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Open Access

Peer-reviewed

Research Article

HIV, the gut microbiome and clinical outcomes, a systematic review

  • Rachel Mac Cann ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    rachelmaccann@svhg.ie

    Affiliations School of Medicine, University College Dublin, Dublin 4, Ireland, Department of Infectious Diseases, St Vincent’s University Hospital, Dublin 4, Ireland, Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin 4, Ireland

    ⨯
  • Ellen Newman,

    Roles Formal analysis, Investigation, Methodology, Software, Writing – review & editing

    Affiliation Department of Infectious Diseases, St Vincent’s University Hospital, Dublin 4, Ireland

    ⨯
  • Declan Devane,

    Roles Data curation, Methodology, Writing – review & editing

    Affiliation School of Nursing and Midwifery, National University of Galway, Galway, Ireland

    ⨯
  • Caroline Sabin,

    Roles Supervision, Validation, Writing – review & editing

    Affiliation Institute for Global Health, Universitay College London, London, United Kingdom

    ⨯
  • Aoife G. Cotter,

    Roles Supervision, Validation, Writing – review & editing

    Affiliations Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin 4, Ireland, Department of Infectious Diseases, Mater Misericordiae University Hospital, Dublin 7, Ireland

    ⨯
  • Alan Landay,

    Roles Supervision, Writing – review & editing

    Affiliation Department of Internal Medicine, Rush University, Chicago, Illinois, United States of America

    ⨯
  • Paul W. O’Toole,

    Roles Supervision, Writing – review & editing

    Affiliation School of Microbiology & APC Microbiome Ireland, University College Cork, Cork, Ireland

    ⨯
  • Patrick W. Mallon

    Roles Conceptualization, Investigation, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliations School of Medicine, University College Dublin, Dublin 4, Ireland, Department of Infectious Diseases, St Vincent’s University Hospital, Dublin 4, Ireland, Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin 4, Ireland

    ⨯

Abstract

Background

Effective antiretroviral therapy (ART) has improved the life expectancy of people with HIV (PWH). However, this population is now experiencing accelerated age‐related comorbidities, contributed to by chronic immune activation and inflammation, with dysbiosis of the gut microbiome also implicated.

Method

We conducted a systematic literature search of PubMed, Embase, Scopus, Cochrane reviews and international conference abstracts for articles that examined for the following non-communicable diseases (NCDs); cardiovascular disease, cancer, frailty, metabolic, bone, renal and neurocognitive disease, in PWH aged >18 years. Studies were included that measured gut microbiome diversity and composition, microbial translocation markers or microbial metabolite markers.

Results

In all, 567 articles were identified and screened of which 87 full‐text articles were assessed for eligibility and 56 were included in the final review. The data suggest a high burden NCD, in particular cardiovascular and metabolic disease in PWH. Alterations in bacterial diversity and structure varied by NCD type, but a general trend in reduced diversity was seen together with alterations in bacterial abundances between different NCD. Lipopolysaccharide was the most commonly investigated marker of microbial translocation across NCD followed by soluble CD14. Short-chain fatty acids, tryptophan and choline metabolites were associated with cardiovascular outcomes and also associated with chronic liver disease (CLD).

Conclusions

This systematic review is the first to summarise the evidence for the association between gut microbiome dysbiosis and NCDs in PWH. Understanding this interaction will provide insights into the pathogenesis of many NCD and help develop novel diagnostic and therapeutic strategies for PWH.

Citation: Mac Cann R, Newman E, Devane D, Sabin C, Cotter AG, Landay A, et al. (2024) HIV, the gut microbiome and clinical outcomes, a systematic review. PLoS ONE 19(12): e0308859. https://doi.org/10.1371/journal.pone.0308859

Editor: Wan-Long Chuang, Kaohsiung Medical University, TAIWAN

Received: May 15, 2024; Accepted: August 1, 2024; Published: December 9, 2024

Copyright: © 2024 Mac Cann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This work was performed within the Irish Clinical Academic Training (ICAT) Programme, supported by the Wellcome Trust and the Health Research Board, the Health Service Executive, National Doctors Training and Planning and the Health and Social Care, Research and Development Division, Northern Ireland. Award Number: 203930/B/16/Z) | Recipient: R Mac Cann.” In addition, we have amended the role of the funder in this statement to read “ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

With effective antiretroviral therapy (ART), many people with HIV (PWH) are now achieving a life expectancy approaching that of the general population [1]. Accumulating evidence points to accelerated aging phenotypes in PWH, with increased risk of several age-related non-communicable diseases (NCD) observed in both resource-rich and limited care settings [1–4].

