Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.

Satiety and the Self-Regulation of Food Take in Children: a Potential Role for Gene-Environment Interplay

Child eating self-regulation refers to behaviors that enable children to start and stop eating in a manner consistent with maintaining energy balance. Perturbations in these behaviors, manifesting as poorer child eating self-regulation, are associated with higher child weight status. Initial research into child eating self-regulation focused on the role of parent feeding styles and behaviors. However, we argue that child eating self-regulation is better understood as arising from a complex interplay between the child and their feeding environment, and highlight newer research into the heritable child characteristics, such as cognitive ability, that play an important role in this dynamic. Therefore, child eating self-regulation arises from gene-environment interactions. Identifying the genes and environmental influences contributing to these will help us tailor our parental feeding advice to the unique nature of the child. In this way, we will devise more effective advice for preventing childhood obesity.

Diet and adipose tissue distributions: The Multi-Ethnic Study of Atherosclerosis

BACKGROUND AND AIMS

Dietary quality affects cardiometabolic risk, yet its pathways of influence on regional adipose tissue depots involved in metabolic and diabetes risk are not well established. We aimed to investigate the relationship between dietary quality and regional adiposity.

METHODS AND RESULTS

We investigated 5079 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) who had food-frequency questionnaires and measurement of pericardial fat and hepatic attenuation at the baseline study visit in MESA, as well as a subgroup with imaging for visceral and subcutaneous fat (N = 1390). A dietary quality score (DietQuality) was constructed to include established food group constituents of a Mediterranean-type diet. Linear models estimated associations of dietary score as well as its constituents with regional adiposity. Baseline mean age was 61 (± 10) years, and approximately half of the participants (47%) were male. Those with a higher DietQuality score were generally older, female, with a lower body mass index, C-reactive protein, and markers of insulin resistance. After adjustment, a higher DietQuality score was associated with lower visceral fat (lowest vs. highest dietary score quartile: 523.6 vs. 460.5 cm(2)/m; P < 0.01 for trend), pericardial fat (47.5 vs. 41.3 cm(3)/m; P < 0.01 for trend), lesser hepatic steatosis (by hepatic attenuation; 58.6 vs. 60.7 Hounsfield units; P < 0.01 for trend), but not subcutaneous fat (P = 0.39). Greater fruits, vegetables, whole grains, seeds/nuts and yogurt intake were associated with decreased adiposity, while red/processed meats were associated with greater regional adiposity.

CONCLUSION

A higher quality diet pattern is associated with less regional adiposity, suggesting a potential mechanism of beneficial dietary effects on diabetes, metabolic, and cardiovascular risk.

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians

BACKGROUND

Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE

We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN

Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS

Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION

The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Genome-wide association study of triglyceride response to a high-fat meal among participants of the NHLBI Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)

OBJECTIVE

The triglyceride (TG) response to a high-fat meal (postprandial lipemia, PPL) affects cardiovascular disease risk and is influenced by genes and environment. Genes involved in lipid metabolism have dominated genetic studies of PPL TG response. We sought to elucidate common genetic variants through a genome-wide association (GWA) study in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN).

METHODS

The GOLDN GWAS discovery sample consisted of 872 participants within families of European ancestry. Genotypes for 2,543,887 variants were measured or imputed from HapMap. Replication of our top results was performed in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 843). PPL TG response phenotypes were constructed from plasma TG measured at baseline (fasting, 0 hour), 3.5 and 6 hours after a high-fat meal, using a random coefficient regression model. Association analyses were adjusted for covariates and principal components, as necessary, in a linear mixed model using the kinship matrix; additional models further adjusted for fasting TG were also performed. Meta-analysis of the discovery and replication studies (n = 1715) was performed on the top SNPs from GOLDN.

RESULTS

GOLDN revealed 111 suggestive (p < 1E-05) associations, with two SNPs meeting GWA significance level (p < 5E-08). Of the two significant SNPs, rs964184 demonstrated evidence of replication (p = 1.20E-03) in the HAPI Heart Study and in a joint analysis, was GWA significant (p = 1.26E-09). Rs964184 has been associated with fasting lipids (TG and HDL) and is near ZPR1 (formerly ZNF259), close to the APOA1/C3/A4/A5 cluster. This association was attenuated upon additional adjustment for fasting TG.

