Independent Study Populations Research Articles

Proteomic signature of HIV-associated subclinical left atrial remodeling and incident heart failure

People living with HIV are at higher risk of heart failure and associated left atrial remodeling compared to people without HIV. Mechanisms are unclear but have been linked to inflammation and premature aging. Here we obtain plasma proteomics concurrently with cardiac magnetic resonance imaging in two independent study populations to identify parallels between HIV-related and aging-related immune dysfunction that could contribute to atrial remodeling and clinical heart failure. We discover a plasma proteomic signature that may in part reflect or contribute to HIV-associated atrial remodeling, many features of which are associated with older age and time to incident heart failure among an independent community-based cohort without HIV. This proteomic profile was statistically enriched for immune checkpoint proteins, tumor necrosis factor signaling, ephrin signaling, and extracellular matrix organization, identifying possible shared pathways in HIV and aging that may contribute to risk of heart failure.

Conclusions Regarding the Role of Expectations in Placebo Analgesia Studies May Depend on How We Investigate It: A Meta-Analysis, Systematic Review, and Proposal for Methodological Discussions.

Expectations are highlighted as a key component in placebo effects. However, there are different approaches to whether and how placebo studies should account for expectations, and the direct contribution has yet to be estimated in meta-analyses. Using different methodological approaches, this meta-analysis and systematic review examines the extent to which expectations contribute to pain in placebo studies. The databases PubMed, PsycINFO, Embase, and Web of Science were searched for placebo analgesia mechanism studies with numerical measures of both expectations and pain. Thirty-one studies, comprising 34 independent study populations (1566 subjects: patients and healthy participants) were included. Two meta-analyses were conducted: meta-analysis 1, using study-level data, estimated the effect of expectation interventions without taking measures of expectations into account (expectations assumed); and meta-analysis 2, using individual-level data, estimated the direct impact of participants' expectations on pain (expectations assessed). Risk of bias was assessed using the Cochrane risk-of-bias tool. Meta-analysis 1 showed a moderate effect of expectation interventions over no expectation intervention on pain intensity (Hedges g = 0.45, I2 = 54.19). Based on 10 studies providing individual-level data, meta-analysis 2 showed that expectations predicted pain intensity in placebo and control groups ( b = 0.36, SE = 0.05), although inconsistently across study methodologies. Participants' expectations contributed moderately to pain in placebo analgesia studies. However, this may largely be influenced by how we measure expectations and how their contribution is conceptualized and analyzed-both within and across studies.

Sociodemographic and Clinical Characteristics of People Living with Dementia and Their Associations with Unmet Healthcare Needs: Insights from the Baseline Assessment of the InDePendent Study.

The healthcare needs of People living with Dementia (PlwD) (such as Alzheimer's disease) are often unmet. Information about the needs of community-dwelling PlwD and their association with sociodemographic and clinical characteristics is needed to fill the knowledge gap regarding factors influencing unmet needs among PlwD and to conduct a comprehensive needs assessment to develop tailored interventions. To describe sociodemographic and clinical characteristics of the InDePendent study population with particular reference to determinants of unmet needs. We analyzed baseline data of the multi-centre cluster-randomized controlled trial (InDePendent) using descriptive statistics to describe patients' sociodemographic and clinical characteristics and Poisson regression models to predict unmet needs, separated by sex. Data were collected personally via face-to-face interviews. Most of the n = 417 participating PlwD were mild to moderately cognitively impaired, were not depressed, had an average of 10.8 diagnoses, took 6.7 medications, and had, on average, 2.4 unmet needs (62% of PlwD had at least one unmet need) measured by the Camberwell Assessment of Need for the Elderly (CANE). Low social support, a high body-mass-index, a lower education, functional impairment, and worse health status were associated with more unmet needs, regardless of sex. In women, higher unmet needs were associated with more depressive symptoms, a poor financial situation, living alone and not being recently treated by a general practitioner. In males, unmet needs increased with the number of medications taken. PlwD had a broad array of unmet healthcare needs, indicating primary healthcare provision improvement potentials. The results underscore the significance of early assessment of patient's clinical characteristics and unmet needs as a basis for individualized gender-sensible intervention strategies.∥ClinicalTrials.gov Identifier: NCT04741932, Registered on February 5, 2021.

Sex-specific and polygenic effects underlying resting heart rate and associated risk of cardiovascular disease.

