OR I G I N A L A R T I C L E Determinants of early change in serum creatinine after initiation of dolutegravir-based antiretroviral therapy in South Africa Rephaim Mpofu1 | Aida N. Kawuma1 | Roeland E. Wasmann1 | Godspower Akpomiemie2 | Nomathemba Chandiwana2 | Simiso Mandisa Sokhela2 | Michelle Moorhouse2 | Willem Daniel Francois Venter2 | Paolo Denti1 | Lubbe Wiesner1 | Frank A. Post3 | David W. Haas4,5 | Gary Maartens1 | Phumla Sinxadi1,6 1Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa 2Ezintsha, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa 3King's College Hospital NHS Foundation Trust, London, UK 4Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA 5Department of Internal Medicine, Meharry Medical College, Nashville, Tennessee, USA 6SAMRC/UCT Platform for Pharmacogenomics Research and Translation (PREMED) unit, Cape Town, South Africa Correspondence Phumla Sinxadi, Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, K45 Old Main Building, Groote Schuur Hospital, Observatory, 7925 Cape Town, South Africa. Email: phumla.sinxadi@uct.ac.za Funding information This work was supported in part by the Wellcome Trust through an investigator award to G.M. (212265/Z/18/Z) and core funding from the Wellcome Centre for Infectious Diseases Research in Africa (203135/Z/16/Z). For the purpose of open access, the author has applied a CC BY public copyright licence to any author-accepted manuscript version arising from this submission. R.M. received training in research that was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43 TW010559. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The National Institute of Allergy and Infectious Diseases Aims: Dolutegravir increases serum creatinine by inhibiting its renal tubular secretion and elimination. We investigated determinants of early changes in serum creatinine in a southern African cohort starting first-line dolutegravir-based antiretroviral ther- apy (ART). Methods: We conducted a secondary analysis of data from participants in a random- ized controlled trial of dolutegravir, emtricitabine and tenofovir disoproxil fumarate (TDF) or tenofovir alafenamide fumarate (TAF) (ADVANCE, NCT03122262). We assessed clinical, pharmacokinetic and genetic factors associated with change in serum creatinine from baseline to Week 4 using linear regression models adjusted for age, sex, baseline serum creatinine, HIV-1 RNA concentration, CD4 T-cell count, total body weight and co-trimoxazole use. Results: We included 689 participants, of whom 470 had pharmacokinetic data and 315 had genetic data. Mean change in serum creatinine was 11.3 (SD 9.9) μmol.L�1. Factors that were positively associated with change in serum creatinine at Week 4 were increased log dolutegravir area under the 24-h concentration–time curve (change in creatinine coefficient [β] = 2.78 μmol.L�1 [95% confidence interval (CI) 0.54, 5.01]), TDF use (β = 2.30 [0.53, 4.06]), male sex (β = 5.20 [2.92, 7.48]), The authors confirm that the Principal Investigators for the clinical study where the samples were obtained were Dr W.D. Francois Venter and Dr S. Sokhela, and that they had direct clinical oversight of the patients. Received: 17 August 2023 Revised: 20 December 2023 Accepted: 3 January 2024 DOI: 10.1111/bcp.16009 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2024 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society. Br J Clin Pharmacol. 2024;90:1247–1257. wileyonlinelibrary.com/journal/bcp 1247 https://orcid.org/0000-0002-4732-5879 https://orcid.org/0000-0001-7975-0178 https://orcid.org/0000-0002-5769-8150 https://orcid.org/0000-0001-8982-1099 https://orcid.org/0000-0001-7866-2651 https://orcid.org/0000-0002-2707-1533 https://orcid.org/0000-0002-8410-3247 https://orcid.org/0000-0002-4157-732X https://orcid.org/0000-0001-7494-079X https://orcid.org/0000-0002-9070-8699 https://orcid.org/0000-0002-2844-1612 https://orcid.org/0000-0002-5813-1594 https://orcid.org/0000-0003-3080-6606 https://orcid.org/0000-0002-1312-3523 mailto:phumla.sinxadi@uct.ac.za https://doi.org/10.1111/bcp.16009 http://creativecommons.org/licenses/by/4.0/ http://wileyonlinelibrary.com/journal/bcp (NIAID) (Award Numbers UM1 AI068634, UM1 AI068636 and UM1 AI106701; to University of Cape Town's Pharmacology laboratory and L.W.). NIH grant support also included AI110527, AI077505 and TR000445 (to D.W.H.). Grant support from USAID, Unitaid and the South African Medical Research Council (SAMRC) was received for the ADVANCE clinical trial (to S.S., N.C. and W.D.F.V.). Salary support to W.D.F.V. under the HLB-SIMPLe Alliance funded under Grant UG3HL156388 with the U.S. Department of Health and Human Services, National Institutes of Health, National Heart, Lung and Blood Institute (NIH/NHLBI). G.M. was supported in part by the National Research Foundation of South Africa (Grant 119078); P.S. was supported in part by the SAMRC under a self-initiated research grant and the National Research Foundation (Thuthuka UID113983 and the Black Academic Advancement Programme UID120647). The ADVANCE study is funded by Unitaid and ViiV Healthcare, with investigational product provided by ViiV Healthcare and Gilead Sciences. baseline serum creatinine (β = �0.22 [�0.31, �0.12]) and UGT1A1 rs929596 A!G polymorphism with a dominant model (β = �2.33 [�4.49, �0.17]). The latter did not withstand correction for multiple testing. Conclusions: Multiple clinical and pharmacokinetic factors were associated with early change in serum creatinine in individuals initiating dolutegravir-based ART. UGT1A1 polymorphisms may play a role, but further research on genetic determinants is needed. K E YWORD S cytochrome P450 enzymes, drug transporters, HIV/AIDS, pharmacogenomics, pharmacokinetic- pharmacodynamic 1 | INTRODUCTION Dolutegravir, an integrase strand transfer inhibitor and recommended component of first-line antiretroviral regimens, increases serum creati- nine by an average of 10% to 15%.1 This typically occurs within the first week of treatment initiation and plateaus by the fourth week.2–4 This does not reflect nephrotoxicity, but is instead due to the inhibi- tion of renal tubular cell transporters that facilitate creatinine elimina- tion by dolutegravir, including organic cation transporter 2 (OCT2), multidrug and toxin extrusion transporter 1 (MATE1) and multidrug and toxin extrusion transporter 2-K (MATE2-K).2,5,6 There is consider- able interindividual variability in the change in serum creatinine after starting dolutegravir: dolutegravir-based antiretroviral therapy (ART) has previously been associated with a mean change in creatinine of 11 μmol.L�1 (standard deviation, SD 8) after 4 weeks of treatment.7 This variability may be due to multiple factors including concomitant medication, remission or resolution of HIV-associated nephropathy with ART, intercurrent illness or genetic factors including those that affect plasma dolutegravir exposure or renal tubular cell transporter function.8 Improved understanding of factors associated with greater increases in serum creatinine when using dolutegravir could reduce the likelihood of unnecessarily changing ART regimens, particularly when dolutegravir is co-administered with other drugs that may cause nephrotoxicity such as tenofovir disoproxil fumarate (TDF). Dolutegravir is primarily metabolized in the liver by uridine 50- diphospho-glucuronosyltransferase 1A1 (UGT1A1),9 and frequent genetic