CONCLUSION

This is the first report of a genome-wide significant association with replication for a novel phenotype, namely PPL TG response. Future investigation into response phenotypes is warranted using pathway analyses, or newer genetic technologies such as metabolomics.

Poor Adherence to US Dietary Guidelines for Children and Adolescents in the National Health and Nutrition Examination Survey Population

BACKGROUND

Poor diet quality in childhood and adolescence is associated with adverse health outcomes throughout life, yet the dietary habits of American children and how they change across childhood and adolescence are unknown.

OBJECTIVES

This study sought to describe diet quality among children and adolescents by assessing adherence to the 2010 Dietary Guidelines for Americans (DGA) and to determine whether any differences in adherence occurred across childhood.

DESIGN, SETTING, AND PARTICIPANTS

We employed a cross-sectional design using data from the National Health and Nutrition Examination Survey (NHANES). Of 9,280 children aged 4 to 18 years who participated in NHANES from 2005 to 2010, those with insufficient data on dietary recall (n=852) or who were pregnant or lactating during the time of interview (n=38) were excluded from the final study sample (n=8,390).

MAIN OUTCOME MEASURES

We measured adherence to the DGA using the Healthy Eating Index 2010 (HEI-2010) and stratified participants into three age groups (4 to 8, 9 to 13, and 14 to 18 years of age). We analyzed each of 12 HEI-2010 components and total HEI-2010 score.

RESULTS

The youngest children had the highest overall diet quality due to significantly greater scores for total fruit, whole fruit, dairy, and whole grains. These children also had the highest scores for sodium, refined grains, and empty calories. Total HEI-2010 scores ranged from 43.59 to 52.11 out of 100, much lower than the minimum score of 80 that is thought to indicate a diet associated with good health.

CONCLUSIONS

Overall, children and adolescents are failing to meet the DGA and may be at an increased risk of chronic diseases throughout life. By analyzing which food groups show differences between age groups, we provide data that can inform the development of dietary interventions to promote specific food groups targeting specific ages and improve diet quality among children and adolescents.

Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

OBJECTIVE

Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS

We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS

We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h).

CONCLUSIONS

Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

Risk profiles for weight gain among postmenopausal women: a classification and regression tree analysis approach

Purpose

Risk factors for obesity and weight gain are typically evaluated individually while “adjusting for” the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight.

Methods

This study included 612 postmenopausal women 50–79 years old, enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared.

Results

Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years).

Conclusions

Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.

Dietary Patterns, Genes, and Health: Challenges and Obstacles to be Overcome

Several dietary approaches have been proposed to prevent the onset of chronic diseases. As yet, no single approach has emerged as having the most consistent health benefits. This arises, in part, due to the fact that diet influences health in the context of individual factors with genetic components. Therefore, the effects of diet on health may be dependent on an individual's genetic background. At this time we lack robust evidence for the effects of interactions between genes and dietary patterns on health. To understand why, I will briefly review the most methodologically strong attempts to identify gene-diet interactions, which will illuminate how the challenges facing all of genetic research apply to the search for gene-diet interactions. Then I will discuss some ways in which these challenges are being addressed that offer hope for the future in which the best diet for an individual is identified based on their genetic variation.

Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants

BACKGROUND

Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.

OBJECTIVES

We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.

DESIGN

We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

RESULTS

We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.

CONCLUSIONS

Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.

Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two US populations

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs.

Cognitive performance and BMI in childhood: Shared genetic influences between reaction time but not response inhibition

OBJECTIVE

The aim of this work is to understand whether shared genetic influences can explain the association between obesity and cognitive performance, including slower and more variable reaction times (RTs) and worse response inhibition.

METHODS

RT on a four-choice RT task and the go/no-go task, and commission errors on the go/no-go task for 1,312 twins ages 7-10 years were measured. BMI was measured at 9-12 years. Biometric twin models were run to give an estimate of the genetic correlation (rG ) between body mass index (BMI) and three cognitive measures: mean RT (MRT), RT variability (RTV; the standard deviation of RTs), and commission errors (a measure of response inhibition).

