Abstract
Serum 25-hydroxyvitamin D [25(OH)D] is often deficient (<12 ng/ml) or insufficient (<20 ng/ml) in youth living with human immunodeficiency virus type 1 infection (YLH). Based on evidence from multiple genome-wide association studies, we hypothesized that genetic factors associated with 25(OH)D deficiency should be readily detectable in YLH even when controlling for other known factors, including use of the antiretroviral drug efavirenz (EFV). Genotyping by bi-directional sequencing targeted 15 single nucleotide polymorphisms (SNPs) at the GC/DBP locus, with a focus on coding and regulatory variants, as well as those repeatedly reported in the literature. Three intronic SNPs (rs222016, rs222020, and rs222029) in a conserved haplotype block had unequivocal association signals (false discovery rate ≤ 0.006). In particular, the minor allele G for rs222020 was highly unfavorable among 192 YLH (99 African–Americans and 93 others), as gauged by relatively low likelihood for 25(OH)D sufficiency at enrollment (odds ratio = 0.31, p = 9.0 × 10-4). In a reduced multivariable model, race, season, latitude, body mass index, exposure to EFV, and rs222020-G were independent factors that collectively accounted for 38% of variance in the log10-transformed 25(OH)D concentration (p < 0.0001). Interaction terms were evident for rs222020-G × season (p < 0.001), latitude × season (especially fall and winter; p < 0.01), and race × EFV use (p = 0.024). Overall, variance in serum 25(OH)D is substantially attributable to multiple factors, but the exact contribution of genetic and non-genetic factors can be obscured by partial overlaps and frequent interactions.
INTRODUCTION
The vitamin D pathway has a wide range of pathophysiological implications, with documented roles in bone metabolism, renal function, cardiovascular disease, and immune responses (; ; ). In the U.S. general population, suboptimal serum 25-hydroxyvitamin D [25(OH)D] concentration (<20 ng/ml)] is highly prevalent (; ). Factors associated with serum 25(OH)D status include race (skin color), seasonal (environmental) fluctuation, behavior, and genetic pre-disposition (; ; ; ; ; ; ).
Suboptimal serum 25(OH)D is seen in 54% of youth living with human immunodeficiency virus type 1 (HIV) infection (YLH; , ). The problem with 25(OH)D insufficiency (<20 ng/ml) or deficiency (<12 ng/ml) can be exacerbated by long-term use of antiretroviral drugs, especially efavirenz (EFV) that is known to interfere with 25(OH)D metabolism (; ). Longitudinal data from YLH with and without vitamin D supplementation can provide an important platform for dissecting multifactorial influences on the vitamin D pathway, including pre-vitamin D transport mediated by the vitamin D-binding protein (VDBP; ).
The GC/DBP gene1 encoding VDBP is mapped to chromosome 4q12-q13, with hundreds of known single nucleotide polymorphisms (SNPs). When 25(OH)D concentration is analyzed as a trait for vitamin D status, both genome-wide association studies () and candidate gene approaches () have consistently pointed to the potential importance of GC SNP variants. In an attempt to confirm the GC genotypes associated with 25(OH)D deficiency, our work here provides further evidence to justify fine-mapping for the GC locus in YLH populations.
MATERIALS AND METHODS
STUDY POPULATION
YLH (18–25 years old) represented two self-identified racial groups (African–American (AAs) and others) participating in a randomized, double-blind, placebo-controlled, multicenter trial (NCT004904122) within the Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN; , ). The research protocols, including procedures for written informed consent, were approved by the Institutional Review Board (IRB) at 16 ATN clinics and 19 International Maternal Pediatric Adolescent AIDS Clinical Trials (IMPAACT) sites in the United States and Puerto Rico. Ancillary studies summarized here were further approved by the IRB at University of Alabama at Birmingham (UAB).
INTERVENTION AND OUTCOME MEASURES
All participants were treated with ≥3 antiretrovirals (ARVs) for ≥90 days and with plasma HIV-1 RNA (viral load) <5,000 copies/mL within 60 days. After screening, subjects free of renal disease, pregnancy, and medicines that may affect bone mineral density, interfere with vitamin D absorption, or cause renal toxicity were enrolled into two relatively equal groups based on their ARV regimens (with or without tenofovir disoproxil fumarate, TDF). Within each group, eligible participants were randomized to receive vitamin D supplementation or placebo every 4 weeks for three doses. Serum 25(OH)D concentration was measured at baseline (week 0) and at study week 12 as the primary outcomes for analyses here.
