher, mimicking those that they are in our current clinical trials. There are research now on MRI techniques after the FAST came out. We said since the FAST can do NASH-NF2 and higher and since MRI-PDFF is more accurate than CAP, MR listography more accurate than the stiffness by fiber scan, let's combine them in logistic regression model and see which parameters will come out and AST actually came out along with PDFF and MRE and it performed very well in predicting NASH-NF2 in higher patients with area under the curve of almost 0.93. Now this is a continuous score. There's another score by the UCSD group from Rohit Lumba called the MAFEB which used two cutoffs for FIB4 and MRE and it predicts NASH-NF2 with very good accuracy as well as F2. There are many abstracts in this meeting comparing the two tests but both of them are very highly accurate. The CT1, multi-parametric CT1, it detects steatohepatitis signal as well as correlate with fibrosis and in this paper from CGH which was pooled data, it predicted NASH-NF2 and higher with area under the curve of 0.78. So tons of data on NASH-NF2 and higher that look like the clinical trial patients. Let's talk about monitoring treatment response which in my mind, it needs more research and more studies. It's not as good as what I showed you just in few minutes. So ALT, this is data from beta colic studies showed that ALT improvement correlated with improvement in histology. So as hepatologists, we all know that ALT is one of the, the continuous decline is a very good biomarker for liver disease and that has been shown in NASH. I think the best study that has been published thus far in IT and monitoring treatment response came in J-HEP in 2020 by Maru Rinella and what she showed in this study from regenerate study showed that ALT-AST-FIP4 as well as transient allostrography dropped in a correlation with fibrosis improvement and worsened in a correlation with fibrosis improvement. But there's one caveat from this study. The area under the curve of one test by itself was not that great which makes you think that you probably need to combine more than one to reach that treatment response accuracy or at least that correlates with histology that you hope for. So this is the transient allostrography correlation with treatment response. Also data that was presented in an abstract format by Vincent Wong showed a fast score here correlates with a drop in histology showing these scores that we are using also can be used to monitor therapies. MRI-PDFF has been the core stone of, the constant of the phase 2A data. A lot of studies use MRI-PDFF especially for drugs that target de novo lipogenesis and it correlated with histological improvement and we use the 30%. CT1 also has been used. A drop by 80 millisecond has been suggested to correlate with histology. So let me show you a response to therapeutic intervention. We have data on blood biomarker and those are the biomarkers imaging as well as a combination of the tests. Nevertheless, I think we still need more data in this area in particular. So the question is, as we saw on staging the disease that combining them will lead to better prediction, is combining NITs to assess treatment response helpful? I think so, but which one is a question that we need to find the answer for? Moving on to correlation with outcome which is what the regulators are asking us for to replace the liver biopsy. I think we have a good evidence of data. So this is an example of data from Stellar and Symtismap study where about 2,000 patient and baseline ELF, Nafl, Fibrosis score, FIB4 and transient allostrography predicted clinical liver events and outcomes with a very high hazard ratios. ELF indeed has been approved as a prognostic test so levels more than 9.8-ish predict progression to cirrhosis and levels more than 1.3 predict progression to clinical outcomes. CT1 also has some data on levels more, score more than 8.75 correlates to clinical outcomes but I think a lot of data comes from the MR allostrography. Our group showed the MR allostrography level of 6.48 correlate with decompensation. Very nice data from Elena Allen Mayo Clinic shows you how increase in stiffness lead to decompensation and it shows you by which degree. Viraj Mehra from UCSD collected these data from multiple centers and published recently a paper in gastroenterology showing that increased stiffness in MRE correlates with clinical liver events. And the MAFIP score also predict clinical liver events. And there's data in this meeting on MAST and MAFIP and clinical outcomes. Too many. And I get this question every single time I give this talk. So simplify it, putting it together. Patients who are at risk for non-alcoholic fatty liver disease, such as type 2 diabetics or two risk of metabolic syndrome, should be screened with a FIP4. After that, you can do ELF or transient listography. And those are the value. And this is when you refer to the hepatologist. Now, this is us. What do we do? We have a toolbox. We have to be creative. We did this with other liver disease. And use two combinations that you like. I think we need more data on that. But I showed you multiple combinations today. And I put some of the medications that are in the pipeline. So maybe you can start with those at a certain point. Indeed, many