Nilanjan Chatterjee, Bloomberg Distinguished Professor

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks …

Background: Breast cancer risk-reducing therapies such as tamoxifen and aromatase inhibitors are effective for ER-positive (ER+) but not for ER-negative disease. As these therapies have side effects it is important to identify women at risk of ER+ disease. We developed and validated ER-specific risk prediction models in a prospective cohort and evaluated the expected gains of predicting ER+ vs overall disease. Methods: The iCARE-Lit model integrates established questionnaire-based risk factors and a 313 variant polygenic risk score. We reparametrized the iCARE-Lit model to estimate risk of ER+ and ER- disease separately by obtaining relative risks from published literature for ages at menarche, menopause, first childbirth, and parity to account for their heterogeneous associations with risk of ER-defined subtypes. We estimated 5-year (yr) absolute risk (AR) for ER+ disease using an overall and ER+ model …

Polygenic Risk Scores (PRS) developed from genome-wide association studies (GWAS) are of increasing interest for various clinical and research applications. Bayesian methods have been particularly popular for building PRS in genome-wide scale because of their natural ability to regularize model and borrow information in high-dimension. In this article, we present new theoretical results, methods, and extensive numerical studies to advance Bayesian methods for PRS applications. We conduct theoretical studies to identify causes of convergence issues of some Bayesian methods when required input GWAS summary-statistics and linkage disequilibrium (LD) (genetic correlation) data are derived from distinct samples. We propose a remedy to the problem by the projection of the summary-statistics data into the column space of the genetic correlation matrix. We further implement a PRS development algorithm under the Bayesian Bridge prior which can allow more flexible specification of effect-size distribution than those allowed under popular alternative methods. Finally, we conduct careful benchmarking studies of alternative Bayesian methods using both simulation studies and real datasets, where we carefully investigate both the effect of prior specification and estimation strategies for LD parameters. These studies show that the proposed algorithm, equipped with the projection approach, the flexible prior specification, and an efficient numerical algorithm leads to the development of the most robust PRS across a wide variety of scenarios.

Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination of (lasso) and (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of …

Background: A genetic variant (rs3824662) at GATA3 was previously associated with risk of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) and relapse. Our recently published childhood Hodgkin lymphoma (HL) study identified a genome-wide significant association for another genetic variant (rs3781093) in high linkage disequilibrium (D’=1.0, R2=0.91) with rs3824662. We hypothesize that GATA3 is a pleiotropic locus associated with multiple childhood cancers. Methods: The study was performed by combining 3 cohorts of childhood cancer survivors: the St Jude Lifetime Cohort Study (SJLIFE), the original and expansion cohorts of the Childhood Cancer Survivor Study (CCSS). The CCSS original cohort had SNP array genotyping and imputation, and the SJLIFE and CCSS expansion cohort underwent whole-genome sequencing. Associations between the variants mapped to GATA3 …

Obesity is a recognised risk factor for many cancers and with rising global prevalence, has become a leading cause of cancer. Here we summarise the current evidence from both population-based epidemiologic investigations and experimental studies on the role of obesity in cancer development. This review presents a new meta-analysis using data from 40 million individuals and reports positive associations with 19 cancer types. Utilising major new data from East Asia, the meta-analysis also shows that the strength of obesity and cancer associations varies regionally, with stronger relative risks for several cancers in East Asia. This review also presents current evidence on the mechanisms linking obesity and cancer and identifies promising future research directions. These include the use of new imaging data to circumvent the methodological issues involved with body mass index and the use of omics technologies to resolve biologic mechanisms with greater precision and clarity.

Integrating results from genome-wide association studies (GWASs) and studies of molecular phenotypes such as gene expressions can improve our understanding of the biological functions of trait-associated variants and can help prioritize candidate genes for downstream analysis. Using reference expression quantitative trait locus (eQTL) studies, several methods have been proposed to identify gene-trait associations, primarily based on gene expression imputation. To increase the statistical power by leveraging substantial eQTL sharing across tissues, meta-analysis methods aggregating such gene-based test results across multiple tissues or contexts have been developed as well. However, most existing meta-analysis methods have limited power to identify associations when the gene has weaker associations in only a few tissues and cannot identify the subset of tissues in which the gene is "activated." For this …

