We're going to move on to our last speaker, Dr. Kwan. He will talk about CSF concentration of macrophage-macrophage inhibitory factors as a potential biomarker of vasospasm in subarachnoid hemorrhage. Thank you for sticking around. My name is Kevin Kwan. I'm a PGY-4 at Northwell. We're located in Long Island, New York. I'll be talking about the role of macrophage inhibitory factor as a potential biomarker for vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage. I have no conflicts of interest. As we all know, subarachnoid hemorrhage with relevance to aneurysmal subtype accounts for about 80%. It affects 30,000 people annually and has a very high mortality rate. Most of this mortality rate is directly due to complications with cerebral vasospasm or delayed cerebral ischemia. The mechanism leading to vasospasm or delayed cerebral ischemia is multifactorial and poorly understood. You can see here in the figure on the left, in the literature there seems to be four main arms of this, brain injury, oxidative stress, vascular pathology, and inflammation. We're most interested in the inflammation part of this mechanism. And we believe that we can exploit these pathways to develop novel biomarkers to predict patients who are going to develop cerebral vasospasm or delayed cerebral ischemia. One particular biomarker that we are very interested in studying is macrophage migration inhibitory factor 1. This is a pleiotropic cytokine. And in the pulmonary literature, it's been shown to contribute to pulmonary vasoconstriction, which we believe has similarities to what happens in the cerebral arterial vasospasm situation. Interestingly, erythrocytes are a major reservoir of MIF. And as I said before, it's directly correlating with the prognosis in patients with pulmonary arterial hypertension. There has been a previous group who did study MIF. They only looked at the levels of MIF in the serum of patients with aneurysal subarachnoid hemorrhage. We also showed in our lab that in hypoxic rodent models who were subjected to hypoxia that on PET imaging, if you use an MIF inhibitor, this abrogated the effect. And interestingly, MIF has been shown to be antagonized by thyroxine, which is a natural antagonist, which suggests potential therapeutic implications for future studies. So the purpose of our investigation was to assess the predictive value of MIF in patients with aneurysal subarachnoid hemorrhage. And we basically looked at vasospasm and delayed cerebral ischemia as our outcome. This is a prospective IRP-approved clinical study at North Shore Hospital. And we enrolled anybody who came in greater than 18 years of age with subarachnoid hemorrhage with radiographic evidence of an aneurysm and required an EVD drain placement. There were two types of patients in our analysis. There are subarachnoid patients, we had in about 25. And we also used as our control normal pressure hydrocephalus patients, which as we know, these patients received lumbar drains for about three days at our institution. And that was a source of clean CSF that we wanted to use for our analysis. MIF concentrations were quantified by ELISA. And our primary outcome measure was cerebral vasospasm. And our secondary outcome measures are listed there. This is just a busy slide, but basically I want to just mention that we looked at Montevideo-Fisher, Hunt-Hess, and WFNS in our subarachnoid patients. Notably, there was a high rate of infection, clinical infection in our subarachnoid patients. It's 24%, as you can see there. And majority of our patients were treated with craniotomy, 64%. Forty percent required a VB shunt. And patients actually did quite well at six months with MRI scores of two. This is a slide just showing that if you look at the MIF levels in the CSF of patients with subarachnoid versus MPH, it's significantly elevated in the subarachnoid population group. This is one of our key slides here. And as you can see on the x-axis, as you go temporally over the course of the patient's stay, you can see that the MIF level actually increases and peaks at day nine. And this, if we just ran a T-test between day three and day nine, and there was a significant difference in regard to the MIF concentration. This is another key slide on the left figure here, just showing that if you do a linear regression analysis of the onset of clinical vasospasm, you quantify a particular day for any particular patient. And you also pick the actual day that the MIF level was highest for that patient. You do a regression analysis for our 14 patients who went to vasospasm. We found a significant correlation with regard to the R-squared. And interestingly, you know, commonly we use in the ICU TCDs to predict vasospasm, but if you compare the similar, you know, day of peak TCD versus the day of peak MIF, that actually did not significantly correlate in our small sample population. This was an honorable concern, was because MIF is harbored in the erythrocytes, whether that would be an issue. So our samples were graded blindly, and we graded from zero to four, four being evidence of the most hemolysis and zero being none by the technician who ran the samples for us. And we actually found a linear correlation between the degree of hemolysis and the degree of MIF in our samples. If you look at radiographic evidence of hemorrhage on CT imaging, again, you see that with more blood on the CT, on the, with MF, modified Fisher scores of four, you also have increased levels of MIF, and that's significantly increased. And finally, looking at delayed cerebral ischemia, we did note an increase in MIF levels as well. This is just a potential caveat of our study, as I said, 24% of our patients had evidence of clinical infection, and unfortunately, MIF levels were also increased in this subgroup of patients and suggest that infection could actually be a potential confounding variable using MIF as a biomarker. So just in conclusion, we believe there's a significant correlation between the day of clinical basis mass and the day of peak MIF, and then you could possibly use this in the future as a predictive biomarker if you want to trend the average day that basal spasm could happen. Secondly, we believe that MIF levels were increased in patients with DCI as well, so you could also predict which patients are more likely going to develop DCI, and so perhaps you want to devote more resources to that patient population. In patients without infection, you could use MIF to predict basal spasm or DCI. Again, that's a potential caveat using this, and we believe MIF is a potential therapy target. As I said, thyroxin is a natural antagonist of MIF, and we also have a small-mock inhibitor, so this could be a potential drug therapy for this, and I just want to thank my group at North Shore. Thank you.

macrophage inhibitory factor

biomarker

vasospasm

delayed cerebral ischemia

subarachnoid hemorrhage