Abstract
Background:
Older adults with HIV (OAH) experience more comorbidities and geriatric syndromes than their HIV-negative peers, perhaps due to chronic inflammation. Cell-free mitochondrial DNA (cfmtDNA) released from cells undergoing necrosis-mediated cell death potentially acts as both a mediator and marker of inflammatory dysregulation. We hypothesized that urinary cfmtDNA would be associated with frailty, body composition and fall history in OAH
Methods:
OAH completed frailty testing, a psychosocial survey, body composition assessment, and measurement of urine cfmtDNA and urine albumin:creatinine in this cross-sectional study. Urine cfmtDNA was measured by qPCR and normalized to urinary creatinine.
Results:
Across 150 participants, the mean age was 61 years (SD 6 years), half identified as Black, one-third were female, and 93% had HIV-1 viral load <200 copies/ml. Two-thirds met criteria for a pre-frail or frail state. Those with unintentional weight loss had higher urine cfmtDNA concentrations (p=0.03). Higher urine cfmtDNA was inversely associated with skeletal muscle index (SMI) (β =−0.19, p<0.01) and fat mass index (FMI) (β =−0.08, p=0.02) in separate multiple linear regression models adjusted for age, sex, and presence of moderate-severe albuminuria.
Conclusions:
In this cross-sectional study of OAH, higher levels of urine cfmtDNA were more common in subjects with less robust physical condition, including unintentional weight loss and less height-scaled body mass of fat and muscle. These findings suggest urine cfmtDNA may reflect pathophysiologic aging processes in OAH, predisposing them to geriatric syndromes. Longitudinal investigation of urine cfmtDNA as a biomarker of geriatric syndromes is warranted.
Background:
HIV-related mortality has decreased in individuals treated with antiretroviral therapy, yet older adults with HIV (OAH) experience more comorbidities and geriatric syndromes than their HIV-negative peers1,2. Inflammatory changes with aging are multifactorial and lead to the accumulation of detrimental molecular changes within cells, which can result in frailty, disability, and death3,4.
Mitochondrial dysfunction contributes to inflammation during aging and muscle wasting processes5,6 and has been proposed as a mechanism driving adverse aging phenotypes in OAH7,8. In the setting of cellular stress, mitochondrial dynamics are disrupted which can result in dysregulated mitophagy, redox imbalance, and cell death9. Hence, mitochondrial DNA in the circulation- termed cell-free mitochondrial DNA (cfmtDNA)- can serve as a damage-associated molecular pattern, stimulating innate immune pathways and recruiting immune cells to propagate the inflammatory response9,10.
CfmtDNA can be detected in body fluids, including plasma and urine, and has been proposed as a mediator and marker of inflammation10–12. Release of cfmtDNA can lead to activation of innate immunity via multiple pathways, including activation of toll-like receptor 9, cGAS-STING, and inflammasomes, which stimulate pro-inflammatory genes to propagate the innate antiviral response and lytic cell death12–14. These inflammatory pathways have widespread physiologic effects, ranging from sepsis to aging phenotypes2,15, and can offer insight into the pathophysiology of inflammaging. We investigated cfmtDNA in urine as a potential marker of pathophysiologic mechanisms that underlie accelerated or accentuated aging in OAH. We hypothesized that OAH with greater cfmtDNA in urine would have a higher burden of frailty and falls, lower height-scaled muscle mass, and higher levels of conventional serum inflammatory markers.
Methods:
OAH (age 50 and older) were randomly selected from a large urban academic medical center outpatient HIV clinical practice and invited to complete a detailed questionnaire focusing on health status, quality of life, depression screening16, psychosocial factors, and substance use17. Participants age 55 and over who completed the questionnaire were invited to participate in a substudy consisting of frailty testing, bioelectric impedance analysis (BIA) to assess body composition, and blood and urine sample collection. Laboratory data were extracted from the electronic medical record, and HIV-1 viral load was dichotomized as > or ≤200 copies/ml. The Veterans Aging Cohort Study (VACS) Index18 was calculated. Participants were asked to fast for ≥ 8 hours prior to the study visit. Study participants provided written informed consent, and this study was approved by the Institutional Review Board.
