The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Physical activity, smoking, and genetic predisposition to obesity in people from Pakistan: the PROMIS study
Open accessAbstract
BACKGROUND: Multiple genetic variants have been reliably associated with obesity-related traits in Europeans, but little is known about their associations and interactions with lifestyle factors in South Asians. METHODS: In 16,157 Pakistani adults (8232 controls; 7925 diagnosed with myocardial infarction [MI]) enrolled in the PROMIS Study, we tested whether: a) BMI-associated loci, individually or in aggregate (as a genetic risk score--GRS), are associated with BMI; b) physical activity and smoking modify the association of these loci with BMI. Analyses were adjusted for age, age(2), sex, MI (yes/no), and population substructure. RESULTS: Of 95 SNPs studied here, 73 showed directionally consistent effects on BMI as reported in Europeans. Each additional BMI-raising allele of the GRS was associated with 0.04 (SE = 0.01) kg/m(2) higher BMI (P = 4.5 × 10(-14)). We observed nominal evidence of interactions of CLIP1 rs11583200 (P(interaction) = 0.014), CADM2 rs13078960 (P(interaction) = 0.037) and GALNT10 rs7715256 (P(interaction) = 0.048) with physical activity, and PTBP2 rs11165643 (P(interaction) = 0.045), HIP1 rs1167827 (P(interaction) = 0.015), C6orf106 rs205262 (P(interaction) = 0.032) and GRID1 rs7899106 (P(interaction) = 0.043) with smoking on BMI. CONCLUSIONS: Most BMI-associated loci have directionally consistent effects on BMI in Pakistanis and Europeans. There were suggestive interactions of established BMI-related SNPs with smoking or physical activity.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
This study's findings on correlates of tobacco use align with prior research.
“our study aligns with prior research (30, 38–40).”
From Community-Based Screening, Brief Intervention, and Referral for Treatment for Unhealthy Tobacco Use: Single Arm Study Experience and Implementation Success in Rural and Semi-Rural Settings, South-West Nigeria (2016) · cites this paper as [39]
The Methods section (page unavailable) says the study found an inverse association between smoking and BMI comparable to findings reported elsewhere. That supports alignment for the smoking–BMI association, but the cited paper does not establish that the citing study’s unspecified other correlates of tobacco use align with prior research. (LLM, conf=0.76)
Experimental — accuracy not yet measuredA positive relationship between tobacco use and low socioeconomic status is in agreement with Western findings and findings from other developing nations.
“our result with respect to a positive relationship between tobacco use and low socioeconomic status is in agreement with Western findings (44) as well as findings from other developing nations (30, 38, 39).”
From Community-Based Screening, Brief Intervention, and Referral for Treatment for Unhealthy Tobacco Use: Single Arm Study Experience and Implementation Success in Rural and Semi-Rural Settings, South-West Nigeria (2016) · cites this paper as [39]
The Methods describe measuring tobacco use, and the Results table reports smoking prevalence, but neither relates tobacco use to socioeconomic status. Searches for socioeconomic status, income, education, and related terms found no passage addressing that relationship or comparing it with findings elsewhere. The supplied passages have no page numbers. (LLM, conf=0.73)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Genetic and Environmental Factors in Relative Body Weight and Human Adiposity
Maes, H. H. M., Neale, M. C., & Eaves, L. J. (1997) · Behavior Genetics · doi:10.1023/a:1025635913927 · Cited by 1,515
Flagged first, then by citations
Research works printed but not linked: 28
- Hubert HB, Feinleib M, McNamara PM, Castelli WP. Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation. 1983;67(5):968–77. · DOI · Paper page
- Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med. 2008;359(20):2105–20. doi: 10.1056/NEJMoa0801891 . · DOI · Paper page
