Chronic liver disease (CLD) and cirrhosis are major sources of morbidity and mortality in the United States. Little is known about the epidemiology of these two diseases in ethnic minority ...populations in the United States. We examined the prevalence of CLD and cirrhosis by underlying etiologies among African Americans, Native Hawaiians, Japanese Americans, Latinos, and whites in the Multiethnic Cohort. CLD and cirrhosis cases were identified using Medicare claims between 1999 and 2012 among the fee‐for‐service participants (n = 106,458). We used International Classification of Diseases Ninth Revision codes, body mass index, history of diabetes mellitus, and alcohol consumption from questionnaires to identify underlying etiologies. A total of 5,783 CLD (3,575 CLD without cirrhosis and 2,208 cirrhosis) cases were identified. The prevalence of CLD ranged from 3.9% in African Americans and Native Hawaiians to 4.1% in whites, 6.7% in Latinos, and 6.9% in Japanese. Nonalcoholic fatty liver disease (NAFLD) was the most common cause of CLD in all ethnic groups combined (52%), followed by alcoholic liver disease (21%). NAFLD was the most common cause of cirrhosis in the entire cohort. By ethnicity, NAFLD was the most common cause of cirrhosis in Japanese Americans, Native Hawaiians, and Latinos, accounting for 32% of cases. Alcoholic liver disease was the most common cause of cirrhosis in whites (38.2%), while hepatitis C virus was the most common cause in African Americans (29.8%). Conclusions: We showed racial/ethnic variations in the prevalence of CLD and cirrhosis by underlying etiology; NAFLD was the most common cause of CLD and cirrhosis in the entire cohort, and the high prevalence of NAFLD among Japanese Americans and Native Hawaiians is a novel finding, warranting further studies to elucidate the causes. (Hepatology 2016;64:1969‐1977)
Haplotype analysis forms the basis of much of genetic association analysis using both related and unrelated individuals (we concentrate on unrelated). For example, haplotype analysis indirectly ...underlies the SNP imputation methods that are used for testing trait associations with known but unmeasured variants and for performing collaborative post-GWAS meta-analysis. This chapter is focused on the direct use of haplotypes in association testing. It reviews the rationale for haplotype-based association testing, discusses statistical issues related to haplotype uncertainty that affect the analysis, then gives practical guidance for testing haplotype-based associations with phenotype or outcome trait, first of candidate gene regions and then for the genome as a whole. Haplotypes are interesting for two reasons, first they may be in closer LD with a causal variant than any single measured SNP, and therefore may enhance the coverage value of the genotypes over single SNP analysis. Second, haplotypes may themselves be the causal variants of interest and some solid examples of this have appeared in the literature.This chapter discusses three possible approaches to incorporation of SNP haplotype analysis into generalized linear regression models: (1) a simple substitution method involving imputed haplotypes, (2) simultaneous maximum likelihood (ML) estimation of all parameters, including haplotype frequencies and regression parameters, and (3) a simplified approximation to full ML for case-control data.Examples of the various approaches for a haplotype analysis of a candidate gene are provided. We compare the behavior of the approximation-based methods and argue that in most instances the simpler methods hold up well in practice. We also describe the practical implementation of haplotype risk estimation genome-wide and discuss several shortcuts that can be used to speed up otherwise potentially very intensive computational requirements.