Unresolved chronic inflammation has been linked to the development of NCD in PWH with gut dysbiosis proposed as one of several underlying mechanisms [5]. HIV infection and viral replication induces profound disruption of gut-associated lymphoid tissue (GALT), which can lead to alterations in gut microbial diversity and species richness. Moreover, commensal bacteria crucial for a healthy gut are replaced by ones that contribute to chronic inflammation and immune dysfunction [6–8]. These compositional changes have been described as a HIV-related microbiota index (HMI) [6]. HIV infection also results in increased microbial translocation (MT) and production of microbiota-produced metabolites [9]. MT occurs when the bacteria (or bacterial products) translocate from the gastrointestinal tract into the systemic circulation, where they can drive inflammation. Markers used for MT include lipopolysaccharide (LPS), soluble C14 (sCD14), β- D -Glucan (BDG) and intestinal fatty acid binding protein (I-FABP), a marker of enterocyte damage. These have been associated with several NCD in the general population such as inflammatory bowel disease [10], liver fibrosis [11] and cardiovascular disease (CVD) [12]. Increased MT has also been associated with poorer health outcomes in PWH [13] including progression of disease and mortality [14].

Microbiota-derived metabolites such as short chain fatty acids (SCFA) can also influence gut function and have been implicated in several NCD [15–17]. Choline metabolites can promote inflammation and include trimethylamine-N-oxide (TMAO), produced in the liver, and trimethylamine (TMA), a product exclusively produced by the gut microbiota [18]. TMAO converts macrophages into foam cells which contribute to atherosclerotic plaque formation [19]. Elevated TMAO levels are linked to higher risk of CVD [20, 21], metabolic dysfunction-associated fatty liver disease (MAFLD) [22], obesity [23] and diabetes [24] in the general population. Disturbances in tryptophan metabolism, primarily mediated through the kynurenine pathway (KP) have also been linked to numerous NCD in the general population, including metabolic syndrome [25], CVD [26], schizophrenia, depression and dementia [27], with metabolites of the KP emerging as implicated in development of NCD in PWH [28]. These characteristic changes after HIV infection are seen in those chronically infected, and studies suggest that these changes cannot be fully restored even after successful virological suppression with ART [29, 30].

Together, these findings point to a novel link between the gut microbiome, MT and microbiota-derived metabolites with the risk of NCD in chronically infected PWH. With a growing aging population of PWH come new challenges with the management of age-related comorbidities. Understanding the knowledge gaps linking inflammation, gut dysfunction and aging in PWH is important for improving health outcomes and identifying those at higher risk.

Objectives

To address this evidence gap, the aim of this systematic review is to summarise the current understanding of the impact of gut microbiome alterations on inflammation and NCD in PWH.

Methods

Protocol and registration

The full protocol, including analysis methods and inclusion criteria, is registered with PROSPERO, number CRD42022352703. This protocol was updated on 10/05/2024 to extend the search timeline to include published papers from January 2012 to April 2024.

Search strategy and study selection

Using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [31] (S1 Table), we conducted a search of Pubmed, Scopus, Embase and Cochrane Reviews for randomized control trials, cohort, case–control and cross-sectional studies published from 1 January 2012 to 21 April 2024 (S2 Table for data sources and search terms, including Mesh headings and Emtree terms). Reference lists from relevant articles were also screened. Only original articles of adult human studies of the gut microbiome published in English were included (Fig 1). We excluded reviews, commentaries and letters. Two reviewers (RMC and EN) screened all identified titles and abstracts. Selected abstracts underwent full text review and were assessed for eligibility, with all authors agreeing on the final studies for inclusion. In this systematic review, all necessary data were available from the included studies. There were no instances of missing data, so no additional steps were required to address data gaps.

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Fig 1. PRISMA flow diagram.

Flow chart of study selection process.

https://doi.org/10.1371/journal.pone.0308859.g001

Quality assessment and data extraction

Extracted data included information on the study authors, year of publication, mean population age, study design, NCD assessed and major findings (NCD association to MT, microbial metabolites and/or gut microbiome compositions). Extraction was conducted using a standardised data extraction form and data were cross-checked for accuracy by the reviewer (RMC) against the source. Quality and risk of bias were assessed using the Joanna Briggs Institute (JBI) Australia tools as appropriate to the study design (see S3–S6 Tables) [32–34]. If a paper included more than one study design (i.e. a cross-sectional analysis and a nested case-control analysis), a JBI score was allocated to each.

Results

Study selection

Initial searches identified 727 studies. After removal of duplicates, 567 underwent abstract review with 480 abstracts that did not meet inclusion criteria removed (Fig 2). The remaining 87 full-text articles were assessed for eligibility and 56 were included in the final review. Article exclusion was predominately due to wrong intervention or outcome measured.

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Fig 2. Interrelationships between gut dysbiosis, inflammation and non-communicable diseases (NCDs).

