Abstract
Background
Prior studies have found that human immunodeficiency virus (HIV) infection is associated with impaired lung function and increased risk of chronic lung disease, but few have included large numbers of women. In this study, we investigate whether HIV infection is associated with differences in lung function in women.
Methods
This was a cross-sectional analysis of participants in the Women’s Interagency HIV Study, a racially and ethnically diverse multicenter cohort of women with and without HIV. In 2018–2019, participants at 9 clinical sites were invited to perform spirometry. Single-breath diffusing capacity for carbon monoxide (DLCO) was also measured at selected sites. The primary outcomes were the post-bronchodilator forced expiratory volume in 1 second (FEV1) and DLCO. Multivariable regression modeling was used to analyze the association of HIV infection and lung function outcomes after adjustment for confounding exposures.
Results
FEV1 measurements from 1489 women (1062 with HIV, 427 without HIV) and DLCO measurements from 671 women (463 with HIV, 208 without HIV) met standards for quality and reproducibility. There was no significant difference in FEV1 between women with and without HIV. Women with HIV had lower DLCO measurements (adjusted difference, –0.73 mL/min/mm Hg; 95% confidence interval, −1.33 to −.14). Among women with HIV, lower nadir CD4 + cell counts and hepatitis C virus infection were associated with lower DLCO measurements.
Conclusions
HIV was associated with impaired respiratory gas exchange in women. Among women with HIV, lower nadir CD4 + cell counts and hepatitis C infection were associated with decreased respiratory gas exchange.
Keywords: HIV, hepatitis C, pulmonary function testing, lung disease, comorbidity
In this multicenter cohort of women with and without human immunodeficiency virus (HIV), HIV infection was associated with impaired respiratory gas exchange. Among participants with HIV, lower nadir CD4 + cell counts and hepatitis C infection were also associated with decreased respiratory gas exchange.
Human immunodeficiency virus (HIV) infection is associated with increased risk for comorbidities, including chronic lung disease [1–4]. Persons with HIV (PWH) experience increased occurrence of chronic obstructive pulmonary disease (COPD), pulmonary hypertension, and lung cancer [5–7]. How HIV contributes to the pathogenesis of comorbid respiratory illnesses is an area of active investigation [8]. Studies of respiratory physiology, that is, lung function, among PWH are vital to understanding how HIV affects respiratory health.
There is accumulating evidence that HIV infection adversely affects aspects of respiratory physiology including expiratory airflow, vital capacity, and respiratory gas exchange, but studies of lung function among PWH have included far fewer women than men [9–17]. Because sex differences influence susceptibility to and the natural history of lung diseases [18–21], there is uncertainty whether effects of HIV on respiratory physiology are accentuated or attenuated by sex. Since women comprise 52% of all PWH worldwide, there is an urgent and unmet need to include women in studies of HIV and lung function [22].
The Women’s Interagency HIV Study (WIHS) is one of the largest prospective cohort studies of women with and without HIV. An earlier study of lung function in 99 WIHS participants (63 with HIV, 36 without HIV) at the San Francisco research site found that HIV infection was associated with impaired respiratory gas exchange [11]. However, the small sample size of this study limited capacity for adjustment of confounding exposures, and the single-center design increased uncertainty regarding external validity. As such, lung function was measured across the entire WIHS cohort in 2018 and 2019. The results of this effort are reported here. The primary objective was to investigate whether, in women, HIV infection is associated with impairment in 2 key clinical dimensions of lung function: expiratory airflow and respiratory gas exchange. Among women with HIV, the relationships between measures of HIV disease severity and hepatitis C virus (HCV) infection with lung function outcomes were also evaluated.
METHODS
Participants and Study Design
The WIHS, now a part of the Multicenter AIDS Cohort Study (MACS)-WIHS Combined Cohort Study, was established in 1993 and has been described in prior publications [23, 24]. From 1 April 2018 to 30 September 2019, WIHS participants at all 9 clinical sites were invited to complete spirometry measurements and, at a subset of 5 sites with the necessary equipment, measurements of single-breath diffusing capacity. Participants were excluded if they were pregnant or had contraindications to lung function testing, such as a recent respiratory infection. Local institutional review boards approved the protocol, and participants provided informed consent.