Frailty Testing:
The frailty phenotype was assessed using criteria from Fried et al19. Participants completed a timed 4-meter walk, dominant-hand grip strength assessments via dynamometer, and self-report questions regarding exhaustion, activity level, and unintentional weight loss of 10 lbs or greater. Individual frailty score components were dichotomized as previously described as frail/pre-frail or non-frail19,20.
Urine Measurements:
Spot urine samples were collected, immediately placed on ice, and centrifuged at 1,000g for 12 minutes at 4°C within 3 hours of collection. CfmtDNA levels were measured by SYBR Green dye-based qPCR assay using a PRISM 7500 sequence detection system (Applied Biosystems) with primer sequences specific for human NADH dehydrogenase 1 gene, as previously described10,11. Urine albumin and creatinine were measured from frozen urine samples, and the estimated glomerular filtration rate (eGFR) was calculated based on serum creatinine with the CKD-Epi equation21.
Body Composition Assessment:
Body composition was assessed with tetra polar bioelectrical impedance analysis (BIA, Quantum IV, RJL Systems, Inc., Clinton Township, MI) by trained study personnel. Raw data were analyzed and reported using the RJL Systems software (BC4 version 4.2.0). Skeletal muscle index and fat mass index were calculated by dividing by height (in meters) squared22.
Inflammatory Biomarker Methods:
Serum samples were stored at −80° C prior to assaying. Interleukin-6 (IL-6), interferon gamma (IFNγ), and tumor necrosis factor alpha (TNFα) were assayed using a multiplex kit (K15052G), and C-reactive protein (CRP) using a singleplex kit (K151STG) from MesoScale Discovery (Rockville, MD). TNF Receptor 1 (TNFR1) was assayed using a Quantikine ELISA kit (DRT100) from R&D Systems (Minneapolis, MN). Assays were run in duplicate with quality controls; 10% were repeated for confirmation. The intra-assay coefficient of variation (CV) for CRP, IL-6, IFN-γ, and TNF-α ranged from 2.4% to 6.4%, and inter-assay CVs ranged from 5.0%−10.2%. The detection limits of CRP, IL-6, IFN-γ, TNF-α, and TNFR1 are 0.01 ng/mL, 0.10 pg/mL, 0.40 pg/mL, 0.20 pg/mL, and 0.80 pg/ml respectively.
Statistical Methods:
Statistical analysis was conducted using Stata/IC version 15.1 (StataCorp LLC, College Station, Texas). Comparisons between groups were conducted by t-test or Wilcoxon rank-sum test. Relationships between urine cfmtDNA levels and clinical variables were explored using backwards stepwise regression models, with a threshold of P<0.10 set as the inclusion threshold. Ordinal logistic and linear regression models were used to assess for relationships between frailty state, frailty components, body composition measurements, and urine cfmtDNA level with adjustment for potential confounders determined a priori or via backwards stepwise regression. Reported p-values are 2-sided.
Results:
There were 164 participants in this study, and 151 provided urine samples. One male participant with a complicated urologic history provided a grossly bloody sample, and was excluded from analysis. Participant demographics are summarized in Table 1. The median VACS index score was 28 (Q1, Q3: 18, 39), which corresponds to a 10.8% risk of mortality in 5 years18.
Table 1.
