Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks

Association of the IGF1 gene with fasting insulin levels

Insulin-like growth factor 1 (IGF-I) has been associated with insulin resistance. Genome-wide association studies (GWASs) of fasting insulin (FI) identified single-nucleotide variants (SNVs) near the IGF1 gene, raising two hypotheses: (1) these associations are mediated by IGF-I levels and (2) these noncoding variants either tag other functional variants in the region or are directly functional. In our study, analyses including 5141 individuals from population-based cohorts suggest that FI associations near IGF1 are not mediated by IGF-I. Analyses of targeted sequencing data in 3539 individuals reveal a large number of novel rare variants at the IGF1 locus and show a FI association with a subset of rare nonsynonymous variants (PSKAT=5.7 × 10(-4)). Conditional analyses suggest that this association is partly explained by the GWAS signal and the presence of a residual independent rare variant effect (Pconditional=0.019). Annotation using ENCODE data suggests that the GWAS variants may have a direct functional role in insulin biology. In conclusion, our study provides insight into variation present at the IGF1 locus and into the genetic architecture underlying FI levels, suggesting that FI associations of SNVs near IGF1 are not mediated by IGF-I and suggesting a role for both rare nonsynonymous and common functional variants in insulin biology.

Progress in methods for rare variant association

Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, methods for rare variant association have been an active area of research for the past decade. Here, we provide a survey of the current literature and developments from the Genetics Analysis Workshop 19 (GAW19) Collapsing Rare Variants working group. In particular, we present the generalized linear regression framework and associated score statistic for the 2 major types of methods: burden and variance components methods. We further show that by simply modifying weights within these frameworks we arrive at many of the popular existing methods, for example, the cohort allelic sums test and sequence kernel association test. Meta-analysis techniques are also described. Next, we describe the 6 contributions from the GAW19 Collapsing Rare Variants working group. These included development of new methods, such as a retrospective likelihood for family data, a method using genomic structure to compare cases and controls, a haplotype-based meta-analysis, and a permutation-based method for combining different statistical tests. In addition, one contribution compared a mega-analysis of family-based and population-based data to meta-analysis. Finally, the power of existing family-based methods for binary traits was compared. We conclude with suggestions for open research questions.

Family-based approaches: design, imputation, analysis, and beyond

Participants in the family-based analysis group at Genetic Analysis Workshop 19 addressed diverse topics, all of which used the family data. Topics addressed included questions of study design and data quality control (QC), genotype imputation to augment available sequence data, and linkage and/or association analyses. Results show that pedigree-based tests that are sensitive to genotype error may be useful for QC. Imputation quality improved with inclusion of small amounts of pedigree information used to phase the data in evaluation of 5 commonly used approaches for imputation in samples of (typically) unrelated subjects. It improved still further when pedigree-based imputation using larger pedigrees was also added. An important distinction was made between methods that do versus do not make use of Mendelian transmission in pedigrees, because this serves as a key difference between underlying models and assumptions. Methods that model relatedness generally had higher power in association testing than did analyses that carry out testing in the presence of a transmission model, but this may reflect details of implementation and/or ability of more general methods to jointly include data from larger pedigrees. In either case, for single nucleotide polymorphism-set approaches, weights that incorporate information on functional effects may be more useful than those that are based only on allele frequencies. The overall results demonstrate that family data continue to provide important information in the search for trait loci.

Evaluation of pleiotropic effects among common genetic loci identified for cardio-metabolic traits in a Korean population

Background

The genetic contribution to complex diseases or traits, including cardio-metabolic traits, has been elucidated recently by large-scale genome-wide association studies. These genome-wide association studies have indicated that most pleiotropic loci contain genes associated with lipids. Clinically, lipid related abnormalities are strongly associated with other diseases such as type 2 diabetes, coronary artery disease and hypertension. The aim of this study was to evaluate the shared genetic background of lipids and other cardio-metabolic traits.

Methods

We conducted meta-analyses of the association between 157 published lipid-associated loci and 10 cardio-metabolic traits in 14,028 Korean individuals genotyped using the Exome chip (Illumina HumanExome BeadChip). We also examined whether the pleiotropic effects of such loci constituted independent (i.e., biological) pleiotropy or mediated pleiotropy in these metabolic pathways.

Results

Eighteen lipid-associated loci were significantly associated with one of six cardio-metabolic traits after correction for multiple testing (P < 3.70 × 10⁻⁴). Region 12q24.12 had pleiotropic effects on fasting plasma glucose, blood pressure and obesity-related traits (body mass index and waist-hip ratio) independent of its effects on the lipid profile. Lipid risk scores, calculated according to whether or not subjects carried the risk allele for lipid traits, were significantly associated with fasting plasma glucose, blood pressure and obesity-related traits.

Conclusions

The 12q24.12 region showed ethnic-specific genetic pleiotropy among cardio-metabolic traits in this study. Our findings may help to account for molecular mechanisms based on shared genetic background underlying not only dyslipidemia, but also cardiovascular disease and type 2 diabetes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-016-0337-1) contains supplementary material, which is available to authorized users.

A null mutation in ANGPTL8 does not associate with either plasma glucose or type 2 diabetes in humans

BACKGROUND

Experiments in mice initially suggested a role for the protein angiopoietin-like 8 (ANGPTL8) in glucose homeostasis. However, subsequent experiments in model systems have challenged this proposed role. We sought to better understand the importance of ANGPTL8 in human glucose homeostasis by examining the association of a null mutation in ANGPTL8 with fasting glucose levels and risk for type 2 diabetes.

METHODS

A naturally-occurring null mutation in human ANGPTL8 (rs145464906; c.361C > T; p.Q121X) is carried by ~1 in 1000 individuals of European ancestry and is associated with higher levels of plasma high-density lipoprotein cholesterol, suggesting that this mutation has functional significance. We examined the association of p.Q121X with fasting glucose levels and risk for type 2 diabetes in up to 95,558 individuals (14,824 type 2 diabetics and 80,734 controls).

