Segregation of LIPG, CETP, and GALNT2 mutations in Caucasian families with extremely high HDL cholesterol

Gene–gene interaction detection with deep learning

The extent to which genetic interactions affect observed phenotypes is generally unknown because current interaction detection approaches only consider simple interactions between top SNPs of genes. We introduce an open-source framework for increasing the power of interaction detection by considering all SNPs within a selected set of genes and complex interactions between them, beyond only the currently considered multiplicative relationships. In brief, the relation between SNPs and a phenotype is captured by a neural network, and the interactions are quantified by Shapley scores between hidden nodes, which are gene representations that optimally combine information from the corresponding SNPs. Additionally, we design a permutation procedure tailored for neural networks to assess the significance of interactions, which outperformed existing alternatives on simulated datasets with complex interactions, and in a cholesterol study on the UK Biobank it detected nine interactions which replicated on an independent FINRISK dataset.

Role of GALNT2 on Insulin Sensitivity, Lipid Metabolism and Fat Homeostasis

O-linked glycosylation, the greatest form of post-translational modifications, plays a key role in regulating the majority of physiological processes. It is, therefore, not surprising that abnormal O-linked glycosylation has been related to several human diseases. Recently, GALNT2, which encodes the GalNAc-transferase 2 involved in the first step of O-linked glycosylation, has attracted great attention as a possible player in many highly prevalent human metabolic diseases, including atherogenic dyslipidemia, type 2 diabetes and obesity, all clustered on the common ground of insulin resistance. Data available both in human and animal models point to GALNT2 as a molecule that shapes the risk of the aforementioned abnormalities affecting diverse protein functions, which eventually cause clinically distinct phenotypes (a typical example of pleiotropism). Pathways linking GALNT2 to dyslipidemia and insulin resistance have been partly identified, while those for type 2 diabetes and obesity are yet to be understood. Here, we will provide a brief overview on the present knowledge on GALNT2 function and dysfunction and propose novel insights on the complex pathogenesis of the aforementioned metabolic diseases, which all impose a heavy burden for patients, their families and the entire society.

Genetics and regulation of HDL metabolism

The inverse association between plasma HDL cholesterol (HDL-C) levels and risk for cardiovascular disease (CVD) has been demonstrated by numerous epidemiological studies. However, efforts to reduce CVD risk by pharmaceutically manipulating HDL-C levels failed and refused the HDL hypothesis. HDL-C levels in the general population are highly heterogeneous and are determined by a combination of genetic and environmental factors. Insights into the causes of HDL-C heterogeneity came from the study of monogenic HDL deficiency syndromes but also from genome wide association and Μendelian randomization studies which revealed the contribution of a large number of loci to low or high HDL-C cases in the general or in restricted ethnic populations. Furthermore, HDL-C levels in the plasma are under the control of transcription factor families acting primarily in the liver including members of the hormone nuclear receptors (PPARs, LXRs, HNF-4) and forkhead box proteins (FOXO1-4) and activating transcription factors (ATFs). The effects of certain lipid lowering drugs used today are based on the modulation of the activity of specific members of these transcription factors. During the past decade, the roles of small or long non-coding RNAs acting post-transcriptionally on the expression of HDL genes have emerged and provided novel insights into HDL regulation and new opportunities for therapeutic interventions. In the present review we summarize recent progress made in the genetics and the regulation (transcriptional and post-transcriptional) of HDL metabolism.

