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. 2024 May 20;110(12):7840–7851. doi: 10.1097/JS9.0000000000001557

Epidemiological investigation of sex hormones and their metabolism-related gene single nucleotide polymorphisms in patients with benign prostatic hyperplasia complicated with late-onset hypogonadism: a retrospective cohort study

Bengen Li 1, Congcong Chen 1, Zongping Chen 1,*, Qixu Ren 1, Ningrui Pan 1, Xu He 1, Min Wang 1, Xiaoyu Ai 1, Youzhuang Zhong 1, You Xiang 1, Bo Chen 1, Jiawei Sun 1, Yu Cao 1, Zhengdong Ouyang 1
PMCID: PMC11634076  PMID: 39806744

Abstract

Background:

Benign prostatic hyperplasia (BPH) is a common disease in middle-aged and elderly men, and its etiology is not completely clear. Late-onset hypogonadism (LOH) is a relatively common disease in the aging process of men. BPH is often accompanied by varying degrees of LOH, and the pathogenesis and progression of the two diseases are related. Sex hormone metabolism-related genes affect sex hormone metabolism, to determine androgen, estrogen, androgen/estrogen ratio, and their single nucleotide polymorphisms (SNPs) are common in the population. The relationship between BPH combined with LOH (LOH-BPH) and SNPs in genes related to sex hormone metabolism is still unclear. In this study, the authors hope to clarify the relationship between them through epidemiological investigation.

Objective:

To investigate the association between LOH-BPH and SNPs of sex hormone metabolism-related genes.

Materials and methods:

A total of 821 middle-aged and elderly men from 1 January 2017 to 31 December 2022, were retrospectively analyzed. According to the diagnosis of LOH-BPH, the patients were divided into LOH-BPH group and non-LOH-BPH group, and the related parameters of the two groups were compared. The parameters included age, total testosterone (tT), estradiol (E2), testosterone/estradiol ratio (T/E), dihydrotestosterone (DHT), sex hormone-binding globulin (SHBG), parameters associated with metabolic syndrome, parameters related to BPH, the International Index of Erectile Function 5 (IIEF-5) and erectile dysfunction (ED), and SNPs of genes related to sex hormone metabolism.

Results:

Sixty-eight participants were excluded from this study, and 753 eventually completed the study. ED accounted for 48.21%, LOH-BPH accounted for 41.30%, and non-LOH-BPH accounted for 58.70%. tT decreased with age and was negatively correlated with age (r=−0.68, P<0.0001). E2 increased with age and was positively correlated with age (r=0.61, P=0.032). T/E decreased with age and was negatively correlated with age (r=−0.71, P<0.0001). After adjusting for age, LOH-BPH is significantly correlated with tT (r=−0.754, OR=0.071, 95% CI: 0.0048–0.105, P<0.0001), E2 (r=0.765, OR=3.855, 95% CI: 1.828–5.833, P<0.0001), T/E (r=−0.751, OR=0.000, 95% CI: 0.000–0.000, P<0.0001) and ED (r=0.973, OR=5.02, 95% CI: 4.898–6.578, P=0.001). At the same time, the AA genotype of rs1843090 (r=−0.613, OR=0.052, 95% CI: 0.006–0.44, P=0.007), the CC genotype of rs2279357 (r=0.636, OR=20.963, 95% CI: 2.268–93.793, P=0.004), the GG genotype of rs743572 (r=0.681, OR=7.642, 95% CI: 5.005–11.668, P<0.0001), the AA genotype of rs712221 (r=−0.012, OR=0.468, 95% CI: 0.220–0.881, P=0.018), and the TT genotype of rs700518 (r=0.699, OR=26.04, 95% CI: 16.142–42.008, P<0.0001) were significantly associated with LOH-BPH.

Conclusions:

The morbidity of LOH-BPH can be associated with SNPs of genes related to sex hormone metabolism.

Keywords: benign prostatic hyperplasia, late-onset hypogonadism, sex hormone, single nucleotide polymorphisms

Introduction

Highlights

  • LOH-BPH can be predicted by single nucleotide polymorphisms of sex hormone metabolism-related genes.

  • The AA genotype of rs1843090 and rs712221 can be a protective factor for LOH-BPH.

  • The CC, GG, TT genotype of rs2279357, rs743572, rs700518 can be a risk factor for LOH-BPH.

  • The imbalance between androgen and estrogen can be the main mechanism of LOH-BPH.

Benign prostatic hyperplasia (BPH) is the most common benign neoplasm of aging men and is present in ~8% of men in the fourth decade of life but up to 90% of men in the ninth decade13. BPH can easily cause lower urinary tract symptoms, which affects the quality of life of patients, and its etiology is not completely clear13. Most scholars believe that the occurrence of BPH is related to the imbalance of sex hormone metabolism, mainly manifested in the increase of serum E2 to tT ratio, and estrogen directly or indirectly affects the growth and differentiation of the prostate46.

The term late-onset hypogonadism (LOH) was coined in 2002 and defined as a disease entity of clinical and biochemical syndrome associated with advancing age, characterized by symptoms and a deficiency in serum testosterone, and its reported prevalence varies from 2.1 to 12.3%713. LOH was classified as a combined primary and secondary hypogonadism since the endocrine capacity of the testes and the pituitary is impaired. Symptoms of LOH include loss of libido, erectile dysfunction, loss of muscle mass, increased body fat, anemia, osteoporosis, depressed mood, decreased vitality, sweating, and hot flushes713.

BPH combined with LOH (LOH-BPH) is common in clinical practice1416. In our previous epidemiological investigation, it was found that the increase of estrogen and the decrease of androgen-to-estrogen ratio was high-risk factors for BPH, moreover, it was associated with rs700518 and rs743572 single nucleotide polymorphisms (SNP)17. The relationship between LOH-BPH and sex hormones and SNP of genes related to sex hormone metabolism is not well reported1821.