Resting heart rate (RHR) is associated with cardiovascular disease (CVD) and mortality. This study aimed to identify genetic loci associated with RHR, develop a genome-wide polygenic risk score (PRS) for RHR, and assess associations between the RHR PRS and CVD outcomes, to better understand the biological mechanisms linking RHR to disease. Sex-specific analyses were conducted to potentially elucidate different pathways between the sexes. We performed a genome-wide meta-analysis of RHR (n = 550 467) using two independent study populations, The Trøndelag Health Study (HUNT) and the UK Biobank (UKB), comprising 69 155 and 481 312 participants, respectively. We also developed a genome-wide PRS for RHR using UKB and tested for association between the PRS and 13 disease outcomes in HUNT. We identified 403, 253, and 167 independent single nucleotide polymorphisms (SNPs) significantly associated with RHR in the total population, women, and men, respectively. The sex-specified analyses indicated differences in the genetic contribution to RHR and revealed loci significantly associated with RHR in only one of the sexes. The SNPs were mapped to genes enriched in heart tissue and cardiac conduction pathways, as well as disease-pathways, including dilated cardiomyopathy. The PRS for RHR was associated with increased risk of hypertension and dilated cardiomyopathy, and decreased risk of atrial fibrillation. Our findings provide insight into the pleiotropic effects of the RHR variants, contributing towards an improved understanding of mechanisms linking RHR and disease. In addition, the sex-specific results might contribute to a more refined understanding of RHR as a risk factor for the different diseases.

Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection.

To develop and evaluate a deep learning (DL) model to assess fundus photograph quality, and quantitatively measure its impact on automated POAG detection in independent study populations. Image quality ground truth was determined by manual review of 2815 fundus photographs of healthy and POAG eyes from the Diagnostic Innovations in Glaucoma Study and African Descent and Glaucoma Evaluation Study (DIGS/ADAGES), as well as 11,350 from the Ocular Hypertension Treatment Study (OHTS). Human experts assessed a photograph as high quality if of sufficient quality to determine POAG status and poor quality if not. A DL quality model was trained on photographs from DIGS/ADAGES and tested on OHTS. The effect of DL quality assessment on DL POAG detection was measured using area under the receiver operating characteristic (AUROC). The DL quality model yielded an AUROC of 0.97 for differentiating between high- and low-quality photographs; qualitative human review affirmed high model performance. Diagnostic accuracy of the DL POAG model was significantly greater (P < 0.001) in good (AUROC, 0.87; 95% CI, 0.80-0.92) compared with poor quality photographs (AUROC, 0.77; 95% CI, 0.67-0.88). The DL quality model was able to accurately assess fundus photograph quality. Using automated quality assessment to filter out low-quality photographs increased the accuracy of a DL POAG detection model. Incorporating DL quality assessment into automated review of fundus photographs can help to decrease the burden of manual review and improve accuracy for automated DL POAG detection.

Lymph node regression after neoadjuvant chemoradiotherapy in rectal cancer.

Lymph node metastases (LNM) are one of the most important prognostic indicators in solid tumours and a major component of cancer staging. Neoadjuvant therapy might influence nodal status by induction of regression. Our aim is to determine the prevalence and role of regression of LNM on outcomes in patients with rectal cancer. Four independent study populations of rectal cancer patients treated with similar regimens of chemoradiotherapy were pooled together to obtain a total cohort of 469 patients. Post-treatment nodal status (ypN) and signs of tumour regression (Reg) were incorporated to form three-tiered (ypN- Reg+, ypN- Reg- and ypN+) and four-tiered (ypN- Reg+, ypN- Reg-, ypN+ Reg+ and ypN+ Reg-) classifications. In our cohort, 31% of patients presented with ypN+ rectal cancer. As expected, we found significantly worse overall survival (OS) in ypN+ patients compared to ypN- patients (P = 0.002). The percentage of ypN- patients with lymph nodes with complete regression was 20% in our cohort. While node-negative patients with and without regression had similar OS (P = 0.09), disease-free survival (DFS) was significantly better in node-negative patients with regression (P = 0.009). Regression in lymph nodes is frequent, and node-negative patients with evidence of lymph node regression have better DFS compared to node-negative patients without such evidence.

CKD-EPI and EKFC GFR Estimating Equations: Performance and Other Considerations for Selecting Equations for Implementation in Adults.