The gut microbiota is shaped by various host factors and has a bidirectional relationship with inflammation, and depending on its composition, it can inhibits or stimulate inflammatory pathways. These, in turn, can promote the onset of various inflammatory conditions such as NCDs.

https://doi.org/10.1371/journal.pone.0308859.g002

General characteristics of included studies

Of the 56 studies included, the highest number of studies were from the USA (n = 30), followed by Denmark and/or Norway (n = 10), Spain (n = 4) and Thailand (n = 3) with the remainder from Italy, China (all N = 2), the UK, Mexico, Australia, Canada and Germany (all N = 1). Most studies (n = 50) included fewer than 500 participants and the mean/median age ranged from 33 to 61 years. Eight studies were conducted in women only and five were conducted in men only. The proportion of males in the 43 mixed-sex studies ranged from 44%-96%. Thirty-six studies (63%) involved virally suppressed populations, ten (17.5%) included mixed populations of PWH with either suppressed or detectable viral loads, and five studies (8%) focused on PWH with detectable viral loads. Five studies (8%) did not specify the viral load status of their cohort.

Among gut microbiome measurements, 25 studies performed 16S rRNA gene amplicon sequencing on faecal bacterial DNA and three studies performed shotgun sequencing for entire community bacterial DNA. The most commonly measured MT markers were sCD14, LPS and LPS-binding protein (LPB). Twelve studies assessed the role of choline metabolites and six studies explored tryptophan metabolism.

Quality assessment

Using the JBI tool, 33 of 40 cross-sectional studies scored at least 6 out of possible 8 points, indicating good reliability and relevance, while the two RCTs scored poorly, scoring 4 and 6 out of a possible 12 points, respectively (S3–S6 Tables). This was largely explained by lack of detail on the RCT design and follow-up as these studies reported post-hoc analyses of larger clinical trials. Major sources of potential bias included poor reporting of inclusion and exclusion criteria and lack of consideration for potential confounding from factors such as diet, sex or socio-economic status.

The chosen papers dealt with one of seven NCD; CVD, metabolic disease, CLD, bone disease, cancer, frailty and neuro-psychiatric disease. Associations between gut microbiome and each specific NCD are reported with the following format; first describing gut microbiome diversity and bacterial composition, then MT marker associations and finally data on choline and KP metabolites with the NCD.

Cardiovascular disease

The risk of CVD in PWH is increased beyond that explained by traditional risk factors alone, with an approximate two-fold increased risk of myocardial infarction (MI) in PWH [35]. CVD accounts for the largest number of studies included in this review (N = 20, Table 1).

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Table 1. Cardiovascular disease.

https://doi.org/10.1371/journal.pone.0308859.t001

Several studies explored diversity and composition changes of the gut microbiome with CVD. Reduced α-diversity was observed in PWH with both clinical CVD (n = 60) and subclinical atherosclerosis [36, 37], but no changes were seen in those with carotid artery plaque (CAP) in the 2022 and 2023 studies of the Women’s Interagency HIV Study (WIHS) cohort [38, 39]. Both studies identified an association between CAP and enrichment of Fusobacterium nucleatum alongside depleted levels of Odoribacter, with Fusobacterium abundance correlating with various plasma lipids and metabolites as well as incidence CAP over seven years [38]. The microbial metabolite imidazole-propionate (ImP) was also positively associated with plaque and several pro-inflammatory markers which they suggest may be related to host immune activation and inflammation. A subsequent study of the WIHS cohort in 2024 found that several sex hormones (oestrogens, androgens and adrenal precursors) tended to associate with lower odds of CAP [40]. These sex hormones were also associated with some bacterial species, which were themselves correlated with CAP. This supports hormonal mechanisms of elevated cardiovascular risk in postmenopausal women with HIV (WWHIV).

in contrast, a study of a predominantly male cohort identified an abundance of Prevotella and Bacteroides in PWH with CVD, with the Prevotella-rich cluster comprising mainly men who have sex with men (MSM) (97%). In addition, a whole genome sequencing study of (n = 129) men with and without HIV found both Rothia mucilaginosa and an Eggerthella unclassified were enriched in those with subclinical atherosclerosis. They also describe an association between specific IL-32 isoforms and CVD and suggest that these are driven by lower levels of the SCFA caproic acid. Together, these three studies demonstrate a possible relationship between altered bacterial diversity and composition with CVD outcomes in PWH. Further studies involving both male and female participants are needed to determine the influence of sex on these alterations.

Three studies examined the association of the MT markers sCD14 and LPS with CVD outcomes in PWH, including progression of atherosclerosis [41], endothelial dysfunction [42] and hypertension [43]. These associations mirror those in the general population, suggesting that sCD14 and LPS may influence CVD outcomes in PWH, either directly or indirectly.

When reviewing the impact of gut-microbiota derived metabolites on CVD outcomes, the largest body of work (10 studies) has explored the association of choline metabolites with CVD in PWH. Most studied TMAO and its precursors, betaine and carnitine, which were linked with increased mean CIMT and progression of CIMT in PWH [44–46]. Less consistent associations between TMAO and coronary artery plaque (CAP were reported, with one study observing an increased risk (RR 1.25) of CAP in PWH (n = 520) with higher plasma TMAO levels and a smaller study (n = 100) reporting an inverted U-shaped association between TMAO and CAP among men with HIV [47]. Similarly, an increase in another choline precursor, TMA, was found to be significantly associated with several markers of calcification and plaque in 155 PWH. Furthermore, higher TMA was associated with both lower HDL and higher levels of LPS [48].