CANDIDATE LOCI AND GENOTYPING
Earlier reports on phenotypes related to vitamin D (; ; ), including bone mineral density and fracture (; ; ), have revealed various loci with modest associations (as judged by effect sizes instead of p values). For this study, SNP selection focused on the most promising GC/DBP locus that encodes vitamin D-binding protein. SNPs reported repeatedly in the literature were considered first, followed by flanking SNPs (to facilitate analysis of linkage disequilibrium, LD) and SNPs found in coding and regulatory sequences. Using DNA extracted from Isohelix buccal swabs (Cell Projects Ltd., Kent, UK), all SNP genotypes were resolved by bi-directional DNA sequencing using the gold-standard Sanger chemistry (Polymorphic DNA Technologies, Inc., Alameda, CA, USA). For SNPs with minor allele frequencies (MAF) exceeding 0.05, the pairwise LD patterns were tested using the HaploView program ().
STATISTICAL ANALYSES
The study population was first grouped by race (AAs vs. others) for comparison of baseline (week 0) characteristics, with Wilcoxon test, Student t-test, and Chi-squared test applied to appropriate measurements. Subsequent analyses focused on three specific aims. Aim 1 was to demonstrate that serum 25(OH)D concentration is a relatively stable phenotype in YLH. Measurements at baseline and at week 12 were compared in participants in the placebo group (who did not receive vitamin D supplementation), using Spearman method (rho) and Pearson’s correlation coefficient (r; before and after log10-transformation/“normalization,” respectively). Aim 2 was to identify individual SNP genotypes associated with three clinically relevant 25(OH)D categories at baseline: <12 ng/ml (deficiency), ≥12–<20 ng/ml (insufficiency) and >20 ng/ml (sufficiency), using the ordinal logistic regression models adjusted for non-genetic factors (age, sex, and race). All relationships with statistical significance (p < 0.05) and low false discovery rate (FDR; q < 0.05) were included in multivariable models. Aim 3 was to quantify multifactorial influences on serum 25(OH)D, when log10-transformed serum 25(OH)D was analyzed as a continuous outcome in generalized linear models (GLMs). The summary statistics focused on relative effect sizes (regression beta and R2 values) attributable to genetic factors (SNP genotypes), demographic features (age, sex, and race), body mass index (BMI), environmental factors (season and latitude), and exposure to EFV. Similar approaches have been applied earlier to analyses of quantitative traits related to HIV infection (). Whenever possible, secondary (exploratory) models were evaluated for AAs and other races separately.
RESULTS
CHARACTERISTICS OF STUDY POPULATION BY RACE
A total of 192 YLH subjects had sufficient data for analyses, with relative equal representation of AAs (n = 99) and others (n = 93; Table 1). At baseline (week 0), these groups were similar (p > 0.20) in terms of age, female to male sex ratio (0.62 vs. 0.58), latitude of residency, enrollment seasons, randomization to vitamin D supplementation (49.5 vs. 52.3%), exposure to EFV (45.5 vs. 37.6%), and CD4+ T-cell (CD4) count (505 ± 149 vs. 550 ± 224 cells/μl of blood). In addition, similar proportions of AAs (13.0%) and others (17.5%) had severe immunodeficiency at baseline (CD4 count < 350 cells/μl). On the other hand, AAs differed from others in serum 25(OH)D concentrations both at baseline (p < 0.0001) and at week 12 (p < 0.01).
