Approved research

Genetic architecture of disease and related anthropometric phenotypes

Lay summary

We are interested in how anthropomorphic and health/disease phenotypes are associated with health and disease. The specific aim of this study is to examine association signals from SNPs, examine how much of the variation is captured by examining all SNPs simultaneously, and look at the extent to which SNPs that predict variation in these phenotypes in one ethnic group also predict variation in these traits in other ethnic groups. We would also like to conduct association analyses of tobacco use and alcohol phenotypes and meta-analyze them with results from other studies. Finally, we are interested in using these phenotypes to test new methods for using SNP data to estimate the heritability of traits. Several ?intermediate? factors, such as anthropometric phenotypes (e.g.,BMI and height) and blood proteins (e.g., cholesterol) affect human health and disease, yet the genetic underpinnings of these phenotypes remain poorly characterized. This is a request for access to data relevant to health elated traits in order to help elucidate the patterns of genetic variation that may underlie these traits. Access to data containing health and disease outcomes will allow study of the genetic variation underlying the particular diseases, and the relationship of that variation to anthropometric risk factors and correlates.Understanding the genetic architecture of anthropomorphic and health/disease phenotypes can lead to greater understanding of the mediating factors that affect the burden of health and disease in modern societies. We plan to use genetic data (single nucleotide polymorphism data) to investigate whether certain genetic variants predict these intermediate and disease traits, and how well we can predict these traits by considering all genetic data simultaneously. Our methods require large samples; we would like access to all whole genome genotyped data possible.

EXPANDED SCOPE 2: In addition to previously discussed approaches, we would like to use UK Biobank exomic and imputed SNP data to a) understand the degree to which gene signals from common variants overlap with gene signals from rare variants; b) explore SNP and gene-by-environment interactions for addiction-related behaviors, psychiatric disorders, and age-related cognitive decline; c) estimate heritability and common familial environmental effects using close and distant relatives as detected using identical by descent segments; and d) examine the genetic and phenotypic factor structure of traits related to psychiatric disorders, personality, pain, and disease.

Scope extension:

ORIGINAL SCOPE: We are interested in how anthropomorphic and health/disease phenotypes are associated with health and disease. The specific aim of this study is to examine association signals from SNPs, examine how much of the variation is captured by examining all SNPs simultaneously, and look at the extent to which SNPs that predict variation in these phenotypes in one ethnic group also predict variation in these traits in other ethnic groups. We would also like to conduct association analyses of tobacco use and alcohol phenotypes and meta-analyze them with results from other studies. Finally, we are interested in using these phenotypes to test new methods for using SNP data to estimate the heritability of traits.

EXPANDED SCOPE: We want to continue to focus on employing and developing methods that elucidate the genetic architecture of complex traits. In addition to previously discussed approaches, we plan to compare estimates of SNP-heritability to those from twin-heritability; to use various reference panels to impute new SNPs, indels, and VNTRs into UK Biobank data; to use distant genetic relatives, identified by whole-genome SNP data, to estimate the (co)heritability and environmental variation of traits; to understand how assortative mating influences heritability estimation; and to use SNP-heritability methods to explore the allelic spectra of traits and annotations that are particularly relevant to trait variation.

EXPANDED SCOPE 2: In addition to previously discussed approaches, we would like to use UK Biobank exomic and imputed SNP data to a) understand the degree to which gene signals from common variants overlap with gene signals from rare variants; b) explore SNP and gene-by-environment interactions for addiction-related behaviors, psychiatric disorders, and age-related cognitive decline; c) estimate heritability and common familial environmental effects using close and distant relatives as detected using identical by descent segments; and d) examine the genetic and phenotypic factor structure of traits related to psychiatric disorders, personality, pain, and disease.