Although these findings suggest that TMAO is associated with atherosclerotic disease, it was not found to be associated with increased risk of MI in a study of (n = 105) PWH or in first-time MI (n = 237), but was found to be elevated in PWH with silent ischemia [49, 52]. Further work using 82Rb PET/CT found no association between TMAO and myocardial perfusion, left ventricular ejection fraction or CAC score in 94 PWH [50]. Conversely, a multisite cross-sectional study (CHART-HIV) discovered higher TMAO and choline levels in PWH with diastolic dysfunction. TMAO and betaine were also significantly associated with myocardial fibrosis measures, and elevated TMAO correlated with cardiac and MT markers like sCD14, NT‐proBNP, troponin‐I, galectin‐3, GDF‐15, and IL‐6 [51]. These findings suggest that, although elevated TMAO and TMA are linked to atherosclerosis and cardiovascular inflammation, further research in larger studies is needed to confirm if this association translates into differences in clinical outcome.

Recently, attention has turned to exploration of the KP and CVD outcomes. One study of the WIHS and MACS cohorts (n = 737) found that PWH exhibit lower tryptophan and higher KTR than those without HIV [52]. Higher plasma kynurenic acid (KA) and KTR significantly associate with an increased risk of CAP. Another study conducted in just the WIHS cohort (n = 361), showed that plasma KA and KA/TRP ratio were positively associated with CAP [53]. Additionally, indole-3-propionate (IPA) and IPA/KA ratio were inversely associated with CAP independent of HIV status. While these studies suggest that elevated TMAO and KP-related metabolites are associated with CVD, data showing if these associations translate to clinical outcomes is limited. It is likely that a combination of metabolites may influence CVD outcomes in PWH and further research in the area is warranted.

Metabolic disease

PWH on successful ART have an increased risk of developing obesity, insulin resistance and metabolic syndrome (MetS), independent of demographic and lifestyle factors [6]. Gut dysbiosis and chronic systemic inflammation are common features of PWH with metabolic changes [54]. Fourteen studies examining these components of metabolic disease were included (Table 2).

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Table 2. Metabolic disease.

https://doi.org/10.1371/journal.pone.0308859.t002

Diabetes

Four studies examined diabetes and microbial diversity in PWH. Although one study found no change in diversity in PWH with diabetes (n = 48) [55], a larger cross-sectional study (n = 84) found lower α-diversity in PWH and diabetes, followed by people without HIV with diabetes [56]. Interestingly, a history of smoking and Framingham risk score were also associated with reduced α-diversity whereas physical activity, metformin use and HDL cholesterol were associated with higher α-diversity. A lower α-diversity and differences in β-diversity was also seen in a study of PWH with prediabetes compared to a normoglycaemia group [57]. In addition, two Firmictus genera was enriched in the prediabetes group and 13 genera were significantly higher in the normoglycaemia group. Similarly, four genera (Finegoldia, Anaerococcus, Sneathia, and Adlercreutzia) were found to be less abundant in a study of WWHV and diabetes compared to controls [55].

Although no studies specifically examined MT markers and diabetes, one investigated endothelial dysfunction in PWH with diabetes (n = 194). They found a higher asymmetric dimethylarginine (ADMA) and lower L-arginine/ADMA ratio, markers of endothelial dysfunction, in PWH with diabetes. They also found a positive correlation between ADMA and TMAO [58]. Higher ADMA levels and lower L-arginine/ADMA ratio was also found to be associated with the KTR, which was higher in a study of PWH with diabetes compared to controls [56]. Similarly, in a study of women with diabetes, irrespective of HIV status, higher plasma levels of several metabolites of the KP were found [55]. Together, these findings indicate that diabetes rather than HIV status has the biggest impact on gut microbiome changes [56].

Obesity

Gut dysbiosis linked to obesity are well-documented in the general population but findings in PWH are mixed [59]. A small study reported lower α-diversity and elevated circulating hsCRP, IL-6, leptin and sCD14 in obese compared to lean individuals [54]. Elevated sCD14 was associated with increased visceral abdominal tissue (VAT), while higher leptin levels correlated with increased subcutaneous abdominal tissue (SAT) area. A larger study of (n = 178) PWH contradict these findings, associating higher sCD14 with lower trunk and limb fat [60]. They also found that increased LPS levels were associated with an elevated Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and triglyceride levels, together with reduced high-density lipoprotein (HDL) levels. Higher I-FABP levels correlated with sugar and saturated SCFA intake in PWH and inversely correlated with body composition, BMI, VAT and SAT [61]. Additionally, fungal translocation marker β-D-glucan (BDG) in a sub-study of a RCT of ART-naïve PWH, showed a twofold increase at week 96, correlating with an 8% rise in trunk fat and 7% increase in total fat [62]. Together, these findings suggest that although associations between inflammatory markers and metabolic risk markers occur, disparities exist with different MT markers and body composition.