Table 1
| Characteristicsa | AAs (n = 99) | Others (n = 93) | Pe |
|---|---|---|---|
| Enrollment season: n (%) | |||
| Winter | 23 (23.2) | 18 (19.4) | |
| Spring | 30 (30.3) | 32 (34.4) | |
| Summer | 24 (24.3) | 23 (24.7) | |
| Fall | 22 (22.2) | 20 (21.5) | |
| At baseline (week 0) | |||
| Age (year): mean ± SD | 20.8 ± 2.0 | 20.9 ± 2.0 | – |
| BMI (kg/m2): mean ± SD | 26.3 ± 7.7 | 24.5 ± 5.5 | 0.058 |
| Sex ratio (F/M) | 0.62 (38/61) | 0.58 (34/59) | – |
| Latitude: n (%) | 0.067 | ||
| ≤35° | 30 (30.3) | 41 (44.1) | |
| >35° and ≤40° | 26 (26.3) | 14 (15.0) | |
| >40° | 43 (43.4) | 38 (40.9) | |
| 25(OH)D (ng/ml): median (IQR) | 14.7 (10.0 - 21.0) | 23.8 (17.4 - 29.9) | <0.0001f |
| log10 25(OH)D: mean ± SD | 1.17 ± 0.23 | 1.37 ± 0.19 | <0.0001 |
| 25(OH)D < 20 ng/ml: n (%) | 71 (71.7) | 32 (34.4) | <0.0001 |
| Vitamin D supplementation (50,000 U/month) | 49 (49.5) | 49 (52.7) | – |
| Exposure to EFV: n (%) | 45 (45.5) | 35 (37.6) | – |
| CD4 count (cells/μl): mean ± SDb | 505 ± 149 | 550 ± 224 | – |
| CD4 < 350 cells/μl: n (%)b | 7 (13.0) | 10 (17.5) | – |
| At week 12 | |||
| 25(OH)D (ng/ml): median (IQR) | 24.3 (15.2 - 30.7) | 27.3 (22.2 - 36.3) | 0.005f |
| log10 25(OH)D: mean ± SD | 1.34 ± 0.26 | 1.46 ± 0.19 | 0.0006 |
| 25(OH)D < 20 ng/ml: n (%) | 33 (35.9) | 17 (18.7) | 0.009 |
| CD4 count (cells/μl): mean ± SDc | 521 ± 161 | 617 ± 280 | 0.051 |
| CD4 < 350 cells/μl: n (%)c | 5 (11.6) | 6 (12.2) | – |
| Between visitsd | |||
| Stability of 25(OH)D: rho (p) | 0.69 (<0.0001) | 0.63 (<0.0001) | – |
| Stability of log10 25(OH)D: r (p) | 0.73 (<0.0001) | 0.77 (<0.0001) | – |
Main characteristics of the study population, after stratification by race/ethnicity.
AAs, African–Americans; BMI, body mass index; F, female; M, male; 25(OH)D, serum 25-hydroxyvitamin D concentration; IQR, interquartile range; SD, standard deviation of the mean; EFV, efavirenz; CD4 count, CD4+ T-cell count in peripheral blood.
Partial data for 54 AAs and 57 others at week 0.
Partial data for 43 AAs and 49 others at week 12.
Restricted to the subset of subjects (46 AAs and 42 others) randomized to the placebo group. Six subjects (four AAs and two others) are excluded because of missing data at week 12.
All p values > 0.20 are omitted (–).
By Wilcoxon test; all other comparisons are done with t-test and Chi-squared test.
STABILITY OF SERUM 25(OH)D CONCENTRATION OVER A 12-WEEK PERIOD
In a subset of subjects (46 AAs and 42 others) who were randomized to the placebo group, log10-transformed 25(OH)D concentrations were moderately stable between the two visits regardless of race (Figure 1), with Pearson r values ranging from 0.73 in AAs (p < 0.0001) to 0.77 in others (p < 0.0001; p > 0.50 between the two r values). Statistical adjustments for other factors slightly improved the r values. For example, when season was treated as a covariate, the adjusted r value became 0.74 in AAs (p < 0.0001) and 0.83 in others (p < 0.0001; p = 0.322 between the two adjusted r values). For 25(OH)D concentrations without log10-transformation, rank correlation between visits (Spearman rho values) ranged from 0.69 in AAs (p < 0.0001) to 0.63 in others (p < 0.0001; p > 0.50 between the two rho values).