Endothelial lipase mediates efficient lipolysis of triglyceride-rich lipoproteins

Triglyceride-rich lipoproteins (TRLs) are circulating reservoirs of fatty acids used as vital energy sources for peripheral tissues. Lipoprotein lipase (LPL) is a predominant enzyme mediating triglyceride (TG) lipolysis and TRL clearance to provide fatty acids to tissues in animals. Physiological and human genetic evidence support a primary role for LPL in hydrolyzing TRL TGs. We hypothesized that endothelial lipase (EL), another extracellular lipase that primarily hydrolyzes lipoprotein phospholipids may also contribute to TRL metabolism. To explore this, we studied the impact of genetic EL loss-of-function on TRL metabolism in humans and mice. Humans carrying a loss-of-function missense variant in LIPG, p.Asn396Ser (rs77960347), demonstrated elevated plasma TGs and elevated phospholipids in TRLs, among other lipoprotein classes. Mice with germline EL deficiency challenged with excess dietary TG through refeeding or a high-fat diet exhibited elevated TGs, delayed dietary TRL clearance, and impaired TRL TG lipolysis in vivo that was rescued by EL reconstitution in the liver. Lipidomic analyses of postprandial plasma from high-fat fed Lipg-/- mice demonstrated accumulation of phospholipids and TGs harboring long-chain polyunsaturated fatty acids (PUFAs), known substrates for EL lipolysis. In vitro and in vivo, EL and LPL together promoted greater TG lipolysis than either extracellular lipase alone. Our data positions EL as a key collaborator of LPL to mediate efficient lipolysis of TRLs in humans and mice.

Unraveling the Complexity of HDL Remodeling: On the Hunt to Restore HDL Quality

Increasing evidence has cast doubt over the HDL-cholesterol hypothesis. The complexity of the HDL particle and its proven susceptibility to remodel has paved the way for intense molecular investigation. This state-of-the-art review discusses the molecular changes in HDL particles that help to explain the failure of large clinical trials intending to interfere with HDL metabolism, and details the chemical modifications and compositional changes in HDL-forming components, as well as miRNA cargo, that render HDL particles ineffective. Finally, the paper discusses the challenges that need to be overcome to shed a light of hope on HDL-targeted approaches.

Identification and characterization of a rare variant in apolipoprotein A-IV, p.(V336M), and evaluation of HDL functionality in a Greek cohort with extreme HDL cholesterol levels

High-Density Lipoprotein cholesterol (HDL-C) levels do not correlate well with Coronary Artery Disease (CAD) risk, while HDL functionality affects atherogenesis and is a better prognostic marker for CAD. Often, the extreme HDL-C levels have a multigenic origin. Here, we searched for single-nucleotide polymorphisms (SNPs) in ten genes of HDL metabolism in a Greek cohort with very low (<10th percentile, n = 13) or very high (>90th percentile, n = 21) HDL-C. We also evaluated the association between HDL-C levels, HDL functionality (anti-oxidant capacity) and CAD in the subjects of this cohort. Individuals with low HDL-C levels had higher triglyceride levels, lower apoA-I levels, decreased HDL anti-oxidant capacity and higher incidence of CAD compared with individuals with control or high HDL-C levels. With next generation sequencing we identified 18 exonic SNPs in 6 genes of HDL metabolism and for selected amino acid changes we performed computer-aided structural analysis and modeling. A previously uncharacterized rare apolipoprotein A-IV variant, apoA-IV [V336M], present in a subject with low HDL-C (14 mg/dL) and CAD, was expressed in recombinant form and structurally and functionally characterized. ApoA-IV [V336M] had similar α-helical content to WT apoA-IV but displayed a small thermodynamic stabilization by chemical unfolding analysis. ApoA-IV [V336M] was able to associate with phospholipids but presented reduced kinetics compared to WT apoA-IV. Overall, we identified a rare apoA-IV variant in a subject with low HDL levels and CAD with altered biophysical and phospholipid binding properties and showed that subjects with very low HDL-C presented with HDL dysfunction and higher incidence of CAD in a Greek cohort.

Polygenic influences on dyslipidemias

PURPOSE OF REVIEW

Rare large-effect genetic variants underlie monogenic dyslipidemias, whereas common small-effect genetic variants - single nucleotide polymorphisms (SNPs) - have modest influences on lipid traits. Over the past decade, these small-effect SNPs have been shown to cumulatively exert consistent effects on lipid phenotypes under a polygenic framework, which is the focus of this review.

