Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease.

BACKGROUND: This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aß) 42/Aß40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening. METHODS: Quantification of plasma pTau217R and Aß42/Aß40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts. RESULTS: Models integrating pTau217R outperformed Aß42/Aß40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%. DISCUSSION: pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aß42/Aß40's range. Combining it with plasma Aß42/Aß40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility. GOV IDENTIFIERS: NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3-45), NCT03887455 (ClarityAD) HIGHLIGHTS: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aß42/Aß40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid.

Predicting clinical progression trajectories of early Alzheimer's disease patients.

BACKGROUND: Models for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring. METHODS: Prediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures. RESULTS: The model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2-year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model-based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%. DISCUSSION: Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.

Urinary miRNAs Predict Metastasis in Patients With Clinically Localized Clear Cell Renal Cell Carcinoma Treated With Nephrectomy.

PURPOSE: Patients with clear cell renal cell carcinoma (ccRCC) might develop metastasis after surgery with curative intent. We aimed to characterize the expression levels of microRNAs in the urine (UmiRNAs) of patients before and after nephrectomy to determine the impact of UmiRNAs expression in the emergence of metastases. METHODS: We prospectively collected pre- and post-nephrectomy urine samples from 117 patients with clinically localized and locally advanced ccRCC. UmiRNAs were extracted, purified, and measured using RT-PCR. Relative quantifications (RQ) of 137 UmiRNAs were calculated through 2-∆∆ method. The post-surgery/pre-surgery RQs ratio represented the magnitude of the expression levels of the UmiRNAs. The association of UmiRNA expression and the development of distant metastases was tested with Cox regression model. RESULTS: Five UmiRNAs (miR-191-5p, miR-324-3p, miR-186-5p, miR-93-5p, miR-30b-5p) levels were upregulated before nephrectomy (p < .05). This conferred a 2- to 4-fold increased risk of metastasis, with miR-191-5p showing the most significant association with this endpoint (HR = 4.16, 95% CI = 1.38-12.58, p = .011). In a multivariate model stratified with stage and Fuhrman grade, we found that miR-191-5p, miR-324-3p, and miR-186-5p exhibited a strong association with metastasis development in patients with pathological T3 (pT3) tumors. Enrichment analysis with the most differentially expressed UmiRNAs showed that these UmiRNAs targeted genes that regulate cell survival and proliferation. CONCLUSION: Our study indicated UmiR-191-5p, UmiR-324-3p, and UmiR-186-5p are potential markers to predict the development of metastasis, particularly in pT3 patients. PATIENT SUMMARY: We compared changes of UmiRNAs expression detected pre- and postnephrectomy of patients with ccRCC. Our findings suggest that UmiRNA expression likely reflects tumor-specific changes that can be promising to predict the metastasis development, particularly in patients with non-metastatic locally advanced ccRCC. If confirmed, these findings may be useful for surveillance protocols for adjuvant therapy protocols.

Preparation and characterisation of linalool oil-in-water starch-based Pickering emulsions and the effects of the addition of cellulose nanocrystals on their stability.

Creaming could be generated during storage of the starch-based Pickering emulsions. And cellulose nanocrystals in the solution are usually dispersed by relatively strong mechanical force, otherwise they may appear in the form of aggregates. In this work, we investigated the effects of cellulose nanocrystals on the stability of the starch-based Pickering emulsions. Results showed that the stability of Pickering emulsions was significantly improved by adding cellulose nanocrystals. Cellulose nanocrystals increased the viscosity, electrostatic repulsion and steric hindrance of the emulsions, which delayed the movement of droplets and obstructed the contact between droplets. This study provides new insights into the preparation and stabilisation of starch-based Pickering emulsions.

Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights.

BACKGROUND: Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology. OBJECTIVE: To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data. DESIGN, SETTING, AND PARTICIPANTS: Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking. RESULTS AND LIMITATIONS: Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10-8) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [pM-I] = 0.004), 8q21.13 (PAG1; pM-I = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; pM-I = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers. CONCLUSIONS: We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer. PATIENT SUMMARY: We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer.

Body mass index and survival after cancer diagnosis: A pan-cancer cohort study of 114 430 patients with cancer.

