Background: Adiponectin has been reported to have a prohibitory effect on prostate cancer. The goal of this study was to evaluate the diagnostic value of adiponectin multimers for prostate cancer.

Methods: Total adiponectin, high- and low-molecular-weight (HMW, LMW), ratios of these measures, and body mass index (BMI) were compared in a prospective prostate cancer–screened cohort. Multivariable logistic regression was used to assess the association between adiponectin measures, their interaction with BMI, and risk of prostate cancer and Gleason score upgrading from biopsy to prostatectomy.

Results: A total of 228 prostate cancer cases and 239 controls were analyzed: 72 (31.6%) of the cancer cases were high grade (Gleason grade ≥7). Only percent HMW had a statistically significant relationship with prostate cancer (P = 0.04). Among normal and overweight men, the risk of prostate cancer increased as percent HMW increased [OR = 1.24 for a doubling of percent HMW, 95% confidence interval (CI), 0.41–3.75 and OR = 1.81; 95% CI, 1.02–3.20, respectively], whereas among obese men, the risk of prostate cancer decreased (OR = 0.62; 95% CI, 0.32–1.18). Among 97 patients who underwent radical prostatectomy, there was no association between Gleason score upgrading and any of the adiponectin multimers.

Conclusion: This study was unable to confirm the utility of total adiponectin as a biomarker for prostate cancer risk. For the adiponectin multimers, only HMW showed increases with prostate cancer but not in all weight classes.

Impact: Although adiponectin may play a role in the pathogenesis of prostate cancer, our results do not support adiponectin multimers as biomarkers of detection. Cancer Epidemiol Biomarkers Prev; 23(2); 309–15. ©2013 AACR.

Adiponectin is an adipocyte-produced cytokine (adipokine) that circulates at high concentrations (3–30 μg/mL). It regulates inflammation (1) and is known for regulating glucose and lipid metabolism through its insulin-sensitizing effects. The adipokine is secreted as a monomeric protein that oligomerizes to form a low-molecular-weight (LMW) trimer, a middle-molecular-weight (MMW) hexamer, and a high-molecular-weight (HMW) 12- to 18-mer (2). The HMW isoform mediates most biological effects, including proinflammatory activity, whereas the LMW isoform is anti-inflammatory (3). Unlike adipokines, such as leptin and TNF-α, adiponectin levels are inversely proportional to an individual's fat mass (4). Low adiponectin concentrations mediate obesity-linked diseases such as type 2 diabetes and cardiovascular diseases (2); this relationship is important as obesity is associated with an increased risk of developing cancers such as colorectal, esophageal, breast, endometrial and, most notably, prostate cancer (3). Adiponectin receptors are expressed on a number of different types of tumor cells (5), and the adipokine has been demonstrated to have direct antiproliferative effects on those neoplastic cells (3). Thus, decreased levels of adiponectin, as occurs in obesity, are hypothesized to play a role in tumorigenesis.

A large body of published literature suggests that adiponectin has an inhibitory effect on prostate cancer development and progression. HMW adiponectin was found to inhibit the proliferation of prostate cancer cell lines (6). Leptin and full-length adiponectin, when combined, inhibited the proliferation of the PC3 human prostate cancer cell line by increasing p53 expression and decreasing BCL2 expression (7). Epidemiologic studies demonstrating an inverse association of adiponectin with stage, grade, or aggressiveness of prostate cancer support the adipokine's antitumorigenic activities (8–12). For example, among men with locally advanced and localized prostate cancer, adiponectin was inversely associated with prostate cancer stage in overweight and obese but not normal weight men (12). Further evidence for a protective role of the adipokine is suggested by the demonstration of 2 single-nucleotide polymorphisms in the adiponectin gene that were associated with decreased adiponectin levels and increased prostate cancer risk (13). However, adiponectin may also promote prostate cancer growth perhaps through amplification of pro-survival phosphoinositide 3-kinase/Akt/mTOR signaling as demonstrated in LNCAp and CWR22Rv1 prostate cancer cell lines (14). In addition, not all epidemiologic studies have demonstrated an inverse association between adiponectin and prostate cancer, stage, or aggressiveness (15–18). One such study found higher adiponectin levels in locally advanced compared with organ-confined prostate cancer (15).

It is thus unclear what the role is of adiponectin in prostate carcinogenesis and as a risk biomarker for this disease. Limitations of studies to date have been the assessment of only total levels of the adipokine but not its mulitmers; for this reason, the full understanding of this biologic system has never been fully elucidated as the different adiponectin multimers have very different yet interacting biological activities (3). For example, change in the ratio of HMW to total adiponectin has been shown to be a sensitive indicator of change in insulin sensitivity in response to antidiabetic treatment (19). In addition, the assessment of adiponectin multimers, as opposed to total levels, has been key to understanding the relationship between adipokines and cardiovascular risk (20, 21). Similarly, HMW adiponectin has been found to be more closely associated with cancer risk than total adiponectin (22).

