Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews.
Brain diseases
Meta-analysis
Nervous system diseases
Protective factors
Risk factors
Systematic review
Umbrella review
Journal
BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723
Informations de publication
Date de publication:
13 01 2021
13 01 2021
Historique:
received:
13
06
2020
accepted:
26
11
2020
entrez:
13
1
2021
pubmed:
14
1
2021
medline:
24
6
2021
Statut:
epublish
Résumé
The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases. We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified. We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia. We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).
Sections du résumé
BACKGROUND
The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases.
METHODS
We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified.
RESULTS
We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia.
CONCLUSIONS
We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).
Identifiants
pubmed: 33435977
doi: 10.1186/s12916-020-01873-7
pii: 10.1186/s12916-020-01873-7
pmc: PMC7805241
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
6Commentaires et corrections
Type : ErratumIn
Références
Global, regional, and national burden of neurological disorders during 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Neurol. 2017;16(11):877–97.
Aromataris E, Fernandez R, Godfrey CM, Holly C, Khalil H, Tungpunkom P. Summarizing systematic reviews: methodological development, conduct and reporting of an umbrella review approach. Int J Evid Based Healthc. 2015;13(3):132–40.
pubmed: 26360830
Organization WH. World report on ageing and health. Geneva: World Health Organization; 2015.
Finlay BB, Humans C. Microbiome. Are noncommunicable diseases communicable? Science (New York). 2020;367(6475):250–1.
Karikari TK, Charway-Felli A, Höglund K, Blennow K, Zetterberg H. Commentary: global, regional, and national burden of neurological disorders during 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Front Neurol. 2018;9:201.
pubmed: 29651272
pmcid: 5885159
Mentis AA, Dardiotis E, Grigoriadis N, Petinaki E, Hadjigeorgiou GM. Viruses and endogenous retroviruses in multiple sclerosis: from correlation to causation. Acta Neurol Scand. 2017;136(6):606–16.
pubmed: 28542724
Little J, Barakat-Haddad C, Martino R, Pringsheim T, Tremlett H, McKay KA, et al. Genetic variation associated with the occurrence and progression of neurological disorders. Neurotoxicology. 2017;61:243–64.
pubmed: 27713094
Cooper J. Disorders are different from diseases. World Psychiatry. 2004;3(1):24.
pubmed: 16633446
pmcid: 1414656
OECD. Health at a glance 2019: OECD indicators. Paris: OECD Publishing; 2019. https://doi.org/10.1787/4dd50c09-en .
doi: 10.1787/4dd50c09-en
Allen LN, Nicholson BD, Yeung BY, Goiana-da-Silva F. Implementation of non-communicable disease policies: a geopolitical analysis of 151 countries. Lancet Glob Health. 2019;8:e50–e58.
Giovannoni G NA, Scheltens P et al. Time matters. A call to prioritize brain health. 2019;Available from: http://www.oxfordhealthpolicyforum.org/reports/brain-diseases/brain-diseases-report .
Qi X, Wang S, Zhang L, Liu L, Wen Y, Ma M, et al. An integrative analysis of transcriptome-wide association study and mRNA expression profile identified candidate genes for attention-deficit/hyperactivity disorder. Psychiatry Res. 2019;282:112639.
pubmed: 31685286
Liao C, Laporte AD, Spiegelman D, Akçimen F, Joober R, Dion PA, et al. Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes. Nat Commun. 2019;10(1):4450.
pubmed: 31575856
pmcid: 6773763
Gusev A, Mancuso N, Won H, Kousi M, Finucane HK, Reshef Y, et al. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet. 2018;50(4):538–48.
pubmed: 29632383
pmcid: 5942893
Khoury MJ, Bertram L, Boffetta P, Butterworth AS, Chanock SJ, Dolan SM, et al. Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases. Am J Epidemiol. 2009;170(3):269–79.
pubmed: 19498075
pmcid: 2714948
Hadjigeorgiou GM, Kountra PM, Koutsis G, Tsimourtou V, Siokas V, Dardioti M, et al. Replication study of GWAS risk loci in Greek multiple sclerosis patients. Neurol Sci. 2019;40(2):253–60.
pubmed: 30361804
Nalls MA, Pankratz N, Lill CM, Do CB, Hernandez DG, Saad M, et al. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease. Nature Genet. 2014;46(9):989–93.
pubmed: 25064009
Belbasis L, Panagiotou OA, Dosis V, Evangelou E. A systematic appraisal of field synopses in genetic epidemiology: a HuGE review. Am J Epidemiol. 2015;181(1):1–16.
pubmed: 25504025
Khoury MJ, McBride CM, Schully SD, Ioannidis JP, Feero WG, Janssens AC, et al. The Scientific Foundation for personal genomics: recommendations from a National Institutes of Health-Centers for Disease Control and Prevention multidisciplinary workshop. Genet Med. 2009;11(8):559–67.
pubmed: 19617843
pmcid: 2936269
Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, Khoury MJ, et al. Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet. 2008;40(7):827–34.
pubmed: 18583979
Lill CM, Roehr JT, McQueen MB, Kavvoura FK, Bagade S, Schjeide B-MM, et al. Comprehensive research synopsis and systematic meta-analyses in Parkinson’s disease genetics: the PDGene database. PLoS Genet. 2012;8(3):e1002548.
pubmed: 22438815
pmcid: 3305333
Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet. 2007;39(1):17–23.
pubmed: 17192785
Lill CM, Abel O, Bertram L, Al-Chalabi A. Keeping up with genetic discoveries in amyotrophic lateral sclerosis: the ALSoD and ALSGene databases. Amyotroph Lateral Scler. 2011;12(4):238–49.
pubmed: 21702733
Zhang X, Gill D, He Y, Yang T, Li X, Monori G, et al. Non-genetic biomarkers and colorectal cancer risk: umbrella review and evidence triangulation. Cancer Med. 2020;9:4823–35.
Richardson TG, Harrison S, Hemani G, Davey SG. An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome. eLife. 2019;8:e43657.