RESULTS

We found no significant association of p.Q121X with either fasting glucose or type 2 diabetes (p-value = 0.90 and 0.65, respectively). Given our sample sizes, we had >98 % power to detect at least a 0.23 mmol/L effect on plasma glucose and >95 % power to detect a 70 % increase in risk for type 2 diabetes.

CONCLUSION

Disruption of ANGPTL8 function in humans does not seem to have a large effect on measures of glucose tolerance.

The effect of phenotypic outliers and non-normality on rare-variant association testing

Rare-variant association studies (RVAS) have made important contributions to human complex trait genetics. These studies rely on specialized statistical methods for analyzing rare-variant associations, both individually and in aggregate. We investigated the impact that phenotypic outliers and non-normality have on the performance of rare-variant association testing procedures. Ignoring outliers or non-normality can significantly inflate Type I error rates. We found that rank-based inverse normal transformation (INT) and trait winsorisation were both effective at maintaining Type I error control without sacrificing power in the presence of outliers. INT was the optimal method for non-normally distributed traits. For RVAS of quantitative traits with outliers or non-normality, we recommend using INT to transform phenotypic values before association testing.

The contribution of rare variation to prostate cancer heritability

We report targeted sequencing of 63 known prostate cancer risk regions in a multi-ancestry study of 9,237 men and use the data to explore the contribution of low-frequency variation to disease risk. We show that SNPs with minor allele frequencies (MAFs) of 0.1-1% explain a substantial fraction of prostate cancer risk in men of African ancestry. We estimate that these SNPs account for 0.12 (standard error (s.e.) = 0.05) of variance in risk (∼42% of the variance contributed by SNPs with MAF of 0.1-50%). This contribution is much larger than the fraction of neutral variation due to SNPs in this class, implying that natural selection has driven down the frequency of many prostate cancer risk alleles; we estimate the coupling between selection and allelic effects at 0.48 (95% confidence interval [0.19, 0.78]) under the Eyre-Walker model. Our results indicate that rare variants make a disproportionate contribution to genetic risk for prostate cancer and suggest the possibility that rare variants may also have an outsize effect on other common traits.

Incorporating Non-Coding Annotations into Rare Variant Analysis

BACKGROUND

The success of collapsing methods which investigate the combined effect of rare variants on complex traits has so far been limited. The manner in which variants within a gene are selected prior to analysis has a crucial impact on this success, which has resulted in analyses conventionally filtering variants according to their consequence. This study investigates whether an alternative approach to filtering, using annotations from recently developed bioinformatics tools, can aid these types of analyses in comparison to conventional approaches.

METHODS & RESULTS

We conducted a candidate gene analysis using the UK10K sequence and lipids data, filtering according to functional annotations using the resource CADD (Combined Annotation-Dependent Depletion) and contrasting results with 'nonsynonymous' and 'loss of function' consequence analyses. Using CADD allowed the inclusion of potentially deleterious intronic variants, which was not possible when filtering by consequence. Overall, different filtering approaches provided similar evidence of association, although filtering according to CADD identified evidence of association between ANGPTL4 and High Density Lipoproteins (P = 0.02, N = 3,210) which was not observed in the other analyses. We also undertook genome-wide analyses to determine how filtering in this manner compared to conventional approaches for gene regions. Results suggested that filtering by annotations according to CADD, as well as other tools known as FATHMM-MKL and DANN, identified association signals not detected when filtering by variant consequence and vice versa.

CONCLUSION

Incorporating variant annotations from non-coding bioinformatics tools should prove to be a valuable asset for rare variant analyses in the future. Filtering by variant consequence is only possible in coding regions of the genome, whereas utilising non-coding bioinformatics annotations provides an opportunity to discover unknown causal variants in non-coding regions as well. This should allow studies to uncover a greater number of causal variants for complex traits and help elucidate their functional role in disease.

Serum β-trophin level as a new marker for noninvasive assessment of nonalcoholic fatty liver disease and liver fibrosis

OBJECTIVE

Nonalcoholic fatty liver disease (NAFLD) is a common chronic liver disease and evaluation of fibrosis is important. We aimed to investigate the utility of serum β-trophin in NAFLD and its ability to predict liver fibrosis.

PATIENTS AND METHODS

Serum samples of consecutive patients with biopsy-proven NAFLD and age-matched and sex-matched healthy controls were used to measure β-trophin using ELISA. Correlations between histopathological features of NAFLD and β-trophin were analyzed. Whereas patients with fibrosis scores less than 2 were grouped in the mild fibrosis group, patients with scores of 2 or more were grouped in the significant fibrosis group. Univariate/multivariate logistic regression analyses were carried out to evaluate the independent predicting factors of liver fibrosis. Receiver operating characteristics (ROCs) were assessed to determine the best cut-off values for NAFLD and fibrosis.

RESULTS

Sixty-nine patients with NAFLD and 69 healthy controls were enrolled in the study. Serum β-trophin levels were lower in NAFLD patients compared with the controls (2.34±0.06 vs. 1.94±0.09 ng/ml, respectively, P<0.001). In NAFLD, serum β-trophin was related to liver fibrosis and inflammation. The mild fibrosis group had higher serum β-trophin levels than the significant fibrosis group (2.11±0.12 vs. 1.72±0.11, respectively, P<0.001). In multivariate analysis, β-trophin remained an independent predictor of significant fibrosis (odds ratio, 0.237; 95% confidence interval, 0.059-0.949; P<0.001). ROC analysis showed that serum β-trophin was statistically significant in the identification of significant fibrosis (area under receiver operating characteristic, 0.844; 95% confidence interval, 0.718-0.970; P<0.001). The best cut-off value was 1.786, with the best sensitivity (71.43%) and specificity (95.65%).

