Sequence variants of elaC homolog 2 (Escherichia coli) (ELAC2) gene and susceptibility to prostate cancer in the Health Professionals Follow-Up Study

Sequence variants of elaC homolog 2 (Escherichia coli) (ELAC2) gene and susceptibility

to prostate cancer in the Health Professionals Follow-Up Study

Yen-Ching Chen

_{, Edward Giovannucci}

_{, Peter Kraft}

and David J.Hunter

1

Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA,2Research Center for Genes, Environment and Human Health and Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei 10020, Taiwan,3Department of Nutrition and4Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA

To whom correspondence should be addressed. Tel:þ1 617 525 2279; Fax:þ1 617 525 2008;

Email: karen.chen@channing.harvard.edu

Two non-synonymous single-nucleotide polymorphisms (SNPs),

Ser217Leu and Ala541Thr, in the elaC homolog 2 (Escherichia

coli) (ELAC2) gene have been related to prostate cancer risk in

previous studies, though with inconsistent results. The association

of ELAC2 haplotypes with prostate cancer risk has not yet been

explored. We assessed whether sequence variants in ELAC2 were

associated with the risk of total or aggressive prostate cancer. In

a nested case–control design within the Health Professionals

Fol-low-Up Study, we identified 659 participants with prostate cancer

diagnosed after they provided a blood specimen in 1993 and

be-fore January 2000. Controls were 656 age-matched men without

prostate cancer who had had a prostate-specific antigen test after

providing a blood specimen. We genotyped eight tagging SNPs in

ELAC2 to test for the association between sequence variances in

ELAC2 and prostate cancer. No individual SNP (including

Ser217-Leu) was associated with the risk of prostate cancer. Ala541Thr is

a rare SNP in this population. One common haplotype (hap4) was

statistically significantly associated with an increased risk of

pros-tate cancer [odds ratio (OR) 5 1.39, 95% confidence interval 5

1.05–1.85]. Two common promoter SNPs and three common

hap-lotypes were statistically significantly associated with aggressive

prostate cancer (carriers versus non-carriers—snp2: OR 5 1.43,

snp3: OR 5 0.69, hap1: OR 5 1.47, hap2: OR 5 0.72, hap4: OR 5

1.51; global P-value for all common haplotypes 5 0.11). Common

SNPs and haplotypes of ELAC2 were associated with risk of

ag-gressive prostate cancer.

Introduction

elaC homolog 2 (Escherichia coli) (ELAC2) is located on

chromo-some 17p11, spans 27 kb and includes 24 exons. Identified as a

pros-tate cancer susceptibility gene (1), it is expressed at high levels in rat

testis and some mouse tissues (2). Although ELAC2 is expressed at

low levels in mouse prostate (2), experimental studies showed that

ELAC2 plays a role in germline proliferation, which is related to cell

cycle and sterility (3), and thus may relate to prostate carcinogenesis.

The amino acid sequence of ELAC2 is similar to that of PSO2 DNA

interstrand cross-link repair proteins and the 73 kD subunit of

mes-senger RNA 3# end cleavage and polyadenylation specificity factor

(CPSF73), which may in turn be related to blocking transcription,

replication and segregation of DNA and regulation of messenger

RNA modifications (1,4).

Two non-synonymous polymorphisms in ELAC2, Ala541Thr and

Ser217Leu, have been well studied. The allele frequency of Thr541

was lower in Japanese subjects (0–1.1%) (5–7) than in

African-Amer-icans (21%) (8) or Caucasians (2.7–10.6%) (8–20). However,

com-paring Thr541 carriers with non-carriers, the risk of sporadic prostate

cancer was higher among Japanese subjects [odds ratio (OR) 5 3.4–

5.1] (6,7) than among Caucasians (OR 5 1.0–2.2) (8–20).

Further-more, Thr541 was not associated with hereditary prostate cancer

(10,12).