Participant Demographics
| Measure | Result (N=150) |
|---|---|
| Age (years) | 61 (SD:6) |
| Female sex | 48 (32%) |
| Race: Black White Other Declined |
75 (50%) 45 (30%) 27 (18%) 3 (2%) |
| Ethnicity: Hispanic/Latinx Non-Hispanic/Latinx Declined |
37 (25%) 91 (61%) 21 (14%) |
| Years with HIV | 25 (22, 29) |
| HIV-1 Viral load <200 copies/ml | 93% |
| CD4 Count | 594 cells/mm3 (104, 1,397) |
| Veteran’s Aging Cohort Study (VACS) Index | 28 (18, 39) |
| HCV Antibody Positive HCV RNA Detectable |
13 (9%) 0 (0%) |
| Body Mass Index (kg/m2) | 27 (25, 31) |
| Elevated depressive symptoms | 73 (49%) |
| CKD-Epi GFR (mL/min/1.73m2) GFR Stages: - G1 (GFR>90) - G2 (GFR 60–90) - G3 (GFR 30–59) - G4 (GFR 15–29) - G5 (GFR <15) |
77 (63, 91) 41 (27%) 77 (51%) 30 (20%) 1 (1%) 1 (1%) |
| Drug Use: Crack, Cocaine, Crystal Methamphetamine and/or Heroin | 11 (7%) |
| Tobacco Smoking (current) | 26 (17%) |
| COPD | 19 (13%) |
| Urine Data: | |
| Log Urine cfmtDNA§ | 2.4x108 copies/gram urine Cr |
| Albumin: Creatinine Ratio Albuminuria Stages: - Normal/Mildly Increased Albuminuria - Moderately Increased Albuminuria -Severely Increased Albuminuria |
8.6mg/g (4.1, 27.7) 94 (64%) 46 (31%) 8 (5%) |
| Skeletal Muscle Index (kg/m2) | 8.9 (7.5, 9.9) |
| Fat Mass Index (kg/m2) | 7.6 (6.1, 10.3) |
| Frailty Testing Non-Frail Pre-Frail Frail Frailty Components: Unintentional Weight Loss Slow Walk Weak Grip Exhaustion Low Physical Activity |
46 (31%) 85 (56%) 19 (13%) 8 (5%) 28(19%) 29 (20%) 50 (34%) 43 (29%) |
Continuous data are expressed as mean (SD) or median (quartile(Q)1, Q3) Abbreviations: CKD-Epi GFR = Glomerular Filtration Rate as calculated by the CKD-Epi equation (mL/min). COPD= Chronic Obstructive Pulmonary Disease. Depression was measured by the CES-D 10 (Center for Epidemiological Studies Depression) 10 question Screen; scores range 0–30, scores above 10 indicated elevated depressive symptoms16. HCV= Hepatitis C Virus.
Urine cfmtDNA is expressed as the natural-log transformed geometric mean with 95%CI: 2.0×108−3.1×108
Urine cfmtDNA levels were natural log transformed due to rightward skew; geometric mean cfmtDNA level in urine was 2.4×108 copies/gram of urine creatinine (95%CI: 2.0×108-3.1×108). Median eGFR was 77.4 mL/min/1.73 m2 (Q1, Q3: 62.7, 91.4). The median urine albumin:creatinine ratio (ACR) was 8.6 mg/g urine creatinine (Q1, Q3: 4.1, 27.7), consistent with 94 (64%) meeting criteria for normal to mildly increased albuminuria (ACR<30), 46 (31%) for moderately increased albuminuria (ACR 30–300), and 8 (5%) for severely increased albuminuria (ACR>300) [Table 1].
In a backwards stepwise linear regression model, urine cfmtDNA as the outcome was associated with greater urine albumin measured per gram of urine creatinine as a continuous variable (β=0.002, p=0.005), greater age (β=0.04, p=0.03), greater CD4 T-cell count (β=0.0007, p=0.034), whereas neither eGFR, diabetes, hypertension, smoking, HIV-1 viral load >200 copies/ml, years living with HIV, nor CD4 T-cell nadir remained in the model. Use of an integrase inhibitor, tenofovir disoproxil fumarate, tenofovir alafenamide, or protease inhibitor, angiotensin converting enzyme inhibitor (ACEi) or angiotensin receptor blocker (ARB) medications did not meet criteria to remain in the model.
Frailty:
Overall, 46 (31%) were nonfrail, 85 (56%) were prefrail, and 19 (13%) were frail. In a univariate ordinal logistic regression model, overall frailty state was related to age; for every 5-year increase in age the odds of greater frailty state increased by 1.5 (95% CI:1.2–2.1, p=0.003). Frailty state, however, was not related to urine cfmtDNA level (p=0.46) in a separate model. The mean urine cfmtDNA level, but not urine ACR, was higher in participants who met frailty criteria for unintentional weight loss (n=8) (p=0.03, p=0.71, respectively) by t-test compared to those with stable weight (n=142) [Figure 1]. The mean urine cfmtDNA level did not differ statistically by other dichotomized frailty components (i.e. slow walk, weak grip, exhaustion, and low physical activity; p=0.46, p=0.53, p=0.23, p=0.68, respectively).
Figure 1: Higher Urine CfmtDNA Levels in OAH with Unintentional Weight Loss.
The boxplots above indicate the minimum, Q1, median, Q3, and maximum log-transformed urine cfmtDNA measurements for the group without unintentional weight loss and the group with unintentional weight loss of 10 pounds or greater.
