Evaluating empirical bounds on complex disease genetic architecture.
Ontology highlight
ABSTRACT:
SUBMITTER: Agarwala V
PROVIDER: S-EPMC4158716 | biostudies-other | 2013 Dec
REPOSITORIES: biostudies-other
Publications
Evaluating empirical bounds on complex disease genetic architecture.
Agarwala Vineeta V Flannick Jason J Sunyaev Shamil S Altshuler David D
Nature genetics 20131020 12
The genetic architecture of human diseases governs the success of genetic mapping and the future of personalized medicine. Although numerous studies have queried the genetic basis of common disease, contradictory hypotheses have been advocated about features of genetic architecture (for example, the contribution of rare versus common variants). We developed an integrated simulation framework, calibrated to empirical data, to enable the systematic evaluation of such hypotheses. For type 2 diabete ...[more]
Similar Datasets
Project description:Genomic prediction of complex human traits (e.g., height, cognitive ability, bone density) and disease risks (e.g., breast cancer, diabetes, heart disease, atrial fibrillation) has advanced considerably in recent years. Using data from the UK Biobank, predictors have been constructed using penalized algorithms that favor sparsity: i.e., which use as few genetic variants as possible. We analyze the specific genetic variants (SNPs) utilized in these predictors, which can vary from dozens to as many as thirty thousand. We find that the fraction of SNPs in or near genic regions varies widely by phenotype. For the majority of disease conditions studied, a large amount of the variance is accounted for by SNPs outside of coding regions. The state of these SNPs cannot be determined from exome-sequencing data. This suggests that exome data alone will miss much of the heritability for these traits-i.e., existing PRS cannot be computed from exome data alone. We also study the fraction of SNPs and of variance that is in common between pairs of predictors. The DNA regions used in disease risk predictors so far constructed seem to be largely disjoint (with a few interesting exceptions), suggesting that individual genetic disease risks are largely uncorrelated. It seems possible in theory for an individual to be a low-risk outlier in all conditions simultaneously.
| S-EPMC7374622 | biostudies-literature
Project description:BackgroundAlzheimer's disease (AD) is a complex multifactorial neurodegenerative disorder and the most common form of dementia. AD is highly heritable, with heritability estimates of ∼70% from twin studies. Progressively larger genome-wide association studies (GWAS) have continued to expand our knowledge of AD/dementia genetic architecture. Until recently these efforts had identified 39 disease susceptibility loci in European ancestry populations.Recent developmentsTwo new AD/dementia GWAS have dramatically expanded the sample sizes and the number of disease susceptibility loci. The first increased total sample size to 1,126,563-with an effective sample size of 332,376-by predominantly including new biobank and population-based dementia datasets. The second, expands on an earlier GWAS from the International Genomics of Alzheimer's Project (IGAP) by increasing the number of clinically-defined AD cases/controls in addition to incorporating biobank dementia datasets, resulting in a total sample size to 788,989 and an effective sample size of 382,472. Collectively both GWAS identified 90 independent variants across 75 AD/dementia susceptibility loci, including 42 novel loci. Pathway analyses indicate the susceptibility loci are enriched for genes involved in amyloid plaque and neurofibrillary tangle formation, cholesterol metabolism, endocytosis/phagocytosis, and the innate immune system. Gene prioritization efforts for the novel loci identified 62 candidate causal genes. Many of the candidate genes from known and newly discovered loci play key roles in macrophages and highlight phagocytic clearance of cholesterol-rich brain tissue debris by microglia (efferocytosis) as a core pathogenetic hub and putative therapeutic target for AD. WHERE NEXT?: While GWAS in European ancestry populations have substantially enhanced our understanding of AD genetic architecture, heritability estimates from population based GWAS cohorts are markedly smaller than those from twin studies. While this missing heritability is likely due to a combination of factors, it highlights that our understanding of AD genetic architecture and genetic risk mechanisms remains incomplete. These knowledge gaps result from several underexplored areas in AD research. First, rare variants remain understudied due to methodological issues in identifying them and the cost of generating sufficiently powered whole exome/genome sequencing datasets. Second, sample sizes of non-European ancestry populations in AD GWAS remain small. Third, GWAS of AD neuroimaging and cerebrospinal fluid endophenotypes remains limited due to low compliance and high costs associated with measuring amyloid-β and tau levels and other disease-relevant biomarkers. Studies generating sequencing data, including diverse populations, and incorporating blood-based AD biomarkers are set to substantially improve our knowledge of AD genetic architecture.
