HIV type 1 drug resistance monitoring in a HIV-1 endemic settings of Kisii, Kenya

doi:10.21203/rs.3.rs-3244038/v1

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HIV type 1 drug resistance monitoring in a HIV-1 endemic settings of Kisii, Kenya

https://doi.org/10.21203/rs.3.rs-3244038/v1

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Background:

Following the improved access to combined antiretroviral therapy (cART) in poor resource limited countries, emergence of HIV drug resistance has been observed and hence limiting the benefit of effective treatment. This study assessed the prevalence and patterns of acquired HIV drug resistance among patient on first-line antiretroviral drugs after twelve months of follow up in Kisii Teaching and referral clinic, Kisii County, Kenya

Methodology:

A longitudinal study with two time CD4 and viral load counts were conducted in a period of 12 months to determine treatment failure and drug resistance during the period between 2018 and 2019. Adults receiving combined first-line antiretroviral treatment at Kisii, Kenya recruited. A Structured questionnaire was administered and demographic data collected. HIV-1 pol genotyping for drug resistance were performed using in-house PCR protocol.

Results:

A total of 75 patients were recruited with a mean age of 36.9 years during the period between 2018 and 2019. Among these patients taking first-line drug, drug-associated mutations for NRTIs occurred in 21 (28%) patients and NNRTIs in 25 (33.3%) patients (33.3%).. Among them, nine (9) patient’s harboured viral strains having both major NNRI and NNRTI drug resistance mutations with four experiencing virological failure. The most frequent major NNRTIs mutation was the TAMs K219Q (n = 13) mutation. The TUM mutans T215K (n = 5), K70R (n = 3), and D67N (n = 1) were also found. The K65R NAMs was also found in patients (n = 2). The T215K (n = 5), K70R (n = 3), and D67N (n = 1) were among the additional TAMs found. The K65R NAMs was also found in patients (n = 2). The most frequent major NNRTI mutation detected was K103N (n = 9), followed by Y181F (n = 6), G190V (n = 5), and n = 2 for each of L100P, K101E, V108A, and Y188H. Also found were other relative non-polymorphic accessory mutations (n = 2) A98G,

Conclusions:

The study's findings demonstrated that the studied population had a low level of acquired HIV treatment resistance. HIV drug resistance would be easily managed if UNAIDS' 95%-95%-95% HIV prevention policy were perfectly implemented.

Antiretroviral drug resistance

resource-limited settings

second-line therapy

With an ambition to end HIV-1 epidemic by 2030, Joint United Nations Programme in the year 2020 adopted fast track strategy, diagnose and treat all and 95% 95% 95% targets approach (1, 2, 3). This approach could maximize the long term effectiveness of first line antiretroviral drugs if we could prevent HIV infection and continue to monitor HIV drug resistance. As result, this could minimize transmission HIV drug resistant strains, optimize patient’s outcome while maintaining the availability of ART drugs programs for these patients (1). However, failure to scale up this strategy, the AIDS epidemic is bound to be faced with poor treatment response, continued need for treatment resulting consequently increasing the future cost of patient management (2). Despite the observed success in implementing this strategy with an effective treatment, leading to reduction of new HIV-1 cases,, some individuals still develop HIV drug resistant strains either due to poor drug adherence, suboptimal treatments, individual pharmacogenomics or drug absorptions challenges (6). Due to occurrence this acquired drugs resistance; it would result into inadequate viral suppression and ongoing transmission within populations (5).