Patel CJ, Bhattacharya J, Butte AJ. An environment-wide association study (EWAS) on type 2 diabetes mellitus. PLoS One. 2010;5(5):e10746.
pubmed: 20505766
pmcid: 2873978
Patel CJ, Cullen MR, Ioannidis JP, Butte AJ. Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels. Int J Epidemiol. 2012;41(3):828–43.
pubmed: 22421054
pmcid: 3396318
Patel CJ, Rehkopf DH, Leppert JT, Bortz WM, Cullen MR, Chertow GM, et al. Systematic evaluation of environmental and behavioural factors associated with all-cause mortality in the United States national health and nutrition examination survey. Int J Epidemiol. 2013;42(6):1795–810.
pubmed: 24345851
pmcid: 3887569
Patel CJ, Ioannidis JP. Studying the elusive environment in large scale. JAMA. 2014;311(21):2173–4.
pubmed: 24893084
pmcid: 4110965
Patel CJ, Ioannidis JP. Placing epidemiological results in the context of multiplicity and typical correlations of exposures. J Epidemiol Commun Health. 2014;68(11):1096–100.
Patel CJ, Manrai AK. Development of exposome correlation globes to map out environment-wide associations. Pac Symp Biocomput Pac. 2015;20:231–42.
Lawlor DA. Fifteen years of epidemiology in BMC Medicine. BMC Med. 2019;17(1):177.
pubmed: 31543077
pmcid: 6755685
Hou Y, Dan X, Babbar M, Wei Y, Hasselbalch SG, Croteau DL, et al. Ageing as a risk factor for neurodegenerative disease. Nat Rev Neurol. 2019;15(10):565–81.
pubmed: 31501588
Radua J, Ramella-Cravaro V, Ioannidis JP, Reichenberg A, Phiphopthatsanee N, Amir T, et al. What causes psychosis? An umbrella review of risk and protective factors. World Psychiatry. 2018;17(1):49–66.
pubmed: 29352556
pmcid: 5775150
Pruss-Ustun A, Wolf J, Corvalan C, Neville T, Bos R, Neira M. Diseases due to unhealthy environments: an updated estimate of the global burden of disease attributable to environmental determinants of health. J Public Health (Oxford). 2017;39(3):464–75.
Organization WH. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization; 2009.
Fusar-Poli P, Radua J. Ten simple rules for conducting umbrella reviews. Evid Based Ment Health. 2018;21(3):95–100.
pubmed: 30006442
Lakhani CM, Tierney BT, Manrai AK, Yang J, Visscher PM, Patel CJ. Repurposing large health insurance claims data to estimate genetic and environmental contributions in 560 phenotypes. Nat Genet. 2019;51(2):327.
pubmed: 30643253
pmcid: 6358510
Becker L, Oxman A. Chapter 22: Overviews of reviews In: Higgins JPT, Green S (editors), Cochrane Handbook for Systematic Reviews of Interventions Version 510 (updated March 2011) The Cochrane Collaboration, 2011. Available: www.cochrane-handbookorg . 2011. Accessed 26 May 2020.
Ioannidis JP. Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. CMAJ. 2009;181(8):488–93.
pubmed: 19654195
pmcid: 2761440
Ioannidis J. Next-generation systematic reviews: prospective meta-analysis, individual-level data, networks and umbrella reviews. Br J Sports Med. 2017;51(20):1456–8.
pubmed: 28223307
Bellon JA, Moreno-Peral P, Motrico E, Rodriguez-Morejon A, Fernandez A, Serrano-Blanco A, et al. Effectiveness of psychological and/or educational interventions to prevent the onset of episodes of depression: a systematic review of systematic reviews and meta-analyses. Prev Med. 2015;76(Suppl):S22–32.
pubmed: 25445331
Kohler CA, Evangelou E, Stubbs B, Solmi M, Veronese N, Belbasis L, et al. Mapping risk factors for depression across the lifespan: an umbrella review of evidence from meta-analyses and Mendelian randomization studies. J Psychiatr Res. 2018;103:189–207.
pubmed: 29886003
Apostolo J, Cooke R, Bobrowicz-Campos E, Santana S, Marcucci M, Cano A, et al. Predicting risk and outcomes for frail older adults: an umbrella review of frailty screening tools. JBI Database System Rev Implement Rep. 2017;15(4):1154–208.
pubmed: 28398987
pmcid: 5457829
Biondi-Zoccai G, Versaci F, Iskandrian AE, Schillaci O, Nudi A, Frati G, et al. Umbrella review and multivariate meta-analysis of diagnostic test accuracy studies on hybrid non-invasive imaging for coronary artery disease. J Nuclear Cardiol. 2018;27:1744–55.
Papola D, Ostuzzi G, Gastaldon C, Morgano GP, Dragioti E, Carvalho AF, et al. Antipsychotic use and risk of life-threatening medical events: umbrella review of observational studies. Acta Psychiatr Scand. 2019;140:227–43.
Ziff OJ, Samra M, Howard JP, Bromage DI, Ruschitzka F, Francis DP, et al. Beta-blocker efficacy across different cardiovascular indications: an umbrella review and meta-analytic assessment. BMC Med. 2020;18(1):103.
pubmed: 32366251
pmcid: 7199339
Yang T, Li X, Montazeri Z, Little J, Farrington SM, Ioannidis JPA, et al. Gene-environment interactions and colorectal cancer risk: an umbrella review of systematic reviews and meta-analyses of observational studies. Int J Cancer. 2019;145(9):2315–29.
pubmed: 30536881
pmcid: 6767750
Bellou V, Belbasis L, Tzoulaki I, Middleton LT, Ioannidis JPA, Evangelou E. Systematic evaluation of the associations between environmental risk factors and dementia: an umbrella review of systematic reviews and meta-analyses. Alzheimers Dement. 2017;13(4):406–18.
pubmed: 27599208
Bellou V, Belbasis L, Tzoulaki I, Evangelou E, Ioannidis JP. Environmental risk factors and Parkinson's disease: an umbrella review of meta-analyses. Parkinsonism Relat Disord. 2016;23:1–9.
pubmed: 26739246
Belbasis L, Bellou V, Evangelou E, Ioannidis JP, Tzoulaki I. Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurol. 2015;14(3):263–73.
pubmed: 25662901
Theodoratou E, Tzoulaki I, Zgaga L, Ioannidis JP. Vitamin D and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomised trials. BMJ. 2014;348:g2035.
pubmed: 24690624
pmcid: 3972415
Harper S. A future for observational epidemiology: clarity, credibility, transparency. Am J Epidemiol. 2019;188(5):840–5.
pubmed: 30877294
Papatheodorou S. Umbrella reviews: what they are and why we need them. Eur J Epidemiol. 2019;34(6):543–6.
pubmed: 30852716
Yu J-T, Xu W, Tan C-C, Andrieu S, Suckling J, Evangelou E, et al. Evidence-based prevention of Alzheimer’s disease: systematic review and meta-analysis of 243 observational prospective studies and 153 randomised controlled trials. J Neurol Neurosurg Psychiatry. 2020;91:1201–9.
