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Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar-sweetened beverages (SSBs) and 100% fruit juices. Low-calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991-2014; N=3146) and Generation Three (2002-2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed-effect linear regression models were used to examine 4-year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low (<1 serving per month) SSB consumption was associated with a greater mean decrease in high-density lipoprotein cholesterol (β±standard error -1.6±0.4 mg/dL; P trend <0.0001) and increase in triglyceride (β±standard error: 4.4±2.2 mg/dL; P trend =0.003) concentrations. Long-term regular SSB consumers also had a higher incidence of high triglyceride (hazard ratio, 1.52; 95% CI, 1.03-2.25) compared with low consumers. Although recent regular low-calorie sweetened beverage consumers had a higher incidence of high non-high-density lipoprotein cholesterol (hazard ratio, 1.40; 95% CI, 1.17-1.69) and low-density lipoprotein cholesterol (hazard ratio, 1.27; 95% CI, 1.05-1.53) concentrations compared with low consumers, cumulative average intakes of low-calorie sweetened beverages were not associated with changes in non-high-density lipoprotein cholesterol, low-density lipoprotein cholesterol concentrations, or incident dyslipidemias. Conclusions SSB intake was associated with adverse changes in high-density lipoprotein cholesterol and triglyceride concentrations, along with a higher risk of incident dyslipidemia, suggesting that increased SSB consumption may contribute to the development of dyslipidemia.

Objective: We sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program., Methods: We performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants., Results: We detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10 -8 ) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10 -8 ). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10 -4 ) and in 17q25 for WMH (rs7214628, p = 2.0 × 10 -3 ) were confirmed. Gene-based tests detected associations ( p ≤ 2.3 × 10 -6 ) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- ( UNC5D ) and Parkinson disease-associated genes ( GBA ). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways., Conclusions: Whole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings., (Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Background: Vitamin D is associated with lung function in cross-sectional studies, and vitamin D inadequacy is hypothesized to play a role in the pathogenesis of chronic obstructive pulmonary disease. Further data are needed to clarify the relation between vitamin D status, genetic variation in vitamin D metabolic genes, and cross-sectional and longitudinal changes in lung function in healthy adults., Methods: We estimated the association between serum 25-hydroxyvitamin D [25(OH)D] and cross-sectional forced expiratory volume in the first second (FEV1) in Framingham Heart Study (FHS) Offspring and Third Generation participants and the association between serum 25(OH)D and longitudinal change in FEV1 in Third Generation participants using linear mixed-effects models. Using a gene-based approach, we investigated the association between 241 SNPs in 6 select vitamin D metabolic genes in relation to longitudinal change in FEV1 in Offspring participants and pursued replication of these findings in a meta-analyzed set of 4 independent cohorts., Results: We found a positive cross-sectional association between 25(OH)D and FEV1 in FHS Offspring and Third Generation participants (P=0.004). There was little or no association between 25(OH)D and longitudinal change in FEV1 in Third Generation participants (P=0.97). In Offspring participants, the CYP2R1 gene, hypothesized to influence usual serum 25(OH)D status, was associated with longitudinal change in FEV1 (gene-based P<0.05). The most significantly associated SNP from CYP2R1 had a consistent direction of association with FEV1 in the meta-analyzed set of replication cohorts, but the association did not reach statistical significance thresholds (P=0.09)., Conclusions: Serum 25(OH)D status was associated with cross-sectional FEV1, but not longitudinal change in FEV1. The inconsistent associations may be driven by differences in the groups studied. CYP2R1 demonstrated a gene-based association with longitudinal change in FEV1 and is a promising candidate gene for further studies.

Objective: Common variants at the 2q36.3-IRS1 locus are associated with insulin resistance (IR), type 2 diabetes (T2D) and coronary artery disease (CAD) in large-scale association studies. We tested the hypothesis that variants at this locus are associated with subclinical atherosclerosis traits., Methods: We studied 2740 Framingham Heart Study participants (54.9% women; mean age 57.8 years) with measures of coronary artery or abdominal aortic calcium, internal and common carotid intima-media thickness, and ankle-brachial index (ABI). We tested 1) four SNPs previously shown to be associated with IR (rs2972146, rs2943650), T2D (rs2943641) or CAD (rs2943634) and 2) any SNP at 2q36.3-IRS1, for association with subclinical atherosclerosis traits, adjusting for atherosclerosis risk factors. We set type 1 error rate for test 1) as 0.05/5 traits = P < 0.01, and for test 2) as 0.05 divided by the effective number of independent tests, divided by 5 for the number of traits analyzed., Results: We found no association between the four known SNPs and subclinical atherosclerosis, but identified one SNP (rs10167219, r(2) with rs2943634 = 0.07) at 2q36.3 that was significantly associated with ABI (corrected P = 0.009). However, rs10167219 was not associated with ABI (P = 0.70) in 35,404 participants in a published ABI association study., Conclusion: Common variants at the 2q36.3-IRS1 locus were not associated with subclinical atherosclerosis traits in this study which was adequately powered to find associations with moderate effect size. Although IR and T2D may be mechanistically linked to CAD via subclinical atherosclerosis, an alternate mechanism for the IR-T2D-CAD associations at 2q36.3-IRS1 must be postulated., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Objective: The RETN gene encodes the adipokine resistin. Associations of RETN with plasma resistin levels, type 2 diabetes, and related metabolic traits have been inconsistent. Using comprehensive linkage disequilibrium mapping, we genotyped tag single nucleotide polymorphisms (SNPs) in RETN and tested associations with plasma resistin levels, risk of diabetes, and glycemic traits., Research Design and Methods: We examined 2,531 Framingham Offspring Study participants for resistin levels, glycemic phenotypes, and incident diabetes over 28 years of follow-up. We genotyped 21 tag SNPs that capture common (minor allele frequency >0.05) or previously reported SNPs at r2 > 0.8 across RETN and its flanking regions. We used sex- and age-adjusted linear mixed-effects models (with/without BMI adjustment) to test additive associations of SNPs with traits, adjusted Cox proportional hazards models accounting for relatedness for incident diabetes, and generated empirical P values (Pe) to control for type 1 error., Results: Four tag SNPs (rs1477341, rs4804765, rs1423096, and rs10401670) on the 3' side of RETN were strongly associated with resistin levels (all minor alleles associated with higher levels, Pe<0.05 after multiple testing correction). rs10401670 was also associated with fasting plasma glucose (Pe = 0.02, BMI adjusted) and mean glucose over follow-up (Pe = 0.01; BMI adjusted). No significant association was observed for adiposity traits. On meta-analysis, the previously reported association of SNP -420C/G (rs1862513) with resistin levels remained significant (P = 0.0009) but with high heterogeneity across studies (P < 0.0001)., Conclusions: SNPs in the 3' region of RETN are associated with resistin levels, and one of them is also associated with glucose levels, although replication is needed.

