Fernando Pires Hartwig

ORCID: 0000-0003-3729-0710
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About
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Research Areas
  • Genetic Associations and Epidemiology
  • Genetic and phenotypic traits in livestock
  • Birth, Development, and Health
  • Sperm and Testicular Function
  • Genetic Mapping and Diversity in Plants and Animals
  • SARS-CoV-2 and COVID-19 Research
  • Advanced Causal Inference Techniques
  • COVID-19 Clinical Research Studies
  • Reproductive Biology and Fertility
  • Breastfeeding Practices and Influences
  • Epigenetics and DNA Methylation
  • Telomeres, Telomerase, and Senescence
  • Child Nutrition and Water Access
  • SARS-CoV-2 detection and testing
  • Global Maternal and Child Health
  • Nutrition, Genetics, and Disease
  • Health, Environment, Cognitive Aging
  • Education during COVID-19 pandemic
  • Obesity, Physical Activity, Diet
  • Reproductive Physiology in Livestock
  • Vaccine Coverage and Hesitancy
  • Statistical Methods in Clinical Trials
  • COVID-19 and Mental Health
  • Nutritional Studies and Diet
  • Seed Germination and Physiology

Universidade Federal de Pelotas
2016-2025

Medical Research Council
2016-2025

University of Bristol
2016-2025

MRC Epidemiology Unit
2017-2024

University of Chicago
2023

Erasmus MC
2023

NIHR Bristol Biomedical Research Centre
2022

Universidade Estadual Paulista (Unesp)
2012-2020

MRC Integrative Epidemiology Unit
2016-2017

University of Rostock
2014

Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data genetic associations for a variety phenotypes from large genome-wide association studies (GWAS) allows straightforward application MR using methods, typically two-sample design. In addition the conventional inverse variance weighting (IVW) method, recently developed such as MR-Egger and weighted median approaches, allow relaxation instrumental variable...

10.1093/ije/dyx102 article EN cc-by International Journal of Epidemiology 2017-05-22

<ns4:p>This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, journal editors reviewers assess manuscripts. The are divided into nine sections: motivation scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary sensitivity (one section on robust methods one other approaches), presentation, interpretation. These will be updated...

10.12688/wellcomeopenres.15555.1 preprint EN cc-by Wellcome Open Research 2019-11-26

<ns4:p>This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, journal editors reviewers assess manuscripts. The are divided into nine sections: motivation scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary sensitivity (one section on robust statistical methods one other approaches), presentation, interpretation. These will...

10.12688/wellcomeopenres.15555.2 preprint EN cc-by Wellcome Open Research 2020-04-28
Jihua Chen Cassandra N. Spracklen Gaëlle Marenne Arushi Varshney Laura J. Corbin and 95 more Jian’an Luan Sara M. Willems Ying Wu Xiaoshuai Zhang Momoko Horikoshi Thibaud Boutin Reedik Mägi Johannes Waage Ruifang Li‐Gao Kei Hang Katie Chan Jie Yao Mila Desi Anasanti Audrey Y. Chu Annique Claringbould Jani Heikkinen Jaeyoung Hong Jouke‐Jan Hottenga Shaofeng Huo Marika Kaakinen Tin Louie Winfried März Hortensia Moreno-Macías Anne Ndungu Sarah C. Nelson Ilja M. Nolte Kari E. North Chelsea K. Raulerson Debashree Ray Rebecca Rohde Denis Rybin Claudia Schurmann Xueling Sim Lorraine Southam Isobel D. Stewart Carol A. Wang Yujie Wang Peitao Wu Weihua Zhang Tarunveer S. Ahluwalia Emil V. R. Appel Lawrence F. Bielak Jennifer A. Brody Noël P. Burtt Claudia Cabrera Brian E. Cade Jin Fang Chai Xiaoran Chai Li-Ching Chang Chien-Hsiun Chen Brian H. Chen Kumaraswamy Naidu Chitrala Yen‐Feng Chiu Hugoline G. de Haan Graciela E. Delgado Ayşe Demirkan Qing Duan Jorgen Engmann Segun Fatumo Javier Gayán Franco Giulianini Jung Ho Gong Stefan Gustafsson Yang Hai Fernando Pires Hartwig Jing He Yoriko Heianza Tao Huang Alicia Huerta-Chagoya Mi Yeong Hwang Richard A. Jensen Takahisa Kawaguchi Katherine A. Kentistou Young Jin Kim Marcus E. Kleber Ishminder K. Kooner Shuiqing Lai Leslie A. Lange Carl D. Langefeld Marie Lauzon Man Li Symen Ligthart Jun Liu Marie Loh Jirong Long Valeriya Lyssenko Massimo Mangino Carola Marzi May E. Montasser Abhishek Nag Masahiro Nakatochi Damia Noce Raymond Noordam Giorgio Pistis Michael Preuß Laura M. Raffield