FIGURE 1
SCREENING FOR INFORMATIVE GC SNPs
DNA sequencing based on 91 samples with most DNA (47 AAs and 44 others) identified 15 informative SNPs with MAF ≥ 0.05 in the overall study population (Table 2). All but one SNP (rs114282916) showed differential distribution between the two racial groups (AAs and others). Most SNPs had weak pairwise LD in both racial groups, but three intronic SNPs (rs222016, rs222020, and rs222029) were within a conserved haplotype block (Figure 2). Additional SNPs dismissed based on rarity of minor alleles (singleton to MAF < 0.05) included rs9016, rs3737553, rs80324156, rs114737000, rs6843222, and 10 polymorphisms not captured in the dbSNP database (last accessed in April 2013).
FIGURE 2
Table 2
| SNP IDa | Alleles | Location | Minor allele frequency | ||
|---|---|---|---|---|---|
| Overall | African–Americans | Others | |||
| rs4588b | C/A | Exon 11 | 0.177 | 0.112 | 0.247 |
| rs7041b | T/G | Exon 11 | 0.310 | 0.143 | 0.489 |
| rs112205706 | G/A | Intron | 0.053 | 0.098 | 0.011 |
| rs222016 | A/G | Intron | 0.383 | 0.565c | 0.205 |
| rs222020b | A/G | Intron | 0.385 | 0.535c | 0.226 |
| rs222029 | A/G | Intron | 0.325 | 0.467 | 0.182 |
| rs2298849 | A/G | Intron | 0.309 | 0.391 | 0.227 |
| rs3733359 | G/A | Promoter | 0.184 | 0.255 | 0.102 |
| rs35096193 | G/T | Promoter | 0.210 | 0.087 | 0.341 |
| rs1565572 | G/T | Promoter | 0.479 | 0.282 | 0.670c |
| rs114282916 | C/T | Promoter | 0.105 | 0.117 | 0.102 |
| rs115617005 | T/C | Promoter | 0.051 | 0.107 | 0 |
| rs76884743 | A/T | Promoter | 0.053 | 0.096 | 0.011 |
| rs113387725 | C/T | Promoter | 0.163 | 0.213 | 0.102 |
| rs80061752 | C/T | Promoter | 0.053 | 0.096 | 0.011 |
Minor allele frequency for 15 GC SNPs resolved by DNA sequencing.
Sorted by location on chromosome 4q (see Figure 2). Six more known SNPs (rs9016, rs3737553, rs80324156, rs114737000, rs6843222, and rs71213589) are dismissed for rarity of their minor alleles.
These SNPs are sequenced for the entire cohort, while others are dropped after the screening phase (based on patterns of linkage disequilibrium and estimates of statistical power).
Minor and major alleles are switched between the two racial groups.
In univariable models testing three clinically relevant 25(OH)D levels at baseline: <12 ng/ml (deficiency), ≥12–<20 ng/ml (insufficiency), and >20 ng/ml (sufficiency), seven SNPs showed promising trend (p < 0.05 and q ≤ 0.10) for associations in dominant models, with proportional odds ratios (pOR) ranging from 0.17 (rs222016 and rs222020, unfavorable) to 3.41 (rs7041, favorable) and q values from 0.002 (rs222016 and rs222020) to 0.10 (rs35096193, favorable; Table 3). Among the top four SNPs with q < 0.05, rs7041 has known associations with vitamin D status and related outcomes (; ). Three other SNPs in strong LD (Figure 2) could be represented by rs222020, which has been associated with vitamin D status and related outcomes as well (; ; ; ). Further genotyping in the rest of the study cohort focused on rs7041 (a coding SNP) and rs222020 (an intronic SNP).
Table 3
| GC SNP genotypes | n (AA + other) | pORa | p | FDR (q)c |
|---|---|---|---|---|
| rs7041 (GG + GT vs. TT) | 90 (46 + 44) | 3.41 | 0.003 | 0.010 |
| rs222016b (GG+AG vs. AA) | 90 (46 + 44) | 0.17 | 0.0003 | 0.002 |
| rs222020b (GG + AG vs. AA) | 91 (47 + 44) | 0.17 | 0.0002 | 0.002 |
| rs222029b (GG + AG vs. AA) | 90 (46 + 44) | 0.24 | 0.001 | 0.006 |
| rs35096193 (TT + TG vs. GG) | 90 (46 + 44) | 2.35 | 0.047 | 0.100 |
| rs76884743 (TT + AT vs. AA) | 91 (47 + 44) | 0.24 | 0.025 | 0.060 |
| rs80061752 (TT + TC vs. CC) | 91 (47 + 44) | 0.24 | 0.025 | 0.060 |
Univariable analyses of seven GC SNPs using baseline (week 0) serum 25(OH)D concentration as three ordinal categories (deficiency, insufficiency, and sufficiency).