UGT1A1 variants are associated with increased dolutegravir exposure. In a southern African population, UGT1A1 polymorphisms rs887829 and rs28899168 were associated with increased plasma dolutegravir exposure.10 A moderate exposure–response relationship has been reported between dolutegravir and change in creatinine clearance over time.3 It is possible that UGT1A1 variants that affect dolutegravir exposure could explain some of the variability in changes in creatinine with dolutegravir. A non-synonymous polymorphism in SLC22A2 that encodes OCT2 (rs316019) has been associated with reduced creatinine secretion.11,12 Additional transporters, MATE1 and MATE2-K, encoded by SLC47A1 and SLC47A2, respectively, are also involved in creatinine excretion.13,14 While few studies have assessed What is already known about this subject • Dolutegravir increases serum creatinine due to the inhibi- tion of renal transporters organic cation transporter 2 and multidrug and toxin extrusion protein 1. • Clinical, pharmacological and genetic determinants of dolutegravir-mediated increase in serum creatinine have not been characterized previously. What this study adds • Plasma dolutegravir exposure, use of tenofovir disoproxil fumarate, male sex and baseline serum creatinine were associated with change in serum creatinine in participants initiating dolutegravir. • Investigations for renal dysfunction may be most appro- priate for patients experiencing early creatinine increases of ≥30 μmol.L�1. 1248 MPOFU ET AL. 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense the role of MATE transporter polymorphisms in dolutegravir pharma- cokinetics/pharmacodynamics (PK/PD), a MATE1 polymorphism (rs2252281) has been associated with enhanced response to metfor- min in patients with diabetes.15 It is important to consider the role of these genetic variants on substrate transport. African populations exhibit a higher degree of genetic diversity than other ancestral groups.16 As most pharmacogenetic studies to date have been conducted in non-African populations, novel genetic variants that affect treatment responses may be discovered in African populations.16,17 The present study aimed to investigate associations between dolutegravir exposure, selected genetic polymorphisms and early changes in serum creatinine concentrations in a southern African cohort of treatment-naïve people with HIV (PWH) who initiated dolutegravir-containing ART. 2 | METHODS 2.1 | Study population We conducted a secondary analysis of clinical, laboratory, pharmaco- kinetic and genetic data collected in the ADVANCE clinical trial (Clinicaltrials.gov identifier: NCT03122262). ADVANCE was a phase 3, single-centre, open label, non-inferiority trial conducted in Johan- nesburg, South Africa. Treatment-naïve PWH were randomly assigned to one of three treatment arms: (1) TDF, emtricitabine (FTC) and dolutegravir; (2) TAF, FTC and dolutegravir; or (3) TDF, FTC and efa- virenz.18 The present analysis included ADVANCE participants who (1) were assigned to dolutegravir-containing arms and (2) had available serum creatinine measurements from baseline (defined as the period between study entry and treatment initiation) and Week 4 after start- ing therapy. 2.2 | Pharmacokinetic sampling Pharmacokinetic samples were collected from a subgroup of partici- pants who provided written informed consent. A subset of participants (n = 41) underwent intensive pharmacokinetic sampling after 96 weeks, and were sampled pre-dose, and at 1, 2, 4, 6, 8, as well as 24 h post dose. The remaining participants underwent sparse sampling at one of 12, 24, 36 or 48 weeks. The samples were stored at �80�C until analysis.10 2.3 | Pharmacokinetic analysis and modelling Plasma dolutegravir concentrations were measured by liquid chroma- tography with mass tandem spectrometry detection using an AB SCIEX API 4000 instrument, in the Division of Clinical Pharmacology at the University of Cape Town as described elsewhere.10 A popula- tion pharmacokinetic model was developed from the intensively sam- pled cohort using non-linear mixed-effects modelling. Individual 24-h dolutegravir area under the concentration–time curve (AUC0–24h) values were estimated from sparse samples using a post hoc Bayesian estimation method that accounted for participant characteristics. Details are described elsewhere.10 2.4 | Genotyping and quality control Whole blood samples were obtained from participants who consented to genetic testing. DNA was extracted from whole blood using a salting out procedure. Genotyping was conducted using the Illumina Infinium Multi-Ethnic Global BeadChip (MEGAEX) at Vanderbilt Tech- nologies for Advanced Genomics (VANTAGE), with quality control performed as described elsewhere.10 For genetic association analyses, we a priori selected 39 polymorphisms in UGT1A1 (rs1042640, rs10929302, rs11891311, rs12474441, rs28946889, rs3755319, rs3771341, rs4148324, rs4148325, rs6431630, rs6742078, rs8330, rs887829, rs929596); SLC22A2 (encoding OCT-2; rs12207180, rs2279463, rs28495851, rs3101823, rs3119304, rs3119311, rs3127573, rs3127575, rs316009, rs316019, rs316020, rs476235, rs515140, rs596881, rs77648599, rs79370442); and SLC47A1 (encoding MATE-1; rs11871125, rs12451696, rs2018675, rs2440164, rs2440165, rs2453580, rs2453583, rs2453584, rs894680). These polymorphisms were selected based on previously reported renal trait associations with P-values <5.0 � 10�8 in the GWAS Catalog,19 as well as polymorphisms associated with drug- related phenotypes with levels of evidence of 1 or 2A in the Pharma- cogenomics Knowledgebase (PharmGKB).20 We excluded three polymorphisms with minor allele frequencies less than 5%, leaving 36 evaluable polymorphisms (12 in UGT1A1, 15 in SLC22A2, 9 in SLC47A1). 2.5 | Statistical and genetic association analyses The primary outcome was change in serum creatinine from baseline to Week 4. Study baseline characteristics and change in serum creati- nine were summarized with descriptive statistics. We assessed the proportion of participants who had a clinically significant increase in serum creatinine using 20 μmol.L�1 and 15% as pre-defined upper limits of expected increases based on literature and national treat- ment guidelines.21–23 We calculated the upper 95% confidence inter- val of the absolute change in serum creatinine, as such confidence intervals are widely used in determining normal ranges.24 Data distri- butions were assessed by visual inspection using histograms, quantile–quantile plots, and were also assessed using the Shapiro– Wilk test. Continuous, non-parametric data were log-transformed. Univariable and multivariable linear regression models were devel- oped to assess relationships between change in serum creatinine and various factors in three separate analyses. First, in a clinical associa- tion analysis, we assessed relationships between change in serum cre- atinine and the following clinical and laboratory variables: age in years, sex (male or female), serum creatinine at baseline, tenofovir MPOFU ET AL. 1249 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense http://Clinicaltrials.gov prodrug allocation group (TDF or TAF, with TAF as reference), base- line CD4 T-cell count, plasma HIV-1 RNA concentration, baseline total body weight and use of co-trimoxazole (a known inhibitor of creati- nine tubular secretion5) in the first 4 weeks of treatment. Second, in a pharmacokinetic