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14 results on '"Yajnik, Pranav"'

2. Exome sequencing of Finnish isolates enhances rare-variant association power

Author

Locke, Adam E, Steinberg, Karyn Meltz, Chiang, Charleston WK, Service, Susan K, Havulinna, Aki S, Stell, Laurel, Pirinen, Matti, Abel, Haley J, Chiang, Colby C, Fulton, Robert S, Jackson, Anne U, Kang, Chul Joo, Kanchi, Krishna L, Koboldt, Daniel C, Larson, David E, Nelson, Joanne, Nicholas, Thomas J, Pietilä, Arto, Ramensky, Vasily, Ray, Debashree, Scott, Laura J, Stringham, Heather M, Vangipurapu, Jagadish, Welch, Ryan, Yajnik, Pranav, Yin, Xianyong, Eriksson, Johan G, Ala-Korpela, Mika, Järvelin, Marjo-Riitta, Männikkö, Minna, Laivuori, Hannele, Dutcher, Susan K, Stitziel, Nathan O, Wilson, Richard K, Hall, Ira M, Sabatti, Chiara, Palotie, Aarno, Salomaa, Veikko, Laakso, Markku, Ripatti, Samuli, Boehnke, Michael, and Freimer, Nelson B

Subjects
Medical Biochemistry and Metabolomics, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Alleles, Cholesterol, HDL, Cluster Analysis, Endpoint Determination, Finland, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Geographic Mapping, Humans, Multifactorial Inheritance, Quantitative Trait Loci, Reproducibility of Results, Exome Sequencing, FinnGen Project, General Science & Technology
Abstract

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

Published
2019

3. Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci.

Author

Service, Susan K, Teslovich, Tanya M, Fuchsberger, Christian, Ramensky, Vasily, Yajnik, Pranav, Koboldt, Daniel C, Larson, David E, Zhang, Qunyuan, Lin, Ling, Welch, Ryan, Ding, Li, McLellan, Michael D, O'Laughlin, Michele, Fronick, Catrina, Fulton, Lucinda L, Magrini, Vincent, Swift, Amy, Elliott, Paul, Jarvelin, Marjo-Riitta, Kaakinen, Marika, McCarthy, Mark I, Peltonen, Leena, Pouta, Anneli, Bonnycastle, Lori L, Collins, Francis S, Narisu, Narisu, Stringham, Heather M, Tuomilehto, Jaakko, Ripatti, Samuli, Fulton, Robert S, Sabatti, Chiara, Wilson, Richard K, Boehnke, Michael, and Freimer, Nelson B

Subjects
Humans, Cholesterol, Genotype, Linkage Disequilibrium, Phenotype, Quantitative Trait Loci, Population Groups, European Continental Ancestry Group, Finland, Cholesterol, HDL, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, HDL, Genetics, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20-30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5' and 3' untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF

Published
2014

4. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Author

Mahajan, Anubha, Wessel, Jennifer, Willems, Sara M., Zhao, Wei, Robertson, Neil R., Chu, Audrey Y., Gan, Wei, Kitajima, Hidetoshi, Taliun, Daniel, Rayner, N. William, Guo, Xiuqing, Lu, Yingchang, Li, Man, Jensen, Richard A., Hu, Yao, Huo, Shaofeng, Lohman, Kurt K., Zhang, Weihua, Cook, James P., Prins, Bram Peter, Flannick, Jason, Grarup, Niels, Trubetskoy, Vassily Vladimirovich, Kravic, Jasmina, Kim, Young Jin, Rybin, Denis V., Yaghootkar, Hanieh, Müller-Nurasyid, Martina, Meidtner, Karina, Li-Gao, Ruifang, Varga, Tibor V., Marten, Jonathan, Li, Jin, Smith, Albert Vernon, An, Ping, Ligthart, Symen, Gustafsson, Stefan, Malerba, Giovanni, Demirkan, Ayse, Tajes, Juan Fernandez, Steinthorsdottir, Valgerdur, Wuttke, Matthias, Lecoeur, Cécile, Preuss, Michael, Bielak, Lawrence F., Graff, Marielisa, Highland, Heather M., Justice, Anne E., Liu, Dajiang J., Marouli, Eirini, Peloso, Gina Marie, Warren, Helen R., Afaq, Saima, Afzal, Shoaib, Ahlqvist, Emma, Almgren, Peter, Amin, Najaf, Bang, Lia B., Bertoni, Alain G., Bombieri, Cristina, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Burtt, Noël P., Canouil, Mickaël, Chen, Yii-Der Ida, Cho, Yoon Shin, Christensen, Cramer, Eastwood, Sophie V., Eckardt, Kai-Uwe, Fischer, Krista, Gambaro, Giovanni, Giedraitis, Vilmantas, Grove, Megan L., de Haan, Hugoline G., Hackinger, Sophie, Hai, Yang, Han, Sohee, Tybjærg-Hansen, Anne, Hivert, Marie-France, Isomaa, Bo, Jäger, Susanne, Jørgensen, Marit E., Jørgensen, Torben, Käräjämäki, Annemari, Kim, Bong-Jo, Kim, Sung Soo, Koistinen, Heikki A., Kovacs, Peter, Kriebel, Jennifer, Kronenberg, Florian, Läll, Kristi, Lange, Leslie A., Lee, Jung-Jin, Lehne, Benjamin, Li, Huaixing, Lin, Keng-Hung, Linneberg, Allan, Liu, Ching-Ti, Liu, Jun, Loh, Marie, Mägi, Reedik, Mamakou, Vasiliki, McKean-Cowdin, Roberta, Nadkarni, Girish, Neville, Matt, Nielsen, Sune F., Ntalla, Ioanna, Peyser, Patricia A., Rathmann, Wolfgang, Rice, Kenneth, Rich, Stephen S., Rode, Line, Rolandsson, Olov, Schönherr, Sebastian, Selvin, Elizabeth, Small, Kerrin S., Stančáková, Alena, Surendran, Praveen, Taylor, Kent D., Teslovich, Tanya M., Thorand, Barbara, Thorleifsson, Gudmar, Tin, Adrienne, Tönjes, Anke, Varbo, Anette, Witte, Daniel R., Wood, Andrew R., Yajnik, Pranav, Yao, Jie, Yengo, Loïc, Young, Robin, Amouyel, Philippe, Boeing, Heiner, Boerwinkle, Eric, Bottinger, Erwin P., Chowdhury, Rajiv, Collins, Francis S., Dedoussis, George, Dehghan, Abbas, Deloukas, Panos, Ferrario, Marco M., Ferrières, Jean, Florez, Jose C., Frossard, Philippe, Gudnason, Vilmundur, Harris, Tamara B., Heckbert, Susan R., Howson, Joanna M. M., Ingelsson, Martin, Kathiresan, Sekar, Kee, Frank, Kuusisto, Johanna, Langenberg, Claudia, Launer, Lenore J., Lindgren, Cecilia M., Männistö, Satu, Meitinger, Thomas, Melander, Olle, Mohlke, Karen L., Moitry, Marie, Morris, Andrew D., Murray, Alison D., de Mutsert, Renée, Orho-Melander, Marju, Owen, Katharine R., Perola, Markus, Peters, Annette, Province, Michael A., Rasheed, Asif, Ridker, Paul M., Rivadineira, Fernando, Rosendaal, Frits R., Rosengren, Anders H., Salomaa, Veikko, Sheu, Wayne H.-H., Sladek, Rob, Smith, Blair H., Strauch, Konstantin, Uitterlinden, André G., Varma, Rohit, Willer, Cristen J., Blüher, Matthias, Butterworth, Adam S., Chambers, John Campbell, Chasman, Daniel I., Danesh, John, van Duijn, Cornelia, Dupuis, Josée, Franco, Oscar H., Franks, Paul W., Froguel, Philippe, Grallert, Harald, Groop, Leif, Han, Bok-Ghee, Hansen, Torben, Hattersley, Andrew T., Hayward, Caroline, Ingelsson, Erik, Kardia, Sharon L. R., Karpe, Fredrik, Kooner, Jaspal Singh, Köttgen, Anna, Kuulasmaa, Kari, Laakso, Markku, Lin, Xu, Lind, Lars, Liu, Yongmei, Loos, Ruth J. F., Marchini, Jonathan, Metspalu, Andres, Mook-Kanamori, Dennis, Nordestgaard, Børge G., Palmer, Colin N. A., Pankow, James S., Pedersen, Oluf, Psaty, Bruce M., Rauramaa, Rainer, Sattar, Naveed, Schulze, Matthias B., Soranzo, Nicole, Spector, Timothy D., Stefansson, Kari, Stumvoll, Michael, Thorsteinsdottir, Unnur, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Wareham, Nicholas J., Wilson, James G., Zeggini, Eleftheria, Scott, Robert A., Barroso, Inês, Frayling, Timothy M., Goodarzi, Mark O., Meigs, James B., Boehnke, Michael, Saleheen, Danish, Morris, Andrew P., Rotter, Jerome I., and McCarthy, Mark I.