RESULTS

Genetic correlations indicated that 20%-30% of the genes underlying BMI were shared with both RT measures. However, only small phenotypic correlations between MRT and RTV with later BMI (rPh  = ∼0.1) were observed. Commission errors were unassociated with later BMI (rPh  = -0.03, ns).

CONCLUSIONS

Our results are the first to demonstrate significant shared genetic effects between RT performance and BMI. Our findings add biological support to the notion that obesity is associated with slower and more variable RTs. However, our results also emphasize the small nature of the association, which may explain previous negative findings.

Genetic risk scores associated with baseline lipoprotein subfraction concentrations do not associate with their responses to fenofibrate

Lipoprotein subclass concentrations are modifiable markers of cardiovascular disease risk. Fenofibrate is known to show beneficial effects on lipoprotein subclasses, but little is known about the role of genetics in mediating the responses of lipoprotein subclasses to fenofibrate. A recent genomewide association study (GWAS) associated several single nucleotide polymorphisms (SNPs) with lipoprotein measures, and validated these associations in two independent populations. We used this information to construct genetic risk scores (GRSs) for fasting lipoprotein measures at baseline (pre-fenofibrate), and aimed to examine whether these GRSs also associated with the responses of lipoproteins to fenofibrate. Fourteen lipoprotein subclass measures were assayed in 817 men and women before and after a three week fenofibrate trial. We set significance at a Bonferroni corrected alpha <0.05 (p < 0.004). Twelve subclass measures changed with fenofibrate administration (each p = 0.003 to <0.0001). Mixed linear models which controlled for age, sex, body mass index (BMI), smoking status, pedigree and study-center, revealed that GRSs were associated with eight baseline lipoprotein measures (p < 0.004), however no GRS was associated with fenofibrate response. These results suggest that the mechanisms for changes in lipoprotein subclass concentrations with fenofibrate treatment are not mediated by the genetic risk for fasting levels.

Methylation at CPT1A locus is associated with lipoprotein subfraction profiles

Lipoprotein subfractions help discriminate cardiometabolic disease risk. Genetic loci validated as associating with lipoprotein measures do not account for a large proportion of the individual variation in lipoprotein measures. We hypothesized that DNA methylation levels across the genome contribute to interindividual variation in lipoprotein measures. Using data from participants of the Genetics of Lipid Lowering Drugs and Diet Network (n = 663 for discovery and n = 331 for replication stages, respectively), we conducted the first systematic screen of the genome to determine associations between methylation status at ∼470,000 cytosine-guanine dinucleotide (CpG) sites in CD4(+) T cells and 14 lipoprotein subfraction measures. We modeled associations between methylation at each CpG site and each lipoprotein measure separately using linear mixed models, adjusted for age, sex, study site, cell purity, and family structure. We identified two CpGs, both in the carnitine palmitoyltransferase-1A (CPT1A) gene, which reached significant levels of association with VLDL and LDL subfraction parameters in both discovery and replication phases (P < 1.1 × 10(-7) in the discovery phase, P < .004 in the replication phase, and P < 1.1 × 10(-12) in the full sample). CPT1A is regulated by PPARα, a ligand for drugs used to reduce CVD. Our associations between methylation in CPT1A and lipoprotein measures highlight the epigenetic role of this gene in metabolic dysfunction.

The separation of ADHD inattention and hyperactivity-impulsivity symptoms: pathways from genetic effects to cognitive impairments and symptoms