Background: Lung cancer is the leading cause of cancer mortality worldwide, and incidence rates for the disease in never-smokers is among the highest in East Asian (EAS) women. Epidermal growth factor receptor (EGFR) is a transmembrane protein that regulates cellular proliferation and apoptosis, and mutations in the EGFR gene have been found to be a defining hallmark of lung adenocarcinoma (LUAD). We investigated if overall genetic susceptibility to LUAD, defined as a polygenic risk score (PRS), is differentially associated with LUAD by EGFR mutation status. Methods: The study consists of 998 female never-smoking histologically confirmed LUAD cases with data on EGFR mutation status and 4,544 female never-smoking controls from the Female Lung Cancer Consortium in Asia. Germline DNA samples were genotyped using the 370K, 610Q, or 660W microarrays. Genomic DNA extracted from fresh …

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

Polygenic risk scores (PRS) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across different populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in the summary statistics from genome-wide association studies (GWAS) across multiple ancestry groups. MUSSEL conducts Bayesian hierarchical modeling under a MUltivariate Spike-and-Slab model for effect-size distribution and incorporates an Ensemble Learning step using super learner to combine information across different tuning parameter settings and ancestry groups. In our simulation studies and data analyses of 16 traits across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. The method, for …

Mendelian randomization (MR) analysis is increasingly popular for testing the causal effect of exposures on disease outcomes using data from genome-wide association studies. In some settings, the underlying exposure, such as systematic inflammation, may not be directly observable, but measurements can be available on multiple biomarkers or other types of traits that are co-regulated by the exposure. We propose a method for MR analysis on latent exposures (MRLE), which tests the significance for, and the direction of, the effect of a latent exposure by leveraging information from multiple related traits. The method is developed by constructing a set of estimating functions based on the second-order moments of GWAS summary association statistics for the observable traits, under a structural equation model where genetic variants are assumed to have indirect effects through the latent exposure and potentially …

Lung cancer is the leading cause of all cancer-related mortality worldwide. The RAS-RAF-MEK-ERK (RAS-MAPK) signaling pathway is critical for maintaining cell survival and proliferation. Somatic mutations in the RAS or RAF genes are associated with frequent hyper-activation of RAS-MAPK pathway in non-small cell lung cancer or NSCLC. While direct inhibitors of KRAS G12C are emerging with promising efficacy, resistance to these agents as well as to inhibitors of RAF and MEK remains an obstacle to long-term patient survival. Therefore, it is essential to understand how drug resistance emerges in lung cancer and to identify bypass survival pathways or compensatory mechanisms that limit the response to RAS-MAPK targeted therapies in lung cancer. Emerging literature indicates a critical role of bromodomain and extra-terminal domain (BET) family of bromodomain proteins (BRD4, BRD3, BRD2) in various …

Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes | Leukemia Skip to main content Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Leukemia View all journals Search My Account Explore content About the journal Publish with us Sign up for alerts RSS feed 1.nature 2.leukemia 3.corrections 4.article Download PDF Correction Published: 04 September 2023 Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes Sonja I. Berndt ORCID: orcid.org/0000-0001-5230-0652 1 na1 , Joseph Vijai 2 na1 , …

Clonal hematopoiesis (CH), while common with aging, confers a high relative risk of hematologic malignancy (HM). Genome-wide association studies have identified multiple germline predisposition loci for CH but many have an unclear functional role. Here we characterized the contribution of pathogenic/likely pathogenic germline variants (PGVs) to CH and its progression to HM using the UK Biobank (UKBB) as a discovery cohort (N=454,859) with validation in Memorial Sloan Kettering IMPACT and The Cancer Genome Atlas (N=24,258). We profiled whole exome sequencing (WES) for PGVs in 240 cancer predisposition genes.We simultaneously analyzedWES for CH driven by single nucleotide variants/indels and SNP array data for mosaic chromosomal alterations.Overall, 8.9% of individuals in the UKBB harbored PGVs in genes with a dominant inheritance mode (5.2% in HM-related genes). To identify …