CONCLUSION

Serum β-trophin may be a potential noninvasive marker for the identification of NAFLD and significant liver fibrosis.

Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese

Blood lipids are important risk factors for coronary artery disease (CAD). Here we perform an exome-wide association study by genotyping 12,685 Chinese, using a custom Illumina HumanExome BeadChip, to identify additional loci influencing lipid levels. Single-variant association analysis on 65,671 single nucleotide polymorphisms reveals 19 loci associated with lipids at exome-wide significance (P<2.69 × 10⁻⁷), including three Asian-specific coding variants in known genes (CETP p.Asp459Gly, PCSK9 p.Arg93Cys and LDLR p.Arg257Trp). Furthermore, missense variants at two novel loci—PNPLA3 p.Ile148Met and PKD1L3 p.Thr429Ser—also influence levels of triglycerides and low-density lipoprotein cholesterol, respectively. Another novel gene, TEAD2, is found to be associated with high-density lipoprotein cholesterol through gene-based association analysis. Most of these newly identified coding variants show suggestive association (P<0.05) with CAD. These findings demonstrate that exome-wide genotyping on samples of non-European ancestry can identify additional population-specific possible causal variants, shedding light on novel lipid biology and CAD.

An important risk factor for coronary artery disease is the level of blood lipids. Here the authors conduct an exome-wide association study in Chinese cohorts and identify three novel loci associated with lipid levels as well as three Asian-specific variants in known loci.

A lipasin/Angptl8 monoclonal antibody lowers mouse serum triglycerides involving increased postprandial activity of the cardiac lipoprotein lipase

Lipasin/Angptl8 is a feeding-induced hepatokine that regulates triglyceride (TAG) metabolism; its therapeutical potential, mechanism of action, and relation to the lipoprotein lipase (LPL), however, remain elusive. We generated five monoclonal lipasin antibodies, among which one lowered the serum TAG level when injected into mice, and the epitope was determined to be EIQVEE. Lipasin-deficient mice exhibited elevated postprandial activity of LPL in the heart and skeletal muscle, but not in white adipose tissue (WAT), suggesting that lipasin suppresses the activity of LPL specifically in cardiac and skeletal muscles. Consistently, mice injected with the effective antibody or with lipasin deficiency had increased postprandial cardiac LPL activity and lower TAG levels only in the fed state. These results suggest that lipasin acts, at least in part, in an endocrine manner. We propose the following model: feeding induces lipasin, activating the lipasin-Angptl3 pathway, which inhibits LPL in cardiac and skeletal muscles to direct circulating TAG to WAT for storage; conversely, fasting induces Angptl4, which inhibits LPL in WAT to direct circulating TAG to cardiac and skeletal muscles for oxidation. This model suggests a general mechanism by which TAG trafficking is coordinated by lipasin, Angptl3 and Angptl4 at different nutritional statuses.

Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology

The Framingham Heart Study (FHS) has conducted seminal research defining cardiovascular disease (CVD) risk factors and fundamentally shaping public health guidelines for CVD prevention over the past five decades. The success of the Original Cohort, initiated in 1948, paved the way for further epidemiological research in preventive cardiology. Due to the keen observations suggesting the role of shared familial factors in the development of CVD, in 1971 the FHS began enroling the second generation cohort, comprising the children of the Original Cohort and the spouses of the children. In 2002, the third generation cohort, comprising the grandchildren of the Original Cohort, was initiated to additionally explore genetic contributions to CVD in greater depth. Additionally, because of the predominance of White individuals of European descent in the three generations of FHS participants noted above, the Heart Study enrolled the OMNI1 and OMNI2 cohorts in 1994 and 2003, respectively, aimed to reflect the current greater racial and ethnic diversity of the town of Framingham. All FHS cohorts have been examined approximately every 2-4 years since the initiation of the study. At these periodic Heart Study examinations, we obtain a medical history and perform a cardiovascular-focused physical examination, 12-lead electrocardiography, blood and urine samples testing and other cardiovascular imaging studies reflecting subclinical disease burden.The FHS has continually evolved along the cutting edge of cardiovascular science and epidemiological research since its inception. Participant studies now additionally include study of cardiovascular imaging, serum and urine biomarkers, genetics/genomics, proteomics, metabolomics and social networks. Numerous ancillary studies have been established, expanding the phenotypes to encompass multiple organ systems including the lungs, brain, bone and fat depots, among others. Whereas the FHS was originally conceived and designed to study the epidemiology of cardiovascular disease, it has evolved over the years with staggering expanded breadth and depth that have far greater implications in the study of the epidemiology of a wide spectrum of human diseases. The FHS welcomes research collaborations using existing or new collection of data. Detailed information regarding the procedures for research application submission and review are available at [http://www.framinghamheartstudy.org/researchers/index.php].

Fine mapping the CETP region reveals a common intronic insertion associated to HDL-C

BACKGROUND

Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein (CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans.

METHODS

We performed a meta-analysis of HDL-C within the CETP region using 59,432 individuals imputed with 1000 Genomes data. We performed replication in an independent sample of 47,866 individuals and validation was done by Sanger sequencing.

RESULTS

The meta-analysis of HDL-C within the CETP region identified five independent variants, including an exonic variant and a common intronic insertion. We replicated these 5 variants significantly in an independent sample of 47,866 individuals. Sanger sequencing of the insertion within a single family confirmed segregation of this variant. The strongest reported association between HDL-C and CETP variants, was rs3764261; however, after conditioning on the five novel variants we identified the support for rs3764261 was highly reduced (β_unadjusted=3.179 mg/dl (P value=5.25×10^-509), β_adjusted=0.859 mg/dl (P value=9.51×10^-25)), and this finding suggests that these five novel variants may partly explain the association of CETP with HDL-C. Indeed, three of the five novel variants (rs34065661, rs5817082, rs7499892) are independent of rs3764261.