of us do that in their clinic. And monitor over time. And then repeat. And when you repeat, see if they are moving the same direction. And there's a response. You continue. If there's no response, partial response, you either add or switch. Maybe this will be the field in the future. But we continue to watch. So key takeaway message from this talk that NITs, I think they can stage the disease accurately, including NASH and F2. And we have strong evidence on that. Monitor response to therapy. We have encouraging data. I think we need more. We have good data correlating with clinical liver events. But we need more prospective data. And I think there's some in this meeting. And we hope for a reward with the liver biopsy, especially in phase 3 in the near future. Thank you very much. And so I'm going to present the next speaker. It's Maha Thiel from Odinese University Hospital from Denmark. And she's going to talk about non-invasive testing in non-alcoholic liver disease. So we'll switch gears. Thank you so much, Maseen. And I hope you are all now confused on a higher level after this storm of non-invasive tests. So I think my job now is to try to boil it a bit down with the focus of alcohol-related liver disease. And first off, I want to thank you for the opportunity to be here today. And first off, we are mainly debating advanced liver fibrosis when we are discussing which diagnostic targets to apply for early detection of liver disease in primary care. And I want to just pause for a second on this diagnostic target of advanced liver fibrosis. Because we published a study last year, and you can see the intermediate line were patients with moderate liver fibrosis, so F2 fibrosis. And in this cohort of alcohol-related liver disease, 20% of those with moderate fibrosis progressed to a liver-related outcome in four years. And this was honestly a big surprise for us that this intermediate group fared so poorly, and quite rapidly so. So you could consider actually in alcohol-related liver disease having a diagnostic target of significant liver fibrosis rather than advanced. However, what this graph also will show you is that the non-invasive test also holds prognostic power. So maybe we shouldn't focus that much on the diagnostic targets, but rather shift towards prognosis. And in the intermediate group who do progress, those were also patients with moderately elevated liver stiffness using FibroScan. So a FibroScan between 10 and 15 kilopascal progressed similarly as those with moderate fibrosis. The same was for the ELF test. And again, it was a surprise to us that the curves were so much overlined. We also did look at these intermediate patients for risk factor behavior during follow-up. And indeed, those that progress rapidly to liver-related outcomes are those with evidence of excessive drinking during follow-up. So that's definitely also something to consider. But OK, let's stick to the target of advanced fibrosis for a minute. And this is just a curve of the discriminative accuracy of the various non-invasive tests in alcohol-related liver disease. And in this study, we found that FibroScan using or transient elastography using FibroScan has a very high diagnostic accuracy with an area under the curve of 0.9. And that is even in an intention to diagnose analysis where we punish FibroScan for the unreliables and the failed measurements. The ELF test is also very good at discriminating advanced fibrosis from lesser stages of fibrosis. But some of the other non-invasive markers are also quite good. So Massine just mentioned this idea of looking at dual non-invasive tests, looking for are they congruent or are they discongruent. And in our clinic, if we have a FibroScan measurement and an ELF measurement, then my personal opinion based on the data is that FibroScan is probably more reliable. So this graph, you can see that in those with a false negative ELF test, the majority of them had a true positive FibroScan test. So FibroScan were elevated in those patients. And similarly, the red dots, those with a false positive ELF test, the majority had normal liver stiffnesses. So again, if liver stiffness is reliable, then it's a very good predictor of advanced fibrosis. We use in the clinic the ELF test in cases where we are in doubt of the FibroScan transient elastography or when it can just not be done. There has been one individual patient data meta-analysis on alcohol-related liver disease only, pooling 10 studies. And it's very clear that in the published studies, the optimal diagnostic cutoffs, they vary immensely from both for significant fibrosis and for advanced fibrosis. And this is probably two things. One is spectrum bias. The majority of studies are smaller and have been done in tertiary care centers. And the second is inflammation. So a lot of the studies that have been done have been done on patients with rather high levels of transaminases and bilirubin. And my personal rule of thumb is that if I have a patient with an elevated liver stiffness, but with transaminases two or three times the upper limit of normal, I'm a bit hesitant about the FibroScan because it may be false positive. For this SICK, I just updated our diagnostic data. So the article we published in 2018 were in 289 patients. And now I update it so it's the full cohort of 460. And you can see that the prevalence of advanced fibrosis in this cohort, because we recruit from primary and secondary care only, is far lower. And the area under the curve for FibroScan is really staggeringly good. But this is just the relationship between sensitivity and specificity. I want to zoom in a little bit on which cutoffs to use. So you can see here that 8 kilopascal is a very good cutoff to rule out advanced fibrosis. So it has a sensitivity of 100%, which means you can be almost certain that if your patient have liver stiffness below 8, they will not have advanced fibrosis. 