Against the backdrop of the 2012 US Preventive Services Task Force recommendation against prostate-specific antigen (PSA) screening for prostate cancer, our Early Detection Research Network (National Cancer Institute) Clinical Epidemiologic and Validation Center has continued the effort to identify biomarkers that will improve the detection of high-grade, potentially lethal cancers (23). In addition, the discovery of biomarkers that would allow for the identification of tumors prone to Gleason score upgrading upon prostatectomy would be clinically useful (24). Herein, we present findings of the impact of adiponectin multimers to improve the detection of consequential prostate cancer in a prospective, population-based cohort study.

Subjects

The San Antonio Biomarkers Of Risk (SABOR) of prostate cancer study is a National Cancer Institute Early Detection Research Network sponsored Clinical and Epidemiologic Validation Center that includes a cohort of more than 4,000 San Antonio and South Texas men without a prior diagnosis of prostate cancer. Men are seen annually. During these visits, a host of clinical and demographic data are updated and biologic samples, including serum for PSA, are collected. Prostate biopsy is performed based on community standards. During more than 13 years of follow-up, 332 men have been diagnosed with prostate cancer (25). From this cohort, a nested case–control population was selected for adiponectin measurement. Cancer cases had PSA, %freePSA, [−2]proPSA, and digital rectal examination (DRE) measured within 2.5 years before diagnosis. Controls had at least 5 years of study follow-up without a diagnosis of prostate cancer; serum samples from controls were accessed from their first study visit. Adiponectin was measured from the same serum sample as PSA. Some participants with prostate cancer subsequently underwent radical prostatectomy; these cases enabled comparison of Gleason score between biopsy and prostatectomy tissue in this subset.

Specimens

Informed consent approved by the Institutional Review Board at the University of Texas Health Science Center at San Antonio was obtained for each participant. Participants had blood drawn in an 8 mL red top Vacutainer tube before their DRE. Whole blood was allowed to clot for 30 minutes at room temperature before serum was separated by centrifugation for 15 minutes at 10°C, distributed into approximately 1 mL aliquots, and immediately frozen at −80°C. Samples were thawed and distributed into smaller aliquots for subsequent analysis of adiponectin multimers.

Serum adiponectin levels were determined using a multimeric ELISA from ALPCO Immunoassays (#47-ADPHU-EO1). This commercially available kit is based on the protease methodologies described by Ebinuma and colleagues (26) that enables the measurement of total adiponectin, HMW, MMW, and LMW multimers. For total adiponectin, samples (10 μL serum) were pretreated with citrate buffer containing SDS, reducing the multimeric adiponectin to dimers, which can then be detected in the sandwich ELISA that utilizes a 96-well plate that is precoated with monoclonal antibody that binds the dimeric form of adiponectin. HMW adiponectin samples (10 μL serum) were pretreated with the kit Protease II that selectively digested LMW and MMW multimers. The remaining HMW adiponectin fraction was treated with the SDS-containing buffer to reduce the multimers to dimers while also stopping protease digestion. Subsequent measurement in the ELISA quantified the amount of HMW adiponectin without detecting the digested LMW and MMW multimers. For MMW + HMW multimers, samples (10 μL serum) were pretreated with the kit Protease I that selectively digested only LMW adiponectin. The remaining MMW + HMW multimers were then digested to dimers using the SDS-containing buffer. Subsequent measurement in the ELISA quantified the amount of reduced MMW and HMW multimers without detecting digested LMW adiponectin. MMW adiponectin concentration (μg/mL) was calculated by subtracting the concentration of HMW adiponectin from the concentration of combined MMW + HMW multimers. For LMW adiponectin (μg/mL), LMW (trimers + albumin-bound trimers) adiponectin concentration (μg/mL) was calculated by subtracting the concentration of combined MMW + HMW multimers from total adiponectin. The samples were run in duplicate and absorbance read at 492 nm within 30 minutes of the addition of a stop reagent to stop color development. Blank values were subtracted from all reading and duplicate readings for each sample subsequently averaged. The interassay CVs for direct measurement of total adiponectin, MMW + HMW multimers, and HMW adiponectin were less than 10% and the sensitivity of the assay was 0.02 ng/mL; these data were based on 3 controls provided by the kit and 2 additional human serum controls, one with high and one with low levels. The percentage of the different multimers of adiponectin was also calculated, including percentage HMW adiponectin (HMW/Total), percentage MMW adiponectin (MMW/Total), percentage LMW adiponectin (LMW/Total), MMW/HMW, LMW/HMW, and MMW/LMW.

Statistical analyses

Continuous and discrete factors were compared between prostate cancer cases and controls using the Mann–Whitney U and the χ2 tests, respectively. The Spearman correlation coefficient was calculated between the adiponectin measures. Area underneath the receiver operating characteristic curves (AUC) were calculated for each of the adiponectin measures and tested against 50% (no discrimination ability) using the Wilcoxon test statistic.

