Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese

doi:10.21203/rs.3.rs-2992126/v1

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Research Article

Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese

https://doi.org/10.21203/rs.3.rs-2992126/v1

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Importance:

Polygenic risk score (PRS) is effective in predict benign prostatic hyperplasia (BPH) incidence, prognosis and risk of operation in Han Chinese.

Objective:

The aim of our study is to investigate the role of PRS for BPH incidence and treatment outcome through hospital-based genome-wide association study (GWAS).

Design, setting, and participants:

The Affymetrix Genome-Wide TWB 2.0 SNP Array genotyped 6,237 male participants with benign prostatic hyperplasia (BPH) and 17,170 non-BPH controls from the Taiwan Precision Medicine Initiative (TPMI). PRS was determined using PGS001865, which included 1,712 single nucleotide polymorphisms. PRS scores were categorized into quartiles (Q1-Q4) and their association with outcomes in BPH patients was analyzed using logistic regression models.

Main outcomes and measures:

We investigated the PRS association with BPH incidence, adjusting for age and PSA levels. We explored PSA's relationship with prostate volume and assessed 5ARI treatment response via percentage reduction in prostate volume per patient. Additionally, we studied the PRS association with TURP risk.

Results:

In a cohort of 23,407 men, 6,237 were diagnosed with BPH. Risk of BPH was higher in the fourth quartile (Q4) than the first quartile (Q1) (OR=1.34, 95% CI=1.24-1.46, p<0.0001), even after adjusting for age (OR=1.39, 95% CI=1.27-1.52, p<0.0001). The Q4 group had larger prostate volume (43.1 ± 25.0 ml) than Q1 (34.6 ± 19.0 ml) (p<0.001), and less volume reduction after 5ARI treatment (Q1: 29.9 ± 16.6 ml, Q4: 25.0 ± 18.6 ml, p=0.011). Q1 had lower cumulative TURP probability at 3, 5, and 10 years compared to Q4 (p=0.045, p=0.009, p<0.001, respectively). PRS Q4 was an independent TURP risk in multivariate COX hazard regression (HR=1.45, 95% CI=1.09-1.92, p=0.012).

Conclusions and relevance:

In this hospital-based cohort, a higher PRS was associated with the susceptibility to BPH in male Han Chinese. In patients with BPH, a higher PRS was associated higher PSA level, larger prostate volume, inferior response of 5ARI and higher risk of TURP. Age, PSA and prostate volume were also independent risk of TURP. Prospective large-scale study with longer follow-up would be needed to validate our result.

benign prostatic hyperplasia

polygenic risk score

prostate-specific antigen level

5 alpha-reductase inhibitor

incidence

prognosis

Question What is the role of polygenic risk score (PRS) in predicting the incidence and treatment outcome of benign prostatic hyperplasia (BPH) in Han Chinese?

Findings In this hospital-based genome-wide association study (GWAS) involving 23,407 male participants, it was discovered that Han Chinese individuals with a higher polygenic risk score (PRS) showed an increased susceptibility to benign prostatic hyperplasia (BPH). Furthermore, patients with elevated PRS exhibited higher levels of prostate-specific antigen (PSA), larger prostate volume, a diminished response to 5-alpha-reductase inhibitor (5ARI) treatment, and a heightened risk of undergoing transurethral resection of the prostate (TURP).

Meaning These findings indicate that PRS can be a valuable predictive tool for assessing the risk of BPH incidence and treatment outcomes in male Han Chinese individuals. However, further large-scale studies with longer follow-up periods are necessary to validate these findings and establish the clinical utility of PRS in BPH management.

Benign prostatic hyperplasia (BPH) is a common condition in elderly men characterized by an enlargement of the prostate gland, leading to low urinary tract symptoms such as frequency, urgency, intermittency, weak stream, strain, and incomplete emptying of the bladder ¹. BPH affects approximately 50% of men over the age of 50 and 90% of men over the age of 80, making it a significant health concern in aging populations worldwide ².

The exact cause of BPH is not fully understood, but it is believed to be a complex interplay between genetic and environmental factors ^3–5. Genetic factors play a crucial role in the development of BPH, with several genes and single nucleotide polymorphisms (SNPs) identified to be associated with an increased risk of BPH ^6–8. These genetic variations may influence the growth of prostate glandular cells, androgen and androgen receptors expression, epithelial-stromal interactions, inflammation, and other biological processes involved in the pathogenesis of BPH ⁹.

