HIV infection results in marked alterations in the gut microbiota (GM), such as the loss of microbial diversity and different taxonomic and metabolic profiles. Despite antiretroviral therapy (ART) partially ablating gastrointestinal alterations, the taxonomic profile after successful new ART has shown wide variations. Our objective was to determine the GM composition and functions in people living with HIV (PLWHIV) under ART in comparison to seronegative controls (SC). Fecal samples from 21 subjects (treated with integrase strand-transfer inhibitors, INSTIs) and 18 SC were included. We employed 16S rRNA amplicon sequencing, coupled with PICRUSt2 and fecal short-chain fatty acid (SCFA) quantification by gas chromatography. The INSTI group showed a decreased α-diversity (p < 0.001) compared to the SC group, at the expense of increased amounts of Pseudomonadota (Proteobacteria), Segatella copri, Lactobacillus, and Gram-negative bacteria. Concurrently, we observed an enrichment in Megasphaera and Butyricicoccus, both SCFA-producing bacteria, and significant elevations in fecal butyrate in this group (p < 0.001). Interestingly, gut dysbiosis in PLWHIV was characterized by a proinflammatory environment orchestrated by Pseudomonadota and elevated levels of butyrate associated with bacterial metabolic pathways, as well as the evident presence of butyrogenic bacteria. The role of this unique GM in PLWHIV should be evaluated, as well as the use of butyrate-based supplements and ART regimens that contain succinate, such as tenofovir disoproxil succinate. This mixed profile is described for the first time in PLWHIV from Mexico.

Background: Methamphetamine (MA) use in people living with HIV (PLWH) has been linked to neurocognitive and behavioral dysregulation. We hypothesized that PLWH with active MA use (MAHIV) would show poorer cognitive performance, greater emotional and sleep burden, higher behavioral risk, and alterations in circulating biomarkers of immune activation and neuronal injury, relative to PLWH without MA use and HIV-negative Controls. Methods: Cross-sectional analytic study of 121 adults: PLWH with MA use (MAHIV, n = 40), PLWH without use (n = 42), and HIV-negative Controls (n = 39). Outcomes were ART discontinuation, physical activity, neurocognition (MoCA), depression (BDI), anxiety (GAD-7), sleep (PSQI), and substance use (ASSIST). Circulating biomarkers measured by ELISA: sCD14, neuron-specific enolase (NSE), S100B, and neurofilament light chain (NfL). Results: MAHIV participants had more frequent ART discontinuation than PLWH and the lowest physical activity. Chemsex with polysubstance use, condomless sex, and multiple partners were most prevalent in MAHIV. This group showed the highest anxiety and depressive burdens, and the greatest sleep disturbances. Global cognition (MoCA) was lowest in MAHIV, with significant deficits in executive function, memory, attention, and language; 82.5% had at least mild cognitive impairment. sCD14 was significantly higher in MAHIV than in PLWH and Controls, and NSE was elevated in both MAHIV and PLWH versus Controls. sCD14 correlated inversely with MoCA and positively with GAD-7 and BDI-II. Conclusions: Among PLWH, MA use is associated with greater ART nonadherence, syndemic mental-health and sleep disturbances, broader neurocognitive deficits, and elevations in circulating sCD14 and NSE. The sCD14–cognition and sCD14–mood relationships highlight chronic immune activation as a candidate pathway for neurocognitive and affective impairment and support sCD14 and NSE as potential stratification and monitoring biomarkers in MA-using PLWH.