Mentis AF, Kararizou E. Does ageing originate in utero? Biogerontology. 2010;11(6):725–9.
pubmed: 20607402
Heindel JJ, Balbus J, Birnbaum L, Brune-Drisse MN, Grandjean P, Gray K, et al. Developmental origins of health and disease: integrating environmental influences. Endocrinology. 2015;156(10):3416–21.
pubmed: 26241070
pmcid: 4588819
Anstey K, Cherbuin N, Budge M, Young J. Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes Rev. 2011;12(5):e426–e37.
pubmed: 21348917
Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells DW, et al. Evaluation of excess significance bias in animal studies of neurological diseases. PLoS Biol. 2013;11(7):e1001609.
pubmed: 23874156
pmcid: 3712913
Tzoulaki I, Siontis KC, Evangelou E, Ioannidis JP. Bias in associations of emerging biomarkers with cardiovascular disease. JAMA Intern Med. 2013;173(8):664–71.
pubmed: 23529078
Organization WH. Neurological disorders: public health challenges. Geneva: World Health Organization; 2006.
Sergentanis TN, Ntanasis-Stathopoulos I, Tzanninis IG, Gavriatopoulou M, Sergentanis IN, Dimopoulos MA, et al. Meat, fish, dairy products and risk of hematological malignancies in adults - a systematic review and meta-analysis of prospective studies. Leukemia lymphoma. 2019;60:1–13.
Hersi M, Quach P, Wang MD, Gomes J, Gaskin J, Krewski D. Systematic reviews of factors associated with the onset and progression of neurological conditions in humans: a methodological overview. Neurotoxicology. 2017;61:12–8.
pubmed: 27377856
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264–9.
pubmed: 19622511
Shea BJ, Hamel C, Wells GA, Bouter LM, Kristjansson E, Grimshaw J, et al. AMSTAR is a reliable and valid measurement tool to assess the methodological quality of systematic reviews. J Clin Epidemiol. 2009;62(10):1013–20.
pubmed: 19230606
Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.
pubmed: 28935701
pmcid: 5833365
Pieper D, Puljak L, González-Lorenzo M, Minozzi S. Minor differences were found between AMSTAR 2 and ROBIS in the assessment of systematic reviews including both randomized and nonrandomized studies. J Clin Epidemiol. 2019;108:26–33.
pubmed: 30543911
Gates A, Gates M, Duarte G, Cary M, Becker M, Prediger B, et al. Evaluation of the reliability, usability, and applicability of AMSTAR, AMSTAR 2, and ROBIS: protocol for a descriptive analytic study. Syst Rev. 2018;7(1):85.
pubmed: 29898777
pmcid: 6000957
Solmi M, Correll CU, Carvalho AF, Ioannidis JPA. The role of meta-analyses and umbrella reviews in assessing the harms of psychotropic medications: beyond qualitative synthesis. Epidemiol Psychiatric Sci. 2018;27(6):537–42.
Pollock M, Fernandes RM, Hartling L. Evaluation of AMSTAR to assess the methodological quality of systematic reviews in overviews of reviews of healthcare interventions. BMC Med Res Methodol. 2017;17(1):48.
pubmed: 28335734
pmcid: 5364717
Lau J, Ioannidis JP, Schmid CH. Quantitative synthesis in systematic reviews. Ann Intern Med. 1997;127(9):820–6.
pubmed: 9382404
DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clin Trials. 1986;7(3):177–88.
pubmed: 3802833
Posadzki PP, Bajpai R, Kyaw BM, Roberts NJ, Brzezinski A, Christopoulos GI, et al. Melatonin and health: an umbrella review of health outcomes and biological mechanisms of action. BMC Med. 2018;16(1):18.
pubmed: 29397794
pmcid: 5798185
Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10(1):101–29.
Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.
pubmed: 9310563
pmcid: 9310563
Grosso G, Godos J, Galvano F, Giovannucci EL. Coffee, caffeine, and health outcomes: an umbrella review. Annu Rev Nutr. 2017;37:131–56.
pubmed: 28826374
Veronese N, Solmi M, Caruso MG, Giannelli G, Osella AR, Evangelou E, et al. Dietary fiber and health outcomes: an umbrella review of systematic reviews and meta-analyses. Am J Clin Nutr. 2018;107(3):436–44.
pubmed: 29566200
Belbasis L, Bellou V, Evangelou E. Environmental risk factors and amyotrophic lateral sclerosis: an umbrella review and critical assessment of current evidence from systematic reviews and meta-analyses of observational studies. Neuroepidemiology. 2016;46(2):96–105.
pubmed: 26731747
Poole R, Kennedy OJ, Roderick P, Fallowfield JA, Hayes PC, Parkes J. Coffee consumption and health: umbrella review of meta-analyses of multiple health outcomes. BMJ. 2017;359:j5024.
pubmed: 29167102
pmcid: 5696634
Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clin Trials. 2007;4(3):245–53.
pubmed: 17715249
Dinu M, Pagliai G, Casini A, Sofi F. Mediterranean diet and multiple health outcomes: an umbrella review of meta-analyses of observational studies and randomised trials. Eur J Clin Nutr. 2018;72(1):30.
pubmed: 28488692
Beecroft SJ, McLean CA, Delatycki MB, Koshy K, Yiu E, Haliloglu G, et al. Expanding the phenotypic spectrum associated with mutations of DYNC1H1. Neuromuscul Disord. 2017;27(7):607–15.
pubmed: 28554554
Veronese N, Demurtas J, Celotto S, Caruso MG, Maggi S, Bolzetta F, et al. Is chocolate consumption associated with health outcomes? An umbrella review of systematic reviews and meta-analyses. Clin Nutr. 2019;38(3):1101–8.
pubmed: 29903472
Galbete C, Schwingshackl L, Schwedhelm C, Boeing H, Schulze MB. Evaluating Mediterranean diet and risk of chronic disease in cohort studies: an umbrella review of meta-analyses. Eur J Epidemiol. 2018;33(10):909–31.
pubmed: 30030684
pmcid: 6153506
McRae MP. Health benefits of dietary whole grains: an umbrella review of meta-analyses. J Chiropr Med. 2017;16(1):10–8.
pubmed: 28228693
Li X, Meng X, Timofeeva M, Tzoulaki I, Tsilidis KK, Ioannidis JP, Campbell H, Theodoratou E. Serum uric acid levels and multiple health outcomes: umbrella review of evidence from observational studies, randomised controlled trials, and Mendelian randomisation studies. BMJ. 2017;357:j2376. https://doi.org/10.1136/bmj.j2376 .
