👤 Aldi T Kraja

The plasma levels of high-density lipoprotein cholesterol (HDL) have an inverse relationship to the risks of atherosclerosis and cardiovascular disease (CVD), and have also been associated with longevity. We sought to identify novel loci for HDL that could potentially provide new insights into biological regulation of HDL metabolism in healthy-longevous subjects. We performed a genome-wide association (GWA) scan on HDL using a mixed model approach to account for family structure using kinship coefficients. A total of 4114 subjects of European descent (480 families) were genotyped at ~2.3 million SNPs and ~38 million SNPs were imputed using the 1000 Genome Cosmopolitan reference panel in MACH. We identified novel variants near-NLRP1 (17p13) associated with an increase of HDL levels at genome-wide significant level (p < 5.0E-08). Additionally, several CETP (16q21) and ZNF259-APOA5-A4-C3-A1 (11q23.3) variants associated with HDL were found, replicating those previously reported in the literature. A possible regulatory variant upstream of NLRP1 that is associated with HDL in these elderly Long Life Family Study (LLFS) subjects may also contribute to their longevity and health. Our NLRP1 intergenic SNPs show a potential regulatory function in Encyclopedia of DNA Elements (ENCODE); however, it is not clear whether they regulate NLRP1 or other more remote gene. NLRP1 plays an important role in the induction of apoptosis, and its inflammasome is critical for mediating innate immune responses. Nlrp1a (a mouse ortholog of human NLRP1) interacts with SREBP-1a (17p11) which has a fundamental role in lipid concentration and composition, and is involved in innate immune response in macrophages. The NLRP1 region is conserved in mammals, but also has evolved adaptively showing signals of positive selection in European populations that might confer an advantage. NLRP1 intergenic SNPs have also been associated with immunity/inflammasome disorders which highlights the biological importance of this chromosomal region. Show less

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation. Show less

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants. Show less

The fibric acid derivative, fenofibrate (FF) has been used in the US since 1998 to manage patients with dyslipidemia. Typical changes in serum lipids as result a of FF treatment include clinically important mean reductions of serum triglycerides (TG) by a mean change of -93.7 mg/dL (-39.3%), increases of high density lipoprotein cholesterol (HDLC) by +5.5 mg/dL (+12.4%), and reductions in low density lipoprotein cholesterol (LDLC) by -17.9 mg/dL (-12.3%). The greatest reductions in serum TG are usually observed in subjects with elevated baseline TGs including those with the metabolic syndrome (MetS). Although statins remain the mainstay of therapy for most dyslipidemic patients, their combined use with FF would be expected to address residual risk resulting from less than optimal TG and HDLC levels in such patients. Clinical trials examining the cardiovascular benefits of FF alone or combined with statins have produced mixed results. These observations underscore our lack of understanding of which patients may benefit from FF therapy and which do not. Although FF's basic mechanism of action is known to involve PPAR-alpha agonist activity resulting in altered transcription of several genes, the actual genetic bases for variability in lipid response is poorly understood. Studies, such as our GOLDN study and others designed to better understand the genetic determinants of variability in the response to FF treatment and lipid levels. As a result several important genetic determinants of lipid levels have been identified. For example, in the GOLDN study SNPs from different genes were significantly associated with baseline lipid levels before treatment (APOA5- rs662799, rs3135506; APOC3- rs5128, rs2854117, rs4520); APOA4- rs5104; PPARA- rs9626730, rs135543, rs11703495; LPL- rs1801177), after treatment PPARA- rs11708495; LPL- rs1801177, and appeared to modulate overall response to FF treatment (NOS3- rs1799983). In this article, we will review the literature leading up to the contemporary use of FF as an agent to manage patients with dyslipidemia and focus on emerging understanding of the genetic variability in response to FF treatment. On the basis of the available evidence, we conclude that FF is of benefit in the treatment of dyslipidemia, especially among those with MetS. However, more work is needed to specifically identify which individuals derive a benefit from FF administration in terms of clinical outcomes and which do not - particularly in the context of type 2 diabetes. Show less

Platelet function mediates both beneficial and harmful effects on human health, but few genes are known to contribute to variability in this process. We tested association of 2.5 million SNPs with platelet aggregation responses to three agonists (ADP, epinephrine and collagen) in two cohorts of European ancestry (NShow less

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity. Show less