Obesity inversely correlates with prostate-specific antigen levels in a population with normal screening results of prostate cancer in northwestern China

Zhang, J.; Ma, Mingju; Nan, Xunyi; Sheng, Binwu

doi:10.1590/1414-431x20165272

Cited by 20 publications

(20 citation statements)

References 30 publications

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“…The PheWAS performed on the SNP associations in this study's BMI cohort identified strong 599 associations of elevated PSA levels with variants in FTO, and indicates that the number of minor 600 alleles of these variants is predictive of elevated PSA. This finding is in contradiction to the reports 601 (Bañez et al 2007;Oh et al 2013;Zhang et al 2016;Bonn et al 2016) indicating an inverse 602 relationship between PSA levels and BMI. However, serum levels of PSA may be elevated due to 603 reasons other than prostatic malignancy.…”

Section: Phewas Of Healthy Nevada Bmi and Obesity 592mentioning

confidence: 64%

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

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Lombardi

et al. 2019

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21The aggregation of Election Health Records (EHR) and personalized genetics leads to powerful 22 discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) 23 and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype 24 associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic 25 and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the 26 Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants 27 that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine 28 associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant 29 SNPs, BMI, and incidence of extreme obesity. The first GWAS excludes DM2-diagnosed individuals 30 and focuses on associations with BMI exclusively. The second GWAS examines the interplay between 31 Type 2 Diabetes (DM2) and BMI. The intersection of significant variants of these two studies is 32 surprising. The third complementary case-control GWAS, with cases defined as extremely obese (Class 33 2 or 3 obesity), identifies strong associations with extreme obesity, including established variants in the 34 FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published 35 associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet 36 also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR 37 database to validate known associations and identify putative novel links with BMI and obesity. 38 39 2014; Qureshi et al. 2017; Huđek et al. 2018; Gonzalez-Herrera et al. 2018), none, to the best of our 63 knowledge, have included comprehensive GWASs on the quantitative BMI metric and on extreme 64 obesity case-control simultaneously, as well as investigated phenotypic associations with BMI, obesity, 65 and significant loci identified by the GWAS. 66 67 Our study begins with the Healthy Nevada Project (HNP), a project centered around a Northern Nevada 68 cohort formed in 2016 and 2017 by Renown Health and the Desert Research Institute in Reno, NV to 69 4investigate factors that may contribute to health outcomes in Northern Nevada. Its first phase provided 70 10,000 individuals in Northern Nevada with genotyping using the 23andMe platform at no cost. 71Renown Health is the only tertiary care health system in the area, and 75% of these 10,000 individuals 72 are cross-referenced in its extensive electronic health records (EHR) database. The Renown EHR 73 database contains 86,610 BMI measurements for these 10,000 individuals over twelve years, along 74 with comprehensive disease diagnoses, (e.g. diabetes or eating disorders) and other general conditions 75 such as pregnancy, allowing for precise individual phenotypic classifications and thereby leading to 76 more robust and meaningful phenotype-genotype associations. 77 78The focus ...

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Section: Phewas Of Healthy Nevada Bmi and Obesity 592mentioning

confidence: 64%

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

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Lombardi

et al. 2019

Preprint

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“…Measures were made at the end of normal expiration with special attention paid to ensure the tape was positioned perpendicular to the long axis of the body and parallel to the oor. A series of four measurements were taken by a single, trained researcher from the right side at the following anatomical locations: i) superior border of the iliac crest, ii) midpoint between the iliac crest and the lowest rib, iii) umbilicus, and iv) minimal waist (18). Waist-to-hip ratio (WHtR) was calculated as WC in centimeters divided by height in centimeters and multiply by a hundred (percentage, %).…”

Section: Determination Of Obesity Factorsmentioning

confidence: 99%

An Inverse Association of Weight and the Occurrence of Asymptomatic Gallbladder Stone Disease in Hypercholesterolemia Patients in Northwest China: A Case-Control Study.

