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1. Fast computation of the eigensystem of genomic similarity matrices

Author

Georg Hahn, Sharon M. Lutz, Julian Hecker, Dmitry Prokopenko, Michael H. Cho, Edwin K. Silverman, Scott T. Weiss, and Christoph Lange

Subjects
Covariance matrix, Fast SVD, Genomic relationship matrix, Jaccard matrix, Principal components, Weighted Jaccard matrix, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract The computation of a similarity measure for genomic data is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases due to confounding by population stratification, for instance in linear regressions. However, the calculation of both a similarity matrix and its singular value decomposition (SVD) are computationally intensive. The contribution of this article is threefold. First, we demonstrate that the calculation of three matrices (called the covariance matrix, the weighted Jaccard matrix, and the genomic relationship matrix) can be reformulated in a unified way which allows for the application of a randomized SVD algorithm, which is faster than the traditional computation. The fast SVD algorithm we present is adapted from an existing randomized SVD algorithm and ensures that all computations are carried out in sparse matrix algebra. The algorithm only assumes that row-wise and column-wise subtraction and multiplication of a vector with a sparse matrix is available, an operation that is efficiently implemented in common sparse matrix packages. An exception is the so-called Jaccard matrix, which does not have a structure applicable for the fast SVD algorithm. Second, an approximate Jaccard matrix is introduced to which the fast SVD computation is applicable. Third, we establish guaranteed theoretical bounds on the accuracy (in $$L_2$$ L 2 norm and angle) between the principal components of the Jaccard matrix and the ones of our proposed approximation, thus putting the proposed Jaccard approximation on a solid mathematical foundation, and derive the theoretical runtime of our algorithm. We illustrate that the approximation error is low in practice and empirically verify the theoretical runtime scalings on both simulated data and data of the 1000 Genome Project.

Published
2024
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2. Multivariate GWAS of Alzheimer’s disease CSF biomarker profiles implies GRIN2D in synaptic functioning

Author

Alexander Neumann, Olena Ohlei, Fahri Küçükali, Isabelle J. Bos, Jigyasha Timsina, Stephanie Vos, Dmitry Prokopenko, Betty M. Tijms, Ulf Andreasson, Kaj Blennow, Rik Vandenberghe, Philip Scheltens, Charlotte E. Teunissen, Sebastiaan Engelborghs, Giovanni B. Frisoni, Oliver Blin, Jill C. Richardson, Régis Bordet, Alberto Lleó, Daniel Alcolea, Julius Popp, Thomas W. Marsh, Priyanka Gorijala, Christopher Clark, Gwendoline Peyratout, Pablo Martinez-Lage, Mikel Tainta, Richard J. B. Dobson, Cristina Legido-Quigley, Christine Van Broeckhoven, Rudolph E. Tanzi, Mara ten Kate, Christina M. Lill, Frederik Barkhof, Carlos Cruchaga, Simon Lovestone, Johannes Streffer, Henrik Zetterberg, Pieter Jelle Visser, Kristel Sleegers, Lars Bertram, and EMIF-AD & ADNI study group

Subjects
Alzheimer’s disease, Dementia, Biomarkers, Cerebrospinal fluid (CSF), Genome-wide association study (GWAS), Multivariate analysis, Medicine, Genetics, QH426-470
Abstract

Abstract Background Genome-wide association studies (GWAS) of Alzheimer’s disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. Methods We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. Results Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. Conclusions These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.

Published
2023
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3. Association of PHACTR1 with Coronary Artery Calcium Differs by Sex and Cigarette Smoking

Author

Kirsten Voorhies, Kendra Young, Fang-Chi Hsu, Nicholette D. Palmer, Merry-Lynn N. McDonald, Sanghun Lee, Georg Hahn, Julian Hecker, Dmitry Prokopenko, Ann Chen Wu, Elizabeth A. Regan, Dawn DeMeo, Greg L. Kinney, James D. Crapo, Michael H. Cho, Edwin K. Silverman, Christoph Lange, Matthew J. Budoff, John E. Hokanson, and Sharon M. Lutz

Subjects
coronary artery calcium, PHACTR1, CDKN2B-AS1, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background: Coronary artery calcium (CAC) is a marker of subclinical atherosclerosis and is a complex heritable trait with both genetic and environmental risk factors, including sex and smoking. Methods: We performed genome-wide association (GWA) analyses for CAC among all participants and stratified by sex in the COPDGene study (n = 6144 participants of European ancestry and n = 2589 participants of African ancestry) with replication in the Diabetes Heart Study (DHS). We adjusted for age, sex, current smoking status, BMI, diabetes, self-reported high blood pressure, self-reported high cholesterol, and genetic ancestry (as summarized by principal components computed within each racial group). For the significant signals from the GWA analyses, we examined the single nucleotide polymorphism (SNP) by sex interactions, stratified by smoking status (current vs. former), and tested for a SNP by smoking status interaction on CAC. Results: We identified genome-wide significant associations for CAC in the chromosome 9p21 region [CDKN2B-AS1] among all COPDGene participants (p = 7.1 × 10−14) and among males (p = 1.0 × 10−9), but the signal was not genome-wide significant among females (p = 6.4 × 10−6). For the sex stratified GWA analyses among females, the chromosome 6p24 region [PHACTR1] had a genome-wide significant association (p = 4.4 × 10−8) with CAC, but this signal was not genome-wide significant among all COPDGene participants (p = 1.7 × 10−7) or males (p = 0.03). There was a significant interaction for the SNP rs9349379 in PHACTR1 with sex (p = 0.02), but the interaction was not significant for the SNP rs10757272 in CDKN2B-AS1 with sex (p = 0.21). In addition, PHACTR1 had a stronger association with CAC among current smokers (p = 6.2 × 10−7) than former smokers (p = 7.5 × 10−3) and the SNP by smoking status interaction was marginally significant (p = 0.03). CDKN2B-AS1 had a strong association with CAC among both former (p = 7.7 × 10−8) and current smokers (p = 1.7 × 10−7) and the SNP by smoking status interaction was not significant (p = 0.40). Conclusions: Among current and former smokers of European ancestry in the COPDGene study, we identified a genome-wide significant association in the chromosome 6p24 region [PHACTR1] with CAC among females, but not among males. This region had a significant SNP by sex and SNP by smoking interaction on CAC.

Published
2024
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4. A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data

Author

Julian Hecker, Sanghun Lee, Priyadarshini Kachroo, Dmitry Prokopenko, Anna Maaser-Hecker, Sharon M. Lutz, Georg Hahn, Rafael Irizarry, Scott T. Weiss, Dawn L. DeMeo, and Christoph Lange

Subjects
DNA methylation, methylation arrays, batch effects, slide effects, EWAS, Genetics, QH426-470
Abstract

ABSTRACTBackground: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.

Published
2023
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5. Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest

Author

Georg Hahn, Sanghun Lee, Dmitry Prokopenko, Jonathan Abraham, Tanya Novak, Julian Hecker, Michael Cho, Surender Khurana, Lindsey R. Baden, Adrienne G. Randolph, Scott T. Weiss, and Christoph Lange

Subjects
SARS-CoV-2, Nucleotide sequences, Outlier detection, Variants of interest, Machine learning, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract As of June 2022, the GISAID database contains more than 11 million SARS-CoV-2 genomes, including several thousand nucleotide sequences for the most common variants such as delta or omicron. These SARS-CoV-2 strains have been collected from patients around the world since the beginning of the pandemic. We start by assessing the similarity of all pairs of nucleotide sequences using the Jaccard index and principal component analysis. As shown previously in the literature, an unsupervised cluster analysis applied to the SARS-CoV-2 genomes results in clusters of sequences according to certain characteristics such as their strain or their clade. Importantly, we observe that nucleotide sequences of common variants are often outliers in clusters of sequences stemming from variants identified earlier on during the pandemic. Motivated by this finding, we are interested in applying outlier detection to nucleotide sequences. We demonstrate that nucleotide sequences of common variants (such as alpha, delta, or omicron) can be identified solely based on a statistical outlier criterion. We argue that outlier detection might be a useful surveillance tool to identify emerging variants in real time as the pandemic progresses.

Published
2022
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6. PILRA polymorphism modifies the effect of APOE4 and GM17 on Alzheimer’s disease risk

Author

Karin Lopatko Lindman, Caroline Jonsson, Bodil Weidung, Jan Olsson, Janardan P. Pandey, Dmitry Prokopenko, Rudolph E. Tanzi, Göran Hallmans, Sture Eriksson, Fredrik Elgh, and Hugo Lövheim

Subjects
Medicine, Science
Abstract

Abstract PILRA (rs1859788 A > G) has been suggested to be a protective variant for Alzheimer’s disease (AD) and is an entry co-receptor for herpes simplex virus-1. We conducted a nested case–control study of 360 1:1-matched AD subjects. Interactions between the PILRA-A allele, APOE risk variants (ε3/ε4 or ε4/ε4) and GM17 for AD risk were modelled. The associations were cross-validated using two independent whole-genome sequencing datasets. We found negative interactions between PILRA-A and GM17 (OR 0.72, 95% CI 0.52–1.00) and between PILRA-A and APOE risk variants (OR 0.56, 95% CI 0.32–0.98) in the discovery dataset. In the replication cohort, a joint effect of PILRA and PILRA × GM 17/17 was observed for the risk of developing AD (p .02). Here, we report a negative effect modification by PILRA on APOE and GM17 high-risk variants for future AD risk in two independent datasets. This highlights the complex genetics of AD.

Published
2022
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7. A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables.

Author

Julian Hecker, Dmitry Prokopenko, Matthew Moll, Sanghun Lee, Wonji Kim, Dandi Qiao, Kirsten Voorhies, Woori Kim, Stijn Vansteelandt, Brian D Hobbs, Michael H Cho, Edwin K Silverman, Sharon M Lutz, Dawn L DeMeo, Scott T Weiss, and Christoph Lange

Subjects
Genetics, QH426-470
Abstract

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since a.) statistical power is often limited and b.) modeling of environmental effects is nontrivial and such model misspecifications can lead to false positive interaction findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy can increase the power to detect interactions, identifying contributing genes and pathways is difficult based on these relatively global results. Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate sets of genetic variants and/or multiple environmental factors. Based on the user's choice of statistical/machine learning approaches, a screening step selects and combines potential interactions into scores with improved interpretability. In the testing step, the application of robust statistics minimizes the susceptibility to main effect misspecifications. Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios, and we show how the screening strategy influences statistical power. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified highly significant interactions based on subcomponents of genetic risk scores. While the contributing single variant interaction signals are weak, our results indicate interaction patterns that result in strong aggregated effects, providing potential insights into underlying gene-environment interaction mechanisms.

Published
2022
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8. Most Pathways Can Be Related to the Pathogenesis of Alzheimer’s Disease

Author

Sarah L. Morgan, Pourya Naderi, Katjuša Koler, Yered Pita-Juarez, Dmitry Prokopenko, Ioannis S. Vlachos, Rudolph E. Tanzi, Lars Bertram, and Winston A. Hide

Subjects
Alzheimer’s disease, pathway, text-mining, disease mechanism, dementia, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Alzheimer’s disease (AD) is a complex neurodegenerative disorder. The relative contribution of the numerous underlying functional mechanisms is poorly understood. To comprehensively understand the context and distribution of pathways that contribute to AD, we performed text-mining to generate an exhaustive, systematic assessment of the breadth and diversity of biological pathways within a corpus of 206,324 dementia publication abstracts. A total of 91% (325/335) of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways have publications containing an association via at least 5 studies, while 63% of pathway terms have at least 50 studies providing a clear association with AD. Despite major technological advances, the same set of top-ranked pathways have been consistently related to AD for 30 years, including AD, immune system, metabolic pathways, cholinergic synapse, long-term depression, proteasome, diabetes, cancer, and chemokine signaling. AD pathways studied appear biased: animal model and human subject studies prioritize different AD pathways. Surprisingly, human genetic discoveries and drug targeting are not enriched in the most frequently studied pathways. Our findings suggest that not only is this disorder incredibly complex, but that its functional reach is also nearly global. As a consequence of our study, research results can now be assessed in the context of the wider AD literature, supporting the design of drug therapies that target a broader range of mechanisms. The results of this study can be explored at www.adpathways.org.