In contrast, the Leu217 allele is more prevalent in Caucasians

(27–46%) than in African Americans (23%) (8) or Japanese (0–3.3%)

(5,6). Three (5,10,17) out of 14 studies found that the Leu217 allele

was statistically significantly associated with prostate cancer [Leu217

carriers versus non-carriers—all cases versus controls: OR 5 0.78

(10); non-aggressive cases versus controls: OR 5 1.34 (17); sporadic

cases versus controls: OR 5 3.11 (5)], whereas the remaining studies

found a null relationship. A meta-analysis showed that the Leu217

variant was statistically significantly associated only with familial

prostate cancer (OR 5 1.37) (6). Taken together, 80% of studies

showed no evidence of association between Leu217 and prostate

can-cer risk. Some studies indicated that the joint effect of Ser217Leu and

Ala541Thr was associated with a higher risk of prostate cancer than

Leu217 alone (1,9,17), whereas others failed to observe this joint

effect (6,10–12,15,16).

Past studies of ELAC2 and prostate cancer risk have focused on the

two common missense variants, Ser217Leu and Ala541Thr, and

re-sults have been inconsistent. However, two single-nucleotide

poly-morphisms (SNPs) provide a relatively small amount of information

for predicting prostate cancer risk. The relationship between

haplo-types in ELAC2 and the risk of sporadic prostate cancer has not been

explored. Therefore, in addition to these two non-synonymous SNPs

in ELAC2, we selected additional tagging SNPs and hypothesized that

haplotypes of ELAC2 are associated with susceptibility to prostate

cancer in the Health Professionals Follow-Up Study. We also explored

the relationship between ELAC2 genetic polymorphisms and

aggres-siveness of prostate cancer.

Materials and methods

Study population

In this nested case–control study, incident prostate cancer cases were identified from the ongoing Health Professionals Follow-Up Study with follow-up from 1986 through 2000. A total of 51 529 USA men aged 40–75 years were enrolled in 1986. At baseline, every participant completed a mailed question-naire on demographics, lifestyle and medical history and a semiquantitative food-frequency questionnaire. Information on exposures and diseases was up-dated every other year, and diet information was upup-dated every 4 years. Deaths were identified through reports by family members or the postal system upon follow-up questionnaires or a search of the National Death Index (21). This study was approved by the Institutional Review Board at the Harvard School of Public Health.

Blood samples (collected in tubes containing sodium ethylenediamine-tetraacetic acid) were obtained from 18 018 of the participants between 1993 and 1995. We obtained informed consent from each subject before blood was drawn. Samples were shipped by overnight courier and centri-fuged; the aliquots, including plasma, erythrocytes and buffy coat, were stored in liquid nitrogen freezers. QIAGEN QIAamp blood extraction kit (QIAGEN, Valencia, CA) was used for DNA extraction. All DNA samples were whole-genome amplified, and quality control (QC) samples had 100% genotype concordance. Among the men who provided a blood specimen, 95% responded to the year 2000 questionnaire, and the 18 who died of prostate cancer before the end of follow-up were included in the case series.

We identified 659 incident prostate cancer cases and 656 controls; all are Caucasians. Each case was matched with one control who was alive, Abbreviations:BMI, body mass index; CI, confidence interval; ELAC2, elaC

homolog 2 (Escherichia coli); OR, odds ratio; QC, quality control; SNP, sin-gle-nucleotide polymorphism.

had not been diagnosed with cancer by the date of the case’s diagnosis and had a prostate-specific antigen test after the date of blood draw. The latter criterion ensured that controls had the opportunity to have an occult prostate cancer diagnosed. All controls had a prostate-specific antigen test within 2.5 years of the date of diagnosis of their matched case. Because plasma analyses were performed on the same case–con-trol set, cases and concase–con-trols were matched on year of birth (±1 year), prostate-specific antigen test prior to blood draw (yes/no), time of blood draw (midnight to before 9 A.M., 9 A.M. to before noon, noon to before 4 P.M. and 4 P.M. to before midnight), season (winter, spring, summer and fall) and year of blood draw. To elucidate the effect of sporadic prostate cancer (prostate cancer that occurs occasionally and at random intervals in a population), we also performed analyses excluding sub-jects with familial prostate cancer cases (two or more family members had prostate cancer cases, n 5 15 cases and 10 controls).