Therefore, in this study, we will investigate whether there is a correlation between SNP of sex hormone metabolism-related genes in BPH patients with or without LOH, to provide a basis for the clinical implementation of the same treatment for different diseases, different treatment for the same disease, and precision medicine for LOH-BPH.

Materials and methods

Patients

This study was a retrospective cohort study. The present study was approved by the Institutional Review Board of Beijing Shijitan Hospital in December 2017 and the Ethics Committee of the Affiliated Hospital of Zunyi Medical University in March 2019 and 2022. All procedures performed in the present study involving human participants were in accordance with the ethical standards of the Institutional Committee and with the 1964 Helsinki Declaration and its later amendments or similar ethical standards. The work has been reported in line with the strengthening the reporting of cohort, cross-sectional, and case–control studies in surgery (STROCSS) criteria (Supplemental Digital Content 1, http://links.lww.com/JS9/C579) and in its references22. The study was registered with the Chinese Clinical Trials Registry, and its registration ID: ChiCTR2200057632. From October 2017 to March 2022, 821, community elderly men (age, 52–86 years) residents who had an international prostate symptom score (IPSS), international index of erectile function 5 (IIEF-5), aging male symptoms (AMS) questionnaire evaluations, and had consecutively participated in prostate examinations at Beijing Shijitan Hospital and Affiliated Hospital of Zunyi Medical University were recruited into this study.

Inclusion criteria: (i) middle-aged and elderly men in the community; (ii) completes the IPSS score and AMS questionnaire; (iii) participated in routine physical examination and the prostate examination; (iv) completed the detection of sex hormones and SNPs of genes related to sex hormone metabolism; (v) completed the blood prostate-specific antigen (PSA) detection, and routine biochemical index detection.

Exclusion criteria: (i) when a PSA greater than 4 ng/ml were encountered, a prostate biopsy was required provided that the criteria for prostate biopsy were met, and the diagnosis of prostate cancer was excluded before participants could be recruited into this study; (ii) to minimize latent confounding factors and bias, the participants who had a history of prostate or urethral surgery, those who had been diagnosed with urologic diseases, including prostatitis, epididymitis, orchitis, testicular tumor, testicular tuberculosis, testicular trauma, testicular absence, cryptorchidism, urethral stricture, urologic infections, malignancy, or neurogenic bladder; (iii) and those who had been taking medicine, including anticholinergics, 5a-reductase inhibitors, phosphodiesterase-5 inhibitors, and hormone replacement therapy were excluded from the study.

Blood specimen collection, detection, and cryopreservation

All the blood specimens were obtained from the subjects in the morning after an overnight fast. The serum PSA levels were determine to use radioimmunoassay. The serum total testosterone (tT), estradiol (E2), dihydrotestosterone (DHT), and androgen-binding globulin (SHBG) was determined by enzyme-linked immunosorbent assay (ELISA) at Beijing Huada Protein Research and Development Center Co., Ltd. Molecular testing laboratory (Beijing Protein Innovation) and the DRG Elisa kits were used. The T/E ratio was calculated using serum total testosterone divided by estradiol. The biochemical analyses, including fasting plasma glucose (FPG), triglycerides (TG), HDL-C, and total cholesterol (TC), were determined by fully automatic biochemical analyzer. The genomic DNA was extracted from peripheral blood (cryopreserved in advance) using standard phenol/chloroform method.

SNP selection and genotyping

A total of 29 SNP in 9 genes related to sex hormone metabolism was detected by matrix assisted laser resolution ionization flight time mass spectrometry (MALDI-TOF-MS), including the following: AR (rs1204038, rs1204039, rs1204040, rs2255702); ESR-α(rs2234693, rs712221, rs532010); CYP17A1(rs4919686, rs3781287, rs743572), CYP1B1(rs10012, rs1056827, rs1056836); SRD5A2 (rs523349, rs632148, rs9332975); SHBG (rs6259, rs2908809, rs858518, rs858521); CYP11A1 (rs2073475, rs2279357, rs7173655, rs1843090); CYP19A1 (rs700518, rs4646); INSL3 (rs6523, rs1003887, rs8112876). These SNPs were selected by Gene Bank database (http://www.ncbi.nlm.nih.gov/SNP) for analysis. Peripheral blood samples from each subject were stored in ethylenediaminetetraacetic acid in blood sampling tubes at −20°C. Genomic DNA was extracted using a standard phenol/chloroform method. PCR amplified target sequences were shown in Appendix Table (Supplemental Digital Content 2, http://links.lww.com/JS9/C580). The reaction contained 20 ng (2 μl) of genomic DNA. Universal reaction condition were detailed in reference17. MALDI-TOF-MS was used for detection, and Typer 4.0 software was used detecting the mass spectra and the target sites of the genotypes for each sample were read according to the mass spectra. Assay design, DNA isolation, PCR amplification, direct sequencing, and analysis was performed with the iPLEX MassARRAY platform (Sequenom)23,24.

Diagnosis of BPH

Medical histories were collected using a standardized structured questionnaire. The Chinese version of IPSS was administered to the subjects for evaluation of urinary symptoms. Prostate volume (PV) was measured and calculated and maximum urinary flow rate (Qmax) was determined (see reference17 for details). All subjects underwent digital examinations of the rectum to exclude palpable prostatic nodules. The reference value of PSA in BPH should meet the following requirements: (i) PSA less than 4 ng/ml; (ii) When PSA is in the gray zone range of 4–10 ng/ml, the ratio of free PSA to total PSA should be greater than 0.16, PSA density should be less than 0.15, PSA velocity should be less than 0.75 ng/ml.y, otherwise prostate biopsy should be performed to exclude prostate cancer; (iii) When PSA was more than 10 ng/ml, prostate biopsy was required to exclude prostate cancer before enrollment in this study. According to results from the placebo-arm study of the Medical Therapy of Prostatic Symptoms Study (MTOPS), TPV >20 cm3 were defined as prostatomegaly25.

