Literature DB >> 32433745

Search for multiple myeloma risk factors using Mendelian randomization.

Molly Went1, Alex J Cornish1, Philip J Law1, Ben Kinnersley1, Mark van Duin2, Niels Weinhold3, Asta Försti4,5,6, Markus Hansson7,8, Pieter Sonneveld2, Hartmut Goldschmidt3,9, Gareth J Morgan10, Kari Hemminki4,11,12, Björn Nilsson7,13, Martin Kaiser14, Richard S Houlston1,14.   

Abstract

The etiology of multiple myeloma (MM) is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited in a Mendelian randomization (MR) phenome-wide association study (PheWAS) to search for factors influencing MM risk. We performed an MR-PheWAS analyzing 249 phenotypes, proxied by 10 225 genetic variants, and summary genetic data from a GWAS of 7717 MM cases and 29 304 controls. Odds ratios (ORs) per 1 standard deviation increase in each phenotype were estimated under an inverse variance weighted random effects model. A Bonferroni-corrected threshold of P = 2 × 10-4 was considered significant, whereas P < .05 was considered suggestive of an association. Although no significant associations with MM risk were observed among the 249 phenotypes, 28 phenotypes showed evidence suggestive of association, including increased levels of serum vitamin B6 and blood carnitine (P = 1.1 × 10-3) with greater MM risk and ω-3 fatty acids (P = 5.4 × 10-4) with reduced MM risk. A suggestive association between increased telomere length and reduced MM risk was also noted; however, this association was primarily driven by the previously identified risk variant rs10936599 at 3q26 (TERC). Although not statistically significant, increased body mass index was associated with increased risk (OR, 1.10; 95% confidence interval, 0.99-1.22), supporting findings from a previous meta-analysis of prospective observational studies. Our study did not provide evidence supporting any modifiable factors examined as having a major influence on MM risk; however, it provides insight into factors for which the evidence has previously been mixed.
© 2020 by The American Society of Hematology.

Entities:  

Mesh:

Year:  2020        PMID: 32433745      PMCID: PMC7252541          DOI: 10.1182/bloodadvances.2020001502

Source DB:  PubMed          Journal:  Blood Adv        ISSN: 2473-9529


  54 in total

1.  Calculating statistical power in Mendelian randomization studies.

Authors:  Marie-Jo A Brion; Konstantin Shakhbazov; Peter M Visscher
Journal:  Int J Epidemiol       Date:  2013-10       Impact factor: 7.196

2.  Risk of multiple myeloma is associated with polymorphisms within telomerase genes and telomere length.

Authors:  Daniele Campa; Alessandro Martino; Judit Varkonyi; Fabienne Lesueur; Krzysztof Jamroziak; Stefano Landi; Artur Jurczyszyn; Herlander Marques; Vibeke Andersen; Manuel Jurado; Hermann Brenner; Mario Petrini; Ulla Vogel; Ramón García-Sanz; Gabriele Buda; Federica Gemignani; Rafael Ríos; Annette Juul Vangsted; Charles Dumontet; Joaquín Martínez-López; María José Moreno; Anna Stępień; Marzena Wątek; Victor Moreno; Aida Karina Dieffenbach; Anna Maria Rossi; Katja Butterbach; Svend E Hove Jacobsen; Hartmut Goldschmidt; Juan Sainz; Jens Hillengass; Enrico Orciuolo; Marek Dudziński; Niels Weinhold; Rui Manuel Reis; Federico Canzian
Journal:  Int J Cancer       Date:  2014-08-06       Impact factor: 7.396

3.  Eight novel loci implicate shared genetic etiology in multiple myeloma, AL amyloidosis, and monoclonal gammopathy of unknown significance.

Authors:  Subhayan Chattopadhyay; Hauke Thomsen; Niels Weinhold; Iman Meziane; Stefanie Huhn; Miguel Inacio da Silva Filho; Pavel Vodicka; Ludmila Vodickova; Per Hoffmann; Markus M Nöthen; Karl-Heinz Jöckel; Börge Schmidt; Stefano Landi; Roman Hajek; Göran Hallmans; Ulrika Pettersson-Kymmer; Claes Ohlsson; Paolo Milani; Giampaolo Merlini; Dorota Rowcieno; Philip Hawkins; Ute Hegenbart; Giovanni Palladini; Ashutosh Wechalekar; Stefan O Schönland; Richard Houlston; Hartmut Goldschmidt; Kari Hemminki; Asta Försti
Journal:  Leukemia       Date:  2019-11-06       Impact factor: 11.528

