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Multi-SNP mediation intersection-union test.

Bioinformatics (Oxford, England)

Zhong W, Spracklen CN, Mohlke KL, Zheng X, Fine J, Li Y.
PMID: 31099385
Bioinformatics. 2019 Nov 01;35(22):4724-4729. doi: 10.1093/bioinformatics/btz285.

SUMMARY: Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if...

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Zhong W, Spracklen CN, Mohlke KL, et al. Multi-SNP mediation intersection-union test. Bioinformatics. 2019;35(22):4724-4729doi: 10.1093/bioinformatics/btz285.
Zhong, W., Spracklen, C. N., Mohlke, K. L., Zheng, X., Fine, J., & Li, Y. (2019). Multi-SNP mediation intersection-union test. Bioinformatics (Oxford, England), 35(22), 4724-4729. https://doi.org/10.1093/bioinformatics/btz285
Zhong, Wujuan, et al. "Multi-SNP mediation intersection-union test." Bioinformatics (Oxford, England) vol. 35,22 (2019): 4724-4729. doi: https://doi.org/10.1093/bioinformatics/btz285
Zhong W, Spracklen CN, Mohlke KL, Zheng X, Fine J, Li Y. Multi-SNP mediation intersection-union test. Bioinformatics. 2019 Nov 01;35(22):4724-4729. doi: 10.1093/bioinformatics/btz285. PMID: 31099385; PMCID: PMC6853702.
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Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation.

Molecular metabolism

Johnson AR, Qin Y, Cozzo AJ, Freemerman AJ, Huang MJ, Zhao L, Sampey BP, Milner JJ, Beck MA, Damania B, Rashid N, Galanko JA, Lee DP, Edin ML, Zeldin DC, Fueger PT, Dietz B, Stahl A, Wu Y, Mohlke KL, Makowski L.
PMID: 27408776
Mol Metab. 2016 Apr 23;5(7):506-526. doi: 10.1016/j.molmet.2016.04.005. eCollection 2016 Jul.

OBJECTIVE: A novel approach to regulate obesity-associated adipose inflammation may be through metabolic reprogramming of macrophages (MΦs). Broadly speaking, MΦs dependent on glucose are pro-inflammatory, classically activated MΦs (CAM), which contribute to adipose inflammation and insulin resistance. In contrast,...

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Johnson AR, Qin Y, Cozzo AJ, et al. Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation. Mol Metab. 2016;5(7):506-526doi: 10.1016/j.molmet.2016.04.005.
Johnson, A. R., Qin, Y., Cozzo, A. J., Freemerman, A. J., Huang, M. J., Zhao, L., Sampey, B. P., Milner, J. J., Beck, M. A., Damania, B., Rashid, N., Galanko, J. A., Lee, D. P., Edin, M. L., Zeldin, D. C., Fueger, P. T., Dietz, B., Stahl, A., Wu, Y., Mohlke, K. L., & Makowski, L. (2016). Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation. Molecular metabolism, 5(7), 506-526. https://doi.org/10.1016/j.molmet.2016.04.005
Johnson, Amy R, et al. "Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation." Molecular metabolism vol. 5,7 (2016): 506-526. doi: https://doi.org/10.1016/j.molmet.2016.04.005
Johnson AR, Qin Y, Cozzo AJ, Freemerman AJ, Huang MJ, Zhao L, Sampey BP, Milner JJ, Beck MA, Damania B, Rashid N, Galanko JA, Lee DP, Edin ML, Zeldin DC, Fueger PT, Dietz B, Stahl A, Wu Y, Mohlke KL, Makowski L. Metabolic reprogramming through fatty acid transport protein 1 (FATP1) regulates macrophage inflammatory potential and adipose inflammation. Mol Metab. 2016 Apr 23;5(7):506-526. doi: 10.1016/j.molmet.2016.04.005. eCollection 2016 Jul. PMID: 27408776; PMCID: PMC4921943.
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Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits.