Diagnosis of LOH

The diagnosis of LOH was based on the criteria for tT levels <12 nmol/l when accompanied by relevant symptoms, especially sexual ones (low sexual desire, reduced spontaneous erections, and erectile dysfunction)9,26,27. Psychological, somatic, and sexual symptoms were assessed for each participant using the AMS questionnaire. And the AMS scale includes 17 items to assess symptoms that may be associated with androgen decline in aging males. Each question is answered on a scale from 1 to 5. The 17 items comprise three subscale: psychological, somatic, and sexual symptoms – all of which were dichotomized into symptomatic (response 3–5) and asymptomatic (response 1–2) categories28.

Definition of LOH-BPH

It meets the diagnostic criteria of BPH and LOH. Additionally, LOH and BPH coexist in the same patient, which is called LOH-BPH9,2527.

Definition of erectile dysfunction (ED)

An IIEF-5 score between 1 and 21 was defined as ED. An IIEF-5 score between 22 and 25 was defined as normal sexual function.

Definition of MetS

MetS was diagnosed using the 2005 National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criterion for Asian Americans (Grundy et al., 2005). The modi-fied NCEP-ATP III defined MetS as the simultaneous occurrence of at least three of the following five risk factors: (i) waist circumference ≥90 cm, (ii) triglycerides ≥1.70 mmol/l or drug treatment for elevated triglycerides, (iii) HDLC <1.04 mmol/l or medicine treatment for reduced HDL-C, (iv) blood pressure ≥130/85 mmHg or antihypertensive drug treatment with a history of hypertension, and (v) FPG ≥6.1 mmol/l, 2-h postprandial blood glucose (2hPG) ≥7.8 mmol/l or drug treatments for elevated glucose.

Cohort grouping and clinical data extraction

Among all participants with BPH, the cohort was divided into two groups according to the presence or absence of LOH: LOH-BPH group and Non-LOH-BPH group. The following parameters was obtained from each participant: age, the body height, body weight, waist circumference (WC), blood pressure includes systolic and diastolic blood pressure, PV, Qmax, tT, E2, DHT, SHBG, FPG, TG, HDL-C, PSA, and 29 SNPs in nine genes related to sex hormone metabolism, including the following: AR (rs1204038, rs1204039, rs1204040, rs2255702); ESR-α(rs2234693, rs712221, rs532010); CYP17A1(rs4919686, rs3781287, rs743572), CYP1B1(rs10012, rs1056827, rs1056836); SRD5A2 (rs523349, rs632148, rs9332975); SHBG (rs6259, rs2908809, rs858518, rs858521); CYP11A1 (rs2073475, rs2279357, rs7173655, rs1843090); CYP19A1 (rs700518, rs4646); INSL3 (rs6523, rs1003887, rs8112876), were genotyped. Whether BPH was diagnosed, whether LOH was diagnosed, whether ED was diagnosed, whether LOH-BPH was diagnosed. The parameters of the extracted data are detailed in Figure 1.

Figure 1.

Figure 1

Flow chart of the study design. AMS, aging male symptoms; BPH, benign prostatic hyperplasia; DHT, dihydrotestosterone; ED, erectile dysfunction; E2, estradiol; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; IIEF-5, international index of erectile function 5; IPSS, international prostate symptom score; LOH, late-onset hypogonadism; MetS, metabolic syndrome; PSA, prostate-specific antigen; PV, prostate volume; Qmax, maximum urinary flow rate; SHBG, sex hormone-binding globulin; SNP, single nucleotide polymorphisms; TG, Triglycerides; tT, total testosterone; WC, Waist circumference.

Statistical analyses

Statistical analyses were performed using Statistical Package for the Social Sciences (IBM Corp.) version 29.0. Selected characteristics are expressed as mean and SD (mean±SD), as well as percentages (%) for comparisons between LOH-BPH and non-LOH-BPH groups. Student’s t-test and one-way analysis of variance (one-way ANOVA) was used for continuous variables. Allelic and genotypic associations were evaluated by χ 2 tests. Correlation coefficients (r) were evaluated by the correlation analysis. Multivariate-adjusted odds ratios (ORs) and 95% CIs were simultaneously estimated by logistic regression analyses. Differences are considered statistically significant when P<0.05.

Theory/calculation

The theory of this study was that SNPs of sex hormone metabolism-related genes affect the levels of sex hormones, resulting in sex hormone imbalance and resulting in the occurrence of LOH-BPH (See Fig. 2 for details).

Figure 2.

Figure 2

Schematic representation of possible mechanisms by which SNPs in genes involved in sex hormone metabolism affect sex hormone levels leading to LOH-BPH. AR, androgen receptor; BPH, benign prostatic hyperplasia; CPY, cytochrome C P450 enzyme; DHT, dihydrotestosterone; ER, estrogen receptor; FE, free estrogen; FT, free testosterone; INSL3, insulin-like growth factor-3; LOH, late-onset hypogonadism; SHBG, sex hormone-binding globulin; SRD5A2, Steroid 5-alpha reductase 2; SF-1, steroidogenic factor-1; StAR, steroidogenic acute regulatory proteins; SNP, single nucleotide polymorphisms; TT, total testosterone; TE, total estrogen.