Serghiou S, Patel CJ, Tan YY, Koay P, Ioannidis JP. Field-wide meta-analyses of observational associations can map selective availability of risk factors and the impact of model specifications. J Clin Epidemiol. 2016;71:58–67.
pubmed: 26415577
Reynolds A, Mann J, Cummings J, Winter N, Mete E, Te Morenga L. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. Lancet (London). 2019;393(10170):434–45.
Krewski D, Barakat-Haddad C, Donnan J, Martino R, Pringsheim T, Tremlett H, et al. Determinants of neurological disease: synthesis of systematic reviews. Neurotoxicology. 2017;61:266–89.
pubmed: 28410962
Abraha I, Rimland JM, Trotta FM, Dell'Aquila G, Cruz-Jentoft A, Petrovic M, et al. Systematic review of systematic reviews of non-pharmacological interventions to treat behavioural disturbances in older patients with dementia. The SENATOR-OnTop series. BMJ Open. 2017;7(3):e012759.
pubmed: 28302633
pmcid: 5372076
Dyer SM, Harrison SL, Laver K, Whitehead C, Crotty M. An overview of systematic reviews of pharmacological and non-pharmacological interventions for the treatment of behavioral and psychological symptoms of dementia. Int Psychogeriatr. 2018;30(3):295–309.
pubmed: 29143695
Gillett G, Tomlinson A, Efthimiou O, Cipriani A. Predicting treatment effects in unipolar depression: a meta-review. Pharmacol Ther. 2020;212:107557.
pubmed: 32437828
Patel B, Legacy J, Hegland KW, Okun MS, Herndon NE. A comprehensive review of the diagnosis and treatment of Parkinson's disease dysphagia and aspiration. Expert Rev Gastroenterol Hepatol. 2020;14(6):411–24.
pubmed: 32657208
Puljak L, Pieper D. Registration of methodological studies, that is, “research-on-research” studies-should it be mandatory? J Clin Epidemiol. 2019;115:35–6.
pubmed: 31279727
Lumley T, Keech A. Meta-meta-analysis with confidence. Lancet. 1995;346(8974):576–7.
pubmed: 7658800
Sáiz-Vazquez O, Puente-Martínez A, Ubillos-Landa S, Pacheco-Bonrostro J, Santabárbara J. Cholesterol and Alzheimer’s disease risk: a Meta-Meta-analysis. Brain Sci. 2020;10(6):386.
pmcid: 7349210
Faggion CM Jr, Diaz KT. Overview authors rarely defined systematic reviews that are included in their overviews. J Clin Epidemiol. 2019;109:70–9.
pubmed: 30684566
Psaltopoulou T, Sergentanis TN, Panagiotakos DB, Sergentanis IN, Kosti R, Scarmeas N. Mediterranean diet, stroke, cognitive impairment, and depression: a meta-analysis. Ann Neurol. 2013;74(4):580–91.
pubmed: 23720230
Bonaccio M, Di Castelnuovo A, Pounis G, Costanzo S, Persichillo M, Cerletti C, et al. High adherence to the Mediterranean diet is associated with cardiovascular protection in higher but not in lower socioeconomic groups: prospective findings from the Moli-sani study. Int J Epidemiol. 2017;46(5):1478–87.
pubmed: 29040542
Liu QP, Wu YF, Cheng HY, Xia T, Ding H, Wang H, et al. Habitual coffee consumption and risk of cognitive decline/dementia: a systematic review and meta-analysis of prospective cohort studies. Nutrition. 2016;32(6):628–36.
pubmed: 26944757
Vercambre MN, Berr C, Ritchie K, Kang JH. Caffeine and cognitive decline in elderly women at high vascular risk. J Alzheimers Dis. 2013;35(2):413–21.
pubmed: 23422357
Kim Y, Je Y, Giovannucci E. Coffee consumption and all-cause and cause-specific mortality: a meta-analysis by potential modifiers. Eur J Epidemiol. 2019;34(8):731–52.
pubmed: 31055709
Stamp L, Dalbeth N. Urate-lowering therapy for asymptomatic hyperuricaemia: a need for caution. Semin Arthritis Rheumatism. 2017;46(4):457–64.
pubmed: 27591828
Yang F, Trolle Lagerros Y, Bellocco R, Adami HO, Fang F, Pedersen NL, et al. Physical activity and risk of Parkinson’s disease in the Swedish National March Cohort. Brain. 2015;138(Pt 2):269–75.
pubmed: 25410713
Iwaki H, Ando R, Miyaue N, Tada S, Tsujii T, Yabe H, et al. One year safety and efficacy of inosine to increase the serum urate level for patients with Parkinson's disease in Japan. J Neurol Sci. 2017;383:75–8.
pubmed: 29246629
Schwarzschild MA, Ascherio A, Beal MF, Cudkowicz ME, Curhan GC, Hare JM, et al. Inosine to increase serum and cerebrospinal fluid urate in Parkinson disease: a randomized clinical trial. JAMA Neurol. 2014;71(2):141–50.
pubmed: 24366103
Tanner CM, Comella CL. When brawn benefits brain: physical activity and Parkinson's disease risk. Brain. 2015;138(Pt 2):238–9.
pubmed: 25627233
pmcid: 4394643
Dardiotis E, Arseniou S, Sokratous M, Tsouris Z, Siokas V, Mentis AA, et al. Vitamin B12, folate, and homocysteine levels and multiple sclerosis: a meta-analysis. Mult Scler Relat Disord. 2017;17:190–7.
pubmed: 29055456
Mentis AA, Dardiotis E, Grigoriadis N, Petinaki E, Hadjigeorgiou GM. Viruses and multiple sclerosis: from mechanisms and pathways to translational research opportunities. Mol Neurobiol. 2017;54(5):3911–23.
pubmed: 28455696
Benedict RH, Weinstock-Guttmam B, Marr K, Valnarov V, Kennedy C, Carl E, et al. Chronic cerebrospinal venous insufficiency is not associated with cognitive impairment in multiple sclerosis. BMC Med. 2013;11:167.
pubmed: 23866161
pmcid: 3734117
Tsivgoulis G, Faissner S, Voumvourakis K, Katsanos AH, Triantafyllou N, Grigoriadis N, et al. “Liberation treatment” for chronic cerebrospinal venous insufficiency in multiple sclerosis: the truth will set you free. Brain Behav. 2015;5(1):3–12.