Laboratory assays

Eight common (frequency . 5%) tagging SNPs in ELAC2 (s1, s4, s5, s7, s11, s13, AT and s17) were selected from the study of Camp et al. (22). Laboratory personnel were blinded to case–control status. All case–control matched pairs were analyzed together using the Sequenom system. Multiplex polymerase chain reactions were carried out to generate short polymerase chain reaction products (.100 bp) containing one SNP. The details of polymerase chain reaction and matrix-assisted laser desorption ionization time-of-flight mass spectrometry are available upon request. Six control DNA samples were used for optimization. The SNP s13 in Camp et al. (22) failed both Sequenom and Taqman assay designs in our population due to low QC rates. This SNP could be replaced by snp5 (Table I) because they were in the same linkage disequi-librium group according to phylogenetic network analysis from Camp et al. (22). Analyses using the Tagger program (http://www.broad.mit.edu/mpg/ tagger/) also suggested that the new set of SNPs after replacement can Table I. Characteristics of ELAC2 SNPs among Caucasians

SNP name SNP name

used in Camp et al. (22)

rs # Nucleotide change (amino acid change)

Location bp relative to start codon ATG

Controls Cases

MAF (%) HWE, P-value MAF (%) HWE, P-value

Snp1 S1 rs2322779 T / C Promoter 12682 16 0.14 19 0.74

Snp2 S4 Not applicable G / A Promoter 6280 30 0.99 33 0.40

Snp3 S5 rs12600940 C / T Promoter 3831 49 0.35 46 0.44

Snp4 S7 rs2051974 G / A Promoter 381 24 0.81 24 0.17

Snp5 SL rs4792311 C / T (Ser217Leu) Exon 6256 32 0.88 32 0.17

Snp6 S11 rs2302069 A / G Intron 7241 14 0.45 13 0.44

Snp7 AT rs5030739 G / A (Ala514Thr) Exon 21363 0 Not applicable 0 Not applicable

Snp8 S17 rs17552022 A / G Exon 22970 13 0.36 14 0.21

HWE, Hardy–Weinberg equilibrium; MAF, minor allele frequency.

Fig. 1. ELAC2linkage disequilibrium plot. This plot was generated by Haploview and Locusview programs. When the approach of Gabriel et al. was used, the eight SNPs formed one block. The rs number on the top from left to right corresponds to the SNP name (e.g. snp1, snp2, etc.). The level of pairwise D#, which indicates the degree of linkage disequilibrium between two SNPs, is shown in the linkage disequilibrium structure in red. Six common haplotypes (frequency . 0.05) were identified.

accurately capture the information within haplotype blocks (r2_{5 0.984).}

Fi-nally, a total of eight SNPs were genotyped in three plexes at the Harvard Partners Center for Genetics and Genomics (Boston, MA). For each SNP, genotyping data were missing for fewer than 5% of the study participants. Sixty-eight QC samples were obtained from 18 external participants who were recruited the same way as the study population, and each of them had two to six duplicates. These QC samples were genotyped together with all other samples in this study. All QC samples passed the QC test with discordance rate 5 0. Ascertainment of prostate cancer

Investigators reviewed the medical and pathology records for men with prostate cancer, reported from the follow-up questionnaire or rarely death certificate, to confirm adenocarcinoma of the prostate and to document clinical presentation, stage and Gleason sum of the tumor. The cases were categorized into regionally invasive or metastatic (stage T3c, N1 or M1), organ-confined or minimal extraprostatic extension (T1b–T3a and N0M0), higher grade (Gleason sum 7) and lower grade (Gleason sum , 7). Incidental microscopic focal tumors (stage T1a) were excluded because they are generally indolent and susceptible to detection bias due to differ-ential rates of surgery for benign prostatic hyperplasia. In addition, men with a pre-vious cancer (except non-melanoma skin cancer) prior to the date of blood draw were excluded. Confirmed non-T1a tumors between blood draw and 31 January 2000 were included. In the blood subcohort, 92% of cases were confirmed by medical record and 5% by other corroborating information; only 3% were based on self-report (23). We included the self-reported cases in the analyses because the concordance between self-reported and medical record-confirmed cases was high (.90%) in this cohort.