10 kilopascal, which is recommended by the Bavino 7, is also good at ruling out. You will miss 6% of the true positives. The sensitivity is 94, but it's still pretty good. And 15 kilopascal is a good ruling cutoff with a specificity of 95. Going from advanced fibrosis to significant fibrosis, then it gets a little more muddy. So you can see that if you want to rule out significant fibrosis in a patient with alcohol-related liver disease, the liver stiffness needs to be almost normal, far below 6 kilopascal for ruling out. And a lot of people tend to say that 8 kilopascal is a marker of significant fibrosis. You will see this in a lot of publications in population-based studies. But I think this graph very clearly shows that, in fact, it's not. 8 kilopascal neither rules insignificant fibrosis or rules out significant fibrosis. It's a good marker to rule out advanced, but it's just not the same as saying 8 kilopascal is significant fibrosis. And this is the same in NAFLD. We mentioned FIP4, and I think FIP4 at the 1.3 cutoff in alcohol-related liver disease is also a good cutoff to rule out advanced liver fibrosis with a 90% sensitivity. However, it's not a good cutoff to rule in, for sure. And I also have some doubts about FIP4, which I will show you later, because I think, for screening purposes, it shouldn't be a standalone test. And I think Madison also very nicely showed this. So which cutoffs to use? Well, I like the Babino 7, Ruler 5. So 5 is normal, 10 kilopascal to rule out compensated advanced chronic liver disease, 15 kilopascal to rule in, and 20 and 25 kilopascal for increasing severity of portal hypertension. So 8 kilopascal, I like that for screening. Again, we want to rule out those with very severe disease who will progress rapidly. But we can retest in those who are just below. OK, moving on a bit to the prognostic part, because transient elastography also holds prognostic power. And you see here that the three-year cumulative incidence of decompensation or death just increases and increases for every 5 kilopascal stepwise increase in liver stiffness. This is for alcohol-related liver disease. But the same analysis has been done for NAFLD. And we see the same pattern, although the three-year cumulative incidences are lower in NAFLD than in ALD. And when we compare transient elastography with the other forms of non-invasive tests, we see that there's really three types moving away from the others in terms of prognostic accuracy, transient elastography, the ELF test, and other forms of elastography. In this analysis, we looked at two-dimensional shear-wave elastography. But point-shear-wave elastography, or AFI, will probably have similar prognostic accuracies. And I'm sure MRE also has. Unfortunately, though, we lack studies in alcohol-related liver disease using MRE. The other blood-based tests has acceptable discriminative accuracies for prognostication of decompensation or death. But they are not that bad. So obviously, they can be used as a form of first-line testing or in centers without elastography, they can be used. So FIP4 is good at ruling out. However, we have the issue that FIP4 is positive in far too many cases. And this is just these three risk groups that we, in the article from 21, used to differentiate people into. And you can see that 60% of the ALD cohort had a FIP4 above the age-adjusted cutoff of 1.3. So in that sense, we are referring far too many patients for subsequent testing. And we are also inducing fear. We are overestimating the risk of having liver-related incidents in the future in these patients. So we need to come up with something that has a second step which is more accurate than FIP4. Finally, I just want to show you data that are new on proteomics. We heard a little bit about proteomics in NAFLD. But in May, we published a study on liver and plasma proteomics in ALD. And we found more than 5,000 different proteins using mass spectrometry in the liver and more than 500 proteins in plasma. More than 400 of those proteins were found in both sites. And interestingly, 46 of them were co-dysregulated with a level of fibrosis stage. So these 46 proteins, I think, are very interesting from a pathophysiological point of view because they will likely be, at least some of them, be something we may target in the future. And you can have a look at this liver proteome atlas and see the different levels in both liver and plasma for every fibrosis stage. Moving on from proteomics to diagnostics, we assembled then proteomics panels for significant fibrosis. So again, the difficult fibrosis diagnostic target for any inflammation and for steatosis in the same cohort. And the proteomics panel were better than