CONCLUSIONS

The causal variants in CETP that account for the association with HDL-C remain unknown. We used studies imputed to the 1000 Genomes reference panel for fine mapping of the CETP region. We identified and validated five variants within this region that may partly account for the association of the known variant (rs3764261), as well as other sources of genetic contribution to HDL-C.

Genetic contribution of SCARB1 variants to lipid traits in African Blacks: a candidate gene association study

Background

High-density lipoprotein cholesterol (HDL-C) exerts many anti-atherogenic properties including its role in reverse cholesterol transport (RCT). Scavenger receptor class B member 1 (SCARB1) plays a key role in RCT by selective uptake of HDL cholesteryl esters. We aimed to explore the genetic contribution of SCARB1 to affecting lipid levels in African Blacks from Nigeria.

Methods

We resequenced 13 exons and exon-intron boundaries of SCARB1 in 95 individuals with extreme HDL-C levels using Sanger method. Then, we genotyped 147 selected variants (78 sequence variants, 69 HapMap tagSNPs, and 2 previously reported relevant variants) in the entire sample of 788 African Blacks using either the iPLEX Gold or TaqMan methods. A total of 137 successfully genotyped variants were further evaluated for association with major lipid traits.

Results

The initial gene-based analysis demonstrated evidence of association with HDL-C and apolipoprotein A-I (ApoA-I). The follow-up single-site analysis revealed nominal evidence of novel associations of nine common variants with HDL-C and/or ApoA-I (P < 0.05). The strongest association was between rs11057851 and HDL-C (P = 0.0043), which remained significant after controlling for multiple testing using false discovery rate. Rare variant association testing revealed a group of 23 rare variants (frequencies ≤1 %) associated with HDL-C (P = 0.0478). Haplotype analysis identified four SCARB1 regions associated with HDL-C (global P < 0.05).

Conclusions

To our knowledge, this is the first report of a comprehensive association study of SCARB1 variations with lipid traits in an African Black population. Our results showed the consistent association of SCARB1 variants with HDL-C across various association analyses, supporting the role of SCARB1 in lipoprotein-lipid regulatory mechanism.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-015-0250-6) contains supplementary material, which is available to authorized users.

RVFam: an R package for rare variant association analysis with family data

Family-based designs offer unique advantage for identifying rare risk variants in genetic association studies. There are existing tools for analyzing rare variants in families but lacking components to handle binary traits properly and survival traits. In this report, we introduce an R software package RVFam (Rare Variant association analysis with Family data) designed to analyze continuous, binary and survival traits against rare and common sequencing variants in genome-wide association studies (GWAS) involving family data. Single and multiple variant association tests were implemented while accounting for arbitrary family structures. Extensive simulation studies were performed to evaluate all the approaches implemented in RVFam.

AVAILABILITY AND IMPLEMENTATION

http://cran.r-project.org/web/packages/RVFam/.

Assessing the Power of Exome Chips

Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% < PAR > 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000–100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging.

Low-frequency germline variants across 6p22.2-6p21.33 are associated with non-obstructive azoospermia in Han Chinese men

Genome-wide association studies (GWAS) have identified several common loci contributing to non-obstructive azoospermia (NOA). However, a substantial fraction of NOA heritability remains undefined, especially those low-frequency [defined here as having a minor allele frequency (MAF) between 0.5 and 5%] and rare (MAF below 0.5%) variants. Here, we performed a 3-stage exome-wide association study in Han Chinese men to evaluate the role of low-frequency or rare germline variants in NOA development. The discovery stage included 962 NOA cases and 1348 healthy male controls genotyped by exome chips and was followed by a 2-stage replication with an additional 2168 cases and 5248 controls. We identified three low-frequency variants located at 6p22.2 (rs2298090 in HIST1H1E encoding p.Lys152Arg: OR = 0.30, P = 2.40 × 10(-16)) and 6p21.33 (rs200847762 in FKBPL encoding p.Pro137Leu: OR = 0.11, P = 3.77 × 10(-16); rs11754464 in MSH5: OR = 1.78, P = 3.71 × 10(-7)) associated with NOA risk after Bonferroni correction. In summary, we report an instance of newly identified signals for NOA risk in genes previously undetected through GWAS on 6p22.2-6p21.33 in a Chinese population and highlight the role of low-frequency variants with a large effect in the process of spermatogenesis.

Perspectives on pharmacogenomics of antiretroviral medications and HIV-associated comorbidities

PURPOSE OF REVIEW

To summarize current knowledge and provide perspective on relationships between human genetic variants, antiretroviral medications, and aging-related complications of HIV-1 infection.

RECENT FINDINGS

Human genetic variants have been convincingly associated with interindividual variability in antiretroviral toxicities, drug disposition, and aging-associated complications in HIV-1 infection. Screening for HLA-B5701 to avoid abacavir hypersensitivity reactions has become a routine part of clinical care, and has markedly improved drug safety. There are well established pharmacogenetic associations with other agents (efavirenz, nevirapine, atazanavir, dolutegravir, and others), but this knowledge has yet to have substantial impact on HIV-1 clinical care. As metabolic complications including diabetes mellitus, dyslipidemia, osteoporosis, and cardiovascular disease are becoming an increasing concern among individuals who are aging with well controlled HIV-1 infection, human genetic variants that predispose to these complications also become more relevant in this population.

SUMMARY

Pharmacogenetic knowledge has already had considerable impact on antiretroviral prescribing. With continued advances in the field of human genomics, the impact of pharmacogenomics on HIV-1 clinical care and research is likely to continue to grow in importance and scope.