Favorable effect (association with vitamin D sufficiency) is reflected by a value of ±1.0 for the proportional odds ratio (pOR).
These SNPs form a single haplotype block regardless of racial background (see Figure 2).
False discovery rate (FDR) is based on p values from analyses of all 15 SNPs shown in Table 2.
UNIVARIABLE AND MULTIVARIABLE MODELS FOR TWO GC SNPs (rs222020 and rs7041) IN THE ENTIRE COHORT
Both rs7401-G and rs222020-G were associated with baseline serum 25(OH)D categories in univariable models (pOR = 2.32 and 0.31, p = 0.008 and 9.0 × 10-4, respectively). After statistical adjustment for demographic features (sex, age, and race) and exposure to EFV, rs7041 allele G was no longer a predictor (adjusted pOR = 1.08 and p = 0.827), while rs222020 allele G remained predictive of serum 25(OH)D categories (pOR = 0.45 and p = 0.014). However, further adjustments for BMI and environmental factors (latitude and enrollment season) diminished the association of rs222020-G (adjusted p = 0.069; Table 4). The strong independent predictors included race (p < 0.0001), enrollment season (p < 0.0001), latitude of residence (p < 0.001), BMI (p = 0.002), and use of EFV (p = 0.006). Summer had the most dramatic impact on seasonal fluctuation in serum 25(OH)D (pOR = 8.23, p < 0.0001), while fall and spring were also quite favorable against winter (pOR = 4.90 and 3.55, respectively).
Table 4
| Independent factors | Relative effectc in a joint (multivariable) model | ||
|---|---|---|---|
| pOR | 95% CI | p | |
| rs222020-Ga | 0.54 | 0.27 - 1.05 | 0.069 |
| Being African–American | 0.21 | 0.11 - 0.41 | <0.0001 |
| Enrollment season | <0.0001 | ||
| Springb | 3.55 | 1.53 - 8.20 | 0.003 |
| Summerb | 8.23 | 3.22 - 21.04 | <0.0001 |
| Fallb | 4.90 | 1.98 - 12.15 | <0.0001 |
| Latitude of residence (trend) | 0.52 | 0.63 - 0.74 | <0.001 |
| Body mass index | 0.93 | 0.88 - 0.97 | 0.002 |
| Use of efavirenz (EFV) | 0.42 | 0.22 - 0.78 | 0.006 |
Independent predictors of serum 25(OH)D concentration as three ordinal categories (deficiency, insufficiency, and sufficiency).
Nucleotide A is the major allele (referent) for rs222020. In a third model, rs222020-G accounts for 3.3% of log10 25(OH)D variance in 93 other subjects (see text).
Winter is the referent in all tests.
Favorable effect (association with vitamin D sufficiency) is reflected by a value of >1.0 for the proportional odds ratio (pOR).
VARIANCE IN log10-TRANSFORMED SERUM 25(OH)D CONCENTRATION EXPLAINED BY GC GENOTYPES AND OTHER PERTINENT FACTORS
At least six factors independently contributed to the variability in log10-transformed serum 25(OH)D concentration (Table 5). When sorted by their relative impact (i.e., beta estimate and semi-partial R2 value), race (AAs vs. other), and season had the greatest effects (adjusted p < 0.0001 and p < 0.001, respectively), followed by latitude (in three major grids; p < 0.001), BMI (p = 0.008), use of EFV (p = 0.016), and rs222020-G (p = 0.023). Collectively, these factors accounted for 38.0% of variance in the log10-transformed 25(OH)D concentration at baseline (p < 0.0001). Other potential factors, including sex, age, and additional GC SNP variants were firmly dismissed (adjusted p > 0.25).