Genome research

Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ.
PMID: 34815310
Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23.

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq...

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Orchard P, Manickam N, Ventresca C, et al. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021;doi: 10.1101/gr.268482.120.
Orchard, P., Manickam, N., Ventresca, C., Vadlamudi, S., Varshney, A., Rai, V., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., Burant, C. F., & Parker, S. C. J. (2021). Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome research, . https://doi.org/10.1101/gr.268482.120
Orchard, Peter, et al. "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits." Genome research vol. (2021). doi: https://doi.org/10.1101/gr.268482.120
Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23. PMID: 34815310; PMCID: PMC8647829.
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Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits.

Genome research

Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ.
PMID: 34815310
Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23.

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq...

Cite
Orchard P, Manickam N, Ventresca C, et al. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021;doi: 10.1101/gr.268482.120.
Orchard, P., Manickam, N., Ventresca, C., Vadlamudi, S., Varshney, A., Rai, V., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., Burant, C. F., & Parker, S. C. J. (2021). Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome research, . https://doi.org/10.1101/gr.268482.120
Orchard, Peter, et al. "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits." Genome research vol. (2021). doi: https://doi.org/10.1101/gr.268482.120
Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23. PMID: 34815310; PMCID: PMC8647829.
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Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes.

Genome medicine

Pan DZ, Miao Z, Comenho C, Rajkumar S, Koka A, Lee SHT, Alvarez M, Kaminska D, Ko A, Sinsheimer JS, Mohlke KL, Mancuso N, Muñoz-Hernandez LL, Herrera-Hernandez M, Tusié-Luna MT, Aguilar-Salinas C, Pietiläinen KH, Pihlajamäki J, Laakso M, Garske KM, Pajukanta P.
PMID: 34340684
Genome Med. 2021 Aug 02;13(1):123. doi: 10.1186/s13073-021-00939-2.

BACKGROUND: Obesity predisposes individuals to multiple cardiometabolic disorders, including type 2 diabetes (T2D). As body mass index (BMI) cannot reliably differentiate fat from lean mass, the metabolically detrimental abdominal obesity has been estimated using waist-hip ratio (WHR). Waist-hip ratio...

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Pan DZ, Miao Z, Comenho C, et al. Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome Med. 2021;13(1):123doi: 10.1186/s13073-021-00939-2.
Pan, D. Z., Miao, Z., Comenho, C., Rajkumar, S., Koka, A., Lee, S. H. T., Alvarez, M., Kaminska, D., Ko, A., Sinsheimer, J. S., Mohlke, K. L., Mancuso, N., Muñoz-Hernandez, L. L., Herrera-Hernandez, M., Tusié-Luna, M. T., Aguilar-Salinas, C., Pietiläinen, K. H., Pihlajamäki, J., Laakso, M., Garske, K. M., & Pajukanta, P. (2021). Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome medicine, 13(1), 123. https://doi.org/10.1186/s13073-021-00939-2
Pan, David Z, et al. "Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes." Genome medicine vol. 13,1 (2021): 123. doi: https://doi.org/10.1186/s13073-021-00939-2
Pan DZ, Miao Z, Comenho C, Rajkumar S, Koka A, Lee SHT, Alvarez M, Kaminska D, Ko A, Sinsheimer JS, Mohlke KL, Mancuso N, Muñoz-Hernandez LL, Herrera-Hernandez M, Tusié-Luna MT, Aguilar-Salinas C, Pietiläinen KH, Pihlajamäki J, Laakso M, Garske KM, Pajukanta P. Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome Med. 2021 Aug 02;13(1):123. doi: 10.1186/s13073-021-00939-2. PMID: 34340684; PMCID: PMC8327600.
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Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs.

Frontiers in genetics

Zhong W, Dong L, Poston TB, Darville T, Spracklen CN, Wu D, Mohlke KL, Li Y, Li Q, Zheng X.
PMID: 32127796
Front Genet. 2020 Feb 07;11:8. doi: 10.3389/fgene.2020.00008. eCollection 2020.