Multivariable logistic regression was used to assess the joint effect of adiponectin measures and interaction with body mass index (BMI) weight classifications on prostate cancer risk. On the subset of participants with a subsequent prostatectomy, logistic regression was used to model the association between the individual adiponectin measures and multiple combinations of them (along with BMI) and Gleason score upgrading from biopsy to prostatectomy. For all logistic regression analyses, all adiponectin measures were transformed to the log-base-2 scale to improve goodness-of-fit. On this scale, odds ratios correspond to the increase in odds of prostate cancer for a doubling of the adiponectin measure. All statistical computations were performed in the SAS version 9.3 for Windows statistical package (SAS Institute, Cary, NC).

A total of 228 prostate cancer cases and 239 controls from the SABOR cohort were included in the analysis (Table 1). Seventy-two (31.6%) of the 228 cancer cases were high grade (Gleason grade 7 or higher). There were no statistical differences between cancer cases and controls in age, race, BMI categories (normal/underweight, overweight, obese) nor in prior biopsy history. Average BMI was slightly higher among prostate cancer cases (mean 28.7 vs. 27.8 kg/m2, P = 0.02). There were significant differences in frequency of abnormal DREs, family history of prostate cancer in a first-degree relative, PSA, %freePSA, and [−2]proPSA (all P < 0.0001). The significance of these differences related to the fact that abnormal DREs and elevated PSA are utilized for identifying men to receive biopsies, which is essential for a cancer diagnosis.

Table 1.

Baseline characteristics among prostate cancer cases and controls

Controls (N = 239)Cases (N = 228)P
Agea, y, mean (SD) 64.4 (8.5) 63.9 (8.2) 0.50 
Range 45.0–83.5 44.4–88.6  
Age, N (%)   0.90 
 40–49 12 (5.0) 13 (5.7)  
 50–59 62 (25.9) 62 (27.2)  
 60–69 104 (43.5) 100 (43.9)  
 ≥70 61 (25.5) 52 (22.8)  
 Missing 0 (0.0) 1 (0.4)  
BMI, kg/m2, mean (SD) 27.8 (4.1) 28.7 (4.5) 0.02 
Range (20.0–48.0) (16.0–45.0)  
BMI, N (%)   0.15 
 <24.9 44 (18.4) 28 (12.3)  
 25.0–29.9 121 (50.6) 117 (51.3)  
 ≥30.0 74 (31.0) 83 (36.4)  
Race, N (%)   0.06 
 White 162 (67.8) 131 (57.5)  
 Black 33 (13.8) 35 (15.4)  
 Hispanic 42 (17.6) 61 (26.7)  
 Other 2 (0.8) 1 (0.4)  
Prior negative biopsy, N (%)   0.42 
 Never 196 (82.0) 180 (79.0)  
 At least one 43 (18.0) 48 (21.0)  
Digital rectal exam, N (%)   <0.0001 
 Normal 230 (96.2) 148 (64.9)  
 Abnormal 7 (2.9) 67 (29.4)  
 Missing 2 (0.9) 13 (5.7)  
Family history, N (%)   <0.0001 
 No 213 (89.1) 171 (75.0)  
 Yes 26 (10.9) 57 (25.0)  
PSAa, ng/mL, mean (SD) 1.5 (1.4) 4.8 (6.5) <0.0001 
Range 0.1 to 8.4 0.3 to 54.8  
%freePSAa, mean (SD) 32.0 (11.7) 21.2 (11.7) <0.0001 
Range 6.6 to 73.0 4.4 to 72.0  
[−2]proPSAa, pg/mL, mean (SD) 8.8 (5.6) 17.4 (33.2) <0.0001 
Range 0.8 to 39.0 2.3 to 447.9  
Gleason score, N (%) 
 <6  6 (2.6)  
 6  140 (61.4)  
 7  54 (23.7)  
 8–10  18 (7.9)  
 Missing  10 (4.4)  
Controls (N = 239)Cases (N = 228)P
Agea, y, mean (SD) 64.4 (8.5) 63.9 (8.2) 0.50 
Range 45.0–83.5 44.4–88.6  
Age, N (%)   0.90 
 40–49 12 (5.0) 13 (5.7)  
 50–59 62 (25.9) 62 (27.2)  
 60–69 104 (43.5) 100 (43.9)  
 ≥70 61 (25.5) 52 (22.8)  
 Missing 0 (0.0) 1 (0.4)  
BMI, kg/m2, mean (SD) 27.8 (4.1) 28.7 (4.5) 0.02 
Range (20.0–48.0) (16.0–45.0)  
BMI, N (%)   0.15 
 <24.9 44 (18.4) 28 (12.3)  
 25.0–29.9 121 (50.6) 117 (51.3)  
 ≥30.0 74 (31.0) 83 (36.4)  
Race, N (%)   0.06 
 White 162 (67.8) 131 (57.5)  
 Black 33 (13.8) 35 (15.4)  
 Hispanic 42 (17.6) 61 (26.7)  
 Other 2 (0.8) 1 (0.4)  
Prior negative biopsy, N (%)   0.42 
 Never 196 (82.0) 180 (79.0)  
 At least one 43 (18.0) 48 (21.0)  
Digital rectal exam, N (%)   <0.0001 
 Normal 230 (96.2) 148 (64.9)  
 Abnormal 7 (2.9) 67 (29.4)  
 Missing 2 (0.9) 13 (5.7)  
Family history, N (%)   <0.0001 
 No 213 (89.1) 171 (75.0)  
 Yes 26 (10.9) 57 (25.0)  
PSAa, ng/mL, mean (SD) 1.5 (1.4) 4.8 (6.5) <0.0001 
Range 0.1 to 8.4 0.3 to 54.8  
%freePSAa, mean (SD) 32.0 (11.7) 21.2 (11.7) <0.0001 
Range 6.6 to 73.0 4.4 to 72.0  
[−2]proPSAa, pg/mL, mean (SD) 8.8 (5.6) 17.4 (33.2) <0.0001 
Range 0.8 to 39.0 2.3 to 447.9  
Gleason score, N (%) 
 <6  6 (2.6)  
 6  140 (61.4)  
 7  54 (23.7)  
 8–10  18 (7.9)  
 Missing  10 (4.4)  