10.1038/s41588-021-00852-9 article EN Nature Genetics 2021-05-31

Population-based data on COVID-19 are essential for guiding policies. There few such studies, particularly from low or middle-income countries. Brazil is currently a hotspot globally. We aimed to investigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence by city and according sex, age, ethnicity group, socioeconomic status, compare seroprevalence estimates with official statistics deaths cases.In this repeated cross-sectional study, we did two surveys in 133...

10.1016/s2214-109x(20)30387-9 article EN cc-by The Lancet Global Health 2020-09-24

<ns3:p>This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, journal editors reviewers assess manuscripts. The are divided into ten sections: motivation scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary sensitivity (one section on robust statistical methods one other approaches), extensions additional analyses,...

10.12688/wellcomeopenres.15555.3 preprint EN cc-by Wellcome Open Research 2023-08-04
Amand F. Schmidt Daniel I. Swerdlow Michael V. Holmes Riyaz Patel Zammy Fairhurst-Hunter and 95 more Donald M. Lyall Fernando Pires Hartwig Bernardo Lessa Horta Elina Hyppönen Christine Power Max Moldovan Erik Van Iperen G. Kees Hovingh Ilja Demuth Kristina Norman Elisabeth Steinhagen‐Thiessen Juri Demuth Lars Bertram Tian Liu Stefan Coassin Johann Willeit Stefan Kiechl Karin Willeit Dan Mason John Wright Richard Morris Goya Wanamethee Peter H. Whincup Yoav Ben‐Shlomo Stela McLachlan Jackie F. Price Mika Kivimäki Catherine Welch Adelaida Sánchez-Gálvez Pedro Marques‐Vidal Andrew Nicolaides Andrie G. Panayiotou N. Charlotte Onland‐Moret Yvonne T. van der Schouw Giuseppe Matullo Giovanni Fiorito Simonetta Guarrera Carlotta Sacerdote Nicholas J. Wareham Claudia Langenberg Robert A. Scott Jian’an Luan Martin Bobák Sofia Malyutina Andrzej Pająk Růžena Kubínová Abdonas Tamošiūnas Hynek Pikhart Lise Lotte N. Husemoen Niels Grarup Oluf Pedersen Torben Hansen Allan Linneberg Kenneth Starup Simonsen Jackie A. Cooper Steve E. Humphries Murray H. Brilliant Terrie Kitchner Hákon Hákonarson David Carrell Catherine A. McCarty H. Lester Kirchner Eric B. Larson David R. Crosslin Mariza de Andrade Dan M. Roden Joshua C. Denny Cara L. Carty Stephen Hancock John Attia Elizabeth G. Holliday Martin O’Donnell Salim Yusuf Michael Chong Guillaume Paré Pim van der Harst M. Abdullah Said Ruben N. Eppinga Niek Verweij Harold Snieder Tim Christen Dennis O. Mook‐Kanamori Stefan Gustafsson Lars Lind Erik Ingelsson Raha Pazoki Oscar H. Franco Albert Hofman André G. Uitterlinden Abbas Dehghan Alexander Teumer Sebastian E. Baumeister Marcus Dörr Markus M. Lerch Uwe Völker

Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions both concentration of LDL cholesterol risk coronary heart disease, but also modest hyperglycaemia, increased bodyweight, modestly type 2 diabetes, which no way offsets their substantial benefits. We sought to investigate associations cholesterol-lowering PCSK9 diabetes related biomarkers gauge likely effects inhibitors on risk.In this mendelian randomisation study, we used data from cohort...