Published
2022
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9. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Author

Xutong Zhao, Dandi Qiao, Chaojie Yang, Silva Kasela, Wonji Kim, Yanlin Ma, Nick Shrine, Chiara Batini, Tamar Sofer, Sarah A. Gagliano Taliun, Phuwanat Sakornsakolpat, Pallavi P. Balte, Dmitry Prokopenko, Bing Yu, Leslie A. Lange, Josée Dupuis, Brian E. Cade, Jiwon Lee, Sina A. Gharib, Michelle Daya, Cecelia A. Laurie, Ingo Ruczinski, L. Adrienne Cupples, Laura R. Loehr, Traci M. Bartz, Alanna C. Morrison, Bruce M. Psaty, Ramachandran S. Vasan, James G. Wilson, Kent D. Taylor, Peter Durda, W. Craig Johnson, Elaine Cornell, Xiuqing Guo, Yongmei Liu, Russell P. Tracy, Kristin G. Ardlie, François Aguet, David J. VanDenBerg, George J. Papanicolaou, Jerome I. Rotter, Kathleen C. Barnes, Deepti Jain, Deborah A. Nickerson, Donna M. Muzny, Ginger A. Metcalf, Harshavardhan Doddapaneni, Shannon Dugan-Perez, Namrata Gupta, Stacey Gabriel, Stephen S. Rich, George T. O’Connor, Susan Redline, Robert M. Reed, Cathy C. Laurie, Martha L. Daviglus, Liana K. Preudhomme, Kristin M. Burkart, Robert C. Kaplan, Louise V. Wain, Martin D. Tobin, Stephanie J. London, Tuuli Lappalainen, Elizabeth C. Oelsner, Goncalo R. Abecasis, Edwin K. Silverman, R. Graham Barr, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lung Working Group, Michael H. Cho, and Ani Manichaikul

Subjects
Science
Abstract

Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.

Published
2020
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10. Estimating the effective sample size in association studies of quantitative traits

Author

Andrey Ziyatdinov, Jihye Kim, Dmitry Prokopenko, Florian Privé, Fabien Laporte, Po-Ru Loh, Peter Kraft, and Hugues Aschard

Subjects
Genetics, QH426-470
Abstract

AbstractThe effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.

Published
2021
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11. On the Recombination Rate Estimation in the Presence of Population Substructure.

Author

Julian Hecker, Dmitry Prokopenko, Christoph Lange, and Heide Löhlein Fier

Subjects
Medicine, Science
Abstract

As recombination events are not uniformly distributed along the human genome, the estimation of fine-scale recombination maps, e.g. HapMap Project, has been one of the major research endeavors over the last couple of years. For simulation studies, these estimates provide realistic reference scenarios to design future study and to develop novel methodology. To achieve a feasible framework for the estimation of such recombination maps, existing methodology uses sample probabilities for a two-locus model with recombination, with recent advances allowing for computationally fast implementations. In this work, we extend the existing theoretical framework for the recombination rate estimation to the presence of population substructure. We show under which assumptions the existing methodology can still be applied. We illustrate our extension of the methodology by an extensive simulation study.

Published
2015
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12. Using Network Methodology to Infer Population Substructure.

Author

Dmitry Prokopenko, Julian Hecker, Edwin Silverman, Markus M Nöthen, Matthias Schmid, Christoph Lange, and Heide Loehlein Fier

Subjects
Medicine, Science
Abstract

One of the main caveats of association studies is the possible affection by bias due to population stratification. Existing methods rely on model-based approaches like structure and ADMIXTURE or on principal component analysis like EIGENSTRAT. Here we provide a novel visualization technique and describe the problem of population substructure from a graph-theoretical point of view. We group the sequenced individuals into triads, which depict the relational structure, on the basis of a predefined pairwise similarity measure. We then merge the triads into a network and apply community detection algorithms in order to identify homogeneous subgroups or communities, which can further be incorporated as covariates into logistic regression. We apply our method to populations from different continents in the 1000 Genomes Project and evaluate the type 1 error based on the empirical p-values. The application to 1000 Genomes data suggests that the network approach provides a very fine resolution of the underlying ancestral population structure. Besides we show in simulations, that in the presence of discrete population structures, our developed approach maintains the type 1 error more precisely than existing approaches.

Published
2015
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14. Clinical Markers Associated With Risk of Suicide or Drug Overdose Among Individuals With Smoking Exposure

Author

Brigid A. Adviento, Elizabeth A. Regan, Barry J. Make, MeiLan K. Han, Marilyn G. Foreman, Anand S. Iyer, Surya P. Bhatt, Victor Kim, Jessica Bon, Xavier Soler, Gregory L. Kinney, Nicola A. Hanania, Katherine E. Lowe, Kristen E. Holm, Abebaw M. Yohannes, Gen Shinozaki, Karin F. Hoth, Jess G. Fiedorowicz, James D. Crapo, Edwin K. Silverman, Terri H. Beaty, Peter J. Castaldi, Michael H. Cho, Dawn L. DeMeo, Adel El Boueiz, Auyon Ghosh, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Wonji Kim, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Dmitry Prokopenko, Matthew Moll, Jarrett Morrow, Dandi Qiao, Aabida Saferali, Phuwanat Sakornsakolpat, Emily S. Wan, Jeong Yun, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Matthew Strand, Jim Crooks, Katherine Pratte, Aastha Khatiwada, Erin Austin, Gregory Kinney, Kendra A. Young, Alejandro A. Diaz, Barry Make, Susan Murray, Elizabeth Regan, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Jeffrey L. Curtis, Perry G. Pernicano, Nicola Hanania, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, George Washko, R. Graham Barr, John Austin, Belinda D’Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Charlene McEvoy, Joseph Tashjian, Robert Wise, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Nirupama Putcha, Richard Casaburi, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Ken M. Kunisaki, Eric L. Flenaugh, Hirut Gebrekristos, Mario Ponce, Silanath Terpenning, Gloria Westney, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Douglas Conrad, Andrew Yen, Alejandro P. Comellas, John Newell, Brad Thompson, Ella Kazerooni, Wassim Labaki, Craig Galban, Dharshan Vummidi, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Divay Chandra, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, Mario E. Ruiz, and Harjinder Singh

Subjects
Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine, Critical Care and Intensive Care Medicine
Published
2023

15. Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer’s disease-associated genes: DTNB and DLG2

Author

David Fardo, Lars Bertram, and Dmitry Prokopenko

Subjects
Cellular and Molecular Neuroscience, Psychiatry and Mental health, Molecular Biology
Abstract

Alzheimer’s disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency p values −6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (pmeta = 4.74 × 10−8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta = 1 × 10−6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.

Published
2022

16. Development of a Blood-based Transcriptional Risk Score for Chronic Obstructive Pulmonary Disease

Author

Matthew Moll, Adel Boueiz, Auyon J. Ghosh, Aabida Saferali, Sool Lee, Zhonghui Xu, Jeong H. Yun, Brian D. Hobbs, Craig P. Hersh, Don D. Sin, Ruth Tal-Singer, Edwin K. Silverman, Michael H. Cho, Peter J. Castaldi, James D. Crapo, Barry J. Make, Elizabeth A. Regan, Terri Beaty, Ferdouse Begum, Michael Cho, Dawn L. DeMeo, Adel R. Boueiz, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Jacqueline Hetmanski, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dmitry Prokopenko, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Gregory Kinney, Kendra A. Young, Surya P. Bhatt, Jessica Bon, Alejandro A. Diaz, Susan Murray, Xavier Soler, Russell P. Bowler, Katerina Kechris, and Farnoush Banaei-Kashani

Subjects
Pulmonary and Respiratory Medicine, COPD, Framingham Risk Score, business.industry, Pulmonary disease, Critical Care and Intensive Care Medicine, medicine.disease, Bioinformatics, Peripheral blood, respiratory tract diseases, Transcriptome, Gene expression, medicine, Polygenic risk score, business
Abstract

Rationale: The ability of peripheral blood biomarkers to assess COPD risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict...

Published
2022

17. Clinically Significant and Comorbid Anxiety and Depression Symptoms Predict Severe Respiratory Exacerbations in Smokers: A Post Hoc Analysis of the COPDGene and SPIROMICS Cohorts

Author

Anand S. Iyer, Trisha M. Parekh, Jacqueline O’Toole, Surya P. Bhatt, Michelle N. Eakin, Jerry A. Krishnan, Abebaw M. Yohannes, Prescott G. Woodruff, Christopher B. Cooper, Richard E. Kanner, Nicola A. Hanania, Mark T. Dransfield, Elizabeth A. Regan, Karin F. Hoth, Victor Kim, James D. Crapo, Edwin K. Silverman, Barry J. Make, Terri Beaty, Ferdouse Begum, Peter J. Castaldi, Michael Cho, Dawn L. DeMeo, Adel R. Boueiz, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dmitry Prokopenko, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Sungho Won, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Huries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San José Estépar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Gregory Kinney, Kendra A. Young, Jessica Bon, Alejandro A. Diaz, Barry Make, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Jeffrey L. Curtis, Perry G. Pernicano, Nicola Hanania, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, George Washko, R. Graham Barr, John Austin, Belinda D’Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Robert Wise, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Los Angeles, Richard Casaburi, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Ken M. Kunisaki, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Douglas Conrad, Andrew Yen, Alejandro P. Comellas, John Newell, Brad Thompson, Ella Kazerooni, Wassim Labaki, Craig Galban, Dharshan Vummidi, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Divay Chandra, Carl Fuhrman, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, Mario E. Ruiz, and Harjinder Singh

Subjects
Pulmonary and Respiratory Medicine, medicine.medical_specialty, Comorbid anxiety, business.industry, Internal medicine, Post-hoc analysis, Medicine, Respiratory system, business, Depressive symptoms
Published
2022

18. The Association Between Lung Hyperinflation and Coronary Artery Disease in Smokers

Author

Divay Chandra, Aman Gupta, Gregory L. Kinney, Carl R. Fuhrman, Joseph K. Leader, Alejandro A. Diaz, Jessica Bon, R. Graham Barr, George Washko, Matthew Budoff, John Hokanson, Frank C. Sciurba, James D. Crapo, Edwin K. Silverman, Barry J. Make, Elizabeth A. Regan, Terri Beaty, Ferdouse Begum, Adel R. Boueiz, Peter J. Castaldi, Michael Cho, Dawn L. DeMeo, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dmitry Prokopenko, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Sungho Won, Mustafa Al Qaisi, Harvey O. Coxson, Teresa Gray, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, John D. Newell, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Douglas Stinson, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Carla G. Wilson, Robert Jensen, Jim Crooks, Douglas Everett, Camille Moore, null Strand, John Hughes, Gregory Kinney, Katherine Pratte, Kendra A. Young, Surya Bhatt, Carlos Martinez, Susan Murray, Xavier Soler, Farnoush Banaei-Kashani, Russell P. Bowler, Katerina Kechris, Jeffrey L. Curtis, Perry G. Pernicano, Nicola Hanania, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, John Austin, Belinda D’Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Charlene McEvoy, Joseph Tashjian, Robert Wise, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Nirupama Putcha, Richard Casaburi, Alessandra Adami, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Michael E. DeBakey, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Ken M. Kunisaki, Eugene Berkowitz, Gloria Westney, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, Victor Kim, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Surya P. Bhatt, Anand Iyer, Hrudaya Nath, J. Michael Wells, Joe Ramsdell, Paul Friedman, Andrew Yen, Alejandro P. Comellas, Karin F. Hoth, John Newell, Brad Thompson, Ella Kazerooni, Carlos H. Martinez, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Carl Fuhrman, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, and Mario E. Ruiz

Subjects
Male, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Coronary Artery Disease, Critical Care and Intensive Care Medicine, COPD: Original Research, Coronary artery disease, 03 medical and health sciences, FEV1/FVC ratio, 0302 clinical medicine, Functional residual capacity, Risk Factors, Internal medicine, medicine, Humans, Lung volumes, 030212 general & internal medicine, Myocardial infarction, Lung, Subclinical infection, COPD, business.industry, Smoking, Organ Size, Middle Aged, respiratory system, medicine.disease, Coronary Vessels, United States, Respiratory Function Tests, respiratory tract diseases, Airway Obstruction, Plethysmography, Biological Variation, Population, Pulmonary Emphysema, 030228 respiratory system, Asymptomatic Diseases, Cohort, Cardiology, Airway Remodeling, Female, Tomography, X-Ray Computed, Cardiology and Cardiovascular Medicine, business
Abstract

BACKGROUND: Smokers manifest varied phenotypes of pulmonary impairment. RESEARCH QUESTION: Which pulmonary phenotypes are associated with coronary artery disease (CAD) in smokers? STUDY DESIGN AND METHODS: We analyzed data from the University of Pittsburgh COPD Specialized Center for Clinically Oriented Research (SCCOR) cohort (n = 481) and the Genetic Epidemiology of COPD (COPDGene) cohort (n = 2,580). Participants were current and former smokers with > 10 pack-years of tobacco exposure. Data from the two cohorts were analyzed separately because of methodologic differences. Lung hyperinflation was assessed by plethysmography in the SCCOR cohort and by inspiratory and expiratory CT scan lung volumes in the COPDGene cohort. Subclinical CAD was assessed as the coronary artery calcium score, whereas clinical CAD was defined as a self-reported history of CAD or myocardial infarction (MI). Analyses were performed in all smokers and then repeated in those with airflow obstruction (FEV(1) to FVC ratio, < 0.70). RESULTS: Pulmonary phenotypes, including airflow limitation, emphysema, lung hyperinflation, diffusion capacity, and radiographic measures of airway remodeling, showed weak to moderate correlations (r < 0.7) with each other. In multivariate models adjusted for pulmonary phenotypes and CAD risk factors, lung hyperinflation was the only phenotype associated with calcium score, history of clinical CAD, or history of MI (per 0.2 higher expiratory and inspiratory CT scan lung volume; coronary calcium: OR, 1.2; 95% CI, 1.1-1.5; P = .02; clinical CAD: OR, 1.6; 95% CI, 1.1-2.3; P = .01; and MI in COPDGene: OR, 1.7; 95% CI, 1.0-2.8; P = .05). FEV(1) and emphysema were associated with increased risk of CAD (P < .05) in models adjusted for CAD risk factors; however, these associations were attenuated on adjusting for lung hyperinflation. Results were the same in those with airflow obstruction and were present in both cohorts. INTERPRETATION: Lung hyperinflation is associated strongly with clinical and subclinical CAD in smokers, including those with airflow obstruction. After lung hyperinflation was accounted for, FEV(1) and emphysema no longer were associated with CAD. Subsequent studies should consider measuring lung hyperinflation and examining its mechanistic role in CAD in current and former smokers.

