So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

/pdf/discovery-and-refinement-of-loci-associated-with-lipid-17wc78w8iu.pdf

Discovery and refinement of loci associated with lipid levels

Although genome-wide association studies (GWASs) have identified numerous loci associated with complex traits, imprecise modeling of the genetic relatedness within study samples may cause substantial inflation of test statistics and possibly spurious associations. Variance component approaches, such as efficient mixed-model association (EMMA), can correct for a wide range of sample structures by explicitly accounting for pairwise relatedness between individuals, using high-density markers to model the phenotype distribution; but such approaches are computationally impractical. We report here a variance component approach implemented in publicly available software, EMMA eXpedited (EMMAX), that reduces the computational time for analyzing large GWAS data sets from years to hours. We apply this method to two human GWAS data sets, performing association analysis for ten quantitative traits from the Northern Finland Birth Cohort and seven common diseases from the Wellcome Trust Case Control Consortium. We find that EMMAX outperforms both principal component analysis and genomic control in correcting for sample structure.

/pdf/variance-component-model-to-account-for-sample-structure-in-19yuqk3ki9.pdf

Variance component model to account for sample structure in genome-wide association studies

Blood pressure is a heritable trait(1) influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (>= 140 mm Hg systolic blood pressure or >= 90 mm Hg diastolic blood pressure)(2). Even small increments in blood pressure are associated with an increased risk of cardiovascular events(3). This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

https://serval.unil.ch/resource/serval:BIB_1DC9105514C9.P002/REF.pdf

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk

The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI (p ¼ 8.6 310 � 7 ), hip circumference (p ¼ 3.4 3 10 � 8 ), and weight (p ¼ 9.1 3 10 � 7 ). In Sardinia, homozygotes for the rare ‘‘G’’ allele of this SNP (minor allele frequency ¼ 0.46) were 1.3 BMI units heavier than homozygotes for the common ‘‘A’’ allele. Within the PFKP gene, rs6602024 showed very strong association with BMI (p ¼4.9 310 � 6 ). Homozygotes for the rare ‘‘A’’ allele of this SNP (minor allele frequency ¼0.12) were 1.8 BMI units heavier than homozygotes for the common ‘‘G’’ allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans (N ¼ 1,496) and in Hispanic Americans (N ¼ 839), we replicated significant association between rs9930506 in the FTO gene and BMI (p-value for meta-analysis of European American and Hispanic American follow-up samples, p ¼0.001), weight (p ¼0.001), and hip circumference (p ¼0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare ‘‘A’’ allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common ‘‘G’’ allele. In summary, we have completed a whole genome– association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population.

/pdf/genome-wide-association-scan-shows-genetic-variants-in-the-1c6gx7vp72.pdf

Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits.

In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14–102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.

/pdf/heritability-of-cardiovascular-and-personality-traits-in-6-5f7pdb3h76.pdf

Paola Loi

Papers

Heritability of Cardiovascular and Personality Traits in 6,148 Sardinians