NOTE: Characteristics of participants used in the analysis.

aAge missing for one cancer case, PSA for 3 cases, %freePSA for 3 cases, [−2]proPSA for 1 case.

Table 2 summarizes adiponectin measures stratified by BMI category. There were no statistically significant differences of any adiponectin measures between prostate cancer cases and controls among normal weight and obese groups. In the overweight group, there were marginally statistically significant differences between prostate cancer cases and controls in HMW adiponectin, percent HMW adiponectin, MMW/HMW, and LMW/HMW (P < 0.05). In this group, both HMW adiponectin and percent HMW adiponectin were higher among cancer cases, whereas both MMW/HMW and LMW/HMW were lower among the cancer cases.

Table 2.

Adiponectin measures stratified by BMI category

All menUnderweight/normal (BMI < 25)Overweight (25 ≤ BMI < 30)Obese (BMI ≥ 30)
Controls (N = 239)Cases (N = 228)Controls (N = 44)Cases (N = 28)Controls (N = 121)Cases (N = 117)Controls (N = 74)Cases (N = 83)
Total 4.52 (3.25–6.15) 4.52 (3.03–6.59) 6.19 (4.47–8.05) 5.01 (4.42–7.94) 4.63 (3.25–5.84) 4.98 (3.26–7.01) 3.72 (2.91–5.08) 3.68 (2.49–5.44) 
HMW 1.96 (1.18–2.93) 1.95 (1.05–3.36) 2.67 (2.03–4.26) 2.51 (1.52–4.36) 1.79a (1.20–2.77) 2.22a (1.30–3.61) 1.53 (0.96–2.48) 1.43 (0.81–2.60) 
MMW 0.96 (0.61–1.28) 0.88 (0.60–1.30) 1.09 (0.76–1.59) 1.14 (0.91–1.44) 0.97 (0.57–1.36) 0.88 (0.63–1.24) 0.86 (0.58–1.13) 0.80 (0.49–1.30) 
LMW 1.59 (1.11–1.98) 1.52 (1.11–2.03) 1.79 (1.43–2.30) 1.61 (1.14–2.20) 1.63 (1.20–1.96) 1.62 (1.15–2.07) 1.25 (0.97–1.71) 1.38 (1.04–1.83) 
HMW/total 0.43 (0.34–0.51) 0.43 (0.35–0.53) 0.46 (0.39–0.54) 0.50 (0.38–0.60) 0.42a (0.34–0.50) 0.45a (0.38–0.55) 0.43 (0.34–0.50) 0.40 (0.30–0.50) 
MMW/total 0.21 (0.16–0.27) 0.20 (0.15–0.26) 0.20 (0.16–0.25) 0.19 (0.15–0.24) 0.21 (0.15–0.28) 0.19 (0.14–0.27) 0.22 (0.17–0.29) 0.21 (0.16–0.25) 
LMW/total 0.35 (0.28–0.42) 0.35 (0.27–0.44) 0.34 (0.27–0.39) 0.32 (0.22–0.43) 0.35 (0.29–0.44) 0.34 (0.27–0.41) 0.36 (0.27–0.42) 0.39 (0.28–0.49) 
MMW/HMW 0.48 (0.33–0.73) 0.46 (0.31–0.72) 0.43 (0.29–0.63) 0.36 (0.25–0.74) 0.49a (0.33–0.76) 0.43a (0.29–0.62) 0.53 (0.35–0.75) 0.50 (0.38–0.79) 
LMW/HMW 0.80 (0.58–1.24) 0.77 (0.51–1.20) 0.71 (0.51–1.05) 0.70 (0.40–0.99) 0.85a (0.62–1.27) 0.73a (0.48–1.05) 0.77 (0.56–1.25) 1.02 (0.54–1.54) 
MMW/LMW 0.59 (0.43–0.83) 0.57 (0.39–0.87) 0.59 (0.45–0.82) 0.65 (0.51–0.96) 0.59 (0.41–0.84) 0.56 (0.39–0.85) 0.62 (0.46–0.83) 0.56 (0.40–0.86) 
All menUnderweight/normal (BMI < 25)Overweight (25 ≤ BMI < 30)Obese (BMI ≥ 30)
Controls (N = 239)Cases (N = 228)Controls (N = 44)Cases (N = 28)Controls (N = 121)Cases (N = 117)Controls (N = 74)Cases (N = 83)
Total 4.52 (3.25–6.15) 4.52 (3.03–6.59) 6.19 (4.47–8.05) 5.01 (4.42–7.94) 4.63 (3.25–5.84) 4.98 (3.26–7.01) 3.72 (2.91–5.08) 3.68 (2.49–5.44) 
HMW 1.96 (1.18–2.93) 1.95 (1.05–3.36) 2.67 (2.03–4.26) 2.51 (1.52–4.36) 1.79a (1.20–2.77) 2.22a (1.30–3.61) 1.53 (0.96–2.48) 1.43 (0.81–2.60) 
MMW 0.96 (0.61–1.28) 0.88 (0.60–1.30) 1.09 (0.76–1.59) 1.14 (0.91–1.44) 0.97 (0.57–1.36) 0.88 (0.63–1.24) 0.86 (0.58–1.13) 0.80 (0.49–1.30) 
LMW 1.59 (1.11–1.98) 1.52 (1.11–2.03) 1.79 (1.43–2.30) 1.61 (1.14–2.20) 1.63 (1.20–1.96) 1.62 (1.15–2.07) 1.25 (0.97–1.71) 1.38 (1.04–1.83) 
HMW/total 0.43 (0.34–0.51) 0.43 (0.35–0.53) 0.46 (0.39–0.54) 0.50 (0.38–0.60) 0.42a (0.34–0.50) 0.45a (0.38–0.55) 0.43 (0.34–0.50) 0.40 (0.30–0.50) 
MMW/total 0.21 (0.16–0.27) 0.20 (0.15–0.26) 0.20 (0.16–0.25) 0.19 (0.15–0.24) 0.21 (0.15–0.28) 0.19 (0.14–0.27) 0.22 (0.17–0.29) 0.21 (0.16–0.25) 
LMW/total 0.35 (0.28–0.42) 0.35 (0.27–0.44) 0.34 (0.27–0.39) 0.32 (0.22–0.43) 0.35 (0.29–0.44) 0.34 (0.27–0.41) 0.36 (0.27–0.42) 0.39 (0.28–0.49) 
MMW/HMW 0.48 (0.33–0.73) 0.46 (0.31–0.72) 0.43 (0.29–0.63) 0.36 (0.25–0.74) 0.49a (0.33–0.76) 0.43a (0.29–0.62) 0.53 (0.35–0.75) 0.50 (0.38–0.79) 
LMW/HMW 0.80 (0.58–1.24) 0.77 (0.51–1.20) 0.71 (0.51–1.05) 0.70 (0.40–0.99) 0.85a (0.62–1.27) 0.73a (0.48–1.05) 0.77 (0.56–1.25) 1.02 (0.54–1.54) 
MMW/LMW 0.59 (0.43–0.83) 0.57 (0.39–0.87) 0.59 (0.45–0.82) 0.65 (0.51–0.96) 0.59 (0.41–0.84) 0.56 (0.39–0.85) 0.62 (0.46–0.83) 0.56 (0.40–0.86) 