association analysis, we assessed relationships between change in serum creatinine and dolutegravir AUC0–24h while adjusting for the clinical covariates noted above. Third, we conducted a genetic association analysis by assessing relationships between change in serum creatinine and pre-selected genetic polymorphisms. Multivariable linear regression models were used to explore potential relationships between genetic polymorphisms and change in serum creatinine at Week 4, using additive, dominant and recessive assump- tions of allelic effects. To adjust for population stratification, we included the first two genetic principal components that were derived as described elsewhere.10,25 The above-mentioned clinical covariates (excluding dolutegravir PK estimates) were also included in the genetic association analysis. To exclude a potential additive influence of dolutegravir exposure on relationships between genetic polymor- phisms and change in creatinine, we conducted sensitivity analyses by including dolutegravir AUC0–24h in genetic regression models examin- ing polymorphisms in SLC22A2 and SLC47A1. To further assess potential relationships between change in creat- inine and polymorphisms in UGT1A1, SLC22A2 and SLC47A1, we con- sidered linkage disequilibrium (LD). Polymorphisms with R-squared (R2) coefficients greater than 0.8 were excluded from sensitivity ana- lyses. LD and statistical significance of associations between polymor- phisms and change in creatinine were illustrated with heatmaps and scatter plots of negative, log-transformed P-values from the linear regression models, respectively. Thresholds for statistical significance in genetic association ana- lyses were adjusted using the Bonferroni method by dividing the over- all threshold of 0.05 by the number of polymorphisms included per genetic model. Statistical and genetic analyses were conducted in STATA 16 IC,26 R version 4.2.227 and PLINK v1.9028 software. 3 | RESULTS A total of 702 participants were enrolled in the two dolutegravir arms of ADVANCE, 689 of whom were included in the clinical association analysis (13 participants were excluded due to absence of serum creati- nine data from Week 4). Of these 689 participants, 470 were included in the pharmacokinetic association analysis (219 who did not undergo pharmacokinetic sampling were excluded), and 315 were included in the genetic association analysis (362 who did not provide consent for genetic testing were excluded, as were 12 who failed genetic data qual- ity checks). Participant baseline characteristics are shown in Table 1. 3.1 | Analysis of clinical variables At Week 4, the mean change in serum creatinine was 11.3 μmol.L�1 (95% confidence interval [95% CI] = 10.5, 12.0), as detailed in Table 2. Participants in the TDF/dolutegravir (TDF/DTG) treatment group expe- rienced a greater increase in serum creatinine compared to those in the TAF/dolutegravir (TAF/DTG) group (12.1 and 10.4 μmol.L�1, respec- tively; P = .021). These changes corresponded to a relative mean change in serum creatinine of 17% overall, 18% in the TDF/DTG group and 16% in the TAF/DTG group. Substantial variability was noted in the change in serum creatinine as evidenced by an interquartile range (IQR) of �14 to 45 μmol.L�1 (range = �25 to 67). Among the 689 partici- pants in the study, 96 (14%) had changes in serum creatinine greater than 20 μmol.L�1, while 388 participants (56%) had treatment-emergent changes in creatinine greater than 15%. The upper bound of the 95% confidence interval for the change in serum creatinine was 31 μmol.L�1, which we rounded down to 30 μmol.L�1 for clinical application—23 (3%) of 689 participants (16 on TDF, 7 on TAF) exceeded this threshold. Univariable and multivariable linear regression analyses of change in serum creatinine at Week 4 are shown in Table 3. In the multivari- able analysis, male sex (P < .001) and TDF use (P = .008) were each positively associated with change in serum creatinine, while baseline serum creatinine was negatively associated with change in serum cre- atinine (P < .001). 3.2 | Pharmacokinetic analyses Univariable and multivariable linear regression showed that higher dolutegravir AUC0–24h was positively associated with change in serum creatinine at Week 4 (β = 2.78; 95% CI 0.54, 5.01; P = .015; Table 4). The modelled relationship between dolutegravir AUC0–24h and change in serum creatinine is presented in Figure 1. The multivariable analysis also found a positive association between change in serum creatinine and male sex, TDF use and lower baseline serum creatinine, in keeping with the clinical association analysis (Table 4). 3.3 | Genetic analysis When analysed using an additive genetic model, none of the 36 evalu- able polymorphisms were associated with change in serum creatinine (Figure 2). The polymorphism with the lowest P-value was UGT1A1 rs1042640 (P = .108; Figure 2; Table S1). Similarly, none of the evalu- ated polymorphisms were significant in recessive models (Figure S1; Table S1). Using a dominant genetic model, UGT1A1 rs929596 A!G was nominally associated with change in serum creatinine, but this did not withstand correction for multiple testing (P = .035; Figure S2; Tables S1 and S2). The mean change in serum creatinine when strati- fied by UGT1A1 rs929596 A!G genotype was 12.5, 9.5 and 12.4 μmol.L�1 for the A/A (major homozygous), A/G (heterozygous) and G/G (minor homozygous) genotypes, respectively (Figure 3). UGT1A1 polymorphism rs887829 C!T and SLC22A2 polymorphism rs316019 C!A were not associated with change in serum creatinine (Figure 3). Polymorphisms with the lowest P-values are shown in Table S1. Assessment of the other covariates in genetic analyses found that TDF use, age, male sex and baseline CD4 T-cell count were 1250 MPOFU ET AL. 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense positively associated with change in serum creatinine, while baseline serum creatinine was negatively associated with change in serum cre- atinine (Table S2). We conducted two sensitivity analyses: (1) We included dolute- gravir AUC0–24h as an additional covariate in models evaluating SLC22A2 and SLC47A1 polymorphisms (24 variants among 282 partici- pants were included; Table S3), and (2) we excluded 11 polymorphisms with LD R2 > .8 (leaving 25 polymorphisms for assessment; Figures S3–S5). Results from these sensitivity analyses were similar to those from the main analyses. 