Despite these variations, a more consistent link between the KP and obesity is evident in PWH. In a study of (n = 939) PWH, a 0.5-unit increase in waist-to-hip ratio was associated with 31% higher KTR, and 44% higher quinolinic-to-KA ratio with lower KA concentrations [28]. Subsequent research revealed that a higher KTR associated with elevated LBP levels, a high VAT-to-SAT ratio, and higher VAT [63]. These findings suggest dysregulated KP contributes to abdominal fat accumulation and increased gut barrier permeability, potentially fuelling inflammation in PWH.

Metabolic syndrome

Four studies explored changes in diversity in those with MetS. One study (n = 51) found no difference in α-diversity in PWH with or without MetS [64], yet another similar-sized study (n = 60) found significantly decreased α-diversity in PWH with MetS, with a bacterial signature dominated by Prevotella [65]. 60% of participants in this group were MSM, possibly influencing this Prevotella enrichment. A larger study (n = 627) found that HIV-related microbiota were associated with increased risk of MetS and VAT accumulation, independent of sexual practice. This risk was pronounced in individuals with previous severe immunodeficiency and driven by an increase in Desulfovibrionaceae and decrease in Clostridia [8]. Desulfovibrionaceae produces hydrogen sulfide, harmful to the gut, while Clostridia, which are known butyrate-producers, promote gut barrier integrity [66].

Compared to MT markers, an increase in cardiovascular and inflammatory markers (PAI-1 and triglycerides-to-HDL-ratio) was seen in those with MetS compared to those without [64]. Another study found higher hsCRP together with an increase in the metabolism of several functional pathways including amino acid and energy metabolism, cofactor, vitamin and LPS biosynthesis pathways in PWH with MetS [65, 67]. Amino acid fermentation affects colonic epithelial cell energy metabolism, while LPS signalling induces inflammation and insulin resistance through MT [68]. Together, these findings suggest a proinflammatory profile in PWH with MetS.

One study employed a multi-omics approach to investigate microbial diversity, untargeted metabolomics, and their connection to diet, inflammatory and immune markers in PWH (n = 59) versus controls (n = 54) [69]. They identified 69 crucial variables (clinical, diet, immune, and microbial) and a subset of 10 highly predictive variables for MetS. Positive correlations between immune markers (LBP, ICAM-1, IL-16, IL-12, GM-CSF) and MetS were found, particulary between LBP and a high BMI. LBP binds to both microbial LPS and lipoteichoic acid, and the presence of elevated LBP in blood is indicative of increased intestinal barrier permeability [70]. Taken together, these associations suggest that inflammation originating from an impaired intestinal barrier is promoting worse metabolic health in PWH.

Bone disease

HIV infection has been associated with low bone mineral density (BMD) and increased fracture risk [71, 72]. Emerging evidence in the general population suggests a close relationship between the gut microbiota and bone metabolism, and microbial alterations have been associated with bone health [73]. Despite this, only one eligible study compared the association between the gut microbiome and bone disease in WWHV (Table 3). They found five genera to be more abundant in those with low BMD together with a distinct metabolite profile [74], suggesting an interplay between altered gut microbiota and metabolites on BMD status in WWHV.

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Table 3. Bone disease.

https://doi.org/10.1371/journal.pone.0308859.t003

Liver disease

CLD has emerged as a leading cause of morbidity and mortality in PWH. Viral hepatitis coinfection and aging has been accompanied by an increased prevalence of cirrhosis and hepatocellular carcinoma (HCC) [75]. Furthermore, MAFLD has been reported in up to 35% of PWH and is expected to become the leading cause of cirrhosis in this population [76]. Eight articles relating to CLD met eligibility criteria for inclusion in this review (Table 4).

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Table 4. Chronic liver disease.

https://doi.org/10.1371/journal.pone.0308859.t004

Two studies explored the impact of HCV infection on bacterial composition in PWH. One study found no differences in bacterial diversity between HCV and HIV/HCV coinfected groups [77] nor were there differences in HCV or HIV/HCV coinfected groups in another study pre and post direct-acting antiviral (DAA) treatment for HCV [78]. Both studies did describe differences in bacterial composition between groups with improvements in gut diversity following DAA therapy, including enrichment of some beneficial bacteria and reductions of pathogenic bacteria. Together these studies suggest that co-infection with HCV does not influence overall bacterial diversity in PWH, but that a microbiota signature may exist in co-infected PWH.