any of the other non-invasive tests that we compare them to, including elastography. And we also validated these findings in an independent cohort, finding, again, similar high discriminative accuracies for both significant fibrosis and inflammation. And when looking at the prognostic data, we found that these panels were very good at predicting not just liver-related events, but also all-cause mortality during a follow-up of four years. So I think the proteomics and other types of omics are very much the future. So to sum everything up, I think we have very robust evidence in alcohol-related liver disease in favor of transient elastography and also other blood-based established non-invasive tests. Elastography is highly accurate for diagnosing and prognosing. And I recommend using the 8, 10, 15, 20, and 25 kilopascal cutoffs for transient elastography. FIP4 can be used to rule out advanced fibrosis, for example, as a first step in population-based studies. But we should remember that we will kind of over-diagnose a large, large amount of patients, especially if we investigate those at risk of liver disease. And in the future, we'll see more omics-based biomarkers, I'm sure, but we'll also see biomarkers for monitoring and, importantly, for biofeedback. So we had a study presented at ILC showing that the act of testing increases motivation to decrease alcohol consumption among a screening population of more than 1,000 people. So the biofeedback aspect, we can really harvest as clinicians. And with that, I thank you for listening. Thank you. Thank you, Dr. Thiel, for that excellent presentation. I would invite all the other three speakers here to join us. We are starting the panel discussion, and you would all agree with me that we had great presentations and we look forward to a great discussion. So we have some floor mics all across the hall, so please use them. Try to identify yourself and then ask the question through the panel, whichever you have. Let me ask first question until Dr. Hufnagel comes. So, Dr. Thiel, excellent presentation. You know, we studied MRI heavily in non-alcoholic fatty liver disease, and we even use it as one of the primary outcomes in phase 2a studies, such as PDFF. We rely on MRE also here and there. Do you think you needed an alcoholic liver disease or you think fibroscan or transcendent allostrography is enough with other biomarkers? For fibrosis, I think that the discriminative accuracy are so high that it's... I'm sure MRE will have similar diagnostic accuracies, maybe even higher, but it's very tough to be higher than 0.96 for advanced fibrosis, for significant fibrosis probably. For the whole steatosis part, this is a bit more tricky because we have shown using CUP that steatosis in alcohol-related liver disease very rapidly disappears with alcohol rehabilitation. So, in a lot of patients, when we biopsy them, if they have quit drinking, we don't find any steatosis. So, in that sense, it's a bit more tricky for the steatosis part. Dr. Hufnagel. It's important to change the economics to be separate from the progress of the storm, from the activity of the storm. The Trump will accommodate the stress test. They don't want to see activity increase. And I think one approach to this is to look at your exceptions, your false negatives, false positives, and say, why? Why was the fib 4 high? Why was the stiffness high? And that list of reasons would be helpful for the clinician when they deal with a patient who has a high stiffness of the liver, but doesn't seem to have liver disease, for instance. So we have 20 minutes, so keep your questions short and answer also. I request the panel to be short so we can take as many questions as possible. I cannot agree more with Dr. Hufnagel. I think you're right. The activity is a little bit less teased out with the non-invasive testing, and we're trying to put the AST along with PDFF. I think the goal at the end is such a prevalent disease, and we're going to treat patients in a few years. Is there something close that can help us with that without doing liver biopsies? But I totally agree with your comment, Dr. Hufnagel. Dr. Thiel, can you give us the list of things? I have just a small comment is that it turns out they're also prognostic. So in that sense, maybe the diagnostic part is less important, because it's also a poor prognostic sign to have high activity. But other than that, I absolutely agree with you that for the treatment purposes, we would probably need to be better at separating the two. Microphone number 10. Hi, amazing talk. Andrew de la Torre, CarePoint Health, Hudson County, New Jersey. It seems to me that it's sort of like more of a progression. So I'm just curious. We've been talking about FIB4 for probably a decade. But what we did in our hospital is we have FIB4 incorporated with our CMP. So anybody who gets a CBC and a CMP has an age gets an automatic FIB4 score. And we use it as a screen. It's not obviously a, you're not going to do a whole lot with it other than maybe say, let's get an elastography. So you talk about proteomics, you're talking about $3,000, $4,000 for this, $3,000, $4,000 for that. FIB4 is free. I mean, so the problem is, the biggest problem when you're outside the world of liver disease, nobody uses it. So if nobody uses it, how