Results

Patient characteristics

In this study, 68 participants were excluded, and 753 eventually accomplished the study. The principal characteristics of the study population are listed in Table 1. The age ranged from 52 to 86 years, tT ranged from 0.21 ng/ml to 32.50 ng/ml, E2 ranged from 12.09 pg/ml to 151.41 ng/ml, T/E ranged from 0.01 ng/pg to 0.89 ng/ml, IIEF-5 ranged from 8 to 24, DHT ranged from 82.62 pg/ml to 2761.41 pg/ml, PSA ranged from 0.03 ng/ml to 9.51 ng/ml, ED, hypertension, hypertriglyceridemia, type 2 diabetes mellitus, obesity, MetS accounted for 48.21, 38.38, 26.83, 38.91, 9.69, 28.55%, respectively. LOH-BPH accounted for 41.30%, and non-LOH-BPH accounted for 58.70%. Smoking, drinking, high-fat high-calorie diet and lack of exercise accounted for 45.15, 48.87, 32.14, and 66.03%, respectively. 69.59% of the patients lived in cities, and 30.41% lived in rural areas. Patients with higher education, secondary education, and lower education accounted for 64.94, 14.21, and 20.85%, respectively.

Table 1.

Baseline characteristics of the participants (n=753).

Variables Mean SD Min Max
Age, years 70.20 8.00 52 86
tT, ng/ml 5.11 2.22 0.21 32.50
E2, pg/ml 40.81 13.71 12.09 151.41
T/E, ng/pg 0.13 0.08 0.01 0.89
IIEF-5 16.75 4.34 8 24
DHT, pg/ml 394.09 192.97 82.62 2761.41
SHBG, nmol/l 94.76 45.51 24.83 207.93
PSA, ng/ml 1.62 1.52 0.03 9.51
FPG, mmol/l 5.53 1.29 3.62 14.52
IPSS 20.35 5.93 7 34
Qmax, ml/sec 16.72 5.91 3.7 39.2
PV, ml 27.86 6.75 20.4 50.9
BMI, kg/m2 25.75 3.01 17.6 38.2
WC, cm 90.59 9.19 64 119
TG, mmol/l 1.79 0.99 0.38 8.76
HDL-C, mmol/l 2.13 1.06 0.55 5.20
Addiction of tobacco, % 45.15 (340/753)
Addiction of alcohol, % 48.87 (368/753)
Diet information
 High-fat high-calorie, % 32.14 (242/753)
 Regular, % 67.86 (511/753)
Physical exercise situation
 Keep exercising, % 33.07 (249/753)
 Lack of exercise, % 66.03 (504/753)
Dwelling environment
 Living in city, % 69.59 (524/753)
 Living in the country, % 30.41 (229/753)
Education background
 ≤6 years, % 20.85 (157/753)
 7–12 years, % 14.21 (107/753)
 ≥13 years, % 64.94 (489/753)
Hypertension, % 38.38 (289/753)
Hypertriglyceridemia, % 26.83 (202/753)
Type 2 diabetes mellitus, % 38.91 (293/753)
Obesity, % 9.69 (73/753)
MetS, % 28.55 (215/753)
ED, % 48.21 (363/753)
Non-LOH-BPH, % 58.70(442/753)
LOH-BPH, % 41.30(311/753)

BPH, benign prostatic hyperplasia; DHT, dihydrotestosterone; E2, estradiol; ED, erectile dysfunction; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; IIEF-5, international index of erectile function 5; IPSS, international prostate symptom score; LOH, late-onset hypogonadism; MetS, metabolic syndrome; PSA, prostate-specific antigen; PV, prostate volume; Qmax, maximum urinary flow rate; SHBG, sex hormone-binding globulin; TG, triglycerides; tT, total testosterone; WC, waist circumference.

Changes of sex hormones (tT, E2, T/E) with age in patients with BPH with or without LOH

As shown in Figure 3, a total of 753 BPH patients with or without LOH was included in this study. We stratified the age by 5 years and analyzed the changes of sex hormones with age. The results showed that tT decreased with age and was negatively correlated with age (r=−0.68, P<0.0001). E2 increased with age and was positively correlated with age (r=0.61, P=0.032). T/E decreased with age and was negatively correlated with age (r=0.71, P<0.0001).

Figure 3.

Figure 3

Changes of sex hormones (tT, E2, T/E) with age in patients with BPH with or without LOH. r stands for correlation coefficient for linear correlation analysis; A: P<0.0001; B: P=0.032; C: P<0.0001; BPH, benign prostatic hyperplasia; E2, estradiol; LOH, late-onset hypogonadism; tT, total testosterone; T/E, the ratio of total testosterone to estradiol.

Association between the disease of LOH-BPH and the related parameters of sex hormone

As shown in Table 2, LOH-BPH is significantly correlated with age (r=0.622, OR=2.834, 95% CI: 1.416–4.948, P=0.023), tT (r=−0.754, OR=0.071, 95% CI: 0.0048–0.105, P<0.0001), E2 (r=0.765, OR=3.855, 95% CI: 1.828–5.833, P<0.0001), T/E (r=−0.675, OR=0.000, 95% CI: 0.000–0.000, P<0.0001), smoking (r=0.758, OR=1.896, 95% CI: 1.241–2.898, P=0.003), drinking (r=0.833, OR=1.894, 95% CI: 1.233–2.908, P=0.004), BMI (r=0.742, OR=1.991, 95% CI: 1.103–3.267, P=0.038), WC (r=0.734, OR=1.985, 95% CI: 1.127–3.391, P=0.036), type 2 diabetes mellitus (r=0.686, OR=3.146, 95% CI: 1.212–5.226, P<0.0001), Obesity (r=0.672, OR=2.126, 95% CI: 1.104–4.095, P=0.024), MetS (r=0.776, OR=158.59, 95% CI: 101.887–257.505, P<0.0001), and ED (r=0.973, OR=5.02, 95% CI: 4.898–6.578, P=0.001). According to the negative correlation coefficient r, OR value less than 1, and 95% CI less than 1, it can be judged that LOH-BPH is negatively correlated with tT, and T/E, and the decreased tT and T/E value can be a risk factor for LOH-BPH. On the contrary, according to the positive correlation coefficient r, an OR value greater than 1, and a 95% CI greater than 1, it can be judged that they can be risk factors for LOH-BPH for age, smoking, drinking, ED, MetS, obesity, type 2 diabetes, the increased BMI and WC, and the elevated E2.

