@article {141, title = {Association between Smoking History and Tumor Mutation Burden in Advanced Non-Small Cell Lung Cancer.}, journal = {Cancer Res}, volume = {81}, year = {2021}, month = {2021 May 01}, pages = {2566-2573}, abstract = {

Lung carcinogenesis is a complex and stepwise process involving accumulation of genetic mutations in signaling and oncogenic pathways via interactions with environmental factors and host susceptibility. Tobacco exposure is the leading cause of lung cancer, but its relationship to clinically relevant mutations and the composite tumor mutation burden (TMB) has not been fully elucidated. In this study, we investigated the dose-response relationship in a retrospective observational study of 931 patients treated for advanced-stage non-small cell lung cancer (NSCLC) between April 2013 and February 2020 at the Dana Farber Cancer Institute and Brigham and Women{\textquoteright}s Hospital. Doubling smoking pack-years was associated with increased and less frequent and mutations, whereas doubling smoking-free months was associated with more frequent . In advanced lung adenocarcinoma, doubling smoking pack-years was associated with an increase in TMB, whereas doubling smoking-free months was associated with a decrease in TMB, after controlling for age, gender, and stage. There is a significant dose-response association of smoking history with genetic alterations in cancer-related pathways and TMB in advanced lung adenocarcinoma. SIGNIFICANCE: This study clarifies the relationship between smoking history and clinically relevant mutations in non-small cell lung cancer, revealing the potential of smoking history as a surrogate for tumor mutation burden.

}, issn = {1538-7445}, doi = {10.1158/0008-5472.CAN-20-3991}, author = {Wang, Xinan and Ricciuti, Biagio and Nguyen, Tom and Li, Xihao and Rabin, Michael S and Awad, Mark M and Lin, Xihong and Johnson, Bruce E and Christiani, David C} } @article {142, title = {Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics.}, journal = {Nat Genet}, volume = {53}, year = {2021}, month = {2021 03}, pages = {313-321}, abstract = {

Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.

}, keywords = {Bardet-Biedl Syndrome, Calcium Channels, Cell Line, Cerebellar Ataxia, DNA Methylation, Gene Expression, Genetic Variation, Humans, Induced Pluripotent Stem Cells, Polymorphism, Single Nucleotide, Proteins, Quantitative Trait Loci, Rare Diseases, Regulatory Sequences, Nucleic Acid, Sequence Analysis, RNA, Whole Genome Sequencing}, issn = {1546-1718}, doi = {10.1038/s41588-021-00800-7}, author = {Bonder, Marc Jan and Smail, Craig and Gloudemans, Michael J and Fr{\'e}sard, Laure and Jakubosky, David and D{\textquoteright}Antonio, Matteo and Li, Xin and Ferraro, Nicole M and Carcamo-Orive, Ivan and Mirauta, Bogdan and Seaton, Daniel D and Cai, Na and Vakili, Dara and Horta, Danilo and Zhao, Chunli and Zastrow, Diane B and Bonner, Devon E and Wheeler, Matthew T and Kilpinen, Helena and Knowles, Joshua W and Smith, Erin N and Frazer, Kelly A and Montgomery, Stephen B and Stegle, Oliver} } @article {136, title = {Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians.}, journal = {Genet Epidemiol}, year = {2021}, month = {2021 Mar 19}, abstract = {

Previous genome-wide association studies (GWASs) have been largely focused on European (EUR) populations. However, polygenic risk scores (PRSs) derived from EUR have been shown to perform worse in non-EURs compared with EURs. In this study, we aim to improve PRS prediction in East Asians (EASs). We introduce a rescaled meta-analysis framework to combine both EUR (N = 122,175) and EAS (N = 30,801) GWAS summary statistics. To improve PRS prediction in EASs, we use a scaling factor to up-weight the EAS data, such that the resulting effect size estimates are more relevant to EASs. We then derive PRSs for EAS from the rescaled meta-analysis results of EAS and EUR data. Evaluated in an independent EAS validation data set, this approach increases the prediction liability-adjusted Nagelkerke{\textquoteright}s pseudo R by 40\%, 41\%, and 5\%, respectively, compared with PRSs derived from an EAS GWAS only, EUR GWAS only, and conventional fixed-effects meta-analysis of EAS and EUR data. The PRS derived from the rescaled meta-analysis approach achieved an area under the receiver operating characteristic curve (AUC)~of 0.6059, higher than AUC = 0.5782, 0.5809, 0.6008 for EAS, EUR, and conventional meta-analysis of EAS and EUR. We further compare PRSs constructed by single-nucleotide polymorphisms that have different linkage disequilibrium (LD) scores and minor allele frequencies (MAFs) between EUR and EAS, and observe that lower LD scores or MAF in EAS correspond to poorer PRS performance (AUC = 0.5677,~0.5530, respectively) than higher LD scores or MAF (AUC = 0.589, 0.5993, respectively). We finally build a PRS stratified by LD score differences in EUR and EAS using rescaled meta-analysis, and obtain an AUC of 0.6096, with improvement over other strategies investigated.

}, issn = {1098-2272}, doi = {10.1002/gepi.22382}, author = {Ji, Ying and Long, Jirong and Kweon, Sun-Seog and Kang, Daehee and Kubo, Michiaki and Park, Boyoung and Shu, Xiao-Ou and Zheng, Wei and Tao, Ran and Li, Bingshan} } @article {129, title = {Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer.}, journal = {Genet Epidemiol}, volume = {45}, year = {2021}, month = {2021 Feb}, pages = {99-114}, abstract = {

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

}, issn = {1098-2272}, doi = {10.1002/gepi.22358}, author = {Sun, Ryan and Xu, Miao and Li, Xihao and Gaynor, Sheila and Zhou, Hufeng and Li, Zilin and Boss{\'e}, Yohan and Lam, Stephen and Tsao, Ming-Sound and Tardon, Adonina and Chen, Chu and Doherty, Jennifer and Goodman, Gary and Bojesen, Stig E and Landi, Maria T and Johansson, Mattias and Field, John K and Bickeb{\"o}ller, Heike and Wichmann, H-Erich and Risch, Angela and Rennert, Gadi and Arnold, Suzanne and Wu, Xifeng and Melander, Olle and Brunnstr{\"o}m, Hans and Le Marchand, Loic and Liu, Geoffrey and Andrew, Angeline and Duell, Eric and Kiemeney, Lambertus A and Shen, Hongbing and Haugen, Aage and Johansson, Mikael and Grankvist, Kjell and Caporaso, Neil and Woll, Penella and Dawn Teare, M and Scelo, Ghislaine and Hong, Yun-Chul and Yuan, Jian-Min and Lazarus, Philip and Schabath, Matthew B and Aldrich, Melinda C and Albanes, Demetrios and Mak, Raymond and Barbie, David and Brennan, Paul and Hung, Rayjean J and Amos, Christopher I and Christiani, David C and Lin, Xihong} } @article {127, title = {Rapid response to the alpha-1 adrenergic agent phenylephrine in the perioperative period is impacted by genomics and ancestry.}, journal = {Pharmacogenomics J}, volume = {21}, year = {2021}, month = {2021 Apr}, pages = {174-189}, abstract = {

The emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes occurring during inpatient clinical care. Here we study the genetic underpinnings of the rapid response to phenylephrine, an α1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery. We quantified this response by extracting blood pressure (BP) measurements 5 min before and after the administration of phenylephrine. Based on this derived phenotype, we show that systematic differences exist between self-reported ancestry groups: European-Americans (EA; n = 1387) have a significantly higher systolic response to phenylephrine than African-Americans (AA; n = 1217) and Hispanic/Latinos (HA; n = 1713) (31.3\% increase, p value < 6e-08 and 22.9\% increase, p value < 5e-05 respectively), after adjusting for genetic ancestry, demographics, and relevant clinical covariates. We performed a genome-wide association study to investigate genetic factors underlying individual differences in this derived phenotype. We discovered genome-wide significant association signals in loci and genes previously associated with BP measured in ambulatory settings, and a general enrichment of association in these genes. Finally, we discovered two low frequency variants, present at ~1\% in EAs and AAs, respectively, where patients carrying one copy of these variants show no phenylephrine response. This work demonstrates our ability to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from dense clinical and physiological measures captured for managing patients during surgery. We identify genetic variants underlying non response to phenylephrine, with implications for preemptive pharmacogenomic screening to improve safety during surgery.

}, issn = {1473-1150}, doi = {10.1038/s41397-020-00194-5}, author = {Wenric, Stephane and Jeff, Janina M and Joseph, Thomas and Yee, Muh-Ching and Belbin, Gillian M and Owusu Obeng, Aniwaa and Ellis, Stephen B and Bottinger, Erwin P and Gottesman, Omri and Levin, Matthew A and Kenny, Eimear E} } @article {134, title = {Regulatory genomic circuitry of human disease loci by integrative epigenomics.}, journal = {Nature}, volume = {590}, year = {2021}, month = {2021 02}, pages = {300-307}, abstract = {

Annotating the molecular basis of human disease remains an unsolved challenge, as 93\% of disease loci are non-coding and gene-regulatory annotations are highly incomplete. Here we present EpiMap, a compendium comprising 10,000~epigenomic maps across 800~samples, which we used to define chromatin states, high-resolution enhancers, enhancer modules, upstream regulators and downstream target genes. We used this resource to annotate 30,000~genetic loci that were associated with 540~traits, predicting trait-relevant tissues, putative causal nucleotide variants in enriched tissue enhancers and candidate tissue-specific target genes for each. We partitioned multifactorial traits into tissue-specific contributing factors with distinct functional enrichments and disease comorbidity patterns, and revealed both single-factor monotropic and multifactor pleiotropic loci. Top-scoring loci frequently had multiple predicted driver variants, converging through multiple enhancers with a common target gene, multiple genes in common tissues, or multiple genes and multiple tissues, indicating extensive pleiotropy. Our results demonstrate the importance of dense, rich, high-resolution epigenomic annotations for the investigation of complex traits.

}, keywords = {Chromatin, Disease, Enhancer Elements, Genetic, Epigenesis, Genetic, Epigenomics, Female, Gene Regulatory Networks, Genetic Loci, Genome-Wide Association Study, Humans, Male, Multifactorial Inheritance, Organ Specificity, Reproducibility of Results}, issn = {1476-4687}, doi = {10.1038/s41586-020-03145-z}, author = {Boix, Carles A and James, Benjamin T and Park, Yongjin P and Meuleman, Wouter and Kellis, Manolis} } @article {137, title = {Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression.}, journal = {Bioinformatics}, year = {2021}, month = {2021 Feb 09}, abstract = {

MOTIVATION: The prediction performance of Cox proportional hazard model suffers when there are only few uncensored events in the training data.

RESULTS: We propose a Sparse-Group regularized Cox regression method to improve the prediction performance of large-scale and high-dimensional survival data with few observed events. Our approach is applicable when there is one or more other survival responses that 1. has a large number of observed events; 2. share a common set of associated predictors with the rare event response. This scenario is common in the UK Biobank (Sudlow et al., 2015) dataset where records for a large number of common and less prevalent diseases of the same set of individuals are available. By analyzing these responses together, we hope to achieve higher prediction performance than when they are analyzed individually. To make this approach practical for large-scale data, we developed an accelerated proximal gradient optimization algorithm as well as a screening procedure inspired by Qian et al. (2020).

AVAILABILITY: https://github.com/rivas-lab/multisnpnet-Cox.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btab095}, author = {Li, Ruilin and Tanigawa, Yosuke and Justesen, Johanne M and Taylor, Jonathan and Hastie, Trevor and Tibshirani, Robert and Rivas, Manuel A} } @article {118, title = {Synaptic processes and immune-related pathways implicated in Tourette syndrome.}, journal = {Transl Psychiatry}, volume = {11}, year = {2021}, month = {2021 01 18}, pages = {56}, abstract = {

Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.

