M. Daniele Fallin

Intra-individual change over time in DNA methylation with familial clustering.

CONTEXT Changes over time in epigenetic marks, which are modifications of DNA such as by DNA methylation, may help explain the late onset of common human diseases. However, changes in methylation or other epigenetic marks over time in a given individual have not yet been investigated. OBJECTIVES To determine whether there are longitudinal changes in global DNA methylation in individuals and to evaluate whether methylation maintenance demonstrates familial clustering. DESIGN, SETTING, AND PARTICIPANTS We measured global DNA methylation by luminometric methylation assay, a quantitative measurement of genome-wide DNA methylation, on DNA sampled at 2 visits on average 11 years apart in 111 individuals from an Icelandic cohort (1991 and 2002-2005) and on average 16 years apart in 126 individuals from a Utah sample (1982-1985 and 1997-2005). MAIN OUTCOME MEASURE Global methylation changes over time. RESULTS Twenty-nine percent of Icelandic individuals showed greater than 10% methylation change over time (P < .001). The family-based Utah sample also showed intra-individual changes over time, and further demonstrated familial clustering of methylation change (P = .003). The family showing the greatest global methylation loss also demonstrated the greatest loss of gene-specific methylation by a separate methylation assay. CONCLUSION These data indicate that methylation changes over time and suggest that methylation maintenance may be under genetic control.

Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis

Epigenetic mechanisms integrate genetic and environmental causes of disease, but comprehensive genome-wide analyses of epigenetic modifications have not yet demonstrated robust association with common diseases. Using Illumina HumanMethylation450 arrays on 354 anti-citrullinated protein antibody–associated rheumatoid arthritis cases and 337 controls, we identified two clusters within the major histocompatibility complex (MHC) region whose differential methylation potentially mediates genetic risk for rheumatoid arthritis. To reduce confounding factors that have hampered previous epigenome-wide studies, we corrected for cellular heterogeneity by estimating and adjusting for cell-type proportions in our blood-derived DNA samples and used mediation analysis to filter out associations likely to be a consequence of disease. Four CpGs also showed an association between genotype and variance of methylation. The associations for both clusters replicated at least one CpG (P < 0.01), with the rest showing suggestive association, in monocyte cell fractions in an independent cohort of 12 cases and 12 controls. Thus, DNA methylation is a potential mediator of genetic risk.

Bipolar I Disorder and Schizophrenia: A 440-Single-Nucleotide Polymorphism Screen of 64 Candidate Genes among Ashkenazi Jewish Case-Parent Trios

Bipolar, schizophrenia, and schizoaffective disorders are common, highly heritable psychiatric disorders, for which familial coaggregation, as well as epidemiological and genetic evidence, suggests overlapping etiologies. No definitive susceptibility genes have yet been identified for any of these disorders. Genetic heterogeneity, combined with phenotypic imprecision and poor marker coverage, has contributed to the difficulty in defining risk variants. We focused on families of Ashkenazi Jewish descent, to reduce genetic heterogeneity, and, as a precursor to genomewide association studies, we undertook a single-nucleotide polymorphism (SNP) genotyping screen of 64 candidate genes (440 SNPs) chosen on the basis of previous linkage or of association and/or biological relevance. We genotyped an average of 6.9 SNPs per gene, with an average density of 1 SNP per 11.9 kb in 323 bipolar I disorder and 274 schizophrenia or schizoaffective Ashkenazi case-parent trios. Using single-SNP and haplotype-based transmission/disequilibrium tests, we ranked genes on the basis of strength of association (P<.01). Six genes (DAO, GRM3, GRM4, GRIN2B, IL2RB, and TUBA8) met this criterion for bipolar I disorder; only DAO has been previously associated with bipolar disorder. Six genes (RGS4, SCA1, GRM4, DPYSL2, NOS1, and GRID1) met this criterion for schizophrenia or schizoaffective disorder; five replicate previous associations, and one, GRID1, shows a novel association with schizophrenia. In addition, six genes (DPYSL2, DTNBP1, G30/G72, GRID1, GRM4, and NOS1) showed overlapping suggestive evidence of association in both disorders. These results may help to prioritize candidate genes for future study from among the many suspected/proposed for schizophrenia and bipolar disorders. They provide further support for shared genetic susceptibility between these two disorders that involve glutamate-signaling pathways.

A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4

Case-parent trios were used in a genome-wide association study of cleft lip with and without cleft palate. SNPs near two genes not previously associated with cleft lip with and without cleft palate (MAFB, most significant SNP rs13041247, with odds ratio (OR) per minor allele = 0.704, 95% CI 0.635–0.778, P = 1.44 × 10−11; and ABCA4, most significant SNP rs560426, with OR = 1.432, 95% CI 1.292–1.587, P = 5.01 × 10−12) and two previously identified regions (at chromosome 8q24 and IRF6) attained genome-wide significance. Stratifying trios into European and Asian ancestry groups revealed differences in statistical significance, although estimated effect sizes remained similar. Replication studies from several populations showed confirming evidence, with families of European ancestry giving stronger evidence for markers in 8q24, whereas Asian families showed stronger evidence for association with MAFB and ABCA4. Expression studies support a role for MAFB in palatal development.

