Genetic Associations with Weight Gain among South Africans who Initiated Dolutegravir-Containing and Tenofovir-Containing Regimens : JAIDS Journal of Acquired Immune Deficiency Syndromes

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Genetic Associations with Weight Gain among South Africans who Initiated Dolutegravir-Containing and Tenofovir-Containing Regimens

Cindi, Zinhle MSca; Maartens, Gary MBChB, FCP, MMeda,b; Bradford, Yuki MSc; Venter, Willem D.F. MBBCh, FCP, PhDd; Sokhela, Simiso MBChBd; Chandiwana, Nomathemba C. MBBCh, MPHd; Haas, David W. MDe,f; Sinxadi, Phumla MBChB, MMed, PhDa

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes 87(3):p 1002-1009, July 1, 2021. | DOI: 10.1097/QAI.0000000000002661

Abstract

INTRODUCTION

The HIV-1 integrase strand transfer inhibitor (INSTI) dolutegravir effectively controls viral replication, is generally well tolerated, and has out-performed several other drugs.1–6 Dolutegravir and other INSTIs are preferred components of first-line antiretroviral therapy (ART) in the United States, Europe, by WHO, and increasingly worldwide.7,8 In Africa, dolutegravir is replacing non-nucleoside reverse transcriptase inhibitors (NNRTIs) such as efavirenz in first-line ART and HIV-1 protease inhibitors in second-line ART regimens.9,10 However, recent reports have associated INSTIs, especially the second generation INSTIs dolutegravir and bictegravir, with greater weight gain than other agents either after ART initiation or switch to INSTI-containing ART.11–17 An early report was an observational cohort study of 495 patients with sustained virologic suppression, 136 of whom switched from efavirenz-containing regimens to INSTI-containing regimens. At 18 months, patients who switched to INSTI-containing regimens gained significantly more weight, especially those who switched to dolutegravir, than those who remained on efavirenz.11 Similar findings of greater weight gain with INSTI-containing regimens as compared with NNRTI or protease inhibitor–containing regimens were reported in a pooled analysis of 8 randomized controlled trials among treatment-naïve individuals initiating ART,16 and in cohort studies of patients with viral suppression on protease inhibitor–containing or NNRTI-containing ART who then switched to INSTIs.18,19

Specific concomitant nucleos(t)ide reverse transcriptase inhibitors (NRTIs) have also been associated with magnitude of weight gain. In randomized controlled trials among HIV-positive patients, the tenofovir prodrug, tenofovir alafenamide (TAF), has been associated with greater weight gain than tenofovir disoproxil fumarate (TDF),16 and in a study of pre-exposure prophylaxis in HIV-negative individuals.20 TAF has become the most widely prescribed NRTI in high-income countries because it causes less kidney and bone toxicity than TDF. There is considerable interest in using TAF rather than TDF in low-income and middle-income countries based on its more favorable safety profile, and likely lower cost for generic manufacture given its much lower dose.10

Additional factors that have been associated with greater weight gain in individuals who initiate ART, and in people with viral suppression on ART who switch to INSTIs, have included Black race and female sex.16,18 Two randomized controlled trials of dolutegravir in Africa have reported 48-week findings including changes in weight. In the NAMSAL study, which randomized ART-naïve participants in Cameroon to dolutegravir or efavirenz, both with TDF and lamivudine, there was greater median weight gain and more treatment-emergent obesity at 48 weeks in the dolutegravir arm.15 In the ADVANCE study, a 3-arm (1) dolutegravir, TAF, and emtricitabine; 2) dolutegravir, TDF, and emtricitabine; or 3) efavirenz, TDF, and emtricitabine randomized controlled trial of ART-naïve participants in South Africa; there was greater mean weight gain and treatment-emergent obesity at 48 weeks in the dolutegravir arms, with the greatest weight increases in the dolutegravir and TAF arm.17 This may be explained, in part, by lesser weight gain among participants receiving efavirenz with TDF, particularly with CYP2B6 slow metabolizer genotypes.21,22

Genomic studies could help elucidate mechanisms underlying greater weight gain with dolutegravir and TAF, which are currently unknown. We conducted analyses to characterize associations between human genetic polymorphisms and magnitude of weight gain among ART-naïve individuals who were randomized to initiate dolutegravir-containing regimens in the ADVANCE study.