Published
2021

19. A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets

Author

Sanghun, Lee, Georg, Hahn, Julian, Hecker, Sharon M, Lutz, Kristina, Mullin, Winston, Hide, Lars, Bertram, Dawn L, DeMeo, Rudolph E, Tanzi, Christoph, Lange, and Dmitry, Prokopenko

Subjects
Molecular Biology, Information Systems
Abstract

Genetic similarity matrices are commonly used to assess population substructure (PS) in genetic studies. Through simulation studies and by the application to whole-genome sequencing (WGS) data, we evaluate the performance of three genetic similarity matrices: the unweighted and weighted Jaccard similarity matrices and the genetic relationship matrix. We describe different scenarios that can create numerical pitfalls and lead to incorrect conclusions in some instances. We consider scenarios in which PS is assessed based on loci that are located across the genome (‘globally’) and based on loci from a specific genomic region (‘locally’). We also compare scenarios in which PS is evaluated based on loci from different minor allele frequency bins: common (>5%), low-frequency (5–0.5%) and rare (

Published
2022

20. Multivariate GWAS of Alzheimer’s disease CSF biomarker profiles implies GRIN2D in synaptic functioning

Author

Alexander Neumann, Fahri Küçükali, Stephanie Vos, Dmitry Prokopenko, Betty Tijms, Rik Vandenberghe, and Cristina Legido-Quigley

Abstract

Genome-wide association studies (GWAS) of Alzheimer’s disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to: 1. identify common genetic variants associated with these CSF profiles; 2. assess the role of associated variants in AD pathophysiology and 3. explore potential sex differences. We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n=205 controls, n=546 mild cognitive impairment, n=222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed sex-specific effects. Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 and GRIN2D) and three were previously described (APOE, TMEM160B and CHI3L). GRIN2D was associated with synaptic functioning, whereas rs145791381 was associated with biomarker evidence of inflammation. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.

Published
2022

21. Whole‐genome sequencing reveals new Alzheimer's disease–associated rare variants in loci related to synaptic function and neuronal development

Author

Dmitry Prokopenko, Inken Wohlers, Rory Kirchner, Lars Bertram, Brad Chapman, Rudolph E. Tanzi, Christoph Lange, Sandeep Amberkar, Winston Hide, Kristina Mullin, Oliver Hofmann, and Sarah L. Morgan

Subjects
0301 basic medicine, Epidemiology, RVAS, Kinesins, Disease, Biology, Ion Channels, Article, DNA sequencing, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Gene Frequency, Developmental Neuroscience, Alzheimer Disease, family‐based association study, neuronal development, Humans, Coding region, Genetic Predisposition to Disease, Multiplex, LOAD, synaptic function, Gene, Exome, Research Articles, Genetic association, Whole genome sequencing, Genetics, Whole Genome Sequencing, Health Policy, rare variants, Membrane Proteins, Proteins, Alzheimer's disease, Minor allele frequency, Psychiatry and Mental health, 030104 developmental biology, Human genome, Neurology (clinical), Geriatrics and Gerontology, whole‐genome sequencing, Microtubule-Associated Proteins, FNBP1L, 030217 neurology & neurosurgery, Research Article, Genome-Wide Association Study
Abstract

INTRODUCTIONGenome-wide association studies have led to numerous genetic loci associated with Alzheimer’s disease (AD). Whole-genome sequencing (WGS) now permit genome-wide analyses to identify rare variants contributing to AD risk.METHODSWe performed single-variant and spatial clustering-based testing on rare variants (minor allele frequency ≤1%) in a family-based WGS-based association study of 2,247 subjects from 605 multiplex AD families, followed by replication in 1,669 unrelated individuals.RESULTSWe identified 13 new AD candidate loci that yielded consistent rare-variant signals in discovery and replication cohorts (4 from single-variant, 9 from spatial-clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, CLSTN2.DISCUSSIONDownstream analyses of these novel loci highlight synaptic function, in contrast to common AD-associated variants, which implicate innate immunity. These loci have not been previously associated with AD, emphasizing the ability of WGS to identify AD-associated rare variants, particularly outside of coding regions.

Published
2021

22. Prevalence of abnormal spirometry in individuals with a smoking history and no known obstructive lung disease

Author

Thuonghien V. Tran, Gregory L. Kinney, Alejandro Comellas, Karin F. Hoth, Arianne K. Baldomero, A. James Mamary, Jeffrey L. Curtis, Nicola Hanania, Richard Casaburi, Kendra A. Young, Victor Kim, Barry Make, Emily S. Wan, Alejandro A. Diaz, John Hokanson, James D. Crapo, Edwin K. Silverman, Surya P. Bhatt, Elizabeth Regan, Spyridon Fortis, Barry J. Make, Elizabeth A. Regan, Terri H. Beaty, Peter J. Castaldi, Michael H. Cho, Dawn L. DeMeo, Adel El Boueiz, Marilyn G. Foreman, Auyon Ghosh, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Wonji Kim, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Dmitry Prokopenko, Matthew Moll, Jarrett Morrow, Dandi Qiao, Aabida Saferali, Phuwanat Sakornsakolpat, Jeong Yun, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Erin Austin, Gregory Kinney, Jessica Bon, Susan Murray, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush BanaeiKashani, Perry G. Pernicano, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, George Washko, R. Graham Barr, John Austin, Belinda D'Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Charlene McEvoy, Joseph Tashjian, Robert Wise, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Nirupama Putcha, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Ken M. Kunisaki, Eric L. Flenaugh, Hirut Gebrekristos, Mario Ponce, Silanath Terpenning, Gloria Westney, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D'Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Douglas Conrad, Andrew Yen, Alejandro P. Comellas, John Newell, Brad Thompson, Ella Kazerooni, Wassim Labaki, Craig Galban, Dharshan Vummidi, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Divay Chandra, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, Mario E. Ruiz, and Harjinder Singh

Subjects
Pulmonary and Respiratory Medicine
Published
2023

23. Novel PKC signaling in Alzheimer’s Disease

Author

M. C. Gauron, Gema Lorden, Dmitry Prokopenko, Rudolph Tanzi, and Alexandra Newton

Subjects
Genetics, Molecular Biology, Biochemistry, Biotechnology
Published
2022

24. Genome-Wide Gene-by-Smoking Interaction Study of Chronic Obstructive Pulmonary Disease

Author

John E. Hokanson, Nick Shrine, Brian D. Hobbs, Dmitry Prokopenko, Carl A. Melbourne, Edwin K. Silverman, Sharon M. Lutz, Louise V. Wain, Martin D. Tobin, Woori Kim, Phuwanat Sakornsakolpat, Terri H. Beaty, and Michael H. Cho

Subjects
Male, Oncology, medicine.medical_specialty, MECOM, Epidemiology, Genome-wide association study, Locus (genetics), White People, Pulmonary Disease, Chronic Obstructive, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Genetic predisposition, medicine, Humans, Genetic Predisposition to Disease, Gene–environment interaction, Allele, 030304 developmental biology, Genetic association, 0303 health sciences, COPD, business.industry, Smoking, Original Contribution, Middle Aged, medicine.disease, United Kingdom, Respiratory Function Tests, 030228 respiratory system, Case-Control Studies, Female, Gene-Environment Interaction, business, Genome-Wide Association Study
Abstract

Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008–2010) and SpiroMeta Consortium (multiple countries, 1947–2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.

Published
2020

25. Machine Learning Characterization of COPD Subtypes

Author

Peter J. Castaldi, Adel Boueiz, Jeong Yun, Raul San Jose Estepar, James C. Ross, George Washko, Michael H. Cho, Craig P. Hersh, Gregory L. Kinney, Kendra A. Young, Elizabeth A. Regan, David A. Lynch, Gerald J. Criner, Jennifer G. Dy, Stephen I. Rennard, Richard Casaburi, Barry J. Make, James Crapo, Edwin K. Silverman, John E. Hokanson, James D. Crapo, Terri Beaty, Ferdouse Begum, Michael Cho, Dawn L. DeMeo, Adel R. Boueiz, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Jacqueline Hetmanski, Brian D. Hobbs, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dmitry Prokopenko, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Sungho Won, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Gregory Kinney, Surya P. Bhatt, Jessica Bon, Alejandro A. Diaz, Barry Make, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, and Farnoush Banaei-Kashani

Subjects
Pulmonary and Respiratory Medicine, Spirometry, COPD, medicine.diagnostic_test, business.industry, Context (language use), Disease, Critical Care and Intensive Care Medicine, medicine.disease, Machine learning, computer.software_genre, Subtyping, respiratory tract diseases, 03 medical and health sciences, 0302 clinical medicine, 030228 respiratory system, Genetic epidemiology, medicine, Clinical significance, 030212 general & internal medicine, Artificial intelligence, Genetic risk, Cardiology and Cardiovascular Medicine, business, computer
Abstract

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.

Published
2020

26. Identification of Novel Alzheimer’s Disease Loci Using Sex-Specific Family-Based Association Analysis of Whole-Genome Sequence Data

Author

Winston Hide, Nan M. Laird, Julian Hecker, Rudolph E. Tanzi, Rory Kirchner, Christoph Lange, Oliver Hoffman, Dawn L. DeMeo, Dmitry Prokopenko, Kristina Mullin, Lars Bertram, and Brad Chapman

Subjects
0301 basic medicine, Data Analysis, Male, Risk, Population, lcsh:Medicine, Genome-wide association study, Neuropathology, Computational biology, Disease, Biology, Genome-wide association studies, Article, 03 medical and health sciences, 0302 clinical medicine, Sex Factors, Alzheimer Disease, Databases, Genetic, Humans, Family, DNA sequencing, Allele, education, lcsh:Science, Alleles, Genetic Association Studies, Whole genome sequencing, Zinc finger, education.field_of_study, Multidisciplinary, Whole Genome Sequencing, lcsh:R, Intracellular Signaling Peptides and Proteins, Quality control, Zinc Fingers, Alzheimer's disease, Minor allele frequency, 030104 developmental biology, Genetic Loci, BTB-POZ Domain, Metalloproteases, Female, lcsh:Q, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

With the advent of whole genome-sequencing (WGS) studies, family-based designs enable sex-specific analysis approaches that can be applied to only affected individuals; tests using family-based designs are attractive because they are completely robust against the effects of population substructure. These advantages make family-based association tests (FBATs) that use siblings as well as parents especially suited for the analysis of late-onset diseases such as Alzheimer’s Disease (AD). However, the application of FBATs to assess sex-specific effects can require additional filtering steps, as sensitivity to sequencing errors is amplified in this type of analysis. Here, we illustrate the implementation of robust analysis approaches and additional filtering steps that can minimize the chances of false positive-findings due to sex-specific sequencing errors. We apply this approach to two family-based AD datasets and identify four novel loci (GRID1, RIOK3, MCPH1, ZBTB7C) showing sex-specific association with AD risk. Following stringent quality control filtering, the strongest candidate is ZBTB7C (Pinter = 1.83 × 10−7), in which the minor allele of rs1944572 confers increased risk for AD in females and protection in males. ZBTB7C encodes the Zinc Finger and BTB Domain Containing 7C, a transcriptional repressor of membrane metalloproteases (MMP). Members of this MMP family were implicated in AD neuropathology.