Table 5
| GC variant and demographic features | Relative impactc on log10 25(OH)D (multivariable model) | ||
|---|---|---|---|
| Δ (Mean ± SE) | R2 | p | |
| rs222020-Ga | -0.07 ± 0.03 | 0.018 | 0.023 |
| Being African–American | -0.15 ± 0.03 | 0.089 | <0.0001 |
| Use of efavirenz (EFV) | -0.07 ± 0.03 | 0.020 | 0.016 |
| BMI (per unit change)b | -0.01 ± 0.00 | 0.025 | 0.008 |
| Latitudeb | -0.06 ± 0.02 | 0.045 | <0.001 |
| Seasonb | NA | 0.073 | <0.001 |
| Spring vs. winter | 0.12 ± 0.04 | NA | 0.003 |
| Summer vs. winter | 0.19 ± 0.04 | NA | <0.0001 |
| Fall vs. winter | 0.13 ± 0.04 | NA | 0.002 |
Independent predictors of baseline (week 0) serum 25(OH)D concentration among 192 youth living with HIV-1 infection: alternative analyses after considering environmental factors.
The AA genotype is treated as the referent for rs222020 allele G.
As defined in Table 1.
For each individual factor, the independent (adjusted) effect size is measured first by the difference (Δ) in serum log10 25(OH)D and then by the R2values (all are under-estimated because of partial overlap). For the overall model, R2 = 0.380 (p < 0.0001).
Ranking of the six individual (independent) predictors of log10-transformed serum 25(OH)D concentration was often complicated by issues with partial overlap. For example, variance explained by the rs222020-G allele varied substantially (from 2.9 to 10.7%) according to the order in which three partially overlapping factors (race, use of EFV, and rs222020-G) were added to the model. In addition, the variance attributable to rs222020-G differed somewhat between AAs (4.5%, adjusted p = 0.029) and others (3.3%, adjusted p = 0.080) when conditioned on the effect of EFV (Table 7). In contrast, after accounting for the effect of rs222020-G, the impact of EFV use on 25(OH)D was only apparent in AAs (adjusted R2 = 8.8%, p = 0.003) and not in others (adjusted R2 = 0.1%, p = 0.812; Table 7).
Table 6
| Interaction termsa | Relative impactd on log10 25(OH)D (multivariable model) | ||
|---|---|---|---|
| Δ (mean ± SE) | R2 | P | |
| rs222020-G × season | NA | 0.055 | <0.001 |
| rs222020-G × springb | -0.22 ± 0.05 | NA | <0.001 |
| Latitude × season | NA | 0.026 | 0.035 |
| Latitude × fallc | -0.11 ± 0.03 | NA | <0.001 |
| Latitude × winterc | -0.10 ± 0.03 | NA | 0.002 |
| Use of EFV × race | NA | 0.015 | 0.024 |
Three independent interaction terms identified by multivariable analyses.
Non-interactive factors (e.g., BMI) are also included in the model. The AA genotype is treated as the referent for rs222020.
Seasonality of the rs222020-G effect is restricted to spring.
Two seasons (fall and winter) capture the main interactive effect of latitude × season.
For each interaction term, the independent effect size is measured first by the difference (Δ) in serum log10 25(OH)D and then by the R2values (all are under-estimated because of partial overlap).
Table 7
| GC variant and two other factors | Relative impactc on log10 25(OH)D (multivariable model) | ||
|---|---|---|---|
| Δ (Mean ± SE) | R2 | P | |
| Overall cohort (N = 192) | |||
| rs222020-Ga | -0.09 ± 0.03 | 0.033 | 0.004 |
| Being African–American | -0.17 ± 0.03 | 0.113 | 2.9 × 10-7 |
| Use of efavirenz (EFV) | -0.07 ± 0.03 | 0.021 | 0.024 |
| African–Americans only (n = 99) | |||
| rs222020-Ga | -0.12 ± 0.05 | 0.045 | 0.029 |
| Use of efavirenz (EFV)b | -0.14 ± 0.04 | 0.088 | 0.003 |
| Others only (n = 93) | |||
| rs222020-Ga | -0.07 ± 0.04 | 0.035 | 0.071 |
Examples of racial differences in genetic association with serum 25(OH)D concentration.
Homozygosity with the major allele A serves as the referent for rs222020.
Not a statistically significant factor in the model for other races (adjusted R2 = 0.001, p = 0.812).