In a backwards stepwise logistic regression model examining unintentional weight loss as the outcome that included urine cfmtDNA, age, moderate-severe albuminuria, drug use, smoking, COPD and depression, only urine cfmtDNA met criteria to remain in the model, and was statistically related to unintentional weight loss with an odds ratio of 2.1 [95% CI: 1.1– 4.0] for every one unit increase in log urine cfmtDNA (p=0.02). In a logistic regression model with unintentional weight loss as the outcome and urine cfmtDNA, age, and urine albumin per gram of creatinine as predictor variables, the relationship between urine cfmtDNA and unintentional weight loss remained statistically significant with an odds ratio of 2.3 (95%CI: 1.2–4.5, p=0.02).
Body Composition:
Median body mass index was in the overweight range (27 kg/m2, Q1, Q3: 25, 31). BIA data were available for 125 participants. In separate multiple linear regression models adjusted for age, sex, and presence of moderate-severe albuminuria, higher urine cfmtDNA was inversely associated with skeletal muscle index (SMI) (β =−0.19, p<0.01) as well as fat mass index (FMI) (β =−0.08, p=0.02). In a backwards stepwise linear regression model exploring the relationship between SMI as the outcome variable and log urine cfmtDNA, albuminuria, eGFR, age, sex, race, CD4 T-cell count, HIV viral load, current smoking, and use of integrase inhibitors, protease inhibitors, TDF or TAF, only log urine cfmtDNA (β= −0.27, p=0.02), female sex (β= −1.8, p<0.01), and current smoking (β= −0.93, p=0.02) met criteria to remain in the model.
Falls:
Falls within the past 6 months were reported by 22% of participants. The proportion of falls was higher with more advanced frailty state (p=0.04) by Chi-squared test. Six-month falls history was not significantly associated with urine cfmtDNA level, unintentional weight loss, SMI, or FMI.
Inflammatory Markers:
CRP, IL-6, IFN-γ, TNF-α, and TNFR1 did not statistically differ between the group with unintentional weight loss and those without by Wilcoxon Rank-Sum test (data not shown). Urine cfmtDNA level was correlated with serum TNFα level (Spearman rho=0.22, p<0.01), had a trend towards correlation with TNFαR1 (rho=0.14, p=0.09), but was not significantly correlated with IL-6, IFNγ nor CRP (data not shown).
Discussion:
In this study of OAH, a substantial portion of participants exhibited physical vulnerabilities, as two-thirds met criteria for a pre-frail or frail state and over one-fifth had experienced a fall in the prior 6 months. Higher levels of urine cfmtDNA were associated with unintentional weight loss, as well as lower SMI and FMI. Urine cfmtDNA was not related to falls, slow gait, weak grip, exhaustion, or low physical activity. Over one-third (36%) of participants exhibited moderate to severe albuminuria, a marker of renal dysfunction, which was related to urine cfmtDNA levels. Overall, these data support mitochondrial dysfunction as a potential contributing factor to less successful aging outcomes, including “shrinking” with unintentional weight loss and lower height-scaled body mass of fat and muscle. Higher CD4 T-cell count was associated with higher urine cfmtDNA levels, which was an unexpected and interesting finding that warrants further investigation.
The pathogenesis of geriatric syndromes in OAH is complex and remains incompletely understood, although it is likely due to multiple factors including chronic inflammation23,24, mitochondrial dysfunction7,25, and cellular death pathways associated with stimulating ongoing inflammation26. Recent data suggest the presence of cfmtDNA may stimulate pathways of immune activation that can lead to autoimmune disease processes27, and mtDNA haplogroup H has been associated with frailty in OAH28. Despite suppression of HIV-1 viremia ongoing inflammation could stimulate cellular metabolic changes which may be reflected by higher cfmtDNA levels, and could be investigated in future studies with radiolabeled tracers29. Urine cfmtDNA has been associated with poor longitudinal renal function, and maintaining healthy mitochondria has been suggested as a key pathway in maintaining kidney health30. As such, understanding the physiologic mechanisms of cfmtDNA may provide insight to the complex process of aging with HIV.