Published
2018
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6. Twins in Guinea-Bissau have a ‘thin-fat’ body composition compared to singletons

Author

Wagh, Rucha, primary, Bjerregaard-Andersen, Morten, additional, Bandyopadhyay, Souvik, additional, Yajnik, Pranav, additional, Prasad, Rashmi B., additional, Otiv, Suhas, additional, Byberg, Stine, additional, Hennild, Ditte Egegaard, additional, Gomes, Gabriel Marciano, additional, Christensen, Kaare, additional, Sodemann, Morten, additional, Jensen, Dorte Møller, additional, and Yajnik, Chittaranjan S., additional

Published
2022
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8. Twins in Guinea-Bissau have a ‘thin-fat’ body composition compared to singletons

Author

Wagh, Rucha, primary, Bjerregaard-Andersen, Morten, additional, Bandyopadhyay, Souvik, additional, Yajnik, Pranav, additional, Prasad, Rashmi B, additional, Byberg, Stine, additional, Hennild, Ditte Egegaard, additional, Gomes, Gabriel Marciano, additional, Christensen, Kaare, additional, Sodemann, Morten, additional, Møller Jensen, Dorte, additional, and Yajnik, Chittaranjan, additional

Published
2021
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10. A Sequential Predictive Power Design for a COVID Vaccine Trial.

Author

Mukherjee, Rajat, Yajnik, Pranav, Muhlemann, Natalia, and Morgan-Bouniol, Caroline

Subjects
*VACCINE trials, *COVID-19 vaccines, *COVID-19, *VACCINE effectiveness, *BCG vaccines
Abstract

Medical investigations for therapeutics and vaccines for combating a pandemic such as COVID-19, call for flexible and adaptive trial designs that are capable of producing robust results amidst uncertainties. Here, we present a Bayesian sequential design to study the efficacy of Bacillus Calmette–Guérin (BCG) in providing protection against COVID-19 infections via its known "trained-immunity" mechanism. The main design consideration is to provide a framework to rapidly establish a proof-of-concept on the vaccine efficacy of BCG under a constantly evolving incidence rate and in the absence of prior efficacy data. The trial design is based on taking several interim looks and calculating the predictive power with the current cohort at each interim look. Decisions to stop the trial for futility or stopping enrollment for efficacy are made based on the current cohort predictive power computation. At any interim, if any of the above decisions cannot be taken then the study continues to enroll till the next interim look. Via extensive numerical studies, we show that the proposed design can achieve the desired frequentist operating characteristics, currently required by regulatory bodies while offering greater flexibility in terms of sample size and the ability to make robust interim decisions. [ABSTRACT FROM AUTHOR]

Published
2022
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11. Multigenerational Undernutrition Increases Susceptibility to Obesity and Diabetes that Is Not Reversed after Dietary Recuperation

Author

Hardikar, Anandwardhan A., Satoor, Sarang N., Karandikar, Mahesh S., Joglekar, Mugdha V., Puranik, Amrutesh S., Wong, Wilson, Kumar, Sandeep, Limaye, Amita, Bhat, Dattatray S., Januszewski, Andrzej S., Umrani, Malati R., Ranjan, Amaresh K., Apte, Kishori, Yajnik, Pranav, Bhonde, Ramesh R., Galande, Sanjeev, Keech, Anthony C., Jenkins, Alicia J., and Yajnik, Chittaranjan S.