A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

Common and Rare Variant Association Study for Plasma Lipids and Coronary Artery Disease

Blood lipid levels are highly heritable and modifiable risk factors for coronary artery disease (CAD), and are the leading cause of death worldwide. These facts have motivated human genetic association studies that have the substantial potential to define the risk factors that are causal and to identify pathways and therapeutic targets for lipids and CAD.The success of the HapMap project that provided an extensive catalog of human genetic variations and the development of microarray based genotyping chips (typically containing variations with allele frequencies ＞ 5%) facilitated common variant association study (CVAS; formerly termed genome-wide association study, GWAS) identifying disease-associated variants in a genome-wide manner. To date, 157 loci associated with blood lipids and 46 loci with CAD have been successfully identified, accounting for approximately 12%-14% of heritability for lipids and 10% of heritability for CAD. However, there is yet a major challenge termed "missing heritability problem," namely the observation that loci detected by CVAS explain only a small fraction of the inferred genetic variations. To explain such missing portions, focuses in genetic association studies have shifted from common to rare variants. However, it is challenging to apply rare variant association study (RVAS) in an unbiased manner because such variants typically lack the sufficient number to be identified statistically.In this review, we provide a current understanding of the genetic architecture mostly derived from CVAS, and several updates on the progress and limitations of RVAS for lipids and CAD.

A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience

The CATHeterization GENetics (CATHGEN) biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010, we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date, race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations included interim information: vital status (verified via National Death Index search and supplemented by Social Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.

Insights into blood lipids from rare variant discovery

Large-scale genome wide screens have discovered over 160 common variants associated with plasma lipids, which are risk factors often linked to heart disease. A large fraction of lipid heritability remains unexplained, and it is hypothesized that rare variants of functional consequence may account for some of the missing heritability. Finding lipid-associated variants that occur less frequently in the human population poses a challenge, primarily due to lack of power and difficulties to identify and test them. Interrogation of the protein-coding regions of the genome using array and sequencing techniques has led to important discoveries of rare variants that affect lipid levels and related disease risk. Here, we summarize the latest methods and findings that contribute to our current understanding of rare variant lipid genetics.

Insights from exome sequencing for endocrine disorders

Whole-exome sequencing has emerged as a fast and effective tool for the elucidation of genetic defects underlying both rare and common human diseases. Increased availability and decreased costs of next-generation sequencing have enabled investigators to use this approach not only in individual patients with rare diseases, but also to screen large cohorts or populations for the genetic determinants of diseases. Within the field of endocrinology, exome sequencing has led to major advancements in our understanding of many disorders including adrenal disease, growth and puberty disorders and type 2 diabetes mellitus, as well as a multitude of rare genetic syndromes with prominent endocrine involvement. In this Review, we provide an overview of these new insights and discuss the role that exome sequencing is expected to have in endocrine research and future clinical practice.

Proprotein convertases in atherogenesis

PURPOSE OF REVIEW

The proprotein convertases subtilisin/kexin (PCSKs) are endoproteases identified as activators of precursors from hormones and peptides. On the basis of the variety of substrates and regulation in disease, they have been recognized as mediators in atherogenesis. The discovery of PCSK9, which regulates low-density lipoprotein receptor cell membrane availability, has led to a resurgence of interest in these enzymes and their function in cardiovascular diseases.

RECENT FINDINGS

Recent data demonstrate that PCSKs are expressed in human atheroma and are regulated in animal models of atherosclerosis. In animal models, inhibition of PCSKs, such as PCSK3, affects cell proliferation and migration as well as inflammation, reducing atherosclerosis. In addition, targeting PCSK9 lowers cholesterol levels and has now been demonstrated to lessen vascular lesion formation in mice. Experimentally investigated novel anti-PCSK9 strategies include genome editing and vaccination. Furthermore, studies show that PCSKs contribute to the initiation and progression of cardiometabolic risk factors, such as insulin resistance and obesity.

SUMMARY

PCSKs affect cardiovascular diseases on multiple levels, including atherosclerotic lesion formation as well as their contribution to cardiometabolic risk factors. PCSK9 is a key regulator of plasma cholesterol levels, thereby potentially affecting atherosclerosis and has rapidly emerged as a pharmacological target.

A multiancestral genome-wide exome array study of Alzheimer disease, frontotemporal dementia, and progressive supranuclear palsy

IMPORTANCE

Previous studies have indicated a heritable component of the etiology of neurodegenerative diseases such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). However, few have examined the contribution of low-frequency coding variants on a genome-wide level.

OBJECTIVE

To identify low-frequency coding variants that affect susceptibility to AD, FTD, and PSP.

DESIGN, SETTING, AND PARTICIPANTS

We used the Illumina HumanExome BeadChip array to genotype a large number of variants (most of which are low-frequency coding variants) in a cohort of patients with neurodegenerative disease (224 with AD, 168 with FTD, and 48 with PSP) and in 224 control individuals without dementia enrolled between 2005-2012 from multiple centers participating in the Genetic Investigation in Frontotemporal Dementia and Alzheimer's Disease (GIFT) Study. An additional multiancestral replication cohort of 240 patients with AD and 240 controls without dementia was used to validate suggestive findings. Variant-level association testing and gene-based testing were performed.

MAIN OUTCOMES AND MEASURES

Statistical association of genetic variants with clinical diagnosis of AD, FTD, and PSP.

RESULTS

Genetic variants typed by the exome array explained 44%, 53%, and 57% of the total phenotypic variance of AD, FTD, and PSP, respectively. An association with the known AD gene ABCA7 was replicated in several ancestries (discovery P=.0049, European P=.041, African American P=.043, and Asian P=.027), suggesting that exonic variants within this gene modify AD susceptibility. In addition, 2 suggestive candidate genes, DYSF (P=5.53×10(-5)) and PAXIP1 (P=2.26×10(-4)), were highlighted in patients with AD and differentially expressed in AD brain. Corroborating evidence from other exome array studies and gene expression data points toward potential involvement of these genes in the pathogenesis of AD.