The recommendation encouraging patients with cancer to keep a normal body mass index (BMI) is largely extrapolated from data on risk of developing cancer. We tested the prospective association between peri-diagnostic (within 1 year post-diagnosis) BMI and all-cause mortality in patients with incident cancers. During 7.2 years of follow-up, 42% (48,340) of the 114 430 patients with cancer died. Spline analysis revealed that compared with a BMI of 22.5, a BMI lower than 22.5 was associated with increased risk of all-cause mortality across 24 cancer types. A BMI higher than 22.5 was associated with reduced all-cause mortality, while a non-linear association was observed; the lowest risk was found at a BMI of 29.6-34.2, and the risk started to return to and above unity at very high BMI values. The reduced mortality risk of high BMI was observed in 23 of 24 cancer types and maintained after attempts to remove potential selection bias, confounding by smoking and comorbidities, and reserve causality. Compared with a normal BMI of 18.5-24.9, the hazard ratios were 0.85 (95% confidence interval [CI], 0.83-0.87) for an overweight BMI (25-29.9) and 0.82 (0.80-0.85) for an obese BMI (≥30), and the associations were generally consistent across cancer types and various subgroups. Obese BMI was associated with increased life expectancy, up to 6 years among men and 3 years among women. In conclusion, while overweight/obese BMI increases the risk of developing cancer in the general population, overweight/obese peri-diagnostic BMI was associated with longer survival in cancer patients.

Trends and Correlates of Breakthrough Infections With SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant has been hypothesized to decrease the efficacy of COVID-19 vaccines. Factors associated with infections with SARS-CoV-2 after vaccination are unknown. In this observational cohort study, we examined two groups in Harris County, Texas: (1) individuals with positive Nucleic Acid Amplification test between 12/14/2020 and 9/30/2021 and (2) the subset of individuals fully vaccinated in the same time period. Infected individuals were classified as a breakthrough if their infection occurred 14 days after their vaccination had been completed. Among fully vaccinated individuals, demographic and vaccine factors associated with breakthrough infections were assessed. Of 146,731 positive SARS-CoV-2 tests, 7.5% were breakthrough infections. Correlates of breakthrough infection included young adult age, female, White race, and receiving the Janssen vaccine, after adjustments including the amount of community spread at the time of infection. Vaccines remained effective in decreasing the probability of testing positive for SARS-CoV-2. The data indicate that increased vaccine booster uptake would help decrease new infections.

A whole-exome case-control association study to characterize the contribution of rare coding variation to pancreatic cancer risk.

Pancreatic cancer is a deadly disease that accounts for approximately 5% of cancer deaths worldwide, with a dismal 5-year survival rate of 10%. Known genetic risk factors explain only a modest proportion of the heritable risk of pancreatic cancer. We conducted a whole-exome case-control sequencing study in 1,591 pancreatic cancer cases and 2,134 cancer-free controls of European ancestry. In our gene-based analysis, ATM ranked first, with a genome-wide significant p value of 1 × 10-8. The odds ratio for protein-truncating variants in ATM was 24, which is substantially higher than prior estimates, although ours includes a broad 95% confidence interval (4.0-1000). SIK3 was the second highest ranking gene (p = 3.84 × 10-6, false discovery rate or FDR = 0.032). We observed nominally significant association signals in several genes of a priori interest, including BRCA2 (p = 4.3 × 10-4), STK11 (p = 0.003), PALB2 (p = 0.019), and TP53 (p = 0.037), and reported risk estimates for known pathogenic variants and variants of uncertain significance (VUS) in these genes. The rare variants in established susceptibility genes explain approximately 24% of log familial relative risk, which is comparable to the contribution from established common susceptibility variants (17%). In conclusion, this study provides new insights into the genetic susceptibility of pancreatic cancer, refining rare variant risk estimates in known pancreatic cancer susceptibility genes and identifying SIK3 as a novel candidate susceptibility gene. This study highlights the prominent importance of ATM truncating variants and the underappreciated role of VUS in pancreatic cancer etiology.

Land use mix and leukocyte telomere length in Mexican Americans.