NOTE: Adiponectin characteristics [medians (interquartile ranges)], μg/mL, by total participants, underweight/normal weight, overweight and obese.

aIndicates P-value < 0.05.

Among all possible multiple combinations of the adiponectin markers, only percent HMW adiponectin had a statistically significant effect on prostate cancer [percent HMW effect (P = 0.04), BMI category (P = 0.10), interaction (P = 0.05)]. Among normal and overweight men, the risk of prostate cancer increased as percent HMW adiponectin increased [OR = 1.24 for a doubling of percent HMW adiponectin, 95% confidence interval (CI), 0.41–3.75 and OR = 1.81; 95% CI, 1.02–3.20, respectively], whereas among obese men, the risk of prostate cancer decreased (OR = 0.62; 95% CI, 0.32–1.18). Figure 1 shows the dependence of prostate cancer risk on percent HMW adiponectin for the 3 BMI groups according to the model. This figure confirmed that overweight men had a higher probability of prostate cancer as percent HMW adiponectin increased; agreeing with Table 2 that percent HMW adiponectin was significantly higher among cancer cases in the overweight group. Among 87 patients who underwent radical prostatectomy and who had both biopsy and prostatectomy Gleason score available, 30 men had a pathologic biopsy Gleason score of 7 or higher and 20 men had an upgrading of Gleason score from biopsy to prostatectomy (Table 3). There was no association between upgrading of Gleason score on prostatectomy and any of the adiponectin multimers, as well as among multiple combinations of the multimers with BMI.

Figure 1.

Risk of prostate cancer according to weight group. Multivariable logistic regression was used to assess the joint effect of adiponectin measures and interaction with BMI.

Figure 1.

Risk of prostate cancer according to weight group. Multivariable logistic regression was used to assess the joint effect of adiponectin measures and interaction with BMI.