METHODS

Study Population

The ADVANCE study in South Africa is a phase 3 noninferiority clinical trial in which 1053 HIV-positive, ART-naïve participants were randomly assigned to 1 of 3 treatment arms 17: (1) dolutegravir, TAF, and emtricitabine; (2) dolutegravir, TDF, and emtricitabine; or (3) efavirenz, TDF, and emtricitabine. DNA samples were collected from 340 (48%) of 702 treatment arm 1 and 2 participants who consented to genetic testing. Although some individuals opted to not participate in the genetic study, many individuals were not offered the opportunity to participate. Ethics approval was granted by the University of Cape Town and Wits University Human Research Ethics Committees.

Genetic Polymorphisms

Whole blood was collected from consenting participants, and DNA extracted using the salting out method as described elsewhere.23 Samples were labeled with coded identifiers. Stored DNA was genotyped using the Illumina Infinium Multi-Ethnic Global BeadChip (MEGAEX) at Vanderbilt Technologies for Advanced Genomics (VANTAGE). Postgenotype quality control was performed by Vanderbilt Technologies for Advanced Genomics Analysis and Research Design (VANGARD). All quality control steps were performed using PLINK version 1.9.24 Genotyping efficiency per participant was >95% for all samples. Markers with genotyping efficiency <95% were censored, as were those with minor allele frequency (MAF) <5%. We excluded 21 samples with overall genotyping call rates <95%. After quality control, data were imputed to 1000 genomes after transforming to genome build 37 using liftOver and stratification by chromosome to parallelize the imputation process.25,26 For each chromosome in each phase, 100% concordance with genotyped data was assessed. Imputed polymorphisms with imputation scores less <0.7, genotyping call rates <95%, or MAF <0.05 were excluded. To address population stratification, we performed data reduction using multidimensional scaling (MDS) implemented in PLINK, which produces a k-dimensional representation of structure. Associations between percentage weight gain from baseline to week 48 and genes relevant to dolutegravir, TAF, and/or TDF metabolism were characterized.

We focused on genes that encode proteins relevant to dolutegravir and tenofovir disposition. Dolutegravir is primarily metabolized by uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) and less so by cytochrome P450 (CYP) 3A4.27 Dolutegravir is also a substrate for ATP-binding cassette transporters B1 (encoded by ABCB1) and G2 (encoded by ABCG2).28 In some studies, polymorphisms in SCL22A6, ABCC2, and ABCC4 were associated with higher tenofovir concentrations29–32 although a subsequent study did not replicate associations between tenofovir concentrations and ABCC family polymorphisms.33 Both TAF and TDF are substrates of P-glycoprotein and human breast cancer resistance protein.34 TDF is a substrate of the OAT1 and OAT3 organic anion transporters35 and is minimally metabolized by CYP3A4.36 We also considered genome-wide associations.

Association Analyses

Multivariable linear regression models were used to characterize associations between polymorphisms relevant to dolutegravir, TAF, and TDF with percentage weight gain from study baseline to week 48. Covariates included baseline age, self-reported sex, and concomitant NRTI, as well as the first 3 MDS coordinates to adjust for population stratification.24 We report the regression coefficient (β) for additive associations with polymorphisms, where positive β values indicate an association with greater weight gain. From the NHGRI-EBI GWAS Catalog (accessed 26 November 2020),37 we identified 86 polymorphisms previously associated with obesity trait in the general population at P < 5.0 × 10−8 in at least 1 published study. Of these, 77 polymorphisms were represented in our genotype data. The Bonferroni method was used to determine significance threshold, with P = 5.0 × 10−8 for genome-wide analyses, and 0.05 divided by the number of polymorphisms tested in targeted polymorphism and gene analyses.

RESULTS

Characteristics of Participants

Among the 340 (92%) participants who consented for genetic analyses, 314 were successfully genotyped and had genome-wide genotype data. Participant disposition is presented in Figure 1. Baseline characteristics of study participants are shown in Table 1. All participants were Black South Africans, and most were women. Baseline characteristics were similar between those who consented and those who did not consent for genotyping (Table 1).