The recommended initial treatment for male patients with BPH or low urinary tract symptoms is alpha-1 adrenoceptor antagonists ¹⁰. If patients continue to experience voiding difficulties despite alpha-1 adrenoceptor antagonists, 5 alpha reductase inhibitor (5ARI) can be used to achieve a prostate volume reduction of 18–28% and improve low urinary tract symptoms by 15–30% through the reduction of dihydrotestosterone ^11–13. In cases where medical treatment fails, patients may undergo surgical intervention such as monopolar transurethral resection of the prostate (TURP), bipolar TURP or laser TURP to relieve outlet obstruction ¹⁴.

Polygenic risk score (PRS) is a recently developed approach that integrates multiple genetic variants to estimate an individual's genetic predisposition to a specific disease or condition ¹⁵. The PRS is typically calculated by assigning weights to each SNPs based on their estimated influence, and then summing these weighted SNPs together. This allows researchers to evaluate the cumulative contribution of these genetic variants to disease prevalence and incidence in a population ¹⁵. PRS has been widely used in the field of genetics to predict the risk of various diseases, such as cancer, cardiovascular disease, and diabetes ^16–18. PRS has also been utilized to evaluate the genetic risk of developing BPH and identify individuals who may be at a higher risk of developing severe symptoms. For instance, a PRS composed of 23 genetic variants has been shown to be associated with elevated levels of prostate-specific antigen (PSA) and an increased likelihood of BPH development ¹⁹.

In this study, we aim to explore the association between BPH and PRS, specifically examining risk of BPH development, prostate volume in patients with BPH, response to 5 alpha-reductase inhibitor (5ARI) treatment, and the risk of transurethral resection of prostate (TURP) in the Asian population. This investigation will be conducted using genome-wide association analysis (GWAS) and data obtained from the Taiwan Precision Medicine Initiative (TPMI).

Study population

Between June 2019 and May 2021, Taichung Veterans General Hospital (TCVGH), a tertiary medical center, conducted patient recruitment for the TPMI project, a nationwide genetic research endeavor led by Academia Sinica in Taiwan. The study received approval from the ethics committee of TCVGH Institutional Review Board (IRB No. CE23119A), and informed consent was obtained from all participants. Male participants were exclusively included in the analysis and patients with confirmed prostate cancer were excluded. Clinical parameters were sourced from the dataset and electronic medical records of TCVGH, utilizing de-identification methods.

Genotyping and quality control

The blood samples were genotyped using the Axiom Genome-Wide TWB 2.0 Array Plate (Affymetrix, Santa Clara, CA, USA), which was specifically designed for the Han Chinese population in Taiwan and contains 714,431 SNPs ²⁰. Quality control and analysis were performed using Affymetrix Power Tools to eliminate markers that did not pass Hardy-Weinberg equilibrium tests (P < 1.0 × 10^–5), had a minor allele frequency less than 0.05, or had a genotype missing rate exceeding 5%. Following quality control, a total of 591,048 SNPs remained for analysis. The custom array utilized in this study provides comprehensive coverage of GWAS SNP data from a large-scale Han Chinese population in Taiwan, as previously described ²¹.

Polygenic risk score analysis

We computed the PRS using the 'score' function of plink version 1.9, which combines the weighted effects of genetic variants based on their effect size ²². In this study, we utilized the PGS001865 PRS, which was derived from a discovery analysis of 1,712 variants associated with benign prostatic hyperplasia (BPH) identified from a Trans-ancestry GWAS for 245 curated traits across nine ancestry groups from the United Kingdom (UK) Biobank ²³. We obtained the list of SNPs and their corresponding effect sizes from the Polygenic score (PGS) catalog ²⁴.

Clinical parameters and outcome evaluation

BPH cases were identified using the International Classification of Diseases, Ninth Revision (ICD-9) code 600 with available medical records. Initially, we analyzed the incidence of BPH among male participants. Subsequently, the genetic profile of the participants was linked to clinical parameters, including age of diagnosis, PSA levels, and medical history. Prostate volume was assessed using transrectal sonography, computed tomography (CT), magnetic resonance imaging (MRI), or transabdominal songraphy. The response to 5ARI medication was determined as the percentage reduction in prostate volume after treatment. Outcome evaluation was based on the incidence of patients who underwent monopolar, bipolar, or laser TURP. The association between PRS and BPH development was examined using logistic regression analysis.