Measurements
Spirometry
Key spirometric measurements include the forced expiratory volume in 1 second (FEV1), which is the volume of gas expelled in the first second of a maximal forced exhalation maneuver, and the forced vital capacity (FVC), which is the total volume of gas expelled in a maximal forced exhalation maneuver. Participants performed spirometry before and after inhaling 360 μg of albuterol via metered-dose inhaler. Measurements were made using an Easy on-PC or EasyOne Pro device (ndd Medizintechnik AG, Zurich, Switzerland). Quality was assessed in accordance with published standards [25]. Further details regarding quality control are described in the Supplementary Methods. Reference values were calculated from published equations derived from the Third National Health and Nutrition Examination Survey [26].
Single-Breath Diffusing Capacity for Carbon Monoxide
The single-breath diffusing capacity for carbon monoxide (DLCO), also referred to as the transfer factor for carbon monoxide, is a measurement of carbon monoxide uptake by the lungs during a single breath held for 10 seconds. Measurements were made using an EasyOne Pro device and were adjusted for hemoglobin and carboxyhemoglobin concentrations. Quality was assessed in accordance with international standards, and reference values were calculated from published equations derived from the First National Health and Nutrition Examination Survey [27, 28].
Demographic, Exposure, and Clinical Data
Data were collected from WIHS participants at semiannual visits using standardized instruments. Key exposures included cigarette smoking (measured in lifetime pack-years) and substance use; marijuana, cocaine, methamphetamine, and heroin exposures were categorized as never use, current use (any use reported in the 6 months prior), and former use (any lifetime use, but no use reported in the 6 months prior). HCV infection was defined as HCV seropositivity upon cohort enrollment or at any time up to lung function testing.
Statistical Analyses
The primary exposure of interest was HIV infection. The coprimary outcomes of interest were the post-bronchodilator FEV1 and the DLCO. Because the FEV1 and DLCO are affected by age, sex, height, and race, these measurements are compared to standardized reference values and reported as a percentage of the predicted value for age, sex, height, and race. Secondary outcomes include the FVC and the post-bronchodilator FEV1-to-FVC ratio.
In addition to their analyses as continuous variables, FEV1 and DLCO were also analyzed as dichotomous variables (less than 80% and 60% of predicted for mild and moderate impairment, respectively). The FEV1-to-FVC ratio was analyzed as a dichotomous variable (greater than or equal to vs less than 0.7, the threshold for diagnosis of COPD) as well.
Characteristics of participants with and without HIV were compared using t tests for continuous variables and the Fisher exact test for categorical variables.
Linear and logistic regression models were used to compare the primary outcomes between participants with and without HIV. A causal model (see the directed acyclic graph in Supplementary Figure 1) identified possible confounding exposures in published literature: cigarette smoking [29], marijuana use [29], cocaine use [30, 31], heroin or injection drug use [32], years of education [33, 34], and HCV infection [11]. Adjusted regression models included these exposures as covariates.
A secondary analysis restricted to participants with HIV examined the relationship between indicators of HIV severity and lung function outcomes. Exposure variables of interest were the CD4 + cell count at the time of lung function testing, lifetime nadir CD4 + cell count, lifetime peak HIV RNA, and cumulative years of exposure to antiretroviral therapy (ART).
Informed by prior research suggesting that HCV infection may affect respiratory gas exchange [11, 35–39], additional secondary analyses compared DLCO between HCV seropositive and seronegative participants. For this analysis, the participants with and without HIV were analyzed separately. Unadjusted and adjusted regression models estimated the association of HCV infection with DLCO.
RESULTS
Of the 2022 women who attended at least 1 study visit during the lung function testing window, 1736 met eligibility criteria and consented to study participation. Post-bronchodilator spirometry measurements from 1489 participants (1062 with HIV, 427 without HIV) and DLCO measurements from 671 participants (463 with HIV, 208 without HIV ) met standards for data quality (see Supplementary Figures 2 and 3 for participant flow diagrams).
Characteristics of Participants With Spirometry Measurements
The median age was 52 years (interquartile range, 44 to 58). Two-thirds (66%) were current or former cigarette smokers (Table 1). Participants with HIV were older, less likely to report ever smoking or using illicit substances, and more likely to be HCV seropositive but were otherwise similar to participants without HIV. Among participants with HIV, nearly all (92%) reported current ART, 69% had undetectable HIV RNA, and the median current CD4 + cell count was 700 cells/mm3.
Table 1.