Table 2.

Association between the disease of LOH-BPH and the related parameters of sex hormone, BPH, and MetS (n=753).

Parameters Number LOH-BPH a P b r OR cB d P 95% CI
Age, year
e(–) 442 69.13±8.37
f(+) 311 70.95±7.65 0.002 0.622 2.834 0.616 0.023 1.416–4.948
tT, ng/ml
e(–) 442 5.66±2.46
f(+) 311 3.30±0.73 <0.0001 −0.754 0.071 −2.643 <0.0001 0.0048–0.105
E2, pg/ml
e(–) 442 38.11±14.12
f(+) 311 44.64±12.14 <0.0001 0.765 3.855 3.156 <0.0001 1.828–5.883
T/E, ng/pg
e(–) 442 0.17±0.09
f(+) 311 0.08±0.03 <0.0001 −0.675 0.000 −96.428 <0.0001 0.000–0.000
SHBG, nmol/l
e(–) 442 87.47±34.81
f(+) 311 55.87±27.21 <0.0001 −0.435 0.996 −0.004 0.689 0.978–1.015
DHT, pg/ml
e(–) 442 427.24±261.23
f(+) 311 331.22±142.59 0.001 −0.117 0.997 −0.003 0.057 0.995-1
ED
e(–) 52 6.91%
f(+) 311 41.30% <0.0001 0.973 5.02 24.64 0.001 4.898–6.578
PSA, ng/ml
e(–) 442 1.64±1.58
f(+) 311 1.61±1.42 0.795 −0.009 1.014 0.014 0.831 0.889–1.157
FPG, mmol/l
e(–) 442 5.62±1.32
f(+) 311 6.50±1.65 <0.0001 0.726 1.209 0.009 0.955 0.784–1.378
IPSS
e(–) 442 20.55±5.99
f(+) 311 20.01±5.83 0.268 −0.04 0.986 −0.014 0.408 0.952–1.022
Qmax, ml/sec
e(–) 442 16.77±5.79
f(+) 311 16.66±6.08 0.811 −0.009 1.005 0.005 0.811 0.964–1.041
PV, ml
e(–) 442 28.29±7.10
f(+) 311 27.26±6.17 0.038 −0.075 0.996 −0.004 0.811 0.966–1.028
BMI, kg/m2
e(–) 442 22.43±2.70
f(+) 311 25.99±3.14 <0.0001 0.742 1.991 1.127 0.038 1.103–3.267
WC, cm
e(–) 442 84.65±7.56
f(+) 311 89.23±8.97 <0.0001 0.734 1.985 1.115 0.036 1.127–3.391
TG, mmol/l
e(–) 442 1.17±0.68
f(+) 311 1.83±1.13 <0.0001 0.659 0.817 −0.202 0.235 0.586–1.140
HDL-C, mmol/l
e(–) 442 2.67±0.79
f(+) 311 1.96±1.12 <0.0001 −0.348 0.986 −0.015 0.942 0.668–1.455
Addiction of tobacco
e(–) 155 20.58%
f(+) 185 24.57% <0.0001 0.758 1.896 0.640 0.003 1.241–2.898
Addiction of alcohol
e(–) 185 24.57%
f(+) 183 24.30% <0.0001 0.833 1.894 0.639 0.004 1.233–2.908
Diet information
 High-fat high-calorie, % 242 40.50% (98/242) 0.758 0.011 0.139 −1.976 0.082 0.015–1.289
 Regular, % 511 41.68% (213/511)
Physical exercise situation
 Keep exercising, % 504 40.87% (206/504)
 Lack of exercise, % 249 42.17% (105/249) 0.734 0.012 0.085 −2.460 0.022 0.01–0.675
Dwelling environment
 Living in city, % 524 42.18% (221/524) 0.462 0.027 0.808 −0.213 0.724 0.249–2.628
 Living in the country, % 229 39.30% (90/229)
Education background
 ≤6 years, % 107 43.93% (47/107)
 7–12 years, % 489 42.13% (206/489) 0.324 0.324 0.837 −0.136 0.718 0.416–1.830
 ≥13 years, % 157 36.94% (58/157) 0.324 0.036 0.644 −0.440 0.355 0.253–1.638
Hypertension
e(-) 82 11.02%
f(+) 206 27.36% <0.0001 0.586 1.653 0.503 0.123 0.873–3.132
Hypertriglyceridemia
e(–) 43 5.71%
f(+) 159 21.12% <0.0001 0.560 0.751 0.286 0.509 0.322–1.754
Type 2 diabetes mellitus
e(–) 107 14.21%
f(+) 186 24.70% <0.0001 0.686 3.146 2.961 <0.0001 1.212–5.226
Obesity
e(–) 26 3.45%
f(+) 47 6.24% 0.021 0.672 2.126 1.564 0.024 1.104–4.095
MetS
e(–) 77 10.23%
f(+) 138 18.33% <0.0001 0.776 158.59 6.364 <0.0001 101.887–257.505
a

Analysis of variance;

b

On behalf of the correlation coefficient;

c

On behalf of the regression coefficient;

d

Binary logistic/Linear regression analysis;

e

On behalf of the Non-LOH-BPH;

f

On behalf of the LOH-BPH;

The boldface represents statistical significance (P<0.05).

BPH, benign prostatic hyperplasia; DHT, dihydrotestosterone; E2, estradiol; ED, erectile dysfunction; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; IPSS, international prostate symptom score; LOH, late-onset hypogonadism; MetS, metabolic syndrome; OR, odds ratio; PSA, prostate-specific antigen; PV, prostate volume; Qmax, maximum urinary flow rate; SHBG, sex hormone-binding globulin; TG, triglycerides; tT, total testosterone; WC, waist circumference.

