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In hemochromatosis, iron overload is due to increased intestinal iron absorption attributable to mutations in several genes involved in the regulation of iron absorption and metabolism. The most common type of hemochromatosis is caused by mutations in the HFE gene, and homozygosity for the HFE p.C282Y mutation is associated with a risk of iron overload. Approximately 1:200 people of Caucasian origin are homozygous for p.C282Y, but only a minority of p.C282Y homozygotes develop significant iron overload. This is attributed in part to the presence of putative genetic modifiers of iron absorption. Recently, we identified GNPAT, encoding glyceronephosphate O-acyltransferase, as a potential modifier of HFE hemochromatosis in a whole-exome sequencing study of p.C282Y homozygotes with extreme iron overload phenotypes. A GNPAT polymorphism (p.D519G, rs11558492) was associated with severe iron overload among p.C282Y homozygous men (Hepatology 2015;62:429-39). Other studies have either substantiated or contradicted the importance of GNPAT p.D519G as a genetic modifier of iron phenotypes in HFE p.C282Y homozygotes. p.D519G is also a risk factor for familial (but not sporadic) porphyria cutanea tarda (Plos One 2016;11:e0163322). Some patients with hemochromatosis phenotypes are heterozygous for p.C282Y and a different HFE polymorphism, p.H63D (which is also common but usually not itself associated with clinically significant iron overload). Many p.C282Y/p.H63D compound heterozygotes have milder iron overload phenotypes than p.C282Y homozygotes. Herein, we report studies of the prevalence of p.D519G in a cohort of compound heterozygous p.C282Y/p.H63D Australian patients, with or without elevated serum ferritin (SF) levels. We also compared p.D519G allele frequency of the present p.C282Y/p.H63D compound heterozygotes with those of large population cohorts. We identified 72 HFE p.C282Y/p.H63D compound heterozygotes with DNA available for analysis. Of these, 9 had missing SF data and were excluded. GNPAT p.D519G was assessed in the remaining 63 subjects. Compound heterozygotes with elevated SF levels ≥300 µg/mL (males) and ≥200 µg/mL (females) were selected as cases (n=28), and participants with SF levels below these cut-offs were classified as controls (n=35). The mean age at the time of testing was 31 y (males 31, females 31) in the control group and 48 y (males 47, females 51) in subjects with elevated SF levels. Among cases, mean SF was 612 µg/L (median 557 µg/L, IQR 361- 821 µg/L). Mean SF in the control group was 85 µg/L (median 58 µg/L, IQR 38 - 121 µg/L). All samples were genotyped for GNPAT p.D519G. We compared the p.D519G allele frequency of the present subjects, with and without elevated SF, to the p.D519G frequency in publically available datasets. p.D519G allele frequency was greater in the elevated SF group (37.5%) than the control group (24.3%), but this difference was not significant (p=0.1285). p.D519G was more prevalent in our cohort of p.C282Y/p.H63D compound heterozygotes with elevated SF (37.5%) than in European populations reported in public datasets: ExAC 19.7%, 1000G 21.3%, gnomAD 20.4%, and ESP 20.6%. There was a significant association between allele count and case/control status among men (type 3 analysis of effects; p = 0.049) but not women. For a male case, the odds of having either 1 or 2 alleles versus having 0 alleles was 5.08 (95% CI, 1.01, 25.66) times higher than that of a male control. In conclusion, our results demonstrate that GNPAT p.D519G is associated with elevated SF levels in Australian HFE p.C282Y/p.H63D compound heterozygotes and that the p.D519G allele frequency is greater in p.C282Y/p.H63D compound heterozygotes with elevated SF than in several large European population cohorts. We found a statistically significant association between the allele count and the case/control status among men. The small number of subjects with elevated SF in our study may have limited our ability to demonstrate significant differences in some comparisons. Some subjects with p.D519G do not have elevated SF, suggesting that there are other factors, genetic or environmental, which also affect iron absorption in p.C282Y/p.H63D compound heterozygotes. Disclosures No relevant conflicts of interest to declare.