Objective: A recent meta-analysis demonstrated a nominal association of the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) K-->Q missense single nucleotide polymorphism (SNP) at position 121 with type 2 diabetes. We set out to confirm the association of ENPP1 K121Q with hyperglycemia, expand this association to insulin resistance traits, and determine whether the association stems from K121Q or another variant in linkage disequilibrium with it., Research Design and Methods: We characterized the haplotype structure of ENPP1 and selected 39 tag SNPs that captured 96% of common variation in the region (minor allele frequency > or =5%) with an r(2) value > or =0.80. We genotyped the SNPs in 2,511 Framingham Heart Study participants and used age- and sex-adjusted linear mixed effects (LME) models to test for association with quantitative metabolic traits. We also examined whether interaction between K121Q and BMI affected glycemic trait levels., Results: The Q allele of K121Q (rs1044498) was associated with increased fasting plasma glucose (FPG), A1C, fasting insulin, and insulin resistance by homeostasis model assessment (HOMA-IR; all P = 0.01-0.006). Two noncoding SNPs (rs7775386 and rs7773477) demonstrated similar associations, but LME models indicated that their effects were not independent from K121Q. We found no association of K121Q with obesity, but interaction models suggested that the effect of the Q allele on FPG and HOMA-IR was stronger in those with a higher BMI (P = 0.008 and 0.01 for interaction, respectively)., Conclusions: The Q allele of ENPP1 K121Q is associated with hyperglycemia and insulin resistance in whites. We found an adiposity-SNP interaction, with a stronger association of K121Q with diabetes-related quantitative traits in people with a higher BMI.

Objective: To use genome-wide fixed marker arrays and improved analytical tools to detect genetic associations with type 2 diabetes in a carefully phenotyped human sample., Research Design and Methods: A total of 1,087 Framingham Heart Study (FHS) family members were genotyped on the Affymetrix 100K single nucleotide polymorphism (SNP) array and examined for association with incident diabetes and six diabetes-related quantitative traits. Quality control filters yielded 66,543 SNPs for association testing. We used two complementary SNP selection strategies (a "lowest P value" strategy and a "multiple related trait" strategy) to prioritize 763 SNPs for replication. We genotyped a subset of 150 SNPs in a nonoverlapping sample of 1,465 FHS unrelated subjects and examined all 763 SNPs for in silico replication in three other 100K and one 500K genome-wide association (GWA) datasets., Results: We replicated associations of 13 SNPs with one or more traits in the FHS unrelated sample (16 expected under the null); none of them showed convincing in silico replication in 100K scans. Seventy-eight SNPs were nominally associated with diabetes in one other 100K GWA scan, and two (rs2863389 and rs7935082) in more than one. Twenty-five SNPs showed promising associations with diabetes-related traits in 500K GWA data; one of them (rs952635) replicated in FHS. Five previously reported associations were confirmed in our initial dataset., Conclusions: The FHS 100K GWA resource is useful for follow-up of genetic associations with diabetes-related quantitative traits. Discovery of new diabetes genes will require larger samples and a denser array combined with well-powered replication strategies.

Vascular inflammation plays a central role in atherosclerosis and inflammatory biomarkers predict risk of cardiovascular disease (CVD). Thus, finding genes that influence systemic levels of inflammatory biomarkers may provide insights into genetic determinants of vascular inflammation and CVD. We conducted variance-component linkage analyses of blood levels of four biomarkers of vascular inflammation [C-reactive protein (CRP), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), soluble intercellular adhesion molecule-1 (sICAM-1)] in 304 extended families from the Framingham Heart Study, using data from a 10cM genome scan. We computed p-values by a permutation approach. Heritability estimates ranged from 14% (IL-6) to 44% (MCP-1) after log transforming and adjusting for covariates. Significant linkage to MCP-1 was found on chromosome 1 (LOD=4.27 at 186cM; genome-wide p=0.005), in a region containing inflammatory candidate genes such as SELE, SELP (E- and P-selectin) and CRP. Other linkage peaks with LOD scores >2 were found for MCP-1 on chromosome 1 (LOD=2.04 at 16cM; LOD=2.34 at 70cM) and chromosome 17 (LOD=2.44 at 22cM) and for sICAM-1 on chromosome 1 at 229cM (LOD=2.09) less than 5cM from the interleukin-10 (IL10) gene. Multiple genes on chromosome 1 may influence inflammatory biomarker levels and may have a potential role in development of CVD.