Both shared and unique genetic risk factors underlie the two symptom domains of attention deficit hyperactivity disorder (ADHD): inattention and hyperactivity-impulsivity. The developmental course and relationship to co-occurring disorders differs across the two symptom domains, highlighting the importance of their partially distinct etiologies. Familial cognitive impairment factors have been identified in ADHD, but whether they show specificity in relation to the two ADHD symptom domains remains poorly understood. We aimed to investigate whether different cognitive impairments are genetically linked to the ADHD symptom domains of inattention versus hyperactivity-impulsivity. We conducted multivariate genetic model fitting analyses on ADHD symptom scores and cognitive data, from go/no-go and fast tasks, collected on a population twin sample of 1,312 children aged 7-10. Reaction time variability (RTV) showed substantial genetic overlap with inattention, as observed in an additive genetic correlation of 0.64, compared to an additive genetic correlation of 0.31 with hyperactivity-impulsivity. Commission errors (CE) showed low additive genetic correlations with both hyperactivity-impulsivity and inattention (genetic correlations of 0.17 and 0.11, respectively). The additive genetic correlation between RTV and CE was also low and non-significant at -0.10, consistent with the etiological separation between the two indices of cognitive impairments. Overall, two key cognitive impairments phenotypically associated with ADHD symptoms, captured by RTV and CE, showed different genetic relationships to the two ADHD symptom domains. The findings extend a previous model of two familial cognitive impairment factors in combined subtype ADHD by separating pathways underlying inattention and hyperactivity-impulsivity symptoms.

The association between LRP-1 variants and chylomicron uptake after a high fat meal

BACKGROUND AND AIMS

In vitro studies suggest that low density lipoprotein receptor-related protein 1 (LRP1) plays a role in the secondary uptake of chylomicrons. In addition, in vivo studies using LRP-1 knockout mice show these animals exhibit delayed chylomicron clearance. Whether this is true in humans is unknown. We aimed to determine whether genetic variants in LRP-1 are associated with postprandial chylomicron uptake in humans given an oral fat challenge.

METHODS AND RESULTS

As many as 817 men and women (mean age +/- standard deviation = 48.4 +/- 16.4 years) forming the study population for the Genetics of Lipid Lowering Drugs Network (GOLDN) study ingested an oral fat load of 700 kilocalories per m² of body surface area at 83% fat, after an 8-h fast. Chylomicrons were measured by nuclear resonance spectroscopy (NMR) at fasting, and 3.5 and 6 h after the meal. 26 Single nucleotide polymorphisms (SNPs) in the LRP-1 gene were genotyped on the Affymetrix 6.0 array. Chylomicrons were, as expected, zero at fasting. Mixed linear models adjusted for age, sex, study site and pedigree tested for associations between LRP-1 SNPs and changes in chylomicron concentrations 3.5-6 h. A gene-based test across all 26 SNPs was conducted which corrected for the linkage disequilibrium (LD) between SNPs. 11 LRP-1 SNPs were significantly associated with the change in chylomicron concentration correction for multiple testing (Q < 0.05). The subsequent gene-based test, was also significant (P = 0.01).

CONCLUSION

These results require replication but strongly indicate the role of LRP1 in postprandial lipoprotein uptake and/or clearance.

Preliminary evidence of genetic determinants of adiponectin response to fenofibrate in the Genetics of Lipid Lowering Drugs and Diet Network

BACKGROUND AND AIMS

Adiponectin is an adipose-secreted protein that has been linked to changes in insulin sensitivity, high-density lipoprotein cholesterol levels, and inflammatory patterns. Although fenofibrate therapy can raise adiponectin levels, treatment response is heterogeneous and heritable, suggesting a role for genetic mediators. This is the first genome-wide association study of fenofibrate effects on circulating adiponectin.

METHODS AND RESULTS

Plasma adiponectin was measured in participants of the Genetics of Lipid Lowering Drugs and Diet Network (n = 793) before and after a 3-week daily treatment with 160 mg of fenofibrate. Associations between variants on the Affymetrix Genome-Wide Human SNP Array 6.0 and adiponectin were assessed using mixed linear models, adjusted for age, sex, site, and family. We observed a statistically significant (P = 5 × 10⁻⁸) association between rs2384207 in 12q24, a region previously linked to several metabolic traits, and the fenofibrate-induced change in circulating adiponectin. Additionally, our genome-wide analysis of baseline adiponectin levels replicated the previously reported association with CDH13 and suggested novel associations with markers near the PCK1, ZBP1, TMEM18, and SCUBE1 genes. The findings from the single marker tests were corroborated in gene-based analyses. Biological pathway analyses suggested a borderline significant association between the EGF receptor signaling pathway and baseline adiponectin levels.