Close modal
Table 3.

Gleason score characteristics of the cohort

Prostatectomy Gleason score
Gleason score56789Total
 
Biopsy Gleason score 37 14 54 
 11 22 
 
 
 Total 47 27 87 
Prostatectomy Gleason score
Gleason score56789Total
 
Biopsy Gleason score 37 14 54 
 11 22 
 
 
 Total 47 27 87 

Mounting evidence indicates that obesity is positively associated with the development of prostate cancer (27). A possible molecular link for this association is adiponectin, an adipose tissue-produced cytokine with anticancer properties that is paradoxically decreased in obese subjects (3). As this adipokine has been reported to be inversely associated with prostate cancer risk, tumor grade, and aggressiveness (8–12), and because studies heretofore have only examined total adiponectin and not its multimers, which exhibit different biological activities (3), we examined multimers of this adipokine to determine if they could serve as biomarkers to improve the detection of potentially lethal prostate cancer.

In our study, adiponectin levels decreased with increasing levels of obesity, as expected. In contrast to most previous reports, we found no differences in any of the adiponectin measures between prostate cancer cases and controls; there was no relationship between total adiponectin levels and risk of prostate cancer. We did find that the risk of prostate cancer increased as the percent HMW adiponectin increased for normal and overweight men, whereas the opposite was found for obese subjects (Fig. 1). Interestingly, a previous study reported that serum adiponectin levels were higher in men with locally advanced cancers (15). A second study found that in normal-weight men with prostate cancer, adiponectin was positively associated with high-stage disease, suggesting that adiponectin may be related to cancer aggressiveness; however, adiponectin levels were inversely associated with high-grade disease in overweight and obese men (16). Unfortunately, none of these studies evaluated adiponectin multimers. The authors of the former study speculated that the increased adiponectin levels might be a protective response against tumor progression. We did not examine the association of adiponectin with tumor stage. Nevertheless, speculating along the lines of Housa and colleagues (15), because HMW adiponectin is well known for its antiproliferative effects on prostate cancer cells (6), perhaps the increased risk of prostate cancer as the percent HMW adiponectin increases in normal and overweight men in our study reflects an appropriate antitumor response. Such an antitumor response may be compromised in obese subjects because of metabolic dysfunction and concurrent downregulation of adiponectin production, which would be expressed as an inverse association between percent adiponectin and risk of prostate cancer. Although this may explain the differential effects of percent HMW adiponectin on prostate cancer risk in our study, it is also possible that this finding is spurious because of the low power for the interactions in our model. Indeed, a significant number of studies seem to indicate that adiponectin levels are inversely related to cancer development and progression.

There are other possible explanations for why the results from our study differ from the majority of previous studies. First, our cohort has a higher average BMI compared with those from other studies, which reflects the higher rates of obesity in South Texas than in the rest of the nation (28). For example, the average BMI in our control and case groups was 27.8 and 28.7, respectively, compared with the Physicians' Health Study average BMI of 24.7 and 24.6 for their control and case groups, respectively (11). Moreover, 30% of the men in our study were extremely obese (BMI ≥ 30), which was 10 times higher than the same group in the Physicians' Health Study. Because PSA levels are lower in overweight/obese men because of hemodilutional effects (29), and because PSA levels are used to determine who should undergo biopsy, it is possible that there were undetected cases of prostate cancer in our control group. Such would be expected to suppress the average total adiponectin levels in the control group. Second, as DRE is also utilized to determine who undergoes biopsy, undetected prostate cancer cases in our control group may have also been increased because of the relatively large number of Hispanic men in our cohort (approximately 40%) who are less likely to have a DRE (unpublished observation). Third, comorbidities that are associated with obesity and whose prevalence are greater among Hispanics, such as diabetes and hypertension (30, 31), can impair kidney function, which is known to increase adiponectin levels (32); this might further obscure adiponectin's association with prostate cancer risk or disease prognosis. Thus, total adiponectin and its multimers had no independent predictive value for either detection or disease prognosis in our cohort, which was composed of 30% men with extreme obesity and 40% men who were Hispanic. Our findings, and the possible explanations for the disparate results between our study and previous ones, suggest that the utilizing adiponectin and its multimers as biomarkers that predict either the presence of prostate cancer or the risk of Gleason score upgrading (a measure of disease prognosis) at radical prostatectomy may be limited, particularly among men at the extremes of obesity or of particular ethnic groups, as they are more susceptible to comorbidities that may influence circulating adiponectin levels.

Our study of adiponectin as a biomarker for prostate cancer has limitations and strengths. Only in a study of full ascertainment of prostate cancer risk (in which all patients undergo prostate biopsy) can it be certain that controls are truly disease free. However, even if biopsy is performed in all cancer-free individuals, this cannot ensure that controls are cancer free. The study's strength lies in the fact that it is a prospective follow-up of community-dwelling men who are not part of a referred population. By defining controls as men who had 5 years of subsequent cancer-free follow-up, we significantly reduced the risk that some may harbor significant, potentially lethal tumors at the time of sample collection. The most important strength of this study was the inclusion of adiponectin multimers to fully explore the relationships beyond simply total adiponectin alone.