}, issn = {2158-3188}, doi = {10.1038/s41398-020-01082-z}, author = {Tsetsos, Fotis and Yu, Dongmei and Sul, Jae Hoon and Huang, Alden Y and Illmann, Cornelia and Osiecki, Lisa and Darrow, Sabrina M and Hirschtritt, Matthew E and Greenberg, Erica and Muller-Vahl, Kirsten R and Stuhrmann, Manfred and Dion, Yves and Rouleau, Guy A and Aschauer, Harald and Stamenkovic, Mara and Schl{\"o}gelhofer, Monika and Sandor, Paul and Barr, Cathy L and Grados, Marco A and Singer, Harvey S and N{\"o}then, Markus M and Hebebrand, Johannes and Hinney, Anke and King, Robert A and Fernandez, Thomas V and Barta, Csaba and Tarnok, Zsanett and Nagy, Peter and Depienne, Christel and Worbe, Yulia and Hartmann, Andreas and Budman, Cathy L and Rizzo, Renata and Lyon, Gholson J and McMahon, William M and Batterson, James R and Cath, Danielle C and Malaty, Irene A and Okun, Michael S and Berlin, Cheston and Woods, Douglas W and Lee, Paul C and Jankovic, Joseph and Robertson, Mary M and Gilbert, Donald L and Brown, Lawrence W and Coffey, Barbara J and Dietrich, Andrea and Hoekstra, Pieter J and Kuperman, Samuel and Zinner, Samuel H and Wagner, Michael and Knowles, James A and Jeremy Willsey, A and Tischfield, Jay A and Heiman, Gary A and Cox, Nancy J and Freimer, Nelson B and Neale, Benjamin M and Davis, Lea K and Coppola, Giovanni and Mathews, Carol A and Scharf, Jeremiah M and Paschou, Peristera and Barr, Cathy L and Batterson, James R and Berlin, Cheston and Budman, Cathy L and Cath, Danielle C and Coppola, Giovanni and Cox, Nancy J and Darrow, Sabrina and Davis, Lea K and Dion, Yves and Freimer, Nelson B and Grados, Marco A and Greenberg, Erica and Hirschtritt, Matthew E and Huang, Alden Y and Illmann, Cornelia and King, Robert A and Kurlan, Roger and Leckman, James F and Lyon, Gholson J and Malaty, Irene A and Mathews, Carol A and McMahon, William M and Neale, Benjamin M and Okun, Michael S and Osiecki, Lisa and Robertson, Mary M and Rouleau, Guy A and Sandor, Paul and Scharf, Jeremiah M and Singer, Harvey S and Smit, Jan H and Sul, Jae Hoon and Yu, Dongmei and Aschauer, Harald Aschauer Harald and Barta, Csaba and Budman, Cathy L and Cath, Danielle C and Depienne, Christel and Hartmann, Andreas and Hebebrand, Johannes and Konstantinidis, Anastasios and Mathews, Carol A and M{\"u}ller-Vahl, Kirsten and Nagy, Peter and N{\"o}then, Markus M and Paschou, Peristera and Rizzo, Renata and Rouleau, Guy A and Sandor, Paul and Scharf, Jeremiah M and Schl{\"o}gelhofer, Monika and Stamenkovic, Mara and Stuhrmann, Manfred and Tsetsos, Fotis and Tarnok, Zsanett and Wolanczyk, Tomasz and Worbe, Yulia and Brown, Lawrence and Cheon, Keun-Ah and Coffey, Barbara J and Dietrich, Andrea and Fernandez, Thomas V and Garcia-Delgar, Blanca and Gilbert, Donald and Grice, Dorothy E and Hagstr{\o}m, Julie and Hedderly, Tammy and Heiman, Gary A and Heyman, Isobel and Hoekstra, Pieter J and Huyser, Chaim and Kim, Young Key and Kim, Young-Shin and King, Robert A and Koh, Yun-Joo and Kook, Sodahm and Kuperman, Samuel and Leventhal, Bennett L and Madruga-Garrido, Marcos and Mir, Pablo and Morer, Astrid and M{\"u}nchau, Alexander and Plessen, Kerstin J and Roessner, Veit and Shin, Eun-Young and Song, Dong-Ho and Song, Jungeun and Tischfield, Jay A and Willsey, A Jeremy and Zinner, Samuel and Aschauer, Harald and Barr, Cathy L and Barta, Csaba and Batterson, James R and Berlin, Cheston and Brown, Lawrence and Budman, Cathy L and Cath, Danielle C and Coffey, Barbara J and Coppola, Giovanni and Cox, Nancy J and Darrow, Sabrina and Davis, Lea K and Depienne, Christel and Dietrich, Andrea and Dion, Yves and Fernandez, Thomas and Freimer, Nelson B and Gilbert, Donald and Grados, Marco A and Greenberg, Erica and Hartmann, Andreas and Hebebrand, Johannes and Heiman, Gary and Hirschtritt, Matthew E and Hoekstra, Pieter and Huang, Alden Y and Illmann, Cornelia and Jankovic, Joseph and King, Robert A and Kuperman, Samuel and Lee, Paul C and Lyon, Gholson J and Malaty, Irene A and Mathews, Carol A and McMahon, William M and M{\"u}ller-Vahl, Kirsten and Nagy, Peter and Neale, Benjamin M and N{\"o}then, Markus M and Okun, Michael S and Osiecki, Lisa and Paschou, Peristera and Rizzo, Renata and Robertson, Mary M and Rouleau, Guy A and Sandor, Paul and Scharf, Jeremiah M and Schl{\"o}gelhofer, Monika and Singer, Harvey S and Stamenkovic, Mara and Stuhrmann, Manfred and Sul, Jae Hoon and Tarnok, Zsanett and Tischfield, Jay and Tsetsos, Fotis and Willsey, A Jeremy and Woods, Douglas and Worbe, Yulia and Yu, Dongmei and Zinner, Samuel} } @article {87, title = {Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts.}, journal = {Am J Hum Genet}, volume = {106}, year = {2020}, month = {2020 01 02}, pages = {112-120}, abstract = {

Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (\~{}38{\texttimes} coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (\~{}10\% and \~{}1\% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in~vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23~mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97~mg/L and major allele homozygotes with mean CRP of 4.11~mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.

}, keywords = {African Continental Ancestry Group, Asian Continental Ancestry Group, C-Reactive Protein, Cohort Studies, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2019.12.002}, author = {Raffield, Laura M and Iyengar, Apoorva K and Wang, Biqi and Gaynor, Sheila M and Spracklen, Cassandra N and Zhong, Xue and Kowalski, Madeline H and Salimi, Shabnam and Polfus, Linda M and Benjamin, Emelia J and Bis, Joshua C and Bowler, Russell and Cade, Brian E and Choi, Won Jung and Comellas, Alejandro P and Correa, Adolfo and Cruz, Pedro and Doddapaneni, Harsha and Durda, Peter and Gogarten, Stephanie M and Jain, Deepti and Kim, Ryan W and Kral, Brian G and Lange, Leslie A and Larson, Martin G and Laurie, Cecelia and Lee, Jiwon and Lee, Seonwook and Lewis, Joshua P and Metcalf, Ginger A and Mitchell, Braxton D and Momin, Zeineen and Muzny, Donna M and Pankratz, Nathan and Park, Cheol Joo and Rich, Stephen S and Rotter, Jerome I and Ryan, Kathleen and Seo, Daekwan and Tracy, Russell P and Viaud-Martinez, Karine A and Yanek, Lisa R and Zhao, Lue Ping and Lin, Xihong and Li, Bingshan and Li, Yun and Dupuis, Jos{\'e}e and Reiner, Alexander P and Mohlke, Karen L and Auer, Paul L} } @article {82, title = {Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis.}, journal = {Genet Med}, volume = {22}, year = {2020}, month = {2020 07}, pages = {1191-1200}, abstract = {

PURPOSE: The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease.

METHODS: We estimated genetically predicted expression (GReX) of cystic fibrosis transmembrane conductance regulator (CFTR) and tested for association with clinical diagnoses in the Vanderbilt University biobank (N = 9142 persons of European descent with 71 cases of CF). The top associated EHR phenotypes were assessed in combination as a phenotype risk score (PheRS) for discriminating CF case status in an additional 2.8 million patients from Vanderbilt University Medical Center (VUMC) and 125,305 adult patients including 25,314 CF cases from MarketScan, an independent external cohort.

RESULTS: GReX of CFTR was associated with EHR phenotypes consistent with CF. PheRS constructed using the EHR phenotypes and weights discovered by the genetic associations improved discriminative power for CF over the initially proposed PheRS in both VUMC and MarketScan.

CONCLUSION: Our study demonstrates the power of EHRs for clinical description of CF and the benefits of using a genetics-informed weighing scheme in construction of a phenotype risk score. This research may find broad applications for phenomic studies of Mendelian disease genes.