Statistical analysis

The Hardy–Weinberg equilibrium test was performed for each SNP among controls. Haplotype block structure (Figure 1) was determined using Haplo-view (http://www.broad.mit.edu/mpg/haploHaplo-view/index.php) and LocusHaplo-view (http://www.broad.mit.edu/mpg/locusview/) programs. The expectation-maxi-mization algorithm (24,25) was applied to construct haplotypes in each block using the Tagsnp program (26). We estimated haplotype frequencies and their 95% confidence interval (CI) using the progressive ligation algorithm (as im-plemented in SAS PROC HAPLOTYPE).

Conditional logistic regression models were used to estimate ORs for dis-ease in participants carrying either 1 or 2 versus 0 copies of the minor allele of each SNP and each multilocus haplotype. Haplotype trend regression (27) was used to test global association between ELAC2 haplotypes and prostate cancer. To assess the risk of sporadic prostate cancer, we performed the same SNP and haplotype association analyses after exclusion of subjects with more than one prostate cancer case in his family. The type I error rate was first controlled by the single multiple-degree-of-freedom test of association between ELAC2 hap-lotypes and prostate cancer. Given a statistically significant global test, haplo-type-specific tests can provide some guidance as to which variants contribute to the statistically significant global test, although the nominal P-values we pres-ent do not control the family-wise error rate for these post hoc comparisons. Second, we performed Westfall’s step-down permutation test (number of per-mutation tests 5 100 000) for SNP and haplotype analyses to correct for multiple comparisons.

Age and family history are known risk factors for prostate cancer (28,29); previous studies found that, compared with lower body mass index (BMI) (,24.9 kg/m2_{), higher BMI (30 kg/m}2_{) was associated with lower risk of}

all prostate cancer (30), as well as early-onset (,60 years old) (31) and high-grade prostate cancer (32,33), but results were not consistent across studies. Family history of prostate cancer was available in 1990, 1992 and 1996; we checked the consistency of data across these time periods and used the updated information in 1996 for analyses. We used the likelihood ratio test to evaluate how these factors modified the association between ELAC2 SNPs or haplo-types and the risk of prostate cancer by comparing a model with terms for main effects and interaction terms with the model with terms for main effects only. Because of the possible role of ELAC2 in germline proliferation and cell cycle (3), aggressiveness of prostate cancer may relate to genetic variations of ELAC2. We tested the association between ELAC2 haplotypes and aggressive-ness of prostate cancer by using the definitions for tumor aggressiveaggressive-ness (ag-gressiveness: stages T3b, T4, N1, M1 or death due to prostate cancer or Gleason sum7). All analyses were conducted with SAS release 9.0 (SAS Institute, Cary, NC), and all statistical tests were two sided.

Results

Eight SNPs in ELAC2 were genotyped. Except for snp7, none of the

rest of the SNPs was out of Hardy–Weinberg equilibrium among

con-trols (Table I). Because snp7 (rs5030739, Ala541Thr) was a rare allele

with no heterozygote and no homozygote variants in this Caucasian

population, it was dropped from the haplotype analyses. The internal

blinded QC specimens did not show evidence of genotyping error.

The study population included 659 incident prostate cancer cases

and 656 matched controls. Age and BMI distributions were similar for

cases and controls (Table II), but family history of prostate cancer

was statistically significantly different (P 5 0.02). The mean age at

starting smoking, lifetime average number of cigarettes/day (include

non-smokers) and alcohol consumption were similar for cases and

controls. The distribution of prostatitis by age group and case–control

status did not show statistically significant difference between cases

and controls (P 5 0.09). Among cases, 79% were in tumor stages

T1b–T3a, 49% had Gleason grades 5–6 and 36% had aggressive

prostate cancer. Eighteen cases died of prostate cancer before 31

January 2000.