Although adiponectin may play a role in the pathogenesis of prostate cancer, our results do not support adiponectin and its multimers as biomarkers of detection or of disease prognosis.

No potential conflicts of interest were disclosed.

Conception and design: D.P. Ankerst, C. Livi, I.M. Thompson Jr, R.J. Leach

Development of methodology: D.P. Ankerst, C. Livi, R.J. Leach

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): C. Livi, I.M. Thompson Jr, R.J. Leach

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): E.A. Medina, X. Shi, D.P. Ankerst, M.V. Medina, I.M. Thompson Jr

Writing, review, and/or revision of the manuscript: E.A. Medina, X. Shi, D.P. Ankerst, M.V. Medina, I.M. Thompson Jr, R.J. Leach

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M.H. Grayson, C. Livi, M.V. Medina, I.M. Thompson Jr

Study supervision: D.P. Ankerst, I.M. Thompson Jr, R.J. Leach

This work was sponsored in part by grants U01CA86402 (IMT) and 5P30 CA0541474 (IMT). E.A. Medina was supported by KL2 TR000118 from the NIH National Center for Advancing Translational Sciences.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Carbone
F
,
La Rocca
C
,
Matarese
G
. 
Immunological functions of leptin and adiponectin
.
Biochimie
2012
;
94
:
2082
8
.
2.
Yamauchi
T
,
Kadowaki
T
. 
Adiponectin receptor as a key player in healthy longevity and obesity-related diseases
.
Cell Metab
2013
;
17
:
185
96
.
3.
Dalamaga
M
,
Diakopoulos
KN
,
Mantzoros
CS
. 
The role of adiponectin in cancer: a review of current evidence
.
Endocr Rev
2012
;
33
:
547
94
.
4.
Piya
MK
,
McTernan
PG
,
Kumar
S
. 
Adipokine inflammation and insulin resistance: the role of glucose, lipids and endotoxin
.
J Endocrinol
2013
;
216
:
T1
T15
.
5.
Vansaun
MN
. 
Molecular pathways: adiponectin and leptin signaling in cancer
.
Clin Cancer Res
2013
;
19
:
1926
32
.
6.
Bub
JD
,
Miyazaki
T
,
Iwamoto
Y
. 
Adiponectin as a growth inhibitor in prostate cancer cells
.
Biochem Biophys Res Commun
2006
;
340
:
1158
66
.
7.
Mistry
T
,
Digby
JE
,
Desai
KM
,
Randeva
HS
. 
Leptin and adiponectin interact in the regulation of prostate cancer cell growth via modulation of p53 and bcl-2 expression
.
BJU Int
2008
;
101
:
1317
22
.
8.
Goktas
S
,
Yilmaz
MI
,
Caglar
K
,
Sonmez
A
,
Kilic
S
,
Bedir
S
. 
Prostate cancer and adiponectin
.
Urology
2005
;
65
:
1168
72
.
9.
Sher
DJ
,
Oh
WK
,
Jacobus
S
,
Regan
MM
,
Lee
GS
,
Mantzoros
C
. 
Relationship between serum adiponectin and prostate cancer grade
.
Prostate
2008
;
68
:
1592
8
.
10.
Arisan
ED
,
Arisan
S
,
Atis
G
,
Palavan-Unsal
N
,
Ergenekon
E
. 
Serum adipocytokine levels in prostate cancer patients
.
Urol Int
2009
;
82
:
203
8
.
11.
Li
H
,
Stampfer
MJ
,
Mucci
L
,
Rifai
N
,
Qiu
W
,
Kurth
T
, et al
A 25-year prospective study of plasma adiponectin and leptin concentrations and prostate cancer risk and survival
.
Clin Chem
2010
;
56
:
34
43
.
12.
Burton
A
,
Martin
RM
,
Holly
J
,
Lane
JA
,
Donovan
JL
,
Hamdy
FC
, et al
Associations of adiponectin and leptin with stage and grade of PSA-detected prostate cancer: the ProtecT study
.
Cancer Causes Control
2013
;
24
:
323
34
.
13.
Dhillon
PK
,
Penney
KL
,
Schumacher
F
,
Rider
JR
,
Sesso
HD
,
Pollak
M
, et al
Common polymorphisms in the adiponectin and its receptor genes, adiponectin levels and the risk of prostate cancer
.
Cancer Epidemiol Biomarkers Prev
2011
;
20
:
2618
27
.
14.
Barb
D
,
Neuwirth
A
,
Mantzoros
CS
,
Balk
SP
. 
Adiponectin signals in prostate cancer cells through Akt to activate the mammalian target of rapamycin pathway
.
Endocr Relat Cancer
2007
;
14
:
995
1005
.
15.
Housa
D
,
Vernerova
Z
,
Heracek
J
,
Prochazka
B
,
Cechak
P
,
Kuncova
J
, et al
Adiponectin as a potential marker of prostate cancer progression: studies in organ-confined and locally advanced prostate cancer