Meta-analysis confirms CR1, CLU, and PICALM as alzheimer disease risk loci and reveals interactions with APOE genotypes.

OBJECTIVES To determine whether genotypes at CLU, PICALM, and CR1 confer risk for Alzheimer disease (AD) and whether risk for AD associated with these genes is influenced by apolipoprotein E (APOE) genotypes. DESIGN Association study of AD and CLU, PICALM, CR1, and APOE genotypes. SETTING Academic research institutions in the United States, Canada, and Israel. PARTICIPANTS Seven thousand seventy cases with AD, 3055 with autopsies, and 8169 elderly cognitively normal controls, 1092 with autopsies, from 12 different studies, including white, African American, Israeli-Arab, and Caribbean Hispanic individuals. RESULTS Unadjusted, CLU (odds ratio [OR], 0.91; 95% confidence interval [CI], 0.85-0.96 for single-nucleotide polymorphism [SNP] rs11136000), CR1 (OR, 1.14; 95% CI, 1.07-1.22; SNP rs3818361), and PICALM (OR, 0.89; 95% CI, 0.84-0.94, SNP rs3851179) were associated with AD in white individuals. None were significantly associated with AD in the other ethnic groups. APOE ε4 was significantly associated with AD (ORs, 1.80-9.05) in all but 1 small white cohort and in the Arab cohort. Adjusting for age, sex, and the presence of at least 1 APOE ε4 allele greatly reduced evidence for association with PICALM but not CR1 or CLU. Models with the main SNP effect, presence or absence of APOE ε4, and an interaction term showed significant interaction between presence or absence of APOE ε4 and PICALM. CONCLUSIONS We confirm in a completely independent data set that CR1, CLU, and PICALM are AD susceptibility loci in European ancestry populations. Genotypes at PICALM confer risk predominantly in APOE ε4-positive subjects. Thus, APOE and PICALM synergistically interact.

DNA methylation age of blood predicts all-cause mortality in later life

BackgroundDNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.ResultsHere we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43.ConclusionsDNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Personalized Epigenomic Signatures That Are Stable Over Time and Covary with Body Mass Index

A genome-scale, gene-specific analysis of DNA methylation in the same individuals over a decade apart identifies a personalized epigenomic signature that may correlate with a common genetic trait. The Writing is on the Genes: Can Epigenomics Predict Disease Risk? In the nature versus nurture debate about human traits, epigenomics holds a special place. Epigenetic changes are physical changes that happen to genes but do not change the gene (DNA) sequence itself—such as DNA methylation. The regulation of these changes is not yet well-understood, providing new ammunition to the age-old argument. It is possible that the methylation pattern is all “nature”, predetermined by a person’s genetic makeup, or alternatively methylation could be a result of “nurture”, reflecting the influence of regulatory signals outside the cell, that is, the environment. Having analyzed the detailed methylation patterns in several dozen individuals at two different time points, over a decade apart, Feinberg et al. present evidence that the answer may actually be both—a combination of genetic determinants and environmental regulation. In this study, the authors analyzed the full methylation pattern at 4.5 million sites genome-wide in 74 volunteers. The participants, who were on average 74 years old at the time of the first visit, provided blood samples again 11 to 14 years later, allowing for comparison of methylation patterns both between individuals, and in the same individuals across time. In doing this, the authors found 227 variably methylated regions (VMRs), which varied widely between the study participants. Of these, 119 VMRs remained stable within each individual over time, constituting an epigenetic fingerprint that may be genetically predetermined and differed between pairs of individual participants. The remaining VMRs were highly variable over time, suggesting that their pattern is affected by environmental influences. Four of the stable VMRs consistently correlated with study subjects’ body mass index in both visits. All four of these sites were located at or near genes that are known to be involved in the pathogenesis of diabetes or obesity, lending biological plausibility to the correlation between the methylation pattern and obesity risk. Through their analysis of the epigenome in a large pool of volunteer subjects, Feinberg et al. have demonstrated a unique signature of stable epigenetic changes within each individual. Several of these stable methylation sites were correlated with the patients’ body mass index. If these results are confirmed in younger individuals and consistent throughout the life span, tests for methylation might be used to screen patients in childhood and identify those at risk for obesity, allowing preventative treatment. In theory, similar testing for other common diseases that may have a stable epigenetic component, such as diabetes or asthma, could allow early intervention and prevention. The epigenome consists of non–sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here, we have performed an unbiased genome-scale analysis of ~4 million CpG sites in 74 individuals with comprehensive array-based relative methylation (CHARM) analysis. We found 227 regions that showed extreme interindividual variability [variably methylated regions (VMRs)] across the genome, which are enriched for developmental genes based on Gene Ontology analysis. Furthermore, half of these VMRs were stable within individuals over an average of 11 years, and these VMRs defined a personalized epigenomic signature. Four of these VMRs showed covariation with body mass index consistently at two study visits and were located in or near genes previously implicated in regulating body weight or diabetes. This work suggests an epigenetic strategy for identifying patients at risk of common disease.