New eGFR equations from Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) using creatinine (eGFRcr), cystatin C (eGFRcys), and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice, leading to uncertainty in selecting equations for implementation. The authors evaluated performance of equations in an independent population of 4050 adults and evaluated other considerations important for implementation. They found that CKD-EPI and EKFC equations are approaching convergence, with better performance of eGFRcr-cys equations in the overall group and fewer differences among race, sex, and age subgroups than eGFRcr equations. Larger differences among eGFRcr equations reflect regional population differences in creatinine, forcing a trade-off between accuracy and uniformity in global implementation of eGFRcr equations. More widespread use of cystatin C could avoid this trade-off. New CKD-EPI and EKFC eGFR equations using eGFRcr, eGFRcys, and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice. A better understanding of the equations, including their performance in race, sex and age subgroups, is important for selection of eGFR equations for global implementation. We evaluated performance (bias and P 30 ) of equations and methods used for equation development in an independent study population comprising 4050 adults pooled from 12 studies. The mean (SD) measured GFR was 76.4 (29.6) ml/min per 1.73 m 2 and age 57.0 (17.4) years, with 1557 (38%) women and 579 (14%) Black participants. Coefficients for creatinine, cystatin C, age, and sex in the CKD-EPI and EKFC equations are similar. Performance of the eGFRcr-cys equations in the overall population (bias <±5 ml/min per 1.73 m 2 and P 30 >90%) was better than the eGFRcr or eGFRcys equations, with fewer differences among race, sex, and age subgroups. Differences in performance across subgroups reflected differences in diversity of source populations and use of variables for race and sex for equation development. Larger differences among eGFRcr equations reflected regional population differences in non-GFR determinants of creatinine. CKD-EPI and EKFC equations are approaching convergence. It is not possible to maximize both accuracy and uniformity in selecting one of the currently available eGFRcr equations for implementation across regions. Decisions should consider methods for equation development in addition to performance. Wider use of cystatin C with creatinine could maximize both accuracy and uniformity of GFR estimation using currently available equations.

Validation of novel DNA methylation markers in cervical precancer and cancer.

We have recently identified, using a genome-wide approach, new methylation markers which were evaluated among various cervical intraepithelial neoplasia (CIN) grades and cervical cancer. We herein validate the methylated state of these genes in independent study populations, based on histology ascertained outcomes regardless of human papillomavirus status. CA10, DPP10, FMN2 and HAS1 (discovery set: 54 normal, 50 CIN1, 40 CIN2, 42 CIN3) were evaluated by targeted bisulfite next generation sequencing (NGS) (Illumina MiSeq platform) in 258 (training set: 100 normal, 50 CIN1, 50 CIN2, 50 CIN3, 8 cancers) and 373 (validation set: 100 normal, 57 CIN1, 61 CIN2, 53 CIN3, 102 cancers) physician-collected samples (PreservCyt). Using targeted amplification NGS data from the training set for 94 normal and eight cancer samples, we calculated for each gene the median methylation value. These were summed and normalized to compute a four-gene Marker Polygenic Score (MPS). We compared the relationship between MPS and progression from normal through CIN grades and cancer, separately in the training and validation sets, and tested its clinical performance via receiver-operating characteristic curves. MPS increased with increasing CIN grade, and accurately predicted cervical cancer in the training (area under the curve, AUC = 0.9950) and validation (AUC = 0.9337) sets, comparing normal to cancer. Using the highest threshold of 100% specificity, sensitivity for detection of cervical cancer was 67.7%; whereas reducing specificity to 95% increased sensitivity to 84.3%. Further evaluation of these biomarkers is warranted in prospective studies.

Serum Metabolomic Markers of Dairy Consumption: Results from the Atherosclerosis Risk in Communities Study and the Bogalusa Heart Study