The genotypes and allele distributions and association in LOH-BPH and Non-LOH-BPH group

As shown in Table 3, the AA genotype of rs1843090 (r=−0.613, OR=0.052, 95% CI: 0.006–0.44, P=0.007), the CC genotype of rs2279357 (r=0.636, OR=20.963, 95% CI: 2.268–93.793, P=0.004), the GG genotype of rs743572 (r=0.681, OR=7.642, 95% CI: 5.005–11.668, P<0.0001), the AA genotype of rs712221 (r=−0.012, OR=0.468, 95% CI: 0.220–0.881, P=0.018), and the TT genotype of rs700518 (r=0.699, OR=26.04, 95% CI: 16.142–42.008, P<0.0001) were significantly associated with LOH-BPH. According to the negative correlation coefficient r, OR value less than 1, and 95% CI less than 1, it can be judged that LOH-BPH is negatively correlated with AA genotype of rs1843090 and AA genotype of rs712221, and AA genotype of rs1843090 and AA genotype of rs712221 can be a protective factor for LOH-BPH. On the contrary, based on a positive correlation coefficient r, an OR value greater than 1, and a 95% CI greater than 1, it can be judged that LOH-BPH is positively correlated with CC genotype of rs2279357, GG genotype of rs743572, and TT genotype of rs700518, and CC genotype of rs2279357, GG genotype of rs743572, and TT genotype of rs700518 can be a risk factor for LOH-BPH.

Table 3.

The genotypes and allele distributions and association in LOH-BPH and Non-LOH-BPH group (n=753).

CHR SNP ID Genes Type Model LOH-BPH, n (%) Non-BPH-LOH, n (%) a P b r OR (95% CI) cB d P
2 rs10012 CYP1B1 0.221 −0.011
GG Allele 200 (64.31) 283 (64.03) 0.410 (0.051–2.448) −0.394 0.298
GC 97 (31.19) 171 (38.69)
CC 14 (4.50) 18 (4.08) 0.124 (0.006–6.447) −1.655 0.317
2 rs1056827 CYP1B1 0.294 −0.053
CC Allele 201 (64.63) 285 (64.48) 1.882 (0.275–12.726) −0.849 0.521
CA 97 (31.19) 138 (31.22)
AA 13 (4.18) 19 (4.30) 4.217 (0.096–282.662) −0.107 0.41
2 rs1056837 CYP1B1 0.312 −0.037
GG Allele 230 (73.95) 346 (78.28) 2.253 (0.810–2.21) −0.107 0.426
GA 77 (24.76) 87 (19.68)
AA 4 (1.29) 9 (2.04) 1.013 (0.014–2.314) −0.057 0.921
15 rs1843090 CYP11A1 0.037 −0.613
GG Allele 112 (34.66) 130 (29.41) 0.556 (0.233–1.046) −3.65 0.089
GA 133 (49.33) 202 (45.70)
AA 66 (16.01) 110 (24.89) 0.052 (0.006–0.44) −2.961 0.007
15 rs2073475 CYP11A1 0.589 −0.05
CC 106 (34.08) 129 (29.19) 0.559 (0.294–1.477) −0.287 0.06
CT 148 (47.59) 229 (51.81)
TT Allele 57 (18.33) 84 (19.00) 1.158 (0.505–2.119) −0.068 0.891
15 rs2279357 CYP11A1 0.041 0.636
CC Allele 113 (36.33) 128 (28.96) 20.963 (2.268–93.793) 3.043 0.004
CT 141 (45.34) 219 (49.55)
TT 57 (18.33) 95 (21.49) 8.002 (0.901–71.092) 2.08 0.062
15 rs7173655 CYP11A1 0.842 0.037
CC Allele 122 (39.23) 178 (40.27) 0.584 (0.288–1.133) 1.175 0.079
CT 146 (46.95) 205 (46.38)
TT 43 (13.82) 59 (13.35) 2.520 (1.054–6.315) 0.03 0.056
10 rs743572 CYP17A1 <0.0001 0.681
GG 192 (30.66) 128 (51.05) 7.642 (5.005–11.668) 2.504 <0.0001
GA 67 (46.64) 199 (26.71)
AA Allele 52 (22.70) 115 (15.60) 1.483 (0.841–4.797) 0.129 0.236
10 rs3781287 CYP17A1 0.573 0.033
GG 92 (29.58) 142 (32.13) 0.545 (0.293–1.013) −0.607 0.055
GT 142 (45.66) 188 (42.53)
TT Allele 77 (24.76) 112 (25.34) 1.233 (0.637–2.387) 0.209 0.534
10 rs4919686 CYP17A1 0.342 0.048
CC 7 (2.25) 10 (2.26) 0.495 (0.102–2.399) 0.142 0.382
CA 59 (18.97) 86 (19.46)
AA Allele 245 (78.78) 346 (78.28) 1.420 (0.792–2.545) 1.634 0.239
15 rs4646 CYP19A1 0.947 −0.034
CC Allele 158 (50.80) 222 (50.23) 0.754 (0.334–1.285) −0.16 0.281
CA 132 (42.45) 185 (41.85)
AA 21 (6.75) 35 (7.92) 1.013 (0.280–2.764) −0.398 0.964
15 rs700518 CYP19A1 <0.0001 0.699
CC 27 (8.68) 99 (22.40) 0.894 (0.532–1.951) 0.556 0.051
CT 64 (20.58) 227 (51.36)
TT Allele 220 (70.74) 116 (26.24) 26.04 (16.142–42.008) 3.745 <0.0001
6 rs532010 ESR1 0.025 0.015
GG 56 (18.01) 82 (18.55) 0.881 (0.333–2.280) 0.679 0.678
GA 134 (43.09) 198 (44.80)
AA Allele 121 (38.90) 162 (36.65) 0.547 (0.270–1.189) 0.167 0.121
6 rs712221 ESR1 0.008 −0.012
AA Allele 83 (26.69) 180 (40.72) 0.468 (0.220–0.881) −0.061 0.018
AT 157 (50.48) 179 (40.50)
TT 71 (22.83) 83 (18.78) 0.883 (0.533–1.462) −0.124 0.629
6 rs2234693 ESR1 0.063 0.034
CC 56 (18.01) 93 (21.04) 1.041 (0.386–2.751) 0.281 0.928
CT 158 (50.80) 211 (47.74)
TT Allele 97 (31.19) 138 (31.22) 1.492 (0.671–3.313) 0.346 0.316
17 rs6259 SHBG 0.974 0.008
GG Allele 210 (67.52) 300 (67.87) 0.869 (0.337–2.236) 0.259 0.789
GA 87 (27.97) 128 (28.96)
AA 14 (4.51) 14 (3.17) 2.197 (0.697–6.929) 0.787 0.179
17 rs858518 SHBG 0.569 0.014
GG 43 (13.83) 54 (12.22) 0.744 (0.326–1.698) 0.765 0.467
GA 128 (41.16) 187 (42.31)
AA Allele 140 (45.01) 201 (45.47) 0.940 (0.501–1.773) −1.333 0.839
17 rs858521 SHBG 0.278 −0.003
GG Allele 165 (53.05) 232 (52.49) 0.773 (0.277–1.847) 0.608 0.495
GC 124 (39.87) 180 (24.43)
CC 22 (7.08) 30 (6.78) 1.1917 (0.351–4.0673) 0.323 0.876
17 rs2908809 SHBG 0.368 −0.009
CC 63 (20.26) 82 (18.55) 0.557 (0.143–1.481) 0.679 0.261
CT 165 (53.05) 245 (55.43)
TT Allele 83 (26.69) 115 (20.02) 0.767 (0.293–1.993) 0.167 0.537
2 rs523349 SRD5A2 0.799 −0.049
GG 99 (31.83) 152 (34.39) 3.063 (0.347–28.28) 0.501 0.372
GC 156 (50.16) 206 (46.61)
CC Allele 56 (18.01) 84 (19.00) 0.447(0.063–2.451) −0.029 0.379
2 rs632148 SRD5A2 0.657 −0.029
GG Allele 67 (21.54) 97 (21.95) 2.124 (0.353–12.804) −1.333 0.466
GC 148 (47.59) 196 (44.34)
CC 96 (30.87) 149 (33.71) 0.241 (0.029–2.2478 0.765 0.239
2 rs9332975 SRD5A2 0.796 0.065
CC 9 (2.89) 8 (1.81) 4.496 (0.212–78.757) 0.67 0.321
CT 46 (14.79) 79 (17.87)
TT Allele 256 (82.32) 355 (80.32) 1.155 (0.501–2.307) 0.051 0.679
19 rs6523 INSL3 0.746 −0.008
TT 82 (21.86) 52 (13.75) 10.20 (0.638–176.246) −0.305 0.560
TC 141 (37.60 160 (42.32)
CC Allele 152 (40.54) 166 (43.65) 0.852 (0.172–5.148) −0.843 0.974
19 rs1003887 INSL3 0.470 −0.032
TT Allele 151 (40.26) 167 (44.17) 1.076 (0.458–2.516) 0.025 0.887
TC 134 (35.73) 156 (41.26)
CC 90 (24.01) 55 (14.55) 1.714 (0.582–5.204) −0.372 0.364
19 rs8112876 INSL3 0.708 0.014
AA 151 (40.26) 167 (44.17) 1.076 (0.458–2.516) 0.769 0.887
AG 134 (35.73) 156 (41.26)
GG Allele 90 (24.01) 55 (14.55) 1.714 (0.582–5.204) 0.403 0.364
X rs1204038 AR GG Allele 375 (100) 378 (100) NS
X rs1204039 AR GG Allele 375 (100) 378 (100) NS
X rs1204040 AR CC Allele 375 (100) 378 (100) NS
X rs2255702 AR CC Allele 375 (100) 378 (100) NS
a