pubmed: 25722945
Wang M-D, Little J, Gomes J, Cashman NR, Krewski D. Identification of risk factors associated with onset and progression of amyotrophic lateral sclerosis using systematic review and meta-analysis. Neurotoxicology. 2017;61:101–30.
pubmed: 27377857
Pingault J-B, O’reilly PF, Schoeler T, Ploubidis GB, Rijsdijk F, Dudbridge F. Using genetic data to strengthen causal inference in observational research. Nat Rev Genet. 2018;19(9):566.
pubmed: 29872216
van der Mei I, Lucas RM, Taylor BV, Valery PC, Dwyer T, Kilpatrick TJ, et al. Population attributable fractions and joint effects of key risk factors for multiple sclerosis. Mult Scler. 2016;22(4):461–9.
pubmed: 26199349
Olsson T, Barcellos LF, Alfredsson L. Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat Rev Neurol. 2017;13(1):25–36.
pubmed: 27934854
Ascherio A, Munger KL, Lunemann JD. The initiation and prevention of multiple sclerosis. Nat Rev Neurol. 2012;8(11):602–12.
pubmed: 23045241
pmcid: 4467212
Koukouli F, Rooy M, Tziotis D, Sailor KA, O'Neill HC, Levenga J, et al. Nicotine reverses hypofrontality in animal models of addiction and schizophrenia. Nat Med. 2017;23(3):347–54.
pubmed: 28112735
pmcid: 5819879
Papatheodorou SI, Tsilidis KK, Evangelou E, Ioannidis JP. Application of credibility ceilings probes the robustness of meta-analyses of biomarkers and cancer risk. J Clin Epidemiol. 2015;68(2):163–74.
pubmed: 25433443
Machado MO, Veronese N, Sanches M, Stubbs B, Koyanagi A, Thompson T, et al. The association of depression and all-cause and cause-specific mortality: an umbrella review of systematic reviews and meta-analyses. BMC Med. 2018;16(1):112.
pubmed: 30025524
pmcid: 6053830
Wirdefeldt K, Adami HO, Cole P, Trichopoulos D, Mandel J. Epidemiology and etiology of Parkinson’s disease: a review of the evidence. Eur J Epidemiol. 2011;26(Suppl 1):S1–58.
pubmed: 21626386
Mentis A-FA. Social determinants of tobacco use: towards an equity lens approach Tob Prev Cessation. 2017;3(7).
Grimshaw G, Stanton A. Tobacco cessation interventions for young people. Cochrane Database Syst Rev. 2006;4.
Ramagopalan SV, Dobson R, Meier UC, Giovannoni G. Multiple sclerosis: risk factors, prodromes, and potential causal pathways. The Lancet Neurology. 2010;9(7):727–39.
pubmed: 20610348
Mentis A-FA, Pantelidi K, Dardiotis E, Hadjigeorgiou GM, Petinaki E. Precision medicine and global health: the good, the bad, and the ugly. Front Med. 2018;5:67.
McKay KA, Tremlett H. The systematic search for risk factors in multiple sclerosis. Lancet Neurol. 2015;14(3):237–8.
pubmed: 25662899
Paez-Colasante X, Figueroa-Romero C, Sakowski SA, Goutman SA, Feldman EL. Amyotrophic lateral sclerosis: mechanisms and therapeutics in the epigenomic era. Nat Rev Neurol. 2015;11(5):266–79.
pubmed: 25896087
Wang MD, Gomes J, Cashman NR, Little J, Krewski D. A meta-analysis of observational studies of the association between chronic occupational exposure to lead and amyotrophic lateral sclerosis. J Occup Environ Med. 2014;56(12):1235–42.
pubmed: 25479292
pmcid: 4243803
Peters TL, Beard JD, Umbach DM, Allen K, Keller J, Mariosa D, et al. Blood levels of trace metals and amyotrophic lateral sclerosis. Neurotoxicology. 2016;54:119–26.
pubmed: 27085208
pmcid: 5451111
Sauzéat L, Bernard E, Perret-Liaudet A, Quadrio I, Vighetto A, Krolak-Salmon P, et al. Isotopic evidence for disrupted copper metabolism in amyotrophic lateral sclerosis. iScience. 2018;6:264–71.
pubmed: 30240616
pmcid: 6137708
Visser AE, D'Ovidio F, Peters S, Vermeulen RC, Beghi E, Chiò A, et al. Multicentre, population-based, case–control study of particulates, combustion products and amyotrophic lateral sclerosis risk. J Neurol Neurosurg Psychiatry. 2019;90:854–60.
Savica R, Rocca WA, Ahlskog JE. When does Parkinson disease start? Arch Neurol. 2010;67(7):798–801.
pubmed: 20625084
Engelender S, Isacson O. The threshold theory for Parkinson’s disease. Trends Neurosci. 2017;40(1):4–14.
pubmed: 27894611
Beach TG, Adler CH, Sue LI, Vedders L, Lue L, White Iii CL, et al. Multi-organ distribution of phosphorylated alpha-synuclein histopathology in subjects with Lewy body disorders. Acta Neuropathol. 2010;119(6):689–702.
pubmed: 20306269
pmcid: 2866090
Kim S, Kwon SH, Kam TI, Panicker N, Karuppagounder SS, Lee S, et al. Transneuronal propagation of pathologic alpha-synuclein from the gut to the brain models Parkinson’s disease. Neuron. 2019;103:627–641.e7.
Killinger BA, Madaj Z, Sikora JW, Rey N, Haas AJ, Vepa Y, et al. The vermiform appendix impacts the risk of developing Parkinson's disease. Science translational medicine. 2018;10(465):eaar5280.
Hopfner F, Höglinger GU, Kuhlenbäumer G, Pottegård A, Wod M, Christensen K, et al. β-adrenoreceptors and the risk of Parkinson’s disease. Lancet Neurol. 2020;19(3):247–54.
pubmed: 31999942
Byers AL, Yaffe K. Depression and risk of developing dementia. Nat Rev Neurol. 2011;7(6):323–31.
pubmed: 21537355
pmcid: 3327554
Diniz BS, Butters MA, Albert SM, Dew MA, Reynolds CF 3rd. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202(5):329–35.
pubmed: 23637108
pmcid: 3640214
Beydoun MA, Beydoun HA, Gamaldo AA, Teel A, Zonderman AB, Wang Y. Epidemiologic studies of modifiable factors associated with cognition and dementia: systematic review and meta-analysis. BMC Public Health. 2014;14:643.
pubmed: 24962204
pmcid: 4099157
Xu W, Tan L, Wang HF, Jiang T, Tan MS, Tan L, et al. Meta-analysis of modifiable risk factors for Alzheimer’s disease. J Neurol Neurosurg Psychiatry. 2015;86(12):1299–306.
pubmed: 26294005
Fratiglioni L, Wang H-X. Brain reserve hypothesis in dementia. J Alzheimers Dis. 2007;12(1):11–22.
pubmed: 17851191
Frieden TR. SHATTUCK LECTURE: the future of public health. New England J Med. 2015;373(18):1748–54.