CONCLUSIONS

We present preliminary evidence linking several biologically relevant genetic variants to adiponectin levels at baseline and in response to fenofibrate therapy. Our findings provide support for fine-mapping of the 12q24 region to investigate the shared biological mechanisms underlying levels of circulating adiponectin and susceptibility to metabolic disease.

Epigenetics and obesity: a relationship waiting to be explained

Obesity can have multifactorial causes that may change with development and are not simply attributable to one's genetic constitution. To date, expensive and laborious genome-wide association studies have only ascribed a small contribution of genetic variants to obesity. The emergence of the field of epigenetics now offers a new paradigm with which to study excess fat mass. Currently, however, there are no compelling epigenetic studies to explain the role of epigenetics in obesity, especially from a developmental perspective. It is clear that until there are advances in the understanding of the main mechanisms by which different fat types, i.e. brown, beige, and white, are established and how these differ between depots and species, population-based studies designed to determine specific aspects of epigenetics will be potentially limited. Obesity is a slowly evolving condition that is not simply explained by changes in the intake of one macronutrient. The latest advances in epigenetics, coupled with the establishment of relevant longitudinal models of obesity, which incorporate functionally relevant end points, may now permit the precise contribution of epigenetic modifications to excess fat mass to be effectively studied.

Lipoprotein receptor-related protein 1 variants and dietary fatty acids: meta-analysis of European origin and African American studies

OBJECTIVE

Low-density lipoprotein-related receptor protein 1 (LRP1) is a multi-functional endocytic receptor and signaling molecule that is expressed in adipose and the hypothalamus. Evidence for a role of LRP1 in adiposity is accumulating from animal and in vitro models, but data from human studies are limited. The study objectives were to evaluate (i) relationships between LRP1 genotype and anthropometric traits, and (ii) whether these relationships were modified by dietary fatty acids.

DESIGN AND METHODS

We conducted race/ethnic-specific meta-analyses using data from 14 studies of US and European whites and 4 of African Americans to evaluate associations of dietary fatty acids and LRP1 genotypes with body mass index (BMI), waist circumference and hip circumference, as well as interactions between dietary fatty acids and LRP1 genotypes. Seven single-nucleotide polymorphisms (SNPs) of LRP1 were evaluated in whites (N up to 42 000) and twelve SNPs in African Americans (N up to 5800).

RESULTS

After adjustment for age, sex and population substructure if relevant, for each one unit greater intake of percentage of energy from saturated fat (SFA), BMI was 0.104 kg m(-2) greater, waist was 0.305 cm larger and hip was 0.168 cm larger (all P<0.0001). Other fatty acids were not associated with outcomes. The association of SFA with outcomes varied by genotype at rs2306692 (genotyped in four studies of whites), where the magnitude of the association of SFA intake with each outcome was greater per additional copy of the T allele: 0.107 kg m(-2) greater for BMI (interaction P=0.0001), 0.267 cm for waist (interaction P=0.001) and 0.21 cm for hip (interaction P=0.001). No other significant interactions were observed.

CONCLUSION

Dietary SFA and LRP1 genotype may interactively influence anthropometric traits. Further exploration of this, and other diet x genotype interactions, may improve understanding of interindividual variability in the relationships of dietary factors with anthropometric traits.

Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake

BACKGROUND

Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.

OBJECTIVE

The objective of the study was to identify common genetic variants that are associated with macronutrient intake.

DESIGN

We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.

RESULTS

A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)).

CONCLUSION

Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Genetic analysis of reaction time variability: room for improvement?

BACKGROUND

Increased reaction time variability (RTV) on cognitive tasks requiring a speeded response is characteristic of several psychiatric disorders. In attention deficit hyperactivity disorder (ADHD), the association with RTV is strong phenotypically and genetically, yet high RTV is not a stable impairment but shows ADHD-sensitive improvement under certain conditions, such as those with rewards. The state regulation theory proposed that the RTV difference score, which captures change from baseline to a rewarded or fast condition, specifically measures 'state regulation'. By contrast, the interpretation of RTV baseline (slow, unrewarded) scores is debated. We aimed to investigate directly the degree of phenotypic and etiological overlap between RTV baseline and RTV difference scores. Method We conducted genetic model fitting analyses on go/no-go and fast task RTV data, across task conditions manipulating rewards and event rate, from a population-based twin sample (n=1314) and an ADHD and control sibling-pair sample (n=1265).