Published
2020

27. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author

Priyadarshini Kachroo, Julian Hecker, Bo L. Chawes, Tarunveer S. Ahluwalia, Michael H. Cho, Dandi Qiao, Rachel S. Kelly, Su H. Chu, Yamini V. Virkud, Mengna Huang, Kathleen C. Barnes, Esteban G. Burchard, Celeste Eng, Donglei Hu, Juan C. Celedón, Michelle Daya, Albert M. Levin, Hongsheng Gui, L. Keoki Williams, Erick Forno, Angel C.Y. Mak, Lydiana Avila, Manuel E. Soto-Quiros, Michelle M. Cloutier, Edna Acosta-Pérez, Glorisa Canino, Klaus Bønnelykke, Hans Bisgaard, Benjamin A. Raby, Christoph Lange, Scott T. Weiss, Jessica A. Lasky-Su, Namiko Abe, Goncalo Abecasis, Christine Albert, Nicholette (Nichole) Palmer Allred, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Terri Beaty, Diane Becker, Lewis Becker, Rebecca Beer, Ferdouse Begum, Amber Beitelshees, Emelia Benjamin, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Ingrid Borecki, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Karen Bunting, Esteban Burchard, Jonathan Cardwell, Cara Carty, Richard Casaburi, James Casella, Mark Chaffin, Christy Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sayantan Das, Sean David, Colleen Davis, Mariza de Andrade, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Ron Do, Qing Duan, Ravi Duggirala, Peter Durda, Susan Dutcher, Charles Eaton, Lynette Ekunwe, Patrick Ellinor, Leslie Emery, Charles Farber, Leanna Farnam, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Yan Gao, Margery Gass, Bruce Gelb, Xiaoqi (Priscilla) Geng, Soren Germer, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, C. Charles Gu, Yue Guan, Xiuqing Guo, Jeff Haessler, Michael Hall, Daniel Harris, Nicola Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, John Hokanson, Kramer Holly, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Min A. Jhun, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Sekar Kathiresan, Laura Kaufman, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Greg Kinney, Barbara Konkle, Charles Kooperberg, Stephanie Krauter, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Seunggeun Shawn Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Yun Li, Honghuang Lin, Keng Han Lin, Simin Liu, Yongmei Liu, Ruth Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Michael Mahaney, Barry Make, Ani Manichaikul, JoAnn Manson, Lauren Margolin, Lisa Martin, Susan Mathai, Rasika Mathias, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Hao Mei, Deborah A. Meyers, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton Mitchell, May E. Montasser, Solomon Musani, Stanford Mwasongwe, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Pradeep Natarajan, Sergei Nekhai, Deborah Nickerson, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, James Pankow, George Papanicolaou, Margaret Parker, Afshin Parsa, Sara Penchev, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Sam Phillips, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Dmitry Prokopenko, Bruce Psaty, Pankaj Qasba, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Vasan Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Elizabeth Regan, Alex Reiner, Ken Rice, Stephen Rich, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Phuwanat Sakornsakolpat, Shabnam Salimi, Steven Salzberg, Kevin Sandow, Vijay Sankaran, Christopher Scheller, Ellen Schmidt, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Vivien Sheehan, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Tamar Sofer, Nona Sotoodehnia, Adrienne Stilp, Elizabeth Streeten, Yun Ju Sung, Jessica Su-Lasky, Jody Sylvia, Adam Szpiro, Carole Sztalryd, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Lesley Tinker, David Tirschwell, Hemant Tiwari, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Emily Wan, Fei Fei Wang, Karol Watson, Daniel E. Weeks, Bruce Weir, Scott Weiss, Lu-Chen Weng, Cristen Willer, Kayleen Williams, Carla Wilson, James Wilson, Quenna Wong, Huichun Xu, Lisa Yanek, Ivana Yang, Rongze Yang, Norann Zaghloul, Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiuwen Zheng, Degui Zhi, Xiang Zhou, Michael Zody, and Sebastian Zoellner

Subjects
Adult, Costa Rica, Male, Pulmonary and Respiratory Medicine, Adolescent, Vital Capacity, Single-nucleotide polymorphism, Pedigree chart, Critical Care and Intensive Care Medicine, Young Adult, 03 medical and health sciences, FEV1/FVC ratio, 0302 clinical medicine, Polymorphism (computer science), Forced Expiratory Volume, Humans, Medicine, SNP, 030212 general & internal medicine, Child, Asthma, Whole Genome Sequencing, business.industry, Middle Aged, respiratory system, medicine.disease, respiratory tract diseases, Minor allele frequency, 030228 respiratory system, Genetic epidemiology, Child, Preschool, Interferon Regulatory Factors, Immunology, Respiratory Physiological Phenomena, Female, Cardiology and Cardiovascular Medicine, business, Cell Adhesion Molecules
Abstract

BACKGROUND: Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma. METHODS: WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician’s diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes. RESULTS: A genome-wide significant association was identified between baseline FEV(1)/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10(−8) in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10(−6)). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV(1) (P = 3.3 × 10(−3)), postbronchodilator (PB) FEV(1) (7.3 × 10(−3)), and PB FEV(1)/FVC ratio (P = 2.7 × 10(−3)). The identified baseline FEV(1)/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR. CONCLUSIONS: These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

Published
2019

28. Unsupervised genome-wide cluster analysis: nucleotide sequences of the omicron variant of SARS-CoV-2 are similar to sequences from early 2020

Author

Georg Hahn, Sanghun Lee, Dmitry Prokopenko, Tanya Novak, Julian Hecker, Surender Khurana, Lindsey R. Baden, Adrienne G. Randolph, Scott T. Weiss, and Christoph Lange

Abstract

The GISAID database contains more than 1,000,000 SARS-CoV-2 genomes, including sequences of the recently discovered SARS-CoV-2 omicron variant and of prior SARS-CoV-2 strains that have been collected from patients around the world since the beginning of the pandemic. We applied unsupervised cluster analysis to the SARS-CoV-2 genomes, assessing their similarity at a genome-wide level based on the Jaccard index and principal component analysis. Our analysis results show that the omicron variant sequences are most similar to sequences that have been submitted early in the pandemic around January 2020. Furthermore, the omicron variants in GISAID are spread across the entire range of the first principal component, suggesting that the strain has been in circulation for some time. This observation supports a long-term infection hypothesis as the omicron strain origin.

Published
2021

29. A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

Author

Julian Hecker, Dmitry Prokopenko, Matthew Moll, Sanghun Lee, Wonji Kim, Dandi Qiao, Kirsten Voorhies, Woori Kim, Stijn Vansteelandt, Brian D. Hobbs, Michael H. Cho, Edwin K. Silverman, Sharon M. Lutz, Dawn L. DeMeo, Scott T. Weiss, and Christoph Lange

Subjects
Cancer Research, Phenotype, Models, Genetic, Genetic Loci, Genetics, Humans, Gene-Environment Interaction, Computer Simulation, Molecular Biology, Polymorphism, Single Nucleotide, Genetics (clinical), Ecology, Evolution, Behavior and Systematics, Genome-Wide Association Study
Abstract

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the user’s unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

Published
2021

30. Alpha-1 Antitrypsin MZ Heterozygosity Is an Endotype of Chronic Obstructive Pulmonary Disease

Author

Auyon J. Ghosh, Brian D. Hobbs, Matthew Moll, Aabida Saferali, Adel Boueiz, Jeong H. Yun, Frank Sciurba, Lucas Barwick, Andrew H. Limper, Kevin Flaherty, Gerard Criner, Kevin K. Brown, Robert Wise, Fernando J. Martinez, David Lomas, Peter J. Castaldi, Vincent J. Carey, Dawn L. DeMeo, Michael H. Cho, Edwin K. Silverman, Craig P. Hersh, James D. Crapo, Barry J. Make, Elizabeth A. Regan, Terri H. Beaty, Adel El-Boueiz, Marilyn G. Foreman, Lystra P. Hayden, Jacqueline Hetmanski, John E. Hokanson, Wonji Kim, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Dmitry Prokopenko, Jarrett Morrow, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Erin Austin, Gregory Kinney, Kendra A. Young, Surya P. Bhatt, Jessica Bon, Alejandro A. Diaz, Barry Make, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Jeffrey L. Curtis, Perry G. Pernicano, Nicola Hanania, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, George Washko, R. Graham Barr, John Austin, Belinda D’Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Charlene McEvoy, Joseph Tashjian, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Nirupama Putcha, Richard Casaburi, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Ken M. Kunisaki, Eric L. Flenaugh, Hirut Gebrekristos, Mario Ponce, Silanath Terpenning, Gloria Westney, Richard Rosiello, David Pace, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, Victor Kim, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Douglas Conrad, Andrew Yen, Alejandro P. Comellas, Karin F. Hoth, John Newell, Brad Thompson, Ella Kazerooni, Wassim Labaki, Craig Galban, Dharshan Vummidi, Joanne Billings, Abbie Begnaud, Tadashi Allen, Divay Chandra, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, Mario E. Ruiz, and Harjinder Singh

Subjects
Male, Endotype, Respiratory System, Critical Care and Intensive Care Medicine, Medical and Health Sciences, Gastroenterology, Loss of heterozygosity, Pulmonary Disease, Chronic Obstructive, Genotype, 80 and over, 2.1 Biological and endogenous factors, Medicine, Longitudinal Studies, Aetiology, Lung, Aged, 80 and over, COPD, RNA sequencing, Middle Aged, Respiratory Function Tests, medicine.anatomical_structure, Phenotype, Meta-analysis, Respiratory, Female, alpha-1 antitrypsin, Genetic Markers, Adult, Pulmonary and Respiratory Medicine, Chronic Obstructive, Heterozygote, medicine.medical_specialty, Chronic Obstructive Pulmonary Disease, Pulmonary disease, Pulmonary Disease, Clinical Research, Internal medicine, alpha 1-Antitrypsin Deficiency, Humans, Allele, Aged, Emphysema, COPDGene Investigators, Whole Genome Sequencing, business.industry, Original Articles, medicine.disease, Survival Analysis, respiratory tract diseases, meta-analysis, alpha 1-Antitrypsin, Case-Control Studies, business
Abstract

RATIONALE: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. OBJECTIVES: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. METHODS: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. MEASUREMENTS AND MAIN RESULTS: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV(1)% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV(1) was 3.9% lower (95% confidence interval [CI], −6.55% to −1.26%) and emphysema (the percentage of lung attenuation areas

Published
2021

31. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

Author

Simon Lovestone, Lars Bertram, Pieter Jelle Visser, Dmitry Prokopenko, Isabelle Bos, Régis Bordet, Daniel Alcolea, Sebastiaan Engelborghs, Betty M. Tijms, Silvy Gabel, Charlotte E. Teunissen, Olivier Blin, Jill C. Richardson, Olena Ohlei, Henrik Zetterberg, Richard Dobson, Christina M. Lill, Christopher M. Clark, Giovanni B. Frisoni, Philip Scheltens, Rik Vandenberghe, Johannes Streffer, Valerija Dobricic, Alberto Lleó, Cristina Legido-Quigley, Andre Franke, Mara ten Kate, Gwendoline Peyratout, Christine Van Broeckhoven, Kaj Blennow, Julius Popp, Frederik Barkhof, Stephanie J.B. Vos, Mikel Tainta, Michael Wittig, Pablo Martinez-Lage, Ulf Andreasson, Shengjun Hong, Alzheimer's Disease Neuroimaging Initiative, Kristel Sleegers, Rudolph E. Tanzi, Neuroimaging Initiative, Clinical sciences, Neuroprotection & Neuromodulation, Neurology, Pathologic Biochemistry and Physiology, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Lille Neurosciences & Cognition - U 1172 (LilNCog), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Neurodegeneration, Laboratory Medicine, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Radiology and nuclear medicine

Subjects
0301 basic medicine, Male, Epidemiology, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, 3&#8208, LOCI, Genome-wide association study, Disease, Bioinformatics, Alzheimer&apos, 0302 clinical medicine, Cerebrospinal fluid, Chitinase-3-like protein 1, like protein 1, Neurofilament Proteins, neurofilament light, Medicine, Nerve Tissue Proteins/genetics, Neurogranin, Biomarker discovery, wide association study, RISK, neurogranin, Health Policy, genome&#8208, Alzheimer's disease, ATLAS, Psychiatry and Mental health, chitinase&#8208, Chitinase-3-Like Protein 1/genetics, Biomarker (medicine), biomarker, Female, Life Sciences & Biomedicine, chitinase-3-like protein 1, PROTEINS, Clinical Neurology, BETA, Nerve Tissue Proteins, cerebrospinal fluid, s disease, 03 medical and health sciences, Cellular and Molecular Neuroscience, Developmental Neuroscience, Neurofilament Proteins/genetics, Alzheimer Disease, Neurogranin/cerebrospinal fluid, Humans, Biomarkers/cerebrospinal fluid, Membrane Proteins/genetics, GENOME-WIDE ASSOCIATION, Genetic association, Aged, Alzheimer Disease/genetics, Science & Technology, business.industry, Membrane Proteins, Genetic architecture, 030104 developmental biology, Neurology (clinical), Human medicine, Neurosciences & Neurology, Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Biomarkers, Genome-Wide Association Study
Abstract