Variation in a Repeat Sequence Determines Whether a Common Variant of the Cystic Fibrosis Transmembrane Conductance Regulator Gene Is Pathogenic or Benign

An abbreviated tract of five thymidines (5T) in intron 8 of the cystic fibrosis transmembrane conductance regulator (CFTR) gene is found in approximately 10% of individuals in the general population. When found in trans with a severe CFTR mutation, 5T can result in male infertility, nonclassic cystic fibrosis, or a normal phenotype. To test whether the number of TG repeats adjacent to 5T influences disease penetrance, we determined TG repeat number in 98 patients with male infertility due to congenital absence of the vas deferens, 9 patients with nonclassic CF, and 27 unaffected individuals (fertile men). Each of the individuals in this study had a severe CFTR mutation on one CFTR gene and 5T on the other. Of the unaffected individuals, 78% (21 of 27) had 5T adjacent to 11 TG repeats, compared with 9% (10 of 107) of affected individuals. Conversely, 91% (97 of 107) of affected individuals had 12 or 13 TG repeats, versus only 22% (6 of 27) of unaffected individuals (P<.00001). Those individuals with 5T adjacent to either 12 or 13 TG repeats were substantially more likely to exhibit an abnormal phenotype than those with 5T adjacent to 11 TG repeats (odds ratio 34.0, 95% CI 11.1-103.7, P<.00001). Thus, determination of TG repeat number will allow for more accurate prediction of benign versus pathogenic 5T alleles.

A comprehensive genetic association study of Alzheimer disease in African Americans.

OBJECTIVES To evaluate the association of genetic variation with late-onset Alzheimer disease (AD) in African Americans, including genes implicated in recent genome-wide association studies of whites. DESIGN We analyzed a genome-wide set of 2.5 million imputed markers to evaluate the genetic basis of AD in an African American population. SUBJECTS Five hundred thirteen well-characterized African American AD cases and 496 cognitively normal African American control subjects. SETTING Data were collected from multiple sites as part of the Multi-Institutional Research on Alzheimer Genetic Epidemiology (MIRAGE) Study and the Henry Ford Health System as part of the Genetic and Environmental Risk Factors for Alzheimer Disease Among African Americans (GenerAAtions) Study. RESULTS Several significant single-nucleotide polymorphisms (SNPs) were observed in the region of the apolipoprotein E gene (APOE). After adjusting for the confounding effects of APOE genotype, one of these SNPs, rs6859 in PVRL2, remained significantly associated with AD (P = .0087). Association was also observed with SNPs in CLU, PICALM, BIN1, EPHA1, MS4A, ABCA7, and CD33, although the effect direction for some SNPs and the most significant SNPs differed from findings in data sets consisting of whites. Finally, using the African American genome-wide association study data set as a discovery sample, we obtained suggestive evidence of association with SNPs for several novel candidate genes. CONCLUSIONS Some genes contribute to AD pathogenesis in both white and African American cohorts, although it is unclear whether the causal variants are the same. A larger African American sample will be needed to confirm novel gene associations, which may be population specific.

Heritability of Platelet Responsiveness to Aspirin in Activation Pathways Directly and Indirectly Related to Cyclooxygenase-1

Background— The inability of aspirin (acetylsalicylic acid [ASA]) to adequately suppress platelet function is associated with future risk of myocardial infarction, stroke, and cardiovascular death. Genetic variation is a proposed but unproved mechanism for insufficient ASA responsiveness. Methods and Results— We examined platelet ASA responsiveness in 1880 asymptomatic subjects (mean age, 44±13 years; 58% women) recruited from 309 white and 208 black families with premature coronary heart disease. Ex vivo platelet function was determined before and after ingestion of ASA (81 mg/d for 2 weeks) with the use of a panel of measures that assessed platelet activation in pathways directly and indirectly related to cyclooxygenase-1, the enzyme inhibited by ASA. The proportion of phenotypic variance related to CHD risk factor covariates was determined by multivariable regression. Heritability of phenotypes was determined with the use of variance components models unadjusted and adjusted for covariates. ASA inhibited arachidonic acid–induced aggregation and thromboxane B2 production by ≥99% (P<0.0001). Inhibition of urinary thromboxane excretion and platelet activation in pathways indirectly related to cyclooxygenase-1 was less pronounced and more variable (inhibition of 0% to 100%). Measured covariates contributed modestly to variability in ASA response phenotypes (r2=0.001 to 0.133). Phenotypes indirectly related to cyclooxygenase-1 were strongly and consistently heritable across races (h2=0.266 to 0.762; P<0.01), but direct cyclooxygenase-1 phenotypes were not. Conclusions— Heritable factors contribute prominently to variability in residual platelet function after ASA exposure. These data suggest a genetic basis for the adequacy of platelet suppression by ASA and potentially for differences in the clinical efficacy of ASA.