Evidence Of Shared Genetic Effects Research Articles

Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits.

We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci. We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test. We identified 6 novels (CD36, PITX2, EMB, ZNF592, YPEL2, and BC043580) and 87 known loci (adaptive sum of powered score test P<5×10-9). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci. Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.

Multi-ethnic genome-wide association study of decomposed cardioelectric phenotypes illustrates strategies to identify and characterize evidence of shared genetic effects for complex traits

Multi-ethnic genome-wide association study of decomposed cardioelectric phenotypes illustrates strategies to identify and characterize evidence of shared genetic effects for complex traits

Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types.

Most autoimmune-disease-risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene-regulatory activity. GWAS loci are also enriched in expression quantitative trait loci (eQTLs), thus suggesting that most risk variants alter gene expression. However, because causal variants are difficult to identify, and cis-eQTLs occur frequently, it remains challenging to identify specific instances of disease-relevant changes to gene regulation. Here, we used a novel joint likelihood framework with higher resolution than that of previous methods to identify loci where autoimmune-disease risk and an eQTL are driven by a single shared genetic effect. Using eQTLs from three major immune subpopulations, we found shared effects in only ∼25% of the loci examined. Thus, we show that a fraction of gene-regulatory changes suggest strong mechanistic hypotheses for disease risk, but we conclude that most risk mechanisms are not likely to involve changes in basal gene expression.

Shared genetic factors influence risk for bipolar disorder and alcohol use disorders

Bipolar disorder and alcohol use disorder (AUD) have a high rate of comorbidity, more than 50% of individuals with bipolar disorder also receive a diagnosis of AUD in their lifetimes. Although both disorders are heritable, it is unclear if the same genetic factors mediate risk for bipolar disorder and AUD. We examined 733 Costa Rican individuals from 61 bipolar pedigrees. Based on a best estimate process, 32% of the sample met criteria for bipolar disorder, 17% had a lifetime AUD diagnosis, 32% met criteria for lifetime nicotine dependence, and 21% had an anxiety disorder. AUD, nicotine dependence and anxiety disorders were relatively more common among individuals with bipolar disorder than in their non-bipolar relatives. All illnesses were shown to be heritable and bipolar disorder was genetically correlated with AUD, nicotine dependence and anxiety disorders. The genetic correlation between bipolar and AUD remained when controlling for anxiety, suggesting that unique genetic factors influence the risk for comorbid bipolar and AUD independent of anxiety. Our findings provide evidence for shared genetic effects on bipolar disorder and AUD risk. Demonstrating that common genetic factors influence these independent diagnostic constructs could help to refine our diagnostic nosology.

Genetic Epidemiology of BMI and Body Mass Change From Adolescence to Young Adulthood

The complex interplay between genes and environment affecting body mass gain over lifecycle periods of risk is not well understood. We use longitudinal sibling cohort data to examine the role of shared household environment, additive genetic, and shared genetic effects on BMI and BMI change. In the National Longitudinal Study of Adolescent Health, siblings and twin pairs sharing households for > or =10 years as adolescents (N = 5,524; mean = 16.5 +/- 1.7 years) were followed into young adulthood (N = 4,368; mean = 22.4 +/- 1.8 years). Using a variance component approach, we quantified genetic and household effects on BMI in siblings and nonsiblings sharing household environments over time. Adjusting for race, age, sex, and age-by-sex interaction, we detected a heritability of 0.43 +/- 0.05 for BMI change. Significant household effects were noted during the young adulthood period only (0.11 +/- 0.06). We find evidence for shared genetic effects between BMI and BMI change during adolescence (genetic correlation (rho(G)) = 0.61 +/- 0.03) and young adulthood (rho(G) = 0.23 +/- 0.06). Our findings support a complex etiology of BMI and BMI change.

Evidence of Shared Genetic Effects Between Pre‐ and Postobesity Epidemic BMI Levels