}, keywords = {Adult, Cystic Fibrosis, Cystic Fibrosis Transmembrane Conductance Regulator, Electronic Health Records, Humans, Mutation, Phenotype}, issn = {1530-0366}, doi = {10.1038/s41436-020-0786-5}, author = {Zhong, Xue and Yin, Zhijun and Jia, Gengjie and Zhou, Dan and Wei, Qiang and Faucon, Annika and Evans, Patrick and Gamazon, Eric R and Li, Bingshan and Tao, Ran and Rzhetsky, Andrey and Bastarache, Lisa and Cox, Nancy J} } @article {120, title = {Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.}, journal = {Nat Genet}, volume = {52}, year = {2020}, month = {2020 11}, pages = {1145-1150}, abstract = {

The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remain unclear. We performed a systematic secondary-variant burden analysis of two independent cohorts of patients with Bardet-Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants in patients with BBS compared with either population controls or a cohort of individuals with a non-BBS diagnosis and recessive variants in the same gene set. Strikingly, we found a significant over-representation of secondary alleles in chaperonin-encoding genes-a finding corroborated by the observation of epistatic interactions involving this complex in vivo. These data indicate a complex genetic architecture for BBS that informs the biological properties of disease modules and presents a model for secondary-variant burden analysis in recessive disorders.

}, keywords = {Alleles, Bardet-Biedl Syndrome, Cohort Studies, Exome, Genetic Variation, Humans}, issn = {1546-1718}, doi = {10.1038/s41588-020-0707-1}, author = {Kousi, Maria and S{\"o}ylemez, Onuralp and Ozanturk, Ayseg{\"u}l and Mourtzi, Niki and Akle, Sebastian and Jungreis, Irwin and Muller, Jean and Cassa, Christopher A and Brand, Harrison and Mokry, Jill Anne and Wolf, Maxim Y and Sadeghpour, Azita and McFadden, Kelsey and Lewis, Richard A and Talkowski, Michael E and Dollfus, H{\'e}l{\`e}ne and Kellis, Manolis and Davis, Erica E and Sunyaev, Shamil R and Katsanis, Nicholas} } @article {119, title = {Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank.}, journal = {Biostatistics}, year = {2020}, month = {2020 Sep 29}, abstract = {

We develop a scalable and highly efficient algorithm to fit a Cox proportional hazard model by maximizing the $L^1$-regularized (Lasso) partial likelihood function, based on the Batch Screening Iterative Lasso (BASIL) method developed in Qian and others (2019). Our algorithm is particularly suitable for large-scale and high-dimensional data that do not fit in the memory. The output of our algorithm is the full Lasso path, the parameter estimates at all predefined regularization parameters, as well as their validation accuracy measured using the concordance index (C-index) or the validation deviance. To demonstrate the effectiveness of our algorithm, we analyze a large genotype-survival time dataset across 306 disease outcomes from the UK Biobank (Sudlow and others, 2015). We provide a publicly available implementation of the proposed approach for genetics data on top of the PLINK2 package and name it snpnet-Cox.

}, issn = {1468-4357}, doi = {10.1093/biostatistics/kxaa038}, author = {Li, Ruilin and Chang, Christopher and Justesen, Johanne M and Tanigawa, Yosuke and Qiang, Junyang and Hastie, Trevor and Rivas, Manuel A and Tibshirani, Robert} } @article {107, title = {Genome-Wide Analysis Reveals Mucociliary Remodeling of the Nasal Airway Epithelium Induced by Urban PM.}, journal = {Am J Respir Cell Mol Biol}, volume = {63}, year = {2020}, month = {2020 08}, pages = {172-184}, abstract = {

Air pollution particulate matter <2.5 μm (PM) exposure is associated with poor respiratory outcomes. Mechanisms underlying PM-induced lung pathobiology are poorly understood but likely involve cellular and molecular changes to the airway epithelium. We extracted and chemically characterized the organic and water-soluble components of air pollution PM samples, then determined the whole transcriptome response of human nasal mucociliary airway epithelial cultures to a dose series of PM extracts. We found that PM organic extract (OE), but not water-soluble extract, elicited a potent, dose-dependent transcriptomic response from the mucociliary epithelium. Exposure to a moderate OE dose modified the expression of 424 genes, including activation of aryl hydrocarbon receptor signaling and an IL-1 inflammatory program. We generated an OE-response gene network defined by eight functional enrichment groups, which exhibited high connectivity through , , and . This OE exposure also robustly activated a mucus secretory expression program (>100 genes), which included transcriptional drivers of mucus metaplasia ( and ). Exposure to a higher OE dose modified the expression of 1,240 genes and further exacerbated expression responses observed at the moderate dose, including the mucus secretory program. Moreover, the higher OE dose significantly increased the / gel-forming mucin expression ratio and strongly downregulated ciliated cell expression programs, including key ciliating cell transcription factors (e.g., and ). Chronic OE stimulation induced mucus metaplasia-like remodeling characterized by increases in MUC5AC secretory cells and MUC5AC mucus secretions. This epithelial remodeling may underlie poor respiratory outcomes associated with high PM exposure.

}, issn = {1535-4989}, doi = {10.1165/rcmb.2019-0454OC}, author = {Montgomery, Michael T and Sajuthi, Satria P and Cho, Seung-Hyun and Everman, Jamie L and Rios, Cydney L and Goldfarbmuren, Katherine C and Jackson, Nathan D and Saef, Benjamin and Cromie, Meghan and Eng, Celeste and Medina, Vivian and Elhawary, Jennifer R and Oh, Sam S and Rodriguez-Santana, Jose and Vladar, Eszter K and Burchard, Esteban G and Seibold, Max A} } @article {105, title = {Lung Function in African American Children with Asthma Is Associated with Novel Regulatory Variants of the KIT Ligand and Gene-By-Air-Pollution Interaction.}, journal = {Genetics}, volume = {215}, year = {2020}, month = {2020 07}, pages = {869-886}, abstract = {

Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV on chromosome 12 in 867 African American children with asthma ( = 1.26 {\texttimes} 10, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with (KIT ligand, also known as ), and their minor alleles were associated with increased expression of the gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure ( = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV, possibly mediated through , in African American children with asthma. This is the first study that has identified a genetic association between lung function and , which has established a role in orchestrating allergic inflammation in asthma.