BackgroundDairy consumption is related to chronic disease risk; however, the measurement of dairy consumption has largely relied upon self-report. Untargeted metabolomics allows for the identification of objective markers of dietary intake. ObjectivesWe aimed to identify associations between dietary dairy intake (total dairy, low-fat dairy, and high-fat dairy) and serum metabolites in 2 independent study populations of United States adults. MethodsDietary intake was assessed with food frequency questionnaires. Multivariable linear regression models were used to estimate cross-sectional associations between dietary intake of dairy and 360 serum metabolites analyzed in 2 subgroups of the Atherosclerosis Risk in Communities study (ARIC; n = 3776). Results from the 2 subgroups were meta-analyzed using fixed effects meta-analysis. Significant meta-analyzed associations in the ARIC study were then tested in the Bogalusa Heart Study (BHS; n = 785). ResultsIn the ARIC study and BHS, the mean age was 54 and 48 years, 61% and 29% were Black, and the mean dairy intake was 1.7 and 1.3 servings/day, respectively. Twenty-nine significant associations between dietary intake of dairy and serum metabolites were identified in the ARIC study (total dairy, n = 14; low-fat dairy, n = 10; high-fat dairy, n = 5). Three associations were also significant in BHS: myristate (14:0) was associated with high-fat dairy, and pantothenate was associated with total dairy and low-fat dairy, but 23 of the 27 associations significant in the ARIC study and tested in BHS were not associated with dairy in BHS. ConclusionsWe identified metabolomic associations with dietary intake of dairy, including 3 associations found in 2 independent cohort studies. These results suggest that myristate (14:0) and pantothenate (vitamin B5) are candidate biomarkers of dairy consumption.

Association of sickle cell trait with adverse pregnancy outcomes in a population-based cohort.

Sickle cell trait (SCT) is common in African descendants. Its association with several adverse pregnancy outcomes (APOs) has been reported but remains inconsistent. The objectives of this study are to test associations of SCT with APOs in non-Hispanic Black women, including (1) validate the associations of SCT with previously reported APOs, (2) test novel associations of SCT with broad spectrum of APOs, and (3) estimate the attributable risk of SCT for implicated APOs. This is a retrospective analysis of a prospectively designed population-based cohort. Women/participants were self-reported non-Hispanic Black women from the UK Biobank (UKB). SCT status was determined based on heterozygous Glu6Val in the HBB gene. Several APOs were studied, including four previously reported SCT-associated APOs (preeclampsia, bacteriuria, pregnancy loss, and preterm delivery), and broad conditions related to pregnancy, childbirth, and the puerperium. APOs were curated by experts' peer review and consensus processes. Associations of SCT with APOs were tested by estimating its relative risk and 95% confidence interval (95% CI), adjusting for number of live births and age at first birth. Attributable risk proportion (ARP) and population attributable risk proportion (PARP) of SCT to APOs were estimated. Among the 4057 self-reported non-Hispanic Black women with pregnancy records in the UKB, 581 (14.32%) were SCT carriers. For four previously reported SCT-associated APOs, two were confirmed at a nominal P < 0.05; relative risk (RR) was 2.39 (95% CI 1.09-5.23) for preeclampsia, and 4.85 (95% CI 1.77-13.27) for bacteriuria. SCT contributed substantially to these two APOs among SCT carriers, with attributable risk proportion estimated at 61.00% and 68.96% for preeclampsia and bacteriuria, respectively. SCT also contributed substantially to these two APOs in the population (self-reported Black UK women), with population attributable risk proportion estimated at 18.30% and 24.14% for preeclampsia and bacteriuria, respectively. In addition, novel associations were found for seven other APOs (nominal P < 0.05). SCT is significantly associated with APOs in this study and contributes substantially to APOs among self-reported Black women in the UK. Confirmation of these findings in independent study populations is required.

AI-Driven sleep staging from actigraphy and heart rate.

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.

Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization.

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10-9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10-4-5.79 × 10-14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10-4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10-4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10-4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3- B cells, CD5+IgD- cells, IgM- cells, IgD-IgM- cells, and CD4-CD8- PBMCs (p = 4.9 × 10-4-8.6 × 10-4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27- cells (p = 9.3 × 10-4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3-, MCP-2-, and IL20-dependent pathways.

Optimum threshold of the 4Kscore for biopsy in men with negative or indeterminate multiparametric magnetic resonance imaging.

