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         'metadata': {'text': 'gene interaction and high predictive value, PLoS One 3 (5) (2008) e2031,doi:10.1371/journal.pone.0002031 .\n[107] M. van Hoek, A. Dehghan, J.C. Witteman, C.M. van Duijn, A.G. Uitterlinden, B.A.\nOostra, A. Hofman, E.J. Sijbrands, A.C. Janssens, Predicting type 2 diabetes based\non polymorphisms from genome-wide association studies: a population-based\nstudy, Diabetes 57 (11) (Nov 2008) 3122 3128.\n[108] Q. Lu, Y. Song, X. Wang, S. Won, Y. Cui, R.C. Elston, The effect of multiple genetic', 
            'title': '2011 - Annotating individual human genomes.pdf', 
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            'text': 'variants in predicting the risk of type 2 diabetes, BMC Proc 3 (Suppl 7) (Dec 15\n2009) S49.\n[109] K. Miyake, W. Yang, K. Hara, K. Yasuda, Y. Horikawa, H. Osawa, H. Furuta, et al.,\nConstruction of a prediction model for type 2 diabetes mellitus in the Japanese\npopulation based on 11 genes with strong evidence of the association, J. Hum.\nGenet. 54 (4) (Apr 2009) 236 241 [Epub 2009 Feb 27].\n[110] P.J. Talmud, A.D. Hingorani, J.A. Cooper, M.G. Marmot, E.J. Brunner, M. Kumari, M.', 'title': '2011 - Annotating individual human genomes.pdf', 
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        {'id': 'bb2a67ec-135b-5d55-b33d-74b1dc085685', 'score': 1.0, 'metadata': {'text': 'type 2 diabetes risk, Diabetes 57 (11) (Nov 2008) 3129 3135.\n[103] Q. Lu, R.C. Elston, Using the optimal receiver operating characteristic curve to\ndesign a predictive genetic test, exempli ed with type 2 diabetes, Am. J. Hum.\nGenet. 82 (3) (Mar 2008) 641 651.\n[104] V. Lyssenko, A. Jonsson, P. Almgren, N. Pulizzi, B. Isomaa, T. Tuomi, G. Berglund, D.\nAltshuler, P. Nilsson, L. Groop, Clinical risk factors, DNA variants, and the\ndevelopment of type 2 diabetes, N. Engl. J. Med. 359 (21) (Nov 20 2008)', 'title': '2011 - Annotating individual human genomes.pdf', 'version': 'v0', 'chunk_order': 158, 'document_id': 'f7b5d738-3f0b-5074-9c21-f6b443b4e07f', 'extraction_id': '80d78615-8424-5478-a01b-73e220bc0345', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': '11fc663d2-2833-51e7-ae6a-55b007a6e27c', 'score': 1.0, 'metadata': {'text': 'insulin resistance, hypertension, and dyslipidemia (Obesity Education Initiative Expert Panel,  1998 ). Insulin resist-ance increases with age, and the incidence of diabetes rises sharply in the elderly (American Diabetes Association,  2010a ). \n In a few patients, genetic mutations appear to be associ-\nated with T2D (Roche  et al.  ,  2005 ; American Diabetes \nAssociation,  2010a ). For example, recent work using the DPP data has led to the identi  cation of 27 single nucle-', 'title': '2012 - Systems Biology Approaches to Nutrition.pdf', 'version': 'v0', 'chunk_order': 9596, 'document_id': '6955478b-950d-5d29-b24c-3a5ca656f3ae', 'extraction_id': 'eb3de845-98db-505c-bb7f-c0f3259875fc', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': 'bb55a705-7399-550e-8285-07c33654b909', 'score': 1.0, 'metadata': {'text': '19. Permutt MA, Wasson J, Cox N: Genetic epidemiology of diabe-\ntes.  J Clin Invest  2005, 115:1431-1439.\n20. Barroso I: Genetics of Type 2 diabetes.   Diabet Med  2005,\n22:517-535.\n21. Parikh H, Groop L: Candidate genes for type 2 diabetes.   Rev\nEndocr Metab Disord  2004, 5:151-176.\n22. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN: Meta-\nanalysis of genetic association studies supports a contribu-\ntion of common variants to su sceptibility to common dis-\nease.   