RECENT FINDINGS

Several groups have reported polygenic risk scores assembled from lipid-associated SNPs, and have applied them to their respective phenotypes. For lipid traits in the normal population distribution, polygenic effects quantified by a score that integrates several common polymorphisms account for about 20-30% of genetic variation. Among individuals at the extremes of the distribution, that is, those with clinical dyslipidemia, the polygenic component includes both rare variants with large effects and common polymorphisms: depending on the trait, 20-50% of susceptibility can be accounted for by this assortment of genetic variants.

SUMMARY

Accounting for polygenic effects increases the numbers of dyslipidemic individuals who can be explained genetically, but a substantial proportion of susceptibility remains unexplained. Whether documenting the polygenic basis of dyslipidemia will affect outcomes in clinical trials or prospective observational studies remains to be determined.

HDL Cholesterol Metabolism and the Risk of CHD: New Insights from Human Genetics

PURPOSE OF REVIEW

Elevated high-density lipoprotein cholesterol levels in the blood (HDL-C) represent one of the strongest epidemiological surrogates for protection against coronary heart disease (CHD), but recent human genetic and pharmacological intervention studies have raised controversy about the causality of this relationship. Here, we review recent discoveries from human genome studies using new analytic tools as well as relevant animal studies that have both addressed, and in some cases, fueled this controversy.

RECENT FINDINGS

Methodologic developments in genotyping and sequencing, such as genome-wide association studies (GWAS), exome sequencing, and exome array genotyping, have been applied to the study of HDL-C and risk of CHD in large, multi-ethnic populations. Some of these efforts focused on population-wide variation in common variants have uncovered new polymorphisms at novel loci associated with HDL-C and, in some cases, CHD risk. Other efforts have discovered loss-of-function variants for the first time in genes previously implicated in HDL metabolism through common variant studies or animal models. These studies have allowed the genetic relationship between these pathways, HDL-C and CHD to be explored in humans for the first time through analysis tools such as Mendelian randomization. We explore these discoveries for selected key HDL-C genes CETP, LCAT, LIPG, SCARB1, and novel loci implicated from GWAS including GALNT2, KLF14, and TTC39B. Recent human genetics findings have identified new nodes regulating HDL metabolism while reshaping our current understanding of known candidate genes to HDL and CHD risk through the study of critical variants across model systems. Despite their effect on HDL-C, variants in many of the reviewed genes were found to lack any association with CHD. These data collectively indicate that HDL-C concentration, which represents a static picture of a very dynamic and heterogeneous metabolic milieu, is unlikely to be itself causally protective against CHD. In this context, human genetics represent an extremely valuable tool to further explore the biological mechanisms regulating HDL metabolism and investigate what role, if any, HDL plays in the pathogenesis of CHD.

Polygenic determinants in extremes of high-density lipoprotein cholesterol

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia.

Identification of a novel LMF1 nonsense mutation responsible for severe hypertriglyceridemia by targeted next-generation sequencing

BACKGROUND

Severe hypertriglyceridemia (HTG) may result from mutations in genes affecting the intravascular lipolysis of triglyceride (TG)-rich lipoproteins.

OBJECTIVE

The aim of this study was to develop a targeted next-generation sequencing panel for the molecular diagnosis of disorders characterized by severe HTG.

METHODS

We developed a targeted customized panel for next-generation sequencing Ion Torrent Personal Genome Machine to capture the coding exons and intron/exon boundaries of 18 genes affecting the main pathways of TG synthesis and metabolism. We sequenced 11 samples of patients with severe HTG (TG>885 mg/dL-10 mmol/L): 4 positive controls in whom pathogenic mutations had previously been identified by Sanger sequencing and 7 patients in whom the molecular defect was still unknown.