F1
FIGURE 1.:
Disposition of study participants. Of 1053 participants enrolled in the ADVANCE study, 314 who had been randomized to dolutegravir-containing regimens were evaluable for genetic associations.
TABLE 1. - Baseline Characteristics in all Dolutegravir Recipients
Participants With Genetic Consent Participants Without Genetic Consent
DTG, TAF, and FTC DTG, TDF, and FTC DTG, TAF or TDF, and FTC
n = 154 n = 166 n = 362
Age in years, (IQR) 32 (27, 38) 32 (27, 37) 32 (26, 37)
Sex
 Male, n (%) 65 (37.4%) 61 (36.8%) 154 (42.5%)
 Female, n (%) 109 (62.6%) 105 (63.3%) 208 (57.5%)
Baseline BMI, kg/m2(IQR) 23.6 (20.6–26.5) 23.0 (20.0–27.1) 23.1 (20.1–27.0)
Weight gain at week 48, kg (IQR) +5.8 (+2.4–+9.4) +2.5 (0.0–+5.6) +2.9 (+0.2–+7.6)
Baseline CD4 count (IQR) 326 (170–502) 272 (159–424) 295 (173–451)
Baseline viral load (IQR) 28,968 (6 180–75,314) 25,703 (6 408–75,619) 22,064 (5 973–73,796)
Viral load suppression (<50 c/µL) at week 48, n (%) 164 (95.9%) 157 (96.3%) 262 (92.6%)
DTG, dolutegravir; FTC, emtricitabine; IQR, interquartile range.

Associations With Dolutegravir-Relevant Polymorphisms and Genes

We first focused on dolutegravir, characterizing associations in polymorphisms that have previously been associated with dolutegravir metabolism or transport (selected a priori for this analysis) and percentage weight gain from baseline to week 48 among all dolutegravir recipients, by multivariable linear regression analysis. Results for all 314 dolutegravir recipients are presented in Table 2. The lowest P-value for association was ABCG2 rs13137622 (β = −1.24, P = 0.03), which was not significant after correcting for multiple testing (cut-off P < 1.0 × 10−3). We next assessed 1729 polymorphisms in ABCB1, ABCG2, CYP3A4, and UGT1A1(±50 kB for each gene) for association with percentage weight gain among all dolutegravir recipients, by multivariable linear regression analysis. The 2 lowest P-values in each gene are presented in Table 1, Supplemental Digital Content, https://links.lww.com/QAI/B623. The lowest P-value overall was ABCG2 rs4148149 (β = −1.96, P = 7.0 × 10−4), which did not achieve the Bonferroni cut-off of P < 2.9 × 10−5.

TABLE 2. - Association Among 314 Dolutegravir Recipients Between Percentage Weight Gain at Week 48 and Selected Polymorphisms Relevant to Dolutegravir
SNP* Gene MAF Beta P
rs13137622 ABCG2 0.46 −1.24 0.03
rs2725252 ABCG2 0.19 −1.29 0.06
rs1042640 UGT1A1 0.18 1.34 0.07
rs10929302 UGT1A1 0.29 1.01 0.09
rs28401781 ABCB1 0.25 −1.12 0.09
rs2246709 CYP3A4 0.31 −0.94 0.12
rs1976391 UGT1A1 0.41 0.84 0.13
rs887829 UGT1A1 0.41 0.81 0.15
rs2231137 ABCG2 0.06 1.73 0.16
rs10011796 ABCG2 0.25 −0.92 0.16
rs12505410 ABCG2 0.1 −1.1 0.24
rs4148738 ABCB1 0.14 −0.89 0.25
rs4124874 UGT1A1 0.37 0.92 0.26
rs3789243 ABCB1 0.38 0.66 0.27
rs1922242 ABCB1 0.45 0.59 0.28
rs10276036 ABCB1 0.15 −0.81 0.28
rs1045642 ABCB1 0.89 0.93 0.35
rs3842 ABCB1 0.28 0.55 0.36
rs2235015 ABCB1 0.36 0.47 0.41
rs3213619 ABCB1 0.17 0.55 0.47
rs10248420 ABCB1 0.35 0.4 0.5
rs2235067 ABCB1 0.15 −0.42 0.6
rs10267099 ABCB1 0.1 0.49 0.6
rs1128503 ABCB1 0.06 0.59 0.61
rs2740574 CYP3A4 0.25 −0.3 0.62
rs11983225 ABCB1 0.21 −0.26 0.72
rs3735451 CYP3A4 0.17 0.24 0.76
rs4646440 CYP3A4 0.08 −0.28 0.78
rs4728709 ABCB1 0.39 0.15 0.79
rs4148740 ABCB1 0.19 −0.17 0.81
rs2242480 CYP3A4 0.14 0.19 0.82
rs7699188 ABCG2 0.44 −0.12 0.83
rs3114020 ABCG2 0.15 −0.17 0.83
rs8330 UGT1A1 0.4 0.12 0.84
rs10280101 ABCB1 0.2 −0.11 0.88
rs4646437 CYP3A4 0.13 0.09 0.92
rs2235047 ABCB1 0.23 −0.05 0.94
rs10929303 UGT1A1 0.37 −0.03 0.95
rs7787082 ABCB1 0.27 −0.02 0.97
rs2235040 ABCB1 0.17 −0.02 0.98
*SNP, single nucleotide polymorphism.
UGT1A1 rs887829 T allele is known to be in strong linkage disequilibrium (LD) with the Gilbert trait decrease expression allele, UGT1A1*28.
Significance threshold was 1.0 × 10−3 for the subset of 40 polymorphisms.