Statistical analysis

In order to assess the association between PRS and the outcome of interest, the PRS values were classified into four groups based on quartiles, denoted as Q1 (0–25%), Q2 (26–50%), Q3 (51–75%), and Q4 (76–100%). Descriptive statistics for continuous variables were presented as mean ± standard deviation (SD), and differences among groups were analyzed using Student's t-test. Categorical variables were presented as number (percent), and group differences were evaluated using Chi-square test. To further examine the relationship between PRS and the outcome, univariable logistic regression analysis was conducted to calculate odds ratio (OR) and 95% confidence interval (95% CI). The risk of BPH surgery was explored using the univariable and multivariable Cox proportional hazards model and used patient’s age at the time of the surgy or at the last follow-up (2022 December 31) as a time variable. The hazard ratio (HR) and corresponding p-value were reported. All statistical analyses were performed using IBM SPSS statistical software for Windows, version 25.0 (IBM Corp., Armonk, NY, United States).

Among the 57,257 participants from the TPMI project at TCVGH, a total of 23,407 male participants were included in the analysis as cases and controls for BPH. The incidence of BPH increased from 23.8% in Q1 to 26.0% in Q2, 27.2% in Q3, and 29.6% in Q4 (Supplemental Table 1). Notably, the risk of BPH was significantly higher in Q4 compared to Q1 (OR = 1.34, 95% CI = 1.24–1.46, p < 0.0001) (Table 1). Furthermore, after adjusting for age, the association remained statistically significant (OR = 1.39, 95% CI = 1.27–1.52, p < 0.0001) (Table 1).

Table 1

Association of PRS (PGS001865) and BPH in study population.
Variables	OR	95% CI		P value^a
Comparison
Q4\|Q1	1.34	1.2397	1.4618	< 0.0001
Q3\|Q1	1.19	1.0985	1.2981	< 0.0001
Q2\|Q1	1.12	1.033	1.222	0.007
Age-adjusted
Q4\|Q1	1.39	1.2707	1.5205	< 0.0001
Q3\|Q1	1.21	1.1072	1.3273	< 0.0001
Q2\|Q1	1.12	1.0228	1.2274	0.014
^a Comparisons of categorical variables were analyzed using the logistic regression.
Abbreviation: BPH = benign prostatic hyperplasia, PRS = polygenic risk score, OR = Odd ratio.

Table 2 presents the characteristics of patients with BPH, and no significant differences were observed in terms of diagnosis age, smoking, 5ARI usage time, hypertension, and diabetes mellitus among the different quartiles of PRS groups. PSA levels were 2.3 ± 4.3, 2.7 ± 10.1, 3.1 ± 5.7, and 3.5 ± 6.3 in Q1 to Q4, respectively, and were significantly higher in Q4 (p < 0.001).

Table 2

Characteristics of the patients with BPH.
Variables		Quartile of polygenic risk score (PGS001865)								P value^a
Variables		Q1 (n = 1377)		Q2 (n = 1525)		Q3 (n = 1594)		Q4 (n = 1741)		P value^a
Demography
	Diagnosis age	63 ± 11		63 ± 11		63 ± 11		63 ± 11		0.46
	Smoking
	No	619	45.0	659	43.2	714	44.8	757	43.5
	Yes	758	55.0	866	56.8	880	55.2	984	56.5	0.69
	PSA	2.3 ± 4.3		2.7 ± 10.1		3.1 ± 5.7		3.5 ± 6.3		< 0.001
	5ARI usage time	439 ± 609		450 ± 681		432 ± 623		435 ± 642		0.98
Comorbidities
	Hypertension
	No	571	41.5	637	41.8	676	42.4	716	41.1
	Yes	806	58.5	888	58.2	918	57.6	1025	58.9	0.90
	Diabetes mellitus
	No	810	58.8	904	59.3	948	59.5	1027	59.0
	Yes	567	41.2	621	40.7	646	40.5	714	41.0	0.98
^a Comparisons of continuous variables using Student's t-test and categorical variables were analyzed using the Chi-square test.
Abbreviation: BPH = benign prostatic hyperplasia, PSA = prostate specific antigen, 5ARI = 5-alpha reductase inhibitor.