Sheng¹,

Zhao²,

Ma³

et al. 2020

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Background Despite the fact that the majority of gallstones formed in the gallbladder are mainly composed of cholesterol, as they are formed from cholesterol-supersaturated bile, there is still no consensus regarding the contribution of blood serum lipids in the pathogenesis of gallbladder stone disease (GSD). Here, we aimed to investigate the relationship between hypercholesterolemia and the risk of new-onset asymptomatic GSD, and to determine the prevalence of factors associated with new-onset asymptomatic GSD in patients with hypercholesterolemia.Methods In this case-control study, we enrolled 927 Chinese patients with new-onset asymptomatic gallstone disease and 845 healthy controls starting in August 2012. Patients were matched for age, gender, race, occupation, systolic blood pressure, diastolic blood pressure, and fasting blood glucose levels (FBG). Body mass index, nonalcoholic fatty liver disease (NAFLD) and serum lipids indexes were compared and the relationships between BMI, blood lipid and gallbladder stone hazards were examined by using logistic multivariate regression models.Results The result showed a significant higher morbidity with GSD in hypercholesterolemia than non-hypercholesterolemia patients (X2=17.211, P<0.001). Of hypercholesterolemia patients, LDL-c (OR=1.493, P=0.029) and NAFLD (OR=2.723, P=0.022) were significant risk factors for GSD, while male sex (OR=0.244, P=0.033), weight (OR=0.961, P=0.022), HDL-c (OR=0.305, P<0.001), and FBG (OR=0.687, P=0.034) significantly negatively correlated with GSD in univariate analysis. Multivariate logistic regression indicated weakly positive correlations with NAFLD (OR=3.284, P=0.054), and significant negative correlations with weight (OR=0.930, P=0.018), HDL-c (OR=0.144, P<0.001), and GSD. Conclusion Hypercholesterolemia acts as an independent risk factor for new-onset asymptomatic GSD, while obesity and NAFLD are synergistic factors. Interestingly, we are the first to report that elevated weight was inversely associated with GSD in patients with hypercholesterolemia.

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“…Prostate cancer is top on the list among causes of cancer-related deaths in men and ranks as the second most common cancer after lung cancer the world over [1]. In Nigeria, there is a gradual trend of rising prostate cancer cases which is attributable to increasing urbanization and changing dietary habit as well as the increased awareness towards the use of health facilities leading to more cases being documented.…”

Section: Introductionmentioning

confidence: 99%

“…Body mass index (BMI) has been linked with aggressive prostate cancer by some studies but its association still requires to be properly established as previous studies have disputed a clear pattern of relationship [2]. Some studies suggest that the effect of BMI on serum prostatespecific antigen levels is inversely related meaning that in obesity or high BMI there is decreased concentration of PSA [1,2]. It is on this premise therefore that some investigators think that obesity, as evidenced by high BMI, might reduce the sensitivity of screening for prostate cancer with prostate-specific antigen (PSA) [3].…”

Section: Introductionmentioning

confidence: 99%

“…This apparent decrease in sensitivity or of PSA concentration was attributed to the dilution effect resulting from raised plasma volume in obese individuals [3]. High BMI as a strong indicator of obesity, is said to be responsible for the myriad of co-morbidities and is on the rise in transitioning economies like Nigeria [1]. Age and ageing have been associated with changes in prostate-specific antigen level, prostate volume and prostatespecific antigen density (PSAD) with elevations seen with increasing age [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Body Mass Index and Age Correlation with Prostate-specific Antigen Density as Prostate Cancer Risk Indicators in a Screened Male University Population in Nigeria: A Pilot Study

Eyam

Bassey

Isiwele

et al. 2019

JCTI

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Background: Prostate-specific antigen density (PSAD) is one of the means of improving PSA sensitivity as a marker of a prostate cancer diagnosis. However, this ability is perceived to be obscured by certain factors such as high body mass index and age in Caucasian and western populations, which tends to reduce its sensitivity and lead to misclassification of at-risk patients for prostate cancer. Aim: We studied the correlation of body mass index (BMI) and age with prostate-specific antigen density (PSAD) as indicators of prostate cancer risk in a screened male population(40 years and above) in the University of Calabar, Nigeria. Study Design: A cross-sectional analytical study with consecutive participant recruitment. Place and Duration of Study: The study was carried out in the University of Calabar Medical centre during a medical outreach. Materials and Methods: The study involved sixty-one (61) healthy male participants. BMI was mathematically determined from the weight and height and was categorized as underweight, normal weight, overweight and obesity based on the WHO classification with values of <18.5, 18.5-24.9, 25.0-29.9, and ≥30 (Kg/m2) respectively. Blood samples were collected and analyzed for PSA and transrectal ultrasound scan was done to estimate the prostate volume and was used to calculate the prostate-specific antigen density. Results: Over 67% of participants had PSA values below 4.0 ng/ml, 14.8% between 4.0-10.0 ng/ml, and 18% above 10.0 ng/ml. Body mass index (BMI) assessment revealed that 1.6% of the sampled population had BMI <18.5 Kg/m2, 32.8% had BMI between 18.5 Kg/m2 and 24.9 Kg/m2, while 50.8% were noticed to have a BMI of between 25.0 Kg/m2 and 29.9 Kg/m2, and 14.8% had BMI of 30 Kg/m2 and above. Conclusion: There was an inverse correlation of BMI with prostate-specific antigen density (PSAD) and a direct correlation of age with PSAD in this study of Nigerian men.

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Obesity inversely correlates with prostate-specific antigen levels in a population with normal screening results of prostate cancer in northwestern China

Cited by 20 publications

References 30 publications

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

An Inverse Association of Weight and the Occurrence of Asymptomatic Gallbladder Stone Disease in Hypercholesterolemia Patients in Northwest China: A Case-Control Study.

Body Mass Index and Age Correlation with Prostate-specific Antigen Density as Prostate Cancer Risk Indicators in a Screened Male University Population in Nigeria: A Pilot Study

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