Construction of regulatory networks using cross-sectional expression profiling of genes is desired, but challenging. The Directed Acyclic Graph (DAG) provides a general framework to infer causal effects from observational data. However, most existing DAG methods assume that all nodes...

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Zhong W, Dong L, Poston TB, et al. Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs. Front Genet. 2020;11:8doi: 10.3389/fgene.2020.00008.
Zhong, W., Dong, L., Poston, T. B., Darville, T., Spracklen, C. N., Wu, D., Mohlke, K. L., Li, Y., Li, Q., & Zheng, X. (2020). Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs. Frontiers in genetics, 118. https://doi.org/10.3389/fgene.2020.00008
Zhong, Wujuan, et al. "Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs." Frontiers in genetics vol. 11 (2020): 8. doi: https://doi.org/10.3389/fgene.2020.00008
Zhong W, Dong L, Poston TB, Darville T, Spracklen CN, Wu D, Mohlke KL, Li Y, Li Q, Zheng X. Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs. Front Genet. 2020 Feb 07;11:8. doi: 10.3389/fgene.2020.00008. eCollection 2020. PMID: 32127796; PMCID: PMC7038820.
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Epigenome-wide association in adipose tissue from the METSIM cohort.

Human molecular genetics

Orozco LD, Farrell C, Hale C, Rubbi L, Rinaldi A, Civelek M, Pan C, Lam L, Montoya D, Edillor C, Seldin M, Boehnke M, Mohlke KL, Jacobsen S, Kuusisto J, Laakso M, Lusis AJ, Pellegrini M.
PMID: 29893869
Hum Mol Genet. 2018 Jul 15;27(14):2586. doi: 10.1093/hmg/ddy205.

No abstract available.

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Orozco LD, Farrell C, Hale C, et al. Epigenome-wide association in adipose tissue from the METSIM cohort. Hum Mol Genet. 2018;27(14):2586doi: 10.1093/hmg/ddy205.
Orozco, L. D., Farrell, C., Hale, C., Rubbi, L., Rinaldi, A., Civelek, M., Pan, C., Lam, L., Montoya, D., Edillor, C., Seldin, M., Boehnke, M., Mohlke, K. L., Jacobsen, S., Kuusisto, J., Laakso, M., Lusis, A. J., & Pellegrini, M. (2018). Epigenome-wide association in adipose tissue from the METSIM cohort. Human molecular genetics, 27(14), 2586. https://doi.org/10.1093/hmg/ddy205
Orozco, Luz D, et al. "Epigenome-wide association in adipose tissue from the METSIM cohort." Human molecular genetics vol. 27,14 (2018): 2586. doi: https://doi.org/10.1093/hmg/ddy205
Orozco LD, Farrell C, Hale C, Rubbi L, Rinaldi A, Civelek M, Pan C, Lam L, Montoya D, Edillor C, Seldin M, Boehnke M, Mohlke KL, Jacobsen S, Kuusisto J, Laakso M, Lusis AJ, Pellegrini M. Epigenome-wide association in adipose tissue from the METSIM cohort. Hum Mol Genet. 2018 Jul 15;27(14):2586. doi: 10.1093/hmg/ddy205. PMID: 29893869; PMCID: PMC6030960.
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Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits.

Genome research

Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ.
PMID: 34815310
Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23.

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq...

Cite
Orchard P, Manickam N, Ventresca C, et al. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021;doi: 10.1101/gr.268482.120.
Orchard, P., Manickam, N., Ventresca, C., Vadlamudi, S., Varshney, A., Rai, V., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., Burant, C. F., & Parker, S. C. J. (2021). Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome research, . https://doi.org/10.1101/gr.268482.120
Orchard, Peter, et al. "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits." Genome research vol. (2021). doi: https://doi.org/10.1101/gr.268482.120
Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23. PMID: 34815310; PMCID: PMC8647829.
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