It has been well-known that built environment features influence the risk of chronic diseases. However, the existing data of its relationship with telomere length, a biomarker of biological aging, is still limited, with no study available for Mexican Americans. This study investigates the relationship between several factors of the built environment with leukocyte telomere length among 5508 Mexican American adults enrolled in Mano-A-Mano, the Mexican American Cohort Study (MACS). Based on the quartile levels of telomere length, the study population was categorized into four groups, from the lowest (1st quartile) to the highest telomere length group (4th quartile). For individual built environment factors, their levels did not differ significantly across four groups. However, in the multinominal logistic regression analysis, increased Rundle's land use mixture (LUM) and Frank's LUM were found statistically significantly associated with increased odds of having high levels of telomere length (Rundle's LUM: 2nd quartile: Odds ratio (OR) 1.26, 95% Confidence interval (CI) 1.07, 1.48; 3rd quartile: OR 1.25, 95% CI 1.06, 1.46; 4th quartile: OR 1.19, 95% CI 1.01, 1.41; Frank's LUM: 2nd quartile: OR 1.34, 95% CI 1.02, 2.63; 3rd quartile: OR 1.55, 95% CI 1.04, 2.91; 4th quartile: OR 1.36, 95% CI 1.05, 2.72, respectively). The associations for Rundle's LUM remained significant after further adjusting other non-redundant built environment factors. Finally, in stratified analysis, we found the association between Rundle's LUM and telomere length was more evident among younger individuals (< 38 years old), women, and those with obesity, born in Mexico, having low levels of physical activity, and having low levels of acculturation than their relative counterparts. In summary, our results indicate that land use mixture may impact telomere length in leukocytes in Mexican Americans.

Impact of Wuhan lockdown on the spread of COVID-19 in China: a study based on the data of population mobility.

This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstly，estimate the daily new infection rate in Wuhan before January 23，2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 days，assuming that the daily new infection in Wuhan after January 23 increased in a high，moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on that，calculate the number of infection cases imported from Wuhan during this period. Finally，predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%，0.026%，0.029%，0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23，2020. If Wuhan lockdown measure had been delayed for 7 days，the daily new infection rate on January 30 would have been 0.335% in the exponential growth model，0.129% in the linear growth model，and 0.070% in the logarithm growth model. Correspondingly，there would have been 32 075，24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland China，and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.

Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.

:To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.

Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.

:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8，2020，the information of 151 confirmed cases in Yueqing，Zhejiang province were obtained，including patients' infection process，population mobility between Yueqing and Wuhan，etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical models，integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemic，the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170，the actual monitoring number of cases in Yueqing as of April 27，2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.

Human ribonuclease 1 serves as a secretory ligand of ephrin A4 receptor and induces breast tumor initiation.

Human ribonuclease 1 (hRNase 1) is critical to extracellular RNA clearance and innate immunity to achieve homeostasis and host defense; however, whether it plays a role in cancer remains elusive. Here, we demonstrate that hRNase 1, independently of its ribonucleolytic activity, enriches the stem-like cell population and enhances the tumor-initiating ability of breast cancer cells. Specifically, secretory hRNase 1 binds to and activates the tyrosine kinase receptor ephrin A4 (EphA4) signaling to promote breast tumor initiation in an autocrine/paracrine manner, which is distinct from the classical EphA4-ephrin juxtacrine signaling through contact-dependent cell-cell communication. In addition, analysis of human breast tumor tissue microarrays reveals a positive correlation between hRNase 1, EphA4 activation, and stem cell marker CD133. Notably, high hRNase 1 level in plasma samples is positively associated with EphA4 activation in tumor tissues from breast cancer patients, highlighting the pathological relevance of the hRNase 1-EphA4 axis in breast cancer. The discovery of hRNase 1 as a secretory ligand of EphA4 that enhances breast cancer stemness suggests a potential treatment strategy by inactivating the hRNase 1-EphA4 axis.

Allostatic score and its associations with demographics, healthy behaviors, tumor characteristics, and mitochondrial DNA among breast cancer patients.

