Blood DNA methylation and liver cancer in American Indians: evidence from the Strong Heart Study

Purpose: Liver cancer incidence among American Indians/Alaska Natives has risen over the past 20 years. Peripheral blood DNA methylation may be associated with liver cancer and could be used as a biomarker for cancer risk. We evaluated the association of blood DNA methylation with risk of liver cancer. Methods: We conducted a prospective cohort study in 2324 American Indians, between age 45 and 75 years, from Arizona, Oklahoma, North Dakota and South Dakota who participated in the Strong Heart Study between 1989 and 1991. Liver cancer deaths (n = 21) were ascertained using death certificates obtained through 2017. The mean follow-up duration (SD) for non-cases was 25.1 (5.6) years and for cases, 11.0 (8.8) years. DNA methylation was assessed from blood samples collected at baseline using MethylationEPIC BeadChip 850 K arrays. We used Cox regression models adjusted for age, sex, center, body mass index, low-density lipoprotein cholesterol, smoking, alcohol consumption, and immune cell proportions to examine the associations. Results: We identified 9 CpG sites associated with liver cancer. cg16057201 annotated to MRFAP1) was hypermethylated among cases vs. non-cases (hazard ratio (HR) for one standard deviation increase in methylation was 1.25 (95% CI 1.14, 1.37). The other eight CpGs were hypomethylated and the corresponding HRs (95% CI) ranged from 0.58 (0.44, 0.75) for cg04967787 (annotated to PPRC1) to 0.77 (0.67, 0.88) for cg08550308. We also assessed 7 differentially methylated CpG sites associated with liver cancer in previous studies. The adjusted HR for cg15079934 (annotated to LPS1) was 1.93 (95% CI 1.10, 3.39). Conclusions: Blood DNA methylation may be associated with liver cancer mortality and may be altered during the development of liver cancer.This work was supported by grants from the National Heart, Lung, and Blood Institute (NHLBI) (Contract Numbers 75N92019D00027, 75N92019D00028, 75N92019D00029 and 75N92019D00030) and previous Grants (R01HL090863, R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and Cooperative Agreements: U01HL41642, U01HL41652, U01HL41654, U01HL65520 and U01HL65521); by the National Institute of Environmental Health Sciences (Grant Numbers R25ES025505, R01ES032638, R01ES021367, R01ES025216, P42ES033719, P30ES009089); by the Chilean CONICYT/FONDECYT-POSTDOCTORADO Nº 3180486 and by a fellowship from “la Caixa” Foundation (ID 100010434) (fellowship code “LCF/BQ/DR19/11740016”). The funders had no role in the planning, conducting, analysis, interpretation, or writing of this study. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the ofcial views of the National Institutes of Health (United States) or the National Health Institute Carlos III (Spain).S

Diabetes Care Among Older Urban American Indians and Alaska Natives

Objective: To assess the prevalence of, and quality of care for, diabetes mellitus among the understudied, yet growing, population of older, urban American Indians and Alaska Natives (AI/ANs). Design: Medical record review. Setting: Urban Indian primary care clinic in Seattle, Washington. Patients: All (N5550) AI/AN patients >=50 years of age. Main Outcomes Measures: Provider-documented medical diagnoses and indicators of quality of care of diabetes. Results: Diabetes mellitus was documented in 113 (21%) of the medical records. Persons with diabetes were more likely than those without (P$.05) to be obese, and to have hypertension, coronary artery disease, and depression. Most patients with diabetes were treated with either insulin (43%) or oral hypoglycemic medication (39%), but 16% received neither. Screening rates within 12 months were high for glycosylated hemoglobin (72%), lipid profile (84%), and foot examination (72%), but were low for urinalysis (23%), ophthalmology referral (23%), and in¯uenza vaccination (46%). Only 46% of patients had ever received pneumococcal vaccination, and even fewer (26%) had received tuberculin skin testing (24%). Although 65% of patients had ever been referred to a dietitian, only 40% had received exercise counseling. The total number of health problems was the factor most often associated with quality of care indicators. Conclusions: The prevalence rate of diabetes among this urban clinic population of older AI/ANs was high. Although performance of quality indicators was suboptimal, it was comparable to, or better than, that found in other older populations for many measures

Choctaw Nation Youth Sun Exposure Survey

The incidence of skin cancer is rising among American Indians (AI) but the prevalence of harmful ultraviolet light (UVL) exposures among AI youth is unknown. In 2013, UVL exposures, protective behaviors, and attitudes toward tanning were assessed among 129 AI and Non-Hispanic (NHW) students in grades 8–12 in Southeastern Oklahoma. Sunburn was reported by more than half the AI students and most of the NHW students. One-third of AI students reported never using sunscreen, compared to less than one-fifth of NHW students, but racial differences were mitigated by propensity to burn. Less than 10% of students never covered their shoulders when outside. Girls, regardless of race, wore hats much less often than boys. Regardless of race or sex, more than one-fourth of students never stayed in the shade, and more than one-tenth never wore sunglasses. The prevalence of outdoor tanning did not differ by race, but more than three-fourths of girls engaged in this activity compared to less than half the boys. Indoor tanning was reported by 45% of the girls, compared to 20% of girls nationwide, with no difference by race. Nearly 10% of boys tanned indoors. Among girls, 18% reported more than ten indoor tanning sessions. Over one-quarter of participants agreed that tanning makes people look more attractive, with no significant difference by race or sex. Investigations of UVL exposures should include AI youth, who have not been represented in previous studies but whose harmful UVL exposures, including indoor tanning, may place them at risk of skin cancer