The study aims to identify the optimal 4Kscore thresholds to determine the need for a prostate biopsy when multiparametric magnetic resonance imaging (MRI) (mpMRI) is negative or indeterminate. We analysed retrospective data from men in eight different institutions who underwent an mpMRI, 4Kscore and prostate biopsy for evaluation of prostate cancer. We selected men with a negative (PIRADS ≤2) or indeterminate (PIRADS 3) mpMRI. 4Kscore values were categorized into ranges of 1-7, 8-19, 20-32 and greater than 32. We evaluated the proportion of men with grade group 2 or higher (GG2+) cancer in groups defined by PIRADS and 4Kscore. We also evaluated the number of biopsies avoided and GG2+ cancer missed in each group reported depend on 4Kscore cutoff points. Among 1111 men who had an mpMRI, 4Kscore and biopsy, 625 of them had PIRADS ≤3 on mpMRI: 374 negative (PIRADS ≤2) and 251 indeterminate (PIRADS 3). In men with a negative mpMRI, we found a 4Kscore cut-point of 33 resulted in an increased risk of GG2+ cancer on biopsy. In patients with an equivocal lesion on mpMRI, men with a 4Kscore cutoff ≥8 had a greater risk of GG2+ cancer on biopsy. Decision curve analysis supported the proposed cut-points in each mpMRI group. In men with negative and indeterminate mpMRI, we found the best 4Kscore threshold to determine the need for biopsy to be 33 and 8 respectively. Future prospective studies in independent populations are needed to confirm these findings.

MP24-12 ASSOCIATION OF RARE MONOGENIC VARIANTS WITH DIAGNOSIS OF BPH USING WHOLE EXOME SEQUENCING IN THE UK BIOBANK

You have accessJournal of UrologyCME1 Apr 2023MP24-12 ASSOCIATION OF RARE MONOGENIC VARIANTS WITH DIAGNOSIS OF BPH USING WHOLE EXOME SEQUENCING IN THE UK BIOBANK Clark Judge, David Nusbaum, Jun Wei, Zhuqing Shi, Andrew Rifkin, S. Lilly Zheng, Brian Helfand, Alexander Glaser, and Jianfeng Xu Clark JudgeClark Judge More articles by this author , David NusbaumDavid Nusbaum More articles by this author , Jun WeiJun Wei More articles by this author , Zhuqing ShiZhuqing Shi More articles by this author , Andrew RifkinAndrew Rifkin More articles by this author , S. Lilly ZhengS. Lilly Zheng More articles by this author , Brian HelfandBrian Helfand More articles by this author , Alexander GlaserAlexander Glaser More articles by this author , and Jianfeng XuJianfeng Xu More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003249.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Benign prostatic hyperplasia (BPH) is a common condition that leads to bothersome lower urinary tract symptoms. Polygenic heritability of BPH has been demonstrated using genetic risk scores derived from common single nucleotide polymorphisms, but rare monogenic gene mutations associated with BPH have not been well described. The objective of this study was to determine the impact of rare monogenic variants on the development of BPH. METHODS: A total of 83,631 men from the UK Biobank (UKB) with whole exome sequencing data were included and categorized based on ICD10 diagnosis of BPH (N40). Of men with BPH, 9,697 were further characterized as undergoing transurethral resection of prostate (TURP). The robust SKAT-O, a novel gene-based analysis of pathogenic/likely pathogenic mutations that properly controls for type I error rates due to unbalanced case-control ratio, was used for association tests adjusting for age at recruitment and genetic background. RESULTS: Nineteen candidate genes were identified as associated with BPH in 9,697 cases compared to 73,934 controls at p<0.001 using SKAT-O (Table). However, none of these associations was significant after adjusting for multiple testing (FDR<0.05). For most of these genes, higher carrier rates in patients undergoing TURP was also found. CONCLUSIONS: In this large study of nearly 84,000 men, several candidate genes were identified. Confirmation in independent study populations is required. Identification of monogenic gene mutations associated with BPH may advance our understanding of disease etiology and identify potential therapeutic targets. Source of Funding: NA © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e322 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Clark Judge More articles by this author David Nusbaum More articles by this author Jun Wei More articles by this author Zhuqing Shi More articles by this author Andrew Rifkin More articles by this author S. Lilly Zheng More articles by this author Brian Helfand More articles by this author Alexander Glaser More articles by this author Jianfeng Xu More articles by this author Expand All Advertisement PDF downloadLoading ...