EXPANDED SCOPE 3: We want to continue to employ and develop approaches that elucidate the genetic architecture of traits, trait heritability, and the causes of phenotypic (co-)variation in health-related and anthropometric traits. In addition to previously discussed approaches, we will investigate the genetic and environmental causes of pairwise resemblance in the UK Biobank by modeling the similarity of close family members and distant relatives (e.g., parent-offspring, siblings, spouses, avunculars, cousins, and more distant relatives up to ~8th degree). We will estimate and model the influences of assortative mating by estimating the degree of partner concordance and using this in models that estimate the genetic and environmental causes of phenotypic (co-)variation and relative similarity. We will use identical by descent haplotypes shared between close and distant relatives to improve phase of genotypic data, which can be used, for example, to differentiate half-relatives of degree Y from full relatives of degree Y+1.

Scope extension:

We are interested in how anthropomorphic and health/disease phenotypes are associated with health and disease. The specific aim of this study is to examine association signals from SNPs, examine how much of the variation is captured by examining all SNPs simultaneously, and look at the extent to which SNPs that predict variation in these phenotypes in one ethnic group also predict variation in these traits in other ethnic groups. We would also like to conduct association analyses of tobacco use and alcohol phenotypes and meta-analyze them with results from other studies. Finally, we are interested in using these phenotypes to test new methods for using SNP data to estimate the heritability of traits.

We want to continue to focus on employing and developing methods that elucidate the genetic architecture of complex traits. In addition to previously discussed approaches, we plan to compare estimates of SNP-heritability to those from twin-heritability; to use various reference panels to impute new SNPs, indels, and VNTRs into UK Biobank data; to use distant genetic relatives, identified by whole-genome SNP data, to estimate the (co)heritability and environmental variation of traits; to understand how assortative mating influences heritability estimation; and to use SNP-heritability methods to explore the allelic spectra of traits and annotations that are particularly relevant to trait variation.

In addition to previously discussed approaches, we would like to use UK Biobank exomic and imputed SNP data to a) understand the degree to which gene signals from common variants overlap with gene signals from rare variants; b) explore SNP and gene-by-environment interactions for addiction-related behaviors, psychiatric disorders, and age-related cognitive decline; c) estimate heritability and common familial environmental effects using close and distant relatives as detected using identical by descent segments; and d) examine the genetic and phenotypic factor structure of traits related to psychiatric disorders, personality, pain, and disease.

We want to continue to employ and develop approaches that elucidate the genetic architecture of traits, trait heritability, and the causes of phenotypic (co-)variation in health-related and anthropometric traits. In addition to previously discussed approaches, we will investigate the genetic and environmental causes of pairwise resemblance in the UK Biobank by modeling the similarity of close family members and distant relatives (e.g., parent-offspring, siblings, spouses, avunculars, cousins, and more distant relatives up to ~8th degree). We will estimate and model the influences of assortative mating by estimating the degree of partner concordance and using this in models that estimate the genetic and environmental causes of phenotypic (co-)variation and relative similarity. We will use identical by descent haplotypes shared between close and distant relatives to improve phase of genotypic data, which can be used, for example, to differentiate half-relatives of degree Y from full relatives of degree Y+1.

We'd like to investigate assortative mating in same-sex couples, similarly to how we investigated assortative mating in opposite-sex couples, the latter of which is already covered under the expanded scope of our application. Performing similar research in same-sex couples is relevant to understanding the inheritance of complex traits/diseases through the framework of familial relationship structures outside the typical nuclear family design. Under a dyadic same-sex rearing environment, both parents contribute to the environment of a child but only one parent, at most, contributes genetic influences, providing an opportunity to help disentangle the effects of genetic and environmental influences in a new way. Future studies that wanted to apply genetic family modeling techniques to families with same-sex parents would need to take assortative mating into account to avoid bias. However, there is currently limited data available on assortative mating patterns in same-sex couples, a gap our proposed research could help fill. We plan to determine putative same-sex couples using methodology similar to the methods we used for opposite sex pairs and plan to use sensitivity measures to assess the likelihood of "false positives." We also plan to compare assortative mating patterns across opposite-sex and same-sex pairs.