RESULTS

The customized panel was accurate, and it allowed to confirm genetic variants previously identified in all positive controls with primary severe HTG. Only 1 patient of 7 with HTG was found to be carrier of a homozygous pathogenic mutation of the third novel mutation of LMF1 gene (c.1380C>G-p.Y460X). The clinical and molecular familial cascade screening allowed the identification of 2 additional affected siblings and 7 heterozygous carriers of the mutation.

CONCLUSIONS

We showed that our targeted resequencing approach for genetic diagnosis of severe HTG appears to be accurate, less time consuming, and more economical compared with traditional Sanger resequencing. The identification of pathogenic mutations in candidate genes remains challenging and clinical resequencing should mainly intended for patients with strong clinical criteria for monogenic severe HTG.

Analysis to Estimate Genetic Variations in the Idarubicin-Resistant Derivative MOLT-3

Gene alterations are a well-established mechanism leading to drug resistance in acute leukemia cells. A full understanding of the mechanisms of drug resistance in these cells will facilitate more effective chemotherapy. In this study, we investigated the mechanism(s) of drug resistance in the human acute leukemia cell line MOLT-3 and its idarubicin-resistant derivative MOLT-3/IDR through complete mitochondrial and nuclear DNA analyses. We identified genetic differences between these two cell lines. The ND3 mutation site (p.Thr61Ile) in the mitochondrial DNA sequence was unique to MOLT-3/IDR cells. Moreover, we identified five candidate genes harboring genetic alterations, including GALNT2, via CGH array analysis. Sequencing of the GALNT2 exon revealed a G1716K mutation present within the stop codon in MOLT-3/IDR cells but absent from MOLT-3 cells. This mutation led to an additional 18 amino acids in the protein encoded by GALNT2. Using real-time PCR, we determined an expression value for this gene of 0.35. Protein structure predictions confirmed a structural change in GALNT2 in MOLT-3/IDR cells that corresponded to the site of the mutation. We speculate that this mutation may be related to idarubicin resistance.

Association of the variants and haplotypes in the DOCK7, PCSK9 and GALNT2 genes and the risk of hyperlipidaemia

Little is known about the association between the single nucleotide polymorphisms (SNPs) and haplotypes of the dedicator of cytokinesis 7 (DOCK7), pro-protein convertase subtilisin/kexin type 9 (PCSK9) and polypeptide N-acetylgalactosaminyltransferase 2 (GALNT2) and serum lipid traits in the Chinese populations. This study was to determine the association between nine SNPs in the three genes and their haplotypes and hypercholesterolaemia (HCH)/hypertriglyceridaemia (HTG), and to identify the possible gene-gene interactions among these SNPs. Genotyping was performed in 733 HCH and 540 HTG participants. The haplotype of C-C-G-C-T-G-C-C-G [in the order of DOCK7 rs1168013 (G>C), rs10889332 (C>T); PCSK9 rs615563 (G>A), rs7552841 (C>T), rs11206517 (T>G); and GALNT2 rs1997947 (G>A), rs2760537 (C>T), rs4846913 (C>A) and rs11122316 (G>A) SNPs] was associated with increased risk of HCH and HTG. The haplotypes of C-C-G-C-T-G-C-C-A and G-C-G-T-T-G-T-C-G were associated with a reduced risk of HCH and HTG. The haplotypes of G-C-G-C-T-G-C-C-A and G-C-G-C-T-G-T-C-G were associated with increased risk of HCH. The haplotypes of C-T-G-C-T-G-C-C-G, G-C-A-C-T-G-C-C-G and G-C-G-C-T-G-C-C-A were associated with an increased risk of HTG. The haplotypes of G-C-G-C-T-G-T-C-A and G-C-G-T-T-G-T-C-G were associated with a reduced risk of HTG. In addition, possible inter-locus interactions among the DOCK7, PCSK9 and GALNT2 SNPs were also noted. However, further functional studies of these genes are still required to clarify which SNPs are functional and how these genes actually affect the serum lipid levels.