Associations With Tenofovir-Relevant Polymorphisms and Genes

We next focused on tenofovir, characterizing associations in polymorphisms that have previously been associated with tenofovir disposition (selected a priori for this analysis) and percentage weight gain from baseline to week 48 among all tenofovir recipients (ie, TDF and TAF), by multivariable linear regression analysis. Results for all 314 tenofovir recipients are presented in Table 2, Supplemental Digital Content, https://links.lww.com/QAI/B623. The lowest P-value for association was ABCC4 rs3742106 (β = 1.59, P = 0.04), which did not achieve the Bonferroni cut-off of P < 3.0 × 10−3. We next assessed all 3945 polymorphisms in ABCC2, ABCC4, ABCC10, SLC22A2, SLC22A6, and SLC22A11 (±50 kB for each gene) for association with percentage weight gain among all tenofovir recipients, by multivariable linear regression analysis. The 2 lowest P-values in each gene are presented in Table 3, Supplemental Digital Content, https://links.lww.com/QAI/B623. The lowest P-value for association overall was ABCC10 rs67861980 (β = 1.82, P = 1.0 × 10−2), which did not achieve the Bonferroni cut-off of P < 1.3 × 10−5.

Genome-Wide Associations With Percent Weight Gain at 48 Weeks

Associations between genetic polymorphisms and percentage weight gain from baseline to week 48 were explored by multivariable linear regression analysis in all participants, followed by separate regression models for those randomized to TDF and TAF. Among all 314 dolutegravir recipients, the lowest P-value for association was TMEM163 rs7590091 (P = 3.7 × 10−8), presented in Figure 2A. In analyses limited to the 160 TAF recipients, the 2 lowest P-values for association were LOC105379130 rs17137701 (P = 6.4 × 10−8) and rs76794506 in an intergenic region on chromosome 10 (P = 8.8 × 10−8), presented in Figure 2B. In analyses limited to the 154 TDF recipients, the lowest P-values for association were LOC105371716 rs76771105 (P = 9.7 × 10−8), presented in Figure 2C. Only TMEM163 rs7590091 was genome-wide significant after correcting for multiple testing. There was no evidence of genomic inflation of each analysis, based on QQ plots.

F2
FIGURE 2.:
Genome-wide associations with weight gain from baseline to week 48 in ADVANCE study participants. Manhattan plots and QQ-plot for genome-wide associations with percentage weight gain from baseline to week 48. Analyses controlled for age, sex, first 3 MDS coordinates, and, in the dolutegravir analysis, concomitant NRTI. Horizontal red lines indicate a genome-wide significance threshold of P < 5.0 × 10−8. A, Associations among 314 participants in the dolutegravir arm. A polymorphism in TMEM163 (rs7590091) achieved genome-wide significance (P = 3.7 × 10−8). B, Associations among 160 participants in the TAF arm. Two polymorphisms, LOC105379130 rs17137701 and rs76794506 in an intergenic region on chromosome 10, had P-values approaching statistical significance (P = 6.4 × 10−8 and P = 8.8 × 10−8, respectively). C, Associations among 154 participants in the TDF arm. The polymorphism LOC105371716 rs76771105 had the lowest P-value (P = 9.7 × 10−8).

Of the 86 polymorphisms identified in the GWAS Catalog, 77 were represented in our genotype data. These are presented in Table 4, Supplemental Digital Content, https://links.lww.com/QAI/B623. The lowest P-value in our analysis was for ETV5 rs1516725 (β = −1.58, P = 0.01). None of the 77 polymorphisms were significant after correcting for multiple testing.

DISCUSSION

In our analysis for association with percentage weight gain, and 59 selected polymorphisms relevant to dolutegravir and tenofovir disposition, ABCG2 rs13137622 and ABCC4 rs3742106 had the lowest P-values, respectively, but were not significant after Bonferroni correction. In targeted analysis involving 1729 polymorphisms in genes suggested to affect dolutegravir disposition, ABCG2 rs4148149 had the lowest P-value, whereas in analysis of 3945 polymorphisms in genes suggested to affect tenofovir disposition, ABCC10 rs67861980 had the lowest P-value. In genome-wide association analysis for each study drug (dolutegravir, TAF, and TDF), we found no associations between polymorphisms relevant to dolutegravir and tenofovir disposition and weight gain. For dolutegravir, only TMEM163 rs7590091 achieved genome-wide significance (β = 3.3, P = 3.7 × 10−8). For TAF and TDF, no polymorphism achieved genome-wide significance.

