Browsing by Author "Helfand, Brian T"
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Item Open Access Shared Inherited Genetics of Benign Prostatic Hyperplasia and Prostate Cancer.(European urology open science, 2022-09) Glaser, Alexander; Shi, Zhuqing; Wei, Jun; Lanman, Nadia A; Ladson-Gary, Skylar; Vickman, Renee E; Franco, Omar E; Crawford, Susan E; Lilly Zheng, S; Hayward, Simon W; Isaacs, William B; Helfand, Brian T; Xu, JianfengBackground
The association between benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remains controversial, largely due to a detection bias in traditional observational studies.Objective
To assess the association between BPH and PCa using inherited single nucleotide polymorphisms (SNPs).Design setting and participants
The participants were White men from the population-based UK Biobank (UKB).Outcome measurements and statistical analysis
The association between BPH and PCa was tested for (1) phenotypic correlation using chi-square, (2) genetic correlation (r g) based on genome-wide SNPs using linkage disequilibrium score regression, and (3) cross-disease genetic associations based on known risk-associated SNPs (15 for BPH and 239 for PCa), individually and cumulatively using genetic risk score (GRS).Results and limitations
Among 214 717 White men in the UKB, 24 623 (11%) and 14 311 (6.7%) had a diagnosis of BPH and PCa, respectively. Diagnoses of these two diseases were significantly correlated (χ2 = 1862.80, p < 0.001). A significant genetic correlation was found (r g = 0.16; 95% confidence interval 0.03-0.28, p = 0.01). In addition, significant cross-disease genetic associations for established risk-associated SNPs were also found. Among the 250 established genome-wide association study-significant SNPs of PCa or BPH, 49 were significantly associated with the risk of the other disease at p < 0.05, significantly more than expected by chance (N = 12, p < 0.001; χ2 test). Furthermore, significant cross-disease GRS associations were also found; GRSBPH was significantly associated with PCa risk (odds ratio [OR] = 1.26 [1.18-1.36], p < 0.001), and GRSPCa was significantly associated with BPH risk (OR = 1.03 [1.02-1.04], p < 0.001). Moreover, GRSBPH was significantly and inversely associated with lethal PCa risk in a PCa case-case analysis (OR = 0.58 [0.41-0.81], p = 0.002). Only White men were studied.Conclusions
BPH and PCa share common inherited genetics, which suggests that the phenotypic association of these two diseases in observational studies is not entirely caused by the detection bias.Patient summary
For the first time, we found that benign prostatic hyperplasia and prostate cancer are genetically related. This finding may have implications in disease etiology and risk stratification.Item Open Access Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study.(PloS one, 2022-01) Andreev, Victor P; Helmuth, Margaret E; Liu, Gang; Smith, Abigail R; Merion, Robert M; Yang, Claire C; Cameron, Anne P; Jelovsek, J Eric; Amundsen, Cindy L; Helfand, Brian T; Bradley, Catherine S; DeLancey, John OL; Griffith, James W; Glaser, Alexander P; Gillespie, Brenda W; Clemens, J Quentin; Lai, H Henry; LURN Study GroupWe present a methodology for subtyping of persons with a common clinical symptom complex by integrating heterogeneous continuous and categorical data. We illustrate it by clustering women with lower urinary tract symptoms (LUTS), who represent a heterogeneous cohort with overlapping symptoms and multifactorial etiology. Data collected in the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN), a multi-center observational study, included self-reported urinary and non-urinary symptoms, bladder diaries, and physical examination data for 545 women. Heterogeneity in these multidimensional data required thorough and non-trivial preprocessing, including scaling by controls and weighting to mitigate data redundancy, while the various data types (continuous and categorical) required novel methodology using a weighted Tanimoto indices approach. Data domains only available on a subset of the cohort were integrated using a semi-supervised clustering approach. Novel contrast criterion for determination of the optimal number of clusters in consensus clustering was introduced and compared with existing criteria. Distinctiveness of the clusters was confirmed by using multiple criteria for cluster quality, and by testing for significantly different variables in pairwise comparisons of the clusters. Cluster dynamics were explored by analyzing longitudinal data at 3- and 12-month follow-up. Five clusters of women with LUTS were identified using the developed methodology. None of the clusters could be characterized by a single symptom, but rather by a distinct combination of symptoms with various levels of severity. Targeted proteomics of serum samples demonstrated that differentially abundant proteins and affected pathways are different across the clusters. The clinical relevance of the identified clusters is discussed and compared with the current conventional approaches to the evaluation of LUTS patients. The rationale and thought process are described for the selection of procedures for data preprocessing, clustering, and cluster evaluation. Suggestions are provided for minimum reporting requirements in publications utilizing clustering methodology with multiple heterogeneous data domains.Item Open Access TNF is a potential therapeutic target to suppress prostatic inflammation and hyperplasia in autoimmune disease.(Nature communications, 2022-04) Vickman, Renee E; Aaron-Brooks, LaTayia; Zhang, Renyuan; Lanman, Nadia A; Lapin, Brittany; Gil, Victoria; Greenberg, Max; Sasaki, Takeshi; Cresswell, Gregory M; Broman, Meaghan M; Paez, J Sebastian; Petkewicz, Jacqueline; Talaty, Pooja; Helfand, Brian T; Glaser, Alexander P; Wang, Chi-Hsiung; Franco, Omar E; Ratliff, Timothy L; Nastiuk, Kent L; Crawford, Susan E; Hayward, Simon WAutoimmune (AI) diseases can affect many organs; however, the prostate has not been considered to be a primary target of these systemic inflammatory processes. Here, we utilize medical record data, patient samples, and in vivo models to evaluate the impact of inflammation, as seen in AI diseases, on prostate tissue. Human and mouse tissues are used to examine whether systemic targeting of inflammation limits prostatic inflammation and hyperplasia. Evaluation of 112,152 medical records indicates that benign prostatic hyperplasia (BPH) prevalence is significantly higher among patients with AI diseases. Furthermore, treating these patients with tumor necrosis factor (TNF)-antagonists significantly decreases BPH incidence. Single-cell RNA-seq and in vitro assays suggest that macrophage-derived TNF stimulates BPH-derived fibroblast proliferation. TNF blockade significantly reduces epithelial hyperplasia, NFκB activation, and macrophage-mediated inflammation within prostate tissues. Together, these studies show that patients with AI diseases have a heightened susceptibility to BPH and that reducing inflammation with a therapeutic agent can suppress BPH.