Characteristics of Participating Women With and Without Human Immunodeficiency Virus at the Time of Pulmonary Function Testing
| Characteristic | With HIV (n = 1062) | Without HIV (n = 427) | P Value |
|---|---|---|---|
| Age, median (Q1–Q3), y | 52 (45–58) | 50 (42–57) | .01 |
| Body mass index, median (Q1–Q3), kg/m2 | 31.2 (26.5–37.9) | 32.6 (26.9–38.3) | .66 |
| Race | .11 | ||
| ȃAmerican Indian or Alaskan Native | 14 (1) | 7 (2) | |
| ȃAsian | 4 (0) | 5 (1) | |
| ȃNative Hawaiian or Pacific Islander | 1 (0) | 0 (0) | |
| ȃBlack | 699 (66) | 285 (67) | |
| ȃWhite | 114 (11) | 33 (8) | |
| ȃOther | 74 (7) | 21 (5) | |
| ȃMultiracial | 155 (15) | 76 (18) | |
| Education | .46 | ||
| ȃ12th grade or less | 677 (64) | 257 (60) | |
| ȃ1–3 years of college | 301 (28) | 132 (31) | |
| ȃ4+ years of college | 84 (8) | 37 (9) | |
| Monthly household income | .18 | ||
| ȃ$12 000 or less | 474 (45) | 183 (43) | |
| ȃ$12 001–$24 000 | 251 (24) | 88 (21) | |
| ȃ$24 001–$36 000 | 122 (11) | 49 (11) | |
| ȃMore than $36 000 | 175 (16) | 93 (22) | |
| Smoking | .005 | ||
| ȃNever | 379 (36) | 122 (29) | |
| ȃFormer | 320 (30) | 123 (29) | |
| ȃCurrent | 363 (34) | 182 (43) | |
| Smoking pack-years, median (Q1–Q3), cumulativea | 8.8 (3.4–16.8) | 9.5 (3.1–18.4) | .62 |
| Substance use | |||
| ȃMarijuana use | |||
| ȃȃCurrent | 228 (21) | 109 (26) | .17 |
| ȃȃEver | 712 (67) | 322 (75) | .002 |
| ȃCocaine or crack use | |||
| ȃȃCurrent | 63 (6) | 37 (9) | .07 |
| ȃȃEver | 444 (42) | 224 (52) | < .001 |
| ȃHeroin or injection drug use | |||
| ȃȃCurrent | 8 (1) | 10 (2) | .02 |
| ȃȃEver | 202 (19) | 106 (25) | .01 |
| ȃMethamphetamine use | |||
| ȃȃCurrent | 5 (1) | 3 (1) | .70 |
| ȃȃEver | 5 (1) | 3 (1) | .70 |
| ȃAny of the above | |||
| ȃȃCurrent | 244 (23) | 119 (29) | .05 |
| ȃȃEver | 743 (70) | 336 (79) | .001 |
| Liver disease | |||
| ȃHepatitis B infection, baseline | 28 (3) | 9 (2) | .43 |
| ȃHepatitis C infection, baseline or during follow-up | 196 (18) | 48 (11) | .001 |
| ȃ Aspartate aminotransferase to platelet ratio index, (Q1–Q3), median | 0.18 (0.14–0.26) | 0.16 (0.12–0.72) | .01 |
| ȃFibrosis-4 index, (Q1–Q3), median | 0.94 (0.7–1.36) | 0.84 (0.61–1.12) | .001 |
| HIV characteristics | |||
| ȃCD4+ cell count nadir, median (Q1–Q3), cells/mm3 | 231 (101–362) | ||
| ȃCD4+ cell count current, median (Q1–Q3), cells/mm3 | 700 (495–938) | ||
| ȃPeak HIV RNA (1000 copies/mL), (Q1–Q3), median | 45 (9.6–140) | ||
| ȃHIV RNA undetectable | 728 (69) | ||
| ȃCurrently on ART | 979 (92) | ||
| ȃCumulative ART years, (Q1–Q3), median | 5.9 (3.8–15) | ||
| ȃHistory of AIDS | 310 (29) | ||
| ȃHistory of Pneumocystis pneumonia | 65 (6) | ||
| Cohort of enrollment | |||
| ȃ1994–1995 | 298 (28) | 101 (24) | .001 |
| ȃ2001–2002 | 205 (19) | 120 (28) | |
| ȃ2011–2012 | 129 (12) | 60 (14) | |
| ȃ2013–2015 | 430 (40) | 146 (34) | |
| Site | .12 | ||
| ȃBrooklyn, New York | 171 (16) | 62 (14) | |
| ȃBronx, New York | 48 (5) | 24 (6) | |
| ȃWashington, District of Columbia | 146 (14) | 65 (15) | |
| ȃSan Francisco, California | 118 (11) | 63 (15) | |
| ȃChicago, Illinois | 136 (13) | 60 (14) | |
| ȃChapel Hill, North Carolina | 111 (10) | 35 (8) | |
| ȃAtlanta, Georgia | 129 (12) | 60 (14) | |
| ȃMiami, Florida | 66 (6) | 20 (5) | |
| ȃBirmingham, Alabama / Jackson, Mississippi | 133 (13) | 38 (9) |
Abbreviations: ART, antiretroviral therapy; HIV, human immunodeficiency virus; Q1, first quartile; Q3, third quartile.
