@article {99, title = {Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.}, journal = {Nat Genet}, volume = {52}, year = {2020}, month = {2020 09}, pages = {969-983}, abstract = {

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce {\textquoteright}annotation principal components{\textquoteright}, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

}, keywords = {Cholesterol, LDL, Computer Simulation, Genetic Predisposition to Disease, Genetic Variation, Genome, Genome-Wide Association Study, Humans, Models, Genetic, Molecular Sequence Annotation, Phenotype, Whole Genome Sequencing}, issn = {1546-1718}, doi = {10.1038/s41588-020-0676-4}, author = {Li, Xihao and Li, Zilin and Zhou, Hufeng and Gaynor, Sheila M and Liu, Yaowu and Chen, Han and Sun, Ryan and Dey, Rounak and Arnett, Donna K and Aslibekyan, Stella and Ballantyne, Christie M and Bielak, Lawrence F and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Broome, Jai G and Conomos, Matthew P and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and Freedman, Barry I and Guo, Xiuqing and Hindy, George and Irvin, Marguerite R and Kardia, Sharon L R and Kathiresan, Sekar and Khan, Alyna T and Kooperberg, Charles L and Laurie, Cathy C and Liu, X Shirley and Mahaney, Michael C and Manichaikul, Ani W and Martin, Lisa W and Mathias, Rasika A and McGarvey, Stephen T and Mitchell, Braxton D and Montasser, May E and Moore, Jill E and Morrison, Alanna C and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Pampana, Akhil and Peralta, Juan M and Peyser, Patricia A and Psaty, Bruce M and Redline, Susan and Rice, Kenneth M and Rich, Stephen S and Smith, Jennifer A and Tiwari, Hemant K and Tsai, Michael Y and Vasan, Ramachandran S and Wang, Fei Fei and Weeks, Daniel E and Weng, Zhiping and Wilson, James G and Yanek, Lisa R and Neale, Benjamin M and Sunyaev, Shamil R and Abecasis, Gon{\c c}alo R and Rotter, Jerome I and Willer, Cristen J and Peloso, Gina M and Natarajan, Pradeep and Lin, Xihong} } @article {113, title = {Improving the trans-ancestry portability of polygenic risk scores by prioritizing variants in predicted cell-type-specific regulatory elements.}, journal = {Nat Genet}, volume = {52}, year = {2020}, month = {2020 12}, pages = {1346-1354}, abstract = {

Poor trans-ancestry portability of polygenic risk scores is a consequence of Eurocentric genetic studies and limited knowledge of shared causal variants. Leveraging regulatory annotations may improve portability by prioritizing functional over tagging variants. We constructed a resource of 707 cell-type-specific IMPACT regulatory annotations by aggregating 5,345 epigenetic datasets to predict binding patterns of 142 transcription factors across 245 cell types. We then partitioned the common SNP heritability of 111 genome-wide association study summary statistics of European (average n ≈ 189,000) and East Asian (average n ≈ 157,000) origin. IMPACT annotations captured consistent SNP heritability between populations, suggesting prioritization of shared functional variants. Variant prioritization using IMPACT resulted in increased trans-ancestry portability of polygenic risk scores from Europeans to East Asians across all 21 phenotypes analyzed (49.9\% mean relative increase in R). Our study identifies a crucial role for functional annotations such as IMPACT to improve the trans-ancestry portability of genetic data.

}, keywords = {Asian Continental Ancestry Group, Base Sequence, Computational Biology, Enhancer Elements, Genetic, European Continental Ancestry Group, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Models, Genetic, Molecular Sequence Annotation, Multifactorial Inheritance, Polymorphism, Single Nucleotide}, issn = {1546-1718}, doi = {10.1038/s41588-020-00740-8}, author = {Amariuta, Tiffany and Ishigaki, Kazuyoshi and Sugishita, Hiroki and Ohta, Tazro and Koido, Masaru and Dey, Kushal K and Matsuda, Koichi and Murakami, Yoshinori and Price, Alkes L and Kawakami, Eiryo and Terao, Chikashi and Raychaudhuri, Soumya} } @article {40, title = {Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations.}, journal = {Nat Genet}, volume = {50}, year = {2018}, month = {2018 Nov}, pages = {1600-1607}, abstract = {

Common variant heritability has been widely reported to be concentrated in variants within cell-type-specific non-coding functional annotations, but little is known about low-frequency variant functional architectures. We partitioned the heritability of both low-frequency (0.5\%<= minor allele frequency <5\%) and common (minor allele frequency >=5\%) variants in 40 UK Biobank traits across a broad set of functional annotations. We determined that non-synonymous coding variants explain 17 {\textpm} 1\% of low-frequency variant heritability ([Formula: see text]) versus 2.1 {\textpm} 0.2\% of common variant heritability ([Formula: see text]). Cell-type-specific non-coding annotations that were significantly enriched for [Formula: see text] of corresponding traits were similarly enriched for [Formula: see text] for most traits, but more enriched for brain-related annotations and traits. For example, H3K4me3 marks in brain dorsolateral prefrontal cortex explain 57 {\textpm} 12\% of [Formula: see text] versus 12 {\textpm} 2\% of [Formula: see text] for neuroticism. Forward simulations confirmed that low-frequency variant enrichment depends on the mean selection coefficient of causal variants in the annotation, and can be used to predict effect size variance of causal rare variants (minor allele frequency <0.5\%).

}, keywords = {Alleles, Biological Specimen Banks, Gene Frequency, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Molecular Sequence Annotation, Open Reading Frames, Polymorphism, Single Nucleotide, Selection, Genetic, United Kingdom, White People}, issn = {1546-1718}, doi = {10.1038/s41588-018-0231-8}, author = {Gazal, Steven and Loh, Po-Ru and Finucane, Hilary K and Ganna, Andrea and Schoech, Armin and Sunyaev, Shamil and Price, Alkes L} } @article {38, title = {Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 Oct}, pages = {1421-1427}, abstract = {

Recent work has hinted at the linkage disequilibrium (LD)-dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) have larger per-SNP heritability. Here we analyzed summary statistics from 56 complex traits (average N = 101,401) by extending stratified LD score regression to continuous annotations. We determined that SNPs with low LLD have significantly larger per-SNP heritability and that roughly half of this effect can be explained by functional annotations negatively correlated with LLD, such as DNase I hypersensitivity sites (DHSs). The remaining signal is largely driven by our finding that more recent common variants tend to have lower LLD and to explain more heritability (P = 2.38 {\texttimes} 10); the youngest 20\% of common SNPs explain 3.9 times more heritability than the oldest 20\%, consistent with the action of negative selection. We also inferred jointly significant effects of other LD-related annotations and confirmed via forward simulations that they jointly predict deleterious effects.

}, keywords = {Alleles, Chi-Square Distribution, Datasets as Topic, Genetic Fitness, Genetic Variation, Humans, Linkage Disequilibrium, Models, Genetic, Molecular Sequence Annotation, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Selection, Genetic}, issn = {1546-1718}, doi = {10.1038/ng.3954}, author = {Gazal, Steven and Finucane, Hilary K and Furlotte, Nicholas A and Loh, Po-Ru and Palamara, Pier Francesco and Liu, Xuanyao and Schoech, Armin and Bulik-Sullivan, Brendan and Neale, Benjamin M and Gusev, Alexander and Price, Alkes L} }