| S-EPMC10024184 | biostudies-literature
Project description:Abetalipoproteinemia and homozygous hypobetalipoproteinemia are classical Mendelian autosomal recessive and co-dominant conditions, respectively, which are phenotypically similar and are usually caused by bi-allelic mutations in MTTP and APOB genes, respectively. Instances of more complex patterns of genomic variants resulting in this distinct phenotype have not been reported.A 43 year-old male had a longstanding severe deficiency of apolipoprotein (apo) B-containing lipoproteins and circulating fat soluble vitamins consistent with either abetalipoproteinemia or homozygous familial hypobetalipoproteinemia (FHBL). He also had acanthocytosis, a long term history of fat malabsorption, and mild retinopathy, but was free from coagulopathy, myopathy and neuropathy. He had taken high dose oral fat soluble vitamins since childhood.Targeted next generation DNA sequencing revealed several rare heterozygous missense variants in both MTTP and APOB genes known or predicted to be deleterious, in addition to a novel heterozygous missense variant in SAR1B, which encodes the gene causing chylomicron retention disease. Evaluation of first degree relatives with mild FHBL clarified the segregation of variants.The proband's characteristic phenotype likely resulted from an oligogenic interaction involving multiple rare variants in MTTP and APOB, and related genes, each of which individually was associated with a milder or minimal clinical and biochemical phenotype.
| S-EPMC5853080 | biostudies-literature
Project description:Stability is a desirable property of complex ecosystems. If a community of interacting species is at a stable equilibrium point then it is able to withstand small perturbations to component species' abundances without suffering adverse effects. In ecology, the Jacobian matrix evaluated at an equilibrium point is known as the community matrix, which describes the population dynamics of interacting species. A system's asymptotic short- and long-term behaviour can be determined from eigenvalues derived from the community matrix. Here we use results from the theory of pseudospectra to describe intermediate, transient dynamics. We first recover the established result that the transition from stable to unstable dynamics includes a region of 'transient instability', where the effect of a small perturbation to species' abundances-to the population vector-is amplified before ultimately decaying. Then we show that the shift from stability to transient instability can be affected by uncertainty in, or small changes to, entries in the community matrix, and determine lower and upper bounds to the maximum amplitude of perturbations to the population vector. Of five different types of community matrix, we find that amplification is least severe when predator-prey interactions dominate. This analysis is relevant to other systems whose dynamics can be expressed in terms of the Jacobian matrix.
| S-EPMC4915621 | biostudies-literature
Project description:With the remarkable development in inexpensive sequencing technologies and supporting computational tools, we have the promise of medicine being personalized by knowledge of the individual genome. Current technologies provide high throughput, but short reads. Reconstruction of the donor genome is based either on de novo assembly of the (short) reads, or on mapping donor reads to a standard reference. While such techniques demonstrate high success rates for inferring 'simple' genomic segments, they are confounded by segments with complex duplication patterns, including regions of direct medical relevance, like the HLA and the KIR regions.In this work, we address this problem with a method for assessing the quality of a predicted genome sequence for complex regions of the genome. This method combines two natural types of evidence: sequence similarity of the mapped reads to the predicted donor genome, and distribution of reads across the predicted genome. We define a new scoring function for read-to-genome matchings, which penalizes for sequence dissimilarities and deviations from expected read location distribution, and present an efficient algorithm for finding matchings that minimize the penalty. The algorithm is based on a formal problem, first defined in this paper, called Coverage Sensitive many-to-many min-cost bipartite Matching (CSM). This new problem variant generalizes the standard (one-to-one) weighted bipartite matching problem, and can be solved using network flows. The resulting Java-based tool, called SAGE (Scoring function for Assembled GEnomes), is freely available upon request. We demonstrate over simulated data that SAGE can be used to infer correct haplotypes of the highly repetitive KIR region on the Human chromosome 19.