For current and former smokers only.
The characteristics of the 671 participants with valid DLCO measurements were similar to those of the 1489 participants with valid spirometry data (Supplementary Table 1).
Association Between HIV Infection and Spirometric Outcomes
Among the 1489 participants with valid post-bronchodilator spirometry data, the median percent predicted FEV1 was similar for participants with and without HIV (90.3% vs 91.8%; Table 2). The difference in FEV1 between participants with and without HIV was not statistically significant in either unadjusted or adjusted analyses.
Table 2.
Differences in Lung Function Between Participating Women With and Without Human Immunodeficiency Virus
| Spirometry Outcomes | With HIV (n = 1062) | Without HIV (n = 427) | Unadjusted Comparisons | Adjusted Comparisons |
|---|---|---|---|---|
| Median (Q1–Q3) | Median (Q1–Q3) | Unadjusted mean difference (95% CI), P value |
Adjusted mean difference (95% CI), P value |
|
| Post-BD FEV1% predicted | 90.3 (79.6–102.6) | 91.8 (80.3–105.1) | −1.3 (−3.3 to .6) .20 |
−1.1 (−3.2 to .9)a .29 |
| Post-BD FVC % predicted | 90.4 (80.1–100.5) | 92.5 (81.1–103.0) | −1.8 (−3.6 to −.02) .047 |
−1.3 (−3.2 to .5)a .14 |
| Post-BD FEV1/FVC ratio | 0.82 (0.77–0.86) | 0.82 (0.77–0.86) | 0.002 (−.007 to .011) .70 |
−0.0004 (−.01 to .009)a .92 |
| n (%) | n (%) | Unadjusted OR (95% CI), P value |
Adjusted OR (95% CI), P value |
|
| Post-BD FEV1 < 80% predicted | 276 (26) | 102 (24) | 1.11 (.86 to 1.45) .40 |
1.10 (.84 to 1.44)a .49 |
| Post-BD FEV1 < 60% predicted | 51 (5) | 26 (6) | 0.78 (.48 to 1.27) .31 |
0.81 (.49 to 1.34)a .42 |
| COPD (FEV1/FVC < 0.7) | 106 (10) | 46 (11) | 0.91 (.64 to 1.32) .65 |
0.98 (.67 to 1.44)a .94 |
| COPD (FEV1/FVC < lower limit of normal) | 109 (10) | 52 (12) | 0.82 (.58 to 1.17) .28 |
0.88 (.61 to 1.26)a .48 |
| Diffusion Outcomes | With HIV (n = 463) | Without HIV (n = 208) | Unadjusted Comparisons | Adjusted Comparisons |
| Median (Q1–Q3) | Median (Q1–Q3) | Unadjusted mean difference (95% CI), P value |
Adjusted mean difference (95% CI), P value |
|
| DLCO % predicted | 84 (73–94) | 89 (76–101) | −4.9 (−7.8 to −2.0) .001 |
−4.8 (−7.7 to −1.9)a .001 |
| DLCO (mL/min/mm Hg) | 16.9 (14–19.3) | 17.6 (15.1–21.0) | −1.10 (−1.81 to −.38) .003 |
−0.73 (−1.33 to −.14)b .02 |
| n (%) | n (%) | Unadjusted OR (95% CI), P value |
Adjusted OR (95% CI), P value |
|
| DLCO < 80% predicted | 191 (41) | 69 (33) | 1.41 (1.00 to 1.99) .047 |
1.47 (1.02 to 2.12)a .040 |
| DLCO < 60% predicted | 39 (8) | 13 (6) | 1.38 (.72 to 2.64) .33 |
1.37 (.69 to 2.72)a .37 |
Abbreviations: BD, bronchodilator; CI, confidence interval; COPD, chronic obstructive pulmonary disease; DLCO, single-breath diffusing capacity for carbon monoxide; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; HIV, human immunodeficiency virus; OR, odds ratio; Q1, first quartile; Q3, third quartile.
