Search

Background Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. Methods The population studied for this investigation included 660 individuals from the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ) in PRECISE and a validated semi-quantitative FFQ in the CaPS. Interaction analyses were performed by including the interaction term in the linear regression model adjusted for age, body mass index, sex and country. Results There was no association between dietary factors and blood lipids after Bonferroni correction and adjustment for confounding factors in either cohort. In the PRECISE study, after correction for multiple testing, there was a statistically significant association of the APOE haplotype (rs7412 and rs429358; E2, E3, and E4) and APOE tagSNP rs445925 with total cholesterol (P = 4 × 10− 4 and P = 0.003, respectively). Carriers of the E2 allele had lower total cholesterol concentration (5.54 ± 0.97 mmol/L) than those with the E3 (5.98 ± 1.05 mmol/L) (P = 0.001) and E4 (6.09 ± 1.06 mmol/L) (P = 2 × 10− 4) alleles. The association of APOE haplotype (E2, E3, and E4) and APOE SNP rs445925 with total cholesterol (P = 2 × 10− 6 and P = 3 × 10− 4, respectively) was further replicated in the CaPS. Additionally, significant association was found between APOE haplotype and APOE SNP rs445925 with low density lipoprotein cholesterol in CaPS (P = 4 × 10− 4 and P = 0.001, respectively). After Bonferroni correction, none of the cohorts showed a statistically significant SNP-diet interaction on lipid outcomes. Conclusion In summary, our findings from the two cohorts confirm that genetic variations at the APOE locus influence plasma total cholesterol concentrations, however, the gene-diet interactions on lipids require further investigation in larger cohorts. Electronic supplementary material The online version of this article (10.1186/s12944-018-0744-2) contains supplementary material, which is available to authorized users.

Joan IA Campbell-Tofte,1 Per Mølgaard,2 Kaj Winther11Department of Clinical Biochemistry, Frederiksberg University Hospital, Frederiksberg, Denmark; 2Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, DenmarkAbstract: Diabetes is a metabolic disorder arising from complex interactions between multiple genetic and/or environmental factors. The characteristic high blood sugar levels result from either lack of the hormone insulin (type 1 diabetes, T1D), or because body tissues do not respond to the hormone (type 2 diabetes, T2D). T1D patients currently need exogenous insulin for life, while for T2D patients who do not respond to diet and exercise regimes, oral anti-diabetic drugs (OADs) and sometimes insulin are administered to help keep their blood glucose as normal as possible. As neither the administration of insulin nor OADs is curative, many patients develop tissue degenerative processes that result in life-threatening diabetes comorbidities. Several surveys of medicinal plants used as anti-diabetic agents amongst different peoples have been published. Some of this interest is driven by the ongoing diabetes pandemic coupled with the inadequacies associated with the current state of-the-art care and management of the syndrome. However, there is a huge cleft between traditional medicine and modern (Western) medicine, with the latter understandably demanding meaningful and scientific validation of anecdotal evidence for acceptance of the former. The main problems for clinical evaluation of medicinal plants with promising anti-diabetic properties reside both with the complexity of components of the plant materials and with the lack of full understanding of the diabetes disease etiology. This review is therefore focused on why research activities involving an integration of Systems Biology-based technologies of pharmacogenomics, metabolomics, and bioinformatics with standard clinical data, should be used for cost-effective validation of the safety and anti-diabetic efficacy of promising medicinal plants. The application of such approaches to studying entire mixtures of plant materials will ensure proper elucidation of novel therapies with improved mechanisms of action, as well as facilitate a personalized clinical use of medicinal plants as anti-diabetic agents.Keywords: medicinal plants, anti-diabetes therapy, natural products, systems biology, 'omics technologies, drug discovery

Hypothyroidism is often detected, and subsequently treated, due to health-related quality of life (HRQL) considerations. However, disease specific HRQL impairments and changes following thyroid hormone substitution have not previously been assessed with a validated disease specific instrument. Eighty-one patients with autoimmune hypothyroidism answered disease-specific (ThyPRO) and generic (SF-36) HRQL questionnaires before and 6 months after initiation of levothyroxine substitution. ThyPRO consists of 85 items that assess physical, mental, and social domains of functioning and well-being in patients with benign thyroid disorders. The items are summarized in 13 scales. SF-36 consists of 36 items summarized in 8 scales. NormativeThyPRO(n= 739) and SF-36 (n = 6,638) data were collected from representative general population samples. Score differences between patients and the general population and associations between thyroid stimulating hormone (TSH) and HRQL were assessed with multivariate linear regression analyses adjusted for age, gender, comorbidity and educational status. Changes following treatment were analyzed with the paired t-test. All analyses were adjusted for multiple testing (Hochberg method). Prior to treatment, patients' ThyPRO scores were impaired, compared to the general population, on all 9 comparable scales ( p-values