INTRODUCTION: Allostatic load (AL), a composite index, has been used to capture variation in life-course stresses. However, few studies have been carried out among breast cancer patients. METHODS: In this study, we examined the cross-sectional association of AL with demographics, healthy behaviors, tumor characteristics, and mitochondrial DNA copy number in breast cancer patients. The study used a sub-sample of 934 women with newly diagnosed breast cancer at M.D. Anderson from 2013 to 2018. To construct the AL score, the study used a battery of seventeen factors that represents the activity of five physiological systems: metabolic, cardiovascular, immunological, renal, and liver. RESULTS: AL was positively associated with the age of disease diagnosis (P = 0.002), and was higher in Black and Hispanic populations than White (P = 0.001 and 0.032, respectively). AL was also found more abundant in those who experienced marital dissolution (P = 0.006), lacked a college education (P = 0.045), currently smoked (P = 0.011), and had low levels of physical activity (P = 0.037) than their counterparts. The study then found that higher AL was associated with increased odds of having poorly differentiated tumors (Odds ratio (OR): 1.40, 95% confidence interval (CI): 1.28, 1.62). An additional significant association was observed between AL with estrogen receptor negative (ER-) (OR = 1.56, 95%CI: 1.02, 2.36) among Black patients. Finally, we observed a significant positive correlation between AL with leukocyte mitochondrial DNA copy number variation (P < 0.001). CONCLUSIONS: We conclude AL is influenced by selected demographics and healthy behaviors, and further is correlated with tumor characteristics and mitochondrial DNA copy number in breast cancer patients.

Immune checkpoint-related serum proteins and genetic variants predict outcomes of localized prostate cancer, a cohort study.

BACKGROUND: The clinical predictors and biological mechanisms for localized prostate cancer (PCa) outcomes remain mostly unknown. We aim to evaluate the role of serum immune-checkpoint-related (ICK) proteins and genetic variations in predicting outcomes of localized PCa. METHODS: We profiled the serum levels of 14 ICK-related proteins (BTLA, GITR, HVEM, IDO, LAG-3, PD-1, PD-L1, PD-L2, Tim-3, CD28, CD80, 4-1BB, CD27, and CTLA-4) in 190 patients with localized PCa. The genotypes of 97 single nucleotide polymorphisms (SNPs) from 19 ICK-related genes were analyzed in an extended population (N = 1762). Meta-data from ArrayExpress and TCGA was employed to validate and to probe functional data. Patients were enrolled and tumor aggressiveness, biochemical recurrence (BCR), and progression information were obtained. Statistical analyses were performed analyzing associations between serum biomarkers, genotypes, mRNA and outcomes. RESULTS: We showed that serum (s)BTLA and sTIM3 levels were associated with PCa aggressiveness (P < 0.05). sCD28, sCD80, sCTLA4, sGITR, sHVEM and sIDO correlated with both BCR and progression risks (all P < 0.05). We further identified ICK variants were significantly associated with aggressiveness, BCR and progression. Among them, 4 SNPs located in CD80 (rs7628626, rs12695388, rs491407, rs6804441) were not only associated with BCR and progression risk, but also correlated with sCD80 level (P < 0.01). rs491407 was further validated in an independent cohort. The CD80 mRNA expression was associated with BCR (HR, 1.85, 95% CI 1.06-3.22, P = 0.03) in meta-analysis of validation cohorts. CONCLUSION: We highlight the prognostic value of serum ICK-related proteins for predicting aggressiveness, BCR and progression of PCa. The genetic variations and mRNA expression in CD80 could be predictors and potential targets of localized PCa.

The relationship between body-mass index and overall survival in non-small cell lung cancer by sex, smoking status, and race: A pooled analysis of 20,937 International lung Cancer consortium (ILCCO) patients.