No SNP (including the non-synonymous SNP Ser217Leu) was

as-sociated with prostate cancer risk (Table III). After dropping the rare

SNP (snp7, Ala541Thr), seven SNPs spanning ELAC2 formed one

block using the algorithm of Gabriel et al. (34), where blocks identified

with the default settings in Haploview were merged if they had

multi-allelic D# .0.8, and the cumulative frequency of common (.5%

fre-quency) haplotypes in the merged block was above 80% (35). Six

common haplotypes (frequency . 5%) were found with an accumulated

Table II. Characteristics of Caucasians in the Health Professionals Follow-Up Study

Variable Cases n 5 659,

N (%)

Controls n 5 656, N (%)

Age (year) (matching factor)

65 297 (45) 302 (46) .65 362 (55) 354 (54) BMI (kg/m2₎ 25 405 (61) 489 (59) 25–30 221 (34) 221 (34) .30 33 (5) 46 (7) Family history of prostate cancer No 528 (80) 557 (85) Yes 131 (20) 99 (15)

Age started smoking 23.0 ± 5.3 22.9 ± 5.4

Lifetime average cigarettes per day

10.5 ± 6.3 10.9 ± 6.7 Alcohol (g/day) 11.4 ± 14.9 10.5 ± 14.7 Prostate-specific antigen at diagnosis of prostate cancer (ng/ml) 11.3 ± 21.0 (n 5 479) Not applicable Stage

T1b-T3a 517 (79) Not applicable

T3b, T4, N1, M1 or death due to prostate cancer

55 (8) Missing 87 (13) Gleason sum 2–4 44 (7) Not applicable 5–6 320 (49) 7 164 (25) 8–10 55 (8) Missing 76 (12) Aggressiveness No 419 (64) Not applicable Yes 240 (36) Missing 0

Death due to prostate cancer

No 641 (97) Not applicable

Yes 18 (3)

Prostatitis

60 35 (24) 18 (15)

.60 111 (76) 102 (85)

Aggressiveness defined as stages T3b, T4, N1, M1 or death due to prostate cancer or Gleason sum7.

frequency of 84% in controls (Table IV), and the P-value for the global

test was 0.18. Men carrying one copy of the variant hap4 had a 1.39-fold

increased risk of prostate cancer (95% CI 5 1.05–1.85) compared with

non-carriers. When subjects were restricted to sporadic prostate cancer,

results changed very little (the P-value for global test became 0.03;

hap4: OR 5 1.41, 95% CI 5 1.06–1.87; data not shown).

We looked at interactions with the following risk factors: age, BMI

and family history of prostate cancer. However, none of these risk

factors modify the association between sequence variants of ELAC2

and prostate cancer.

We also explored the main effects for aggressive and

non-aggres-sive prostate cancer separately (Table V). Two SNPs showed a

statis-tically significant association with aggressive prostate cancer (carriers

versus non-carriers—snp2: OR 5 1.43, 95% CI 5 1.06–1.93; snp3:

OR 5 0.69, 95% CI 5 0.50–0.95). For haplotype analysis (global test

P-value 5 0.11), hap1 and hap4 variant carriers had a 1.47- and

1.51-fold increased risk of aggressive prostate cancer (95% CI 5 1.08–1.99

and 1.04–2.18, respectively) compared with non-carriers. Hap2

vari-ant carriers showed 0.72-fold risk of prostate cancer (95% CI 5

0.52–0.98) compared with non-carriers. Results were not statistically

significant for non-aggressive prostate cancer. After correction for

multiple comparisons by the permutation test, hap4 is the only

haplotype that remained statistically significantly associated with

sporadic prostate cancer (P for permutation test 5 0.0069).