For each factor shown in individual models, the independent effect size is measured first by the difference (Δ) in serum log10 25(OH)D (the reference group is negative for all factors) and then by the R2 values.
INTERACTION TERMS
Multivariable models further revealed several pairwise interactions, i.e., rs222020-G × season (p < 0.001), latitude × season (especially fall and winter; p < 0.01), and race × EFV use (p = 0.024). Seasonality of the rs222020-G effect on 25(OH)D was apparently restricted to spring, as genotype-specific differences were not detected in other seasons (Figure 3).
FIGURE 3
OBSERVATION OF DIFFERENCES BETWEEN RACIAL GROUPS
At least two racial differences were noted in separate analyses of AAs (n = 99) and other races (n = 93). First, negative association of rs222020-G with 25(OH)D was restricted to AAs (R2 = 4.5%, adjusted p = 0.029) and not other subjects (3.3%, adjusted p = 0.080) when conditioned on the effect of EFV (Table 7). Second, the deleterious impact of EFV use on 25(OH)D was seen in AAs (adjusted R2 = 8.8%, p = 0.003) and not in other subjects (adjusted R2 = 0.1%, p = 0.812) after accounting for the contribution of rs222020-G.
DISCUSSION
Despite a modest sample size, our analyses here reveal five major findings concerning vitamin D metabolism in youth living with HIV-1 infection. First, serum 25(OH)D concentration is relatively stable over a 12-week period regardless of race. Second, at least one GC SNP variant, the rs222020-G allele, is independently predictive of suboptimal serum 25(OH)D, especially during the spring season. Third, use of EFV is associated with low serum 25(OH)D in the combined cohort based on univariable models, but the EFV effect is restricted to AAs when the rs222020-G allele is added to multivariable models. Fourth, the exact contribution of genetic and non-genetic factors (latitude, season, BMI, and race) can be obscured by partial overlaps and frequent interactions. Fifth, statistical models are not uniformly applicable to racial groups. Most of these observations are novel and highly relevant to public health.
As a main focus of this study, the GC gene3 consists of 13 exons and has hundreds of known SNPs, but neither genome-wide association studies nor candidate gene approaches reported in the literature have covered this locus sufficiently enough to allow fine-mapping. To avoid heavy penalty for multiple testing of randomly selected GC SNPs, we chose to examine coding and regulatory (promoter) sequences at both ends of several SNPs with relatively consistent associations. For example, the minor allele G (or C in the complementary strand) for rs222020 has been highlighted recently in the context of compression strength index of the femoral neck (), peripheral arthritis in ankylosing spondylitis (), and plasma 25(OH)D concentration (). By analyzing rs222020 and multiple neighboring SNPs, it was evident that rs222020-G is able to tag several intronic variants within a single haplotype block. However, rs222020-G did not seem to tag other functionally relevant variants. Mechanisms underlying its independent association with suboptimal 25(OH)D concentration remain elusive, and search for further clues may need to consider less obvious pathways (DNA–DNA and DNA–protein interactions) being actively pursued by the ENCODE project (; ; ; ).
Two other prominent GC SNPs, rs7041, and rs4588, do cause amino acid substitutions at codon 416 (D/E) and codon 420 (T/K), respectively, in exon 11. Three haplotypes involving these non-synonymous SNPs correspond to different protein isoforms known as GC1F, GC1S, and GC2. Earlier studies have demonstrated the potential importance of rs7041 variants alone () or in conjunction with rs4588 variants (). Although rs7041-G appeared to be highly favorable in our initial screening (univariable models only), it was subsequently dismissed by multivariable models in which race and other prominent factors were treated as covariates. The distribution of rs7041-G differs between AAs (low) and other races (high; Table 2), so definitive analyses may require a third population with intermediate allele frequency. Nonetheless, rs7041-G may serve as a useful biomarker for disparity in serum 25(OH)D concentration, especially since its biological relevance is so obvious. Additional GC SNPs of interest, including rs2070741 () and rs2282679 (), are not part of our study design. Judging by their reported effect sizes, it is unlikely that inclusion of these SNPs will alter our main conclusions.