CONCLUSIONS AND RELEVANCE

Low-frequency coding variants with intermediate effect size may account for a significant fraction of the genetic susceptibility to AD and FTD. Furthermore, we found evidence that coding variants in the known susceptibility gene ABCA7, as well as candidate genes DYSF and PAXIP1, confer risk for AD.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Human genetic studies have demonstrated that quantitative human anthropometric and metabolic traits, including body mass index, waist-hip ratio, and plasma concentrations of glucose and insulin, are highly heritable, and are established risk factors for type 2 diabetes and cardiovascular diseases. Although many regions of the genome have been associated with these traits, the specific genes responsible have not yet been identified. By making use of advanced statistical “imputation” techniques applied to more than 87,000 individuals of European ancestry, and publicly available “reference panels” of more than 37 million genetic variants, we have been able to identify novel regions of the genome associated with these glycaemic and obesity-related traits and localise genes within these regions that are most likely to be causal. This improved understanding of the biological mechanisms underlying glycaemic and obesity-related traits is extremely important because it may advance drug development for downstream disease endpoints, ultimately leading to public health benefits.

Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF

Fibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.

Genetic variants in the ADAMTS13 and SUPT3H genes are associated with ADAMTS13 activity

We identify rs41314453 as the strongest genetic predictor of ADAMTS13 activity, associated with a decrease of >20%. We present evidence of further independent associations with a common variant in SUPT3H, as well as 5 variants at the ADAMTS13 locus.

Novel genes in LDL metabolism--a comprehensive overview

PURPOSE OF REVIEW

To summarize recent findings from genome-wide association studies (GWAS), whole-exome sequencing of patients with familial hypercholesterolemia and 'exome chip' studies pointing to novel genes in LDL metabolism.

RECENT FINDINGS

The genetic loci for ATP-binding cassette transporters G5 and G8, Niemann-Pick C1-Like protein 1, sortilin-1, ABO blood-group glycosyltransferases, myosin regulatory light chain-interacting protein and cholesterol 7α-hydroxylase have all consistently been associated with LDL cholesterol levels and/or coronary artery disease in GWAS. Whole-exome sequencing and 'exome chip' studies have additionally suggested several novel genes in LDL metabolism including insulin-induced gene 2, signal transducing adaptor family member 1, lysosomal acid lipase A, patatin-like phospholipase domain-containing protein 5 and transmembrane 6 superfamily member 2. Most of these findings still require independent replications and/or functional studies to confirm the exact role in LDL metabolism and the clinical implications for human health.

SUMMARY

GWAS, exome sequencing studies, and recently 'exome chip' studies have suggested several novel genes with effects on LDL cholesterol. Novel genes in LDL metabolism will improve our understanding of mechanisms in LDL metabolism, and may lead to the identification of new drug targets to reduce LDL cholesterol levels.

Low-frequency coding variants at 6p21.33 and 20q11.21 are associated with lung cancer risk in Chinese populations

Genome-wide association studies have successfully identified a subset of common variants associated with lung cancer risk. However, these variants explain only a fraction of lung cancer heritability. It has been proposed that low-frequency or rare variants might have strong effects and contribute to the missing heritability. To assess the role of low-frequency or rare variants in lung cancer development, we analyzed exome chips representing 1,348 lung cancer subjects and 1,998 control subjects during the discovery stage and subsequently evaluated promising associations in an additional 4,699 affected subjects and 4,915 control subjects during the replication stages. Single-variant and gene-based analyses were carried out for coding variants with a minor allele frequency less than 0.05. We identified three low-frequency missense variants in BAT2 (rs9469031, c.1544C>T [p.Pro515Leu]; odds ratio [OR] = 0.55, p = 1.28 × 10(-10)), FKBPL (rs200847762, c.410C>T [p.Pro137Leu]; OR = 0.25, p = 9.79 × 10(-12)), and BPIFB1 (rs6141383, c.850G>A [p.Val284Met]; OR = 1.72, p = 1.79 × 10(-7)); these variants were associated with lung cancer risk. rs9469031 in BAT2 and rs6141383 in BPIFB1 were also associated with the age of onset of lung cancer (p = 0.001 and 0.006, respectively). BAT2 and FKBPL at 6p21.33 and BPIFB1 at 20q11.21 were differentially expressed in lung tumors and paired normal tissues. Gene-based analysis revealed that FKBPL, in which two independent variants were identified, might account for the association with lung cancer risk at 6p21.33. Our results highlight the important role low-frequency variants play in lung cancer susceptibility and indicate that candidate genes at 6p21.33 and 20q11.21 are potentially biologically relevant to lung carcinogenesis.

Glucokinase regulatory protein: complexity at the crossroads of triglyceride and glucose metabolism

PURPOSE OF REVIEW

Glucokinase regulator (GCKR) encodes glucokinase regulatory protein (GKRP), a hepatocyte-specific inhibitor of the glucose-metabolizing enzyme glucokinase (GCK). Genome-wide association studies have identified a common coding variant within GCKR associated with multiple metabolic traits. This review focuses on recent insights into the critical role of GKRP in hepatic glucose metabolism that have stemmed from the study of human genetics. This knowledge has improved our understanding of glucose and lipid physiology and informed the development of targeted molecular therapeutics for diabetes.

RECENT FINDINGS

Rare GCKR variants have effects on GKRP expression, localization, and activity. These variants are collectively associated with hypertriglyceridaemia but are not causal. Crystal structures of GKRP and the GCK-GKRP complex have been solved, providing greater insight into the molecular interactions between these proteins. Finally, small molecules have been identified that directly bind GKRP and reduce blood glucose levels in rodent models of diabetes.

SUMMARY

GCKR variants across the allelic spectrum have effects on glucose and lipid homeostasis. Functional analysis has highlighted numerous molecular mechanisms for GKRP dysfunction. Hepatocyte-specific GCK activation via small molecule GKRP inhibition may be a new avenue for type 2 diabetes treatment, particularly considering evidence indicating GKRP loss-of-function alone does not cause hypertriglyceridaemia.