MP41-12 ASSOCIATION OF KIDNEY CANCER WITH BOTH NOVEL AND REPORTED MONOGENIC GENE MUTATIONS: RESULTS OF WHOLE EXOME SEQUENCING IN THE UK BIOBANK

You have accessJournal of UrologyCME1 Apr 2023MP41-12 ASSOCIATION OF KIDNEY CANCER WITH BOTH NOVEL AND REPORTED MONOGENIC GENE MUTATIONS: RESULTS OF WHOLE EXOME SEQUENCING IN THE UK BIOBANK Jun Wei, Kristian Novakovic, Zhuqing Shi, Andrew Rifkin, S. Lilly Zheng, Brian Helfand, and Jianfeng Xu Jun WeiJun Wei More articles by this author , Kristian NovakovicKristian Novakovic More articles by this author , Zhuqing ShiZhuqing Shi More articles by this author , Andrew RifkinAndrew Rifkin More articles by this author , S. Lilly ZhengS. Lilly Zheng More articles by this author , Brian HelfandBrian Helfand More articles by this author , and Jianfeng XuJianfeng Xu More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003279.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Pathogenic mutations in several cancer susceptibility genes have been reported in kidney cancer patients. However, their associations with kidney cancer have not been formally tested in well-characterized case-control studies and using the same sequencing and analytical pipeline. The objective of this study was to systematically evaluate association of kidney cancer with genes in the exome in a well-characterized prospective population-based case-control cohort. METHODS: A total of 187,966 subjects from the UK Biobank (UKB) with whole exome sequencing data were included in the analysis, including 1,217 kidney cancer patients (ICD10 C64). Pathogenic/likely pathogenic (P/LP) mutations were annotated based on criteria of the American College of Medical Genetics. The robust SKAT-O, a novel gene-based analysis that properly controls for type I error rates due to unbalanced case-control ratio, was used for association tests adjusting for age at recruitment, gender and genetic background. RESULTS: Among the 21 previously reported candidate genes, three were statistically significant at P<0.05, including VHL, SDHB, and CHEK2 (Table). In addition, associations with 9 novel genes (at P<0.0001) were found, including ZNF772, PRIMPOL, HES4, MOXD1, KRTAP10-9, ZNF827, ACAN, CDK20, and LRRFIP1. While these associations were only marginally significant after adjusting for multiple testing, they have potential roles in cancer development. For example, ZNF772 is predicted to enable DNA-binding transcription factor activity, RNA polymerase II-specific and RNA polymerase II cis-regulatory region sequence-specific DNA binding activity which are all known to be dysregulated in cancer. CONCLUSIONS: Identification of genes that influence kidney cancer may advance our understanding of disease etiology and identify potential therapeutic targets. Using the same sequencing method and mutation annotation pipeline in the largest population-based cohort to date, we confirmed several previously reported genes and identified several novel candidate genes for their association with kidney cancer. Confirmation in independent study populations is required for these novel candidate genes. Source of Funding: None. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e559 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jun Wei More articles by this author Kristian Novakovic More articles by this author Zhuqing Shi More articles by this author Andrew Rifkin More articles by this author S. Lilly Zheng More articles by this author Brian Helfand More articles by this author Jianfeng Xu More articles by this author Expand All Advertisement PDF downloadLoading ...

Validation of the ONKOTEV Risk Prediction Model for Venous Thromboembolism in Outpatients With Cancer

The assessment of the risk of venous thromboembolism (VTE) among outpatients with cancer represents an unsolved topic. Current international guidelines recommend primary prophylaxis for patients at intermediate to high risk of VTE, indicated by a Khorana score of 2 or more. A previous prospective study developed the ONKOTEV score, a 4-variable risk assessment model (RAM) consisting of a Khorana score of more than 2, metastatic disease, vascular or lymphatic compression, and previous VTE event. To validate the ONKOTEV score as a novel RAM to assess the risk of VTE among outpatients with cancer. ONKOTEV-2 is a noninterventional prognostic study conducted in 3 European centers located in Italy, Germany, and the United Kingdom among a prospective cohort of 425 ambulatory patients with a histologically confirmed diagnosis of a solid tumor who were receiving active treatments. The total study duration was 52 months, with an accrual period of 28 months (from May 1, 2015, to September 30, 2017) and an overall follow up-period of 24 months (data were censored September 30, 2019). Statistical analysis was performed in October 2019. The ONKOTEV score was calculated for each patient at baseline by collecting clinical, laboratory, and imaging data from tests performed for routine practice. Each patient was then observed to detect any thromboembolic event throughout the study period. The primary outcome of the study was the incidence of VTE, including deep vein thrombosis and pulmonary embolism. A total of 425 patients (242 women [56.9%]; median age, 61 years [range, 20-92 years]) were included in the validation cohort of the study. The cumulative incidences for the risk of developing VTE at 6 months were 2.6% (95% CI, 0.7%-6.9%), 9.1% (95% CI, 5.8%-13.2%), 32.3% (95% CI, 21.0%-44.1%), and 19.3% (95% CI, 2.5%-48.0%), respectively, among 425 patients with an ONKOTEV score of 0, 1, 2, and greater than 2 (P < .001). The time-dependent area under the curve at 3, 6, and 12 months was 70.1% (95% CI, 62.1%-78.7%), 72.9% (95% CI, 65.6%-79.1%), and 72.2% (95% CI, 65.2%-77.3%), respectively. This study suggests that, because the ONKOTEV score has been validated in this independent study population as a novel predictive RAM for cancer-associated thrombosis, it can be adopted into practice and into clinical interventional trials as a decision-making tool for primary prophylaxis.

