Alexis C. Frazier-Wood

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).

Neuropsychological correlates of emotional lability in children with ADHD

BACKGROUNDnEmotional 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.nnnMETHODSnA 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.nnnRESULTSnNeuropsychological 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.nnnCONCLUSIONSnThe 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.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.

Neuropsychological intra-individual variability explains unique genetic variance of ADHD and shows suggestive linkage to chromosomes 12, 13 and 17.

Attention‐deficit/hyperactivity disorder (ADHD) is a highly heritable neuropsychiatric disorder that is usually accompanied by neuropsychological impairments. The use of heritable, psychometrically robust traits that show association with the disorder of interest can increase the power of gene‐finding studies. Due to the robust association of intra‐individual variability with ADHD on a phenotypic and genetic level, intra‐individual variability is a prime candidate for such an attempt. We aimed to combine intra‐individual variability measures across tasks into one more heritable measure, to examine the relatedness to other cognitive factors, and to explore the genetic underpinnings through quantitative trait linkage analysis. Intra‐individual variability measures from seven tasks were available for 238 ADHD families (350 ADHD‐affected and 195 non‐affected children) and 147 control families (271 children). Intra‐individual variability measures from seven different tasks shared common variance and could be used to construct an aggregated measure. This aggregated measure was largely independent from other cognitive factors related to ADHD and showed suggestive linkage to chromosomes 12q24.3 (LODu2009=u20092.93), 13q22.2 (LODu2009=u20092.36), and 17p13.3 (LODu2009=u20092.00). A common intra‐individual variability construct can be extracted from very diverse neuropsychological tasks; this construct taps into unique genetic aspects of ADHD and may relate to loci conferring risk for ADHD (12q24.3 and 17p13.3) and possibly autism (12q24.3). Given that joining of data across sites boosts the power for genetic analyses, our findings are promising in showing that intra‐individual variability measures are viable candidates for across site analyses where different tasks have been used.

Omega-6 fatty acid biomarkers and incident type 2 diabetes: Pooled analysis of individual-level data for 39 740 adults from 20 prospective cohort studies

BACKGROUNDnThe metabolic effects of omega-6 polyunsaturated fatty acids (PUFAs) remain contentious, and little evidence is available regarding their potential role in primary prevention of type 2 diabetes. We aimed to assess the associations of linoleic acid and arachidonic acid biomarkers with incident type 2 diabetes.nnnMETHODSnWe did a pooled analysis of new, harmonised, individual-level analyses for the biomarkers linoleic acid and its metabolite arachidonic acid and incident type 2 diabetes. We analysed data from 20 prospective cohort studies from ten countries (Iceland, the Netherlands, the USA, Taiwan, the UK, Germany, Finland, Australia, Sweden, and France), with biomarkers sampled between 1970 and 2010. Participants included in the analyses were aged 18 years or older and had data available for linoleic acid and arachidonic acid biomarkers at baseline. We excluded participants with type 2 diabetes at baseline. The main outcome was the association between omega-6 PUFA biomarkers and incident type 2 diabetes. We assessed the relative risk of type 2 diabetes prospectively for each cohort and lipid compartment separately using a prespecified analytic plan for exposures, covariates, effect modifiers, and analysis, and the findings were then pooled using inverse-variance weighted meta-analysis.nnnFINDINGSnParticipants were 39u2008740 adults, aged (range of cohort means) 49-76 years with a BMI (range of cohort means) of 23·3-28·4 kg/m2, who did not have type 2 diabetes at baseline. During a follow-up of 366u2008073 person-years, we identified 4347 cases of incident type 2 diabetes. In multivariable-adjusted pooled analyses, higher proportions of linoleic acid biomarkers as percentages of total fatty acid were associated with a lower risk of type 2 diabetes overall (risk ratio [RR] per interquintile range 0·65, 95% CI 0·60-0·72, p<0·0001; I2=53·9%, pheterogeneity=0·002). The associations between linoleic acid biomarkers and type 2 diabetes were generally similar in different lipid compartments, including phospholipids, plasma, cholesterol esters, and adipose tissue. Levels of arachidonic acid biomarker were not significantly associated with type 2 diabetes risk overall (RR per interquintile range 0·96, 95% CI 0·88-1·05; p=0·38; I2=63·0%, pheterogeneity<0·0001). The associations between linoleic acid and arachidonic acid biomarkers and the risk of type 2 diabetes were not significantly modified by any prespecified potential sources of heterogeneity (ie, age, BMI, sex, race, aspirin use, omega-3 PUFA levels, or variants of the FADS gene; all pheterogeneity≥0·13).nnnINTERPRETATIONnFindings suggest that linoleic acid has long-term benefits for the prevention of type 2 diabetes and that arachidonic acid is not harmful.nnnFUNDINGnFunders are shown in the appendix.