- Sullivan PW, Morrato EH, Ghushchyan V, Wyatt HR, Hill JO. Obesity, inactivity, and the prevalence of diabetes and diabetes-related cardiovascular comorbidities in the U.S., 2000–2002. Diabetes Care. 2005;28(7):1599–603. · DOI
- Zhou ZY, Liu YK, Chen HL, Liu F. Body mass index and knee osteoarthritis risk: a dose–response meta-analysis. Obesity (Silver Spring). 2014;22(10):2180–5. doi: 10.1002/oby.20835 . · DOI
- Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9945):766–81. doi: 10.1016/S0140-6736(14)60460-8 . · DOI · Paper page
- Bell CG, Walley AJ, Froguel P. The genetics of human obesity. Nat Rev Genet. 2005;6(3):221–34. doi: 10.1038/nrg1556 . · DOI
- Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–206. doi: 10.1038/nature14177 . · DOI · Paper page
- Ahmad S, Rukh G, Varga TV, Ali A, Kurbasic A, Shungin D, et al. Gene x physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. PLoS Genet. 2013;9(7):e1003607. doi: 10.1371/journal.pgen.1003607 . · DOI
- Ahmad T, Lee IM, Pare G, Chasman DI, Rose L, Ridker PM, et al. Lifestyle interaction with fat mass and obesity-associated (FTO) genotype and risk of obesity in apparently healthy U.S. women. Diabetes Care. 2011;34(3):675–80. doi: 10.2337/dc10-0948 . · DOI
- Andreasen CH, Stender-Petersen KL, Mogensen MS, Torekov SS, Wegner L, Andersen G, et al. Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat accumulation. Diabetes. 2008;57(1):95–101. doi: 10.2337/db07-0910 . · DOI · Paper page
- Franks PW, Jablonski KA, Delahanty LM, McAteer JB, Kahn SE, Knowler WC, et al. Assessing gene-treatment interactions at the FTO and INSIG2 loci on obesity-related traits in the Diabetes Prevention Program. Diabetologia. 2008;51(12):2214–23. doi: 10.1007/s00125-008-1158-x . · DOI
- Kilpelainen TO, Qi L, Brage S, Sharp SJ, Sonestedt E, Demerath E, et al. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children. PLoS Med. 2011;8(11):e1001116. doi: 10.1371/journal.pmed.1001116 . · DOI
- Li S, Zhao JH, Luan J, Ekelund U, Luben RN, Khaw KT, et al. Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study. PLoS Med. 2010;7:8. doi: 10.1371/journal.pmed.1000332 . · DOI
- Qi Q, Li Y, Chomistek AK, Kang JH, Curhan GC, Pasquale LR, et al. Television watching, leisure-time physical activity and the genetic predisposition in relation to body mass index in women and men. Circulation. 2012;126(15):1821–7. doi: 10.1161/circulationaha.112.098061 . · DOI
- Saleheen D, Zaidi M, Rasheed A, Ahmad U, Hakeem A, Murtaza M, et al. The Pakistan Risk of Myocardial Infarction Study: a resource for the study of genetic, lifestyle and other determinants of myocardial infarction in South Asia. Eur J Epidemiol. 2009;24(6):329–38. doi: 10.1007/s10654-009-9334-y . · DOI
- Saleheen D, Alexander M, Rasheed A, Wormser D, Soranzo N, Hammond N, et al. Association of the 9p21.3 locus with risk of first-ever myocardial infarction in Pakistanis: case–control study in South Asia and updated meta-analysis of Europeans. Arterioscler Thromb Vasc Biol. 2010;30(7):1467–73. doi: 10.1161/ATVBAHA.109.197210 . · DOI
- Kooner JS, Saleheen D, Sim X, Sehmi J, Zhang W, Frossard P, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011;43(10):984–9. doi: 10.1038/ng.921 . · DOI
- WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63. doi: 10.1016/S0140-6736(03)15268-3 . · DOI · Paper page
- Delabie J, Shipman R, Bruggen J, De Strooper B, van Leuven F, Tarcsay L, et al. Expression of the novel intermediate filament-associated protein restin in Hodgkin’s disease and anaplastic large-cell lymphoma. Blood. 1992;80(11):2891–6. · DOI
- Nakano A, Takashima S. LKB1 and AMP-activated protein kinase: regulators of cell polarity. Genes Cells. 2012;17(9):737–47. doi: 10.1111/j.1365-2443.2012.01629.x . · DOI
- Nakano A, Kato H, Watanabe T, Min KD, Yamazaki S, Asano Y, et al. AMPK controls the speed of microtubule polymerization and directional cell migration through CLIP-170 phosphorylation. Nat Cell Biol. 2010;12(6):583–90. doi: 10.1038/ncb2060 . · DOI