INTRODUCTION: Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. METHODS: We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates. RESULTS: We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1. DISCUSSION: Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD. ispartof: ALZHEIMERS & DEMENTIA vol:17 issue:10 pages:1628-1640 ispartof: location:United States status: published

Published
2021

32. Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2

Author

Dmitry, Prokopenko, Sanghun, Lee, Julian, Hecker, Kristina, Mullin, Sarah, Morgan, Yuriko, Katsumata, Michael W, Weiner, David W, Fardo, Nan, Laird, Lars, Bertram, Winston, Hide, Christoph, Lange, and Rudolph E, Tanzi

Subjects
Whole Genome Sequencing, Alzheimer Disease, Tumor Suppressor Proteins, Dystrophin-Associated Proteins, Neuropeptides, Humans, Dithionitrobenzoic Acid, Genetic Predisposition to Disease, Genomics, Guanylate Kinases, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract

Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values10

Published
2021

33. Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer’s disease-associated genes: DTNB and DLG2

Author

Weiner Mw, Rudolph E. Tanzi, Lars Bertram, Sanghun Lee, Christian E. Lange, Sarah L. Morgan, Dmitry Prokopenko, Kristina Mullin, Yuriko Katsumata, David W. Fardo, Winston Hide, Nan M. Laird, and Julian Hecker

Subjects
Genetics, Minor allele frequency, Whole genome sequencing, DTNB, Complex disease, Disease, Biology, Gene, Genetic association
Abstract

Alzheimer’s disease (AD) is a genetically complex disease for which roughly 30 genes have been identified via genome-wide association studies. We attempted to identify rare variants (minor allele frequency −6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden test and replicated in case/control samples from the ADSP study (pmeta = 4.74×10−8). SKAT analysis revealed region-based association around the discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta =1×10−6). Here, in a region-based GSAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.

Published
2021

34. Estimating the effective sample size in association studies of quantitative traits

Author

Dmitry Prokopenko, Florian Privé, Fabien Laporte, Andrey Ziyatdinov, Jihye Kim, Po-Ru Loh, Hugues Aschard, Peter Kraft, Harvard T.H. Chan School of Public Health, Massachusetts General Hospital [Boston], Aarhus University [Aarhus], Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Institut Pasteur [Paris], This work was supported by the National Institutes of Health grants R21HG007687 (National Human Genome Research Institute) and R01CA194393 (National Cancer Institute). The research was conducted using the UK Biobank Resource under application #16549., Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), and Institut Pasteur [Paris] (IP)

Subjects
AcademicSubjects/SCI01140, Multifactorial Inheritance, Linear mixed models, AcademicSubjects/SCI00010, POWER, MODELS, Genome-wide association study, Quadratic form (statistics), Quantitative trait locus, QH426-470, VARIANTS, AcademicSubjects/SCI01180, Polymorphism, Single Nucleotide, Generalized linear mixed model, 03 medical and health sciences, Effective sample size, Statistics, Genetics, LINKAGE, Humans, GWAS, 030304 developmental biology, Mathematics, Genetic association, Investigation, 0303 health sciences, [STAT.AP]Statistics [stat]/Applications [stat.AP], JOINT, 030305 genetics & heredity, Estimator, gwas, effective sample size, linear mixed models, GENOME, Phenotype, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Sample size determination, Sample Size, Linear Models, AcademicSubjects/SCI00960, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [STAT.ME]Statistics [stat]/Methodology [stat.ME], Genome-Wide Association Study
Abstract

The effective sample size (ESS) is a quantity estimated in genome-wide association studies (GWAS) with related individuals and/or linear mixed models used in analysis. ESS originally measured relative power in family-based GWAS and has recently become important for correcting GWAS summary statistics in post-GWAS analyses. However, existing ESS approaches have been overlooked and based on empirical estimation. This work presents an analytical form of ESS in mixed-model GWAS of quantitative traits, which is derived using the expectation of quadratic form and validated in extensive simulations. We illustrate the performance and relevance of our ESS estimator in common GWAS scenarios and analytically show that (i) family-based studies are consistently underpowered compared to studies of unrelated individuals of the same sample size; (ii) conditioning on polygenic genetic effect by linear mixed models boosts power; and (iii) power of detecting gene-environment interaction can be substantially gained or lost in family-based designs depending on exposure distribution. We further analyze UK Biobank dataset in two samples of 336,347 unrelated and 68,910 related individuals. Analysis in unrelated individuals reveals a high accuracy of our ESS estimator compared to the existing empirical approach; and analysis of related individuals suggests that the loss in effective sample size due to relatedness is at most 0.94x. Overall, we provide an analytical form of ESS for guiding GWAS designs and processing summary statistics in post-GWAS analyses.

Published
2021

35. Reply to Neupane et al.: Replication study of AD‐associated rare variants

Author

Dmitry, Prokopenko, Sarah L, Morgan, Christoph, Lange, Winston, Hide, Lars, Bertram, and Rudolph E, Tanzi

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022

36. Integrative Genomics Analysis Identifies ACVR1B as a Candidate Causal Gene of Emphysema Distribution

Author

Adel Boueiz, Betty Pham, Robert Chase, Andrew Lamb, Sool Lee, Zun Zar Chi Naing, Michael H. Cho, Margaret M. Parker, Phuwanat Sakornsakolpat, Craig P. Hersh, James D. Crapo, Andrew B. Stergachis, Ruth Tal-Singer, Dawn L. DeMeo, Edwin K. Silverman, Xiaobo Zhou, Peter J. Castaldi, Barry J. Make, Elizabeth A. Regan, Terri Beaty, Ferdouse Begum, Michael Cho, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Dandi Qiao, Emily S. Wan, Sungho Won, Dmitry Prokopenko, Mustafa Al Qaisi, Harvey O. Coxson, Teresa Gray, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, John D. Newell, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Douglas Stinson, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, George Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Camille Moore, Matt Strand, John Hughes, Gregory Kinney, Katherine Pratte, Kendra A. Young, Surya Bhatt, Jessica Bon, Barry Make, Carlos Martinez, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Y. Ivanov, K. Kostov, J. Bourbeau, M. Fitzgerald, P. Hernandez, K. Killian, R. Levy, F. Maltais, D. O’Donnell, J. Krepelka, J. Vestbo, E. Wouters, D. Quinn, P. Bakke, M. Kosnik, A. Agusti, J. Sauleda, Y. Feschenko, V. Gavrisyuk, L. Yashina, N. Monogarova, P. Calverley, D. Lomas, W. MacNee, D. Singh, J. Wedzicha, A. Anzueto, S. Braman, R. Casaburi, B. Celli, G. Giessel, M. Gotfried, G. Greenwald, Rancho Mirage, N. Hanania, D. Mahler, B. Make, S. Rennard, C. Rochester, P. Scanlon, D. Schuller, F. Sciurba, A. Sharafkhaneh, T. Siler, E. Silverman, A. Wanner, R. Wise, R. ZuWallack, H. Coxson, C. Crim, L. Edwards, R. Tal-Singer, J. Yates, B. Miller, Per Bakke, Amund Gulsvik, RS: NUTRIM - R3 - Respiratory & Age-related Health, Pulmonologie, and MUMC+: MA Longziekten (3)

Subjects
EXPRESSION, 0301 basic medicine, Pulmonary and Respiratory Medicine, Quantitative Trait Loci, Clinical Biochemistry, Genome-wide association study, Computational biology, Biology, Polymorphism, Single Nucleotide, Proof of Concept Study, OBSTRUCTIVE PULMONARY-DISEASE, chronic obstructive pulmonary disease, Transforming Growth Factor beta1, Jurkat Cells, Pulmonary Disease, Chronic Obstructive, integrative genomics, 03 medical and health sciences, 0302 clinical medicine, T-Lymphocyte Subsets, Cell Line, Tumor, Humans, WIDE ASSOCIATION, GWAS, Distribution (pharmacology), Genetic Predisposition to Disease, LUNG-VOLUME-REDUCTION, Lung, Molecular Biology, Gene, ACVR1B, Original Research, ACVR1B gene, Genetic association, Emphysema, emphysema distribution, LANDSCAPE, transforming growth factor-beta signaling, Editorials, DNA, Genomics, Cell Biology, Integrative genomics, Causal gene, ACVR1B Gene, 030104 developmental biology, Pulmonary Emphysema, 030228 respiratory system, Activin Receptors, Type I, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWAS) have identified multiple associations with emphysema apicobasal distribution (EABD), but the biological functions of these variants are unknown. To characterize the functions of EABD-associated variants, we integrated GWAS results with 1) expression quantitative trait loci (eQTL) from the Genotype Tissue Expression (GTEx) project and subjects in the COPDGene (Genetic Epidemiology of COPD) study and 2) cell type epigenomic marks from the Roadmap Epigenomics project. On the basis of these analyses, we selected a variant near ACVR1B (activin A receptor type 1B) for functional validation. SNPs from 168 loci with P values less than 5 × 10(−5) in the largest GWAS meta-analysis of EABD were analyzed. Eighty-four loci overlapped eQTL, with 12 of these loci showing greater than 80% likelihood of harboring a single, shared GWAS and eQTL causal variant. Seventeen cell types were enriched for overlap between EABD loci and Roadmap Epigenomics marks (permutation P

Published
2019

37. New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

Author

Phuwanat Sakornsakolpat, James F. Wilson, María Soler Artigas, Beate Stubbe, Nicholas J. Wareham, James D. Crapo, Victoria E. Jackson, Eleftheria Zeggini, Olga G. Troyanskaya, Medea Imboden, A. Mesut Erzurumluoglu, Adam S. Butterworth, Carl A. Melbourne, Ian Sayers, Lars Lind, Stefan Weiss, Margaret M. Parker, Timmers Prhj, Edwin K. Silverman, John C. Whittaker, Ian P. Hall, Ozren Polasek, Mika Kähönen, Katherine A. Fawcett, Anna Hansell, Liming Li, David J. Porteous, Louise V. Wain, Robert A. Scott, Richard Packer, Richard J. Allen, Robin G Walters, Anna L. Guyatt, Terho Lehtimäki, Nicole Probst-Hensch, Shona M. Kerr, Christian Gieger, Matthias Wielscher, Rajesh Rawal, Jing Hua Zhao, John E. Hokanson, Holger Schulz, Nicola F. Reeve, Claudia Langenberg, Ke Hao, Corry-Anke Brandsma, Megan L. Paynton, Vitart, Dmitry Prokopenko, Jennie Hui, Eugene R. Bleecker, Ma'en Obeidat, John Danesh, Ralf Ewert, Benjamin B. Sun, Frank Dudbridge, Jian Zhou, Brian D. Hobbs, Blair H. Smith, Don D. Sin, Dawn L. DeMeo, Joseph C. Maranville, Ida Surakka, Alison Catherine Murray, Nicholas Locantore, Katherine A. Kentistou, Terri H. Beaty, Igor Rudan, Kuang Lin, Amund Gulsvik, Ian J. Deary, Ruth Tal-Singer, Kijoung Song, David C. Nickle, Michael H. Cho, Jian'an Luan, Joshua D. Hoffman, Georg Homuth, Zhengming Chen, Dandi Qiao, Heiko Runz, Per Bakke, Chiara Batini, Caroline Hayward, Stefan Karrasch, Alan James, Andrew P. Morris, Prescott G. Woodruff, Laura M Yerges Armstrong, David Sparrow, Ulf Gyllensten, James P. Cook, Jonathan Marten, Olli T. Raitakari, Nick Shrine, Deborah A. Meyers, Tobin, Ruth Boxall, Marjo-Riitta Järvelin, David P. Strachan, Sarah E. Harris, Philippe Joubert, Stefan Enroth, Xingnan Li, van den Berge M, Anubha Mahajan, Yohan Bossé, Peter K. Joshi, Shrine, Nick [0000-0003-3641-4371], Guyatt, Anna L [0000-0003-1860-6337], Hobbs, Brian D [0000-0001-9564-0745], Sakornsakolpat, Phuwanat [0000-0002-4308-0974], Obeidat, Ma'en [0000-0002-5443-2752], Weiss, Stefan [0000-0002-3553-4315], Kentistou, Katherine A [0000-0002-5816-664X], Sun, Benjamin B [0000-0001-6347-2281], Enroth, Stefan [0000-0002-5056-9137], Vitart, Veronique [0000-0002-4991-3797], Allen, Richard J [0000-0002-8450-3056], Beaty, Terri H [0000-0002-7644-1705], Bossé, Yohan [0000-0002-3067-3711], Joshi, Peter K [0000-0002-6361-5059], Mahajan, Anubha [0000-0001-5585-3420], Murray, Alison [0000-0003-4915-4847], Porteous, David J [0000-0003-1249-6106], Sayers, Ian [0000-0001-5601-5410], Smith, Blair H [0000-0002-5362-9430], Tal-Singer, Ruth [0000-0002-5275-8062], Timmers, Paul RHJ [0000-0002-5197-1267], Troyanskaya, Olga G [0000-0002-5676-5737], Rudan, Igor [0000-0001-6993-6884], Wilson, James F [0000-0001-5751-9178], Zeggini, Eleftheria [0000-0003-4238-659X], Hayward, Caroline [0000-0002-9405-9550], Morris, Andrew P [0000-0002-6805-6014], Butterworth, Adam S [0000-0002-6915-9015], Walters, Robin G [0000-0002-9179-0321], Cho, Michael H [0000-0002-4907-1657], Strachan, David P [0000-0001-7854-1366], Tobin, Martin D [0000-0002-3596-7874], Wain, Louise V [0000-0003-4951-1867], Apollo - University of Cambridge Repository, Institute for Molecular Medicine Finland, Groningen Research Institute for Asthma and COPD (GRIAC), UNIVERSITY OF OULU, and Commission of the European Communities