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), marijuana use (current, former, or never), and hepatitis C infection.
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), marijuana use (current, former, or never), hepatitis C infection, race (Black, White, multiracial, or other), height, and age.
Participants with HIV had a lower percent predicted FVC than participants without HIV (unadjusted mean difference, −1.8). However, after adjustment for confounding exposures, the confidence intervals did not exclude the possibility of no effect.
The median FEV1-to-FVC ratio was the same for participants with and without HIV (0.82). The prevalence of COPD, defined as an FEV1-to-FVC ratio of less than 0.7, was not significantly different between participants with and without HIV (10% vs 11%). Using an alternative criterion to define COPD as an FEV1-to-FVC ratio less than the lower limit of normal yielded similar results.
Association Between HIV Infection and Respiratory Gas Exchange
Participants with HIV had lower DLCO measurements than participants without HIV (Table 2). After adjustment for confounding exposures, HIV infection was associated with a lower percent predicted DLCO of 4.8 (95% confidence interval [CI], −7.7 to −1.9; P = .001).
In a sensitivity analysis, the inclusion of study site and enrollment cohort in the regression model did not appreciably change the estimate of effect of HIV infection on DLCO (−4.9; 95% CI, −7.6 to −2.1; P = .001).
A sensitivity analysis that modeled the diffusing capacity outcome in native units (mL/min/mm Hg) while adjusting for both confounding exposures as well as factors known to affect the outcome (age, height, and race) confirmed the association of HIV infection with lower DLCO. On average, the DLCO for participants with HIV was 0.73 mL/min/mm Hg less than for participants without HIV (95% CI, −1.33 to −.14; P = .02).
When DLCO was modeled as a dichotomous outcome, participants with HIV had 1.47 times the odds of having mild diffusion impairment or worse (DLCO less than 80% of predicted) compared with participants without HIV, after adjustment for confounding exposures (95% CI, 1.02 to 2.12; P = .04). We did not find that participants with HIV were significantly more likely to have moderate diffusion impairment or worse (DLCO less than 60% of predicted) compared with participants without HIV (adjusted odds ratio, 1.37; 95% CI, .69 to 2.72; P = .37). However, the small number of participants with this degree of diffusion impairment may have limited statistical power to evaluate this threshold.
Participants who underwent diffusing capacity measurements had spirometry results that were similar to those for participants who did not (see Supplementary Table 2).
Indicators of HIV Severity and Lung Function
Among participants with HIV, a greater cumulative number of years of ART was associated with a larger FEV1 (Table 3); for every 10 years of ART, the percent predicted FEV1 was higher by 2.5 (95% CI, .8 to 4.2; P = .004). For diffusing capacity, a lower lifetime nadir CD4 + cell count was associated with a lower DLCO; for every decrease in 100 cells/μL, the percent predicted DLCO was lower by 1.0 (95% CI, −.3 to −1.7; P = .004).
Table 3.
Relationship Between Human Immunodeficiency Virus (HIV) Disease Variables and Pulmonary Function Outcomes Among Participating Women With HIV
| Outcome | Current CD4 + cell Count (per 100 Cells/μL) |
Nadir CD4 + cell Count (per 100 Cells/μL) |
Years of ART Exposure (per 10 Years of ART) |
Peak Human Immunodeficiency Virus RNA Viral Load (log10 Transformed) |
|---|---|---|---|---|
| Adjusted mean difference (95% CI), P valuea | ||||
| Post-BD FEV1% predicted | 0.0 (−0.3 to 0.3), .87 |
0.0 (−0.6 to 0.6), .98 |
2.5 (0.8 to 4.2), .004 |
−0.2 (−1.3 to 1.0), .79 |
| DLCO % predicted | 0.3 (−0.1 to 0.8), .09 |
1.0 (0.3 to 1.7), .004 |
−1.8 (−4.6 to 1.1), .22 |
−0.8 (−2.2 to 0.8), .34 |
| Adjusted odds ratio (95% CI), P valuea | ||||
| Post-BD FEV1 < 80% predicted | 1.0 (0.96 to 1.04), .87 |
1.0 (0.92 to 1.08), .95 |
0.76 (0.59 to 0.97), .03 |
0.98 (0.85 to 1.14), .84 |
| DLCO < 80% predicted | 0.95 (0.91 to 1.01), .12 |
0.89 (0.81 to 0.99), .03 |
1.12 (0.77 to 1.66), .54 |
1.05 (0.85 to 1.31), .62 |
Abbreviations: ART, antiretroviral therapy; BD, bronchodilator; CI, confidence interval; DLCO, single-breath diffusing capacity for carbon monoxide; FEV1, forced expiratory volume in 1 second.