Since 2014, HIV infected patient could be initiated on treatment regardless of their CD4 count, viral load or disease AIDS staging (NASCOP). Before the current treatment guidelines were revised, the first-line drugs were two Nucleoside Reverse Transcriptase Inhibitors (NRTIs), (3TC (/FTC) + AZT/TDF) plus one Non-Nucleoside Reverse Transcriptase Inhibitor, (NNRTI), (EFV/NVP) (7) while protease inhibitors (PIs) reserved for second line (3). To address the challenge of treatment failure, WHO recommended the use of integrase strand transfer inhibitors (INSTIs), Dolutegravir (DTG), as a potent (9) and hence preferred based on its effectiveness though in combination with other drugs (1). Since 2019, the current ART treatment is lamivudine (3TC) + dolutegravir (DTG) + tenofovir disoproxil fumarate (TDF) + or TDF + 3TC + efavirenz (EFV) or abacavir (ABC) instead of TDF in case of renal failure. However, in case for patients who may not tolerate DTG are put on atazanavir/ritonavir (ATV/r) (5). In case of any treatment failure on lopinavir/ritonavir, zidovudine (AZT), nevirapine (NVP), and EFV the patient could be switched to DTG or ATV/r. On persistent virological failure, patients are switched to second line even though no drug resistance testing is not considered. These drugs are; AZT + 3TC + ATV/r, TDF + 3TC + ATV/r, or DTG (1). However, in the current guideline, drug resistance testing only considered when protease based first-line or second line drugs fails and hence switched to third line drugs as the last option (5).

In Kisii County by 2018, from current implementation of UNAIDS 95 95 95 strategy, the data has revealed that for those on HIV-1 treatment, those with total viral loads suppression is > 90%, viral load coverage (70%), drug stock out (0%), proportion of people receiving second line (> 5%), those exposed in children 89% and while those targeted and now retain on 12 months was > 85% (9). Despite this recorded national data towards improved HIV transmission prevention and improved patients response to treatment, the occurrence of acquired HIV drug resistance is invertible. HIV drug resistance could limit so far achieved benefits and treatment response. Even if testing of HIV-1 drug resistance could only be determined after the failure of PI-based drugs or second line regimen, if testing prior to treatment could be conducted as a personalized patient treatment monitoring could be used, administered an ineffective drugs or experience drug toxicities could be avoid. Following this limitations, the prevalence of ART drug resistance among drug experience patients remains elusive. Therefore, as part of the evaluating achievement of implemented ambitious 95 95 95 programs, we conducted a study with aim of determining the prevalence of acquired drug resistance among patients receiving treatment regardless of the status or levels of viremia among patients receiving antiretroviral treatment at Kisii Teaching and Referral hospital, Kisii after being on treatment for a period of 12months.

A longitudinal prospective cohort study among HIV-1 infected patients attending Kisii teaching and Referral Hospital (KTRH) HIV care clinics Recruited study patients were those that were newly diagnosed with HIV status, adults aged ≥18 years old and willing to participate in the study while on first –line antiretroviral treatment for a period of 12 months. A structured questionnaire was administered and demographic data on age, sex and marital status obtained prior to blood collection.

Ethical approval

The ethical approved was obtained from scientific ethical review committee of Kenyatta University. Written informed consent was obtained from all the study participants before executing this study

The CD4 T –lymphocyte count

The lymphocyte subsets were analysed using a FACSCalibur flow cytometer (Becton Dickinson Immunocytometry Systems, San Jose, California) with three monoclonal antibodies (BD Tritest CD4-FITC/CD8-PE/CD3-PerCP reagent) according to the manufacturer’s instructions (10) Immunological failure was defined as failure to achieve a CD4 gain of at least 50 cells at 6^th month post therapy or having an absolute CD4 count of less than 100 cells/mm³ after one year of therapy (10,11).

HIV-1 Viral Load determination

Viral loads were determined using an automated m2000 Abbott Real Time HIV-1 assay system following manufacturer’s instructions (Abbott Laboratories, Abbott Park, Illinois) with a lower limit of quantitation of 40 copies/ml of plasma. Virological failure was confirmed with those with RNA copies (above 1000 copies/ml) before confirming with HIV drug resistance testing (11). .

