Associations between APOE variants and metabolic traits and the impact of psychological stress

Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations

BACKGROUND

Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations.

METHODS

Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals.

RESULTS

Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation.

CONCLUSIONS

Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.

Apolipoprotein E genetic variants interact with Mediterranean diet to modulate postprandial hypertriglyceridemia in coronary heart disease patients: CORDIOPREV study

BACKGROUND

We try to explore whether long-term consumption of two healthy dietary patterns (low-fat [LF] diet or Mediterranean diet [MedDiet]) interacts with the apolipoprotein E (APOE) single-nucleotide polymorphisms (SNPs: rs439401, rs440446 and rs7412) modulating postprandial hypertriglyceridemia (ppHTG) in coronary heart disease (CHD) patients.

METHODS AND RESULTS

We selected patients from the CORDIOPREV study with genotyping and who underwent an oral fat load test (FLT) at baseline and after 3 years follow-up (n = 506). After 3 years of follow-up, we found a gene-diet interaction between the APOE rs439401 SNP and MedDiet. Specifically, T-allele carriers in the MedDiet group showed a more significant decrease in postprandial triglycerides (TG: P = 0.03) and large triacylglycerol-rich lipoproteins (TRLs) TG (large TRLs TG; P = 0.01) compared with CC subjects. Consistently, the area under the curve of TG (AUC-TG; P-interaction = 0.03) and AUC-large TRLs TG (P-interaction = 0.02) were significantly lower in T-allele carriers compared with CC subjects.

CONCLUSIONS

The long-term consumption of a MedDiet modulates ppHTG through APOE genetic variants in CHD patients. This gene-diet interaction may contribute to a more precise dietary advice in CHD patients.

Gene polymorphisms of stress hormone and cytokine receptors associate with immunomodulatory profile and psychological measurement

OBJECTIVE

We sought to identify whether stable single nucleotide polymorphisms (SNPs) of various endocrine and immune molecules could be used as biomarkers associated with specific immune alterations and chronic stress measures in normal humans.

METHODS

A total of 207 volunteer participants answered stress questionnaire and gave peripheral blood cells for identification of SNPs in genes coding for glucocorticoid receptor (GR), beta 2 adrenergic receptor (B2AR), interferon-gamma receptors (IFNGR1, IFNGR2), and interleukin-4 receptor (IL4R). Immunoregulatory profiles were measured by flow cytometry and genotyping assays were performed by allelic discrimination real-time PCR.

RESULTS

Several significant differences were revealed in associations between stress marker and immune indicators based on SNP categories. For instance, Th1 levels of the minor alleles of GR TthIIII (AA) and IFNGR2 Q64R (Arg/Arg) groups were positively associated with chronic stress (PSS) (p = 0.024 and 0.005, respectively) compared with wild type (WT) and negatively associated with PSS in the heterozygous genotypes of GR BclI and IL4R Ile50Val (p = 0.040 and p = 0.052, respectively). Treg levels of the minor alleles of BclI (GG) and IFNGR1 T-56C (CC) groups were positively associated with PSS (p = 0.045 and p = 0.010, respectively) and negatively associated in the minor allele (Val/Val) of IL4R Ile50Va and the heterozygous genotype of IL4R Q576R (p = 0.041 and p = 0.017, respectively) compared to WT.

CONCLUSION

The data support the notion that gene polymorphisms from various components of the psychoneuroendocrine-immune network may be useful as biomarkers to categorize individual stress-associated immune responses.

Longitudinal analysis is more powerful than cross-sectional analysis in detecting genetic association with neuroimaging phenotypes

Most existing genome-wide association analyses are cross-sectional, utilizing only phenotypic data at a single time point, e.g. baseline. On the other hand, longitudinal studies, such as Alzheimer's Disease Neuroimaging Initiative (ADNI), collect phenotypic information at multiple time points. In this article, as a case study, we conducted both longitudinal and cross-sectional analyses of the ADNI data with several brain imaging (not clinical diagnosis) phenotypes, demonstrating the power gains of longitudinal analysis over cross-sectional analysis. Specifically, we scanned genome-wide single nucleotide polymorphisms (SNPs) with 56 brain-wide imaging phenotypes processed by FreeSurfer on 638 subjects. At the genome-wide significance level P < 1.8 x 10(9)) or a less stringent level (e.g. P < 10(7)), longitudinal analysis of the phenotypic data from the baseline to month 48 identified more SNP-phenotype associations than cross-sectional analysis of only the baseline data. In particular, at the genome-wide significance level, both SNP rs429358 in gene APOE and SNP rs2075650 in gene TOMM40 were confirmed to be associated with various imaging phenotypes in multiple regions of interests (ROIs) by both analyses, though longitudinal analysis detected more regional phenotypes associated with the two SNPs and indicated another significant SNP rs439401 in gene APOE. In light of the power advantage of longitudinal analysis, we advocate its use in current and future longitudinal neuroimaging studies.