}, issn = {1943-2631}, doi = {10.1534/genetics.120.303231}, author = {Mak, Angel C Y and Sajuthi, Satria and Joo, Jaehyun and Xiao, Shujie and Sleiman, Patrick M and White, Marquitta J and Lee, Eunice Y and Saef, Benjamin and Hu, Donglei and Gui, Hongsheng and Keys, Kevin L and Lurmann, Fred and Jain, Deepti and Abecasis, Goncalo and Kang, Hyun Min and Nickerson, Deborah A and Germer, Soren and Zody, Michael C and Winterkorn, Lara and Reeves, Catherine and Huntsman, Scott and Eng, Celeste and Salazar, Sandra and Oh, Sam S and Gilliland, Frank D and Chen, Zhanghua and Kumar, Rajesh and Mart{\'\i}nez, Fernando D and Wu, Ann Chen and Ziv, Elad and Hakonarson, Hakon and Himes, Blanca E and Williams, L Keoki and Seibold, Max A and Burchard, Esteban G} } @article {89, title = {A positively selected FBN1 missense variant reduces height in Peruvian individuals.}, journal = {Nature}, volume = {582}, year = {2020}, month = {2020 06}, pages = {234-239}, abstract = {

On average, Peruvian individuals are among the shortest in the world. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7\%) reduces height by 2.2~cm (4.4~cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin~1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.

}, keywords = {Body Height, Female, Fibrillin-1, Gene Frequency, Genome-Wide Association Study, Heredity, Humans, Indians, South American, Male, Microfibrils, Mutation, Missense, Peru, Selection, Genetic}, issn = {1476-4687}, doi = {10.1038/s41586-020-2302-0}, author = {Asgari, Samira and Luo, Yang and Akbari, Ali and Belbin, Gillian M and Li, Xinyi and Harris, Daniel N and Selig, Martin and Bartell, Eric and Calderon, Roger and Slowikowski, Kamil and Contreras, Carmen and Yataco, Rosa and Galea, Jerome T and Jimenez, Judith and Coit, Julia M and Farro{\~n}ay, Chandel and Nazarian, Rosalynn M and O{\textquoteright}Connor, Timothy D and Dietz, Harry C and Hirschhorn, Joel N and Guio, Heinner and Lecca, Leonid and Kenny, Eimear E and Freeman, Esther E and Murray, Megan B and Raychaudhuri, Soumya} } @article {97, title = {PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.}, journal = {Genome Biol}, volume = {21}, year = {2020}, month = {2020 08 26}, pages = {217}, abstract = {

Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN{\textquoteright}s performance on synthetic data and two real data sets for lipid traits and Alzheimer{\textquoteright}s disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.

}, issn = {1474-760X}, doi = {10.1186/s13059-020-02121-0}, author = {Tang, Zheng-Zheng and Sliwoski, Gregory R and Chen, Guanhua and Jin, Bowen and Bush, William S and Li, Bingshan and Capra, John A} } @article {109, title = {Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 10 12}, pages = {5139}, abstract = {

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

}, keywords = {Angiotensin-Converting Enzyme 2, Betacoronavirus, Child, Coronavirus Infections, COVID-19, Epithelial Cells, Gene Expression Profiling, Gene Expression Regulation, Genetic Variation, Host-Pathogen Interactions, Humans, Inflammation, Interferons, Interleukin-13, Middle Aged, Nasal Mucosa, Pandemics, Peptidyl-Dipeptidase A, Pneumonia, Viral, SARS-CoV-2, Serine Endopeptidases, Virus Internalization}, issn = {2041-1723}, doi = {10.1038/s41467-020-18781-2}, author = {Sajuthi, Satria P and DeFord, Peter and Li, Yingchun and Jackson, Nathan D and Montgomery, Michael T and Everman, Jamie L and Rios, Cydney L and Pruesse, Elmar and Nolin, James D and Plender, Elizabeth G and Wechsler, Michael E and Mak, Angel C Y and Eng, Celeste and Salazar, Sandra and Medina, Vivian and Wohlford, Eric M and Huntsman, Scott and Nickerson, Deborah A and Germer, Soren and Zody, Michael C and Abecasis, Goncalo and Kang, Hyun Min and Rice, Kenneth M and Kumar, Rajesh and Oh, Sam and Rodriguez-Santana, Jose and Burchard, Esteban G and Seibold, Max A} } @article {115, title = {Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium.}, journal = {bioRxiv}, year = {2020}, month = {2020 Apr 10}, abstract = {

Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both and , that vary in frequency across world populations. Importantly, we find is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

}, doi = {10.1101/2020.04.09.034454}, author = {Sajuthi, Satria P and DeFord, Peter and Jackson, Nathan D and Montgomery, Michael T and Everman, Jamie L and Rios, Cydney L and Pruesse, Elmar and Nolin, James D and Plender, Elizabeth G and Wechsler, Michael E and Mak, Angel Cy and Eng, Celeste and Salazar, Sandra and Medina, Vivian and Wohlford, Eric M and Huntsman, Scott and Nickerson, Deborah A and Germer, Soren and Zody, Michael C and Abecasis, Goncalo and Kang, Hyun Min and Rice, Kenneth M and Kumar, Rajesh and Oh, Sam and Rodriguez-Santana, Jose and Burchard, Esteban G and Seibold, Max A} } @article {111, title = {A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis.}, journal = {Nat Genet}, volume = {52}, year = {2020}, month = {2020 11}, pages = {1239-1246}, abstract = {

Here, we present a joint-tissue imputation (JTI) approach and a Mendelian randomization framework for causal inference, MR-JTI. JTI borrows information across transcriptomes of different tissues, leveraging shared genetic regulation, to improve prediction performance in a tissue-dependent manner. Notably, JTI includes the single-tissue imputation method PrediXcan as a special case and outperforms other single-tissue approaches (the Bayesian sparse linear mixed model and Dirichlet process regression). MR-JTI models variant-level heterogeneity (primarily due to horizontal pleiotropy, addressing a major challenge of transcriptome-wide association study interpretation) and performs causal inference with type I error control. We make explicit the connection between the genetic architecture of gene expression and of complex traits and the suitability of Mendelian randomization as a causal inference strategy for transcriptome-wide association studies. We provide a resource of imputation models generated from GTEx and PsychENCODE panels. Analysis of biobanks and meta-analysis data, and extensive simulations show substantially improved statistical power, replication and causal mapping rate for JTI relative to existing approaches.

}, keywords = {Animals, Gene Expression Profiling, Genetic Association Studies, Humans, Lipoproteins, LDL, Mendelian Randomization Analysis, Mice, Models, Genetic, Multifactorial Inheritance, Predictive Value of Tests}, issn = {1546-1718}, doi = {10.1038/s41588-020-0706-2}, author = {Zhou, Dan and Jiang, Yi and Zhong, Xue and Cox, Nancy J and Liu, Chunyu and Gamazon, Eric R} } @article {64, title = {A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data.}, journal = {Nat Neurosci}, volume = {22}, year = {2019}, month = {2019 05}, pages = {691-699}, abstract = {

Genome-wide association studies (GWAS) have identified more than 100 schizophrenia (SCZ)-associated loci, but using these findings to illuminate disease biology remains a challenge. Here we present integrative risk gene selector (iRIGS), a Bayesian framework that integrates multi-omics data and gene networks to infer risk genes in GWAS loci. By applying iRIGS to SCZ GWAS data, we predicted a set of high-confidence risk genes, most of which are not the nearest genes to the GWAS index variants. High-confidence risk genes account for a significantly enriched heritability, as estimated by stratified linkage disequilibrium score regression. Moreover, high-confidence risk genes are predominantly expressed in brain tissues, especially prenatally, and are enriched for targets of approved drugs, suggesting opportunities to reposition existing drugs for SCZ. Thus, iRIGS can leverage accumulating functional genomics and GWAS data to advance our understanding of SCZ etiology and potential therapeutics.