Few studies have explored the genetic underpinnings of intra-abdominal visceral fat deposition, which varies substantially by sex and race/ethnicity. Among 1,787 participants in the Multiethnic ...Cohort (MEC)-Adiposity Phenotype Study (MEC-APS), we conducted a genome-wide association study (GWAS) of the percent visceral adiposity tissue (VAT) area out of the overall abdominal area, averaged across L1-L5 (%VAT), measured by abdominal magnetic resonance imaging (MRI). A genome-wide significant signal was found on chromosome 2q14.3 in the sex-combined GWAS (lead variant rs79837492: Beta per effect allele = -4.76; P = 2.62 × 10-8) and in the male-only GWAS (lead variant rs2968545: (Beta = -6.50; P = 1.09 × 10-9), and one suggestive variant was found at 13q12.11 in the female-only GWAS (rs79926925: Beta = 6.95; P = 8.15 × 10-8). The negatively associated variants were most common in European Americans (T allele of rs79837492; 5%) and African Americans (C allele of rs2968545; 5%) and not observed in Japanese Americans, whereas the positively associated variant was most common in Japanese Americans (C allele of rs79926925, 5%), which was all consistent with the racial/ethnic %VAT differences. In a validation step among UK Biobank participants (N = 23,699 of mainly British and Irish ancestry) with MRI-based VAT volume, both rs79837492 (Beta = -0.026, P = 0.019) and rs2968545 (Beta = -0.028, P = 0.010) were significantly associated in men only (n = 11,524). In the MEC-APS, the association between rs79926925 and plasma sex hormone binding globulin levels reached statistical significance in females, but not in males, with adjustment for total adiposity (Beta = -0.24; P = 0.028), on the log scale. Rs79837492 and rs2968545 are located in intron 5 of CNTNAP5, and rs79926925, in an intergenic region between GJB6 and CRYL1. These novel findings differing by sex and racial/ethnic group warrant replication in additional diverse studies with direct visceral fat measurements.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We compared fat storage in the abdominal region among individuals from 5 different ethnic–racial groups to determine whether fat storage is associated with disparities observed in metabolic syndrome ...and other obesity-associated diseases.
We collected data from 1794 participants in the Multiethnic Cohort Study (60–77 years old; of African, European white, Japanese, Latino, or Native Hawaiian ancestry) with body mass index values of 17.1–46.2 kg/m2. From May 2013 through April 2016, participants visited the study clinic to undergo body measurements, an interview, and a blood collection. Participants were evaluated by dual-energy x-ray absorptiometry and abdominal magnetic resonance imaging. Among ethnic groups, we compared adiposity of the trunk, intra-abdominal visceral cavity, and liver, adjusting for total fat mass; we evaluated the association of adult weight change with abdominal adiposity; and we examined the prevalence of metabolic syndrome mediated by abdominal adiposity.
Relative amounts of trunk, visceral, and liver fat varied significantly with ethnicity—they were highest in Japanese Americans, lowest in African Americans, and intermediate in the other groups. Compared with African Americans, the mean visceral fat area was 45% and 73% greater in Japanese American men and women, respectively, and the mean measurements of liver fat were 61% and 122% greater in Japanese American men and women. The visceral and hepatic adiposity associated with weight gain since participants were 21 years old varied in a similar pattern among ethnic–racial groups. In the mediation analysis, visceral and liver fat jointly accounted for a statistically significant fraction of the difference in metabolic syndrome prevalence, compared with white persons, for African Americans, Japanese Americans, and Native Hawaiian women, independently of total fat mass.
In an analysis of data from the participants in the Multiethnic Cohort Study, we found extensive differences among ethnic–racial groups in the propensity to store fat intra-abdominally. This observation should be considered by clinicians in the prevention and early detection of metabolic disorders.
It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact ...result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10(-4)) and similar in all populations (odds ratios 1.09-1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; P(het) = 3.8×10(-4)). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding "synthetic associations" of rare mutations in T2D.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Ionizing radiation is an established carcinogen, but risks from low-dose exposures are controversial. Since the Biological Effects of Ionizing Radiation VII review of the ...epidemiological data in 2006, many subsequent publications have reported excess cancer risks from low-dose exposures. Our aim was to systematically review these studies to assess the magnitude of the risk and whether the positive findings could be explained by biases.