Published
2015
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13. Bias, Precision and Power of Some Techniques in Genome-Wide Association Analysis

Author

Yajnik, Pranav

Subjects
Genetic epidemiology, Genome-wide association analysis, Covariate adjusted trait, Imputation quality, External controls
Abstract

Genome-wide association studies (GWAS) have successfully identified thousands of genetic loci associated with a wide variety of human phenotypic traits. In this thesis, we evaluate the bias, precision and power of three statistical techniques employed in GWAS. In Chapter 2, we assess bias and power for adjusted-trait regression (ATR). ATR is a modification to the traditional ordinary least-squares estimation and F-test hypothesis testing techniques for quantitative trait multiple linear regression models. ATR involves performing bivariate correlation analysis between a genetic variant (or set of genetic variants) and a covariate-adjusted trait, obtained by regressing the trait on covariates. We show that ATR effect size estimates for single variant analysis are biased towards the null by a factor equal to coefficient of determination obtained from the regression of genetic variant onto covariates. We derive the exact distributions of ATR test statistics and show that ATR is less powerful than traditional methods when the genetic variant are correlated with covariates. The loss of power increases as stringency of Type 1 error control increases. The maximum possible power loss for the ATR multi-variant test is completely characterized by the canonical correlation between genetic variants and covariates. We show that, for typical covariates like genetic principal components, the loss of power will likely be low in practice. In Chapter 3, we assess three genetic imputation quality scores (allelic-RSQ, MACH-RSQ and INFO) as predictors for realized imputation quality (squared correlation between true genotypes and imputed dosages) for low-frequency and rare variants. We assess the impact of using different imputation algorithms (Beagle 4.2, minimac3 and IMPUTE 2) and reference panels (1000 Genomes [1KG] and Haplotype Reference Consortium [HRC]) on the relationship between imputation quality scores and realized quality. We imputed genotypes into 8,378 participants using each imputation algorithm with the 1KG panel and minimac3 with the HRC panel. We show that MACH-RSQ and INFO are identical when calculated on the same data. We observe that allelic-RSQ predicts realized quality less well than MACH-RSQ/INFO for low-frequency and rare variants. Realized quality decreases as minor allele frequency (MAF) decreases. The mean absolute difference (MAD) between quality scores and realized quality increases as MAF decreases. Imputation with HRC resulted in better realized quality for low-frequency and rare variants compared to imputation with 1KG. However, the MAD between quality scores and realized quality for low-frequency and rare variants was similar for both panels. In chapter 4, we assess the efficiency gained or lost by adding an external sample with missing case-control status to an (internal) case-control study sample. We propose a method for estimation and testing that accounts for the known (or presumed) proportion of cases in the external sample. Misspecification of the external sample case proportion leads to biased estimation; in particular, treating the external sample as a control sample leads to underestimation of the effect size. However, the proposed test controls Type 1 error regardless of the particular value chosen for the presumptive external sample case proportion. When treating the external participants as controls, addition of external participants improves power if the proportion of cases in the internal sample is at least twice that in the external sample.

Published
2020

14. Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power

Author

Locke, Adam E., Steinberg, Karyn Meltz, Chiang, Charleston W. K., Service, Susan K., Havulinna, Aki S., Stell, Laurel, Pirinen, Matti, Abel, Haley J., Chiang, Colby C., Fulton, Robert S., Jackson, Anne U., Kang, Chul Joo, Kanchi, Krishna L., Koboldt, Daniel C., Larson, David E., Nelson, Joanne, Nicholas, Thomas J., Pietilä, Arto, Ramensky, Vasily, Ray, Debashree, Scott, Laura J., Stringham, Heather M., Vangipurapu, Jagadish, Welch, Ryan, Yajnik, Pranav, Yin, Xianyong, Eriksson, Johan G., Ala-Korpela, Mika, Järvelin, Marjo-Riitta, Männikkö, Minna, Laivuori, Hannele, Dutcher, Susan K., Stitziel, Nathan O., Wilson, Richard K., Hall, Ira M., Sabatti, Chiara, Palotie, Aarno, Salomaa, Veikko, Laakso, Markku, Ripatti, Samuli, Boehnke, Michael, and Freimer, Nelson B.

Abstract

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019
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