RESULTS

Phenotypic and genetic/familial correlations were consistently high (0.72-0.98) between RTV baseline and difference scores, across tasks, manipulations and samples. By contrast, correlations were low between RTV in the manipulated condition and difference scores. A comparison across two different go/no-go task RTV difference scores (slow-fast/slow-incentive) showed high phenotypic and genetic/familial overlap (r = 0.75-0.83).

CONCLUSIONS

Our finding that RTV difference scores measure largely the same etiological process as RTV under baseline condition supports theories emphasizing the malleability of the observed high RTV. Given the statistical shortcomings of difference scores, we recommend the use of RTV baseline scores for most analyses, including genetic analyses.

Genetic variants associated with VLDL, LDL and HDL particle size differ with race/ethnicity

Specific constellations of lipoprotein particle features, reflected as differences in mean lipoprotein particle diameters, are associated with risk of insulin resistance (IR) and cardiovascular disease (CVD). The associations of lipid profiles with disease risk differ by race/ethnicity, the reason for this is not clear. We aimed to examine whether there were additional genetic differences between racial/ethnic groups on lipoprotein profile. Genotypes were assessed using the Affymetrix 6.0 array in 817 related Caucasian participants of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Association analysis was conducted on fasting mean particle diameters using linear models, adjusted for age, sex and study center as fixed effects, and pedigree as a random effect. Replication of associations reaching P < 1.97 × 10(-05) (the level at which we achieved at least 80% power to replicate SNP-phenotype associations) was conducted in the Caucasian population of the Multi-Ethnic Study of Atherosclerosis (MESA; N = 2,430). Variants which replicated across both Caucasian populations were subsequently tested for association in the African-American (N = 1,594), Chinese (N = 758), and Hispanic (N = 1,422) populations of MESA. Variants in the APOB gene region were significantly associated with mean VLDL diameter in GOLDN, and in the Caucasian and Hispanic populations of MESA, while variation in the hepatic lipase (LIPC) gene was associated with mean HDL diameter in both Caucasians populations only. Our findings suggest that the genetic underpinnings of mean lipoprotein diameter differ by race/ethnicity. As lipoprotein diameters are modifiable, this may lead new strategies to modify lipoprotein profiles during the reduction of IR that are sensitive to race/ethnicity.

Genetic analysis of 16 NMR-lipoprotein fractions in humans, the GOLDN study

Sixteen nuclear magnetic resonance (NMR) spectroscopy lipoprotein measurements of more than 1,000 subjects of GOLDN study, at fasting and at 3.5 and 6 h after a postprandial fat (PPL) challenge at visits 2 and 4, before and after a 3 weeks Fenofibrate (FF) treatment, were included in 6 time-independent multivariate factor analyses. Their top 1,541 unique SNPs were assessed for association with GOLDN NMR-particles and classical lipids. Several SNPs with -log₁₀ p > 7.3 and MAF ≥ 0.10, mostly intergenic associated with NMR-single traits near genes FAM84B (8q24.21), CRIPT (2p21), ACOXL (2q13), BCL2L11 (2q13), PCDH10 (4q28.3), NXPH1 (7p22), and SLC24A4 (14q32.12) in association with NMR-LDLs; HOMER1 (5q14.2), KIT (4q11-q12), VSNL1 (2p24.3), QPRT (16p11.2), SYNPR (3p14.2), NXPH1 (7p22), NELL1 (11p15.1), and RUNX3 (1p36) with NMR-HDLs; and DOK5-CBLN4-MC3R (20q13), NELL1 (11p15.1), STXBP6 (14q12), APOB (2p24-p23), GPR133 (12q24.33), FAM84B (8q24.21) and NR5A2 (1q32.1) in association with NMR-VLDLs particles. NMR single traits associations produced 75 % of 114 significant candidates, 7 % belonged to classical lipids and 18 % overlapped, and 16 % matched for time of discovery between NMR- and classical traits. Five proxy genes, (ACOXL, FAM84B, NXPH1, STK40 and VAPA) showed pleiotropic effects. While tagged for significant associations in our study and with some extra evidence from the literature, candidates as CBNL4, FAM84B, NXPH1, SLC24A4 remain unclear for their functional relation to lipid metabolism. Although GOLDN study is one of the largest in studying PPL and FF treatment effects, the relatively small samples (over 700-1,000 subjects) in association tests appeals for a replication of such a study. Thus, further investigation is needed.