We also assessed whether prostatitis affected the association

be-tween ELAC2 genotypes and the risk of prostate cancer. Prostatitis

status did not modify the association between hap1 and prostate

can-cer (one variant carrier of hap1 versus non-carrier: OR 5 5.45, 95%

CI 5 1.60–18.6, P interaction 5 0.12) among younger men (age



60) (data not shown). Results were also not statistically significant

among older men (age . 60).

Discussion

For main effect, none of the tagging SNPs was associated with the risk

of prostate cancer. In contrast, hap4 was associated with an increased

risk of prostate cancer. Hap1 and hap4 were related to increased and

hap2 to decreased risk of aggressive prostate cancer. This is the first

demonstration that common SNPs and haplotypes in ELAC2 are

as-sociated with aggressive prostate cancer. A previous study (22) found

that a very rare 8-SNP haplotype (frequency, case: 0.022, controls: 0)

was associated with ‘familial early-onset’ prostate cancer. Since the

Table IV. ORs between ELAC2 haplotypes and the risk of prostate cancer

Haplotype Prevalence among

controls, % (95% CI)

0 copies 1 copy 2 copies P-value

Case/control OR Case/control OR (95% CI) Case/control OR (95% CI) All prostate cancer (global test P 5 0.18)

Hap1: TACGCAA 26.2 (23.8–28.6) 330/359 1.00 277/250 1.21 (0.96–1.53) 52/47 1.20 (0.79–1.84) 0.24 Hap2: TGTACAA 22.8 (20.5 –25.1) 396/386 1.00 225/239 0.92 (0.73–1.16) 38/31 1.21 (0.73–1.99) 0.53 Hap3: TGTGTGA 12.2 (10.4–14.0) 520/506 1.00 133/142 0.90 (0.69–1.18) 6/8 0.73 (0.25–2.11) 0.65 Hap4: CGCGTAG 8.9 (7.4–10.5) 512/542 1.00 142/109 1.39 (1.05–1.85) 5/5 0.96 (0.26–3.51) 0.07 Hap5: TGCGCAA 8.4 (6.9–9.9) 556/550 1.00 101/101 0.98 (0.72–1.35) 2/5 0.43 (0.08–2.34) 0.59 Hap6: TGTGCAA 5.0 (3.7–6.1) 613/596 1.00 44/55 0.77 (0.50–1.18) 2/5 0.39 (0.08–2.04) 0.25 Others 16.5

Sporadic prostate cancer (global test P 5 0.03)

Hap1: TACGCAA 26.2 (23.8–28.6) 321/354 1.00 271/245 1.25 (0.98–1.58) 52/47 1.23 (0.80–1.89) 0.16 Hap2: TGTACAA 22.9 (20.6–25.2) 388/379 1.00 219/236 0.90 (0.71–1.14) 37/31 1.18 (0.71–1.94) 0.50 Hap3: TGTGTGA 11.9 (10.2–13.7) 510/500 1.00 129/139 0.90 (0.68–1.19) 5/7 0.71 (0.22–2.25) 0.65 Hap4: CGCGTAG 9.0 (7.4–10.5) 498/533 1.00 141/108 1.41 (1.06–1.87) 5/5 0.97 (0.26–3.54) 0.06 Hap5: TGCGCAA 8.5 (7.0–10.0) 544/540 1.00 98/101 0.97 (0.71–1.33) 2/5 0.42 (0.08–2.33) 0.58 Others 21.5

_{P-value was for testing the null hypothesis: OR}

1 copy5 OR2 copies5 1.