Nat Genet  2003, 33:177-182.', 'title': '2006 - β2-adrenergic receptor and UCP3 variants modulate the relationship between age and type 2 diabetes mellitus.pdf', 'version': 'v0', 'chunk_order': 86, 'document_id': '0ea34c04-5d09-5a32-89a7-c3add179927a', 'extraction_id': 'acf69ed8-c7b0-5d9f-8005-de020c9cf699', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': '9bff43c0-fd12-572e-9996-24957edd17d2', 'score': 1.0, 'metadata': {'text': 'insulin-dependent diabetes and schizophrenia, twin studies have demon-strated the existence of a significant genetic component (Kyvik et al., 1995;Plomin et al., 1994). Genetic factors also influence cardiovascular diseaseswhich occur in early or midlife, while for cardiovascular diseases occur-ring late in life there is little evidence of a genetic effect (Marenberg et al.,1994). Dementia has a very strong genetic component, not only withregard to early-onset monogenic types but also to late-onset', 'title': '2001 - Demography in the age of genomics.pdf', 'version': 'v0', 'chunk_order': 452, 'document_id': '0f07fa43-feb6-5656-b7e7-b8faa86f5623', 'extraction_id': '5f24a851-1de6-5b6e-8230-2da08806b01a', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': '2df84ccc-0d32-582e-bda6-9cd46bee5378', 'score': 1.0, 'metadata': {'text': 'Three categories of increased risk of developing diabetes \nare currently recognized by the ADA: an FPG between 5.6 and 6.9   mmol/L (100 and 125   mg/dL), de  ned as having \nimpaired fasting glucose (IFG); a 2 - h OGTT between 7.8 and 11   mmol/L (140 and 199   mg/dL), de  ned as having \nimpaired glucose tolerance (IGT); an A1C between 5.7 and 6.4% with values between 6.0 and 6.4 considered very high risk (American Diabetes Association,  2010a ). \n It is estimated that approximately one - fourth of indi-', 'title': '2012 - Systems Biology Approaches to Nutrition.pdf', 'version': 'v0', 'chunk_order': 9590, 'document_id': '6955478b-950d-5d29-b24c-3a5ca656f3ae', 'extraction_id': 'eb3de845-98db-505c-bb7f-c0f3259875fc', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': 'ff30f187-d5c3-5d01-8026-0588a77e9f44', 'score': 1.0, 'metadata': {'text': '20 90 D20S451 0.006 10.7 5.4 (34) 8.42 5.4 (61) 0.30 (long duration)\nInteraction with age at diagnosis of diabetes\n19 1 D1S1665 0.004 37.4 8.1 (66) 41.2 8.3 (81) 0.23 (early onset)\n2 159 D2S1399/D2S1353 0.023 40.8 8.2 (53) 38.8 8.5 (94) 0.16 (late onset)\n3 135 D3S2460 0.036 37.7 8.6 (66) 41.0 8.0 (81) 0.16 (early onset)\n4 146 D4S1625 0.005 37.9 7.4 (52) 40.4 8.9 (95) 0.23 (early onset)\n65 5 D6S2427 0.024 38.0 7.8 (70) 40.9 8.8 (77) 0.18 (early onset)', 'title': '2004 - A genome scan for diabetic nephropathy in African Americans.pdf', 'version': 'v0', 'chunk_order': 64, 'document_id': '5798fb6b-b3e6-57c4-9823-5428853dbfa1', 'extraction_id': '01ec7832-8a80-5f5e-aa26-3648f572c4a1', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': '57dc1ee5-4252-52c3-92cb-e2ac36cdc4d6', 'score': 1.0, 'metadata': {'text': 'prevention, even though there are great concerns about how such\ninformation will be perceived and utilized [68]. Recent studies in\ndiabetes and cardiovascular disease suggest that the addition of\npreviously associated genetic risk loci in clinical risk models of those\ndiseases increases both discriminative and predictive accuracy, albeit\nonly marginally. Typically, the strongest predictors of disease onset\nare known clinical risk factors such as body mass index, age, or', 'title': '2011 - Annotating individual human genomes.pdf', 'version': 'v0', 'chunk_order': 66, 'document_id': 'f7b5d738-3f0b-5074-9c21-f6b443b4e07f', 'extraction_id': 'c17c74fa-12a3-5072-bb48-c179055db14d', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}, {'id': 'ff801099-e737-57b1-91af-a4cea20adb87', 'score': 1.0, 'metadata': {'text': 'and sex, weight for height greater than the 85th percentile, or weight greater than 120% of ideal for height) who also have any two of the following risk factors: family history of T2D (  rst -  or second - degree relative), maternal history \nof diabetes or GDM during child  s gestation, member of high - risk race/ethnicity group (Native American, African -(40   in) in men is considered an indicator of increased', 'title': '2012 - Systems Biology Approaches to Nutrition.pdf', 'version': 'v0', 'chunk_order': 9595, 'document_id': '6955478b-950d-5d29-b24c-3a5ca656f3ae', 'extraction_id': 'eb3de845-98db-505c-bb7f-c0f3259875fc', 'associatedQuery': 'List any factors that help predict early onset of diabetes.'}}], 'kg_search_results': None},

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