In studies of MAFLD, one study found distinct beta-diversity and microbial composition in those with MAFLD, regardless of HIV status [79]. In contrast, a similar-sized study found no difference in the bacterial composition between PWH with and without MAFLD or fibrosis [80]. These studies differed in their definition of MAFLD however, with the former study screening participants based on the presence of transaminitis and the latter study including participants with liver-biopsy proven MAFLD. A recent study of the Miami Adult Studies on HIV (MASH) cohort explored the association between diet and liver fibrosis in PWH [81]. They found that a lower dairy intake was seen in participants with a higher FIB-4 score, yet the study also found that participants in this study displayed poorer diet quality compared to the general U.S. population. They also found differences in bacterial composition based on FIB-4 score, with a higher relative abundances of butyrate-producing taxa seen in those with a low FIB-4 score. These studies suggest that the composition of gut microbiota may play a role in MAFLD, with potential implications for dietary interventions however further studies are warranted to understand these associations in PWH with MAFLD.

In addition to composition changes, three studies included associations between MT markers and CLD. Following HCV infection, both MT markers (I-FABP, LBP, sCD14) and kynurenine levels were found to be higher in coinfected and monoinfected individuals compared to uninfected controls [82]. Following HCV treatment, these markers all decreased suggesting that inflammation associated with HCV viraemia may be a driver of these MT responses. In other studies of CLD, LPS, sCD14 and AAL were strongly associated with development of cirrhosis among those with HIV/HCV coinfection, and sCD14 was found to be correlated with the presence of MAFLD and liver fibrosis stage [80, 83]. Overall, this suggests that these markers may serve as indicators of CLD severity or progression in HIV/HCV coinfection.

Two studies of the KP both found that the KTR was highest in HIV/HCV coinfection and one found that a doubling of kynurenine levels was associated with 29.6% increase in FIB-4 scores [82, 84]. In HCV/HIV subjects, kynurenine was primarily elevated in fibrotic patients and correlated with IP-10, a marker of HIV and HCV disease progression, as well as aspartate aminotransaminase to platelet ratio (APRI scores) and insulin levels. Kynurenine levels and the KTR showed no change before and after HCV treatment, but there was an improvement in the APRI score. Both these studies suggest that KTR may modify the association between HIV infection and higher fibrosis in HCV co-infection.

Cancer

As PWH age, the risk of cancer increases. Most HIV-associated cancers are caused by oncoviruses such as HHV-8, Epstein–Barr virus (EBV), high-risk human papillomavirus (HPV), HBV, HCV, and Merkel-cell polyomavirus [85]. HIV-associated and HIV non-associated cancers were included in our search terms for this review, and 3 studies met eligibility criteria (Table 5).

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Table 5. Cancer.

https://doi.org/10.1371/journal.pone.0308859.t005

In a study of HPV-associated anal cytology changes (n = 36), a marked gut dysbiosis was evident in PWH with altered anal HPV and a distinct composition difference was seen in those with high-risk HPV compared to low-risk HPV genotypes [86]. Conversely, no differences in the MT markers sCD14, LPS, calprotectin and I-FABP were seen between these groups. Another study found distinct diversity changes in samples collected from rectal mucosa biopsies compared to faecal samples and suggest that certain prevalent taxa taken from rectal biopsies could be used as diagnostic markers for particular histological- graded lesions [87]. Finally, a large retrospective cohort study (n = 246) of lymphoma cases in the US [88] found elevated circulating levels of sCD14 and LPS were associated with a 2.5–3 fold increased risk of non-Hodgkins lymphoma (NHL) in PWH, with sCD14 positively correlated with levels of lambda free light chains. These studies suggest that the presence of certain proinflammatory or pathogenic bacteria are associated with HPV-associated pre-cancerous changes and that although MT markers may not be associated with HPV, they could be prognostic in certain cases of NHL.

Frailty

Impairments in physical function among ART-treated PWH have been linked to systemic inflammation. Emerging evidence supports an association between the gut microbiome and physical function/frailty [89]. Three studies on frailty met our eligibility criteria (Table 6). A small study (n = 36) found no significant differences in overall bacterial diversity, physical function, and body composition between older PWH and controls [90]. However, the gut microbiome composition in older PWH differed from that in older negative controls, suggesting a unique aging gut profile in PWH. They also found that higher faecal levels of the SCFA butyrate was associated with increased grip strength in both groups. In contrast, a second similar sized study (n = 36) did find diversity differences between older PWH and HIV negative controls, but found no changes between frail or non-frail groups controls as measured by the Fried Frailty Index [91]. The larger HIV Neurobehavioral Research Center study (n = 398) identified a distinct gut microbiome in PWH with impairment in activities of daily living (ADLs) that was enriched in Bacteroides [92], which has previously been associated with cognitive decline in other studies of PWH [93]. Despite different frailty assessments, all studies imply unique microbiome compositions in older, frailer PWH, emphasising the complexity of studying and measuring frailty in aging.

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Table 6. Frailty.

https://doi.org/10.1371/journal.pone.0308859.t006

Neuro-psychiatric conditions

The term “gut-brain axis” is a bidirectional communication network that links the enteric and central nervous systems (CNS). Explored in conditions like Alzheimer’s, Parkinson’s [94], and Multiple Sclerosis [95], it extends also to neurocognitive and mood disorders [96]. Seven articles relating to mental health and neurological disorders met eligibility criteria (Table 7).