Beyond the genetics of HDL: why is HDL cholesterol inversely related to cardiovascular disease?

There is unequivocal evidence that high-density lipoprotein (HDL) cholesterol levels in plasma are inversely associated with the risk of cardiovascular disease (CVD). Studies of families with inherited HDL disorders and genetic association studies in general (and patient) population samples have identified a large number of factors that control HDL cholesterol levels. However, they have not resolved why HDL cholesterol and CVD are inversely related. A growing body of evidence from nongenetic studies shows that HDL in patients at increased risk of CVD has lost its protective properties and that increasing the cholesterol content of HDL does not result in the desired effects. Hopefully, these insights can help improve strategies to successfully intervene in HDL metabolism. It is clear that there is a need to revisit the HDL hypothesis in an unbiased manner. True insights into the molecular mechanisms that regulate plasma HDL cholesterol and triglycerides or control HDL function could provide the handholds that are needed to develop treatment for, e.g., type 2 diabetes and the metabolic syndrome. Especially genome-wide association studies have provided many candidate genes for such studies. In this review we have tried to cover the main molecular studies that have been produced over the past few years. It is clear that we are only at the very start of understanding how the newly identified factors may control HDL metabolism. In addition, the most recent findings underscore the intricate relations between HDL, triglyceride, and glucose metabolism indicating that these parameters need to be studied simultaneously.

A glycogene mutation map for discovery of diseases of glycosylation

Glycosylation of proteins and lipids involves over 200 known glycosyltransferases (GTs), and deleterious defects in many of the genes encoding these enzymes cause disorders collectively classified as congenital disorders of glycosylation (CDGs). Most known CDGs are caused by defects in glycogenes that affect glycosylation globally. Many GTs are members of homologous isoenzyme families and deficiencies in individual isoenzymes may not affect glycosylation globally. In line with this, there appears to be an underrepresentation of disease-causing glycogenes among these larger isoenzyme homologous families. However, genome-wide association studies have identified such isoenzyme genes as candidates for different diseases, but validation is not straightforward without biomarkers. Large-scale whole-exome sequencing (WES) provides access to mutations in, for example, GT genes in populations, which can be used to predict and/or analyze functional deleterious mutations. Here, we constructed a draft of a functional mutational map of glycogenes, GlyMAP, from WES of a rather homogenous population of 2000 Danes. We cataloged all missense mutations and used prediction algorithms, manual inspection and in case of carbohydrate-active enzymes family GT27 experimental analysis of mutations to map deleterious mutations. GlyMAP (http://glymap.glycomics.ku.dk) provides a first global view of the genetic stability of the glycogenome and should serve as a tool for discovery of novel CDGs.

A preliminary study of the relationship between promoter methylation of the ABCG1, GALNT2 and HMGCR genes and coronary heart disease

AIMS

To investigate the association of ABCG1, GALNT2 and HMGCR genes promoter DNA methylation with coronary heart disease (CHD) and explore the interaction between their methylation status and the CHD patients' clinical characteristics in Han Chinese population.

METHODS AND RESULTS

Methylation-specific polymerase chain reaction (MSP) technology was used to examine the role of the aberrant gene promoter methylation in CHD in Han Chinese population. A total of 85 CHD patients and 54 participants without CHD confirmed by angiography were recruited. 82.8% of the participants with ABCG1 gene promoter hypermethylation have CHD, while only 17.4% of the participants without hypermethylation have it. The average age of the participants with GALNT2 gene promoter hypermethylation is 62.10 ± 8.21, while that of the participants without hypermethylation is 57.28 ± 9.87; in the former group, 75.4% of the participants have CHD, compared to only 50% in the latter group. As for the HMGCR gene, the average age of the participants with promoter hypermethylation is 63.24 ± 8.10 and that of the participants without hypermethylation is 57.79 ± 9.55; its promoter hypermethylation is likely to be related to smoking. Our results indicated a significant statistical association of promoter methylation of the ABCG1 gene with increased risk of CHD (OR = 19.966; 95% CI, 7.319-54.468; P*<0.001; P*: adjusted for age, gender, smoking, lipid level, hypertension, and diabetes). Similar results were obtained for that of the GALNT2 gene (OR = 2.978; 95% CI, 1.335-6.646; P* = 0.008), but not of HMGCR gene (OR = 1.388; 95% CI, 0.572-3.371; P*  = 0.469).