HIV drug resistance determination

Viral DNA was extracted from whole blood using QIAamp ® DSP Virus Spin Qiagen Kit (Qiagen Inc., Basel, Switzerland) protocol according to the manufacturer’s instructions. Partially HIV-1 pol gene was amplified in nested PCR using primers RT18 (5’-GGAAACCAAAAATGATAGGGGGAATTGGAGG-3’) and KS104 (5’-TGACTTGCCCAATTTAGTTTTCCCACTAA-3’) and KS101 (5’-GTAGGACCTACACCTGTTCAACATAATTGGAAG-3’) and KS102 (5’-CCCATCCAAAGAAATGGAGGAGGTTCTTTCTGATG-3’) in the second round. The amplification conditions were 1 cycle of 95°C for 10 min and 35 cycles of 95°C for 30 seconds, 55°C for 30 seconds, and 72°C for one minute, with a final extension of 72°C for 10 minutes (12-14). The amplified products were confirmed by visualization with ethidium bromide staining of the gel. Positive generated amplicons were directly sequenced using Big Dye technology on ABI 310 (Applied Biosystems, Foster City, CA) (13). Stanford HIV drug resistance database (version 8.8) was used for interpretation of genotypic drug resistance (13). Drug resistance was defined as any major mutations associated with NRTI or NNRTI drugs. The defined thymidine analogue mutations (TAMs) would include any classical mutations in either ; M41L, L210W and T215Y or D67N, K70R, T215F and K219EQ pathways and Nucleoside analogue mutations (NAMs) K65R mutations (14).

Patient’s characteristics

Of all 95 patients that were enrolled into the study, 8 were lost on follow up with others through due to loss of contacts, traced or missed clinics visits. However, 5 participants died with others being lost during follow ups. A total of 82 patients were enrolled into the study with only 75 successful monitored for a period of 12 months. Of the 75 patients included in this study, 46(61.3%) were female and 29 (38.7%) male aged between 18 and 68 years. Majority of the participants were married 36 (48%) with 2(2.7%) widower as the least. Most of the study participants had college levels of education with the least being those with informal education (Table 1).

CD4 and viral load counts

The participants had mean CD4 counts, 730.5 (SD-190.9) cells/mm³ with most of the participants 67 (89.3%) having their CD4 count above 301cells/mm³.

The estimation CD4 count in both 6^th and 12^th month intervals, the CD counts were 418.23 (SD=186.5) and 627.3 (SD=174.3) respectively with no immunological failure. In addition, only four (4) patients had a virological failure (>1000cps/ml). A comparison between gender and age in association with CD4 counts was performed. From the analysis, neither gender (p=0.576) nor the age (p=0.844) had any significant relationship with the levels of CD4 counts (Table 2).

Prevalence of HIV drug resistance

All the participants were on first-line ART. The drug combinations consisted of EFV/TDF/3TC 3 (4%), EFV/DDI/3TC 3 (4%), EFV/ABC/3TC 3 (4%), EFV/AZT/3TC 29(38.7%), for Efaverenz combinations while NVP/DDI/3TC 14 (18.7%) and NVP/AZT/3TC 16 (21.3%), NVP/ABC/3TC 7 (9.3%).

Of the 75 patients on first –line drugs, 21 (28%) had developed NRTIs drug associated resistance mutations. The K219Q (n=13) TAM mutation was the most common major NRTI mutation selected among those patients on AZT. Other TAMs; M184V (n=9), T215K (n=5) K70R (n=3) and D67N (n=1) mutations were also detected. Therefore, twelve (12) individuals had viral strains with either one or more TAMS mutations in addition to M184V mutations. There was no occurrence where 1st M41L, L210W, T215Y or 2nd D67N, K70R, T215F, K219Q pathways occurred in a patient simultaneously. The second pathway was the most common occurrence especially among patients who were on either AZT or DDI drug combinations.

However, one participant using AZT was infected with a strain with a single T215Y TAM mutation along with M184V and V75I mutations.

For NAMs, K65R mutation was detected in (n=2) patients. These mutations occurred among patients who were on AZT or DDI regimens. There is no patient who harbored viral strains with both NAMs and TAMs mutations. However, it is only one of these patients that had a M184V mutation due to 3TC drug combinations. Lastly, multi drug resistance mutations; (n=1) each for E44D, L74V, (n=5 ) Y115F and (n=2) V75M, (n=1) in T69N and 77L mutations that are not yet been full associated with drug resistance were also detected (Table 3).