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Table 7. Mental Health and neurological disorders.

https://doi.org/10.1371/journal.pone.0308859.t007

A small cross-sectional study of ART-naïve PWH (n = 85) did not find associations between gut microbial dysbiosis and HIV-associated neurocognitive disorders (HAND). Despite a relatively young cohort (median age 33), 46% met HAND criteria by the Montreal Cognitive Assessment (MoCA) test [97]. A similar sized study (n = 102) found no diversity differences between PWH with and without neurocognitive impairment (NCI) but noted varied microbial abundance, including increased Spirochaetes and Epsilonbacteraeota in the NCI group [98] and decreased abundance of butyrate-producing bacteria in the non-NCI group. In contrast, a larger cross-sectional study of women with and without HIV (n = 466) did find higher α-diversity measures in women with NCI compared to those without. They also found a distinct microbial composition associated with NCI and this was more pronounced in WWHV [99]. These studies suggest that while gut microbial diversity might not directly correlate with HAND in certain populations, specific microbial abundances may be associated with NCI in PWH, with variations observed by gender.

Other studies have explored gut dysbiosis associated with other neurological conditions. In measures of depression, PWH (n = 96) had increased abundance of F. prausnitzii [100] and PWH co-infected with HCV with a history of Major Depressive Disorder (MDD) had enrichment of Enterobacteriaceae, Alistepes onderdonkii, Bacteroides and Parabacteroides distasonis [101]. In measures of distal neuropathic pain (DNP), neuropathic parasthesia and neuropathic sensory loss, a lower α-diversity was seen in PWH together with an increased ratio of Blautia and Clostridium to Lachnospira [102] (Table 7).

In addition to compositional changes, the MT marker sCD14 was found to be elevated in subjects with NCI in a cohort of PWH (n = 97) with nadir CD4 counts <300 cells/mm3 [103]. Elevated sCD14 was seen in subjects with impaired testing in attention and learning domains and correlated inversely with global, attention, and learning T scores, suggesting these domains are the main drivers of impairment [98]. In addition to MT changes, the NCI group had higher CIMT, CAP and cholesterol than the non-NCI group. Together, these studies suggest that overall microbiome diversity in HAND is apparently unaltered, but that a gut microbiota composition signature may exist in certain neurocognitive conditions including HAND, DNP and MDD in PWH. Future studies in neuro-psychiatric conditions should also explore the role of other MT markers and metabolites, including those of the KP.

Discussion

This systematic review is the first to summarise the evidence of age-related comorbidities and their associations with gut dysbiosis in chronically-infected PWH. We describe studies that examine alterations in gut diversity, composition, MT and microbiota-derived metabolites, revealing overlapping and interacting contributions to NCD development (Fig 2).

Across studies, gut diversity was consistently lower in PWH compared to controls, but diversity changes differed depending on the NCD assessed. For instance, no difference in diversity was seen in HAND vs non-HAND groups [97, 98, 100] yet significant changes were seen in those with DNP [102] and a lifetime history of depression [101]. Examining HAND classification in these studies reveals significant variation in diagnostic criteria with the lack of a consensus on HAND definition complicating research in this field [104]. Similarly, conflicting results of diversity changes are seen in studies of frailty [90–92], MAFLD [79, 80] and CVD [36, 40, 105].

In addition to diversity, microbial composition differed between PWH and controls and also by NCD. In studies of frailty, bacterial compositions were distinct between frail versus non-frail groups and between PWH and controls, suggesting that a unique gut-physical function axis exists in PWH [90, 92]. Similarly, in studies of HPV-related cancer, compositions differed depending on both histological grade [86] and the type of sample studied (rectal mucosa versus faecal samples) [87]. Distinct compositional differences are also found between body type (lean, generally obese and viscerally obese) [54] and between those with prediabetes and normoglycaemia [57]. In contrast, assessments of diversity were conflicting in studies of HIV/HCV coinfection. However, these studies differed in their design and in the outcomes being assessed. For instance, some studies focused on the impacts of chronic HCV infection on the gut microbiome [77] whilst others compared gut dysbiosis pre- and post-DAA treatment [78]. Overall, these studies show that compositional changes and not diversity may be more important in differentiating risk of NCD in PWH.

The most commonly assessed MT markers were sCD14 and LPS and they have been associated with progression of atherosclerosis [41], hypertension [43] and with HCV-related liver disease progression [83]. sCD14 has been linked with HAND diagnosis [103], increased risk for NHL [88], liver fibrosis and MAFLD [80] in PWH. Higher plasma sCD14 levels have previously been associated with immune activation and all-cause mortality in PWH [106, 107] and so it comes as no surprise that this marker is also associated with progression of NCD in HIV. However, sCD14 serves as a biomarker of monocyte activation and reflects LPS-induced monocyte activation but is not a specific MT marker. Furthermore, the relationship between sCD14 and LPS is complex in PWH, with increased sCD14 associated with high LPS [108], low LPS levels [109] and neither [107] in different studies. This variability may be due to laboratory difficulties, HIV disease severity, ART duration [110], genetic factors [111] and the intestinal microbiota [112]. In addition, LPS may respond to stimuli other than endotoxins from gut bacteria [113], complicating it’s interpretability.