}, keywords = {Animals, Bayes Theorem, Disease Models, Animal, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Mice, Risk Factors, Schizophrenia}, issn = {1546-1726}, doi = {10.1038/s41593-019-0382-7}, author = {Wang, Quan and Chen, Rui and Cheng, Feixiong and Wei, Qiang and Ji, Ying and Yang, Hai and Zhong, Xue and Tao, Ran and Wen, Zhexing and Sutcliffe, James S and Liu, Chunyu and Cook, Edwin H and Cox, Nancy J and Li, Bingshan} } @article {66, title = {Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 Sep 06}, pages = {4064}, abstract = {

Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we apply truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identify key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

}, issn = {2041-1723}, doi = {10.1038/s41467-019-11953-9}, author = {Tanigawa, Yosuke and Li, Jiehan and Justesen, Johanne M and Horn, Heiko and Aguirre, Matthew and DeBoever, Christopher and Chang, Chris and Narasimhan, Balasubramanian and Lage, Kasper and Hastie, Trevor and Park, Chong Y and Bejerano, Gill and Ingelsson, Erik and Rivas, Manuel A} } @article {60, title = {De novo pattern discovery enables robust assessment of functional consequences of non-coding variants.}, journal = {Bioinformatics}, volume = {35}, year = {2019}, month = {2019 May 01}, pages = {1453-1460}, abstract = {

MOTIVATION: Given the complexity of genome regions, prioritize the functional effects of non-coding variants remains a challenge. Although several frameworks have been proposed for the evaluation of the functionality of non-coding variants, most of them used {\textquoteright}black boxes{\textquoteright} methods that simplify the task as the pathogenicity/benign classification problem, which ignores the distinct regulatory mechanisms of variants and leads to less desirable performance. In this study, we developed DVAR, an unsupervised framework that leverage various biochemical and evolutionary evidence to distinguish the gene regulatory categories of variants and assess their comprehensive functional impact simultaneously.

RESULTS: DVAR performed de novo pattern discovery in high-dimensional data and identified five regulatory clusters of non-coding variants. Leveraging the new insights into the multiple functional patterns, it measures both the between-class and the within-class functional implication of the variants to achieve accurate prioritization. Compared to other two-class learning methods, it showed improved performance in identification of clinically significant variants, fine-mapped GWAS variants, eQTLs and expression-modulating variants. Moreover, it has superior performance on disease causal variants verified by genome-editing (like CRISPR-Cas9), which could provide a pre-selection strategy for genome-editing technologies across the whole genome. Finally, evaluated in BioVU and UK Biobank, two large-scale DNA biobanks linked to complete electronic health records, DVAR demonstrated its effectiveness in prioritizing non-coding variants associated with medical phenotypes.

AVAILABILITY AND IMPLEMENTATION: The C++ and Python source codes, the pre-computed DVAR-cluster labels and DVAR-scores across the whole genome are available at https://www.vumc.org/cgg/dvar.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, issn = {1367-4811}, doi = {10.1093/bioinformatics/bty826}, author = {Yang, Hai and Chen, Rui and Wang, Quan and Wei, Qiang and Ji, Ying and Zheng, Guangze and Zhong, Xue and Cox, Nancy J and Li, Bingshan} } @article {52, title = {Differential NOVA2-Mediated Splicing in Excitatory and Inhibitory Neurons Regulates Cortical Development and Cerebellar Function.}, journal = {Neuron}, volume = {101}, year = {2019}, month = {2019 Feb 20}, pages = {707-720.e5}, abstract = {

RNA-binding proteins (RBPs) regulate genetic diversity, but the degree to which they do so in individual cell types in~vivo is unknown. We developed NOVA2 cTag-crosslinking and immunoprecipitation (CLIP) to generate functional RBP-RNA maps from different neuronal populations in the mouse brain. Combining cell type datasets from Nova2-cTag and Nova2 conditional knockout mice revealed differential NOVA2 regulatory actions on alternative splicing (AS) on the same transcripts expressed in different neurons. This includes functional differences in transcripts expressed in cortical and cerebellar excitatory versus inhibitory neurons, where we find NOVA2 is required for, respectively, development of laminar structure, motor coordination, and synapse formation. We also find that NOVA2-regulated AS is coupled to NOVA2 regulation of intron retention in hundreds of transcripts, which can sequester the trans-acting splicing factor PTBP2. In summary, cTag-CLIP complements single-cell RNA sequencing (RNA-seq) studies by providing a means for understanding RNA regulation of functional cell diversity.

}, keywords = {Alternative Splicing, Animals, Antigens, Neoplasm, Cells, Cultured, Cerebellum, Cerebral Cortex, Excitatory Postsynaptic Potentials, Female, Inhibitory Postsynaptic Potentials, Male, Mice, Mice, Inbred C57BL, Nerve Tissue Proteins, Neuro-Oncological Ventral Antigen, Neurogenesis, Neurons, Polypyrimidine Tract-Binding Protein, RNA-Binding Proteins}, issn = {1097-4199}, doi = {10.1016/j.neuron.2018.12.019}, author = {Saito, Yuhki and Yuan, Yuan and Zucker-Scharff, Ilana and Fak, John J and Jereb, Sa{\v s}a and Tajima, Yoko and Licatalosi, Donny D and Darnell, Robert B} } @article {50, title = {Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies.}, journal = {Am J Hum Genet}, volume = {104}, year = {2019}, month = {2019 Feb 07}, pages = {260-274}, abstract = {

With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute{\textquoteright}s Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

}, keywords = {Chromosomes, Human, Pair 4, Cloud Computing, Female, Fibrinogen, Genetic Association Studies, Genetics, Population, Humans, Male, Models, Genetic, National Heart, Lung, and Blood Institute (U.S.), Precision Medicine, Research Design, Time Factors, United States, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2018.12.012}, author = {Chen, Han and Huffman, Jennifer E and Brody, Jennifer A and Wang, Chaolong and Lee, Seunggeun and Li, Zilin and Gogarten, Stephanie M and Sofer, Tamar and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Bowler, Russell P and Cade, Brian E and Cho, Michael H and Correa, Adolfo and Curran, Joanne E and de Vries, Paul S and Glahn, David C and Guo, Xiuqing and Johnson, Andrew D and Kardia, Sharon and Kooperberg, Charles and Lewis, Joshua P and Liu, Xiaoming and Mathias, Rasika A and Mitchell, Braxton D and O{\textquoteright}Connell, Jeffrey R and Peyser, Patricia A and Post, Wendy S and Reiner, Alex P and Rich, Stephen S and Rotter, Jerome I and Silverman, Edwin K and Smith, Jennifer A and Vasan, Ramachandran S and Wilson, James G and Yanek, Lisa R and Redline, Susan and Smith, Nicholas L and Boerwinkle, Eric and Borecki, Ingrid B and Cupples, L Adrienne and Laurie, Cathy C and Morrison, Alanna C and Rice, Kenneth M and Lin, Xihong} } @article {62, title = {Genome sequencing analysis identifies Epstein-Barr virus subtypes associated with high risk of nasopharyngeal carcinoma.}, journal = {Nat Genet}, volume = {51}, year = {2019}, month = {2019 Jul}, pages = {1131-1136}, abstract = {