GNPAT (chromosome 1q42.2) encodes the peroxisomal enzyme glyceronephosphate O-acyltransferase. In a previous study, DNA of men with hemochromatosis and HFE p.C282Y homozygosity and either markedly increased iron stores or normal or mildly increased iron stores were evaluated with exome sequencing. Positivity for the GNPAT polymorphism p.D519G (rs11558492) was significantly greater in men with markedly increased iron stores (McLaren CE et al., Hepatology 2015;62:429-39). This result suggests that the p.D519G is a candidate modifier of iron phenotypes in p.C282Y homozygotes. To learn more, we examined associations of p.D519G, age, iron-related variables, and daily alcohol consumption with iron stores in p.C282Y homozygotes classified by extremes of iron overload phenotypes. We defined markedly increased iron stores as serum ferritin >1000 µg/L and either hepatic iron >236 µmol/g dry weight or mobilizable iron >10 g by induction phlebotomy (men and women). Normal or mildly elevated iron stores were defined as serum ferritin There were 56 participants (53 men, 3 women), of whom 41 (38 men, 3 women) had markedly increased iron stores and 15 others had normal or mildly increased iron stores (all men). The mean age of the 56 participants was 55 ± 10 (SD) y. Prevalences of swollen/tender 2nd/3rd metacarpophalangeal joints and elevated serum levels of aspartate or alanine aminotransferase were significantly greater in participants with markedly increased iron stores. Only participants with markedly increased iron stores had cirrhosis proven by biopsy. Odds ratios of having markedly increased iron stores for each of the six variables, as determined by univariate logistic regression, are displayed in Table 1. In the multivariable analysis, p.D519G positivity was the only exposure variable significantly associated with markedly increased iron stores (odds ratio 9.9, 95% CI [1.6, 60.3], p = 0.0126). Area under the curve for the multivariable logistic regression analysis was 0.82. We conclude that GNPAT p.D519G is strongly associated with markedly increased iron stores in p.C282Y homozygotes after correction for age, iron-related variables, and daily alcohol consumption. It remains unknown whether p.D519G directly enhances iron transport into the blood by absorptive enterocytes, indirectly augments iron absorption by suppressing hepcidin, or is linked to a putative iron absorption promoter on chromosome 1q. Disclosures No relevant conflicts of interest to declare.

It is well-recognized that Helicobacter pylori infection causes gastrointestinal blood loss and iron deficiency. H. pylori gastritis has also been implicated in iron deficiency refractory to oral iron replacement therapy. Although H. pylori infection is common in multiple populations, less is known about the extent to which H. pylori contributes to iron deficiency in different racial/ethnic groups. To address this question, we tested the serum collected from men aged ≥ 25 y and women ≥ 50 y in the Hemochromatosis and Iron Overload Screening (HEIRS) Study to identify those with iron deficiency (defined as serum ferritin ≤ 12 mg/L [cases]) and iron-replete controls (serum ferritin > 100 mg/L in men, serum ferritin > 50 mg/L in women). All samples were tested for H. pylori IgG antibodies and for antibodies to CagA (cytotoxin-associated gene-bearing strain). We tested 571 cases and 1142 controls. Participants were considered to have evidence of H. pylori infection if they had positive results for both antibodies or for either antibody alone. Participants who did not have a result for either test were excluded. We examined the association between the presence of H. pylori in cases and controls among Caucasians, Asian/Pacific Islanders, African Americans, and Hispanics. Among Caucasians, evidence of H. pylori infection was comparable in cases and controls; 170 of 735 controls (23.1%) and 97 of 363 cases (26.7%), respectively, were positive. Similar results were found in African Americans (56.3% of 144 controls; 55.8% of 77 cases) and Hispanics (66.7% of 159 controls; 59.5% of 79 cases). However, in Asian/Pacific Islanders, the prevalence of H. pylori was higher among cases (62.8% of 51) than controls (44.1% of 102), p=0.029 by the likelihood ratio Chi-Square test. The relative risk (RR) of iron deficiency among those with H. pylori-positivity was significantly greater than in those without (RR, 1.66; 95% CI [1.04, 2.66]). A comparison of subgroups by positivity for IgG or CagA showed that the relative risk of iron deficiency was increased among those with IgG positivity, with or without Cag A positivity (RR, 1.80 and 1.90, respectively), but not among those with CagA positivity alone (RR, 1.00). H. pylori infection is a frequent contributor to iron deficiency but is also common in the general population. Our results indicate that among HEIRS Study Asian/Pacific Islander participants, H. pylori infection is more prevalent in cases with iron deficiency than in controls. In contrast, there was no difference in the prevalence of H. pylori infection between cases and controls among Caucasians, African Americans, and Hispanics. These results have implications for the investigation of iron deficiency in Asians and Pacific Islanders. Disclosures No relevant conflicts of interest to declare.