Estimated (n=25) NNRTIs drug associated mutations were detected. The K103N (n=9 mutations was most common major NNRTI mutation. The other detected major mutations were Y181F (n=6). G190V (n=5), E138Q (n=3), (n=2) each for A98G,V, L100P, K101E.108A and Y188H mutations. However, other mutations; (n=43) P255H was most predominantly detected. This mutation occurred as expected among patients who were on either EFV or NVP and K103N combinations (Table 4). The other detected minor NNRTI mutations; M230L (n=36), L234I (n=33), V179I (n=32), F227L (n=18) and Q182Y (n=1) mutations.

In overall analysis of all the study participants, 9 patients had major drug resistance mutations indicative of treatment failure. Among them, four had confirmed virological failure. From the 12 months follow up four patients had virological failure. These patients were infected with viral strains harboring drug resistance mutations; TAMs and NAMs mutations in two patients (Table 5). According to implemented 95% 95% 95% HIV-1 treatment and prevention strategy, in this study had 86.3% (82/95) retention, 96% 71/75) viral suppression were detected among the recruited participants.

In this study, 21 participants had acquired drugs resistance mutations against both NNRTIs and NRTIs inhibitors. The patterns of detected mutations resembled those of HIV-1 subtype B. During the course of treatment, these drug resistance mutations had developed to diverse ART regimens (15). Based on its conferred major drug resistance to 9 (12%) of infected participants, it is an indicative of underlying treatment failure. In comparison to previous studies, these findings were fund to be low (16, 17). Despite the recorded drug resistance mutations, there was a high proportion of patients (66.7%) that had no mutations that are associated with drug resistance. These findings were higher than those previously reported in Kenya (45.5%–47.3%). Kenya (16, 17). These results point to increased treatment accessibility and drug adherence or occurrence of mutations off the target sites. It also demonstrates the results of a dedicated, successfully implemented 95% 95% 95 HIV prevention policy.

The K219Q was the most predominant mutation followed by K103N and M184V. Despite that all patients were on 3TC or majority of them on AZT or equal proportion on NVP/EFV regimens, low proportion of these patients failed due to K219Q, M184V and K103N mutations respectively. These mutations are known to reduce the efficacy of these drugs. These findings were similar those previous obtained in Kenya (16, 17). In this study, TAMs and NAMs drug resistance mutation were analysed with aim to predicting the possible switching to second line drugs. The K65R which is rare mutation associated with reduced efficacy in didanosine, abacavir, stavudine, tenofovir and rarely lamivudine in an exposed patient (18) was detected in two patients. These patients were on DDI/NVP and AZT/NVP regimens. In one patient, it occurred in combination with M184V thus reducing the efficacy of DDI and 3TC. In addition, the same patient also failed in NVP efficacy due to simultaneous occurrence of K101E, Y181C and G190A mutations. However K65R mutations occurred singly without Q151 in one patient who was on AZT treatment. This mutation probably increased the susceptibility of AZT (19), probably playing a role in the lack of detection of any other mutations.

In contrast to earlier studies (16) that found high rates of TAMs, this study found low rates of TAMs that also occurred singly, indicating better adherence and the tolerance of these medications. Despite the possibility that high rates could result from keeping patients on longer failed TAMs (20) in this study, good treatment adherence and monitoring were a factor in the rates that were found. Depending on NVP or EFV regimen, the occurrence of NNRTIs mutations were varied among participants. Despite the patient being on either NVP or EFV, they both selected, A98G, L100P, K101E, K103N, V106I, V108A, E138A, Y181C and G190I mutations in varied proportions (Table 4). These mutations are known to reduce susceptibility to NVP and EFV. These mutations have also been shown to increase rilpivirine, donavirine, etravirine resistance, drugs which could be utilized as second- or third-line drugs (21).In addition, other minor mutations could confer resistance in association with other to rilpivirine; V179L, Y188L, F227C and M230L were also detected. Occurrence of these mutations could be associated with exerted drug or immune pressures to the viruses. Nevertheless, the high NNRTIs associated mutations could also the nature of low genetic barrier in these drugs (22).