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), marijuana use (current, former, or never), and hepatitis C infection.
Hepatitis C and Respiratory Gas Exchange
In multivariable regression modeling of the association between HIV and DLCO, HCV infection was associated with lower percent predicted DLCO (adjusted mean difference, −7.4; 95% CI, −11.4 to −3.3). Secondary analyses stratified participants by HIV status to model the relationship between HCV infection and DLCO among participants with HIV and participants without HIV separately (Table 4). Among participants with HIV, HCV infection was associated with a lower percent predicted DLCO by 8.3 after adjustment for confounding exposures, including cigarette smoking and heroin use (95% CI, −13.3 to −3.3; P = .001). Among participants without HIV, the point estimate for the effect of HCV infection on percent predicted DLCO was of similar magnitude (−6.3; 95% CI, −13.4 to .9; P = .09).
Table 4.
Relationship Between Hepatitis C Infection and Diffusing Capacity Among Participating Women With and Without Human Immunodeficiency Virus
| Outcome | Hepatitis C Positive | Hepatitis C Negative | Unadjusted comparisons | Adjusted comparisons |
|---|---|---|---|---|
| Median (Q1–Q3) | Median (Q1–Q3) | Unadjusted mean difference (95% CI), P value | Adjusted mean difference (95% CI), P value | |
| Overall | n = 127 | n = 543 | ||
| DLCO % predicted | −7.4 (−11.4 to −3.3)a <.001 |
|||
| With HIV only | n = 92 | n = 370 | ||
| DLCO % predicted | 75 (63–85) | 86 (77–96) | −11.1 (−14.7 to −7.4) <.001 |
−8.3 (−13.3 to −3.3)b .001 |
| Without HIV only | n = 35 | n = 173 | ||
| DLCO % predicted | 80 (70–94) | 90 (79–102) | −7.6 (−14.2 to −1.0) .02 |
−6.3 (−13.4 to .9)c .09 |
Abbreviations: CI, confidence interval; DLCO, single-breath diffusing capacity for carbon monoxide; HIV, human immunodeficiency virus; Q1, first quartile; Q3, third quartile.
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), marijuana use (current, former, or never), and HIV infection.
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), marijuana use (current, former, or never), and nadir CD4 + cell count (log transformed).
Adjusted for smoking (pack-years), education, ever heroin or injection drug use, cocaine use (current, former, or never), and marijuana use.
To investigate whether any effect of HCV on impaired DLCO was mediated by the development of liver fibrosis, a sensitivity analysis excluded participants with HCV who had ever reported a diagnosis of cirrhosis or had an aspartate aminotransferase-to-platelet ratio (APRI) greater than 0.5, a parameter that correlates with moderate liver fibrosis [40]. Excluding participants with HCV infection and a history of cirrhosis or a high APRI value (4 with HIV and 8 without HIV) did not substantially change the association between HCV infection and DLCO (a lower percent predicted DLCO by 9.6 among participants with HIV and 5.9 among participants without HIV).
DISCUSSION
In this racially, ethnically, and geographically diverse cohort of women with and without HIV, we found that HIV infection was associated with lower DLCO. We did not observe an association between HIV infection and lower FEV1. Among women with HIV, lower lifetime nadir CD4 + cell counts and HCV infection were associated with lower DLCO.
In this cohort, women with HIV had lower FEV1 measurements (the median value being 90.3% of predicted) than expected for age, height, sex, and race, indicating increased expiratory airflow obstruction when compared to a reference population. However, when compared to WIHS participants without HIV—a sample of women with similar demographic characteristics and, in some cases, with increased prevalence of exposures known to cause airflow obstruction such as cigarette smoking—there was no significant difference in FEV1, even after adjustment for confounding exposures. There was also no difference in the prevalence of COPD among participants with and without HIV.
