1. Liu CCI, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol.  2013 Feb 9 (2):106-18.  Doi: 10.1038/nrneurol. 2012.263.
  2. Shankar GM, Li S Mehta TH, Garcia-Munoz A., Shepardson NE, Smith I, Brett FM, Farrell MA, Rowan MJ, Lemere CA Regan CM, Walsh DM, Sabatinis BL, Selkoe DJ (Aug 2008). “Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory”. Nature Medicine. 14 (8): 837-42. dol:10.1038/nm1782.
  3. Prelli F, Castario E., Glenner GG, Frangione B (Aug 1988). “Differences between vascular and plaque core amyloid in Alzheimer’s disease”.  Journal of Neurochemistry.  51 (2):648-51.  Doi:10.1111/j.1471-4159.1988.tb01087.x.
  4. Harold, D. et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat. Genet. 41, 1088-1093 (2009).
  5. Lambert, J.C. et al Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease.   Genet.41, 1094-1099 (2009).

Behavioral Health

  1. Woo JM et al. The association between panic disorder and the L/L genotype of catechol-O-methyltransferase. J Psych Res. 2004; 38:365-370.
  2. Ganji V et al. Serum vitamin D concentrations are related to depression in young adult US population: the Third National Health and Nutrition Examination Survey. Int Arch Med. 2010; 3:29.
  3. Beydoun MA et al. Serum folate, vitamin B-12 and homocysteine and their association with depressive symptoms among US adults. Psychosom Med. 2010; 72:862-873.
  4. Gilbody S et al. Methylenetetrahydrofolate reductase (MTHFR) genetic polymorphisms and psychiatric disorders: a HuGE review. Am J Epidem. 2007; 165:1-13.
  5. Samer CF et al. Applications of CYP450 testing in the clinical setting. Mol Diagn Ther. 2013; 17:165-184.

Bone Health

  1. Estrada K et al. Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet. 2012; 44(5):491–501.
  2. Koller DL et al. Meta-analysis of genome-wide studies identifies WNT16 and ESR1 snps associated with bone mineral density in premenopausal women.  J Bone Miner Res. 2013; 28(3):547–558.
  3. Haussler CA et al. Molecular Mechanisms of Vitamin D Action. Calcified Tissue International 2013; 92:77-98
  4. Kim JH et al. Wnt signaling in bone formation and its therapeutic potential for bone diseases. Ther Adv Musculoskel Dis. 2014; 5(1):13–31.
  5. Bone Health and Osteoporosis: A Report of the Surgeon General. Rockville (MD): Office of the Surgeon General (US): 2004.

Cardiac Health

  1. Wilson PWF. www.UpToDate.com.  Overview of the risk equivalents and established risk factors for cardiovascular disease.
  2. Munir M et al. The association of 9p21-3 locus with coronary atherosclerosis: a systematic review and meta-analysis. Medical Genetics. 2014; 15:1-10.
  3. Karvanen J et al. The Impact of Newly Identified Loci on Coronary Heart Disease, Stroke and total Mortality in the MORGAM Prospective Cohorts. Genetic Epidemiology. 2009; 33:237-246.
  4. Zende PD et al. Apolipoprotein E Gene Polymorphism and Its Effect on Plasma Lipids in Arteriosclerosis. Journal of Clinical and Diagnostic Research. 2013; 7:2149-2152.
  5. Kotze MJ & SJ van Rensburg. Pathology supports genetic testing and treatment of cardiovascular disease in middle age for prevention of Alzheimer’s disease. Metabolic Brain Disease. 2012; 27:255-266.
  6. Szabo GV. The role and importance of gene polymorphisms in the development of atherosclerosis. Interventional Medicine & Applied Science. 2013; 5(1):46-51.
  7. Goracy I et al. C677T polymorphism of the methylenetetrahydrofolate reductase gene and the risk of ischemic stroke in Polish subjects. J Appl Genet. 2009;50(1):63–7.
  8. Daly A. Pharmacogenetics of adverse drug reactions. Genome Medicine. 2013; 5 (5):1-12
  9. Gharani N et al. The Coriell personalized medicine collaborative pharmacogenomics appraisal, evidence scoring and interpretation system. Genome Medicine. 2013; 5 (93):1-19.
  10. Mendis S et al. World Health Organization; 2011. Global atlas on cardiovascular disease prevention and control.