INTRODUCTION: The relationship between Body-Mass-Index (BMI) and lung cancer prognosis is heterogeneous. We evaluated the impact of sex, smoking and race on the relationship between BMI and overall survival (OS) in non-small-cell-lung-cancer (NSCLC). METHODS: Data from 16 individual ILCCO studies were pooled to assess interactions between BMI and the following factors on OS: self-reported race, smoking status and sex, using Cox models (adjusted hazard ratios; aHR) with interaction terms and adjusted penalized smoothing spline plots in stratified analyses. RESULTS: Among 20,937 NSCLC patients with BMI values, females = 47 %; never-smokers = 14 %; White-patients = 76 %. BMI showed differential survival according to race whereby compared to normal-BMI patients, being underweight was associated with poor survival among white patients (OS, aHR = 1.66) but not among black patients (aHR = 1.06; pinteraction = 0.02). Comparing overweight/obese to normal weight patients, Black NSCLC patients who were overweight/obese also had relatively better OS (pinteraction = 0.06) when compared to White-patients. BMI was least associated with survival in Asian-patients and never-smokers. The outcomes of female ever-smokers at the extremes of BMI were associated with worse outcomes in both the underweight (pinteraction<0.001) and obese categories (pinteraction = 0.004) relative to the normal-BMI category, when compared to male ever-smokers. CONCLUSION: Underweight and obese female ever-smokers were associated with worse outcomes in White-patients. These BMI associations were not observed in Asian-patients and never-smokers. Black-patients had more favorable outcomes in the extremes of BMI when compared to White-patients. Body composition in Black-patients, and NSCLC subtypes more commonly seen in Asian-patients and never-smokers, may account for differences in these BMI-OS relationships.

HIF3A DNA methylation, obesity and weight gain, and breast cancer risk among Mexican American women.

OBJECTIVE: In previous epigenome-wide association studies, Hypoxia inducible Factor 3 Alpha Subunit (HIF3A) DNA methylation has been reported to be associated with body mass index (BMI) and weight change. However, none of these studies have included Mexican Americans. METHODS: In the current study, we assessed levels of HIF3A methylation in 927 Mexican American women identified from Mano-A-Mano, the Mexican American Cohort study. RESULTS: Significantly higher methylation levels at three CpG sites (position 46801557, 46801642, and 46801699) were observed in obese women compared to non-obese women (P < 0.05). Furthermore, we found that elevated methylation levels at those three CpG sites were associated with significant weight gain (P < 0.05), defined as an increase in BMI by at least one category between the baseline and the follow-up, with a median follow-up time of 39 months. Then, using pre-diagnostic blood DNA samples, we found increased DNA methylation at CpG 46801642 to be associated with a 1.35-fold increased risk of breast cancer (Hazard Ratio (HR) = 1.35, 95% Confidence Interval (CI): 1.02, 3.01), with a median follow-up time of 127 months. Using the Cancer Genome Atlas (TCGA) data, we further found that levels of HIF3A were significantly higher-methylated and down-regulated in breast tumor than in normal tissues (P < 1 × 1012 for both). CONCLUSION: Thus, our results provide evidence to support the role of HIF3A in obesity, weight gain, and the development of breast cancer.

Validation of plasma metabolites associated with breast cancer risk among Mexican Americans.

In our previous breast cancer case control study in Hispanics, we found 14 metabolites whose levels differed between cases and controls. To validate the results, we carried out a nested case control study of 100 incident breast cancer and 100 matched healthy women identified from the Mano-A-Mano Mexican American Cohort study. With the adjustment of parity, education, birth place, language acculturation, BMI category, smoking, drinking, physical activity, and sitting time, 4 metabolites were associated with breast cancer risk: 3-hydroxyoctanoate (Odds ratio (OR) = 1.51, 95% confidence interval (CI): 1.10, 3.47), 3-hydroxybutyrate (BHBA) (OR = 1.42, 95%CI: 1.01, 3.72), linoleate (18:2n6) (OR = 1.39, 95% CI: 1.07, 4.04), and bilirubin (OR = 0.54, 95%CI: 0.42, 0.95). Then, we used 3 non-redundant metabolites, namely 3-hydroxyoctanoate, linoleate (18:2n6), and bilirubin, to generate a metabolic risk score. Increased metabolites risk score was associated with a 1.67-fold increased risk of breast cancer (OR = 1.67, 95%CI: 1.32, 3.94). And the significant association was more evident among those who were diagnosed with cancer earlier during the follow-up (≤ 5 years) than their counterparts. In conclusion, we identified four significant metabolites which may help elucidate metabolic pathways that contribute to breast carcinogenesis. Our findings warrant further replication efforts.