4 | DISCUSSION Among participants who were randomized to receive dolutegravir- containing ART during participation in ADVANCE, we found that mean serum creatinine increased by 11 μmol.L�1 from baseline to Week 4. Increased dolutegravir exposure, TDF use, older age, higher baseline CD4 T-cell count and male sex were independently associ- ated with an increase in serum creatinine, while higher baseline serum creatinine and UGT1A1 polymorphism rs929596 A!G were indepen- dently associated with a decrease in serum creatinine, though the TABLE 1 Study baseline characteristics of ADVANCE participants included in association analyses of clinical, pharmacokinetic and genetic variables. Variables Clinical (SD/IQR) Pharmacokinetic (SD/IQR) Genetic (SD/IQR) (n = 689) (n = 470) (n = 315) Age (years)† 32 (8) 33 (8) 32 (8) Sex Female 414 (60%) 280 (60%) 199 (63%) Male 275 (40%) 190 (40%) 116 (37%) Treatment group TDF 344 (50%) 234 (50%) 155 (49%) TAF 345 (50%) 236 (50%) 160 (51%) Nationality Malawi 7 (1%) 7 (1%) 5 (2%) Mozambique 14 (2%) 8 (2%) 6 (2%) South Africa 427 (62%) 285 (61%) 177 (56%) Zimbabwe 222 (32%) 157 (33%) 119 (38%) Othera 19 (3%) 13 (3%) 8 (3%) Total body weight (kg)† 69 (14) 69 (14) 68 (14) Serum creatinine (μmol.L�1)† 65 (14) 65 (14) 64 (13) log10 HIV-1 RNA concentration (cp.mL�1)* 4.4 (3.8, 4.9) 4.4 (3.8, 4.9) 4.4 (3.8, 4.9) CD4 T-cell count (cells.mm�3)* 292 (170, 457) 282 (170, 444) 292 (163, 459) Concomitant co-trimoxazole No 573 (83%) 384 (82%) 265 (84%) Yes 116 (17%) 86 (18%) 50 (16%) Note: Continuous variables are presented as means† or medians*, and standard deviations† or interquartile ranges* in parentheses. Abbreviations: TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate. aNationalities of participants included in the ‘other’ category: Democratic Republic of the Congo, Eswatini, Lesotho, Nigeria and Zambia. TABLE 2 Summary of absolute and relative per cent change in creatinine (μmol.L�1) at Week 4 in participants initiated on dolutegravir- containing antiretroviral therapy, stratified by tenofovir treatment group. Treatment groups Sample size Mean (%) 95% CI Min (%) Max (%) SD P-valuea TDF 344 12.1 (18%) 11.0, 13.2 �25.0 (�21%) 67.0 (120%) 10.4 .021 TAF 345 10.4 (16%) 9.4, 11.4 �17.0 (�19%) 51.0 (159%) 9.4 Overall 689 11.3 (17%) 10.5, 12.0 �25.0 (�21%) 67.0 (120%) 9.9 Note: Relative per cent change from baseline reported in brackets. Abbreviations: 95% CI, 95% confidence interval; SD, standard deviation; TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate. aP-value was calculated to evaluate the significance of change in serum creatinine between treatment group using a Student's two sample t-test with unequal variance. MPOFU ET AL. 1251 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense latter did not withstand correction for multiple testing. These findings help interpret the magnitude of change in renal function at Week 4 in individuals initiating dolutegravir-based ART. The early increase in serum creatinine in participants after dolute- gravir initiation is similar to that observed in other clinical trials.2,28,29 A phase I, placebo-controlled study that included healthy participants who were treated with 50 mg of dolutegravir given once or twice daily for 2 weeks, found a 10% and 14% decrease in creatinine clear- ance, respectively, by the end of Week 2.2 Similarly, a phase IIb dose- ranging study that included treatment-naïve adults with HIV found that dolutegravir 50 mg once daily was associated with a mean increase in serum creatinine of 12.2 μmol.L�1 after 1 week of therapy that persisted over the course of the trial.30 Importantly, these studies did not find evidence of nephrotoxicity associated with these changes in creatinine. The large variability observed in this analysis and previ- ous studies confirm that most patients will experience modest increases in serum creatinine on dolutegravir, however, some patients may experience relatively higher increases in serum creatinine that are not necessarily indicative of impaired renal function. Our finding that dolutegravir exposure is associated with increases in serum creatinine is consistent with previous studies.3 Novel features of our analysis include the relative contribution of TDF to change in serum creatinine compared with TAF, the potential con- tribution of genetic variability, and that the study involved an African TABLE 3 Univariable and multivariable linear regression models of associations of clinical variables with change in serum creatinine from baseline to Week 4 on dolutegravir. Variables Univariable regression Multivariable regression Beta (95% CI) P-value Beta (95% CI) P-valuea Age (years) 0.06 (�0.04, 0.16) .254 0.08 (�0.02, 0.18) .113 Male sex (ref = female) 1.05 (�0.50, 2.60) .185 4.37 (2.43, 6.31) <.001 TDF use (ref = TAF) 1.74 (0.26, 3.22) .022 1.96 (0.52, 3.40) .008 Baseline serum creatinine (μmol.L�1) �0.09 (�0.15, �0.03) .003 �0.20 (�0.27, �0.12) <.001 log10 HIV-1 RNA concentration (cp.mL�1) 0.81 (�0.26, 1.87) .138 0.33 (�0.83, 1.50) .576 ln CD4 T-cell count (cells.mm�3) �0.55 (�1.40, 0.31) .209 0.07 (�0.94, 1.08) .895 Concomitant co-trimoxazole (ref = no) 1.64 (�0.61, 3.89) .152 0.77 (�1.76, 3.30) .549 Total body weight (kg) �0.01 (�0.07, 0.04) .629 0.01 (�0.05, 0.07) .690 Note: A negative regression beta value (coefficient) indicates a decrease in change in creatinine per unit increase in variable value. Variables included in the multivariable regression: age, sex, TDF use, baseline serum creatinine, log10 HIV-1 RNA concentration, ln CD4 T-cell count, concomitant co-trimoxazole use and total body weight. Abbreviations: TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate. aP-values calculated with Student's t-tests. TABLE 4 Univariable and multivariable linear regression models assessing association between pharmacokinetic variables (including dolutegravir AUC0–24h) and change in serum creatinine from baseline to Week 4. Variables Univariable regression Multivariable regression Beta (95% CI) P-value Beta (95% CI) P-valuea ln dolutegravir AUC0–24h (mg.h.L�1) 2.56 (0.33, 4.80) .025 2.78 (0.54, 5.01) .015 Age (years) 0.06 (�0.07, 0.19) .370 0.11 (�0.01, 0.24) .080 Male sex (ref = female) 1.39 (�0.51, 3.29) .151 5.20 (2.92, 7.48) <.001 TDF use (ref = TAF) 2.26 (0.47, 4.06) .014 2.30 (0.53, 4.06) .011 Baseline serum creatinine (μmol.L�1) �0.10 (�0.18, �0.02) .018 �0.22 (�0.31, �0.12) <.001 log10 HIV-1 RNA concentration (cp.mL�1) 0.24 (�1.02, 1.50) .712 �0.38 (�1.73, 0.97) .579 ln CD4 T-cell count (cells.mm�3) �0.39 (�1.40, 0.62) .446 �0.08 (�1.29, 1.13) .899 Concomitant co-trimoxazole (ref = no) 1.39 (�1.26, 4.04) .304 0.82 (�2.07, 3.71) .578 Total body weight (kg) �0.05 (�0.10, 0.01) .093 �0.01 (�0.08, 0.05) .682 Note: A negative regression beta value (coefficient) indicates a decrease in change in creatinine per unit increase in variable value. Variables included in the multivariable regression: dolutegravir AUC0–24h, age, sex, TDF use, baseline serum creatinine, log10 HIV-1 RNA concentration, ln CD4 T-cell count, concomitant co-trimoxazole use and total body weight. Abbreviations: TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate. aP-values calculated with Student's t-tests. 1252 MPOFU ET AL. 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense population. To our knowledge, this is the largest study to date to eval- uate PK/PD associations between dolutegravir exposure and early changes in serum creatinine. As dolutegravir is an inhibitor of OCT-2, one of the main renal transporters responsible for creatinine elimina- tion, individuals with factors that increase dolutegravir concentrations are more likely to experience greater changes in serum creatinine. The modest changes observed in this study should not impact clinical care. Rather, they should serve as a reference against which subsequent creatinine measurements can be compared, thus allowing individuals with progressive decline in renal function due to other causes to be identified. Our finding that TDF was independently associated with an increase in serum creatinine when compared to TAF is in keeping with TAF's improved renal safety profile. Interestingly, this difference occurred early, within the first 4 weeks of treatment. A single arm study of PWH that were switched from a TDF-containing ART regi- men to one containing elvitegravir/cobicistat, FTC and TAF, observed increases in