Table 3 demonstrates the outcomes of patients with BPH. Prostate volume was found to increase significantly from Q1 to Q4 (34.6 ± 19.0, 37.3 ± 21.4, 41.3 ± 24.2, and 43.1 ± 25.0, respectively) (p < 0.001). Additionally, the response to 5ARI medication, measured as reduction in volume, was inferior in Q4 compared to Q1 (29.9 ± 16.6, 30.4 ± 16.8, 26.7 ± 17.4, and 25.0 ± 18.6, respectively) (p = 0.011).

Table 3

Characteristics of the patients with BPH.
Variables	Quartile of polygenic risk score (PGS001865)								P value^a
Variables	Q1 (n = 1377)		Q2 (n = 1525)		Q3 (n = 1594)		Q4 (n = 1741)		P value^a
Prostate volume (ml)	34.6 ± 19.0		37.3 ± 21.4		41.3 ± 24.2		43.1 ± 25.0		< 0.001
Reduction volume after 5ARI (%)	29.9 ± 16.6		30.4 ± 16.8		26.7 ± 17.4		25.0 ± 18.6		0.011
TURP (n, %)
No	1297	94.2	1426	93.5	1469	92.2	1565	89.9
Yes	80	5.8	99	6.5	125	7.8	176	10.1	< 0.001
a Comparisons of continuous variables using Student's t-test and categorical variables were analyzed using the Chi-square test.
Abbreviation: BPH = benign prostatic hyperplasia, 5ARI = 5 alpha reductase inhibitor, TURP = transurethral resection of prostate.

The risk of patients undergoing TURP was found to be higher in Q4 compared to Q1 (Q1 to Q4: 5.8%, 6.5%, 7.8%, and 10.1%, respectively, p < 0.001) (Table 3). Table 4 presents the adjusted TURP probability over time, with significant differences observed starting from the third year. The 3-year TURP probability in Q1 to Q4 was 4.7%, 5.0%, 5.2%, and 6.7%, respectively (p = 0.045). The 5-year TURP probability in Q1 to Q4 was 5.2%, 5.9%, 6.0%, and 7.9%, respectively (p = 0.009). The 10-year TURP probability in Q1 to Q4 was 5.7%, 6.4%, 7.8%, and 9.9%, respectively (p < 0.001). Figure 1 displays the cumulative incidence of TURP in the four quartile groups, with significantly higher rates observed in Q4 (p < 0.001).

Table 4

BPH Q1-4 TURP probability.
Variables	Quartile of polygenic risk score (PGS001865)				P value
Variables	Q1	Q2	Q3	Q4	P value
Time (year)
1	0.039	0.035	0.037	0.048	0.188
3	0.047	0.050	0.052	0.067	0.045
5	0.052	0.059	0.060	0.079	0.009
10	0.057	0.064	0.078	0.099	< 0.001
Abbreviation: BPH = benign prostatic hyperplasia, TURP = transurethral resection of prostate.

Table 5 employed uni- and multivariable Cox hazard regression to investigate the risk factors for TURP in BPH. After adjusting for age, prostate volume, and PSA, we found that PRS was an independent risk factor, with a HR of 1.45 (95% CI = 1.090–1.920, p = 0.012) for Q4 compared to Q1. Additionally, age (HR = 1.010, 95% CI = 1.001–1.019, p = 0.028), prostate volume (HR = 1.013, 95% CI = 1.011–1.016, p < 0.001), and PSA (HR = 1.017, 95% CI = 1.009–1.025, p < 0.001) were identified as other independent risk factors for TURP.

Table 5

Assessing the risk of surgery in BPH patients.
Variables	Univariable model			Multivariable model
Variables	HR	95% CI	P value^a	HR	95% CI	P value^a
Age	1.025	1.017–1.033	< 0.001	1.010	1.001–1.019	0.028
Quartile
PGS Q1	1	-	-	1	-	-
PGS Q2	0.810	0.650–1.010	0.059	1.080	0.790–1.480	0.615
PGS Q3	1.020	0.830–1.240	0.889	1.110	0.820–1.500	0.505
PGS Q4	1.500	1.250–1.810	< 0.001	1.450	1.090–1.920	0.012
Prostate volume (ml)	1.014	1.012–1.016	< 0.001	1.013	1.011–1.016	< 0.001
PSA	1.009	1.006–1.013	< 0.001	1.017	1.009–1.025	< 0.001
a Cox proportional hazard regression.
Abbreviation: BPH = benign prostatic hyperplasia, HR = hazard ratio, PRS = polygenic risk score, PSA = prostate specific antigen.