Table III. SNP analysis by ELAC2 genotypes

SNP 0 copies 1 copy 2 copies P-value

Case/control OR Case/control OR (95% CI) Case/control OR (95% CI)

All prostate cancer

Snp1 428/447 1.00 198/186 1.11 (0.87–1.41) 21/12 1.82 (0.89–3.75) 0.20 Snp2 288/314 1.00 293/272 1.18 (0.94–1.49) 64/59 1.19 (0.80–1.75) 0.33 Snp3 179/161 1.00 328/330 0.89 (0.69–1.16) 133/146 0.82 (0.60–1.13) 0.46 Snp4 376/370 1.00 223/237 0.93 (0.73–1.17) 44/36 1.21 (0.76–1.92) 0.52 Snp5 308/296 1.00 263/280 0.90 (0.71–1.13) 72/68 1.01 (0.70–1.46) 0.63 Snp6 480/472 1.00 152/157 0.95 (0.73–1.22) 9/10 0.89 (0.36–2.22) 0.89 Snp8 472/487 1.00 164/149 1.13 (0.88–1.46) 9/8 1.16 (0.44–3.03) 0.63

Sporadic prostate cancer

Snp1 418/440 1.00 193/183 1.10 (0.87–1.41) 21/12 1.84 (0.89–3.78) 0.20 Snp2 280/312 1.00 287/265 1.21 (0.96–1.53) 63/58 1.21 (0.82–1.79) 0.23 Snp3 178/159 1.00 320/325 0.88 (0.68–1.14) 127/143 0.80 (0.58–1.10) 0.36 Snp4 369/363 1.00 216/234 0.91 (0.72–1.15) 43/36 1.18 (0.74–1.88) 0.49 Snp5 301/293 1.00 258/274 0.91 (0.72–1.15) 69/67 1.00 (0.69–1.45) 0.73 Snp6 471/466 1.00 147/154 0.94 (0.72–1.22) 8/9 0.91 (0.35–2.38) 0.87 Snp8 458/478 1.00 163/148 1.14 (0.88–1.48) 9/8 1.16 (0.44–3.04) 0.59

_{P-value was for testing the null hypothesis: OR}

outcomes selected by Camp et al. (22) (familial prostate cancer) and

our study (.98% were sporadic prostate cancer) were different, our

results were not comparable. The results changed very little after we

restricted all cases to sporadic prostate cancer.

Two non-synonymous SNPs, Ser217Leu and Ala541Thr,

corre-sponding to snp5 and snp7 in our study, have been widely explored

previously. In our study, Ala541Thr was too rare to support statistical

analyses. Ala541 of ELAC2 is located directly beside the histidine

motif (1) and is important to 3#-tRNAse catalytic activity for

remov-ing a 3# trailer from precursor tRNA (36). This may explain its

association with prostate cancer in some studies (6,7,9,15). A

meta-analysis (37) showed that Thr541 carriers accounted for 2% of

pros-tate cancer in the general population. Thr541 is a very rare allele in

our study population (Table I), which might be a result of genotyping

error. However, Thr541 is in strong linkage disequilibrium with

Leu217 (9–12,15,20), which was not associated with the risk of

pros-tate cancer. Therefore, exclusion of Ala541Thr from haplotype

anal-yses had a negligible effect on our results. Fewer than a quarter of

previous studies found that either Ser217Leu or Ala541Thr was

as-sociated with the risk of prostate cancer. Because of the null findings

in the majority of studies on these two SNPs, we included more

common tagging SNPs and performed haplotype analyses to capture

more genetic information than that provided by individual SNPs.

Our study does have some advantages. We restricted subjects to

Caucasians, and thus population stratification is not a concern. Large

sample size, high concordance rate in genotyping QC samples, few

self-reported cases (3%) and high concordance between self-reported

and medical record-confirmed cases (90%) increased the reliability of

our findings. However, the low frequency of Thr541 in this population

as compared with other Caucasian populations may be a result of

sample variation across Caucasian populations. The tagging SNP

ap-proach, using a small set of representative SNPs, is a cost-effective

approach for haplotype analyses.

A study in Caenorhabditis elegans showed that reduction of the

gene activity of hoe-1 (the homolog of ELAC2) resulted from

activa-tion of mutaactiva-tion in ras and led to subsequent reducactiva-tion of germline

proliferation (3). In addition, the amino acid sequence of ELAC2 is

similar to some proteins (1,4) with known functions, as described in

the Introduction. This suggests that the sequence variants in ELAC2

may either indirectly deactivate the mutation in ras gene, which leads

to inhibition of germline proliferation, or through messenger RNA

modification and then the formation of subsequent carcinogenesis in

the prostate. We did not observe a statistically significant association

between genetic variations in ELAC2 and the risk of prostate cancer.