creatinine-estimated glomerular filtration rate (eGFR) and reductions in low molecular weight proteinuria in as few as 4 weeks.31 This observation is not limited to PWH: HIV-negative par- ticipants that were on pre-exposure prophylaxis and randomized to receive daily TDF/FTC also experienced a decline in eGFR and increased proteinuria within 4 weeks of treatment initiation com- pared to those on daily TAF/FTC.32 There are a few potential explanations for this: These early changes in creatinine may be medi- ated by further inhibition of creatinine elimination due to tenofovir.33 Tenofovir is a substrate of additional renal transporters that facilitate creatinine clearance such as organic anion transporters 1 and 3 (located on the basolateral membrane) and multidrug resistance protein transporter 4 (located on the luminal membrane).34,35 TDF results in a 10-fold increase in plasma tenofovir exposure compared to TAF, and this may be associated with increased competitive inhibi- tion of renal transporters that normally facilitate creatinine elimina- tion.36,37 Additionally, tenofovir may have modest potential for mitochondrial toxicity, though data are conflicting.37–39 As creatinine secretion is facilitated by energy-dependent transporters, a relative increase in mitochondrial toxicity in individuals receiving TDF may contribute towards further alterations in creatinine secretion. There- fore, exposure-dependent inhibition of these transporters by tenofo- vir may explain the increased serum creatinine during this short period of observation in our study. We found a possible association between changes in serum creat- inine and UGT1A1 rs929596 A!G polymorphism when dominant allelic effects were assumed. Participants with either an A/G or G/G genotype for this polymorphism were independently associated with a decrease in serum creatinine concentrations compared to those with the A/A genotype. While this was not significant after correcting for multiple testing, it lends support to the concept that UGT1A1 F IGURE 1 Linear relationship between change in serum creatinine and dolutegravir AUC0–24h based on the multivariable linear regression analysis. The scatter plot graph illustrates the predicted values of change in serum creatinine, calculated with estimated marginal means based on a multivariable linear regression model from the pharmacokinetic association analysis. Dolutegravir area under the concentration–time curve (AUC0–24h) values were incrementally increased within the range of observed dolutegravir exposure estimates, while holding constant at their means other variables, namely, age, sex, baseline serum creatinine, tenofovir treatment group (TDF or TAF use), HIV-1 RNA concentration, CD4 T-cell count, total body weight and concomitant co-trimoxazole use. The continuous lines on the scatter plot depict associations between natural log-transformed dolutegravir AUC0–24h values and model-based predictions of change in serum creatinine, while the observed changes in creatinine values are illustrated with circles. The P-value, determined with a Student's t-test, indicates the statistical significance of the estimated dolutegravir AUC0–24h variable in the multivariable linear regression model described in Table 4. MPOFU ET AL. 1253 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense polymorphisms may contribute to the variability in serum creatinine changes because of increased dolutegravir concentrations. This poly- morphism has previously been associated with increased total bilirubin concentrations, likely due to reduced glucuronidation activity of variant UGT1A1 enzymes compared to those encoded by the com- mon genotype.40 A recent genome-wide association study found that F IGURE 2 Linkage disequilibrium and significance of polymorphism associations within UGT1A1, SLC22A2 and SLC47A1 from additive regression models of genetic association analyses. The white-red colour gradient in this heatmap illustrates the pairwise linkage disequilibrium (LD) measured by R2, with red colour intensity indicating higher LD. Statistical significance of polymorphisms in the additive regression models are illustrated in the scatter plot using negative log-transformed P-values as determined by Student's t-tests. Higher negative log-transformed P- values indicate increased probability of statistical significance. The thresholds of significance without (red dashed line) and with (white dashed line) correction for multiple testing by the Bonferroni method are 0.05 and 1.39 � 10�3 respectively. Chr 2 = Chromosome 2; Chr 6 = Chromosome 6; Chr 17 = Chromosome 17. F IGURE 3 Observed change in serum creatinine at Week 4 by rs929596 (UGT1A1), rs887829 (UGT1A1) and rs316019 (SLC22A2) genotypes in participants initiated on dolutegravir-containing antiretroviral therapy. A jitter plot of the observed change in serum creatinine at Week 4 by rs929596 (UGT1A1), rs887829 (UGT1A1) and rs316019 (SLC22A2) genotypes in participants initiated on dolutegravir-containing antiretroviral therapy is shown. The plot displays the impact of UGT1A1 and SLC22A2 polymorphisms on the change in serum creatinine at Week 4. Error bars are displayed using standard deviation. P-values indicate statistical significance of polymorphisms from the additive and dominant§ models and were calculated using Student's t-test. 1254 MPOFU ET AL. 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense homozygous minor allele carriers of the UGT1A1 polymorphism rs887829 exhibited a 26% reduction in dolutegravir clearance com- pared to those homozygous for the major allele.10 The rs929596 and rs887829 polymorphisms have been mapped to a UGT1A cluster located on Chromosome 2 that houses multiple protein-coding, and non-encoding, genes.40 These polymorphisms were in moderate LD in this population (R2 = .75), which suggests that their effects may not be entirely independent. Our analysis did not find a significant associ- ation with the rs887829 polymorphism; however, it is possible that each polymorphism may have independent, additive effects on change in serum creatinine. We also did not find any significant associations between changes in serum creatinine and the genetic variants of SLC22A2 or SLC47A1. Prior studies have reported relationships between SLC22A2 variants (e.g., rs316019 C!A) and an increased risk for neuropsychiatric adverse effects on dolutegravir, while SLC47A1 variants have been linked to enhanced metformin responses in patients with diabetes.15,41 The lack of association in our study could be attributed to several factors including small effect sizes requiring larger samples, or the absence of polymorphisms in the pop- ulation that influence renal transporter function. We identified associations between changes in serum creatinine and four participant characteristics: age, sex, serum creatinine at baseline and CD4 cell count. Regarding age, similar magnitudes of association were noted within all sets of multivariable regression ana- lyses; however, this factor was only significant in the genetic ana- lyses. Older adults experience physiological changes to renal tubular handling of creatinine that may modify the magnitude of dolutegra- vir's inhibitory effect.42 Sex-related differences in creatinine clear- ance are well documented, with males generally demonstrating higher creatinine clearance compared to females.43,44 HIV-associated nephropathy and opportunistic