- Chang G, Xu S, Dhir R, Chandran U, O’Keefe DS, Greenberg NM, et al. Hypoexpression and epigenetic regulation of candidate tumor suppressor gene CADM-2 in human prostate cancer. Clin Cancer Res. 2010;16(22):5390–401. doi: 10.1158/1078-0432.CCR-10-1461 . · DOI
- Pietri T, Easley-Neal C, Wilson C, Washbourne P. Six cadm/SynCAM genes are expressed in the nervous system of developing zebrafish. Dev Dyn. 2008;237(1):233–46. doi: 10.1002/dvdy.21397 . · DOI
- Perrine CL, Ganguli A, Wu P, Bertozzi CR, Fritz TA, Raman J, et al. Glycopeptide-preferring polypeptide GalNAc transferase 10 (ppGalNAc T10), involved in mucin-type O-glycosylation, has a unique GalNAc-O-Ser/Thr-binding site in its catalytic domain not found in ppGalNAc T1 or T2. J Biol Chem. 2009;284(30):20387–97. doi: 10.1074/jbc.M109.017236 . · DOI
- Romanelli MG, Diani E, Lievens PM. New insights into functional roles of the polypyrimidine tract-binding protein. Int J Mol Sci. 2013;14(11):22906–32. doi: 10.3390/ijms141122906 . · DOI
- Legendre-Guillemin V, Metzler M, Lemaire JF, Philie J, Gan L, Hayden MR, et al. Huntingtin interacting protein 1 (HIP1) regulates clathrin assembly through direct binding to the regulatory region of the clathrin light chain. J Biol Chem. 2005;280(7):6101–8. doi: 10.1074/jbc.M408430200 . · DOI
- Li S, Zhao JH, Luan J, Luben RN, Rodwell SA, Khaw KT, et al. Cumulative effects and predictive value of common obesity-susceptibility variants identified by genome-wide association studies. Am J Clin Nutr. 2010;91(1):184–90. doi: 10.3945/ajcn.2009.28403 . · DOI
- Sandholt CH, Sparso T, Grarup N, Albrechtsen A, Almind K, Hansen L, et al. Combined analyses of 20 common obesity susceptibility variants. Diabetes. 2010;59(7):1667–73. doi: 10.2337/db09-1042 . · DOI
Cited by
Sorted by citations
Lasebikan, V. O., & Ola, B. A. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00134 · Cited by 8
Metadata
- Authors
- Ahmad, S., Zhao, W., Renström, F., Rasheed, A., Samuel, M., Zaidi, M., Shah, N., Mallick, N. H., Zaman, K. S., Ishaq, M., Rasheed, S. Z., Memon, F.-U.-R., Hanif, B., Lakhani, M. S., Ahmed, F., Kazmi, S. U., Frossard, P., Franks, P. W., & Saleheen, D.
- Affiliations
- Lund University (SE)
- University of Pennsylvania (US)
- Center for Non-Communicable Diseases (PK)
- COMSATS University Islamabad (PK)
- National Institute of Cardiovascular Diseases (PK)
- Karachi Institute of Heart Diseases (PK)
- Tabba Heart Institute (PK)
- Liaquat National Hospital (PK)
- University of Karachi (PK)
- Harvard University (US)
- Corresponding author
- Franks, Paul W.
- Saleheen, Danish
- ORCID
- Venue
- BMC Medical Genetics
- Published
- 2015-12
- Volume
- 16
- Issue
- 1
- Pages
- 114-114
- ISSN
- 1471-2350 (ISSN-L)
- PMC
- PMC4683724
- OpenAlex
- W2215500817
- Cited by
- 34
- References
- 1
- Citations by year
- 2026: 2 · 2024: 3 · 2023: 5 · 2022: 2 · 2021: 5 · 2020: 2 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 3
- FWCI
- 2.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Genetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Nazarbayev University Repository (Nazarbayev University) (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DiVA at Umeå University (Umeå University) (submittedVersion, other-oa)
- Discovery Research Portal (University of Dundee) (submittedVersion, cc-by)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Wellcome Trust
- Pfizer
- Fogarty International Center
- National Heart, Lung, and Blood Institute
- British Heart Foundation
- Hjärt-Lungfonden
- Svenska Sällskapet för Medicinsk Forskning
- Knut och Alice Wallenbergs Stiftelse
- Novo Nordisk
- Vetenskapsrådet
- Skåne Health Authority
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- obesity, body mass index, genetic susceptibility, polygenic risk score, physical activity, smoking, gene-environment interaction, South Asians, Pakistani adults, myocardial infarction, CADM2, PTBP2, HIP1, genetic variants
- MeSH terms
- Adult, Alleles, Female, Gene Frequency, Genotype, Humans, Male, Middle Aged, Motor Activity, Myocardial Infarction, Obesity, Pakistan, Risk Factors, Smoking, Body Mass Index, Odds Ratio, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