Abstract 5281 Bivariate mixture modeling was used to analyze joint population distributions of transferrin saturation (TS) and serum ferritin concentration (SF) measured in the Hemochromatosis and Iron Overload Screening (HEIRS) Study (McLaren et al.Translational Research 2008 151(2), 97−109). Four components (C1, C2, C3, and C4) were identified with successively age−adjusted increasing means for TS and SF from data contributed by 26,832 African Americans, 12,620 Asians, 12,264 Hispanics, and 43,254 whites. We used data from the Australian “HealthIron” study of genetic and environmental modifiers of hereditary hemochromatosis to validate the mixture model approach for component analysis and to determine whether the component distributions appear to be stable over time or whether an individual's TS and SF values move from one component to another. Between 2004−2006, a sample of participants of northern European descent was selected from the Melbourne Collaborative Cohort Study (n=31,192 (17,951 women) recruited 1990–1994) to participate in the HealthIron study (n=1,438 (783 women)). Of these, 1,052 (579 women) participated in CAPI interviews and clinical examination. We applied the bivariate mixture modeling approach to TS and SF data from HealthIron. Follow−up data were excluded for individuals who were treated after baseline evaluations. The EMMIX program was used to predict component membership for HealthIron participants using the model based on the HEIRS data alone. Component transition probabilities over time were estimated as observed proportions. Analyses were performed separately for baseline and follow−up data. Four components (C1, C2, C3, C4) with successively age−adjusted increasing means for TS and SF, were identified using baseline data from 926 whites (426 men, 500 women) and using follow−up data from 771 whites (341 men, 430 women). At baseline, the largest component, C2, had normal mean TS (28% for women, 35% for men) and SF (139 mg/L for women, 309 μg/L for men), higher than the upper 95% confidence limits for means in analyses of HEIRS data. At follow−up, the largest component, C2, had normal mean TS (29% for women, 33% for men) and SF (124 μg/L for women, 183 μg/L for men) consisting of component proportions 0.64 for women and 0.72 for men. C3 and C4 had progressively higher mean values for TS and SF with progressively lower component proportions. At baseline, C1 had mean TS values of 15% for women (27% for men), and mean SF values of 23 mg/L for women (59 mg/L for men), similar to those found using HEIRS data. At follow−up, C1 had mean TS values of 18% for women and men, and mean SF values of 21 μg/L for women and 20 μg/L for men. Only female C282Y homozygotes for the iron gene, HFE, showed evidence that component transition probabilities shifted significantly over time;19 of 49 (39%) had TS and SF values that were in the same bivariate component at baseline and follow−up (Test of Symmetry, p=0.014). As for analyses of data from the HEIRS Study, a mixture of four components was found in data from HealthIron participants suggesting that the model is transferable from one white population to another, although estimated means within components may differ. The longitudinal aspect of this study illustrates that, with the exception of female C282Y homozygotes, the components of the mixture distributions are largely stable over time. Disclosures: No relevant conflicts of interest to declare.

In previous investigations, we modeled the distribution of transferrin saturation (TS) in Caucasians and demonstrated a strong association between HFE genotype and TS subpopulations. Extending this approach, we now have analyzed joint population distributions of TS and serum ferritin concentration (SF) measured in the multi-ethnic Hemochromatosis and Iron Overload Screening (HEIRS) Study and examined the association of these distributions with the presence of HFE C282Y and H63D mutations, self-reported liver disease, and iron deficiency (defined as SF adjusted odds of iron deficiency were significantly higher in the 1st component (15–48 for women, 61–3530 for men); adjusted odds of self-reported liver disease were significantly higher in the 3rd and 4th components for African-American women and all men; and adjusted odds of any HFE mutation were increased in the 3rd component (1.4–1.8 for women, 1.2–1.9 for men) and in the 4th component for Hispanic and White women (1.5, 5.2, respectively) and men (2.8, 4.7, respectively). Joint mixture modeling identifies one component with lower mean SF and TS at risk for iron deficiency and two components with higher mean SF and TS at risk for liver disorders and HFE mutations. This approach permits characterization of the aggregate effects of hereditary or acquired factors that influence these serum iron measures in populations, and complements and enhances genetic and phenotypic testing for assessment of disease characteristics. Table 1 Range of estimates from models.