.
Physiol Res
2008
;
57
:
451
8
.
16.
Freedland
SJ
,
Sokoll
LJ
,
Platz
EA
,
Mangold
LA
,
Bruzek
DJ
,
Mohr
P
, et al
Association between serum adiponectin, and pathological stage and grade in men undergoing radical prostatectomy
.
J Urol
2005
;
174
:
1266
70
.
17.
Baillargeon
J
,
Platz
EA
,
Rose
DP
,
Pollock
BH
,
Ankerst
DP
,
Haffner
S
, et al
Obesity, adipokines, and prostate cancer in a prospective population-based study
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
1331
5
.
18.
Lopez Fontana
CM
,
Maselli
ME
,
Perez Elizalde
RF
,
Di Milta Monaco
NA
,
Uvilla Recupero
AL
,
Lopez Laur
JD
. 
Leptin increases prostate cancer aggressiveness
.
J Physiol Biochem
2011
;
67
:
531
8
.
19.
Tonelli
J
,
Li
W
,
Kishore
P
,
Pajvani
UB
,
Kwon
E
,
Weaver
C
, et al
Mechanisms of early insulin-sensitizing effects of thiazolidinediones in type 2 diabetes
.
Diabetes
2004
;
53
:
1621
9
.
20.
Aso
Y
,
Yamamoto
R
,
Wakabayashi
S
,
Uchida
T
,
Takayanagi
K
,
Takebayashi
K
, et al
Comparison of serum high-molecular weight (HMW) adiponectin with total adiponectin concentrations in type 2 diabetic patients with coronary artery disease using a novel enzyme-linked immunosorbent assay to detect HMW adiponectin
.
Diabetes
2006
;
55
:
1954
60
.
21.
Baessler
A
,
Schlossbauer
S
,
Stark
K
,
Strack
C
,
Riegger
G
,
Schunkert
H
, et al
Adiponectin multimeric forms but not total adiponectin levels are associated with myocardial infarction in non-diabetic men
.
J Atheroscler Thromb
2011
;
18
:
616
27
.
22.
Chen
MW
,
Ye
S
,
Zhao
LL
,
Wang
SY
,
Li
YX
,
Yu
CJ
, et al
Association of plasma total and high-molecular-weight adiponectin with risk of colorectal cancer: an observational study in Chinese male
.
Med Oncol
2012
;
29
:
3129
35
.
23.
Moyer
VA
. 
Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement
.
Ann Intern Med
2012
;
157
:
120
34
.
24.
Serkin
FB
,
Soderdahl
DW
,
Cullen
J
,
Chen
Y
,
Hernandez
J
. 
Patient risk stratification using Gleason score concordance and upgrading among men with prostate biopsy Gleason score 6 or 7
.
Urol Oncol
2010
;
28
:
302
7
.
25.
Liang
Y
,
Ankerst
DP
,
Ketchum
NS
,
Ercole
B
,
Shah
G
,
Shaughnessy
JD
 Jr
, et al
Prospective evaluation of operating characteristics of prostate cancer detection biomarkers
.
J Urol
2011
;
185
:
104
10
.
26.
Ebinuma
H
,
Miida
T
,
Yamauchi
T
,
Hada
Y
,
Hara
K
,
Kubota
N
, et al
Improved ELISA for selective measurement of adiponectin multimers and identification of adiponectin in human cerebrospinal fluid
.
Clin Chem
2007
;
53
:
1541
4
.
27.
Allott
EH
,
Masko
EM
,
Freedland
SJ
. 
Obesity and prostate cancer: weighing the evidence
.
Eur Urol
2013
;
63
:
800
9
.
28.
Texas Behavioral Risk Factor Surveillance System Combined Year Dataset, Statewide BRFSS Survey, 2002–2005
.
Center for Health Statistics Community Assessment Texas Department of State Health Services
.
29.
Banez
LL
,
Hamilton
RJ
,
Partin
AW
,
Vollmer
RT
,
Sun
L
,
Rodriguez
C
, et al
Obesity-related plasma hemodilution and PSA concentration among men with prostate cancer
.
JAMA
2007
;
298
:
2275
80
.
30.
Sullivan
PW
,
Ghushchyan
VH
,
Ben-Joseph
R
. 
The impact of obesity on diabetes, hyperlipidemia and hypertension in the United States
.
Qual Life Res
2008
;
17
:
1063
71
.
31.
Romero
CX
,
Romero
TE
,
Shlay
JC
,
Ogden
LG
,
Dabelea
D
. 
Changing trends in the prevalence and disparities of obesity and other cardiovascular disease risk factors in three racial/ethnic groups of USA adults
.
Adv Prev Med
2012
;
2012
:
172423
.
32.
Looker
HC
,
Krakoff
J
,
Funahashi
T
,
Matsuzawa
Y
,
Tanaka
S
,
Nelson
RG
, et al
Adiponectin concentrations are influenced by renal function and diabetes duration in Pima Indians with type 2 diabetes
.
J Clin Endocrinol Metab
2004
;
89
:
4010
7
.