However, ELAC2 common SNPs and haplotypes were statistically

significantly related to aggressive prostate cancer. More experimental

and association studies are warranted to explain the role of ELAC2 in

prostate carcinogenesis.

Funding

National Institutes of Health (UO1 CA98233, CA55075).

Acknowledgements

The authors are grateful to Pati Soule and Ana-Tereza Andrade for DNA sample extraction and to the Partners High-Throughput Genotyping Center (Dr David Kwiatkowski, Alison Brown and Maura Regan) for genotyping. Conflict of Interest Statement: None declared.

Table V. ELAC2 SNP and haplotypes and risk of aggressive and non-aggressive prostate cancer

Non-carriers Carriers P-value

Cases/controls OR Cases/controls OR (95% CI)

SNP

Aggressive prostate cancer

Snp1 158/447 1.00 78/198 1.10 (0.80–1.52) 0.55 Snp2 94/314 1.00 141/331 1.43 (1.06–1.93) 0.02 Snp3 76/161 1.00 157/476 0.69 (0.50–0.95) 0.03 Snp4 152/370 1.00 83/273 0.74 (0.54–1.01) 0.05 Snp5 112/296 1.00 122/348 0.92 (0.68–1.24) 0.57 Snp6 174/472 1.00 58/167 0.93 (0.66–1.32) 0.69 Snp8 172/487 1.00 63/157 1.13 (0.80–1.58) 0.50

Non-aggressive prostate cancer

Snp1 270/447 1.00 141/198 1.18 (0.91–1.54) 0.21 Snp2 194/314 1.00 216/331 1.06 (0.83–1.36) 0.65 Snp3 103/161 1.00 304/476 1.00 (0.75–1.34) 0.98 Snp4 224/370 1.00 184/273 1.11 (0.87–1.43) 0.40 Snp5 196/296 1.00 213/348 0.92 (0.72–1.19) 0.53 Snp6 306/472 1.00 103/167 0.95 (0.72–1.26) 0.73 Snp8 300/487 1.00 110/157 1.14 (0.86–1.51) 0.37 Haplotype

Aggressive prostate cancer (global test P 5 0.11)

Hap1: TACGCAA 109/358 1.00 131/298 1.47 (1.08–1.99) 0.01 Hap2: TGTACAA 183/542 1.00 80/269 0.72 (0.52–0.98) 0.04 Hap3: TGTGTGA 160/387 1.00 51/151 0.91 (0.63–1.31) 0.60 Hap4: CGCGTAG 169/383 1.00 57/114 1.51 (1.04–2.18) 0.03 Hap5: TGCGCAA 197/550 1.00 43/106 1.14 (0.76–1.72) 0.52 Hap6: TGTGCAA 189/505 1.00 14/60 0.59 (0.32–1.11) 0.09

Non-aggressive prostate cancer (global test P 5 0.27)

Hap1: TACGCAA 221/358 1.00 198/298 1.08 (0.84–1.39) 0.55 Hap2: TGTACAA 329/542 1.00 183/269 1.11 (0.87–1.43) 0.40 Hap3: TGTGTGA 236/387 1.00 88/151 0.89 (0.65–1.20) 0.44 Hap4: CGCGTAG 257/383 1.00 90/114 1.31 (0.96–1.80) 0.09 Hap5: TGCGCAA 359/550 1.00 60/106 0.85 (0.59–1.22) 0.38 Hap6: TGTGCAA 331/505 1.00 32/60 0.82 (0.52–1.30) 0.40

Aggressive prostate cancer was defined as stages T3b, T4, N1, M1 or death due to prostate cancer or Gleason sum7.

_{P-value was for testing the null hypothesis: OR}

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