CONCLUSIONS

The present work provides evidence to support the association of promoter DNA methylation status with the risk profile of CHD. Our data indicates that promoter DNA hypermethylation of the ABCG1 and GALNT2 genes, but not the HMGCR gene, is associated with an increased risk of CHD. CHD, smoking and aging are likely to be the important factors influencing DNA hypermethylation.

Identification of four novel genes contributing to familial elevated plasma HDL cholesterol in humans

While genetic determinants strongly influence HDL cholesterol (HDLc) levels, most genetic causes underlying variation in HDLc remain unknown. We aimed to identify novel rare mutations with large effects in candidate genes contributing to extreme HDLc in humans, utilizing family-based Mendelian genetics. We performed next-generation sequencing of 456 candidate HDLc-regulating genes in 200 unrelated probands with extremely low (≤10th percentile) or high (≥90th percentile) HDLc. Probands were excluded if known mutations existed in the established HDLc-regulating genes ABCA1, APOA1, LCAT, cholesteryl ester transfer protein (CETP), endothelial lipase (LIPG), and UDP-N-acetyl-α-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 2 (GALNT2). We identified 93 novel coding or splice-site variants in 72 candidate genes. Each variant was genotyped in the proband's family. Family-based association analyses were performed for variants with sufficient power to detect significance at P < 0.05 with a total of 627 family members being assessed. Mutations in the genes glucokinase regulatory protein (GCKR), RNase L (RNASEL), leukocyte immunoglobulin-like receptor 3 (LILRA3), and dynein axonemal heavy chain 10 (DNAH10) segregated with elevated HDLc levels in families, while no mutations associated with low HDLc. Taken together, we have identified mutations in four novel genes that may play a role in regulating HDLc levels in humans.

Flow-mediated dilation, carotid wall thickness and HDL function in subjects with hyperalphalipoproteinemia

BACKGROUND AND AIMS

The relationships between very high plasma HDLc and subclinical atherosclerosis are still a matter of debate.

METHODS AND RESULTS

Twenty subjects with primary hyperalphalipoproteinemia (HAL, with HDLc in the highest 10th percentile and absence of overt secondary causes of this condition), aged 30-65 years, were compared with 20 age and sex-matched controls. Lipid determination, lipoprotein particle distribution (Lipoprint(®)), Cholesterol Efflux Capacity (CEC), plasma adhesion molecule, analyses of CETP, SRB1 and LIPG genes and of different markers of subclinical vascular disease (ankle-brachial index, ABI; carotid intima-media thickness, cIMT; brachial-artery flow mediated dilation, FMD) were performed. Fasting HDLc levels were 40 mg/dl higher in HAL subjects while LDLc concentration was comparable to control group. CETP gene analysis in HAL subjects identified one novel rare Single Nucleotide Polymorphism (SNP, Asp131Asn), possibly damaging, while the common SNP p.Val422Ile was highly prevalent (50% vs. 27.4% in a control population). No rare mutations associated with HAL were found in SR-B1 and LIPG genes. Polyacrylamide gel electrophoresis in HAL subjects disclosed larger and more buoyant HDL particles than in controls, while LDL profile was much more similar. ABI, cIMT and arterial plaques did not differ in cases and controls and the two groups showed comparable FMD at brachial artery examination. Similarly, ABCA1 and ABCG1 HDL-mediated CEC, the most relevant for atheroprotection, did not discriminate between the groups and only ABCG1 pathway seemed somewhat related to arterial reactivity.