Our study represents the first to demonstrate a significant association between PRS and BPH within the Han Chinese population. Through the analysis of data gathered from the TCVGH-TPMI cohort, we discovered that PRS serves as a reliable predictor of BPH incidence, as well as other clinical parameters, including prostate volume, response to 5ARI medications, and the future risk of requiring TURP.

As BPH is a prevalent condition among elderly men, identifying individuals at a higher risk of developing it can assist with early intervention and management. The heritability of BPH and male lower urinary tract symptoms in twins has been estimated to range from 20–83% across various cohorts, strongly indicating that genetic factors play a significant role in the development of BPH ^5,25,26.

Numerous genes have been shown to be associated with the development of BPH. Among these genes, steroid 5α-reductase 1 (SRD5A1) and steroid 5α-reductase 2 (SRD5A2) encode 5α-reductase type 1 and type 2, respectively, which are involved in testosterone metabolism and have been associated with an increased risk of prostatic hyperplasia ^27,28. SRD5A2 is abundantly expressed in the male reproductive system, where it catalyzes the conversion of testosterone to dihydrotestosterone (DHT) ²⁹. A decrease in the expression of SRD5A2 has been associated with underdeveloped and atypical genitalia, while an increase in its expression has been linked to excessive DHT production and an increased risk of BPH ^30,31. 5ARIs, such as finasteride and dutasteride, primarily target SRD5A2 and reduce the levels of DHT, thereby indicating their effectiveness in treating BPH ³¹.

The androgen receptor (AR) signaling pathway has been established as a key contributor to BPH development. Increased AR expression in stromal cells can modify the interaction between epithelial and stromal cells, making the prostate more sensitive to androgen and resulting in hyperplastic growth ³². Blocking or decreasing AR signaling pathway expression could decrease prostate volume and relieve lower urinary tract symptoms ^32–34. Specific AR gene polymorphisms, such as SNP rs6152 in the first exon of the AR gene, have been associated with AR expression and the development of androgenetic alopecia and BPH ³⁵. Genomic studies have suggested that FOXA1 regulates the expression of AR and that deletion of FOXA1 in the luminal epithelium of adult mice causes prostatic hyperplasia ^36,37. Additionally, NFIB has been found to interact with FOXA1 as a cofactor in regulating AR target gene expression, and loss of NFIB induces prostatic hyperplasia in a mouse model ³⁸. Although the precise mechanism by which these transcription factors contribute to the pathogenesis of BPH remains unclear, various potential genes have been identified to exhibit association with the development of BPH through different etiologies.

The PRS, which is based on multiple genetic markers associated with BPH, can provide a comprehensive risk assessment that takes into account the genetic predisposition of an individual ¹⁵. The positive correlation between PRS and BPH incidence suggests that individuals with higher PRS may have a higher risk of developing BPH, and close monitoring and appropriate interventions should be considered in this population.

Gudmundsson et al. provided initial evidence for a positive association between PRS and BPH. Their study utilized data from the Icelandic BPH/LUTS dataset and the UK Biobank dataset, which included a total of 20,621 BPH patients and 280,541 controls of European ancestry. Through genome-wide analysis, the researchers identified 23 variants at 14 loci that were significantly associated with BPH development. Further analysis revealed a strong correlation between PRS and elevated prostate-specific antigen (PSA) levels, as well as an increased risk of BPH development ¹⁹. Glaser et al. utilized genome-wide data from the UK Biobank to investigate the genetic relationship between BPH and prostate cancer ³⁹. They found that the two conditions share common inherited genetics. In addition to the study by Conti et al., which identified 239 risk SNPs for prostate cancer, Glaser et al. identified 15 risk SNPs for BPH development, and 49 of the identified SNPs were significantly associated with the risk of the other disease ^39,40. Furthermore, the PRS for BPH was significantly associated with prostate cancer risk, and vice versa ³⁹. This suggests that PRS could serve as a comprehensive risk assessment tool for predicting the development of both BPH and prostate cancer. In summary, genetics play a significant role in the occurrence of BPH, and PRS can provide valuable insights for disease prediction.