Recent developments in genome and exome-wide analyses of plasma lipids

PURPOSE OF REVIEW

Genome-wide association scans (GWAS) have identified over 100 human loci associated with variation in lipids. The identification of novel genes and variants that affect lipid levels is made possible by next-generation sequencing, rare variant discovery and analytic advances. The current status of the genetic basis of lipid traits will be presented.

RECENT FINDINGS

Expansion of GWAS sample sizes for lipid traits has not substantially increased the proportion of trait variance explained by common genetic variants (less than 15% of trait variation captured). Although GWAS has discovered novel loci and pathways with putative biological function and impact on cardiovascular disease risk, discovery of the genes in these loci remains challenging. Exome sequencing promises to identify genes with protein-coding variants with a large impact on lipids, as shown for LDL-cholesterol levels associated with novel (PNPLA5) and known (LDLR, PCSK9, APOB) genes.

SUMMARY

Current results have increased our understanding of the genetic architecture of lipids, expanding the range of effect and frequency for variants identified for lipid traits. Identification of novel lipid-associated gene variants, even if small in effect or rare in the population, could provide important novel drug targets and biological pathways for dyslipidemia.

ANGPTL8/betatrophin does not control pancreatic beta cell expansion

Recently, it was reported that angiopoietin-like protein 8 (ANGPTL8) was the long-sought "betatrophin" that could control pancreatic beta cell proliferation. However, studies of Angptl8(?/?) mice revealed profound reduction of triglyceride levels, but no abnormalities in glucose homeostasis. We now report that Angptl8(?/?) mice undergo entirely normal beta cell expansion in response to insulin resistance resulting from either a high-fat diet or from the administration of the insulin receptor antagonist S961. Furthermore, overexpression of ANGPTL8 in livers of mice doubles plasma triglyceride levels, but does not alter beta cell expansion nor glucose metabolism. These data indicate that ANGPTL8 does not play a role in controlling beta cell growth, nor can it be given to induce such expansion. The findings that plasma triglyceride levels are reduced by Angptl8 deletion and increased following ANGPTL8 overexpression support the possibility that inhibition of ANGPTL8 represents a therapeutic strategy for hypertriglyceridemia.

Rare variant association studies: considerations, challenges and opportunities

Genome-wide association studies (GWASs) have successfully uncovered thousands of robust associations between common variants and complex traits and diseases. Despite these successes, much of the heritability of these traits remains unexplained. Because low-frequency and rare variants are not tagged by conventional genome-wide genotyping arrays, they may represent an important and understudied component of complex trait genetics. In contrast to common variant GWASs, there are many different types of study designs, assays and analytic techniques that can be utilized for rare variant association studies (RVASs). In this review, we briefly present the different technologies available to identify rare genetic variants, including novel exome arrays. We also compare the different study designs for RVASs and argue that the best design will likely be phenotype-dependent. We discuss the main analytical issues relevant to RVASs, including the different statistical methods that can be used to test genetic associations with rare variants and the various bioinformatic approaches to predicting in silico biological functions for variants. Finally, we describe recent rare variant association findings, highlighting the unexpected conclusion that most rare variants have modest-to-small effect sizes on phenotypic variation. This observation has major implications for our understanding of the genetic architecture of complex traits in the context of the unexplained heritability challenge.

Genetics and causality of triglyceride-rich lipoproteins in atherosclerotic cardiovascular disease

Triglycerides represent 1 component of a heterogeneous pool of triglyceride-rich lipoproteins (TGRLs). The reliance on triglycerides or TGRLs as cardiovascular disease (CVD) risk biomarkers prompted investigations into therapies that lower plasma triglycerides as a means to reduce CVD events. Genetic studies identified TGRL components and pathways involved in their synthesis and metabolism. We advocate that only a subset of genetic mechanisms regulating TGRLs contribute to the risk of CVD events. This "omic" approach recently resulted in new targets for reducing CVD events.

Systematic cell-based phenotyping of missense alleles empowers rare variant association studies: a case for LDLR and myocardial infarction

A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.

Exome sequencing has proven powerful to identify protein-coding variation across the human genome, unravel the basis of monogenic diseases and discover rare alleles that confer risk for complex disease. Nevertheless, two key challenges limit its application to complex phenotypes: first, most alleles identified in a population are extremely rare; and second, most alleles are neutral on protein activities. Consequently, association tests that rely on enumerating rare alleles in cases and controls (termed rare variant association studies, RVAS) are typically underpowered, as the many neutral alleles dampen signals that arise from the few alleles that disrupt protein functions. Strategies to securely discriminate disruptive from neutral variants are immature, in particular for missense variants. Here we show that the statistical power of RVAS improves dramatically if variants are stratified according to their in vitro ascertained functions. We establish scalable technology to objectively profile the biological effects of exome-identified missense variants in the low-density lipoprotein receptor (LDLR) through systematic overexpression and complementation experiments in cells. We demonstrate that carriers of LDLR alleles, which our experiments identify as “disruptive-missense”, have higher plasma LDL-C, and that considering in vitro data may make it possible to reduce RVAS sample sizes by more than 2-fold.

Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.

Association of exome sequences with plasma C-reactive protein levels in >9000 participants

C-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.

Circulating betatrophin is elevated in patients with type 1 and type 2 diabetes

There is evidence that betatrophin, a hormone derived from adipose tissue and liver, affects the proliferation of pancreatic beta cells in mice. The aim of this study was to examine circulating betatrophin concentrations in Japanese healthy controls and patients with type 1 and type 2 diabetes. A total of 76 subjects (12 healthy controls, 34 type 1 diabetes, 30 type 2 diabetes) were enrolled in the study. Circulating betatrophin was measured with an ELISA kit and clinical parameters related to betatrophin were analyzed statistically. Circulating betatrophin (Log transformed) was significantly increased in patients with diabetes compared with healthy subjects (healthy controls, 2.29 ± 0.51; type 1 diabetes, 2.94 ± 0.44; type 2 diabetes, 3.17 ± 0.18; p<0.001, 4.1 to 5.4 times in pg/mL order). Age, HbA1c, fasting plasma glucose and Log triglyceride were strongly associated with Log betatrophin in all subjects (n=76) in correlation analysis. In type 1 diabetes, there was a correlation between Log betatrophin and Log CPR. These results provide the first evidence that circulating betatrophin is significantly elevated in Japanese patients with diabetes. The findings of this pilot study also suggest a possibility of association between the level of betatrophin and the levels of glucose and triglycerides.