In contrast to our findings, prior work in men has suggested an adverse impact of HIV on FEV1 [2, 10, 12, 13, 15, 16]. It is possible that the effect of HIV infection on expiratory airflow obstruction is specific to male sex. However, our results may be subject to survival bias as a result of the cross-sectional study design. Longitudinal lung function testing is underway in this cohort to determine whether women with HIV have accelerated decline in FEV1 as has been observed in other populations [41, 42].
We found that HIV infection is associated with lower DLCO measurements, which is consistent with an earlier study of lung function among WIHS participants at the San Francisco clinical site [11] and with other studies of mostly men, both in the pre-ART and the ART eras [9, 14, 32]. We note that this is the largest study of diffusing capacity in women with HIV to date. Strengths of this study include a sample population that is demographically representative of women with HIV in the United States, as well as detailed longitudinal data on confounding exposures. The effect estimate we observed was greater than in an earlier multicenter study of men in the MACS, suggesting the possibility of differential sex-specific effects on DLCO [14]. However, our estimate was smaller than among WIHS participants in San Francisco only (4.8 vs 5.8) [11], possibly due to differences in sample characteristics and analytic approach.
The mechanism by which HIV infection affects DLCO is not fully understood. DLCO is decreased in pathologic processes that reduce the surface area and volume of the pulmonary vascular bed. Whether diffusion impairment among PWH reflects incipient, preclinical emphysema; interstitial lung disease; pulmonary vascular disease; or some combination of these is uncertain. Also, it is not known whether diffusion impairment is a direct effect of HIV infection in lung tissue or if it is mediated by systemic immunosuppression or immune activation [43, 44]. Nevertheless, DLCO is an important marker of lung disease among those with and without HIV and has been associated with decreased quality of life and increased risk of mortality [45, 46]. Our study highlights the need to understand the pathologic processes by which HIV infection might cause impaired respiratory gas exchange.
In analyses limited to participants with HIV, a lower nadir CD4 + cell count was associated with decreased DLCO, which is consistent with prior studies among men with HIV in the MACS and among US veterans with HIV who obtain care at Veterans Affairs medical centers [9, 14]. We also found that a greater number of years of cumulative ART was associated with higher FEV1. However, this finding has not been observed elsewhere and should be considered provisional since cross-sectional studies such as this may be subject to survival bias.
We observed a robust association between HCV infection and DLCO in this cohort, which was also observed by Fitzpatrick et al [11]. In the earlier study of WIHS participants in San Francisco, however, key exposures, such as injection drug use, were not included in multivariable regression modeling due to sample size limitations (27 HCV seropositive women). In this larger multicenter study of WIHS participants, the relationship between HCV infection and DLCO persisted among women with HIV, even after adjustment for cigarette smoking and injection drug use.
Other than Fitzpatrick et al, prior studies have found that persons with HCV infection have a higher than expected prevalence of diffusion impairment (ranging from 10% to 76%), but these studies were small, mostly without seronegative comparison groups, and not directly comparable due to differences in target populations and measurement methods [35–39]. Our analysis provides further evidence of a relationship between HCV infection and diffusion impairment.
How HCV may adversely affect respiratory gas exchange is uncertain. Liver cirrhosis is a known cause of diffusion impairment, mediated in part by the hepatopulmonary syndrome [47, 48]. However, advanced liver disease is unlikely to explain the observed relationship between HCV infection and diffusion impairment in the study population, since few participants had cirrhosis and their exclusion did not affect the results. Alternatively, the effect of HCV on diffusing capacity may be mediated by cryoglobulins, low levels of which are common among persons with chronic HCV infection [49], which may cause a subclinical pulmonary vasculitis that could interfere with respiratory gas exchange [50].
Particular features of the WIHS cohort make this analysis a unique contribution to the literature on comorbidities associated with HIV. The WIHS is comprised of women, who are underrepresented in the scientific literature on HIV and lung function. Semiannual participant follow-up enabled frequent measurement of key exposure variables, such as cigarette smoking. The enrollment of participants without HIV who have similar demographic characteristics to participants with HIV may reduce unmeasured confounding.