Subjects
Male, Smoking/genetics, LOCI, Genome-wide association study, VARIANTS, Bioinformatics, Genome-wide association studies, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Polymorphism (computer science), Risk Factors, GWAS, GENOME-WIDE ASSOCIATION, HERITABILITY, COPD, Lung, 11 Medical and Health Sciences, Genetics & Heredity, Aged, 80 and over, 0303 health sciences, Genetic Predisposition to Disease/genetics, Smoking, 1184 Genetics, developmental biology, physiology, Middle Aged, Polymorphism, Single Nucleotide/genetics, 3. Good health, medicine.anatomical_structure, Meta-analysis, Genome-Wide Association Study/methods, Medical genetics, Female, Life Sciences & Biomedicine, medicine.medical_specialty, Understanding Society Scientific Group, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Genetics, medicine, Humans, Genetic Predisposition to Disease, 030304 developmental biology, Genetic association, Aged, Respiratory tract diseases, Science & Technology, Case-control study, Lung/physiopathology, 06 Biological Sciences, medicine.disease, Pulmonary Disease, Chronic Obstructive/genetics, respiratory tract diseases, Case-Control Studies, 3111 Biomedicine, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study
Abstract

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent patient populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never-smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD., Editorial summary: A genome-wide association study in over 400,000 individuals identifies 139 new signals for lung function. These variants can predict chronic obstructive pulmonary disease in independent, trans-ethnic cohorts.

Published
2019

38. Zinc finger protein 33B demonstrates sex interaction with atopy-related markers in childhood asthma

Author

Sanghun Lee, Dmitry Prokopenko, Rachel S. Kelly, Sharon Lutz, Jessica Ann Lasky-Su, Michael H. Cho, Cecelia Laurie, Juan C. Celedón, Christoph Lange, Scott T. Weiss, Julian Hecker, and Dawn L. DeMeo

Subjects
Pulmonary and Respiratory Medicine
Abstract

BackgroundSex differences related to immune responses can influence atopic manifestations in childhood asthma. While genome-wide association studies have investigated a sex-specific genetic architecture of the immune response, gene-by-sex interactions have not been extensively analysed for atopy-related markers including allergy skin tests, IgE and eosinophils in asthmatic children.MethodsWe performed a genome-wide gene-by-sex interaction analysis for atopy-related markers using whole-genome sequencing data based on 889 trios from the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) and 284 trios from the Childhood Asthma Management Program (CAMP). We also tested the findings in UK Biobank participants with self-reported childhood asthma. Furthermore, downstream analyses in GACRS integrated gene expression to disentangle observed associations.ResultsSingle nucleotide polymorphism (SNP) rs1255383 at 10q11.21 demonstrated a genome-wide significant gene-by-sex interaction (pinteraction=9.08×10−10) for atopy (positive skin test) with opposite direction of effects between females and males. In the UK Biobank participants with a history of childhood asthma, the signal was consistently observed with the same sex-specific effect directions for high eosinophil count (pinteraction=0.0058). Gene expression ofZNF33B(zinc finger protein 33B), located at 10q11.21, was moderately associated with atopy in girls, but not in boys.ConclusionsWe report SNPs in/near a zinc finger gene as novel sex-differential loci for atopy-related markers with opposite effect directions in females and males. A potential role forZNF33Bshould be studied further as an important driver of sex-divergent features of atopy in childhood asthma.

Published
2022

39. Longitudinal Phenotypes and Mortality in Preserved Ratio Impaired Spirometry in the COPDGene Study

Author

Emily S. Wan, Spyridon Fortis, Elizabeth A. Regan, John Hokanson, MeiLan K. Han, Richard Casaburi, Barry J. Make, James D. Crapo, Dawn L. DeMeo, Edwin K. Silverman, Terri Beaty, Ferdouse Begum, Peter J. Castaldi, Michael Cho, Adel R. Boueiz, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dandi Qiao, Sungho Won, Phuwanat Sakornsakolpat, Dmitry Prokopenko, Mustafa Al Qaisi, Harvey O. Coxson, Teresa Gray, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, David A. Lynch, John D. Newell, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Douglas Stinson, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bram van Ginneken, Eva van Rikxoort, George Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Camille Moore, Matt Strand, John Hughes, Gregory Kinney, Katherine Pratte, Kendra A. Young, Surya Bhatt, Jessica Bon, Barry Make, Carlos Martinez, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Jeffrey L. Curtis, Carlos H. Martinez, Perry G. Pernicano, Nicola Hanania, Philip Alapat, Mustafa Atik, Venkata Bandi, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Arun Nachiappan, Amit Parulekar, Craig Hersh, R. Graham Barr, John Austin, Belinda D’Souza, Gregory D. N. Pearson, Anna Rozenshtein, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Charlene McEvoy, Joseph Tashjian, Robert Wise, Robert Brown, Nadia N. Hansel, Karen Horton, Allison Lambert, Nirupama Putcha, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, Eugene Berkowitz, Gloria Westney, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, Victor Kim, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Joe Ramsdell, Paul Friedman, Andrew Yen, Alejandro P. Comellas, Karin F. Hoth, John Newell, Brad Thompson, Ella Kazerooni, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Divay Chandra, Carl Fuhrman, Joel Weissfeld, Antonio Anzueto, Sandra Adams, Diego Maselli-Caceres, and Mario E. Ruiz

Subjects
Pulmonary and Respiratory Medicine, Spirometry, medicine.medical_specialty, medicine.diagnostic_test, business.industry, Follow up studies, Critical Care and Intensive Care Medicine, 03 medical and health sciences, 0302 clinical medicine, 030228 respiratory system, Internal medicine, Cardiology, medicine, 030212 general & internal medicine, Prism, business
Abstract

Rationale: Increasing awareness of the prevalence and significance of Preserved Ratio Impaired Spirometry (PRISm), alternatively known as restrictive or Global Initiative for Chronic Obstructive Lu...

Published
2018

40. An APP ectodomain mutation outside of the Aβ domain promotes Aβ production in vitro and deposition in vivo

Author

Ian Q. Weigle, Weinong Han, Manish Aryal, Rudolph E. Tanzi, Dmitry Prokopenko, Sangram S. Sisodia, Xulun Zhang, Sherri Y Zhen, Can Martin Zhang, and Yingxia Liang

Subjects
0301 basic medicine, Genetically modified mouse, Immunology, Mice, Transgenic, medicine.disease_cause, Article, Mice, 03 medical and health sciences, Exon, 0302 clinical medicine, Alzheimer Disease, Amyloid precursor protein, medicine, Animals, Immunology and Allergy, Mutation, Amyloid beta-Peptides, biology, Chemistry, Endoplasmic reticulum, Brain, Exons, Transfection, In vitro, Cell biology, 030104 developmental biology, Ectodomain, biology.protein, 030217 neurology & neurosurgery, Neuroscience
Abstract

The study demonstrates that the S198P mutation in APP promotes accelerated folding and egress to late compartments leading to enhanced Aβ production and deposition in vivo., Familial Alzheimer’s disease (FAD)–linked mutations in the APP gene occur either within the Aβ-coding region or immediately proximal and are located in exons 16 and 17, which encode Aβ peptides. We have identified an extremely rare, partially penetrant, single nucleotide variant (SNV), rs145081708, in APP that corresponds to a Ser198Pro substitution in exon 5. We now report that in stably transfected cells, expression of APP harboring the S198P mutation (APPS198P) leads to elevated production of Aβ peptides by an unconventional mechanism in which the folding and exit of APPS198P from the endoplasmic reticulum is accelerated. More importantly, coexpression of APP S198P and the FAD-linked PS1ΔE9 variant in the brains of male and female transgenic mice leads to elevated steady-state Aβ peptide levels and acceleration of Aβ deposition compared with age- and gender-matched mice expressing APP and PS1ΔE9. This is the first AD-linked mutation in APP present outside of exons 16 and 17 that enhances Aβ production and deposition.

Published
2021

41. A smoothed version of the Lassosum penalty for fitting integrated risk models

Author

Christoph Lange, Dmitry Prokopenko, Georg Hahn, Kristina Mullin, Sharon M. Lutz, and Rudolph E. Tanzi

Subjects
Computer science, Covariate, Statistics, Pulmonary disease, Polygenic risk score, Metric (unit), Area under the roc curve, Smoothing, Odds
Abstract

Polygenic risk scores are a popular means to predict the disease risk or disease susceptibility of an individual based on its genotype information. When adding other important epidemiological covariates such as age or sex, we speak of an integrated risk model. Methodological advances for fitting more accurate integrated risk models are of immediate importance to improve the precision of risk prediction, thereby potentially identifying patients at high risk early on when they are still able to benefit from preventive steps/interventions targeted at increasing their odds of survival, or at reducing their chance of getting a disease in the first place. This article proposes a smoothed version of the “Lassosum” penalty used to fit polygenic risk scores and integrated risk models. The smoothing allows one to obtain explicit gradients everywhere for efficient minimization of the Lassosum objective function while guaranteeing bounds on the accuracy of the fit. An experimental section on both Alzheimer’s disease and COPD (chronic obstructive pulmonary disease) demonstrates the increased accuracy of the proposed smoothed Lassosum penalty compared to the original Lassosum algorithm, allowing it to draw equal with state-of-the-art methodology such as LDpred2 when evaluated via the AUC (area under the ROC curve) metric.