10.1016/s2213-8587(16)30396-5 article EN cc-by The Lancet Diabetes & Endocrinology 2016-11-28

Abstract Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding familial effects. Here we describe methods for within-family analyses and use simulation show that family-based reduce such biases. We illustrate empirically how effects affect estimates using data 61,008 siblings the Nord-Trøndelag Health Study UK Biobank replicated our findings 222,368 23andMe. Both within family reproduced established lower BMI reducing risk...

10.1038/s41467-020-17117-4 article EN cc-by Nature Communications 2020-07-14

Positive associations between inflammatory biomarkers and risk of psychiatric disorders, including schizophrenia, have been reported in observational studies. However, conventional studies are prone to bias, such as reverse causation residual confounding, thus limiting our understanding the effect (if any) on schizophrenia risk.To evaluate whether an developing schizophrenia.Two-sample mendelian randomization study using genetic variants associated with instrumental variables improve...

10.1001/jamapsychiatry.2017.3191 article EN cc-by JAMA Psychiatry 2017-11-01

<b>Objective</b>&nbsp;To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. <b>Design</b>&nbsp;Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. <b>Setting</b>&nbsp;The main analysis used from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies predominantly high income countries. Findings mendelian analyses were then compared against results traditional...

10.1136/bmj.j3542 article EN cc-by BMJ 2017-08-30

Population-based data on COVID-19 are urgently needed. We report three rounds of probability sample household surveys in the state Rio Grande do Sul (Brazil), carried out nine large municipalities using Wondfo lateral flow point-of-care test for immunoglobulin M and G antibodies against SARS-CoV-2 (https://en.wondfo.com.cn/product/wondfo-sars-cov-2-antibody-test-lateral-flow-method-2/). Before survey use, assay underwent four validation studies with pooled estimates sensitivity (84.8%; 95%...

10.1038/s41591-020-0992-3 article EN other-oa Nature Medicine 2020-07-08
Yun Ju Sung Thomas W. Winkler Lisa de las Fuentes Amy R. Bentley Michael R. Brown and 95 more Aldi T. Kraja Karen Schwander Ιωάννα Ντάλλα Xiuqing Guo Nora Franceschini Yingchang Lu Ching‐Yu Cheng Xueling Sim Dina Vojinović Jonathan Marten Solomon K. Musani Changwei Li Mary F. Feitosa Tuomas O. Kilpeläinen Melissa A. Richard Raymond Noordam Stella Aslibekyan Hugues Aschard Traci M. Bartz Rajkumar Dorajoo Yongmei Liu Alisa K. Manning Tuomo Rankinen Albert V. Smith Salman M. Tajuddin Bamidele O. Tayo Helen R. Warren Wei Zhao Yanhua Zhou Nana Matoba Tamar Sofer Maris Alver Marzyeh Amini Mathilde Boissel Jin Fang Chai Xu Chen Jasmin Divers Ilaria Gandin Chuan Gao Franco Giulianini Anuj Goel Sarah E. Harris Fernando Pires Hartwig A.R.V.R. Horimoto Fang‐Chi Hsu Anne Jackson Mika Kähönen Anuradhani Kasturiratne Brigitte Kühnel Karin Leander Wen‐Jane Lee Keng‐Hung Lin Jian ’an Luan Colin A. McKenzie He Meian Christopher P. Nelson Rainer Rauramaa Nicole Schupf Robert A. Scott Wayne H.-H. Sheu Alena Stančáková Fumihiko Takeuchi Peter J. van der Most Tibor V. Varga Heming Wang Yajuan Wang Erin B. Ware Stefan Weiß Wanqing Wen Lisa R. Yanek Weihua Zhang Jing Hua Zhao Saima Afaq Tamuno Alfred Najaf Amin Dan E. Arking Tin Aung R. Graham Barr Lawrence F. Bielak Eric Boerwinkle Erwin P. Böttinger Peter S. Braund Jennifer A. Brody Ulrich Broeckel Claudia P. Cabrera Brian E. Cade Yu Caizheng A.M. Campbell Mickaël Canouil Aravinda Chakravarti Ganesh Chauhan Kaare Christensen Massimiliano Cocca Francis S. Collins John Connell

