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      Pregnancy and weaning regulate human maternal liver size and function

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          Significance

          These human data are consistent with reproductive control of liver size and function in women and concur with recent observations in rodents, suggesting a conserved liver biology. The question of whether this described liver biology has implications for maternal health during pregnancy or sex-specific risk for liver disease remains to be determined. However, our evidence suggestive of weaning-induced liver involution in women may lead to improved understanding of the high rates of liver metastasis observed in young postpartum breast cancer patients.

          Abstract

          During pregnancy, the rodent liver undergoes hepatocyte proliferation and increases in size, followed by weaning-induced involution via hepatocyte cell death and stromal remodeling, creating a prometastatic niche. These data suggest a mechanism for increased liver metastasis in breast cancer patients with recent childbirth. It is unknown whether the human liver changes in size and function during pregnancy and weaning. In this study, abdominal imaging was obtained in healthy women at early and late pregnancy and postwean. During pregnancy time points, glucose production and utilization and circulating bile acids were measured. Independently of weight gain, most women’s livers increased in size with pregnancy, then returned to baseline postwean. Putative roles for bile acids in liver growth and regression were observed. Together, the data support the hypothesis that the human liver is regulated by reproductive state with growth during pregnancy and volume loss postwean. These findings have implications for sex-specific liver diseases and for breast cancer outcomes.

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          Most cited references62

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

              DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                22 November 2021
                30 November 2021
                22 November 2021
                : 118
                : 48
                : e2107269118
                Affiliations
                [1] aDepartment of Cell, Developmental, and Cancer Biology, Oregon Health & Science University , Portland, OR 97239;
                [2] bCenter for Health Research, Kaiser Permanente Northwest , Portland, OR 97227;
                [3] cKnight Cardiovascular Institute, Oregon Health & Science University , Portland, OR 97239;
                [4] dPublic Health Sciences Division/Translational Research Program, Fred Hutchinson Cancer Research Center , Seattle, WA 98109;
                [5] eComputational Biology Program, Oregon Health & Science University , Portland, OR 97201;
                [6] fDepartment of Chemical Physiology and Biochemistry, Oregon Health & Science University , Portland, OR 97239;
                [7] gAdvanced Imaging Research Center, Oregon Health & Science University , Portland, OR 97239;
                [8] hDepartment of Medicine, Division of Gastroenterology and Hepatology, Oregon Health & Science University , Portland, OR 97239;
                [9] iDepartment of Diagnostic Radiology, Oregon Health & Science University , Portland, OR 97239;
                [10] jMother Infant Research Institute, Department of Obstetrics and Gynecology, Tufts University School of Medicine , Boston, MA 02111;
                [11] kDepartment of Molecular Microbiology and Immunology, Oregon Health & Science University , Portland, OR 97273;
                [12] lKnight Cancer Institute, Oregon Health & Science University , Portland, OR 97201;
                [13] mYoung Women’s Breast Cancer Translational Program, University of Colorado Anschutz Medical Campus , Aurora, CO 80045
                Author notes
                1To whom correspondence may be addressed. Email: schedin@ 123456ohsu.edu .

                Edited by David D. Moore, University of California, Berkeley, CA, and approved October 14, 2021 (received for review April 16, 2021)

                Author contributions: A.Q.B., K.K.V., J.Q.P., E.G., A.R.G., and P.S. designed research; A.Q.B., K.K.V., J.Q.P., E.G., X.G., A.D., E.B., W.R., W.N., and P.S. performed research; A.D. contributed new reagents/analytic tools; A.Q.B., K.K.V., J.Q.P., M.F., E.G., X.G., M.C.L., E.B., P.C., Z.X., and P.S. analyzed data; and A.Q.B. and P.S. wrote the paper.

                Author information
                https://orcid.org/0000-0001-7912-6084
                https://orcid.org/0000-0001-5505-6333
                https://orcid.org/0000-0002-0886-321X
                https://orcid.org/0000-0001-8910-0259
                https://orcid.org/0000-0003-1532-1328
                https://orcid.org/0000-0003-3291-3034
                https://orcid.org/0000-0003-3364-8324
                https://orcid.org/0000-0003-4244-987X
                Article
                202107269
                10.1073/pnas.2107269118
                8640831
                34815335
                84bef3b0-8dee-451f-8a7a-0f6527a6e804
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                : 07 October 2021
                Page count
                Pages: 10
                Funding
                Funded by: U.S. Department of Defense (DOD) 100000005
                Award ID: BC170206
                Award Recipient : Pepper Schedin
                Funded by: HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 100000062
                Award ID: #R01DK098707
                Award Recipient : Kimberly K Vesco
                Categories
                427
                Biological Sciences
                Physiology

                liver,pregnancy,bile acids,maternal health
                liver, pregnancy, bile acids, maternal health

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