Mixed findings in linking MT markers with MetsS may stem from variations in methods used to assess MetS [8, 60, 64]. Some studies measured levels of lipoproteins and other atherosclerotic markers, whilst others used DEXA scan or CT scan measurements of body composition. Furthermore, only half of MetS studies included uninfected controls, complicating the distinction between HIV-related changes and metabolic changes. Other MT markers of interest include the fungal marker BDG and I-FABP, an indicator of enterocyte damage. Studies found that these markers associated with increased adiposity in PWH, suggesting that intestinal damage is linked with nutrient malabsorption and inflammation [61, 62]. Further investigation of these markers with NCDs could offer insights into gut barrier disruption and systemic inflammation.

The gut microbiota produces SCFA and various metabolites, such as those of the KP and choline metabolism, involved in multiple human physiological pathways. The KTR is consistently higher in PWH compared to controls [28, 56, 82] and KP metabolites are associated with vascular endothelial dysfunction [52], CAP development [39], liver fibrosis [84] and increased adiposity [28] in PWH. Choline metabolites (TMA and TMAO) are similarly associated with progression of atherosclerosis [114], CAP [48] and also myocardial fibrosis [51]. Whilst these studies draw conclusions based on associations, a further understanding of the mechanistic links driving these associations is needed in order to draw meaningful conclusions.

All studies included in this review were conducted in people with chronic HIV, predominantly with suppressed viral loads. Only two studies compared treated and untreated HIV directly [60, 115]. One study found that TMAO was linked to sCD14 in untreated people with HIV, but not to platelet hyperreactivity in either group. The other found higher triglycerides and insulin resistance in untreated people, and an association between MT and lower HDL in treated HIV, with no body composition differences between groups. These studies suggest some possible differences in NCD measures between treated and untreated chronic HIV infection, but few studies exist due to early ART initiation.

The strengths of this review include: (1) a registered review protocol with a comprehensive search strategy across five databases; (2) evaluation of many studies that include an older population; (3) assessment of populations chronically infected with HIV and (4) evaluation of microbiome composition, MT markers and gut microbiota-derived metabolites as tools for assessing the gut microbiome’s impact on comorbidities in PWH. However, limitations include few studies involving gut biopsies, technical variations with MT assays and responses, cross-sectional study designs preventing causal inferences and a lack of diversity in terms of geography, ethnicity, socioeconomic status and gender. Finally, whilst renal disease is commonly reported in PWH, notably no studies looked specifically at associations with this comorbidity.

Conclusions

The burden of age-related comorbidities causes significant morbidity and mortality for PWH. The lack of prospective studies that link changes in gut dysbiosis to NCD development remains a significant research gap. Further studies on the mechanistic links between gut dysfunction, inflammation and these comorbidities is vital for developing new diagnostic and therapeutic approaches in PWH.

Supporting information

S1 Table. PRISMA 2020 checklist.

https://doi.org/10.1371/journal.pone.0308859.s001

(DOCX)

S2 Table. Table summary of search strategy and searching strings for the Pubmed, Scopus and Embase databases.

https://doi.org/10.1371/journal.pone.0308859.s002

(DOCX)

S3 Table. Quality appraisal result of included studies; using Joanna Briggs Institute (JBI) quality appraisal checklist for cross-sectional study designs.

https://doi.org/10.1371/journal.pone.0308859.s003

(DOCX)

S4 Table. Quality appraisal result of included studies; using Joanna Briggs Institute (JBI) quality appraisal checklist for cohort study designs.

https://doi.org/10.1371/journal.pone.0308859.s004

(DOCX)

S5 Table. Quality appraisal result of included studies; using Joanna Briggs Institute (JBI) quality appraisal checklist for case-control study designs.

https://doi.org/10.1371/journal.pone.0308859.s005

(DOCX)

S6 Table. Quality appraisal result of included studies; using Joanna Briggs Institute (JBI) quality appraisal checklist for randomised control study designs.

https://doi.org/10.1371/journal.pone.0308859.s006

(DOCX)

S7 Table. All data extracted from the Pubmed, Embase and Scopus databases.

https://doi.org/10.1371/journal.pone.0308859.s007

(XLSX)

S8 Table. Quality appraisal result of included studies; using Joanna Briggs Institute (JBI) quality appraisal checklist for each study type.

https://doi.org/10.1371/journal.pone.0308859.s008

(XLSX)

S9 Table. All studies identified in the literature search, including those that were excluded from the analyses.

https://doi.org/10.1371/journal.pone.0308859.s009

(XLSX)

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