Epstein-Barr virus (EBV) infection is ubiquitous worldwide and is associated with multiple cancers, including nasopharyngeal carcinoma (NPC). The importance of EBV viral genomic variation in NPC development and its striking epidemic in southern China has been poorly explored. Through large-scale genome sequencing of 270 EBV isolates and two-stage association study of EBV isolates from China, we identify two non-synonymous EBV variants within BALF2 that are strongly associated with the risk of NPC (odds ratio (OR) = 8.69, P = 9.69 {\texttimes} 10 for SNP 162476_C; OR = 6.14, P = 2.40 {\texttimes} 10 for SNP 163364_T). The cumulative effects of these variants contribute to 83\% of the overall risk of NPC in southern China. Phylogenetic analysis of the risk variants reveals a unique origin in Asia, followed by clonal expansion in NPC-endemic regions. Our results provide novel insights into the NPC endemic in southern China and also enable the identification of high-risk individuals for NPC prevention.

}, issn = {1546-1718}, doi = {10.1038/s41588-019-0436-5}, author = {Xu, Miao and Yao, Youyuan and Chen, Hui and Zhang, Shanshan and Cao, Su-Mei and Zhang, Zhe and Luo, Bing and Liu, Zhiwei and Li, Zilin and Xiang, Tong and He, Guiping and Feng, Qi-Sheng and Chen, Li-Zhen and Guo, Xiang and Jia, Wei-Hua and Chen, Ming-Yuan and Zhang, Xiao and Xie, Shang-Hang and Peng, Roujun and Chang, Ellen T and Pedergnana, Vincent and Feng, Lin and Bei, Jin-Xin and Xu, Rui-Hua and Zeng, Mu-Sheng and Ye, Weimin and Adami, Hans-Olov and Lin, Xihong and Zhai, Weiwei and Zeng, Yi-Xin and Liu, Jianjun} } @article {63, title = {Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts.}, journal = {Nat Med}, volume = {25}, year = {2019}, month = {2019 06}, pages = {911-919}, abstract = {

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene. The current molecular diagnostic rate is estimated at 50\%, with whole-exome sequencing (WES) among the most successful approaches. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases. This includes muscle biopsies from patients with undiagnosed rare muscle disorders, and cultured fibroblasts from patients with mitochondrial disorders. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5\% diagnostic rate, and an additional 16.7\% with improved candidate gene resolution.

}, keywords = {Acid Ceramidase, Case-Control Studies, Child, Child, Preschool, Cohort Studies, Female, Genetic Variation, Humans, Male, Models, Genetic, Mutation, Oxidoreductases Acting on CH-CH Group Donors, Potassium Channels, Rare Diseases, RNA, RNA Splicing, Sequence Analysis, RNA, Whole Exome Sequencing}, issn = {1546-170X}, doi = {10.1038/s41591-019-0457-8}, author = {Fr{\'e}sard, Laure and Smail, Craig and Ferraro, Nicole M and Teran, Nicole A and Li, Xin and Smith, Kevin S and Bonner, Devon and Kernohan, Kristin D and Marwaha, Shruti and Zappala, Zachary and Balliu, Brunilda and Davis, Joe R and Liu, Boxiang and Prybol, Cameron J and Kohler, Jennefer N and Zastrow, Diane B and Reuter, Chloe M and Fisk, Dianna G and Grove, Megan E and Davidson, Jean M and Hartley, Taila and Joshi, Ruchi and Strober, Benjamin J and Utiramerur, Sowmithri and Lind, Lars and Ingelsson, Erik and Battle, Alexis and Bejerano, Gill and Bernstein, Jonathan A and Ashley, Euan A and Boycott, Kym M and Merker, Jason D and Wheeler, Matthew T and Montgomery, Stephen B} } @article {55, title = {Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.}, journal = {Curr Protoc Hum Genet}, volume = {101}, year = {2019}, month = {2019 04}, pages = {e83}, abstract = {

With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. {\textcopyright} 2019 by John Wiley \& Sons, Inc.

}, keywords = {Algorithms, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, High-Throughput Nucleotide Sequencing, Humans, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Whole Exome Sequencing, Whole Genome Sequencing}, issn = {1934-8258}, doi = {10.1002/cphg.83}, author = {Weissenkampen, J Dylan and Jiang, Yu and Eckert, Scott and Jiang, Bibo and Li, Bingshan and Liu, Dajiang J} } @article {48, title = {Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 Feb 15}, pages = {790}, abstract = {

Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 - p)], where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1\%) explain less than 10\% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.

}, keywords = {Algorithms, Alleles, Biological Specimen Banks, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Selection, Genetic, United Kingdom}, issn = {2041-1723}, doi = {10.1038/s41467-019-08424-6}, author = {Schoech, Armin P and Jordan, Daniel M and Loh, Po-Ru and Gazal, Steven and O{\textquoteright}Connor, Luke J and Balick, Daniel J and Palamara, Pier F and Finucane, Hilary K and Sunyaev, Shamil R and Price, Alkes L} } @article {22, title = {Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.}, journal = {Am J Epidemiol}, volume = {186}, year = {2017}, month = {2017 Oct 01}, pages = {753-761}, abstract = {

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G{\texttimes}Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G{\texttimes}E discovery. This paper highlights current and critical issues and themes in G{\texttimes}E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

}, keywords = {Disease, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Software}, issn = {1476-6256}, doi = {10.1093/aje/kwx227}, author = {McAllister, Kimberly and Mechanic, Leah E and Amos, Christopher and Aschard, Hugues and Blair, Ian A and Chatterjee, Nilanjan and Conti, David and Gauderman, W James and Hsu, Li and Hutter, Carolyn M and Jankowska, Marta M and Kerr, Jacqueline and Kraft, Peter and Montgomery, Stephen B and Mukherjee, Bhramar and Papanicolaou, George J and Patel, Chirag J and Ritchie, Marylyn D and Ritz, Beate R and Thomas, Duncan C and Wei, Peng and Witte, John S} } @article {11, title = {Estimating the selective effects of heterozygous protein-truncating variants from human exome data.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 May}, pages = {806-810}, abstract = {

The evolutionary cost of gene loss is a central question in genetics and has been investigated in model organisms and human cell lines. In humans, tolerance of the loss of one or both functional copies of a gene is related to the gene{\textquoteright}s causal role in disease. However, estimates of the selection and dominance coefficients in humans have been elusive. Here we analyze exome sequence data from 60,706 individuals to make genome-wide estimates of selection against heterozygous loss of gene function. Using this distribution of selection coefficients for heterozygous protein-truncating variants (PTVs), we provide corresponding Bayesian estimates for individual genes. We find that genes under the strongest selection are enriched in embryonic lethal mouse knockouts, Mendelian disease-associated genes, and regulators of transcription. Screening by essentiality, we find a large set of genes under strong selection that are likely to have crucial functions but have not yet been thoroughly characterized.