Naik Y, Baker P, Ismail SA, Tillmann T, Bash K, Quantz D, et al. Going upstream–an umbrella review of the macroeconomic determinants of health and health inequalities. BMC Public Health. 2019;19(1):1678.
pubmed: 31842835
pmcid: 6915896
Laaser U, Dorey S, Nurse J. A plea for global health action bottom-up. Front Public Health. 2016;4:241.
pubmed: 27843892
pmcid: 5086808
Ham C. Improving the performance of health services: the role of clinical leadership. Lancet. 2003;361(9373):1978–80.
pubmed: 12801754
Reich MR, Takemi K, Roberts MJ, Hsiao WC. Global action on health systems: a proposal for the Toyako G8 summit. Lancet. 2008;371(9615):865–9.
Rasooly D, Ioannidis JPA, Khoury MJ, Patel CJ. Family history-wide association study (“FamWAS”) for identifying clinical and environmental risk factors for common chronic diseases. Am J Epidemiol. 2019;.
Chrousos GP, Kino T. Glucocorticoid signaling in the cell. Expanding clinical implications to complex human behavioral and somatic disorders. Ann N Y Acad Sci. 2009;1179:153–66.
pubmed: 19906238
pmcid: 2791367
Yu K, Lv J, Qiu G, Yu C, Guo Y, Bian Z, et al. Cooking fuels and risk of all-cause and cardiopulmonary mortality in urban China: a prospective cohort study. Lancet Glob Health. 2020;8(3):e430–e9.
pubmed: 31972151
pmcid: 7031698
Rosengren A, Smyth A, Rangarajan S, Ramasundarahettige C, Bangdiwala SI, AlHabib KF, et al. Socioeconomic status and risk of cardiovascular disease in 20 low-income, middle-income, and high-income countries: the Prospective Urban Rural Epidemiologic (PURE) study. Lancet Glob Health. 2019;7(6):e748–e60.
pubmed: 31028013
Lilford R, Kyobutungi C, Ndugwa R, Sartori J, Watson SI, Sliuzas R, et al. Because space matters: conceptual framework to help distinguish slum from non-slum urban areas. BMJ Glob Health. 2019;4(2):e001267.
pubmed: 31139443
pmcid: 6509608
Willett WC, Ludwig DS. Milk and health. N Engl J Med. 2020;382(7):644–54.
pubmed: 32053300
Berman MG, Kardan O, Kotabe HP, Nusbaum HC, London SE. The promise of environmental neuroscience. Nat Hum Behav. 2019;3(5):414–7.
pubmed: 31089299
O'Sullivan JW, Muntinga T, Grigg S, Ioannidis JPA. Prevalence and outcomes of incidental imaging findings: umbrella review. Bmj. 2018;361:k2387.
pubmed: 29914908
pmcid: 6283350
Goldman JS. Predictive genetic counseling for neurodegenerative diseases: past, present, and future. Cold Spring Harb Perspect Med. 2020;10(7):a036525. https://doi.org/10.1101/cshperspect.a036525 . PMID: 31548223; PMCID: PMC7328452.
Kamoen O, Maqueda V, Yperzeele L, Pottel H, Cras P, Vanhooren G, et al. Stroke coach: a pilot study of a personal digital coaching program for patients after ischemic stroke. Acta Neurol Belg. 2020;120(1):91–7.
pubmed: 31701472
Leonenko G, Sims R, Shoai M, Frizzati A, Bossu P, Spalletta G, et al. Polygenic risk and hazard scores for Alzheimer’s disease prediction. Ann Clin Transl Neurol. 2019;6(3):456–65.
pubmed: 30911569
pmcid: 6414493
WHO. Risk reduction of cognitive decline and dementia France: 2019 Available from https://www.who.int/mental_health/neurology/dementia/guidelines_risk_reduction/en/ . Accessed 26 May 2020.
Armon C, Traynor BJ. High BMI is associated with low ALS risk: what does it mean? Neurology. 2019;93(5):189–91.
pubmed: 31243070
Husain M, Roiser JP. Neuroscience of apathy and anhedonia: a transdiagnostic approach. Nat Rev Neurosci. 2018;19(8):470–84.
pubmed: 29946157
Romer AL, Knodt AR, Sison ML, Ireland D, Houts R, Ramrakha S, et al. Replicability of structural brain alterations associated with general psychopathology: evidence from a population-representative birth cohort. Mol Psychiatry. 2019; https://doi.org/10.1038/s41380-019-0621-z .
Ritchie K, Carriere I, Ritchie CW, Berr C, Artero S, Ancelin ML. Designing prevention programmes to reduce incidence of dementia: prospective cohort study of modifiable risk factors. BMJ. 2010;341:c3885.
pubmed: 20688841
pmcid: 2917002
Silagy CA, Middleton P, Hopewell S. Publishing protocols of systematic reviews: comparing what was done to what was planned. JAMA. 2002;287(21):2831–4.
pubmed: 12038926
Baron R, Ferriero DM, Frisoni GB, Bettegowda C, Gokaslan ZL, Kessler JA, et al. Neurology—the next 10 years. Nat Rev Neurol. 2015;11(11):658.
pubmed: 26503922
Prasad V. Our best weapons against cancer are not magic bullets. Nature. 2020;577(7791):451.
pubmed: 31965108
Silberholz J, Bertsimas D, Vahdat L. Clinical benefit, toxicity and cost of metastatic breast cancer therapies: systematic review and meta-analysis. Breast Cancer Res Treat. 2019;176(3):535–43. https://doi.org/10.1007/s10549-019-05208-w .
Wang MD, Little J. How credible are meta-analyses of risk factors based on observational studies for amyotrophic lateral sclerosis a new insight from an umbrella review. Neuroepidemiology. 2016;46(4):271–2.
pubmed: 27064494
Prüss-Ustün A, van Deventer E, Mudu P, Campbell-Lendrum D, Vickers C, Ivanov I, et al. Environmental risks and non-communicable diseases. Bmj. 2019;364:l265.
pubmed: 30692085
pmcid: 6348403
Organization WH, Canada PHAo, Canada CPHAo. Preventing chronic diseases: a vital investment. Geneva: World Health Organization; 2005.