Our study is unique in that it focused on urine cfmtDNA as a novel biomarker in OAH, and to our knowledge, is the first study to evaluate urine cfmtDNA in relation to frailty or body composition. A strength of our study is the diverse participant population, with just over half identifying as Black, and over one-third women. Our study also assessed a broad range of psychosocial, functional, and biometric variables, which allowed for consideration of potential confounding factors in analyses of frailty, weight loss and body composition.
Our study has several limitations. Firstly, participants were recruited from a single academic medical center clinic in New York City, and it is possible that those who chose to participate may have been more health-conscious. We attempted to reduce such selection bias by randomly selecting individuals from the entire patient pool to invite to the study. Secondly, our data are limited by a lack of HIV-negative controls, which would help to determine whether cfmtDNA shows similar links among those without HIV. Thirdly, we relied on BIA to assess body composition and could not evaluate muscle quality or fat distribution31. We collected cross-sectional data from participants at the time of study enrollment and do not have historical data of prior ARV regimens, nor prior smoking history. Finally, the absolute difference in urine cfmtDNA levels between the group with unintentional weight loss and the group without was small, albeit statistically significant, and lacks a longitudinal assessment to measure body composition change and frailty transitions. Future studies could include evaluation of matched HIV-negative controls and longitudinal timepoints to assess how body composition, frailty, and renal function evolve over time in OAH in relation to urine cfmtDNA levels.
In summary, our data suggest that urine cfmtDNA may provide insight into the complex process of accelerated/accentuated aging in OAH, as higher levels of urine cfmtDNA were more common in participants with less robust physical condition. Hence, urine cfmtDNA has potential to serve as a biomarker of pathophysiologic aging processes that predispose OAH to geriatric syndromes, and longitudinal studies are warranted.
Funding Support:
NIH/NIAID T32 AI007613, National Center for Advancing Translational Sciences UL1TR000457, NCI K99 CA245488, American Psychological Foundation (Visionary Grant), Gilead Sciences, Weill Cornell Medicine Fund for the Future
Disclosures: C.J, H.D, Y.Z, and M.R. have no conflicts of interest. K.H. reports personal fees from Faeth Therapeutics, Inc., other from PESI, Inc, outside the submitted work; MC is supported by the NIH. The spouse of MC is a cofounder and shareholder, and serves on the Scientific Advisory Board of Proterris, SG is supported by unrestricted research grants from the NIH, Indiana University, and GlaxoSmithKline/ViiV. He has also received advisory fees from GlaxoSmithKline/ViiV and Gilead Sciences. E.S reports a grant from Gilead Sciences during the conduct of the study, M.G. reports grants from Gilead Sciences, during the conduct of the study; grants and personal fees from Regeneron, personal fees from Sobi, personal fees from UpToDate, personal fees from Springer, outside the submitted work.
References:
- 1.Guaraldi G, Orlando G, Zona S, et al. Premature age-related comorbidities among HIV-infected persons compared with the general population. Clinical Infectious Diseases 2011;53:1120–6. [DOI] [PubMed] [Google Scholar]
- 2.Pelchen-Matthews A, Ryom L, Borges ÁH, et al. Aging and the evolution of comorbidities among HIV-positive individuals in a European cohort. Aids 2018;32:2405–16. [DOI] [PubMed] [Google Scholar]
- 3.López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell 2013;153:1194–217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Visser M, Schaap LA. Consequences of sarcopenia. Clinics in geriatric medicine 2011;27:387–99. [DOI] [PubMed] [Google Scholar]
- 5.Picca A, Guerra F, Calvani R, et al. Mitochondrial dysfunction and aging: Insights from the analysis of extracellular vesicles. International journal of molecular sciences 2019;20:805. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Picca A, Lezza AMS, Leeuwenburgh C, et al. Circulating mitochondrial DNA at the crossroads of mitochondrial dysfunction and inflammation during aging and muscle wasting disorders. Rejuvenation research 2018;21:350–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Hunt M, Payne BA. Mitochondria and ageing with HIV. Current Opinion in HIV and AIDS 2019. [DOI] [PubMed] [Google Scholar]