diseases that can cause renal impair- ment become more common as the CD4 cell count declines. Previous studies have reported associations between CD4 cell count and improved renal function within the first few weeks of initiating ART.45 Our study has limitations. First, this was a secondary data analy- sis, therefore, we did not perform sample size calculations. As we used a convenience sampling strategy, only some participants had DNA extracted; the sample size may therefore have been inadequate to detect weak genetic associations, or with infrequent variants, and may have been subject to selection bias. Secondly, dolutegravir dosing in the group that underwent sparse pharmacokinetic sampling was not observed, and, therefore, pharmacokinetic modelling of its expo- sure may have been inaccurate. In addition, the estimation of dolute- gravir exposure was based on sparse samples obtained after 4 weeks of treatment, which may not adequately reflect exposure at the 4-week time point. However, it is expected that dolutegravir concen- trations would have reached steady state by Week 4, and would remain stable until pharmacokinetic sampling occurred, thus reducing the impact of this limitation on these results. While our study focused on the systemic exposure of dolutegravir and its relationship with changes in serum creatinine, it is important to consider the potential role of dolutegravir metabolites in renal function. Approximately 31% of the total oral dose of dolutegravir is excreted in urine, mostly through either glucuronide or hydroxyl metabolites.46 We did not measure dolutegravir metabolites and could not investigate their potential effects on change in creatinine. Furthermore, the use of a population pharmacokinetic or physiologically-based PK/PD model that incorporates the disposition of the parent drug and its metabo- lites, pharmacogenetics and the observed pharmacodynamic changes may have improved the robustness of these findings. This is an area worthy of future study. Our findings provide clinicians with reassurance regarding the implications of these modest changes in creatinine. It has been suggested that creatinine increases due to dolutegravir are unlikely to exceed 20 μmol.L�1 and that greater increases should prompt consideration for alternative causes.21–23 However, we found that a substantial proportion of participants on TDF and dolutegravir had changes in serum creatinine greater than this. We propose consid- eration of a higher threshold (e.g., 30 μmol.L�1) based on the sample distribution and addition of 1.96 standard deviations from the mean, to guide the need for closer monitoring and further diag- nostic investigations. We also suggest that alternative methods to assess renal function using other, freely filtered endogenous markers such as cystatin C, should be considered for patients on dolutegravir as they are not dependent on OCT-2 transport and are therefore less susceptible to dolutegravir's effects on creatinine elimination.47–49 In conclusion, we identified clinical and pharmacokinetic determi- nants of early changes in creatinine in southern Africans initiated on dolutegravir-containing ART. UGT1A1 polymorphisms may play a role, but further research is needed. Investigations examining gene–gene and gene–environment interactions may provide additional insight into the risk of clinically relevant changes in creatinine concentrations in the presence of multiple polymorphisms. Although the long-term significance of these early increases in serum creatinine remains uncertain, improved understanding of the underlying mechanisms and predisposing factors may avoid unnecessary changes to otherwise effective ART regimens. AUTHOR CONTRIBUTIONS Nomathemba Chandiwana, Simiso Mandisa Sokhela and Willem Daniel Francois Venter were responsible for the overall conduct of the clinical trial that provided data for this analysis. Godspower Akpomiemie was involved in the curation and management of the original clinical trial data. Rephaim Mpofu was responsible for concep- tualization, data curation and management specific to this study, data analysis, presentation and interpretation of results and manuscript development. Phumla Sinxadi and Gary Maartens were responsible for conceptualization, data analysis and interpretation and manuscript development stages. David W. Haas and Frank A. Post provided input during study design, analysis and manuscript development and editing stages. Lubbe Wiesner supervised the dolutegravir concentration assay procedures, and Aida N. Kawuma, Roeland E. Wasmann and Paolo Denti performed the pharmacokinetic modelling. All authors reviewed the final manuscript. MPOFU ET AL. 1255 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense ACKNOWLEDGEMENTS We would like to thank all those involved in the study for their contri- bution, including the ADVANCE study participants. Computations were performed using facilities provided by the University of Cape Town's Information and Communication Technology Services High Performance Computing team (https://uctpc.uct.ac.za). CONFLICT OF INTEREST STATEMENT Ezintsha receives funding from the Bill and Melinda Gates Foundation, SA Medical Research Council, National Institutes for Health, AIDS Fonds, Unitaid, Foundation for Innovative New Diagnostics and the Children's Investment Fund Foundation; has recently received funding from USAID; and receives drug donations from ViiV Healthcare, Merck and Gilead Sciences for investigator-led clinical studies. The unit does investigator-led studies with Merck and ViiV providing financial support and is doing commercial drug studies for Merck. The unit performs evaluations of diagnostic devices for multiple biotech companies. Individually, W.D.F.V. receives honoraria for talks and advisory board membership for Gilead, ViiV, Mylan, Merck, Adcock-Ingram, Aspen, Abbott, Roche, J&J and Virology Education. S.S. and N.C. report grant support from ViiV Healthcare and Gilead Sciences during the conduct of the study. F.A.P. has received hono- raria from ViiV Healthcare, Gilead Sciences and Merck, and research grants from ViiV Healthcare and Gilead Sciences. For the remaining authors, no conflicts of interest were declared. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. ORCID Rephaim Mpofu https://orcid.org/0000-0002-4732-5879 Aida N. Kawuma https://orcid.org/0000-0001-7975-0178 Roeland E. Wasmann https://orcid.org/0000-0002-5769-8150 Godspower Akpomiemie https://orcid.org/0000-0001-8982-1099 Nomathemba Chandiwana https://orcid.org/0000-0001-7866- 2651 Simiso Mandisa Sokhela https://orcid.org/0000-0002-2707-1533 Michelle Moorhouse https://orcid.org/0000-0002-8410-3247 Willem Daniel Francois Venter https://orcid.org/0000-0002-4157- 732X Paolo Denti https://orcid.org/0000-0001-7494-079X Lubbe Wiesner https://orcid.org/0000-0002-9070-8699 Frank A. Post https://orcid.org/0000-0002-2844-1612 David W. Haas https://orcid.org/0000-0002-5813-1594 Gary Maartens https://orcid.org/0000-0003-3080-6606 Phumla Sinxadi https://orcid.org/0000-0002-1312-3523 REFERENCES 1. World Health Organization. Update of recommendations on first- and second-line antiretroviral regimens. [Internet]. 2019. Accessed January 26, 2024. Available from: https://apps.who.int/iris/ bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf 2. Koteff J, Borland J, Chen S, et al. A phase 1 study to evaluate the effect of dolutegravir on renal function via measurement of iohexol and para-aminohippurate clearance in healthy subjects. Br J Clin Pharmacol. 