This is the first study to explore associations between dolutegravir or tenofovir-associated weight gain and polymorphisms in genes relevant to their disposition, including ABCG2 and ABCC4. In studies of ABCG2-null mice, ABCG2 deficiency did not affect dolutegravir metabolism or excretion.38 In addition, polymorphisms in the ABCC family have previously been associated with proximal kidney tubule cell dysfunction, including ABCC2 rs717620, ABCC4 rs3742106, ABCC10 rs2125739, and ABCC10 rs9349256,39–41 with possibly greater risk of renal dysfunction among HIV- positive patients of African descent than of European descent.42 In our study, ABCC4 rs3742106 (P = 0.05) and ABCC10 rs2125739 (P = 0.77) were not significantly associated with weight gain. The lack of association between ABCG2 or ABCC family polymorphisms and weight gain suggests a relationship that may not be driven by plasma drug concentrations.

In genome-wide analyses, TMEM163 rs7590091 was significantly associated with weight gain. TMEM163 encodes transmembrane protein 163,43 a zinc-binding protein that has been reported to interact with the ion channel transient receptor potential mucolipin-1 (TRPML1), which may help maintain zinc homeostasis in a cell-type specific manner.44 A previous study observed a reduction in TMEM163 mRNA and protein expression levels in mucolipidosis type IV (MLIV) fibroblast cells which correlated with increased lysosomal zinc levels.44 It has been reported that variants of zinc transported proteins on pancreatic β-cells are associated with type 2 diabetes mellitus.45,46 Two other TMEM163 polymorphisms, rs6723108 and rs998451, have been associated with reduced fasting plasma insulin levels and homeostasis model assessment of insulin resistance (HOMA-IR), suggesting that TMEM163 might modulate susceptibility to type 2 diabetes mellitus by affecting insulin secretion.47 The TMEM163 rs6723108 polymorphism has also been associated with waist circumference.47 However, a relationship between TMEM163 and dolutegravir has not been previously reported. This possible association warrants replication. In analyses focused on polymorphisms previously associated with obesity trait in the general population, the lowest P-value was with ETV5 rs1516725 (β = −1.58, P = 0.01). The gene ETV5 encodes a transcription factor. Polymorphisms in ETV5 have been associated with body mass index and bipolar disorder,48 and inhibition of ETV5 homolog in Drosophila melanogaster induced bipolar disorder and obesity-related phenotypes.49

Mechanisms underlying greater weight gain with dolutegravir and with TAF are unknown. One hypothesis for the greater weight gain observed with TAF compared with TDF is that this reflects TDF-induced depletion of mitochondrial DNA in adipocytes, or some other off-target metabolic effect. In addition, TDF may cause loss of appetite. In a clinical trial of patients in the United States randomized to initiate efavirenz-containing ART, lesser weight gain occurred among CYP2B6 slow metabolizers who were also randomized to receive concomitant TDF, but not those randomized to receive concomitant abacavir.21

Our study had limitations. We only considered individual polymorphisms. It is possible that other approaches, such as the polygenetic risk score, may identify associations not apparent in our analyses. We did not consider mitochondrial genetics or epigenetics. Although associations with pharmacogenetic variants can often be identified with small sample sizes, because of large effect sizes, a larger study would have greater power to detect associations, especially in the TDF and TAF subgroup analyses. Fifty two percent of participants from the main ADVANCE study did not consent to genotyping, resulting in a smaller sample size and reduced power to detect associations. We are encouraged that baseline characteristics were similar between the 2 groups, suggesting that our results are likely generalizable to the larger ADVANCE study population.

In summary, we identified potential associations between human genetic polymorphisms and percentage weight gain during the first 48 weeks of ART initiation with dolutegravir plus emtricitabine and either TAF or TDF. No polymorphisms in genes relevant to dolutegravir, TAF, or TDF were significantly associated with weight gain after correcting for multiple testing. In a genome-wide association analysis among dolutegravir recipients, a polymorphism in TMEM163 achieved genome-wide significance. This association needs to be replicated in other cohorts before a causal link can be made with weight gain.

ACKNOWLEDGMENTS

The authors thank the Fogarty International Center of the National Institutes of Health for the support. In addition, the authors are grateful to the study participants.

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Keywords:

weight gain; dolutegravir; tenofovir; pharmacogenetics

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