10.1016/j.ajhg.2018.01.015 article EN publisher-specific-oa The American Journal of Human Genetics 2018-02-15
Aldi T. Kraja Chunyu Liu Jessica L. Fetterman Mariaelisa Graff Henri Theil and 95 more C. Charles Gu Lisa R. Yanek Mary F. Feitosa Dan E. Arking Daniel I. Chasman Kristin L. Young Symen Ligthart W. David Hill Stefan Weiß Jian’an Luan Franco Giulianini Ruifang Li‐Gao Fernando Pires Hartwig Shiow J. Lin Lihua Wang Tom G. Richardson Jie Yao Eliana Portilla-Fernández Mohsen Ghanbari Mary K. Wojczynski Wen‐Jane Lee Maria Argos Sebastian M. Armasu Ruteja A. Barve Kathleen A. Ryan Ping An Thomas Baranski Suzette J. Bielinski Donald W. Bowden Ulrich Broeckel Kaare Christensen Audrey Y. Chu Janie Corley Simon R. Cox André G. Uitterlinden Fernando Rivadeneira Cheryl D. Cropp E. Warwick Daw Diana van Heemst Lisa de las Fuentes He Gao Ioanna Tzoulaki Tarunveer S. Ahluwalia Renée de Mutsert Leslie Emery A. Mesut Erzurumluoglu James A. Perry Mao Fu Nita G. Forouhi Zhenglong Gu Yang Hai Sarah E. Harris Gibran Hemani Steven C. Hunt Marguerite R. Irvin Anna Jonsson Anne E. Justice Nicola D. Kerrison Nicholas B. Larson Keng-Hung Lin Latisha Love‐Gregory Rasika A. Mathias Joseph H. Lee Matthias Nauck Raymond Noordam Ken K. Ong James S. Pankow Amit Patki Alison Pattie Astrid Petersmann Qibin Qi Rasmus Ribel‐Madsen Rebecca Rohde Kevin Sandow Theresia M. Schnurr Tamar Sofer John M. Starr Adele M. Taylor Alexander Teumer Nicholas J. Timpson Hugoline G. de Haan Yujie Wang Peter Weeke Christine A. Williams Hongsheng Wu Wei Yang Donglin Zeng Daniel R. Witte Bruce S. Weir Nicholas J. Wareham Henrik Vestergaard Stephen T. Turner Christian Torp‐Pedersen Evie Stergiakouli Wayne Huey‐Herng Sheu

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear (MT-nDNA). In CHARGEmtDNA+ Consortium, we studied associations mtDNA MT-nDNA with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation imputation variants was followed single-variant gene-based...

10.1016/j.ajhg.2018.12.001 article EN cc-by The American Journal of Human Genetics 2018-12-27

Abstract Mendelian randomization (MR) has been increasingly used to strengthen causal inference in observational epidemiology. Methodological developments the field allow detecting and/or adjusting for different potential sources of bias, mainly bias due horizontal pleiotropy (or “off‐target” genetic effects). Another source is nonrandom matching between spouses (i.e., assortative mating). In this study, we performed simulations investigate caused MR by mating. We found that can arise either...

10.1002/gepi.22138 article EN cc-by Genetic Epidemiology 2018-07-03

Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide studies (GWAS) to estimate causal effects modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt direct genetic variants trait interest. One, both or neither exposure and outcome may have been adjusted covariables.We performed a simulation study comprising different scenarios that could motivate covariable adjustment analysed real data...

10.1093/ije/dyaa266 article EN cc-by International Journal of Epidemiology 2021-02-12
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