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.

Human knockout research: new horizons and opportunities

Although numerous approaches have been pursued to understand the function of human genes, Mendelian genetics has by far provided the most compelling and medically actionable dataset. Biallelic loss-of-function (LOF) mutations are observed in the majority of autosomal recessive Mendelian disorders, representing natural human knockouts and offering a unique opportunity to study the physiological and developmental context of these genes. The restriction of such context to 'disease' states is artificial, however, and the recent ability to survey entire human genomes for biallelic LOF mutations has revealed a surprising landscape of knockout events in 'healthy' individuals, sparking interest in their role in phenotypic diversity beyond disease causation. As I discuss in this review, the potentially wide implications of human knockout research warrant increased investment and multidisciplinary collaborations to overcome existing challenges and reap its benefits.

Comprehensive analysis of patients with Stargardt macular dystrophy reveals new genotype-phenotype correlations and unexpected diagnostic revisions

PURPOSE

Stargardt macular dystrophy (STGD) results in early central vision loss. We sought to explain the genetic cause of STGD in a cohort of 88 patients from three different cultural backgrounds.

METHODS

Next-generation sequencing using a novel capture panel was used to search for disease-causing mutations. Patients with undetermined causes were clinically reexamined and tested for copy-number variations as well as intronic mutations.

RESULTS

We determined the cause of disease in 67% of our patients. Our analysis identified 35 novel ABCA4 alleles. Eleven patients had mutations in genes not previously reported to cause STGD. Finally, 45% of our patients with unsolved causes had single deleterious mutations in ABCA4, a recessive disease gene. No likely pathogenic copy-number variations were identified.

CONCLUSION

This study expands our knowledge of STGD by identifying dozens of novel alleles that cause the disease. The frequency of single mutations in ABCA4 among STGD patients is higher than that among controls, indicating that these mutations contribute to disease. Disease in 11 patients was explained by mutations outside ABCA4, underlining the need to genotype all retinal disease genes to maximize genetic diagnostic rates. Few ABCA4 mutations were observed in our French Canadian patients. This population may contain an unidentified founder mutation. Our results indicate that copy-number variations are unlikely to be a major cause of STGD.

Examining rare and low-frequency genetic variants previously associated with lone or familial forms of atrial fibrillation in an electronic medical record system: a cautionary note

BACKGROUND

Studies in individuals or small kindreds have implicated rare variants in 25 different genes in lone and familial atrial fibrillation (AF) using linkage and segregation analysis, functional characterization, and rarity in public databases. Here, we used a cohort of 20 204 patients of European or African ancestry with electronic medical records and exome chip data to compare the frequency of AF among carriers and noncarriers of these rare variants.

METHODS AND RESULTS

The exome chip included 19 of 115 rare variants, in 9 genes, previously associated with lone or familial AF. Using validated algorithms querying a combination of clinical notes, structured billing codes, ECG reports, and procedure codes, we identified 1056 AF cases (>18 years) and 19 148 non-AF controls (>50 years) with available genotype data on the Illumina HumanExome BeadChip v.1.0 in the Vanderbilt electronic medical record-linked DNA repository, BioVU. Known correlations between AF and common variants at 4q25 were replicated. None of the 19 variants previously associated with AF were over-represented among AF cases (P>0.1 for all), and the frequency of variant carriers among non-AF controls was >0.1% for 14 of 19. Repeat analyses using non-AF controls aged >60 (n=14 904), >70 (n=9670), and >80 (n=4729) years did not influence these findings.

CONCLUSIONS

Rare variants previously implicated in lone or familial forms of AF present on the exome chip are detected at low frequencies in a general population but are not associated with AF. These findings emphasize the need for caution when ascribing variants as pathogenic or causative.

Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9): Lessons Learned from Patients with Hypercholesterolemia

BACKGROUND

Identification of the proprotein convertase subtilisin/kexin type 9 (PCSK9) as the third gene causing familial hypercholesterolemia (FH) and understanding its complex biology has led to the discovery of a novel class of therapeutic agents.

CONTENT

PCSK9 undergoes autocatalytic cleavage in the endoplasmic reticulum and enters the secretory pathway. The PCSK9 gene is under the regulatory control of sterol receptor binding proteins 1 and 2. Statins increase PCSK9 and this may modulate the response to this class of medications. In plasma, PCSK9 binds to the epidermal growth factor–like domain of the LDL receptor (LDL-R) on the cell and, once incorporated in the late endosomal pathway, directs the LDL-R toward lysosomal degradation rather than recycling to the plasma membrane. Thus, gain-of-function PCSK9 mutations lead to an FH phenotype, whereas loss-of-function mutations are associated with increased LDL-R–mediated endocytosis of LDL particles and lower LDL cholesterol in plasma. Inhibition of PCSK9 is thus an attractive therapeutic target. Presently, this is achieved by using monoclonal antibodies for allosteric inhibition of the PCSK9–LDL-R interaction. Phase 2 and 3 clinical trials in patients with moderate and severe hypercholesterolemia (including FH) show that this approach is safe and highly efficacious to lower LDL-C and lipoprotein(a).

SUMMARY

PCSK9 has other biological roles observed in vitro and in animal studies, including viral entry into the cell, insulin resistance, and hepatic tissue repair. Given the potential number of humans exposed to this novel class of medications, careful evaluation of clinical trial results is warranted.