Methods
Eligible studies had mean cumulative doses of less than 100 mGy, individualized dose estimates, risk estimates, and confidence intervals (CI) for the dose-response and were published in 2006–2017. We summarized the evidence for bias (dose error, confounding, outcome ascertainment) and its likely direction for each study. We tested whether the median excess relative risk (ERR) per unit dose equals zero and assessed the impact of excluding positive studies with potential bias away from the null. We performed a meta-analysis to quantify the ERR and assess consistency across studies for all solid cancers and leukemia.
Results
Of the 26 eligible studies, 8 concerned environmental, 4 medical, and 14 occupational exposure. For solid cancers, 16 of 22 studies reported positive ERRs per unit dose, and we rejected the hypothesis that the median ERR equals zero (P = .03). After exclusion of 4 positive studies with potential positive bias, 12 of 18 studies reported positive ERRs per unit dose (P = .12). For leukemia, 17 of 20 studies were positive, and we rejected the hypothesis that the median ERR per unit dose equals zero (P = .001), also after exclusion of 5 positive studies with potential positive bias (P = .02). For adulthood exposure, the meta-ERR at 100 mGy was 0.029 (95% CI = 0.011 to 0.047) for solid cancers and 0.16 (95% CI = 0.07 to 0.25) for leukemia. For childhood exposure, the meta-ERR at 100 mGy for leukemia was 2.84 (95% CI = 0.37 to 5.32); there were only two eligible studies of all solid cancers.
Conclusions
Our systematic assessments in this monograph showed that these new epidemiological studies are characterized by several limitations, but only a few positive studies were potentially biased away from the null. After exclusion of these studies, the majority of studies still reported positive risk estimates. We therefore conclude that these new epidemiological studies directly support excess cancer risks from low-dose ionizing radiation. Furthermore, the magnitude of the cancer risks from these low-dose radiation exposures was statistically compatible with the radiation dose-related cancer risks of the atomic bomb survivors.
While smoking is the primary cause of lung cancer, only 11-24% of smokers develop the malignancy over their lifetime. The primary addictive agent in tobacco smoke is nicotine and variation in ...nicotine metabolism may influence the smoking levels of an individual. Therefore, inter-individual variation in lung cancer risk among smokers may be due in part to differences in the activity of enzymes involved in nicotine metabolism. In most smokers, cytochrome P450 2A6 (CYP2A6)-catalyzed C-oxidation accounts for >75% of nicotine metabolism, and the activity of this enzyme has been shown to correlate with the amount of nicotine and carcinogens drawn from cigarettes. We prospectively evaluated the association of urinary biomarkers of nicotine uptake (total nicotine equivalents TNE) and CYP2A6 activity (ratio of urinary total trans-3'-hydroxycotinine to cotinine) with lung cancer risk among 2,309 Multiethnic Cohort Study participants who were current smokers at time of urine collection; 92 cases were diagnosed during a mean follow-up of 9.5 years. We found that higher CYP2A6 activity and TNE was associated with increased lung cancer risk after adjusting for age, sex, race/ethnicity, body mass index, smoking duration, and urinary creatinine (p's = 0.002). The association for CYP2A6 activity remained even after adjusting for self-reported cigarettes per day (CPD) (Hazard Ratio HR per unit increase in log-CYP2A6 activity = 1.52; p = 0.005) and after adjusting for TNE (HR = 1.46; p = 0.01). In contrast, the association between TNE and lung cancer risk was of borderline statistical significance when adjusted for CPD (HR = 1.53; p = 0.06) and not statistically significant when further adjusted for CYP2A6 activity (HR = 1.30; p = 0.22). These findings suggest that CYP2A6 activity provides information on lung cancer risk that is not captured by smoking history or a (short-term) biomarker of dose. CYP2A6 activity should be further studied as a risk biomarker for smoking-related lung cancer.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
We previously found that African Americans and Native Hawaiians were at highest lung cancer risk compared with Japanese Americans and Latinos; whites were midway in risk. These ...differences were more evident at relatively low levels of smoking intensity, fewer than 20 cigarettes per day (CPD), than at higher intensity.