4.  Variants in ELL2 influencing immunoglobulin levels associate with multiple myeloma.

Authors:  Bhairavi Swaminathan; Guðmar Thorleifsson; Magnus Jöud; Mina Ali; Ellinor Johnsson; Ram Ajore; Patrick Sulem; Britt-Marie Halvarsson; Guðmundur Eyjolfsson; Vilhelmina Haraldsdottir; Christina Hultman; Erik Ingelsson; Sigurður Y Kristinsson; Anna K Kähler; Stig Lenhoff; Gisli Masson; Ulf-Henrik Mellqvist; Robert Månsson; Sven Nelander; Isleifur Olafsson; Olof Sigurðardottir; Hlif Steingrimsdóttir; Annette Vangsted; Ulla Vogel; Anders Waage; Hareth Nahi; Daniel F Gudbjartsson; Thorunn Rafnar; Ingemar Turesson; Urban Gullberg; Kári Stefánsson; Markus Hansson; Unnur Thorsteinsdóttir; Björn Nilsson
Journal:  Nat Commun       Date:  2015-05-26       Impact factor: 14.919

5.  Common variation at 3q26.2, 6p21.33, 17p11.2 and 22q13.1 influences multiple myeloma risk.

Authors:  Daniel Chubb; Niels Weinhold; Peter Broderick; Bowang Chen; David C Johnson; Asta Försti; Jayaram Vijayakrishnan; Gabriele Migliorini; Sara E Dobbins; Amy Holroyd; Dirk Hose; Brian A Walker; Faith E Davies; Walter A Gregory; Graham H Jackson; Julie A Irving; Guy Pratt; Chris Fegan; James Al Fenton; Kai Neben; Per Hoffmann; Markus M Nöthen; Thomas W Mühleisen; Lewin Eisele; Fiona M Ross; Christian Straka; Hermann Einsele; Christian Langer; Elisabeth Dörner; James M Allan; Anna Jauch; Gareth J Morgan; Kari Hemminki; Richard S Houlston; Hartmut Goldschmidt
Journal:  Nat Genet       Date:  2013-08-18       Impact factor: 38.330

6.  Global Burden of Multiple Myeloma: A Systematic Analysis for the Global Burden of Disease Study 2016.

Authors:  Andrew J Cowan; Christine Allen; Aleksandra Barac; Huda Basaleem; Isabela Bensenor; Maria Paula Curado; Kyle Foreman; Rahul Gupta; James Harvey; H Dean Hosgood; Mihajlo Jakovljevic; Yousef Khader; Shai Linn; Deepesh Lad; Lorenzo Mantovani; Vuong Minh Nong; Ali Mokdad; Mohsen Naghavi; Maarten Postma; Gholamreza Roshandel; Katya Shackelford; Mekonnen Sisay; Cuong Tat Nguyen; Tung Thanh Tran; Bach Tran Xuan; Kingsley Nnanna Ukwaja; Stein Emil Vollset; Elisabete Weiderpass; Edward N Libby; Christina Fitzmaurice
Journal:  JAMA Oncol       Date:  2018-09-01       Impact factor: 31.777

7.  Genome-wide association study identifies multiple susceptibility loci for multiple myeloma.

Authors:  Jonathan S Mitchell; Ni Li; Niels Weinhold; Asta Försti; Mina Ali; Mark van Duin; Gudmar Thorleifsson; David C Johnson; Bowang Chen; Britt-Marie Halvarsson; Daniel F Gudbjartsson; Rowan Kuiper; Owen W Stephens; Uta Bertsch; Peter Broderick; Chiara Campo; Hermann Einsele; Walter A Gregory; Urban Gullberg; Marc Henrion; Jens Hillengass; Per Hoffmann; Graham H Jackson; Ellinor Johnsson; Magnus Jöud; Sigurður Y Kristinsson; Stig Lenhoff; Oleg Lenive; Ulf-Henrik Mellqvist; Gabriele Migliorini; Hareth Nahi; Sven Nelander; Jolanta Nickel; Markus M Nöthen; Thorunn Rafnar; Fiona M Ross; Miguel Inacio da Silva Filho; Bhairavi Swaminathan; Hauke Thomsen; Ingemar Turesson; Annette Vangsted; Ulla Vogel; Anders Waage; Brian A Walker; Anna-Karin Wihlborg; Annemiek Broyl; Faith E Davies; Unnur Thorsteinsdottir; Christian Langer; Markus Hansson; Martin Kaiser; Pieter Sonneveld; Kari Stefansson; Gareth J Morgan; Hartmut Goldschmidt; Kari Hemminki; Björn Nilsson; Richard S Houlston
Journal:  Nat Commun       Date:  2016-07-01       Impact factor: 14.919

8.  Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator.