are you going to find people who are high risk for cirrhosis? So I'm just curious. How many people have an EHR system that routinely gives you a FIB4 score along the lines of a GFR that we give to everybody? So I think that's where we as liver specialists needs to go, bringing tests like FIB4 to the mindset of the internist or the family practitioner so they're at least getting a FIB4. We can debate about the weaknesses and strengths of a FIB4. But if you don't get a test at all, all those cirrhotics are just out there. And then they'll show up in your ER four or five years later with their GI bleed, their hepatoma, or their ascites. Yeah, I think we totally agree with you. What we said is when we simplified the message, their clinical pathways ask in primary care and endocrine to screen with FIB4 simple test and then followed by another test if needed. Where the proteomics and all this, we're trying to tease out those NASH and F2 and higher in the research kind of continuing outcomes. I have to take another one, if you don't mind. Thank you so much for your comment. Microphone number three. Yeah, Scheinbaum Phoenix. Do we have any data comparing CAP scores with PDFF in terms of fatty content of livers? Oh, in alcohol? Non-alcohol. I think for an athlete, it's pretty sure that PDFF is by far the more accurate. OK. And there are correlation between the two. So there is correlation. And with the improved CAP, the smart exam and all this, the CAP technology is improving. So this now is around. Thank you. Microphone number nine. Thank you. I'm Dr. Nipun from PGI Chandigarh, India. So Dr. Naureddin, congratulations for the machine learning model which you developed. I have a question regarding this. You know, the precision of FIB4 depends also on the population you are trying to focus on. Say for an example, in Asian population, we have recently conducted a GoAsia consortium study where we found around 67% of discriminative accuracy of FIB4 in Asian patients across eight countries in across the Asian medical centers. So also in Indian data, we have previous studies showing poor accuracy of FIB4 area under the curve ranging around 65% to 67%. So should there be a population-derived cutoffs? This is question number one. Question number two is the accuracy is dependent upon the type of population, F2, F3, and F4, in your population. If you have more number of F4 patients, you're probably going to have more accuracy or more area under the curve for FIB4. So this is question number two. And machine learning, again, we have also validated that random forest is performing superior. We'll be presenting as a poster tomorrow. I guess I'll start from the end. That's why we did the random forest to look for easy, cheap tests that are more accurate. And I do agree with you that FIB4 has some issues. Indeed, I have a lot of issues with it. There's a nice paper from Hans Hagstrom showing that almost half of the patient in the low and indeterminate values, if you do it one time, they had outcomes eventually. And you have to beat it repetitively. So again, there are issues. But we have clinical pathways now. I think they are right about recommending cheap tests to screen for high-risk population after unawareness of this disease by primary case for many years. So I think we achieved this step. We have to continue with it. But I agree with your comments. Yaron, you want to ask next? Three? Three. Hi, Yaron Rotan from NADDK. A somewhat heretic question about the non-invasive tests. I think that the structure of sequential testing to trim down is effective in trimming down the number of patients that arrive to the hepatology clinic. And I'm wondering whether instead our goal should be to improve the sensitivity of the first test. Because 90% sensitivity of a first-line test is something that we would never tolerate. Remember the older people here, older, more mature, remember the days of hep C when we did sequential antibody testing. And the first test has to have almost perfect sensitivity. 90% sensitivity of FIB4 misses about 50% of serotics that never reach into the algorithm. So I wonder whether we're looking at improving accuracy instead of improving sensitivity of the first line. So did you indicate you're one of the mature? You already commented on my line. I think you're right with it. I like the sequential and the primary came in combo in hepatology clinic. If that answer your question quickly. I think the problem is before hepatology clinic. But for sure, we need to work on finding something that is better. I mean, it's so funny. FIB4 was developed for hep C in a tertiary cohort of, I think it was less than 700 or 600 patients. And we are still using it today. So for sure, it's outdated. But until we have something else, this is as good as it gets. I think we have a lot of questions on FIB4. I think both of the speakers made a point. Use it to rule out an advanced disease. And once you have a cutoff and above that, then try to find the next set of markers to then screen your patients for advanced disease. Microphone number 11. Yes. First of all, excellent lectures, one and all. I wonder if people could comment on, it seems that we tend to look at biomarkers as a static measure versus a dynamic measure. In other words, how we get to a certain point