| S-EPMC3622632 | biostudies-literature
Project description:Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype-metabolite associations distributed non-randomly within the genome. These clusters of genotype-metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype-metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable.
| S-EPMC2973833 | biostudies-literature
Project description:Epistasis and pleiotropy feature prominently in the genetic architecture of quantitative traits but are difficult to assess in outbred populations. We performed a diallel cross among coisogenic Drosophila P-element mutations associated with hyperaggressive behavior and showed extensive epistatic and pleiotropic effects on aggression, brain morphology, and genome-wide transcript abundance in head tissues. Epistatic interactions were often of greater magnitude than homozygous effects, and the topology of epistatic networks varied among these phenotypes. The transcriptional signatures of homozygous and double heterozygous genotypes derived from the six mutations imply a large mutational target for aggressive behavior and point to evolutionarily conserved genetic mechanisms and neural signaling pathways affecting this universal fitness trait.
| S-EPMC3193212 | biostudies-literature
Project description:Maize (Zea mays) tassels underwent profound morphological changes during maize domestication and improvement. Although a number of genes affecting maize inflorescence development have been identified, the genetic basis of the morphological changes in maize tassels since domestication is not well understood. Here, using a large population of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped using 19 838 single nucleotide polymorphism (SNP) markers, we performed high-resolution quantitative trait locus (QTL) mapping for five tassel morphological traits. We showed that the five tassel traits were associated with different genetic architecture features. Known genes for maize inflorescence development identified by mutagenesis were significantly enriched in the tassel trait QTLs, and many of these genes, including ramosa1 (ra1), barren inflorescence2 (bif2), unbranched2 (ub2), zea floricaula leafy2 (zfl2) and barren stalk fastigiate1 (baf1), showed evidence of selection. An in-depth nucleotide diversity analysis at the bif2 locus identified strong selection signatures in the 5'-regulatory region. We also found that several known flowering time genes co-localized with tassel trait QTLs. A further association analysis indicated that the maize photoperiod gene ZmCCT was significantly associated with tassel size variation. Using near-isogenic lines, we narrowed down a major-effect QTL for tassel length, qTL9-1, to a 513-kb physical region. These results provide important insights into the genetic architecture that controls maize tassel evolution.
| S-EPMC5363343 | biostudies-literature
Project description:Advances in genetic and genomic technologies over the last thirty years have greatly enhanced our knowledge concerning the genetic architecture of Alzheimer's disease (AD). Several genes including APP, PSEN1, PSEN2, and APOE have been shown to exhibit large effects on disease susceptibility, with the remaining risk loci having much smaller effects on AD risk. Notably, common genetic variants impacting AD are not randomly distributed across the genome. Instead, these variants are enriched within regulatory elements active in human myeloid cells, and to a lesser extent liver cells, implicating these cell and tissue types as critical to disease etiology. Integrative approaches are emerging as highly effective for identifying the specific target genes through which AD risk variants act and will likely yield important insights related to potential therapeutic targets in the coming years. In the future, additional consideration of sex- and ethnicity-specific contributions to risk as well as the contribution of complex gene-gene and gene-environment interactions will likely be necessary to further improve our understanding of AD genetic architecture.
| S-EPMC7409822 | biostudies-literature
Project description:We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA) studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ) same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women.
| S-EPMC3525575 | biostudies-literature