Despite the findings, the study had limitations. The crossectional approach and single sampling approach on genotyping drug resistance at 12 months period could not further confirm virological failure on those detected with, major drug resistances . Nevertheless, the rule out blips which could occur even during effective treatment could not be confirmed. The study findings could not be generalized to rest of the country or nation as an overall efficiency of national ART program. The genotypic analysis for drug resistance was based on HIV-pol gene, which does not present all drug targets.

The study findings showed that acquired HIV-1 drug resistance was low in the studied population. This suggests that with effective implementation of UNAIDS' 95%-95%-95% HIV prevention and treatment programs, the detected HIV-1 drug resistance mutations could be maintained low proportion and effective treatment.

Ethics approval and consent to participate

This study was ethically approved by Kenyatta University scientific ethical committee and consent sought from study participants before the start of this study.

Consent for publication

Not applicable

Availability of data and materials

The data and materials used in this study are available upon request

Competing interests

The authors declare that they have no competing interests.

Funding

We acknowledge JICA/PAUSTI and JKUAT that partially funded this study.

Author contributions

Conceived and designed the experiments: SNM, AKN, enrolled the patients: SNM, AKN performed the experiments: All authors managed data and analysis, prepared, read and approve the final manuscripts.

Acknowledgments

The authors are grateful to the study participants for their invaluable support by consenting to the use of their samples in the study. We also appreciate and thank Kisii Teaching Referral Hospital staff for support and allowing us to conduct this study.

SEQUENCE DATA

The HIV-pol RT sequences were deposited at the Genebank under the following accession numbers ON325699 - ON325742 & MK 458883 – MK 458933

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Table 1: Demographic characteristic of HIV infected patients

Patients’ Characteristics
Gender	Experienced n (%)75	p value
Male	29(38.7)
Female	46(61.3)
Marital Status
Single	27(36)
Married	36(48)
Divorced	3(4)
Separated	3(4)
Widow	4(5.3)
Widower	2(2.7)
Age (years)
Range	18-68
mean(±SD)	33.5 (SD: 13.04)
18-30	22 (29.2)
31-40	23 (30.1)
41-50	20 (26.5)
51-6 0	7 (9.7)
>60	3(4.0)
Education levels
Primary level	8 (10.6)
Secondary	25 (33.3)
Tertially/ college	30 (40)
Universities	11 (14.7)
	1(1.4)

Table 2 Immunological and virological characteristic of treated HIV infected patients

Drug experienced n=75				p-value
	ALL	F	M
Gender	n=75 (%)	n(46)	n(29)	0.576
Mean age (years)		30.5	40.2	0.576
CD4 Counts (Cells/mm3) Mean (SD)	730.5 (SD-190.9)
<200	3(4)	2	1	0.844
201-300	5(6.7)	3	2
301-400	18 (24)	7	4
401-500	23(30.7)	7	9
>500	26(34.6)	6	6
Baseline	418.23 (SD=186.5)
6^th month	616.2 (SD=230.9
12^th Month	627.3(SD 174.3)	634.6(SD 176.9)	622.1 (SD 175.7)
WHO staging
WHO stage 1	49	13	10
WHO stage 2	18	3	2
WHO stage 4	5	3	2
WHO stage 4	3	2	1
Mean Viral Load (cps/ml)
Baseline	406.5(SD=44.7)
6^th Month	526.8(SD=52.3)
12^th month	446.5 SD=56.6)
Virological failure (>1000cps/ml)	4	3	1

KEY: F: Female, M: Male

Table 3: Frequency of NRTIs drug resistance mutations among treated patients with duo nucleoside RT inhibitors plus NRTI first-line drugs