Our finding on GC SNP rs222020 here is highly consistent with earlier observations based on two independent Caucasian populations (). The effect size (R2) reported for rs222020 ranges from 1% to 4% in Caucasians, which is quite similar to what we can demonstrate for YLH (Table 5). However, by our assessment, the association of rs222020 genotypes with 25(OH)D concentration is heavily dependent on seasonal fluctuation. Studies that evaluate subjects in the spring season alone can lead to over-estimates, while analyses biased for other seasons can easily miss the genetic effect (Table 6; Figure 3). Future studies will clearly need to consider the strong impact of season and latitude on vitamin D metabolism.
Recognition of EFV as another factor that influences vitamin D metabolism is also well expected (; ). Of note, the unfavorable impact of EFV was mostly restricted to AAs. Such racial disparities may reflect the sensitivity or vulnerability of AAs to therapeutic complications when they are already prone to having suboptimal 25(OH)D concentration. Fortunately, response to vitamin D supplementation is not compromised by use of EFV (). Further elucidation of race-specific effects of EFV will need to rely on large cohorts with prospective data.
In summary, our study identified at least six partially overlapping but independent factors that collectively account for 38% of variance in serum 25(OH)D concentration. The complex picture can attest to the need for cautionary interpretation of results from univariable models, as exemplified by analysis of GC SNPs rs7401 and rs222020. Fine-mapping of the GC locus for causal variants is more difficult than expected because (i) rs222020-G and related GC variants are not in clear LD with coding and promoter sequence polymorphisms; (ii) the effect of rs7041-G is clearly confounded by racial background, and (iii) serum 25(OH)D concentration as a quantitative or semi-quantitative trait can fluctuate over time (seasonality). These observations should benefit follow-up studies on GC genotypes and vitamin D metabolism, probably beyond the setting of chronic HIV infection and long-term therapeutic complications.
Statements
Author contributions
Charles B. Stephensen, Kathleen Mulligan, Brandy Rutledge, Patricia M. Flynn, Jorge Lujan-Zilbermann, Rohan Hazra, Craig M. Wilson, Peter L. Havens, and Jianming Tang designed the study. Jorge Lujan-Zilbermann helped with patient recruitment and enrollment at one of the sites for Adolescent Medicine Trials Network for HIV/AIDS Interventions. Travis R. Porter, Peter L. Havens, and Jianming Tang procured samples and reagents. Travis R. Porter, Xuelin Li, and Jianming Tang managed and analyzed the data. All authors contributed to the writing and proof reading of this manuscript.
Acknowledgments
This work was the result of collective efforts by the ATN 063 protocol team (, ). We thank principal investigators, their staff, as well as participants at all clinical sites for their valuable contribution to various aspects of this study. We also thank Wei Song for interim data analyses. Funding for this study came from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), through grant U01-HD040533 to CMW. The contents in this manuscript are the responsibility of the study authors and do not necessarily reflect the views of NICHD or the United States government.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
antiretroviral, genetics, HIV-1, race, youth, vitamin D
Citation
Porter TR, Li X, Stephensen CB, Mulligan K, Rutledge B, Flynn PM, Lujan-Zilbermann J, Hazra R, Wilson CM, Havens PL, Tang J and Adolescent MedicineTrials Network for HIV/AIDS Interventions (ATN) 063 study team (2013) Genetic associations with 25-hydroxyvitamin D deficiency in HIV-1-infected youth: fine-mapping for the GC/DBP gene that encodes the vitamin D-binding protein. Front. Genet. 4:234. doi: 10.3389/fgene.2013.00234
Received
03 September 2013
Accepted
22 October 2013
Published
14 November 2013
Volume
4 - 2013
Edited by
José A. G. Agúndez, University of Extremadura, Spain
Reviewed by
Diego Maria Michele Fornasari, University of Milan, Italy; Mehmet Tevfik Dorak, Florida International University, USA
Copyright
© 2013 Porter, Li, Stephensen, Mulligan, Rutledge, Flynn, Lujan-Zilbermann, Hazra, Wilson, Havens, Tang and for the Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN) 063 study team.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jianming Tang, Department of Medicine, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL 35294, USA e-mail: jtang@uab.edu
This article was submitted to Pharmacogenetics and Pharmacogenomics, a section of the journal Frontiers in Genetics.
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