Methods
We apportioned lung cancer risk into three parts: age-specific background risk (among never smokers), an excess relative risk term for cumulative smoking, and modifiers of the smoking effect: race and years-quit smoking. We also explored the effect of replacing self-reports of CPD with a urinary biomarker—total nicotine equivalents—using data from a urinary biomarker substudy.
Results
Total lung cancers increased from 1979 to 4993 compared to earlier analysis. Estimated excess relative risks for lung cancer due to smoking for 50 years at 10 CPD (25 pack-years) ranged from 21.9 (95% CI = 18.0 to 25.8) for Native Hawaiians to 8.0 (95% CI = 6.6 to 9.4) for Latinos over the five groups. The risk from smoking was higher for squamous cell carcinomas and small cell cancers than for adenocarcinomas. Racial differences consistent with earlier patterns were seen for overall cancer and for cancer subtypes. Adjusting for predicted total nicotine equivalents, Japanese Americans no longer exhibit a lower risk, and African Americans are no longer at higher risk, compared to whites. Striking risk differences between Native Hawaiians and Latinos persist.
Conclusions
Racial differences in lung cancer risk persist in the Multiethnic Cohort study that are not easily explained by variations in self-reported or urinary biomarker-measured smoking intensities.
In a population of almost 184,000 prospectively studied participants, the risk of lung cancer was ascertained according to the level of cigarette smoking and ethnic or racial background. Among those ...who smoked no more than 30 cigarettes per day, the relative risk of lung cancer was highest among African Americans and native Hawaiians, as compared with whites, Hispanics, and Japanese Americans.
Among those who smoked no more than 30 cigarettes per day, the relative risk of lung cancer was highest among African Americans and native Hawaiians, as compared with whites, Hispanics, and Japanese Americans.
The incidence of lung cancer is substantially higher among blacks, Native Hawaiians, and other Polynesians and lower among Japanese Americans and Hispanics than among whites in the United States.
1
The vast majority (80 to 90 percent) of these cases are attributable to cigarette smoking. Smoking behavior also varies widely among these ethnic and racial groups. In aggregated population surveys conducted in the United States, the age-adjusted prevalence of cigarette smoking was 30.1 percent among black adults and 27.3 percent among white adults.
2
Only 8.0 percent of black smokers, however, were reported to be heavy smokers (smoking at least 25 cigarettes . . .
In epidemiological studies, exposures of interest are often measured with uncertainties, which may be independent or correlated. Independent errors can often be characterized relatively easily while ...correlated measurement errors have shared and hierarchical components that complicate the description of their structure. For some important studies, Monte Carlo dosimetry systems that provide multiple realizations of exposure estimates have been used to represent such complex error structures. While the effects of independent measurement errors on parameter estimation and methods to correct these effects have been studied comprehensively in the epidemiological literature, the literature on the effects of correlated errors, and associated correction methods is much more sparse. In this paper, we implement a novel method that calculates corrected confidence intervals based on the approximate asymptotic distribution of parameter estimates in linear excess relative risk (ERR) models. These models are widely used in survival analysis, particularly in radiation epidemiology. Specifically, for the dose effect estimate of interest (increase in relative risk per unit dose), a mixture distribution consisting of a normal and a lognormal component is applied. This choice of asymptotic approximation guarantees that corrected confidence intervals will always be bounded, a result which does not hold under a normal approximation. A simulation study was conducted to evaluate the proposed method in survival analysis using a realistic ERR model. We used both simulated Monte Carlo dosimetry systems (MCDS) and actual dose histories from the Mayak Worker Dosimetry System 2013, a MCDS for plutonium exposures in the Mayak Worker Cohort. Results show our proposed methods provide much improved coverage probabilities for the dose effect parameter, and noticeable improvements for other model parameters.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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