χ 2 test;

b

On behalf of the correlation coefficient;

c

On behalf of the regression coefficient;

d

Multivariate logistic regression analysis;

The boldface represents statistical significance (P<0.05).

BPH, benign prostatic hyperplasia; CHR, chromosome; LOH, late-onset hypogonadism; OR, odds ratio; SNP, single nucleotide polymorphisms.

Discussion

This study evaluated the association of sex hormones and SNPs in genes involved in sex hormone metabolism with LOH-BPH. It was found that tT decreased with age and was negatively correlated with age. E2 increased with age and was positively correlated with age. T/E decreased with age and was negatively correlated with age in patients with BPH with or without LOH. It was also discover that LOH-BPH was correlated with age, smoking, drinking, ED, MetS, type 2 diabetes mellitus, obesity, and the decreased tT and T/E, the increased BMI and WC, the elevated E2. At the same time, LOH-BPH was also correlated with the AA genotype of rs1843090, CC genotype of rs2279357, GG genotype of rs743572, AA genotype of rs712221, and the TT genotype of rs700518.

The results of this study showed that serum E2 level increases with age, which is not only positively correlated with age, but also can be a risk factor for LOH-BPH. At the same time, tT and T/E are not only negatively correlated with age, but also decreased tT and T/E can be risk factors for LOH-BPH. This phenomenon indicates that LOH-BPH is related to sex hormone imbalance, which is chiefly manifested in the increase of estrogen, the decrease of androgen and the decrease of androgen/estrogen ratio. According to the previous literature, BPH is considered an androgen target tissue and an estrogen target tissue26,29. Furthermore, our results showed a correlation between the decrease in tT and the increase in E2 (r=−0.57, P<0.0001, results not shown). Taken together with these results, we speculate that the elevation of estrogen can be secondary to androgen depletion and has an effect on BPH with or without LOH. According to Figure 2, our speculated mechanism of LOH-BPH shows that androgen can be converted to estrogen by aromatase, namely CYP19, which can be the main cause of sex hormone imbalance. This provides a basis for the treatment of androgen supplement and aromatase inhibitor to prevent the conversion of androgen to estrogens.