Our research findings demonstrate a positive correlation between PRS and susceptibility to BPH. Notably, our study deviates from previous literature that has predominantly focused on individuals of European ancestry, as we have specifically analyzed the Han Chinese population. Additionally, patients with prostate cancer were excluded from analysis to prevent any potential confounding factors. As a single-center cohort study, our research benefits from ample medical record availability. We leveraged this advantage by measuring prostate volume as an outcome and discovered that genome-wide factors not only correlated with disease diagnosis ^41,42. To the best of our knowledge, this is the first report of such a correlation in the literature. Furthermore, our findings echo those of Gudmundsson et al., as we also observed an association between PRS and elevated PSA levels ¹⁹.

Secondly, our study revealed that a lower PRS score was associated with a more favorable response to 5ARI treatment. 5ARI medications, such as finasteride and dutasteride, work by inhibiting the conversion of testosterone to dihydrotestosterone (DHT), which is a key hormonal factor in the development of BPH ⁴³. 5ARI is known to inhibit the activity of the enzyme 5α-reductase, leading to a decrease in DHT levels, induction of apoptosis in prostate epithelial cells, and a resulting reduction in prostate size by approximately 18–28% ^44,45. The main target of 5ARI, SRD5A2, is an integral membrane enzyme involved in steroid metabolism. It catalyzes the conversion of testosterone to DHT ⁴⁶. Prior research has linked high expression of SRD5A2 to increased prostate volume and metabolic syndromes ²⁷. Additionally, Gu et al. reported 11 tagging SNPs in the SRD5A1 and SRD5A2 genes. Among them, rs523349 and rs9332975 at SRD5A2 were significantly associated with baseline prostate volume, rs166050 at SRD5A1 was associated with the posttreatment change in total prostate volume by 5ARI ^47,48. Furthermore, Austin et al. reported that activation of NF-κB and AR variant 7 (AR-V7) could result in increased SRD5A2 expression, leading to in vivo prostate growth resistant to 5ARI treatment ⁴⁹. Conclusively, the finding that PRS is associated with the response to 5ARI medications suggests that genetic factors may influence the efficacy of these medications. PRS can potentially be used to identify individuals who are more likely to respond to 5ARI medications and those who may require alternative treatment options.

Finally, this study also reveals that PRS can predict the risk of requiring TURP in the future. TURP is a common surgical intervention for BPH that is indicated when conservative treatments fail to provide adequate symptom relief ^50,51. The finding that PRS is associated with the risk of requiring TURP suggests that genetic factors may influence the disease progression of BPH and the need for surgical intervention. PRS can potentially be used as a prognostic tool to identify individuals at higher risk of requiring TURP in the future, and appropriate management strategies can be implemented accordingly.

There are several limitations to this study that should be acknowledged. Firstly, the PRS is based on genetic markers that have been identified in previous studies, and the selection of genetic markers may not be comprehensive. Our study was unable to provide a definitive explanation for the specific impact of individual genes on the development of benign prostatic hyperplasia. Further research is needed to identify additional genetic markers that may contribute to the prediction of BPH incidence and related parameters. Secondly, the sample size of this study may be relatively small, and larger studies are needed to validate the findings and establish the clinical utility of PRS in predicting BPH outcomes. Additionally, this study is based on a Taiwanese population, and the findings may not be directly applicable to other ethnic populations. Further studies in diverse populations are warranted to assess the generalizability of the findings.

Conflicts of Interest

The contributing authors declare that the research had no commercial or financial relationships related to the potential conflict of interest.

Author Contributions

Study design and protocol development: SCH, THH, JRL, ICC; manuscript writing and editing: SCH, ICC; statistical analysis: ICC, GCL; data collection and patient management: SCH, LWC, SSW, JRL; supervision or mentorship: SCH, LWC, THH, GCL, SSW, JRL and ICC. All authors reviewed the final manuscript.

Ethics Statement

The studies involving human participants were reviewed and approved by certification at Taichung Veteran General Hospital, Taiwan, with Certification of approval with IRB: CE23119A. The patients/participants provided their written informed consent to participate in this study.

Funding

This study was funded by Taichung Veterans General Hospital, Taiwan [grant numbers TCVGH- TCVGH-1127304B].

Availability of data and materials

The original contributions presented in the study are included in the article and further inquiries can be directed to the corresponding author.

Data Sharing Statement

All data used in this study are available in this article.

Acknowledgments

We thank all of the participants and investigators from the Taiwan Precision Medicine Initiative. The authors sincerely appreciate the assistance of the Center for Translational Medicine of Taichung Veterans General Hospital.

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Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese

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