Perkins JM, Subramanian S, Christakis NA. Social networks and health: a systematic review of sociocentric network studies in low-and middle-income countries. Soc Sci Med. 2015;125:60–78.
pubmed: 25442969
Lahiri DK, Maloney B, Bayon BL, Chopra N, White FA, Greig NH, et al. Transgenerational latent early-life associated regulation unites environment and genetics across generations. Epigenomics. 2016;8(3):373–87.
pubmed: 26950428
pmcid: 4864244
Mentis AFA. To what extent are Greek children exposed to the risk of a lifelong, intergenerationally transmitted poverty? Poverty Public Policy. 2015;7(4):357–81.
Lahiri DK, Maloney B. The “LEARn”(latent early-life associated regulation) model integrates environmental risk factors and the developmental basis of Alzheimer’s disease, and proposes remedial steps. Exp Gerontol. 2010;45(4):291–6.
pubmed: 20064601
pmcid: 2881328
Wells JC. The capacity–load model of non-communicable disease risk: understanding the effects of child malnutrition, ethnicity and the social determinants of health. Eur J Clin Nutr. 2018;72(5):688–97.
pubmed: 29748656
Trichopoulos D. Hypothesis: does breast cancer originate in utero? Lancet. 1990;335(8695):939–40.
pubmed: 1970028
Turner MC, Vineis P, Seleiro E, Dijmarescu M, Balshaw D, Bertollini R, et al. EXPOsOMICS: final policy workshop and stakeholder consultation. BMC Public Health. 2018;18(1):260.
pubmed: 29448939
pmcid: 5815236
Charmandari E, Achermann JC, Carel JC, Soder O, Chrousos GP. Stress response and child health. Science Signal. 2012;5(248):mr1.
Chrousos GP. Stress and disorders of the stress system. Nat Rev Endocrinol. 2009;5(7):374.
pubmed: 19488073
Chrousos GP, Kino T. Glucocorticoid action networks and complex psychiatric and/or somatic disorders. Stress. 2007;10(2):213–9.
pubmed: 17514590
Michelson D, Stone L, Galliven E, Magiakou MA, Chrousos GP, Sternberg EM, et al. Multiple sclerosis is associated with alterations in hypothalamic-pituitary-adrenal axis function. J Clin Endocrinol Metab. 1994;79(3):848–53.
pubmed: 8077372
Gassen NC, Chrousos GP, Binder EB, Zannas AS. Life stress, glucocorticoid signaling, and the aging epigenome: implications for aging-related diseases. Neurosci Biobehav Rev. 2017;74(Pt B):356–65.
pubmed: 27343999
Moher D, Klassen TP, Schulz KF, Berlin JA, Jadad AR, Liberati A. What contributions do languages other than English make on the results of meta-analyses? J Clin Epidemiol. 2000;53(9):964–72.
pubmed: 11004423
Vink A, Hanser S. Music-based therapeutic interventions for people with dementia: a mini-review. Medicines. 2018;5(4):109.
pmcid: 6313334
He Y, Li X, Gasevic D, Brunt E, McLachlan F, Millenson M, et al. Statins and multiple noncardiovascular outcomes: umbrella review of meta-analyses of observational studies and randomized controlled trials. Ann Intern Med. 2018;169(8):543–53.
pubmed: 30304368
Xy H, Lin J, Ww G. Risk factors and therapies in vascular diseases: an umbrella review of updated systematic reviews and meta-analyses. J Cell Physiol. 2019;234(6):8221–32.
Li N, Wu X, Zhuang W, Xia L, Chen Y, Zhao R, et al. Soy and isoflavone consumption and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomized trials in humans. Mol Nutr Food Res. 2020;64(4):1900751.
Dragioti E, Solmi M, Favaro A, Fusar-Poli P, Dazzan P, Thompson T, et al. Association of antidepressant use with adverse health outcomes: a systematic umbrella review. JAMA Psychiatry. 2019;76(12):1241–55.
pubmed: 31577342
pmcid: 6777224
Seitz MW, Listl S, Bartols A, Schubert I, Blaschke K, Haux C, et al. Current knowledge on correlations between highly prevalent dental conditions and chronic diseases: an umbrella review [dataset]. 2019.
Ehsan A, Klaas HS, Bastianen A, Spini D. Social capital and health: a systematic review of systematic reviews. SSM-Popul Health. 2019;8:100425.
pubmed: 31431915
pmcid: 6580321
Wan Q, Li N, Du L, Zhao R, Yi M, Xu Q, et al. Allium vegetable consumption and health: an umbrella review of meta-analyses of multiple health outcomes. Food Sci Nutr. 2019;7(8):2451–70.
pubmed: 31428334
pmcid: 6694434
Grabovac I, Veronese N, Stefanac S, Haider S, Jackson SE, Koyanagi A, et al. Human immunodeficiency virus infection and diverse physical health outcomes: an umbrella review of meta-analyses of observational studies. Cli Infect Dis. 2020;70(9):1809–15.
Marventano S, Godos J, Tieri M, Ghelfi F, Titta L, Lafranconi A, et al. Egg consumption and human health: an umbrella review of observational studies. Int J Food Sci Nutr. 2020;71(3):325–31.
pubmed: 31379223
Khan SU, Khan MU, Riaz H, Valavoor S, Zhao D, Vaughan L, et al. Effects of nutritional supplements and dietary interventions on cardiovascular outcomes: an umbrella review and evidence map. Ann Intern Med. 2019;171(3):190–8.
pubmed: 31284304
pmcid: 7261374
Yi M, Wu X, Zhuang W, Xia L, Chen Y, Zhao R, et al. Tea consumption and health outcomes: umbrella review of meta-analyses of observational studies in humans. Mol Nutr Food Res. 2019;63(16):1900389.