- 8.Cossarizza A, Pinti M, Nasi M, et al. Increased plasma levels of extracellular mitochondrial DNA during HIV infection: a new role for mitochondrial damage-associated molecular patterns during inflammation. Mitochondrion 2011;11:750–5. [DOI] [PubMed] [Google Scholar]
- 9.Bhatia D, Capili A, Choi ME. Mitochondrial dysfunction in kidney injury, inflammation, and disease: potential therapeutic approaches. Kidney Research and Clinical Practice 2020;39:244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Nakahira K, Kyung S-Y, Rogers AJ, et al. Circulating mitochondrial DNA in patients in the ICU as a marker of mortality: derivation and validation. PLoS medicine 2013;10:e1001577. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Zhang WZ, Rice MC, Hoffman KL, et al. Association of urine mitochondrial DNA with clinical measures of COPD in the SPIROMICS cohort. JCI insight 2020;5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Banoth B, Cassel SL. Mitochondria in innate immune signaling. Translational Research 2018;202:52–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.West AP, Khoury-Hanold W, Staron M, et al. Mitochondrial DNA stress primes the antiviral innate immune response. Nature 2015;520:553–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Broz P, Dixit VM. Inflammasomes: mechanism of assembly, regulation and signalling. Nature Reviews Immunology 2016;16:407–20. [DOI] [PubMed] [Google Scholar]
- 15.Rosenthal J, Tyor W. Aging, comorbidities, and the importance of finding biomarkers for HIV-associated neurocognitive disorders. Journal of neurovirology 2019;25:673–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Zhang W, O’Brien N, Forrest JI, et al. Validating a shortened depression scale (10 item CES-D) among HIV-positive people in British Columbia, Canada. PloS one 2012;7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Erenrich R, Seidel L, Brennan-Ing M, Karpiak S HIV and Aging in San Francisco: Frindings from the Research on Older Adults with HIV (ROAH) 2.0 San Francisco Study.. https://bit.ly/2AhRvJV2018.
- 18.Justice A, McGinnis K, Skanderson M, et al. Towards a combined prognostic index for survival in HIV infection: the role of ‘non-HIV’biomarkers. HIV medicine 2010;11:143–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2001;56:M146–M57. [DOI] [PubMed] [Google Scholar]
- 20.Erlandson KM, Wu K, Koletar SL, et al. Association Between Frailty and Components of the Frailty Phenotype With Modifiable Risk Factors and Antiretroviral Therapy. J Infect Dis 2017;215:933–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Annals of internal medicine 2009;150:604–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chang C-I, Chen C-Y, Huang K-C, Wu C-H, Hsiung C, Hsu C-C. Comparison of three BIA muscle indices for sarcopenia screening in old adults. European geriatric medicine 2013;4:145–9. [Google Scholar]
- 23.Sereti I, Krebs SJ, Phanuphak N, et al. Editor’s choice: Persistent, Albeit Reduced, Chronic Inflammation in Persons Starting Antiretroviral Therapy in Acute HIV Infection. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America 2017;64:124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Erlandson KM, Ng D, Jacobson LP, et al. Inflammation, Immune Activation, Immunosenescence, and Hormonal Biomarkers in the Frailty-Related Phenotype of Men with or at Risk for HIV. The Journal of infectious diseases 2016:jiw523. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Hulgan T, Gerschenson M. HIV and mitochondria: more than just drug toxicity. Oxford University Press; 2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hunt PW, Lee SA, Siedner MJ. Immunologic biomarkers, morbidity, and mortality in treated HIV infection. The Journal of infectious diseases 2016;214:S44–S50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Crow MK. Mitochondrial DNA promotes autoimmunity. Science 2019;366:1445–6. [DOI] [PubMed] [Google Scholar]
- 28.Erlandson KM, Bradford Y, Samuels DC, et al. Mitochondrial DNA Haplogroups and Frailty in Adults Living with HIV. AIDS Research and Human Retroviruses 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Li J, Lu J, Zhou Y. Mitochondrial-targeted molecular imaging in cardiac disease. BioMed research international 2017;2017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Chang C-C, Chiu P-F, Wu C-L, et al. Urinary cell-free mitochondrial and nuclear deoxyribonucleic acid correlates with the prognosis of chronic kidney diseases. BMC nephrology 2019;20:391. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Natsag J, Erlandson KM, Sellmeyer DE, et al. HIV infection is associated with increased fatty infiltration of the thigh muscle with aging independent of fat distribution. PloS one 2017;12:e0169184. [DOI] [PMC free article] [PubMed] [Google Scholar]