Limitations of this analysis include the cross-sectional study design, which is subject to known biases. The lack of detailed echocardiographic, lung imaging, or right heart catheterization data limits mechanistic understanding of how HIV and HCV may cause diffusion impairment. Data on the prevalence of chronic bronchitis were not collected. Last, the small number of HCV-seropositive participants without HIV (n = 35) may have reduced power to detect a significant association between HCV and DLCO among persons without HIV.
CONCLUSIONS
HIV infection is associated with lower DLCO in women. Among women with HIV, a lower nadir CD4 + cell count and HCV infection are associated with lower DLCO. Further research is needed to understand the mechanisms by which HIV and HCV may affect DLCO.
Supplementary Data
Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments. The authors thank each of the Women’s Interagency HIV Study (WIHS) participants for their contributions to our understanding of respiratory health among persons with human immunodeficiency virus.
Disclaimer . The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH) or the US Department of Veterans Affairs.
Financial support. Multicenter AIDS Cohort Study / Women's Interagency HIV Study Combined Cohort Study (MWCCS) (principal investigators): Atlanta Clinical Research Site (CRS) (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; Bronx CRS (K. A. and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D’Souza, S. J. G., and Elizabeth Golub), U01-HL146193; Chicago–Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Chicago–Northwestern CRS (Steven Wolinsky), U01-HL146240; Northern California CRS (Bradley Aouizerat, Jennifer Price, and P. C. T.), U01-HL146242; Los Angeles CRS (Roger Detels and Matthew Mimiaga), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01-HL146208; University of Alabama at Birmingham and University of Mississippi Medical Center CRS (Mirjam-Colette Kempf, Jodie Dionne-Odom, and Deborah Konkle-Parker), U01-HL146192; University of North Carolina at Chapel Hill CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional cofunding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institute on Aging, National Institute of Dental & Craniofacial Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Nursing Research, National Cancer Institute, National Institute on Alcohol Abuse and Alcoholism, National Institute on Deafness and Other Communication Disorders, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute on Minority Health and Health Disparities, and in coordination and alignment with the research priorities of the NIH, Office of AIDS Research. MWCCS data collection is also supported by UL1-TR000004 (University of California San Francisco Clinical and Translational Science Institute), UL1-TR003098 (Johns Hopkins Institute for Clinical and Translational Research), UL1-TR001881 (University of California Los Angeles Clinical and Translational Science Institute), P30-AI-050409 (Emory Center for AIDS Research), P30-AI-073961 (Miami Center for AIDS Research), P30-AI-050410 (Center for AIDS Research, University of North Carolina at Chapel Hill), P30-AI-027767 (Center for AIDS Research, University of Alabama at Birmingham), and P30-MH-116867 (Center for HIV and Research in Mental Health at the University of Miami). The study was also supported by the NHLBI (K12 HL143961, R. J. W; R01 HL151421, S. P. B.; UG3 HL155806, S. P. B.), NIAID (K24 AI 108516, P. C. T.), National Institute of Biomedical Imaging and Bioengineering (R21 EB027891, S. P. B.), and the resources and the use of facilities at the Minneapolis Veterans Affairs Medical Center in Minneapolis. K. M. K. reports support for the present article from NIH/NHLBI (U01 AI034989).
Supplementary Material
Contributor Information
Richard J Wang, Department of Medicine, University of California–San Francisco, San Francisco, California, USA.
Mehdi Nouraie, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Ken M Kunisaki, Department of Medicine, Minneapolis Veterans Affairs Health Care System, Minneapolis, Minnesota, USA; Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA.
Laurence Huang, Department of Medicine, University of California–San Francisco, San Francisco, California, USA.
Phyllis C Tien, Department of Medicine, University of California–San Francisco, San Francisco, California, USA; Department of Medicine, San Francisco Veterans Affairs Health Care System, San Francisco, California, USA.
Kathryn Anastos, Department of Medicine, Albert Einstein College of Medicine, New York, New York, USA.
Neha Bhandari, Department of Medicine, Cook County Health, Chicago, Illinois, USA.
Surya P Bhatt, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Hector Bolivar, Department of Medicine, University of Miami, Miami, Florida, USA.
Sushma K Cribbs, Department of Medicine, Atlanta Veterans Affairs Health Care System, Atlanta, Georgia, USA; Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
Robert Foronjy, Department of Medicine, SUNY Downstate Health Sciences University, New York, New York, USA.
Stephen J Gange, Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA.
Deepa Lazarous, Department of Medicine, Georgetown University, Washington, D.C., USA.
Alison Morris, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
M Bradley Drummond, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
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