United States has experienced a widespread obesity epidemic. However, it is unclear whether the obesogenic environment has uncovered genes previously unimportant in adiposity or whether genes influencing obesity are the same before and after the obesity epidemic. The objective of this study was to test whether BMI pre- and postobesity epidemic would be controlled by shared genetic effects. A 25-30-year follow-up of parents and children who participated in the National Institutes of Health-National Heart, Lung, and Blood Institute Lipid Research Clinics (LRC) Princeton School Study, 1973-1976, were followed up in 1999-2004 in the Princeton Follow-up Study (PFS). Heritability of BMI and genetic correlations between pre-epidemic BMI and BMI z-scores in adolescents and postobesity epidemic BMI were calculated. Even though they had similar ages, offspring had higher BMI in PFS than their parents in LRC (28.5 +/- 6.6 vs. 26.1 +/- 4.4, P < 0.0001). BMI measurements in offspring were strongly heritable (BMI(LRC): h(2) = 0.78 +/- 0.17; BMI z-score(LRC): h(2) = 0.61 +/- 0.16; BMI(PFS): h(2) = 0.64 +/- 0.16, all P < or = 0.0001). Further, the change of BMI exhibited a high heritability (h(2) = 0.51 +/- 0.18, P = 0.003). Bivariate analysis of BMI in LRC and PFS showed significant genetic correlation (0.70 +/- 0.16, P = 0.005), whereas the environmental correlation was not significant (0.36 +/- 0.17). Although the obesogenic environment may have changed between the 1970s and 2000s, many of the same genes are likely to be involved in establishing genetic susceptibility to obesity. Furthermore, shared genetic effects survive the period of the transition from adolescence to adulthood.

Further evidence for shared genetic effects between psychotic bipolar disorder and P50 suppression: A combined twin and family study

P50 suppression deficit has been reported in patients with psychotic bipolar disorder. In our previous report on twin pairs concordant and discordant for bipolar disorder, we found significant genetic overlap between bipolar disorder and P50 sensory gating. However, the sample size in that study was relatively small. A separate study, the Maudsley Bipolar Family Study, reported diminished P50 gating in unaffected relatives of psychotic bipolar patients. However, genetic and environmental influences are confounded in family studies due to lack of monozygotic (MZ) twin pairs. The current study combines the twin sample and the family sample in order to improve statistical power and study design, with the aims of: (1) substantiating the association between psychotic bipolar disorder and diminished P50 suppression and (2) verifying the genetic overlap between the two traits reported in the twin sample. We also assessed the relationship between bipolar disorder and an alternative suppression index, the P50 Condition-Testing (C-T) amplitude difference. A total of 309 subjects was included in this study, comprising 91 twin pairs, 31 bipolar families, and 45 unrelated healthy controls. Statistical analyses were based on structural equation modeling. Bipolar disorder was significantly associated with a diminished P50 suppression ratio and decreased C-T amplitude difference. Shared genetic factors were the main source of these associations. Suppression impairment was due to larger, poorly gated, T amplitude responses. The results provide further evidence that impaired P50 suppressions are promising endophenotypes for psychotic bipolar disorder. The non-specificity of impaired P50 suppression may reflect the impact of shared psychosis susceptibility genes.

Comparison of strategies for identification of regulatory quantitative trait loci of transcript expression traits

In order to identify regulatory genes, we determined the heritability of gene transcripts, performed linkage analysis to identify quantitative trait loci (QTLs), and evaluated the evidence for shared genetic effects among transcripts with co-localized QTLs in non-diseased participants from 14 CEPH (Centre d'Etude du Polymorphisme Humain) Utah families. Seventy-six percent of transcripts had a significant heritability and 54% of them had LOD score >or= 1.8. Bivariate genetic analysis of 15 transcripts that had co-localized QTLs on 4q28.2-q31.1 identified significant genetic correlation among some transcripts although no improvement in the magnitude of LOD scores in this region was noted. Similar results were found in analysis of 12 transcripts, that had co-localized QTLs in the 13q34 region. Principal-component analyses did not improve the ability to identify chromosomal regions of co-localized gene expressions.

Quantitative genetic analysis of lipoproteins in Finnish hyperlipidemic families

P16 Familial combined hyperlipidemia (FCHL) is a common familial dyslipidemia associated with CVD risk. FCHL is characterized by higher levels of apolipoprotein B (ApoB),triglyceride (TG), smaller low-density lipoprotein particle size (LDL size) and lower high-density lipoprotein cholesterol (HDLC). The purpose of this analysis was to evaluate evidence for shared genetic effects between these fasting measurements in 365 subjects in 37 Finnish FCHL families. Mean age was 48 yrs (SD=16), 50% were male. Quantitative genetic analysis was used to evaluate the genetic (ρG) and environmental (ρE) correlations between each pair of risk factors (RF) adjusting for age and sex. Heritability was significant(p&lt;0.02) for each RF. The ρG for each pair reflects shared genetic influences, i.e. genes that influence variation in both RF of the pair. The ρG’s for LDL size and both TG and HDLC suggest that these RF share a majority of genes in common. ρG for ApoB and TG shows that these RF also share genes in common, suggesting that at least two sets of genes influence the lipoprotein RF characterizing FCHL. Shared environmental (ρE) factors also contribute to the covariation in each pair. Using this information in mapping studies may improve power to detect genes underlying these lipoprotein abnormalities, and lead to a better understanding of genetic susceptibility to CVD in FCHL. Table 1.