CONCLUSIONS

HDL dimension, function and genetics seem scarcely related to subclinical atherosclerosis and vascular reactivity in middle-aged HAL subjects.

Evaluation of the causality of the low-density lipoprotein receptor gene (LDLR) for serum lipids in pigs

A significant quantitative trait locus (QTL) for low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) was identified around the LDLR gene on chromosome 2 (SSC2) in a White Duroc × Erhualian F2 resource population and Sutai pigs in our previous study. However, in previous reports, the causality of LDLR with serum lipids is controversial in pigs. To systematically assess the causality of LDLR with serum lipids, association analyses were successively performed in three populations: Sutai pigs, a White Duroc × Erhualian F2 resource population and a Duroc × (Landrace × Large White) population. We first performed a haplotype-based association study with 60K SNP genotyping data and evidenced the significant association with LDL-C and TC around the LDLR gene region. We also found that there is more than one QTL for LDL-C and TC on SSC2. Then, we evaluated the causalities of two missense mutations, c.1812C>T and c.1520A>G, with LDL-C and TC. We revealed that the c.1812C>T SNP showed the strongest association with LDL-C (P = 5.40 × 10(-11) ) and TC (P = 3.64 × 10(-8) ) and explained all the QTL effect in Sutai pigs. Haplotype analysis found that two missense SNPs locate within a 1.93-Mb haplotype block. One major haplotype showed the strongest significant association with LDL-C (P = 4.62 × 10(-18) ) and TC (P = 1.06 × 10(-9) ). However, the c.1812C>T SNP was not identified in the White Duroc × Erhualian intercross, and the association of c.1520A>G with both LDL-C and TC did not achieve significance in this F2 population, suggesting population heterogeneity. Both missense mutations were identified in the Duroc × (Landrace × Large White) population and showed significant associations with LDL-C and TC. Our data give evidence that the LDLR gene should be a candidate causative gene for LDL-C and TC in pigs, but heterogeneity exists in different populations.

First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene

GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.

Diagnosis and management of familial dyslipoproteinemias

The three major pathways of lipoprotein metabolism provide a superb paradigm to delineate systematically the familial dyslipoproteinemias. Such understanding leads to improved diagnosis and treatment of patients. In the exogenous (intestinal) pathway, defects in LPL, apoC-II, APOA-V, and GPIHBP1 disrupt the catabolism of chylomicrons and hepatic uptake of their remnants, producing very high TG. In the endogenous (hepatic) pathway, six disorders affect the activity of the LDLR and markedly increase LDL. These include FH, FDB, ARH, PCSK9 gain-of-function mutations, sitosterolemia and loss of 7 alpha hydroxylase. Hepatic overproduction of VLDL occurs in FCHL, hyperapoB, LDL subclass pattern B, FDH and syndrome X, often due to insulin resistance and resulting in high TG, elevated small LDL particles and low HDL-C. Defects in APOB-100 and loss-of-function mutations in PCSK9 are associated with low LDL-C, decreased CVD and longevity. An absence of MTP leads to marked reduction in chylomicrons and VLDL, causing abetalipoproteinemia. In the reverse cholesterol pathway, deletions or nonsense mutations in apoA-I or ABCA1 transporter disrupt the formation of the nascent HDL particle. Mutations in LCAT disrupt esterification of cholesterol in nascent HDL by LCAT and apoA-1, and formation of spherical HDL. Mutations in either CETP or SR-B1 and familial high HDL lead to increased large HDL particles, the effect of which on CVD is not resolved. The major goal is to prevent or ameliorate the major complications of many familial dyslipoproteinemias, namely, premature CVD or pancreatitis. Dietary and drug treatment specific for each inherited disorder is reviewed.

