Teddy Salan, PhD
University of Miami
Co-Authors: Fernando M Moradel Cano1, Sulaiman A Sheriff1, Lisa J Reidy1, Dario N Ayala1, Ranya Marrakchi El Fellah1, Eva Widerstrom-Noga1, Suresh Pallikkuth1, Denise C Vidot1, Allan E Rodriguez1, Robert L Cook2, Varan Govind1
1University of Miami, 2University of Florida
Background: Delta-9-tetrahydrocannabinol (Δ9-THC), one of the main psychoactive components in cannabis, acts on the central nervous system through interaction with cannabinoid receptors that are densely distributed within brain networks, altering brain chemistry. However, despite increasing cannabis use, especially among people with HIV (PWH), few studies have investigated the direct influence of cannabis on brain metabolites.
Objective: This study aims to associate plasma Δ9-THC, 11-hydroxy-Δ9-THC (11-OH-THC), and carboxy-Δ9-THC (THC-COOH) metabolites with brain metabolite concentrations in PWH and people without HIV (PWoH). Brain metabolites were evaluated using our whole-brain magnetic resonance spectroscopic imaging (MRSI) technique for measuring N-acetyl aspartate (NAA; neuronal viability), creatine (Cre; cellular energy), choline (Cho; membrane turnover), glutamate+glutamine (Glx; neurotransmitters) and myo-inositol (m-Ins; inflammation).
Methods: Plasma samples and 3T MRI data were collected from 16 PWH (38±7.5 y.o.) and 17 PWoH (37.4±7.8 y.o.) who use cannabis. The protocol included whole-brain short-TE MRSI (TE/TR: 17.6/1551 ms; 17 minutes) and T1-MRI. MRSI data were processed using MIDAS software to estimate neurometabolite concentrations at 47 brain anatomical regions-of-interest (ROI) from the AAL47 atlas, using appropriate data quality criteria. Plasma samples were extracted using a solid phase extraction (SPE) technique and analyzed using a Gas Chromatography Tandem Mass Spectrometry (GC-MS/MS) to quantify Δ9-THC, 11-OH-THC, and THC-COOH. At each ROI, we performed Spearman correlations to associate plasma THC with neurometabolite level, and tested for homogeneity of variance between PWH and PWoH (significance at p0.05) was observed, this effect with stronger among PWH. Plasma COOH-THC positively correlated with m-Ins in multiple brain ROIs including caudate (rho=0.53, p=0.007), cuneus (rho=0.62, p=<0.001), occipital lobe (rho=0.55, p=0.004), and lingual gyrus (rho=0.43, p=0.03) with no differences between PWH and PWoH. However, Δ9-THC and 11-OH-THC correlated positively with m-Ins among PWoH, but negatively in PWH at the same ROIs.
Conclusions: Higher 11-OH-THC and COOH-THC associated with lower Cho and higher m-Ins, respectively, reflecting impaired myelinization and increased inflammation. However, Δ9-THC and 11-OH-THC had differential effects on m-Ins with higher inflammation in PWoH and lower inflammation in PWH. Further analysis should investigate whether plasma cannabinoid metabolite levels are associated with overall systemic inflammation, measured by plasma biomarkers, and how this relates to brain outcomes. We will also evaluate the effect of co-variates such as BMI, sex, frequency/duration and mode of administration.