10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Causal Effects of Serum Levels of n-3 or n-6 Polyunsaturated Fatty Acids on Coronary Artery Disease: Mendelian Randomization Study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We aimed to investigate the causal effects of n-3 and n-6 polyunsaturated fatty acids (PUFAs) on the risk of coronary artery disease (CAD) through Mendelian randomization (MR) analysis. This MR study utilized a genetic instrument developed from previous genome-wide association studies for various serum n-3 and n-6 PUFA levels. First, we calculated the allele scores for genetic predisposition of PUFAs in individuals of European ancestry in the UK Biobank data ( N = 337,129). The allele score-based MR was obtained by regressing the allele scores to CAD risks. Second, summary-level MR was performed with the CARDIoGRAMplusC4D data for CAD ( N = 184,305). Higher genetically predicted eicosapentaenoic acid and dihomo-gamma-linolenic acid levels were significantly associated with a lower risk of CAD both in the allele-score-based and summary-level MR analyses. Higher allele scores for linoleic acid level were significantly associated with lower CAD risks, and in the summary-level MR, the causal estimates by the pleiotropy-robust MR methods also indicated that higher linoleic acid levels cause a lower risk of CAD. Arachidonic acid showed significant causal estimates for a higher risk of CAD. This study supports the causal effects of certain n-3 and n-6 PUFA types on the risk of CAD.

          Related collections

          Most cited references47

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Second-generation PLINK: rising to the challenge of larger and richer datasets

          PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

            Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                28 April 2021
                May 2021
                : 13
                : 5
                : 1490
                Affiliations
                [1 ]Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Korea; mailofsehoon@ 123456gmail.com (S.P.); yonsukim@ 123456snu.ac.kr (Y.S.K.)
                [2 ]Department of Internal Medicine, Armed Forces Capital Hospital, Seongnam 13574, Gyeonggi-do, Korea
                [3 ]Division of Nephrology, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Uijeongbu 11759, Gyeonggi-do, Korea; sjlee891016@ 123456hanmail.net (S.L.); wooo35@ 123456empas.com (Y.L.)
                [4 ]Department of Internal Medicine, Keimyung University School of Medicine, Daegu 42601, Korea; yaerim86@ 123456gmail.com
                [5 ]Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Korea; ahdia0602@ 123456naver.com (M.W.K.); imyongkim@ 123456gmail.com (Y.C.K.); hansway80@ 123456gmail.com (S.S.H.); mdhjlee@ 123456gmail.com (H.L.); junephro@ 123456gmail.com (K.W.J.)
                [6 ]Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul 03080, Korea; kksoo716@ 123456gmail.com
                [7 ]Department of Internal Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea; nephrolee@ 123456gmail.com (J.P.L.); cslimjy@ 123456snu.ac.kr (C.S.L.)
                [8 ]Kidney Research Institute, Seoul National University, Seoul 03080, Korea
                [9 ]Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul 07061, Korea
                Author notes
                [* ]Correspondence: dkkim73@ 123456gmail.com ; Tel.: +82-2-2072-2303; Fax: +82-2-745-2264
                Author information
                https://orcid.org/0000-0003-1596-1528
                https://orcid.org/0000-0002-4586-5062
                https://orcid.org/0000-0002-1873-1587
                https://orcid.org/0000-0001-9941-7858
                https://orcid.org/0000-0002-5195-7852
                Article
                nutrients-13-01490
                10.3390/nu13051490
                8145894
                33924952
                5abb0473-b6eb-48a1-a6d2-1d9cf0a3f27e
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 31 March 2021
                : 26 April 2021
                Categories
                Article

                Nutrition & Dietetics
                coronary artery disease,mendelian randomization,polyunsaturated fatty acids,myocardial infarction,risk factor

                Comments

                Comment on this article