}, keywords = {Algorithms, Animals, Bayes Theorem, Exome, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Heterozygote, Humans, Mice, Knockout, Models, Genetic, Mutation, Selection, Genetic, Sequence Analysis, DNA}, issn = {1546-1718}, doi = {10.1038/ng.3831}, author = {Cassa, Christopher A and Weghorn, Donate and Balick, Daniel J and Jordan, Daniel M and Nusinow, David and Samocha, Kaitlin E and O{\textquoteright}Donnell-Luria, Anne and MacArthur, Daniel G and Daly, Mark J and Beier, David R and Sunyaev, Shamil R} } @article {32, title = {Genetic identification of a common collagen disease in puerto ricans via identity-by-descent mapping in a health system.}, journal = {Elife}, volume = {6}, year = {2017}, month = {2017 Sep 12}, abstract = {

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic Bio biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, , with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2\% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

}, keywords = {Adolescent, Adult, Aged, Child, Collagen Diseases, Female, Fibrillar Collagens, Genotype, Heterozygote, Hispanic or Latino, Homozygote, Humans, Male, Middle Aged, Molecular Epidemiology, Multigene Family, Musculoskeletal Diseases, New York City, Pedigree, Whole Genome Sequencing, Young Adult}, issn = {2050-084X}, doi = {10.7554/eLife.25060}, author = {Belbin, Gillian Morven and Odgis, Jacqueline and Sorokin, Elena P and Yee, Muh-Ching and Kohli, Sumita and Glicksberg, Benjamin S and Gignoux, Christopher R and Wojcik, Genevieve L and Van Vleck, Tielman and Jeff, Janina M and Linderman, Michael and Schurmann, Claudia and Ruderfer, Douglas and Cai, Xiaoqiang and Merkelson, Amanda and Justice, Anne E and Young, Kristin L and Graff, Misa and North, Kari E and Peters, Ulrike and James, Regina and Hindorff, Lucia and Kornreich, Ruth and Edelmann, Lisa and Gottesman, Omri and Stahl, Eli Ea and Cho, Judy H and Loos, Ruth Jf and Bottinger, Erwin P and Nadkarni, Girish N and Abul-Husn, Noura S and Kenny, Eimear E} } @article {26, title = {Improved methods for multi-trait fine mapping of pleiotropic risk loci.}, journal = {Bioinformatics}, volume = {33}, year = {2017}, month = {2017 Jan 15}, pages = {248-255}, abstract = {

MOTIVATION: Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation.

RESULTS: In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90\% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data.

AVAILABILITY AND IMPLEMENTATION: The fastPAINTOR framework is implemented in the PAINTOR v3.0 package which is publicly available to the research community http://bogdan.bioinformatics.ucla.edu/software/paintor CONTACT: gkichaev@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online.

}, keywords = {Chromosome Mapping, Genetic Diseases, Inborn, Genetic Loci, Genetic Pleiotropy, Genome-Wide Association Study, Genomics, Humans, Linkage Disequilibrium, Lipid Metabolism, Models, Genetic, Polymorphism, Single Nucleotide, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btw615}, author = {Kichaev, Gleb and Roytman, Megan and Johnson, Ruth and Eskin, Eleazar and Lindstr{\"o}m, Sara and Kraft, Peter and Pasaniuc, Bogdan} } @article {9, title = {Population- and individual-specific regulatory variation in Sardinia.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 May}, pages = {700-707}, abstract = {

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

}, keywords = {Alternative Splicing, Chromosome Mapping, Family Health, Female, Gene Expression Profiling, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Genotype, Humans, Italy, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Transcription Initiation Site}, issn = {1546-1718}, doi = {10.1038/ng.3840}, author = {Pala, Mauro and Zappala, Zachary and Marongiu, Mara and Li, Xin and Davis, Joe R and Cusano, Roberto and Crobu, Francesca and Kukurba, Kimberly R and Gloudemans, Michael J and Reinier, Frederic and Berutti, Riccardo and Piras, Maria G and Mulas, Antonella and Zoledziewska, Magdalena and Marongiu, Michele and Sorokin, Elena P and Hess, Gaelen T and Smith, Kevin S and Busonero, Fabio and Maschio, Andrea and Steri, Maristella and Sidore, Carlo and Sanna, Serena and Fiorillo, Edoardo and Bassik, Michael C and Sawcer, Stephen J and Battle, Alexis and Novembre, John and Jones, Chris and Angius, Andrea and Abecasis, Gon{\c c}alo R and Schlessinger, David and Cucca, Francesco and Montgomery, Stephen B} } @article {16, title = {Testing for the indirect effect under the null for genome-wide mediation analyses.}, journal = {Genet Epidemiol}, volume = {41}, year = {2017}, month = {2017 Dec}, pages = {824-833}, abstract = {

Mediation analysis helps researchers assess whether part or all of an exposure{\textquoteright}s effect on an outcome is due to an intermediate variable. The indirect effect can help in designing interventions on the mediator as opposed to the exposure and better understanding the outcome{\textquoteright}s mechanisms. Mediation analysis has seen increased use in genome-wide epidemiological studies to test for an exposure of interest being mediated through a genomic measure such as gene expression or DNA methylation (DNAm). Testing for the indirect effect is challenged by the fact that the null hypothesis is composite. We examined the performance of commonly used mediation testing methods for the indirect effect in genome-wide mediation studies. When there is no association between the exposure and the mediator and no association between the mediator and the outcome, we show that these common tests are overly conservative. This is a case that will arise frequently in genome-wide mediation studies. Caution is hence needed when applying the commonly used mediation tests in genome-wide mediation studies. We evaluated the performance of these methods using simulation studies, and performed an epigenome-wide mediation association study in the Normative Aging Study, analyzing DNAm as a mediator of the effect of pack-years on FEV .

}, keywords = {Basic Helix-Loop-Helix Transcription Factors, DNA Methylation, Epigenomics, Genome-Wide Association Study, Humans, Lung Neoplasms, Models, Genetic, Repressor Proteins}, issn = {1098-2272}, doi = {10.1002/gepi.22084}, author = {Barfield, Richard and Shen, Jincheng and Just, Allan C and Vokonas, Pantel S and Schwartz, Joel and Baccarelli, Andrea A and VanderWeele, Tyler J and Lin, Xihong} }