The PPAR Alpha gene is associated with triglyceride, low-density cholesterol, and inflammation marker response to fenofibrate intervention: The GOLDN Study

As a peroxisome proliferator-activated receptor alpha (PPARα) agonist, fenofibrate favorably modulates dyslipidemia and inflammation markers, which are associated with cardiovascular risk. To determine whether variation in the PPARα receptor gene was associated with lipid and inflammatory marker response, we conducted a 3-week trial of fenofibrate in 861 men and women. Mixed linear models that controlled for age and sex, as well as family pedigree and study center, were constructed using single-nucleotide polymorphisms (SNPs) in the PPARα gene as predictors and changes in fasting triglycerides (TGs), cholesterol and inflammatory markers as outcomes. Significant associations with low-density cholesterol and interleukin-2 (P<0.001) responses to fenofibrate were found. Although there were suggestive associations with tumor necrosis factor-alpha and TG responses (P<0.05), these did not survive the correction for multiple testing. We conclude that variants in the PPARα gene may contribute to future pharmacogenomic paradigms seeking to predict fenofibrate responders from both an anti-dyslipidemic and anti-inflammatory perspective.

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, nu200a=u200a861) 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, nu200a=u200a267). 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 interactionu200a=u200a 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.

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 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 6xa0h after a postprandial fat (PPL) challenge at visits 2 and 4, before and after a 3xa0weeks 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 −log10pxa0>xa07.3 and MAFxa0≥xa00.10, 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 75xa0% of 114 significant candidates, 7xa0% belonged to classical lipids and 18xa0% overlapped, and 16xa0% 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.

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

BACKGROUND AND AIMSnAdiponectin 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.nnnMETHODS AND RESULTSnPlasma 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.nnnCONCLUSIONSnWe 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.

Genome-wide association study indicates variants associated with insulin signaling and inflammation mediate lipoprotein responses to fenofibrate

Objective A shift towards overall larger very low-density lipoprotein (VLDL), and smaller low-density lipoprotein and high-density lipoprotein (HDL) diameters occurs in insulin resistance (IR), which reflects shifts in the distribution of the subfraction concentrations. Fenofibrate, indicated for hypertriglyceridemia, simultaneously reduces IR and shifts in lipoprotein diameter. Individual responses to fenofibrate vary, and we conducted a genome-wide association study to identify genetic differences that could contribute to such differences. Methods Association analysis was conducted between single nucleotide polymorphisms (SNPs) on the Affymetrix 6.0 array and fasting particle diameter responses to a 12-week fenofibrate trial, in 817 related Caucasian participants of the Genetics of Lipid Lowering Drugs and Diet Network. Linear models were conducted, which adjusted for age, sex and study center as fixed effects, and pedigree as a random effect. The top three SNPs associated with each fraction were examined subsequently for associations with changes in subfraction concentrations. Results SNPs in AHCYL2 and CD36 genes reached, or closely approached, genome-wide levels of significance with VLDL and HDL diameter responses to fenofibrate, respectively (P=4×10−9 and 8×10−8). SNPs in AHCYL2 were associated with a decrease in the concentration of the large VLDL subfraction only (P=0.002). SNPs associated with HDL diameter change were not associated with a single subfraction concentration change (P>0.05) indicating small shifts across all subfractions. Conclusion We report novel associations between lipoprotein diameter responses to fenofibrate and the AHCYL2 and CD36 genes. Previous associations of these genes with IR emphasize the role of IR in mediating lipoprotein response to fenofibrate.