2013;75(4):990-996. doi:10.1111/j.1365-2125.2012. 04440.x 3. Zhang J, Hayes S, Sadler BM, et al. Population pharmacokinetics of dolutegravir in HIV-infected treatment-naive patients. Br J Clin Phar- macol. 2015;80(3):502-514. doi:10.1111/bcp.12639 4. Lindeman TA, Duggan JM, Sahloff EG. Evaluation of serum creatinine changes with integrase inhibitor use in human immunodeficiency virus-1 infected adults. Open Forum Infect Dis. 2016;3(2):ofw053. doi: 10.1093/ofid/ofw053 5. Chu X, Bleasby K, Chan GH, Nunes I, Evers R. The complexities of interpreting reversible elevated serum creatinine levels in drug devel- opment: does a correlation with inhibition of renal transporters exist? Drug Metab Dispos. 2016;44(9):1498-1509. doi:10.1124/dmd.115. 067694 6. Nakada T, Kudo T, Kume T, Kusuhara H, Ito K. Estimation of changes in serum creatinine and creatinine clearance caused by renal trans- porter inhibition in healthy subjects. Drug Metab Pharmacokinet. 2019;34(4):233-238. doi:10.1016/j.dmpk.2019.02.006 7. Walmsley SL, Antela A, Clumeck N, et al. Dolutegravir plus abacavir- lamivudine for the treatment of HIV-1 infection. N Engl J Med. 2013; 369(19):1807-1818. doi:10.1056/NEJMoa1215541 8. Post FA, Hamzah L. Correcting eGFR for the effects of ART on tubu- lar creatinine secretion: does one size fit all? Antivir Ther. 2020;25(5): 241-243. doi:10.3851/imp3378 9. Kandel CE, Walmsley SL. Dolutegravir—a review of the pharmacology, efficacy, and safety in the treatment of HIV. Drug Des Devel Ther. 2015;9:3547-3555. doi:10.2147/dddt.S84850 10. Cindi Z, Kawuma AN, Maartens G, et al. Pharmacogenetics of dolutegravir plasma exposure among Southern Africans living with HIV. J Infect Dis. 2022;226(9):1616-1625. doi:10.1093/infdis/ jiac174 11. Chambers JC, Zhang W, Lord GM, et al. Genetic loci influencing kid- ney function and chronic kidney disease. Nat Genet. 2010;42(5):373- 375. doi:10.1038/ng.566 12. Reznichenko A, Sinkeler SJ, Snieder H, et al. SLC22A2 is associated with tubular creatinine secretion and bias of estimated GFR in renal transplantation. Physiol Genomics. 2013;45(6):201-209. doi:10.1152/ physiolgenomics.00087.2012 13. Yonezawa A, Inui K. Importance of the multidrug and toxin extrusion MATE/SLC47A family to pharmacokinetics, pharmacodynamics/ toxicodynamics and pharmacogenomics. Br J Pharmacol. 2011;164(7): 1817-1825. doi:10.1111/j.1476-5381.2011.01394.x 14. Masuda S, Terada T, Yonezawa A, et al. Identification and functional characterization of a new human kidney-specific H+/organic cation antiporter, kidney-specific multidrug and toxin extrusion 2. J Am Soc Nephrol. 2006;17(8):2127-2135. doi:10.1681/asn.2006030205 15. Stocker SL, Morrissey KM, Yee SW, et al. The effect of novel pro- moter variants in MATE1 and MATE2 on the pharmacokinetics and pharmacodynamics of metformin. Clin Pharmacol Ther. 2013;93(2): 186-194. doi:10.1038/clpt.2012.210 16. Rajman I, Knapp L, Hanna I. Genetic diversity in drug transporters: impact in African populations. Clin Transl Sci. 2020;13(5):848-860. doi:10.1111/cts.12769 17. Pereira L, Mutesa L, Tindana P, Ramsay M. African genetic diversity and adaptation inform a precision medicine agenda. Nat Rev Genet. 2021;22(5):284-306. doi:10.1038/s41576-020-00306-8 18. Venter WDF, Sokhela S, Simmons B, et al. Dolutegravir with emtrici- tabine and tenofovir alafenamide or tenofovir disoproxil fumarate versus efavirenz, emtricitabine, and tenofovir disoproxil fumarate for initial treatment of HIV-1 infection (ADVANCE): week 96 results from a randomised, phase 3, non-inferiority trial. Lancet HIV. 2020;7(10): e666-e676. doi:10.1016/s2352-3018(20)30241-1 1256 MPOFU ET AL. 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://uctpc.uct.ac.za https://orcid.org/0000-0002-4732-5879 https://orcid.org/0000-0002-4732-5879 https://orcid.org/0000-0001-7975-0178 https://orcid.org/0000-0001-7975-0178 https://orcid.org/0000-0002-5769-8150 https://orcid.org/0000-0002-5769-8150 https://orcid.org/0000-0001-8982-1099 https://orcid.org/0000-0001-8982-1099 https://orcid.org/0000-0001-7866-2651 https://orcid.org/0000-0001-7866-2651 https://orcid.org/0000-0001-7866-2651 https://orcid.org/0000-0002-2707-1533 https://orcid.org/0000-0002-2707-1533 https://orcid.org/0000-0002-8410-3247 https://orcid.org/0000-0002-8410-3247 https://orcid.org/0000-0002-4157-732X https://orcid.org/0000-0002-4157-732X https://orcid.org/0000-0002-4157-732X https://orcid.org/0000-0001-7494-079X https://orcid.org/0000-0001-7494-079X https://orcid.org/0000-0002-9070-8699 https://orcid.org/0000-0002-9070-8699 https://orcid.org/0000-0002-2844-1612 https://orcid.org/0000-0002-2844-1612 https://orcid.org/0000-0002-5813-1594 https://orcid.org/0000-0002-5813-1594 https://orcid.org/0000-0003-3080-6606 https://orcid.org/0000-0003-3080-6606 https://orcid.org/0000-0002-1312-3523 https://orcid.org/0000-0002-1312-3523 https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf info:doi/10.1111/j.1365-2125.2012.04440.x info:doi/10.1111/j.1365-2125.2012.04440.x info:doi/10.1111/bcp.12639 info:doi/10.1093/ofid/ofw053 info:doi/10.1124/dmd.115.067694 info:doi/10.1124/dmd.115.067694 info:doi/10.1016/j.dmpk.2019.02.006 info:doi/10.1056/NEJMoa1215541 info:doi/10.3851/imp3378 info:doi/10.2147/dddt.S84850 info:doi/10.1093/infdis/jiac174 info:doi/10.1093/infdis/jiac174 info:doi/10.1038/ng.566 info:doi/10.1152/physiolgenomics.00087.2012 info:doi/10.1152/physiolgenomics.00087.2012 info:doi/10.1111/j.1476-5381.2011.01394.x info:doi/10.1681/asn.2006030205 info:doi/10.1038/clpt.2012.210 info:doi/10.1111/cts.12769 info:doi/10.1038/s41576-020-00306-8 info:doi/10.1016/s2352-3018(20)30241-1 19. Sollis E, Mosaku A, Abid A, et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res. 2023; 51(D1):D977-D985. doi:10.1093/nar/gkac1010 20. Whirl-Carrillo M, Huddart R, Gong L, et al. An evidence-based frame- work for evaluating pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2021;110(3):563-572. doi:10.1002/ cpt.2350 21. National Department of Health. 2019 ART Clinical Guidelines for the management of HIV in adults, pregnancy, adolescents, chil- dren, infants and neonates. [Internet]. 2019. Accessed February 15, 2023. Available from: https://www.nicd.ac.za/wp-content/uploads/ 2019/11/2019-ART-Clinical-Guidelines-25-Nov.pdf 22. Nel J, Dlamini S, Meintjes G, et al. Southern African HIV Clinicians Society guidelines for antiretroviral therapy in adults: 2020 update. South Afr J HIV Med. 2020;21(1):a1115. doi:10.4102/sajhivmed. v21i1.1115 23. Milburn J, Jones R, Levy JB. Renal effects of novel antiretroviral drugs. Nephrol Dial Transplant. 2017;32(3):434-439. doi:10.1093/ndt/ gfw064 24. Whitley E, Ball J. Statistics review 2: samples and populations. Crit Care. 2002;6(2):143-148. doi:10.1186/cc1473 25. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904-909. doi:10.1038/ng1847 26. StataCorp. Stata Statistical Software: Release 16. StataCorp LLC; 2019. 27. Posit Team. RStudio: Integrated Development Environment for R. Posit Software, PBC; 2022. http://www.posit.co/ 28. Raffi F, Rachlis A, Stellbrink HJ, et al. Once-daily dolutegravir versus raltegravir in antiretroviral-naive adults with HIV-1 infection: 48 week results from the randomised, double-blind, non-inferiority SPRING-2 study. Lancet. 