Chronic family stress moderates the association between a TOMM40 variant and triglyceride levels in two independent Caucasian samples

TOMM40 SNP rs157580 has been associated with triglyceride levels in genome-wide association studies (GWAS). Chronic caregiving stress moderates the association between triglyceride levels and a nearby SNP rs439401 that is associated with triglyceride levels in GWAS. Here, we report data from two independent Caucasian samples (242 U.S. women and men; 466 Danish men) testing the hypothesis that chronic family stress also moderates the association between rs157580 and triglyceride levels. The interaction of rs157580 and family stress in predicting triglyceride levels was statistically significant in the U.S. sample (p=0.004) and marginally significant (p=0.075) in the Danish sample. The G allele of rs157580 was associated with increased triglyceride levels among family stressed cases in both samples compared with A/A cases, but not among controls. Chronic family stress moderates the association of rs157580 variants with triglyceride levels and should be taken into account for disease risk assessment and potential intervention.

Long-Term Impact of Caregiving and Metabolic Syndrome with Perceived Decline in Cognitive Function 8 Years Later: A Pilot Study Suggesting Important Avenues for Future Research

The chronic stress of caregiving has been associated with increased risk for cognitive decline and dementia. One theoretical model suggests that a group of risk factors known as the metabolic syndrome MET_SYN (e.g. hypertension, poor glucose regulation, central obesity, and high triglyceride levels) that have demonstrated associations with both stress and cognitive decline, may mediate the association between caregiver stress and cognitive decline. It is also possible that caregiving may moderate the association between MET_SYN and cognitive decline. The present study examined these two potential models. The study sample consisted of 53 caregivers for a relative with dementia and 24 participants who did not have caregiving responsibilities at baseline. We examined associations among caregiving history (yes/no), self-reported decline in cognitive function (the AD8) at follow-up, and a MET_SYN factor comprised of increased systolic blood pressure (SBP), glycosylated hemoglobin concentration (HbA1c), waist circumference, and triglyceride levels at baseline when caregiving was assessed. MET_SYN was associated with AD8 (p = 0.010). Caregiving history was not directly associated with AD8 ratings, however, caregiving did moderate the association between MET_SYN and AD8 (p = 0.043) assessed 8 years later. In caregivers MET_SYN scores reflecting higher risk were associated with scores on the AD8 indicting decline, whereas, in controls MET_SYN was unrelated to AD8 assessment. Thus, it can be concluded that caregiver stress may increase the association between metabolic risk factors and decline in cognitive functioning up to 8 years later.

Gene-Lifestyle Interactions in Obesity

Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.

DNA methylation differences at growth related genes correlate with birth weight: a molecular signature linked to developmental origins of adult disease?

Background

Infant birth weight is a complex quantitative trait associated with both neonatal and long-term health outcomes. Numerous studies have been published in which candidate genes (IGF1, IGF2, IGF2R, IGF binding proteins, PHLDA2 and PLAGL1) have been associated with birth weight, but these studies are difficult to reproduce in man and large cohort studies are needed due to the large inter individual variance in transcription levels. Also, very little of the trait variance is explained. We decided to identify additional candidates without regard for what is known about the genes. We hypothesize that DNA methylation differences between individuals can serve as markers of gene "expression potential" at growth related genes throughout development and that these differences may correlate with birth weight better than single time point measures of gene expression.

Methods

We performed DNA methylation and transcript profiling on cord blood and placenta from newborns. We then used novel computational approaches to identify genes correlated with birth weight.

Results

We identified 23 genes whose methylation levels explain 70-87% of the variance in birth weight. Six of these (ANGPT4, APOE, CDK2, GRB10, OSBPL5 and REG1B) are associated with growth phenotypes in human or mouse models. Gene expression profiling explained a much smaller fraction of variance in birth weight than did DNA methylation. We further show that two genes, the transcriptional repressor MSX1 and the growth factor receptor adaptor protein GRB10, are correlated with transcriptional control of at least seven genes reported to be involved in fetal or placental growth, suggesting that we have identified important networks in growth control. GRB10 methylation is also correlated with genes involved in reactive oxygen species signaling, stress signaling and oxygen sensing and more recent data implicate GRB10 in insulin signaling.

Conclusions

Single time point measurements of gene expression may reflect many factors unrelated to birth weight, while inter-individual differences in DNA methylation may represent a "molecular fossil record" of differences in birth weight-related gene expression. Finding these "unexpected" pathways may tell us something about the long-term association between low birth weight and adult disease, as well as which genes may be susceptible to environmental effects. These findings increase our understanding of the molecular mechanisms involved in human development and disease progression.