		n/75	NAMs		TAMs					MDR			OTHERS
NNRTI	NRTI		K65	M184	T215	K70	D67	T69	K219	Y115	L74	E44	77	V75
			R	V	K/S/T/Y	R	N	N/S/A/I/E	QE	F	V	D	L	M
			n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n (%)	n(%)	n (%)	n (%)
EFV combinations
	TDF/3TC	3		1(33.3)						1(33.3)			1(33.3)
	AZT/3TC	29		3(10.3)	2(6.9)				1(3.4)	1(3.4)
	DDI/3TC	3							3(100)
	ABC/3TC	3							3(100)
Sub total		38	0	4	2	0	0	0	7	2	0	0	1	0
NVP combinations
	TDF/3TC	0
	AZT/3TC	16	1(6.3)	3(18.6)	1(6.3)	1(6.3)		1(6.3)	1(6.3)	1(6.3)				1(6.3)
	DDI/3TC	14	1(7.1)	2(21.4)	2(21.4)	1(7.1)	1(7.1)		3(21.4)	2(14.3)	1(7.1)	1(7.1)	1(7.1)	1(7.1)
	ABC/3TC	7							2 (28.6)
Sub total		37	2	5	3	2	1	1	6	3	1	1	1	2
	Total	75	2	4	6	2	1	1	13	5	1	1	1	2

Table 4 Frequency of NNRTIs drug resistance mutations among treated patients with duo nucleoside RT inhibitors plus NRTI first-line drugs

ARV Regiments		n/75	NNRTIS											OTHERS
NNRTI	NRTI		L100	K103	V106	V108	V179	Y181	Y188	V190	F227	M230	A98	F116	V118I	E138	L234	236	P255
			P/Q/L	NS	A/M	I	I	C/F	H	I	L	L	G	Y	I	A	I	L	H
			n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)	n(%)
EFV combinations
	TDF/3TC	3		1(33.3)	1(33.3)	1(33.3)			1(33.3)					2 (66.7)	1(33.3)
	AZT/3TC	29		4(13.8)	1(13.8)	1(3.4)	12 41.4)			1(3.4)	6 (20.7)	19 (65.5)			5(17.2)	2(6.9)	14(48.3)		28(96.6)
	DDI/3TC	3					1(33.3)	2(66.6)		1(33.3)	2(66.&)						1(33.3)
	ABC/3TC	3		2 (66.7)			1(33.3)				1(33.3)						1(33.3)
Subtotal Total		38		7	2	2	14	1	1	1	9	19	0	2	6	2	16	0	28
NVP combinations
	TDF/3TC	0
	AZT/3TC	16		2(12.5)	2(12.5)	2(12.5)	12(75)	1 (6.3)	2 (12.5)	2 (12.5	6(37.5)	12(75)	1 (6.3)	1 (6.3)	1 (6.3)		12(75)	1 (6.3)	11(68.8)
	DDI/3TC	14	2(14.3)		2(14.3)	2(14.3)	4(28.6)	1(7.1)	1(7.1)	1(7.1)	1(7.1)	3(21.4)	1 (7.1)			1(7.1)	4(28.6		3(21.4)
	ABC/3TC	7					2(28.6)	2(28.6)			2(28.6)	2(28.6)					1(14.3)		1(14.3)
	Sub total	37	2	2	4		18	3	2	2	9	17	2	1	1	1	17	1	15
	Totals	75	2	9	6	6	32	4	3	3	18	36	2	3	7	3	33	1	43

Table 5: Drug resistance profiles among virological failure patients after 12 months follow ups

Sequence Header	Viral Load cps/ml	NRTI mutations (TAMs/NAMs)	NNRTI mutations	Others mutations
MK458902	1100	M184L, T215S,K219N	Y188S,G190V, V106W, V108L	P255H,L234L
MK458890.	1200	T215K, K70R, D67I, K219N	L100Q, V179L,Y181H,Y188N,	P255H, M230L, F227L,L234I,P236L
MK458923	1130	K65R, Y115F, M184V, F77L	106A, F227L, V108I, V75I, V179I	M230L,L234I

No competing interests reported.

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HIV type 1 drug resistance monitoring in a HIV-1 endemic settings of Kisii, Kenya

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Abstract

Background:

Methodology:

Results:

Conclusions:

Introduction

Laboratory Methods

The CD4 T –lymphocyte count

Results

CD4 and viral load counts

Prevalence of HIV drug resistance

Discussion

Conclusions

Declarations

References

Tables

Additional Declarations

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