Published
2021

42. Emphysema Progression and Lung Function Decline Among Angiotensin Converting Enzyme Inhibitors and Angiotensin-Receptor Blockade Users in the COPDGene Cohort

Author

Vickram Tejwani, Ashraf Fawzy, Nirupama Putcha, Peter J. Castaldi, Michael H. Cho, Katherine A. Pratte, Surya P. Bhatt, David A. Lynch, Stephen M. Humphries, Gregory L. Kinney, Franco R. D’Alessio, Nadia N. Hansel, James D. Crapo, Edwin K. Silverman, Barry J. Make, Elizabeth A. Regan, Terri Beaty, Ferdouse Begum, Michael Cho, Dawn L. DeMeo, Adel R. Boueiz, Marilyn G. Foreman, Eitan Halper-Stromberg, Lystra P. Hayden, Craig P. Hersh, Jacqueline Hetmanski, Brian D. Hobbs, John E. Hokanson, Nan Laird, Christoph Lange, Sharon M. Lutz, Merry-Lynn McDonald, Margaret M. Parker, Dmitry Prokopenko, Dandi Qiao, Phuwanat Sakornsakolpat, Emily S. Wan, Sungho Won, Juan Pablo Centeno, Jean-Paul Charbonnier, Harvey O. Coxson, Craig J. Galban, MeiLan K. Han, Eric A. Hoffman, Stephen Humphries, Francine L. Jacobson, Philip F. Judy, Ella A. Kazerooni, Alex Kluiber, Pietro Nardelli, John D. Newell, Aleena Notary, Andrea Oh, James C. Ross, Raul San Jose Estepar, Joyce Schroeder, Jered Sieren, Berend C. Stoel, Juerg Tschirren, Edwin Van Beek, Bramvan Ginneken, Eva van Rikxoort, Gonzalo Vegas Sanchez-Ferrero, Lucas Veitel, George R. Washko, Carla G. Wilson, Robert Jensen, Douglas Everett, Jim Crooks, Katherine Pratte, Matt Strand, Gregory Kinney, Kendra A. Young, Jessica Bon, Alejandro A. Diaz, Barry Make, Susan Murray, Elizabeth Regan, Xavier Soler, Russell P. Bowler, Katerina Kechris, Farnoush Banaei-Kashani, Jeffrey L. Curtis, Perry G. Pernicano, Nicola Hanania, Mustafa Atik, Aladin Boriek, Kalpatha Guntupalli, Elizabeth Guy, Amit Parulekar, Craig Hersh, George Washko, R. Graham Barr, John Austin, Belinda D’Souza, Byron Thomashow, Neil MacIntyre, H. Page McAdams, Lacey Washington, Eric Flenaugh, Silanth Terpenning, Charlene McEvoy, Joseph Tashjian, Robert Wise, Robert Brown, Karen Horton, Allison Lambert, Richard Casaburi, Alessandra Adami, Matthew Budoff, Hans Fischer, Janos Porszasz, Harry Rossiter, William Stringer, Amir Sharafkhaneh, Charlie Lan, Christine Wendt, Brian Bell, KenM. Kunisaki, Russell Bowler, Richard Rosiello, David Pace, Gerard Criner, David Ciccolella, Francis Cordova, Chandra Dass, Gilbert D’Alonzo, Parag Desai, Michael Jacobs, Steven Kelsen, Victor Kim, A. James Mamary, Nathaniel Marchetti, Aditi Satti, Kartik Shenoy, Robert M. Steiner, Alex Swift, Irene Swift, Maria Elena Vega-Sanchez, Mark Dransfield, William Bailey, Anand Iyer, Hrudaya Nath, J. Michael Wells, Douglas Conrad, Andrew Yen, Alejandro P. Comellas, Karin F. Hoth, John Newell, Brad Thompson, Ella Kazerooni, Wassim Labaki, Craig Galban, Dharshan Vummidi, Joanne Billings, Abbie Begnaud, Tadashi Allen, Frank Sciurba, Divay Chandra, Carl Fuhrman, and Joel Weissfeld

Subjects
Pulmonary and Respiratory Medicine, Male, Angiotensin receptor, medicine.medical_specialty, Population, Vital Capacity, Angiotensin-Converting Enzyme Inhibitors, Walk Test, Critical Care and Intensive Care Medicine, Cohort Studies, 03 medical and health sciences, Angiotensin Receptor Antagonists, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Internal medicine, Forced Expiratory Volume, Medicine, Humans, cardiovascular diseases, 030212 general & internal medicine, Prospective Studies, education, Aged, COPD, education.field_of_study, Lung, biology, business.industry, Angiotensin-converting enzyme, respiratory system, Middle Aged, Protective Factors, medicine.disease, Angiotensin II, respiratory tract diseases, medicine.anatomical_structure, 030228 respiratory system, Genetic epidemiology, Pulmonary Emphysema, Spirometry, Cohort, biology.protein, Cardiology, Disease Progression, Female, Cardiology and Cardiovascular Medicine, business, Lung Volume Measurements, Tomography, X-Ray Computed
Abstract

Background Attenuation of transforming growth factor β by blocking angiotensin II has been shown to reduce emphysema in a murine model. General population studies have demonstrated that the use of angiotensin converting enzyme inhibitors (ACEis) and angiotensin-receptor blockers (ARBs) is associated with reduction of emphysema progression in former smokers and that the use of ACEis is associated with reduction of FEV1 progression in current smokers. Research Question Is use of ACEi and ARB associated with less progression of emphysema and FEV1 decline among individuals with COPD or baseline emphysema? Methods Former and current smokers from the Genetic Epidemiology of COPD Study who attended baseline and 5-year follow-up visits, did not change smoking status, and underwent chest CT imaging were included. Adjusted linear mixed models were used to evaluate progression of adjusted lung density (ALD), percent emphysema (%total lung volume Results Over 5 years of follow-up, compared with nonusers, ACEi and ARB users with COPD showed slower ALD progression (adjusted mean difference [aMD], 1.6; 95% CI, 0.34-2.9). Slowed lung function decline was not observed based on phase 1 medication (aMD of FEV1 % predicted, 0.83; 95% CI, –0.62 to 2.3), but was when analysis was limited to consistent ACEi and ARB users (aMD of FEV1 % predicted, 1.9; 95% CI, 0.14-3.6). No effect modification by smoking status was found for radiographic outcomes, and the lung function effect was more pronounced in former smokers. Results were similar among participants with baseline emphysema. Interpretation Among participants with spirometry-confirmed COPD or baseline emphysema, ACEi and ARB use was associated with slower progression of emphysema and lung function decline. Trial Registry ClinicalTrials.gov ; No.: NCT00608764; URL: www.clinicaltrials.gov

Published
2020

43. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Author

Pablo Martinez-Lage, Ulf Andreasson, Richard Dobson, Ellis Niemantsverdriet, Fabian Kilpert, Mikel Tainta, Michael Wittig, Mara ten Kate, Simon Lovestone, Lars Bertram, Henrik Zetterberg, Stephanie J.B. Vos, Dmitry Prokopenko, Frederik Barkhof, Jolien Schaeverbeke, Philip Scheltens, Shengjun Hong, Jill C. Richardson, Olivier Blin, Valerija Dobricic, Pieter Jelle Visser, Silvy Gabel, Cristina Legido-Quigley, Giovanni B. Frisoni, Johannes Streffer, Isabel Sala, Sebastiaan Engelborghs, José Luis Molinuevo, Andre Franke, Alberto Lleó, Isabelle Bos, Rudolph E. Tanzi, Lorena Rami, Kristel Sleegers, Betty M. Tijms, Régis Bordet, Charlotte E. Teunissen, Petronella Kettunen, Rik Vandenberghe, Julius Popp, Isabelle Cleynen, Gwendoline Peyratout, Kaj Blennow, Anders Wallin, Christine Van Broeckhoven, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Alzheimers Dis Neuroimaging Initia, Universität zu Lübeck = University of Lübeck [Lübeck], Massachusetts General Hospital [Boston], Maastricht University [Maastricht], Vrije Universiteit Amsterdam [Amsterdam] (VU), University of Gothenburg (GU), Sahlgrenska University Hospital [Gothenburg], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), University Hospitals Leuven [Leuven], University of Antwerp (UA), Vrije Universiteit Brussel (VUB), Université de Genève = University of Geneva (UNIGE), Istituto Centro San Giovanni di Dio Fatebenefratelli, Partenaires INRAE, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), GlaxoSmithKline [Stevenage, UK] (GSK), GlaxoSmithKline [Headquarters, London, UK] (GSK), CHU Lille, Université de Lille, Clinic Barcelona Hospital Universitari, University of Oxford, Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III [Madrid] (ISC), Geneva University Hospital (HUG), Lausanne University Hospital, Center for Research and Advanced Therapies CITA-Alzheimer Foundation [San Sebastián], King‘s College London, University College of London [London] (UCL), Steno Diabetes Center, VIB [Belgium], Amsterdam UMC - Amsterdam University Medical Center, UCL Institute of Neurology, Queen Square [London], UK Dementia Research Institute (UK DRI), UCB BioPharma [Braine l’Alleud, Belgium], Christian-Albrechts University of Kiel, University of Oslo (UiO), Alzheimer's Disease Neuroimaging Initiative (ADNI), Amsterdam Neuroscience - Neurodegeneration, Neurology, Laboratory Medicine, Radiology and nuclear medicine, Clinical sciences, Neuroprotection & Neuromodulation, and Pathologic Biochemistry and Physiology

Subjects
0301 basic medicine, Male, Genome-wide association study, 0302 clinical medicine, RISK VARIANTS, Biomarker discovery, MIF-AD Multimodal Biomarker Discovery dataset, Psychiatry, Alzheimer's disease, Psychiatry and Mental health, Female, Life Sciences & Biomedicine, SUSCEPTIBILITY LOCI, Neuroscience(all), Single-nucleotide polymorphism, Genomics, tau Proteins, Computational biology, Biology, Molecular neuroscience, elderly, Article, lcsh:RC321-571, 03 medical and health sciences, Cellular and Molecular Neuroscience, Alzheimer Disease, medicine, Dementia, SNP, Humans, CSF biomarkers, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, Aged, Amyloid beta-Peptides, Science & Technology, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, Neurodegenerative disorder, medicine.disease, Personalized medicine, Genetic architecture, Peptide Fragments, 030104 developmental biology, Human medicine, TAU, business, 030217 neurology & neurosurgery, Biomarkers, dementia, Genome-Wide Association Study
Abstract

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case–control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case–control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

Published
2020

44. Gga3 deletion and a GGA3 rare variant associated with late onset Alzheimer’s disease trigger BACE1 accumulation in axonal swellings

Author

WonHee Kim, Selene Lomoio, Edward K. Robinson, Giuseppina Tesco, Matthew E. Kennedy, Kevin Z. Ho, Rudolph E. Tanzi, Rachel Willen, and Dmitry Prokopenko

Subjects
Signal transducing adaptor protein, General Medicine, Disease, Biology, In vitro, Article, Cell biology, Pathogenesis, nervous system, In vivo, mental disorders, Axoplasmic transport, Extracellular, Loss function
Abstract

Axonal dystrophy, indicative of perturbed axonal transport, occurs early during Alzheimer’s disease (AD) pathogenesis. Little is known about the mechanisms underlying this initial sign of the pathology. This study proves that Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3) loss of function due to Gga3 genetic deletion or a GGA3 rare variant that co-segregates with late-onset AD (LOAD), disrupt the axonal trafficking of the β-site APP-cleaving enzyme 1 (BACE1) resulting in its accumulation in axonal swellings in cultured neurons and in vivo. We show that BACE pharmacological inhibition ameliorates BACE1 axonal trafficking and diminishes axonal dystrophies in Gga3 null neurons in vitro and in vivo. These data indicate that axonal accumulation of BACE1 engendered by GGA3 loss of function results in local toxicity leading to axonopathy. Gga3 deletion exacerbates axonal dystrophies in a mouse model of AD prior to amyloid-beta (Aβ) deposition. Our study strongly supports a role for GGA3 in AD pathogenesis, where GGA3 loss of function triggers BACE1 axonal accumulation independently of extracellular Aβ, and initiates a cascade of events leading to the axonal damage distinctive of the early stage of AD.

Published
2020

45. Aβ-accelerated neurodegeneration caused by Alzheimer’s-associated ACE variant R1279Q is rescued by angiotensin system inhibition in mice

Author

Rory Kirchner, Rudolph E. Tanzi, Eric P. Cunningham, Ross Brimberry, Robert Vassar, Taleen Hanania, Peter I. Song, Leah K. Cuddy, Winston Hide, Daniele Procissi, Steven C. Leiser, Brad Chapman, Oliver Hofmann, and Dmitry Prokopenko

Subjects
0301 basic medicine, medicine.medical_specialty, Microglia, business.industry, Neurodegeneration, General Medicine, Hippocampal formation, medicine.disease, Angiotensin II, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Endocrinology, medicine.anatomical_structure, Internal medicine, Renin–angiotensin system, medicine, Alzheimer's disease, business, Receptor, 030217 neurology & neurosurgery, Neuroinflammation
Abstract

Recent genome-wide association studies identified the angiotensin-converting enzyme gene (ACE) as an Alzheimer's disease (AD) risk locus. However, the pathogenic mechanism by which ACE causes AD is unknown. Using whole-genome sequencing, we identified rare ACE coding variants in AD families and investigated one, ACE1 R1279Q, in knockin (KI) mice. Similar to AD, ACE1 was increased in neurons, but not microglia or astrocytes, of KI brains, which became elevated further with age. Angiotensin II (angII) and angII receptor AT1R signaling were also increased in KI brains. Autosomal dominant neurodegeneration and neuroinflammation occurred with aging in KI hippocampus, which were absent in the cortex and cerebellum. Female KI mice exhibited greater hippocampal electroencephalograph disruption and memory impairment compared to males. ACE variant effects were more pronounced in female KI mice, suggesting a mechanism for higher AD risk in women. Hippocampal neurodegeneration was completely rescued by treatment with brain-penetrant drugs that inhibit ACE1 and AT1R. Although ACE variant-induced neurodegeneration did not depend on β-amyloid (Aβ) pathology, amyloidosis in 5XFAD mice crossed to KI mice accelerated neurodegeneration and neuroinflammation, whereas Aβ deposition was unchanged. KI mice had normal blood pressure and cerebrovascular functions. Our findings strongly suggest that increased ACE1/angII signaling causes aging-dependent, Aβ-accelerated selective hippocampal neuron vulnerability and female susceptibility, hallmarks of AD that have hitherto been enigmatic. We conclude that repurposed brain-penetrant ACE inhibitors and AT1R blockers may protect against AD.