Evidence of a polygenic origin of extreme high-density lipoprotein cholesterol levels

OBJECTIVE

There are several known monogenic causes of high and low high-density lipoprotein cholesterol (HDL-C) levels, but traditional sequencing studies have had limited success in identifying mutations in the majority of individuals with extreme HDL-C levels. The aim of this study was to assess the power of a targeted high-throughput sequencing strategy to elucidate the genetic basis of extreme HDL-C phenotypes.

APPROACH AND RESULTS

We sequenced 195 genes with either established or implicated roles in lipid and lipoprotein metabolism plus 78 lipid-unrelated genes in patients with HDL-C <1st (n=40) or >99th (n=40) percentile values, and the results were compared with those of 498 individuals representative of the Dutch general population and 95 subjects with normal HDL-C (between 40th and 60th percentile values). The extreme HDL cohort carried more rare nonsynonymous variants in the lipid geneset than both the general population (odds ratio, 1.39; P=0.019) and normal HDL-C (odds ratio, 1.43; P=0.040) cohorts. The prevalence of such variants in the lipid-related and lipid-unrelated genesets was similar in the control groups, indicative of equal mutation rates. In the extreme HDL cohort, however, there was enrichment of rare nonsynonymous variants in the lipid versus the control geneset (odds ratio, 2.23; P<0.0001), and 70% of the lipid-related variants altered conserved nucleotides. The lipid geneset comprised 4 nonsense, 10 splice-site, and 8 coding indel variants, whereas the control geneset contained only 1 such variant. In the lipid geneset, 87% and 28% of the patients carried ≥ 2 and ≥ 5 rare variants.

CONCLUSIONS

This study suggests that most extreme HDL-C phenotypes have a polygenic origin.

Single nucleotide polymorphisms in CETP, SLC46A1, SLC19A1, CD36, BCMO1, APOA5, and ABCA1 are significant predictors of plasma HDL in healthy adults

Background

In a marker-trait association study we estimated the statistical significance of 65 single nucleotide polymorphisms (SNP) in 23 candidate genes on HDL levels of two independent Caucasian populations. Each population consisted of men and women and their HDL levels were adjusted for gender and body weight. We used a linear regression model. Selected genes corresponded to folate metabolism, vitamins B-12, A, and E, and cholesterol pathways or lipid metabolism.

Methods

Extracted DNA from both the Sacramento and Beltsville populations was analyzed using an allele discrimination assay with a MALDI-TOF mass spectrometry platform. The adjusted phenotype, y, was HDL levels adjusted for gender and body weight only statistical analyses were performed using the genotype association and regression modules from the SNP Variation Suite v7.

Results

Statistically significant SNP (where P values were adjusted for false discovery rate) included: CETP (rs7499892 and rs5882); SLC46A1 (rs37514694; rs739439); SLC19A1 (rs3788199); CD36 (rs3211956); BCMO1 (rs6564851), APOA5 (rs662799), and ABCA1 (rs4149267). Many prior association trends of the SNP with HDL were replicated in our cross-validation study. Significantly, the association of SNP in folate transporters (SLC46A1 rs37514694 and rs739439; SLC19A1 rs3788199) with HDL was identified in our study.

Conclusions

Given recent literature on the role of niacin in the biogenesis of HDL, focus on status and metabolism of B-vitamins and metabolites of eccentric cleavage of β-carotene with lipid metabolism is exciting for future study.

Hunting human disease genes: lessons from the past, challenges for the future

The concept that a specific alteration in an individual’s DNA can result in disease is central to our notion of molecular medicine. The molecular basis of more than 3,500 Mendelian disorders has now been identified. In contrast, the identification of genes for common disease has been much more challenging. We discuss historical and contemporary approaches to disease gene identification, focusing on novel opportunities such as the use of population extremes and the identification of rare variants. While our ability to sequence DNA has advanced dramatically, assigning function to a given sequence change remains a major challenge, highlighting the need for both bioinformatics and functional approaches to appropriately interpret these data. We review progress in mapping and identifying human disease genes and discuss future challenges and opportunities for the field.