Introduction: Identifying parallel survival pathways or compensatory mechanisms that limit the response to targeted therapy is critical to discover effective combinatorial strategies for the treatment of lung cancer and to prevent emergence of drug resistance Results: Using combination drug screening in a panel of cell line models of non-small cell lung cancer (NSCLC), we identified the tumor suppressor STK11 (aka LKB1) as a molecular biomarker of sensitivity to BET and RAS-MAPK pathway inhibitors combination in NSCLC. We found a small molecule inhibitor of BET (bromodomain and extra terminal) family proteins (BRD4, 3, 2), PLX51107, suppressed BRAF and KRAS mutant NSCLC cell proliferation and in combination with RAS (KRAS G12C), RAF or MEK inhibitor led to pronounced loss in cell viability with potent MYC downregulation and synergistic apoptosis induction in vitro and potent tumor regression or …

BackgroundThe pathophysiological causes of kidney disease are not fully understood. Here we show that the integration of genome-wide genetic, transcriptomic, and proteomic association studies can nominate causal determinants of kidney function and damage.ResultsThrough transcriptome-wide association studies (TWAS) in kidney cortex, kidney tubule, liver, and whole blood and proteome-wide association studies (PWAS) in plasma, we assess for effects of 12,893 genes and 1342 proteins on kidney filtration (glomerular filtration rate (GFR) estimated by creatinine; GFR estimated by cystatin C; and blood urea nitrogen) and kidney damage (albuminuria). We find 1561 associations distributed among 260 genomic regions that are supported as putatively causal. We then prioritize 153 of these genomic regions using additional colocalization analyses. Our genome-wide findings are supported by existing …

Integrated step‐selection analysis (ISSA) is frequently used to study habitat selection using animal movement data. Methods for incorporating random effects in ISSA have been developed, making it possible to quantify variability among animals in their space‐use patterns. Although it is possible to model variability in both habitat selection and movement parameters, applications to date have focused on the former despite the widely acknowledged and important role that movement plays in determining ecological processes from the individual to ecosystem level. One potential explanation for this omission is the absence of readily available software or examples demonstrating methods for estimating movement parameters in ISSA with random effects. We demonstrated methods for characterizing among‐individual variability in both movement and habitat‐selection parameters using a simulated data set and by …

Genetically predicted proteins have been associated with pancreatic cancer risk previously. We aimed to externally validate the associations of 53 candidate proteins with pancreatic cancer risk using directly measured, prediagnostic levels. We conducted a prospective cohort study of 10 355 US Black and White men and women in the Atherosclerosis Risk in Communities (ARIC) study. Aptamer‐based plasma proteomic profiling was previously performed using blood collected in 1993 to 1995, from which the proteins were selected. By 2015 (median: 20 years), 93 incident pancreatic cancer cases were ascertained. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for protein tertiles, and adjust for age, race, and known risk factors. Of the 53 proteins, three were statistically significantly, positively associated with risk—GLCE (tertile 3 vs 1: HR = 1.88, 95% CI: 1.12‐3.13 …

Polygenic risk scores (PRS) are rapidly emerging as aggregated measures of disease-risk associated with many genetic variants. Understanding the interplay of PRS with environmental factors is critical for interpreting and applying PRS in a wide variety of settings. We develop an efficient method for simultaneously modeling gene-environment correlations and interactions using PRS in case-control studies. We use a logistic-normal regression modeling framework to specify the disease risk and PRS distribution in the underlying population and propose joint inference across the two models using the retrospective likelihood of the case-control data. Extensive simulation studies demonstrate the flexibility of the method in trading-off bias and efficiency for the estimation of various model parameters compared to the standard logistic regression or a case-only analysis for gene-environment interactions, or a control-only …

ImportanceEstimating absolute risk of lung cancer for never-smoking individuals is important to inform lung cancer screening programs.ObjectivesTo integrate data on environmental tobacco smoke (ETS), a known lung cancer risk factor, with a polygenic risk score (PRS) that captures overall genetic susceptibility, to estimate the absolute risk of lung adenocarcinoma (LUAD) among never-smokers in Taiwan.Design, Setting, and ParticipantsThe analyses were conducted in never-smoking women in the Taiwan Genetic Epidemiology Study of Lung Adenocarcinoma, a case-control study. Participants were recruited between September 17, 2002, and March 30, 2011. Data analysis was performed from January 17 to July 15, 2022.ExposuresA PRS was derived using 25 genetic variants that achieved genome-wide significance (P < 5 × 10−8) in a recent genome-wide association study, and ETS was defined as never …