Published
2020

46. locStra: Fast analysis of regional/global stratification in whole-genome sequencing studies

Author

Dmitry Prokopenko, Georg Hahn, Christoph Lange, Michael H. Cho, Sharon M. Lutz, Scott T. Weiss, Julian Hecker, and Edwin K. Silverman

Subjects
Jaccard index, Epidemiology, Computer science, Population, Population stratification, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Matrix (mathematics), Similarity (network science), Sliding window protocol, Humans, education, Genetics (clinical), Eigenvalues and eigenvectors, 030304 developmental biology, Sparse matrix, 0303 health sciences, education.field_of_study, Genome, Whole Genome Sequencing, 030305 genetics & heredity, Genomics, Algorithm, Algorithms, Genome-Wide Association Study
Abstract

locStra is an R -package for the analysis of regional and global population stratification in whole-genome sequencing (WGS) studies, where regional stratification refers to the substructure defined by the loci in a particular region on the genome. Population substructure can be assessed based on the genetic covariance matrix, the genomic relationship matrix, and the unweighted/weighted genetic Jaccard similarity matrix. Using a sliding window approach, the regional similarity matrices are compared with the global ones, based on user-defined window sizes and metrics, for example, the correlation between regional and global eigenvectors. An algorithm for the specification of the window size is provided. As the implementation fully exploits sparse matrix algebra and is written in C++, the analysis is highly efficient. Even on single cores, for realistic study sizes (several thousand subjects, several million rare variants per subject), the runtime for the genome-wide computation of all regional similarity matrices does typically not exceed one hour, enabling an unprecedented investigation of regional stratification across the entire genome. The package is applied to three WGS studies, illustrating the varying patterns of regional substructure across the genome and its beneficial effects on association testing.

Published
2020

47. locStra: Fast analysis of regional/global stratification in whole genome sequencing (WGS) studies

Author

Julian Hecker, Edwin K. Silverman, Scott T. Weiss, Dmitry Prokopenko, Georg Hahn, Christoph Lange, Sharon M. Lutz, and Michael H. Cho

Subjects
Whole genome sequencing, education.field_of_study, Jaccard index, Computer science, Population, Locus (genetics), computer.software_genre, Genome, Matrix (mathematics), Similarity (network science), Data mining, education, computer, Sparse matrix
Abstract

locStra is an R-package for the analysis of regional and global population stratification in whole genome sequencing studies, where regional stratification refers to the substructure defined by the loci in a particular region on the genome. Population substructure can be assessed based on the genetic covariance matrix, the genomic relationship matrix, and the unweighted/weighted genetic Jaccard similarity matrix. Using a sliding window approach, the regional similarity matrices are compared to the global ones, based on user-defined window sizes and metrics, e.g. the correlation between regional and global eigenvectors. An algorithm for the specification of the window size is provided. As the implementation fully exploits sparse matrix algebra and is written in C++, the analysis is highly efficient. Even on single cores, for realistic study sizes (several thousand subjects, several million RVs per subject), the runtime for the genome-wide computation of all regional similarity matrices does typically not exceed one hour, enabling an unprecedented investigation of regional stratification across the entire genome. The package is applied to three WGS studies, illustrating the varying patterns of regional substructure across the genome and its beneficial effects on association testing.

Published
2020
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48. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Author

Namrata Gupta, Peter Durda, Elizabeth C. Oelsner, Martha L. Daviglus, Martin D. Tobin, James G. Wilson, Liana K. Preudhomme, Laura R. Loehr, Ingo Ruczinski, Pallavi Balte, Ramachandran S. Vasan, R. Graham Barr, Phuwanat Sakornsakolpat, Stephanie J. London, Robert M. Reed, Elaine Cornell, Josée Dupuis, Dandi Qiao, Dmitry Prokopenko, Russell P. Tracy, Alanna C. Morrison, Robert C. Kaplan, Cathy C. Laurie, Sina A. Gharib, Donna M. Muzny, Kent D. Taylor, Cecelia A. Laurie, Wonji Kim, Stephen S. Rich, Brian E. Cade, Kristin M. Burkart, Tamar Sofer, George T. O'Connor, Chiara Batini, Louise V. Wain, Leslie A. Lange, Ani Manichaikul, Susan Redline, Yanlin Ma, Bruce M. Psaty, Xutong Zhao, Yongmei Liu, Chaojie Yang, Edwin K. Silverman, David J. Vandenberg, Deborah A. Nickerson, George J. Papanicolaou, Bing Yu, L. Adrienne Cupples, Kathleen C. Barnes, François Aguet, Silva Kasela, Stacey Gabriel, Kristin G. Ardlie, Xiuqing Guo, Gonçalo R. Abecasis, Shannon Dugan-Perez, Harshavardhan Doddapaneni, Jerome I. Rotter, Ginger A. Metcalf, W. Craig Johnson, Michelle Daya, Nick Shrine, Sarah A Gagliano Taliun, Traci M. Bartz, Jiwon Lee, Deepti Jain, Tuuli Lappalainen, and Michael H. Cho

Subjects
0301 basic medicine, Male, TOPMed Lung Working Group, General Physics and Astronomy, Genome-wide association study, Genome-wide association studies, Pulmonary function testing, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Polymorphism (computer science), 80 and over, 2.1 Biological and endogenous factors, DNA sequencing, Aetiology, lcsh:Science, Lung, Genetics, African Americans, Aged, 80 and over, COPD, education.field_of_study, Multidisciplinary, Chronic obstructive pulmonary disease, Intracellular Signaling Peptides and Proteins, Single Nucleotide, Middle Aged, Biobank, Protein Inhibitors of Activated STAT, 030220 oncology & carcinogenesis, Respiratory, Respiratory Physiological Phenomena, Small Ubiquitin-Related Modifier Proteins, Female, Biotechnology, Adult, Chronic Obstructive, Chronic Obstructive Pulmonary Disease, Science, Population, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, and over, Biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, Pulmonary Disease, 03 medical and health sciences, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, medicine, Humans, Genetic Predisposition to Disease, Polymorphism, education, Aged, Whole genome sequencing, Whole Genome Sequencing, Human Genome, Calcium-Binding Proteins, General Chemistry, Precision medicine, medicine.disease, respiratory tract diseases, Black or African American, 030104 developmental biology, Good Health and Well Being, Genetic Loci, Feasibility Studies, lcsh:Q, 2.4 Surveillance and distribution, Follow-Up Studies, Genome-Wide Association Study
Abstract

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry., Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.

Published
2020

49. Disease Progression Modeling in Chronic Obstructive Pulmonary Disease

Author

Barry J. Make, Venkata Bandi, Douglas Stinson, Ella A. Kazerooni, Harry B. Rossiter, Farnoush Banaei-Kashani, Xavier Soler, Arun C. Nachiappan, Paul J. Friedman, Karen M. Horton, Terri H. Beaty, Christine H. Wendt, Andrew Yen, Philip F. Judy, Ferdouse Begum, Jeffrey L. Curtis, Lystra P. Hayden, Joe W. Ramsdell, Peter J. Castaldi, Alejandro P. Comellas, Emily S. Wan, Susan Murray, Aladin M. Boriek, David Pace, Jessica Bon, Nadia N. Hansel, Chandra Dass, Marilyn G. Foreman, Neil R. MacIntyre, Kartik Shenoy, David A. Lynch, Brian D. Hobbs, Raúl San José Estépar, John D. Newell, Philip Alapat, Karin F. Hoth, Stephen M. Humphries, Robert M. Steiner, Alessandra Adami, R.P. Bowler, Parag Desai, Mustafa Al Qaisi, Anna Rozenshtein, Joel L. Weissfeld, Robert A. Wise, Nan M. Laird, Margaret M. Parker, Felix J. S. Bragman, Camille M. Moore, Abbie Begnaud, Allison A. Lambert, Elizabeth Guy, Michael R. Jacobs, Mario E. Ruiz, Dawn L. DeMeo, Sungho Won, Alex Kluiber, Amit D. Parulekar, John H. M. Austin, Nathaniel Marchetti, Dandi Qiao, Douglas Everett, Joseph H. Tashjian, Juerg Tschirren, Kendra A. Young, Adel Boueiz, James D. Crapo, Gregory L. Kinney, Richard Casaburi, Russell P. Bowler, Daniel C. Alexander, Francis Cordova, Craig P. Hersh, George R. Washko, H. Page McAdams, Amir Sharafkhaneh, A. James Mamary, J. Michael Wells, Lacey Washington, MeiLan K. Han, Mark T. Dransfield, Nirupama Putcha, Craig J. Galbán, Dmitry Prokopenko, Eric A. Hoffman, Gloria Westney, Katerina Kechris, Bojidar Rangelov, Carla Wilson, Charlene McEvoy, Divay Chandra, Edwin J R van Beek, Carlos H. Martinez, Kalpatha Guntupalli, Gregory D.N. Pearson, Diego Maselli-Caceres, James C. Ross, Katherine A. Pratte, Christoph Lange, David Ciccolella, Charlie Lan, R. Graham Barr, Phuwanat Sakornsakolpat, Aditi Satti, Irene Swift, Robert H. Brown, Hans Fischer, Victor Kim, Maria Elena Vega-Sanchez, Sandra G. Adams, Belinda D’Souza, Perry G. Pernicano, Bram van Ginneken, Hrudaya Nath, Byron Thomashow, Jim Crooks, Joanne Billings, Jered Sieren, Eitan Halper-Stromberg, Matthew J. Budoff, William C. Bailey, Eva M. van Rikxoort, Merry-Lynn McDonald, Francine L. Jacobson, Edwin K. Silverman, John E. Hokanson, Robert L. Jensen, John Hughes, Michael H. Cho, Alexandra L. Young, Steven G. Kelsen, Janos Porszasz, Jacqueline B. Hetmanski, Alex Swift, John R. Hurst, Elizabeth A. Regan, Anand S Iyer, Frank C. Sciurba, Mustafa A. Atik, Gerard J. Criner, Antonio Anzueto, Sharon M. Lutz, David J. Hawkes, Carl R. Fuhrman, William W. Stringer, Harvey O. Coxson, Berend C. Stoel, Eugene Berkowitz, Joyce D. Schroeder, Tadashi Allen, Surya P. Bhatt, Matthew Strand, Brad H. Thompson, Nicola A. Hanania, Brian Bell, Teresa Gray, Gilbert E. D'Alonzo, and Richard Rosiello

Subjects
Pulmonary and Respiratory Medicine, Male, medicine.medical_specialty, Pulmonary disease, Critical Care and Intensive Care Medicine, Machine Learning, 03 medical and health sciences, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Internal medicine, medicine, Humans, 030212 general & internal medicine, Aged, COPD, business.industry, Disease progression, Editorials, Original Articles, Middle Aged, Models, Theoretical, respiratory system, medicine.disease, respiratory tract diseases, 030228 respiratory system, Disease Progression, Bronchitis, Female, Ct imaging, business, Tomography, X-Ray Computed, Rare cancers Radboud Institute for Health Sciences [Radboudumc 9]
Abstract

Contains fulltext : 220761.pdf (Publisher’s version ) (Open Access) Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue-->Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway-->Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue-->Airway group; r = -0.14 [P = 0.011] in the Airway-->Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD."

Published
2020

50. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

Author

Mikel Tainta, Olivier Blin, Richard Dobson, Isabelle Bos, Julius Popp, Betty M. Tijms, Daniel Alcolea, Michael Wittig, Jill C. Richardson, Christopher M. Clark, Alberto Lleó, Shengjun Hong, Pieter Jelle Visser, Pablo Martinez-Lage, Ulf Andreasson, Valerija Dobricic, Sebastiaan Engelborghs, Johannes Streffer, Kristel Sleegers, Rik Vandenberghe, Andre Franke, Kaj Blennow, Cristina Legido-Quigley, Gwendoline Peyratout, Christine Van Broeckhoven, Mara ten Kate, Rudolph E. Tanzi, Giovanni B. Frisoni, Frederik Barkhof, Régis Bordet, Dmitry Prokopenko, Silvy Gabel, Charlotte E. Teunissen, Simon Lovestone, Henrik Zetterberg, Lars Bertram, Philip Scheltens, and Stephanie J. B. Vos

Subjects
Cerebrospinal fluid, Genotype, Genome-wide association study, Computational biology, Neurogranin, Biomarker discovery, Quantitative trait locus, Biology, Phenotype, Genetic architecture
Abstract

BackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimer’s disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome.MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates.FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1.InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

Published
2020

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