Nutritional Health

  1. Borel P et al. Genetic Variations Involved in Interindividual Variability in Carotenoid Status. Mol Nutr and Food Res. 2012; 56(2):228-40.
  2. Benyamin B et al. Common variants in TMPRSS6 are associated with iron status and erythrocyte volume. Nat Genet. 2009; 41:1173-1175
  3. Malik S et al. Common variants of the vitamin D binding protein gene and adverse health outcomes Crit Rev Clin Lab Sci, 2013; 50(1):1–22.
  4. Tanaka T et al. Genome-wide association study of vitamin B6, vitamin B12, folate, and homocysteine blood concentrations. Am. J. Hum. Genet., 2009; 84:477–482.
  5. Frosst P et al. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet. 1995;10:111–3.

Pain Management

  1. Janicki P. Pharmacogenomics of Pain Management in T.R. Deer et al. (eds.) Comprehensive treatment of chronic pain by medical, interventional, and integrative approaches. 2013; 23-33.
  2. Marucci C et al, Unrecognized drug-drug interactions; a cause of intraoperative cardiac arrest? Anesth Analg. 2006; 102(5):1569-1572.
  3. Phillips KA et al. Potential role of pharmacogenomics in reducing adverse drug reactions: a systematic review. JAMA. 2001; 286(18):2270-2279.
  4. Ingelman-Sunberg M: Pharmacogenetics of cytochrome P450 and its applications in drug therapy: the past, present and future. Trends Pharmacol Sci 2004; 25:193-200.
  5. Galley HF et al. Pharmacogenetics and anesthesiologists. Pharmacogenomics 2005; 6:849-856.
  6. Fagerlund TH and O Braaten. No pain relief from codeine? An introduction to pharmacogenetics. Acta Anaesthesiol Scand 2001; 45:140-149.
  7. www.painmed.org/files/drug-metabolism-chart.pdf

Weight Management

  1. Loos RJF et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nature Genetics. 2008;40:768-775.
  2. Frayling TM et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007; 316: 889–894.
  3. Masuo K et al. Relationships of Adrenoreceptor Polymorphisms with Obesity. Journal of Obesity. 2011.
  4. Bauer F et al. Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference. American Journal of Clinical Nutrition. 2009; 90: 951-959.
  5. Baier LJ et al. An amino acid substitution in the human intestinal fatty acid binding protein is associated with increased fatty acid binding, increased fat oxidation, and insulin resistance. J Clin Invest.1995;95:1281-1287.
  6. Jaaskelainen A et al. Meal Frequencies Modify the Effect of Common Genetic Variants on Body Mass Index in Adolescents of the Northern Finland Bith Cohort 1986. PLOS One. 2013; 8:9: e73802.
  7. Contact Us for a More Extensive Reference List


  1. Frosst P  et al. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet. 1995;10:111–3.
  2. Van der Put NM et al. A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? Am J Hum Genet. 1998; 62(5):1044–51.
  3. Weisberg I et al. A second genetic polymorphism in methylenetetrahydrofolate reductase (MTHFR) associated with decreased enzyme activity. Mol Genet Metab. 1998; 64:169–72.

Celiac – DQ2/DQ8

  1. Megiorni F et al. HLA-DQ and risk gradient for celiac disease. Hum Imm. 2009; 70:55-59.
  2. Megiorni F et al. HLA-DQA1 and HLA-DQB1 in celiac disease predisposition: practical implications of the HLA molecular typing. J of Biomed Sci. 2012; 19:88.
  3. Abadie et al. Integration of genetic and immunological insights into a model of celiac disease pathogenesis. Annu. Rev. Immunol. 2011; 29:493-525.
  4. Kagnoff MF. Celiac disease: pathogenesis of a model immunogenetic disease. J Clin Invest. 2007; 117:41-49.
  5. Megiorni F et al. HLA-DQ and susceptibility to celiac disease: evidence for gender differences and parent-of-origin effects. Am J Gastroenterol. 2008; 103:997-1003.
  6. Karell et al. HLA types in celiac disease patients not carrying the DQA1*05-DQB1*02(DQ2) heterodimer: results from the European genetics cluster of celiac disease. Hum Immunol. 2003; 64:469-477

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