IFNL4 genotype influences the rate of HIV-1 seroconversion in men who have sex with men

Figures & data

Table 1. Parameters associated with HIV infection during the follow-up

Variables	HIV-non-infected (n=362)	HIV-infected (n=257)	Univariate p	Multivariate p, AOR (95%CI)
Risk score>2, n (%)	161 (44,5)	166 (64,6)	<0.001	<0.001, 2.42 (1.72–3.39)
Age, years*	36 (31–44)	35 (29–41)	0.004	<0.001, .97‡ (0.95–0.98)
INFL4 GG/GT/TT, n (%)	30/144/188 (8.3/39.8/51.9)	39/89/129 (15.2/34.6/50.2)	0.007†	0.007†, .49 (0.28–0.82)

OR, Odds ratio; CI, Confidence interval.

*Median (quartile 1- quartile 3).

‡For one unit increase.

†TT/TT+TT+GT vs. GG.

Table 2. Genotypic distribution of INFL4 genotypes in all the cohort, vaccinees and placebo-treated subjects of the Vax004 clinical trial

Treatment	HIV seroconversion	Genotypesa
		G/G	G/TT	TT/TT
All	HIV-positive, n (%) P ^H-^W = 0.0007	39 (15.2)	89 (34.6)	129 (50.1)
	HIV-negative, n (%)* P ^H-^W = 0.4	30 (8.2)	144 (39.7)	188 (51.9)
	OR (95% CI), P-value ^b	0.52 (0.3–0.8), 0.007
	Adjusted OR (95% CI) and P-value^c	0.48 (0.2–0.8), P= 0.008
Vaccinees		Genotypesa
		G/G	G/TT	TT/TT
	HIV-positive, n (%) P ^H-^W = p=0.01	28 (15.2)	67 (36.4)	89 (48.3)
	HIV-negative, n (%) P ^H-^W = 0.39	16 (8.2)	88 (45.3)	90 (46.3)
	OR (95% CI), P-value ^b	0.52 (0.2–0.9), 0.03
	Adjusted OR (95% CI) and P-value^c	.49 (0.2–0.9), P= 0.043
Placebo		Genotypesa
		G/G	G/TT	TT/TT
	HIV-positive, n (%) P ^H-^W = 0.01	11 (15.1)	22 (30.0)	40 (54.0)
	HIV-negative, n (%) P ^H-^W = 0.14	14 (8.3)	56 (33.3)	98 (58.3)
	OR (95% CI), P-value ^b	0.5 (0.2–1.2), 0.1
	Adjusted OR (95% CI), and P-value^c	0.45 (0.18–1.07), P= 0.07

OR: Odds Ratio. CI: Confidence interval. ^H-W Test for deviation from Hardy-Weinberg equilibrium.

Data are genotype counts (%).

Univariate logistic regression.

Adjusted OR and adjusted P values were calculated using a multivariable logistic regression model including IFNL4 genotype, age, risk of HIV-1 infection according to baseline sexual behavior and vaccination status.

Figure 1. Kaplan-Meier plot of rate of HIV-1 seroconversion according to IFNL4 genotypes. Survival curves were compared under a dominant model for rs368234815 polymorphism (TT+GT vs. GG) by the log-rank test (P=0.01). G is the functional IFNL4 allele.

Table 3. Predictors of the HIV-1 seroconversion

Variables	Events, n (%)	Univariate p; HOR (95%CI)	Multivariate p; HOR (95%CI)
Baseline sexual risk behaviour score≥2 score<2	166 (50,8) 91 (31.2)	<0.001; 1.86 (1.44–2.41)	<0.001; 1,93 (0.1.50–2.50)
Age, years	-	0.002; 0.098‡ (0.97–0.99)	<0.001; 0.97‡ (0.96–0.99)
INFL4 TT/TT+TT+GT carriers GG cariers	218 (39.6) 39 (69.0)	0.019; 0.67 (0.47–0.94)	0.028; .68 (0.48–0.96)

HOR, Hazard odds ratio; CI, Confidence interval.

‡For one unit increase.

Figure 2. Forest plot of meta-analysis of the men who have sex with men (MSM-USA-Vax004 trial), serodiscordant couples (Sex Italy and Spain), and intravenous drug users (IDU) populations from Spain and Estonia (https://metagenyo.genyo.es/) [19]. Odds ratio (OR) and 95% confidence interval (95%-CI) and fixed-effect meta-analysis. P=1.3 x 10-5 for a dominant model of the protective allele (G/G vs.TT/TT+TT/G).

Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available. The data generated during the current study are available from the corresponding author on reasonable request.