Is non-alcoholic fatty liver disease a sign of left ventricular diastolic dysfunction in patients with type 2 diabetes mellitus? A systematic review and meta-analysis

Recent studies have associated non-alcoholic fatty liver disease (NAFLD) with impaired cardiac function. However, patients with type 2 diabetes mellitus (T2DM), a high-risk group for left ventricular diastolic dysfunction (LVDD),...

Plasma Protein Biomarkers of Healthy Dietary Patterns: Results from the Atherosclerosis Risk in Communities Study and the Framingham Heart Study

BackgroundMolecular mechanisms underlying the benefits of healthy dietary patterns are poorly understood. Identifying protein biomarkers of dietary patterns can contribute to characterizing biological pathways influenced by food intake. ObjectivesThis study aimed to identify protein biomarkers associated with four indexes of healthy dietary patterns: Healthy Eating Index-2015 (HEI-2015); Alternative Healthy Eating Index-2010 (AHEI-2010); DASH diet; and alternate Mediterranean Diet (aMED). MethodsAnalyses were conducted on 10,490 Black and White men and women aged 49–73 y from the ARIC study at visit 3 (1993–1995). Dietary intake data were collected using a food frequency questionnaire, and plasma proteins were quantified using an aptamer-based proteomics assay. Multivariable linear regression models were used to examine the association between 4955 proteins and dietary patterns. We performed pathway overrepresentation analysis for diet-related proteins. An independent study population from the Framingham Heart Study was used for replication analyses. ResultsIn the multivariable-adjusted models, 282 out of 4955 proteins (5.7%) were significantly associated with at least one dietary pattern (HEI-2015: 137; AHEI-2010: 72; DASH: 254; aMED: 35; P value < 0.05/4955 = 1.01 × 10−5). There were 148 proteins that were associated with only one dietary pattern (HEI-2015: 22; AHEI-2010: 5; DASH: 121; aMED: 0), and 20 proteins were associated with all four dietary patterns. Five unique biological pathways were significantly enriched by diet-related proteins. Seven out of 20 proteins associated with all dietary patterns in the ARIC study were available for replication analyses, and 6 out of these 7 proteins were consistent in direction and significantly associated with at least 1 dietary pattern in the Framingham Heart Study (HEI-2015: 2; AHEI-2010: 4; DASH: 6; aMED: 4; P value < 0.05/7 = 7.14 × 10−3). ConclusionsA large-scale proteomic analysis identified plasma protein biomarkers that are representative of healthy dietary patterns among middle-aged and older US adult population. These protein biomarkers may be useful objective indicators of healthy dietary patterns.

Genome-Wide Association Study of Metachronous Colorectal Adenoma Risk among Participants in the Selenium Trial

Genetic variants related to colorectal adenoma may help identify those who are at highest risk of colorectal cancer development or illuminate potential chemopreventive strategies. The purpose of this genome-wide association study was to identify genetic variants that are associated with risk of developing a metachronous colorectal adenoma among 1,215 study participants of European descent from the Selenium Trial. Associations of variants were assessed with logistic regression analyses and validated in an independent case-control study population of 1,491 participants from the Colorectal Cancer Study of Austria (CORSA). No statistically significant genome-wide associations between any variant and metachronous adenoma were identified after correction for multiple comparisons. However, an intron variant of FAT3 gene, rs61901554, showed a suggestive association (P = 1.10 × 10−6) and was associated with advanced adenomas in CORSA (P = 0.04). Two intronic variants, rs12728998 and rs6699944 in NLRP3 were also observed to have suggestive associations with metachronous lesions (P = 2.00 × 10−6) in the Selenium Trial and were associated with advanced adenoma in CORSA (P = 0.03). Our results provide new areas of investigation for the genetic basis of the development of metachronous colorectal adenoma and support a role for FAT3 involvement in the Wnt/β-catenin pathway leading to colorectal neoplasia. Trial Registration number: NCT00078897 (ClinicalTrials.gov).