Neuropsychological correlates of emotional lability in children with ADHD

BACKGROUND

Emotional lability (EL) is commonly seen in patients with attention-deficit/hyperactivity disorder (ADHD). The reasons for this association remain currently unknown. To address this question, we examined the relationship between ADHD and EL symptoms, and performance on a range of neuropsychological tasks to clarify whether EL symptoms are predicted by particular cognitive and/or motivational dysfunctions and whether these associations are mediated by the presence of ADHD symptoms.

METHODS

A large multi-site sample of 424 carefully diagnosed ADHD cases and 564 unaffected siblings and controls aged 6-18 years performed a broad neuropsychological test battery, including a Go/No-Go Task, a warned four-choice Reaction Time task, the Maudsley Index of Childhood Delay Aversion and Digit span backwards. Neuropsychological variables were aggregated as indices of processing speed, response variability, executive functions, choice impulsivity and the influence of energetic and/or motivational factors. EL and ADHD symptoms were regressed on each neuropsychological variable in separate analyses controlling for age, gender and IQ, and, in subsequent regression analyses, for ADHD and EL symptoms respectively.

RESULTS

Neuropsychological variables significantly predicted ADHD and EL symptoms with moderate-to-low regression coefficients. However, the association between neuropsychological parameters on EL disappeared entirely when the effect of ADHD symptoms was taken into account, revealing that the association between the neuropsychological performance measures and EL is completely mediated statistically by variations in ADHD symptoms. Conversely, neuropsychological effects on ADHD symptoms remained after EL symptom severity was taken into account.

CONCLUSIONS

The neuropsychological parameters examined, herein, predict ADHD more strongly than EL. They cannot explain EL symptoms beyond what is already accounted for by ADHD symptom severity. The association between EL and ADHD cannot be explained by these cognitive or motivational deficits. Alternative mechanisms, including overlapping genetic influences (pleiotropic effects) and/or alternative neuropsychological processes need to be considered.

Variants identified in a GWAS meta-analysis for blood lipids are associated with the lipid response to fenofibrate

A recent large-scale meta-analysis of genome-wide studies has identified 95 loci, 59 of them novel, as statistically significant predictors of blood lipid traits; we tested whether the same loci explain the observed heterogeneity in response to lipid-lowering therapy with fenofibrate. Using data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, n = 861) we fit linear mixed models with the genetic markers as predictors and high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and triglyceride concentrations as outcomes. For all four traits, we analyzed both baseline levels and changes in response to treatment with fenofibrate. For the markers that were significantly associated with fenofibrate response, we fit additional models evaluating potential epistatic interactions. All models were adjusted for age, sex, and study center as fixed effects, and pedigree as a random effect. Statistically significant associations were observed between the rs964184 polymorphism near APOA1 (P-value≤0.0001) and fenofibrate response for HDL and triglycerides. The association was replicated in the Pharmacogenetics of Hypertriglyceridemia in Hispanics study (HyperTG, n = 267). Suggestive associations with fenofibrate response were observed for markers in or near PDE3A, MOSC1, FLJ36070, CETP, the APOE-APOC1-APOC4-APOC2, and CILP2. Finally, we present strong evidence for epistasis (P-value for interaction =  0.0006 in GOLDN, 0.05 in HyperTG) between rs10401969 near CILP2 and rs4420638 in the APOE-APOC1-APOC4-APOC2 cluster with total cholesterol response to fenofibrate. In conclusion, we present evidence linking several novel and biologically relevant genetic polymorphisms to lipid lowering drug response, as well as suggesting novel gene-gene interactions in fenofibrate pharmacogenetics.