Godos J, Tieri M, Ghelfi F, Titta L, Marventano S, Lafranconi A, et al. Dairy foods and health: an umbrella review of observational studies. Int J Food Sci Nutr. 2020;71(2):138–51.
pubmed: 31199182
Smith L, Luchini C, Demurtas J, Soysal P, Stubbs B, Hamer M, et al. Telomere length and health outcomes: an umbrella review of systematic reviews and meta-analyses of observational studies. Ageing Res Rev. 2019;51:1–10.
pubmed: 30776454
Veronese N, Demurtas J, Pesolillo G, Celotto S, Barnini T, Calusi G, et al. Magnesium and health outcomes: an umbrella review of systematic reviews and meta-analyses of observational and intervention studies. Eur J Nutr. 2020;59(1):263–72.
pubmed: 30684032
Angelino D, Godos J, Ghelfi F, Tieri M, Titta L, Lafranconi A, et al. Fruit and vegetable consumption and health outcomes: an umbrella review of observational studies. Int J Food Sci Nutr. 2019;70(6):652–67.
pubmed: 30764679
Wallace TC, Bailey RL, Blumberg JB, Burton-Freeman B, Chen CO, Crowe-White KM, et al. Fruits, vegetables, and health: a comprehensive narrative, umbrella review of the science and recommendations for enhanced public policy to improve intake. Crit Rev Food Sci Nutr. 2020;60(13):2174–211.
pubmed: 31267783
Kelly MM, Griffith PB. The influence of preterm birth beyond infancy: umbrella review of outcomes of adolescents and adults born preterm. J Am Assoc Nurse Pract. 2020;32(8):555–62.
pubmed: 31651585
Chiavaroli L, Viguiliouk E, Nishi SK, Blanco Mejia S, Rahelić D, Kahleová H, et al. DASH dietary pattern and cardiometabolic outcomes: an umbrella review of systematic reviews and meta-analyses. Nutrients. 2019;11(2):338.
pmcid: 6413235
Viguiliouk E, Glenn AJ, Nishi SK, Chiavaroli L, Seider M, Khan T, et al. Associations between dietary pulses alone or with other legumes and cardiometabolic disease outcomes: an umbrella review and updated systematic review and meta-analysis of prospective cohort studies. Adv Nutr. 2019;10(Supplement_4):S308–S19.
pubmed: 31728500
pmcid: 6855952
Fewell Z, Davey Smith G, Sterne JA. The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study. Am J Epidemiol. 2007;166(6):646–55.
pubmed: 17615092
Kleinberg S, Hripcsak G. A review of causal inference for biomedical informatics. J Biomed Informatics. 2011;44(6):1102–12.
Patel CJ, Burford B, Ioannidis JPA. Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations. J Clin Epidemiol. 2015;68(9):1046–58.
pubmed: 26279400
pmcid: 4555355
Schooling CM, Jones HE. Clarifying questions about “risk factors”: predictors versus explanation. Emerg Themes Epidemiol. 2018;15(1):10.
pubmed: 30116285
pmcid: 6083579
Mentis AFA, Papavassiliou AG. Correcting “insertion-deletion mutations” in medical terminology. J Cell Mol Med. 2018;22(12):6408.
pubmed: 30187998
pmcid: 6237611
Smith GD, Ebrahim S. Epidemiology—is it time to call it a day? Oxford: Oxford University Press; 2001.
Lodi S, Phillips A, Lundgren J, Logan R, Sharma S, Cole SR, et al. Effect estimates in randomized trials and observational studies: comparing apples with apples. Am J Epidemiol. 2019;188(8):1569–77.
pubmed: 31063192
pmcid: 6670045
Pinnock H, Parke HL, Panagioti M, Daines L, Pearce G, Epiphaniou E, et al. Systematic meta-review of supported self-management for asthma: a healthcare perspective. BMC Med. 2017;15(1):64.
pubmed: 28302126
pmcid: 5356253
Heslehurst N, Brown H, Pemu A, Coleman H, Rankin J. Perinatal health outcomes and care among asylum seekers and refugees: a systematic review of systematic reviews. BMC Med. 2018;16(1):89.
pubmed: 29890984
pmcid: 5996508
Chesney E, Goodwin GM, Fazel S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry. 2014;13(2):153–60.
pubmed: 24890068
pmcid: 4102288
Garcia-Rudolph A, Sanchez-Pinsach D, Salleras EO, Tormos JM. Subacute stroke physical rehabilitation evidence in activities of daily living outcomes: a systematic review of meta-analyses of randomized controlled trials. Medicine. 2019;98(8):e14501.
pubmed: 30813152
pmcid: 6408050
Donnan J, Walsh S, Fortin Y, Gaskin J, Sikora L, Morrissey A, et al. Factors associated with the onset and progression of neurotrauma: a systematic review of systematic reviews and meta-analyses. Neurotoxicology. 2017;61:234–41.
pubmed: 27006002
Chalkias A, Ioannidis JPA. Interventions to improve cardiopulmonary resuscitation: a review of meta-analyses and future agenda. Critical care (London). 2019;23(1):210.
Paquette M, Alotaibi AM, Nieuwlaat R, Santesso N, Mbuagbaw L. A meta-epidemiological study of subgroup analyses in cochrane systematic reviews of atrial fibrillation. Syst Rev. 2019;8(1):241.
pubmed: 31653275
pmcid: 6814034
Hazar N, Seddigh L, Rampisheh Z, Nojomi M. Population attributable fraction of modifiable risk factors for Alzheimer disease: a systematic review of systematic reviews. Iran J Neurol. 2016;15(3):164–72.
pubmed: 27648178
pmcid: 5027152
Martinic MK, Pieper D, Glatt A, Puljak L. Definition of a systematic review used in overviews of systematic reviews, meta-epidemiological studies and textbooks. BMC Med Res Methodol. 2019;19(1):203.
Zhou X, Menche J, Barabási A-L, Sharma A. Human symptoms–disease network. Nat Commun. 2014;5:4212.
Menche J, Sharma A, Kitsak M, Ghiassian SD, Vidal M, Loscalzo J, et al. Uncovering disease-disease relationships through the incomplete interactome. Science. 2015;347(6224):1257601.
pubmed: 25700523
pmcid: 4435741
Adam D. The gene-based hack that is revolutionizing epidemiology. Nature. 2019;576(7786):196–9.
pubmed: 31822846
Elliott JH, Synnot A, Turner T, Simmonds M, Akl EA, McDonald S, et al. Living systematic review: 1. Introduction—the why, what, when, and how. J Clin Epidemiol. 2017;91:23–30.
pubmed: 28912002
Belbasis L, Bellou V, Evangelou E, Tzoulaki I. Environmental factors and risk of multiple sclerosis: findings from meta-analyses and Mendelian randomization studies. Mult Scler. 2020;26(4):397–404.
pubmed: 32249718
Macdonald H, Loder E, Abbasi K. Living systematic reviews at the BMJ. BMJ. 2020;370:m2925.
pubmed: 32732314