P-538 KATNAL1 polymorphisms confer susceptibility to severe phenotypes of male infertility in a large European cohort

Abstract Study question What is the contribution of the common variation of KATNAL1 to the development of severe spermatogenic failure (SPGF) in a phenotypically well-characterized cohort? Summary answer An allelic combination of KATNAL1 single-nucleotide polymorphisms (SNPs) increases the risk to develop SPGF, likely by altering the expression and splicing pattern of the gene. What is known already Spermatogenesis is a process that requires an exhaustive control of gene expression, and subtle alterations of its molecular regulatory network can lead to male infertility. The aetiology of most SPGF cases remains unknown, and increasing evidence clearly suggests that the idiopathic form of SPGF represents a complex trait, in which genetic susceptibility is conferred by the accumulation of risk alleles in genetically predisposed men. In this regard, previous studies reported that rare genetic mutations and polymorphisms in the KATNAL1 locus lead to male infertility through the disruption of microtubule remodelling and premature germ cell exfoliation. Study design, size, duration We designed a case-control genetic association study including three SNPs (rs2077011, rs7338931, and rs2149971) in the 3' and 5' regulatory regions of KATNAL1, which tagged the common genetic variability in the region. The allele frequencies in the study population, composed of 715 infertile men diagnosed with idiopathic SPGF, were compared to those observed in a control group comprising 1058 fertile men from Spain and Portugal. Participants/materials, setting, methods The SPGF group comprised 210 men with severe oligospermia (SO) and 505 with non-obstructive azoospermia (NOA). The latter were phenotypically characterised according to the histological examination of testis biopsies and its outcome (Sertoli cell-only syndrome, SCO; maturation arrest, MA; hypospermatogenesis, HS; and testicular sperm extraction, TESE). After genotyping, case-control association analyses by logistic regression were conducted. In silico functional characterization of risk variants was also carried out using public multiomic databases and bioinformatic tools. Main results and the role of chance Significant genetic associations with different SPGF patterns and/or TESE outcome were observed even after correction for multiple testing when independent SNP models were tested. However, in all cases, the haplotype model including the three risk alleles (rs2077011*C | rs7338931*T | rs2149971*A) was the most informative. This haplotype was specifically over-represented in the SPGF group (P = 3.45E-02, OR = 2.33), which includes all infertile men, and in the NOA group (P = 8.22E-03, OR = 2.97). In addition, subtype-specific associations were observed with the most severe subgroups, namely MA (P = 2.44E-02, OR = 5.00), SCO (P = 4.03E-03, OR = 5.16), and unsuccessful TESE outcome (P = 2.22E-04, OR = 6.13), which indicates the relevant role of KATNAL1 in spermatogenesis development. We prioritized the most likely causal variant/s based on in silico analyses addressing the possible functional implication of the tagged variants. We observed that an alteration of the KATNAL1 splicing pattern, by favouring the overrepresentation of a short non-functional transcript isoform in the testis, might be the cause behind the observed genetic association. The analysis of the testis transcriptome at the single cell level showed that KATNAL1 transcripts were mostly presented in spermatocytes and early spermatids at puberty, which correlates with its effect of premature exfoliation and loss of the germ cells. Limitations, reasons for caution Although a previous low-powered study reported suggestive associations between KATNAL1 and SPGF, additional genetic association studies in independent populations should be conducted to confirm our findings. Moreover, the statistical power for the overall analysis was appropriate, but the subphenotype analyses were performed with reduced power due to smaller study groups. Wider implications of the findings Our results suggest a relevant role of the common genetic variation of KATNAL1 in the susceptibility to develop the most severe histological phenotypes of NOA (i.e., SCO and MA). Studies like the one presented here may definitively help to develop future non-invasive molecular markers of TESE success. Trial registration number Not Applicable