In terms of gene polymorphism, the results of this study showed that LOH-BPH was correlated with the AA genotype of rs1843090 of CYP11A1, CC genotype of rs2279357 of CYP11A1, GG genotype of rs743572 of CYP17A1, AA genotype of rs712221 of ESR1 and the TT genotype of rs700518 of CYP19A1. Moreover, AA genotype of rs1843090 of CYP11A1 and AA genotype of rs712221 of ESR1 was protective factors for LOH-BPH, and CC genotype of rs2279357 of CYP11A1, GG genotype of rs743572 of CYP17A1, and TT genotype of rs700518 of CYP19A1 were risk factors for LOH-BPH (see Table 3, Figs. 1 and 2). This finding has not been reported previously, which provides a basis for predicting the occurrence of LOH-BPH by detecting gene polymorphism, provides direction for further research, and provides a reference for the same treatment for different diseases and different treatment for the same disease1721,30.

In this study, we confirmed the association between sex hormone imbalance and LOH-BPH, as well as the association between SNPs of genes related to sex hormone metabolism and LOH-BPH. In terms of SNPs, ESR1, CYP19A1, CYP17A1, CYP11A1 genes were associated with LOH-BPH. Nevertheless, no significant association was found for the other genes, which needs to be further studied.

In this study, we also discovered that LOH-BPH was associated with age, smoking, drinking, ED, obesity, type 2 diabetes mellitus, MetS, and they were risk factors for LOH-BPH. This is consistent with previous research reports, indicating that these diseases are related to living habits, dietary habits and aging2,7,12,13,17,2628. At the same time, these diseases can be attributed to metabolic diseases, and may have the same etiology and pathogenesis, which provides a basis for further research.

The present study had some limitations. This study involved only Chinese people, with a majority of Han Chinese and a small number of Hui, Miao, Uighur, and Tibetan. There were differences in gene polymorphism of different ethnic groups. This study did not take these into consideration. Moreover, genetic polymorphism detection was targeted, not whole-genome sequencing. The research population was from only two centers of data and the sample size was relatively small. These limitations may have influenced actual results and conclusions. It is necessary for more central and large case studies to confirm the present conclusions.

Conclusion

Based on the above analysis, the conclusion of this study is that the morbidity of LOH-BPH can be associated with SNPs of genes related to sex hormone metabolism. Furthermore, the AA genotype of rs1843090 of CYP11A1 and AA genotype of rs712221 of ESR1 can be a protective factor for LOH-BPH, the CC genotype of rs2279357 of CYP11A1, GG genotype of rs743572 of CYP17A1 and TT genotype of rs700518 of CYP19A1 can be a risk factor for LOH-BPH.

Ethical approval

This study was approved by the Ethics Committee of the Affiliated Hospital of Zunyi Medical University, and the Ethics Approval number was KLL-2022-391. This work has been reported in line with the STROCSS criteria. The work has been reported in line with the STROCSS criteria and in it is references [see References 22].

Consent

Yes, we have included this part in the submission and manuscript.

Source of funding

This study did not win any fund support, which is very regrettable for us. So the funding Statement was not applicable.

Author contribution

X.A., Z.O., C.C., B.C., Y.C., M.W., J.S., N.P., and X.H: participated in the test and data collection; Q.R. and Y.Z.: participated in the test, data collection, and manuscript writing; B.L. and Y.X.: participated in summarizing the test data, data analysis, and manuscript writing; Z.P.C.: formed the project development and writing – review and editing.

Conflicts of interest disclosure

The author declares no conflict of interest.

Research registration unique identifying number (UIN)

  1. Name of the registry: Chinese Clinical Trial Registry.

  2. Unique identifying number or registration ID: ChiCTR2200057632.

  3. Hyperlink to your specific registration:http://www.chictr.org.cn/showproj.aspx?proj=155496

Guarantor

Zongping Chen.

Data availability statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Or through the registered website Chinese Clinical Trial Registry to get it.

Supplementary Material

SUPPLEMENTARY MATERIAL
js9-110-7840-s001.pdf (351KB, pdf)
js9-110-7840-s002.doc (78KB, doc)

Acknowledgements

In this study, Professor Yuanzhong Zhou from the School of Public Health Management of Zunyi Medical University gave us guidance in data statistics. Thanks Professor Zhou! We also wish to acknowledge the efforts of the participants and investigators of the study. Additionally, the authors would like to thank Jichun Deng from New Oriental Education & Technology Group Inc. for proofreading.

Footnotes

Bengen Li, Congcong Chen, Qixu Ren, Youzhuang Zhong, You Xiang, and Bo Chen are co-first author.

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.lww.com/international-journal-of-surgery.

Published online 20 May 2024

Contributor Information

Bengen Li, Email: 1136593110@qq.com.

Congcong Chen, Email: 13676081388@139.com.

Zongping Chen, Email: 2404259310@qq.com.

Qixu Ren, Email: 1350812088@qq.com.

Ningrui Pan, Email: 601044962@qq.com.

Xu He, Email: 732890412@qq.com.

Min Wang, Email: 2966415585@qq.com.

Xiaoyu Ai, Email: 945344295@qq.com.

Youzhuang Zhong, Email: 1146803345@qq.com.

You Xiang, Email: 573492721@qq.com.

Bo Chen, Email: 18300924543@163.com.

Jiawei Sun, Email: 1530184399@qq.com.

Yu Cao, Email: 1183928101@qq.com.

Zhengdong Ouyang, Email: Ouyangzhendong0713@163.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SUPPLEMENTARY MATERIAL
js9-110-7840-s001.pdf (351KB, pdf)
js9-110-7840-s002.doc (78KB, doc)

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Or through the registered website Chinese Clinical Trial Registry to get it.


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