Authors:  Jack Bowden; George Davey Smith; Philip C Haycock; Stephen Burgess
Journal:  Genet Epidemiol       Date:  2016-04-07       Impact factor: 2.135

9.  Novel therapies for multiple myeloma.

Authors:  Craig T Wallington-Beddoe; Stuart M Pitson
Journal:  Aging (Albany NY)       Date:  2017-08-28       Impact factor: 5.682

10.  Dietary intake is associated with risk of multiple myeloma and its precursor disease.

Authors:  Marianna Thordardottir; Ebba K Lindqvist; Sigrun H Lund; Rene Costello; Debra Burton; Laufey Steingrimsdottir; Neha Korde; Sham Mailankody; Gudny Eiriksdottir; Lenore J Launer; Vilmundur Gudnason; Tamara B Harris; Ola Landgren; Johanna E Torfadottir; Sigurdur Y Kristinsson
Journal:  PLoS One       Date:  2018-11-01       Impact factor: 3.240

View more
  9 in total

1.  Adiposity and cancer: a Mendelian randomization analysis in the UK biobank.

Authors:  Muktar Ahmed; Anwar Mulugeta; S Hong Lee; Ville-Petteri Mäkinen; Terry Boyle; Elina Hyppönen
Journal:  Int J Obes (Lond)       Date:  2021-08-27       Impact factor: 5.095

2.  The Role of Mendelian Randomization Studies in Deciphering the Effect of Obesity on Cancer.

Authors:  Zhe Fang; Mingyang Song; Dong Hoon Lee; Edward L Giovannucci
Journal:  J Natl Cancer Inst       Date:  2022-03-08       Impact factor: 13.506

3.  Mendelian randomization study updates the effect of 25-hydroxyvitamin D levels on the risk of multiple sclerosis.

Authors:  Renxi Wang
Journal:  J Transl Med       Date:  2022-01-03       Impact factor: 5.531

4.  Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies.

Authors:  Susanna C Larsson; Stephen Burgess
Journal:  BMC Med       Date:  2021-12-15       Impact factor: 8.775

Review 5.  Genome Instability in Multiple Myeloma: Facts and Factors.

Authors:  Anna Y Aksenova; Anna S Zhuk; Artem G Lada; Irina V Zotova; Elena I Stepchenkova; Ivan I Kostroma; Sergey V Gritsaev; Youri I Pavlov
Journal:  Cancers (Basel)       Date:  2021-11-26       Impact factor: 6.639

6.  Mendelian Randomization Study on the Putative Causal Effects of Omega-3 Fatty Acids on Low Back Pain.

Authors:  Shan Zhou; Gaizhi Zhu; Yaqi Xu; Ran Gao; Huan Li; Gencheng Han; Wenting Su; Renxi Wang
Journal:  Front Nutr       Date:  2022-02-14

Review 7.  Metabolic Disorders in Multiple Myeloma.

Authors:  Maria Gavriatopoulou; Stavroula A Paschou; Ioannis Ntanasis-Stathopoulos; Meletios A Dimopoulos
Journal:  Int J Mol Sci       Date:  2021-10-22       Impact factor: 5.923

8.  Assessing the Relationship Between Leukocyte Telomere Length and Cancer Risk/Mortality in UK Biobank and TCGA Datasets With the Genetic Risk Score and Mendelian Randomization Approaches.

Authors:  Yixin Gao; Yongyue Wei; Xiang Zhou; Shuiping Huang; Huashuo Zhao; Ping Zeng
Journal:  Front Genet       Date:  2020-10-23       Impact factor: 4.599

9.  Systematic review of Mendelian randomization studies on risk of cancer.

Authors:  Georgios Markozannes; Afroditi Kanellopoulou; Olympia Dimopoulou; Dimitrios Kosmidis; Xiaomeng Zhang; Lijuan Wang; Evropi Theodoratou; Dipender Gill; Stephen Burgess; Konstantinos K Tsilidis
Journal:  BMC Med       Date:  2022-02-02       Impact factor: 11.150

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.