2013;381(9868):735-743. doi:10.1016/s0140-6736 (12)61853-4 29. Cahn P, Madero JS, Arribas JR, et al. Dolutegravir plus lamivudine ver- sus dolutegravir plus tenofovir disoproxil fumarate and emtricitabine in antiretroviral-naive adults with HIV-1 infection (GEMINI-1 and GEMINI-2): week 48 results from two multicentre, double-blind, ran- domised, non-inferiority, phase 3 trials. Lancet. 2019;393(10167): 143-155. doi:10.1016/S0140-6736(18)324620 30. Stellbrink H-J, Reynes J, Lazzarin A, et al. Dolutegravir in antiretroviral-naive adults with HIV-1. AIDS. 2013;27(11):1771-1778. doi:10.1097/qad.0b013e3283612419 31. Post FA, Tebas P, Clarke A, et al. Switching to tenofovir alafenamide, coformulated with elvitegravir, cobicistat, and emtricitabine, in HIV- infected adults with renal impairment: 96-week results from a single- arm, multicenter, open-label phase 3 study. J Acqir Immune Defic Syndr. 2017;74(2):180-184. doi:10.1097/qai.0000000000001186 32. Mills A, Workowski K, Campbell T, et al. Renal outcomes for participants taking F/TAF vs. F/TDF for HIV PrEP in the DISCOVER trial. Open Forum Infect Dis. 2019;6(Suppl 2):S64. doi:10.1093/ofid/ ofz359.139 33. Gutiérrez F, Fulladosa X, Barril G, Domingo P. Renal tubular transporter-mediated interactions of HIV drugs: implications for patient management. AIDS Rev. 2014;16(4):199-212. 34. Venter WDF, Fabian J, Feldman C. An overview of tenofovir and renal disease for the HIV-treating clinician. South Afr J HIV Med. 2018;19(1):817. doi:10.4102/sajhivmed.v19i1.817 35. Bam RA, Yant SR, Cihlar T. Tenofovir alafenamide is not a substrate for renal organic anion transporters (OATs) and does not exhibit OAT-dependent cytotoxicity. Antivir Ther. 2014;19(7):687-692. doi: 10.3851/IMP2770 36. Aloy B, Tazi I, Bagnis CI, et al. Is tenofovir alafenamide safer than tenofovir disoproxil fumarate for the kidneys? AIDS Rev. 2016;18(4): 184-192. 37. Hall AM. Update on tenofovir toxicity in the kidney. Pediatr Nephrol. 2013;28(7):1011-1023. doi:10.1007/s00467-012-2269-7 38. Stray KM, Park Y, Babusis D, et al. Tenofovir alafenamide (TAF) does not deplete mitochondrial DNA in human T-cell lines at intracellular concentrations exceeding clinically relevant drug expo- sures. Antiviral Res. 2017;140:116-120. doi:10.1016/j.antiviral.2017. 01.014 39. Venhoff N, Setzer B, Melkaoui K, Walker UA. Mitochondrial toxicity of tenofovir, emtricitabine and abacavir alone and in combination with additional nucleoside reverse transcriptase inhibitors. Antivir Ther. 2007;12(7):1075-1085. doi:10.1177/135965350701200704 40. Coltell O, Asensio EM, Sorlí JV, et al. Genome-wide association study (GWAS) on bilirubin concentrations in subjects with metabolic syn- drome: sex-specific GWAS analysis and gene-diet interactions in a Mediterranean population. Nutrients. 2019;11(1):90. doi:10.3390/ nu11010090 41. Borghetti A, Calcagno A, Lombardi F, et al. SLC22A2 variants and dolutegravir levels correlate with psychiatric symptoms in persons with HIV. J Antimicrob Chemother. 2019;74(4):1035-1043. doi:10. 1093/jac/dky508 42. Morrissey KM, Stocker SL, Wittwer MB, Xu L, Giacomini KM. Renal transporters in drug development. Annu Rev Pharmacol Toxicol. 2013; 53(1):503-529. doi:10.1146/annurev-pharmtox-011112-140317 43. Bjornsson TD. Use of serum creatinine concentrations to determine renal function. Clin Pharmacokinet. 1979;4(3):200-222. doi:10.2165/ 00003088-197904030-00003 44. Saboli�c I, Asif AR, Budach WE, Wanke C, Bahn A, Burckhardt G. Gen- der differences in kidney function. Pflügers Archiv. 2007;455(3):397- 429. doi:10.1007/s00424-007-0308-1 45. Reid A, Stöhr W, Walker AS, et al. Severe renal dysfunction and risk factors associated with renal impairment in HIV-infected adults in Africa initiating antiretroviral therapy. Clin Infect Dis. 2008;46(8): 1271-1281. doi:10.1086/533468 46. Castellino S, Moss L, Wagner D, et al. Metabolism, excretion, and mass balance of the HIV-1 integrase inhibitor dolutegravir in humans. Antimicrob Agents Chemother. 2013;57(8):3536-3546. doi:10.1128/ aac.00292-13 47. Yoshino Y, Koga I, Seo K, Kitazawa T, Ota Y. Short communication: the clinical value of cystatin C as a marker of renal function in HIV patients receiving dolutegravir. AIDS Res Hum Retroviruses. 2017; 33(11):1080-1082. doi:10.1089/aid.2017.0074 48. Palich R, Tubiana R, Abdi B, et al. Plasma cystatin C as a marker for estimated glomerular filtration rate assessment in HIV-1-infected patients treated with dolutegravir-based ART. J Antimicrob Che- mother. 2018;73(7):1935-1939. doi:10.1093/jac/dky112 49. Mazaheri T, Buchanan D, Hung R, et al. Creatinine and cystatin C-based estimated glomerular filtration rate estimates of kidney func- tion in Black people with HIV on antiretroviral therapy. AIDS. 2023; 37(5):753-758. doi:10.1097/qad.0000000000003466 SUPPORTING INFORMATION Additional supporting information can be found online in the Support- ing Information section at the end of this article. How to cite this article: Mpofu R, Kawuma AN, Wasmann RE, et al. Determinants of early change in serum creatinine after initiation of dolutegravir-based antiretroviral therapy in South Africa. Br J Clin Pharmacol. 2024;90(5):1247‐1257. doi:10. 1111/bcp.16009 MPOFU ET AL. 1257 13652125, 2024, 5, D ow nloaded from https://bpspubs.onlinelibrary.w iley.com /doi/10.1111/bcp.16009 by U niversity O f W itw atersrand, W iley O nline L ibrary on [19/08/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense info:doi/10.1093/nar/gkac1010 info:doi/10.1002/cpt.2350 info:doi/10.1002/cpt.2350 https://www.nicd.ac.za/wp-content/uploads/2019/11/2019-ART-Clinical-Guidelines-25-Nov.pdf https://www.nicd.ac.za/wp-content/uploads/2019/11/2019-ART-Clinical-Guidelines-25-Nov.pdf info:doi/10.4102/sajhivmed.v21i1.1115 info:doi/10.4102/sajhivmed.v21i1.1115 info:doi/10.1093/ndt/gfw064 info:doi/10.1093/ndt/gfw064 info:doi/10.1186/cc1473 info:doi/10.1038/ng1847 http://www.posit.co/ info:doi/10.1016/s0140-6736(12)61853-4 info:doi/10.1016/s0140-6736(12)61853-4 info:doi/10.1016/S0140-6736(18)324620 info:doi/10.1097/qad.0b013e3283612419 info:doi/10.1097/qai.0000000000001186 info:doi/10.1093/ofid/ofz359.139 info:doi/10.1093/ofid/ofz359.139 info:doi/10.4102/sajhivmed.v19i1.817 info:doi/10.3851/IMP2770 info:doi/10.1007/s00467-012-2269-7 info:doi/10.1016/j.antiviral.2017.01.014 info:doi/10.1016/j.antiviral.2017.01.014 info:doi/10.1177/135965350701200704 info:doi/10.3390/nu11010090 info:doi/10.3390/nu11010090 info:doi/10.1093/jac/dky508 info:doi/10.1093/jac/dky508 info:doi/10.1146/annurev-pharmtox-011112-140317 info:doi/10.2165/00003088-197904030-00003 info:doi/10.2165/00003088-197904030-00003 info:doi/10.1007/s00424-007-0308-1 info:doi/10.1086/533468 info:doi/10.1128/aac.00292-13 info:doi/10.1128/aac.00292-13 info:doi/10.1089/aid.2017.0074 info:doi/10.1093/jac/dky112 info:doi/10.1097/qad.0000000000003466 info:doi/10.1111/bcp.16009 info:doi/10.1111/bcp.16009 Determinants of early change in serum creatinine after initiation of dolutegravir-based antiretroviral therapy in South Africa 1 INTRODUCTION What is already known about this subject What this study adds 2 METHODS 2.1 Study population 2.2 Pharmacokinetic sampling 2.3 Pharmacokinetic analysis and modelling 2.4 Genotyping and quality control 2.5 Statistical and genetic association analyses 3 RESULTS 3.1 Analysis of clinical variables 3.2 Pharmacokinetic analyses 3.3 Genetic analysis 4 DISCUSSION AUTHOR CONTRIBUTIONS ACKNOWLEDGEMENTS CONFLICT OF INTEREST STATEMENT DATA AVAILABILITY STATEMENT REFERENCES