DNA methylation and cancer incidence: lymphatic-hematopoietic versus solid cancers in the Strong Heart Study.

Epigenetic alterations may contribute to early detection of cancer. We evaluated the association of blood DNA methylation with lymphatic-hematopoietic cancers and, for comparison, with solid cancers. We also evaluated the predictive ability of DNA methylation for lymphatic-hematopoietic cancers. Blood DNA methylation was measured using the Illumina Infinium methylationEPIC array in 2324 Strong Heart Study participants (41.4% men, mean age 56 years). 788,368 CpG sites were available for differential DNA methylation analysis for lymphatic-hematopoietic, solid and overall cancers using elastic-net and Cox regression models. We conducted replication in an independent population: the Framingham Heart Study. We also analyzed differential variability and conducted bioinformatic analyses to assess for potential biological mechanisms. Over a follow-up of up to 28 years (mean 15), we identified 41 lymphatic-hematopoietic and 394 solid cancer cases. A total of 126 CpGs for lymphatic-hematopoietic cancers, 396 for solid cancers, and 414 for overall cancers were selected as predictors by the elastic-net model. For lymphatic-hematopoietic cancers, the predictive ability (C index) increased from 0.58 to 0.87 when adding these 126 CpGs to the risk factor model in the discovery set. The association was replicated with hazard ratios in the same direction in 28 CpGs in the Framingham Heart Study. When considering the association of variability, rather than mean differences, we found 432 differentially variable regions for lymphatic-hematopoietic cancers. This study suggests that differential methylation and differential variability in blood DNA methylation are associated with lymphatic-hematopoietic cancer risk. DNA methylation data may contribute to early detection of lymphatic-hematopoietic cancers.This work was supported by grants from the National Heart, Lung, and Blood Institute (NHLBI) (Contract Numbers 75N92019D00027, 75N92019D00028, 75N92019D00029 and 75N92019D00030) and previous Grants (R01HL090863, R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and Cooperative Agreements: U01HL41642, U01HL41652, U01HL41654, U01HL65520 and U01HL65521); by the National Institute of Environmental Health Sciences (Grant Numbers R01ES021367, R01ES025216, P42ES010349, P30ES009089); by the Chilean CONICYT/FONDECYT-POSTDOCTORADO Nº3180486 and by a fellowship from “la Caixa” Foundation (ID 100010434) (fellowship code “LCF/BQ/DR19/11740016”). The funders had no role in the planning, conducting, analysis, interpretation, or writing of this study. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (United States) or the National Health Institute Carlos III (Spain).S

DNA methylation and cancer incidence: lymphatic–hematopoietic versus solid cancers in the Strong Heart Study

Background Epigenetic alterations may contribute to early detection of cancer. We evaluated the association of blood DNA methylation with lymphatic–hematopoietic cancers and, for comparison, with solid cancers. We also evaluated the predictive ability of DNA methylation for lymphatic–hematopoietic cancers. Methods Blood DNA methylation was measured using the Illumina Infinium methylationEPIC array in 2324 Strong Heart Study participants (41.4% men, mean age 56 years). 788,368 CpG sites were available for differential DNA methylation analysis for lymphatic–hematopoietic, solid and overall cancers using elastic-net and Cox regression models. We conducted replication in an independent population: the Framingham Heart Study. We also analyzed differential variability and conducted bioinformatic analyses to assess for potential biological mechanisms. Results Over a follow-up of up to 28 years (mean 15), we identified 41 lymphatic–hematopoietic and 394 solid cancer cases. A total of 126 CpGs for lymphatic–hematopoietic cancers, 396 for solid cancers, and 414 for overall cancers were selected as predictors by the elastic-net model. For lymphatic–hematopoietic cancers, the predictive ability (C index) increased from 0.58 to 0.87 when adding these 126 CpGs to the risk factor model in the discovery set. The association was replicated with hazard ratios in the same direction in 28 CpGs in the Framingham Heart Study. When considering the association of variability, rather than mean differences, we found 432 differentially variable regions for lymphatic–hematopoietic cancers. Conclusions This study suggests that differential methylation and differential variability in blood DNA methylation are associated with lymphatic–hematopoietic cancer risk. DNA methylation data may contribute to early detection of lymphatic–hematopoietic cancers