Background: Methamphetamine (MA) use in people living with HIV (PLWH) has been linked to neurocognitive and behavioral dysregulation. We hypothesized that PLWH with active MA use (MAHIV) would show poorer cognitive performance, greater emotional and sleep burden, higher behavioral risk, and alterations in circulating bi-omarkers of immune activation and neuronal injury, relative to PLWH without MA use and HIV-negative controls. Methods: Cross-sectional analytic study of 121 adults: PLWH with methamphetamine use (MAHIV, n=40), PLWH without use (n=42), and HIV-negative controls (n=39). Outcomes were ART discontinuation, physical activity, neurocognition (MoCA), depression (BDI), anxiety (GAD-7), sleep (PSQI), and sub-stance use (ASSIST). Circulating biomarkers measured by ELISA: sCD14, neuron-specific enolase (NSE), S100B, and neurofilament light chain (NfL). Results: MAHIV participants had more frequent ART discontinuation than PLWH and the lowest physical activity. Chemsex with polysubstance use, condomless sex, and multiple partners were most prevalent in MAHIV. This group showed the highest anxiety and depressive burdens, and the greatest sleep disturbances. Global cognition (MoCA) was lowest in MAHIV, with significant deficits in executive function, memory, atten-tion, and language; 82.5% had at least mild cognitive impairment. sCD14 was significantly higher in MAHIV than in PLWH and controls, and NSE was elevated in both MAHIV and PLWH versus controls. sCD14 correlated inversely with MoCA and posi-tively with GAD-7 and BDI-II. Conclusions: Among PLWH, MA use is associated with greater ART nonadherence, syndemic mental-health and sleep disturbances, broader neurocognitive deficits, and elevations in circulating sCD14 and NSE. The sCD14–cognition and sCD14–mood relationships highlight chronic immune activation as a candidate pathway for neurocognitive and affective impairment and support sCD14 and NSE as potential stratification and monitoring biomarkers in MA-using PLWH.

Background/Objectives: HIV infection has been associated with an increased incidence of non-communicable comorbidities, including metabolic disorders. This phenomenon has been linked to gut microbiota dysbiosis, which involves not only changes in bacterial composition but also functional alterations in metabolite production. The objective of this study was to describe the impact of intestinal microbial metabolomics on the development of type 2 diabetes in people living with HIV. Methods: This study provides a narrative synthesis of current evidence addressing the role of gut microbiota-derived metabolites in immunometabolic regulation and their implications in HIV-associated type 2 diabetes. Results: Microbial metabolites play a fundamental role in regulating key physiological processes such as intestinal permeability, systemic immune activation, and glucose metabolism. Compounds such as short-chain fatty acids, tryptophan catabolites, secondary bile acids, trimethylamine N-oxide, and imidazole propionate have been shown to significantly influence immunometabolic balance. In people living with HIV, these microbial products may exert diverse effects depending on their chemical nature and the molecular pathways they activate in peripheral tissues. The interaction between dysbiosis, chronic low-grade inflammation, and HIV-associated metabolic disturbances may contribute to the early onset of type 2 diabetes beyond traditional risk factors. Conclusions: Recognizing the role of microbial metabolites in the context of HIV infection is essential to broaden our pathophysiological understanding of associated metabolic comorbidities. It also opens opportunities to develop more comprehensive diagnostic and therapeutic strategies that include modulation of the gut microbiota and its metabolic activity for the prevention and management of type 2 diabetes in this population.

People Living with HIV (PLWHIV) present an increased risk of developing non-communicable diseases, such as type 2 diabetes (T2D), making it crucial to optimize glycemic control and assess metabolic markers. HbA1c is considered the gold standard for evaluating glycemic control, while fructosamine (FA) offers advantages in assessing non-glycemic determinants. Discrepancies between HbA1c and FA are common and may be influenced by temporal factors. The Glycation Gap (G-gap) emerges as a tool to clarify these discrepancies. A cross-sectional analytical study was conducted involving PLWHIV with various glycemic statuses, as well as patients with T2D and controls. Sociodemographic data were collected along with blood samples to measure biochemical profiles and FA. HbA1c predicted from FA (pHbA1c) was calculated using a linear regression equation, facilitating G-gap determination. A positive correlation was found between G-gap and levels of VLDL-C and triglycerides (TG). Additionally, a negative correlation was observed between HDL-C levels < 40 mg/dL and a positive G-gap. These associations suggest that the G-gap may be a useful tool for metabolic evaluation in PLWHIV and a preventive method for identifying individuals at risk of developing chronic complications related to T2D.