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      Identification of host gene-microbiome associations in colorectal cancer patients using mendelian randomization

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          Abstract

          Background

          There are many studies indicating that alterations in the abundance of certain gut microbiota are associated with colorectal cancer (CRC). However, a causal relationship has not been identified due to confounding factors such as lifestyle, environmental, and possible reverse causal associations between the two. Furthermore, certain host gene mutations can also contribute to the development of CRC. However, the association between genes and gut microbes in patients with CRC has not been extensively studied.

          Methods

          We conducted a two-sample Mendelian randomization (MR) study to reveal the causal relationship between gut microbiota and CRC. We obtained SNPs associated with gut microbiome abundance as instrumental variables (IVs) from a large-scale, multi-ethnic GWAS study, and extracted CRC-related datasets from an East Asian Population genetic consortia GWAS (AGWAS) study and FinnGen consortium, respectively. We analyzed a total of 166 bacterial features at four taxonomic levels, including order, family, genus, and species. The inverse-variance-weighted (IVW), weighted median, MR-Egger, and simple median methods were applied to the MR analysis, and the robustness of the results were tested using a series of sensitivity analyses. We extracted IVs of gut microbiota with direct causal association with CRC for SNP annotation to identify the genes in which these genetic variants were located to reveal the possible host gene-microbiome associations in CRC patients.

          Results

          The findings from our MR analysis based on CRC-associated GWAS datasets from AGWAS revealed causal relationships between 6 bacterial taxa and CRC at a locus-wide significance level (P < 1 × 10 –5). The IVW method found that family Porphyromonadaceae, genera Anaerotruncus, Intestinibacter, Slackia, and Ruminococcaceae UCG004, and species Eubacterium coprostanoligenes group were positively associated with CRC risk, which was generally consistent with the results of other complementary analyses. The results of a meta-analysis of the MR estimates from the AGWAS and the FinnGen datasets showed that family Porphyromonadaceae and genera Slackia, Anaerotruncus, and Intestinibacter replicated the same causal association. Sensitivity analysis of all causal associations did not indicate significant heterogeneity, horizontal pleiotropy, or reverse causal associations. We annotated the SNPs at a locus-wide significance level of the above intestinal flora and identified 24 host genes that may be related to pathogenic intestinal microflora in CRC patients.

          Conclusion

          This study supported the causal relationship of gut microbiota on CRC and revealed a possible correlation between genes and pathogenic microbiota in CRC. These findings suggested that the study of the gut microbiome and its further multi-omics analysis was important for the prevention and treatment of CRC.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12967-023-04335-9.

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          Most cited references55

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Cancer statistics, 2023

            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes using incidence data collected by central cancer registries and mortality data collected by the National Center for Health Statistics. In 2023, 1,958,310 new cancer cases and 609,820 cancer deaths are projected to occur in the United States. Cancer incidence increased for prostate cancer by 3% annually from 2014 through 2019 after two decades of decline, translating to an additional 99,000 new cases; otherwise, however, incidence trends were more favorable in men compared to women. For example, lung cancer in women decreased at one half the pace of men (1.1% vs. 2.6% annually) from 2015 through 2019, and breast and uterine corpus cancers continued to increase, as did liver cancer and melanoma, both of which stabilized in men aged 50 years and older and declined in younger men. However, a 65% drop in cervical cancer incidence during 2012 through 2019 among women in their early 20s, the first cohort to receive the human papillomavirus vaccine, foreshadows steep reductions in the burden of human papillomavirus-associated cancers, the majority of which occur in women. Despite the pandemic, and in contrast with other leading causes of death, the cancer death rate continued to decline from 2019 to 2020 (by 1.5%), contributing to a 33% overall reduction since 1991 and an estimated 3.8 million deaths averted. This progress increasingly reflects advances in treatment, which are particularly evident in the rapid declines in mortality (approximately 2% annually during 2016 through 2020) for leukemia, melanoma, and kidney cancer, despite stable/increasing incidence, and accelerated declines for lung cancer. In summary, although cancer mortality rates continue to decline, future progress may be attenuated by rising incidence for breast, prostate, and uterine corpus cancers, which also happen to have the largest racial disparities in mortality.
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              Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

              Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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                Author and article information

                Contributors
                tongyingying-89@163.com
                yd15yt88@163.com
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                10 August 2023
                10 August 2023
                2023
                : 21
                : 535
                Affiliations
                GRID grid.478016.c, ISNI 0000 0004 7664 6350, Department of Oncology, , Beijing Luhe Hospital Affiliated to Capital Medical University, ; Beijing, 101149 China
                Article
                4335
                10.1186/s12967-023-04335-9
                10416448
                37563724
                5cd8e989-d74c-4e26-94e0-34fb8f5cb5fb
                © BioMed Central Ltd., part of Springer Nature 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 12 March 2023
                : 9 July 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100009592, Beijing Municipal Science and Technology Commission;
                Award ID: KM202010025005
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100010270, Capital Health Research and Development of Special Fund;
                Award ID: 2022-2-7083
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004826, Natural Science Foundation of Beijing Municipality;
                Award ID: 7222100
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Medicine
                mendelian randomization (mr),gut microbiota,gene,colorectal cancer (crc),causal relationship

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