might be just as important as where we actually are. Is there data about looking at the change in whatever parameter about the prognostic importance of that? Great question. I think it's because we did not have so many data. There's an abstract from the NASCRN in this meeting. I think it's oral. Look at the changes of transient allostrography over time and its prediction for outcomes. So look for that. I think it's a very good study. Microphone 9. Yes. I'm Dr. Sareen from New Delhi. My question is to Dr. Maza, where she uses Bavino7, the rule of five, which was developed primarily for compensated advanced chronic liver disease, mainly for NASH. The problem of combining that for alcohol are twofold. Most of the people with alcohol would have raised AST, ALT, and they have inflammation. And secondly, these patients have a huge potential of reversibility. So in my opinion, and I would like your advice and others, that we should have separate cutoffs clearly for alcoholic liver disease rather than that. And looking at your own data, you have said 5.9. And I think that looks to me a little worrisome because general population cutoffs are six. So I want comments on these two. So I think we can use the rule of five for both NAFLD and ALD. There are two points to this. First, again, as I showed, it performs very good in ALD as well as in NAFLD, even better in ALD than NAFLD. Second, I think it's important to have uniform guidance. Again, we are debating whether GPs even know FIP4 and will even use FIP4. So if we start now coming up with etiology-dependent cutoffs that need to be tailored to an individual's risk factors, I think we are kind of blocking ourselves. So I think the uniforming of the cutoff that was done in the PAVINO 7 guidance is good. For ruling out a significant fibrosis, I mean, significant fibrosis is a very difficult diagnostic target. And I think this is what I tried to show, that you need to have normal liver stiffnesses, far below 6 kilopascal, to use elastography as a rule out. So really, we need to acknowledge that significant fibrosis is very difficult to diagnose. And with all fairness, I think he mentioned a point that I think you mentioned in your talk with elevated liver enzymes. So can you comment on it again? I think you guys are agreeing. Oh, yeah. So I think it very much depends on where you are seeing the patients. And a lot of the studies that have been done previously have seen the patients when they were hospitalized for abstinence treatment in alcohol rehabilitation centers. And so obviously, these will be very high drinkers with often high levels of transaminases. Whereas the average patient is not like that. The average patient have far lower levels of transaminases. And also, we need to acknowledge that they're not necessarily alcohol dependent. They do not necessarily have an addiction. So we have a large screening cohort in Odense. And only one in four have an audit score pointing towards addiction, whereas the other half has audit scores pointing more towards harmful use. So I think it depends on where you find the patients. But I think Dr. Sarin also has a point when it comes to the etiology of the disease. It's, for example, an alcohol. The impact of acute alcohol intake cannot be ignored in a patient who has a FibroScan reading of eight or nine compared to somebody who is abstinent. Similarly, Dr. Rubin said platelets could be low just because the patient is drinking. So I think that part has to be taken into consideration also. And I think there are cutoffs for both. I don't know for FIF4, but for FibroScan, there are cutoffs of when the patient is actively drinking and the patient is abstinent in terms of F1, F2, F3, and F4 readings. Let's take one more question. Yeah, we are almost on time. Three, and I apologize for the rest. Let's take, I've been waiting for some time. I'm here, a fellow at UCSF. Question for Dr. Etiel about the setting of where we can use a FibroScan. Do you recommend, because most of patients with alcohol use disorder usually just come to ED because of alcohol use disorder complication, do you recommend using FibroScan as a screening in even ED setting when they come with intoxication or any problem for alcohol? Or you think on that setting because of the inflammation, that may not be as useful tool? I think we should be careful about where we offer the testing. I think motivation is a very, very important part here, not just in alcohol, but also in NAFLD. And if patients with NAFLD and ALD are not motivated to enter into treatment or management of their liver disease, we shouldn't test them because then why does it matter? And I think in the emergency department, this is not the right place or time. So I would personally not have a FibroScan there. I would rather in the GP. Thank you. Thank you very much for attending the first part of this session. So at 3.30, we are going to come back for the second part. We are going to continue with the case of George that Dr. Nureddin present. And we are going to discuss about targets, treatment, and outcomes. So 3.30, everyone here. Thank you.

non-invasive biomarkers

diagnosis

prognosis

NAFLD

advanced fibrosis

FIB-4 test

ELF

NASH-FIB score

APRI

multiple tests

response to therapy

machine learning tests

liver disease markers