Large-Scale Screening for Monogenic and Clinically Defined Familial Hypercholesterolemia in Iceland

Objective: Familial hypercholesterolemia (FH) is traditionally defined as a monogenic disease characterized by severely elevated LDL-C (low-density lipoprotein cholesterol) levels. In practice, FH is commonly a clinical diagnosis without confirmation of a causative mutation. In this study, we sought to characterize and compare monogenic and clinically defined FH in a large sample of Icelanders. Approach and Results: We whole-genome sequenced 49 962 Icelanders and imputed the identified variants into an overall sample of 166 281 chip-genotyped Icelanders. We identified 20 FH mutations in LDLR, APOB, and PCSK9 with combined prevalence of 1 in 836. Monogenic FH was associated with severely elevated LDL-C levels and increased risk of premature coronary disease, aortic valve stenosis, and high burden of coronary atherosclerosis. We used a modified version of the Dutch Lipid Clinic Network criteria to screen for the clinical FH phenotype among living adult participants (N=79 058). Clinical FH was found in 2.2% of participants, of whom only 5.2% had monogenic FH. Mutation-negative clinical FH has a strong polygenic basis. Both individuals with monogenic FH and individuals with mutation-negative clinical FH were markedly undertreated with cholesterol-lowering medications and only a minority attained an LDL-C target of <2.6 mmol/L (<100 mg/dL; 11.0% and 24.9%, respectively) or <1.8 mmol/L (<70 mg/dL; 0.0% and 5.2%, respectively), as recommended for primary prevention by European Society of Cardiology/European Atherosclerosis Society cholesterol guidelines. Conclusions: Clinically defined FH is a relatively common phenotype that is explained by monogenic FH in only a minority of cases. Both monogenic and clinical FH confer high cardiovascular risk but are markedly undertreated.

Association of Genetically Predicted Lipid Levels With the Extent of Coronary Atherosclerosis in Icelandic Adults

Importance

Genetic studies have evaluated the influence of blood lipid levels on the risk of coronary artery disease (CAD), but less is known about how they are associated with the extent of coronary atherosclerosis.

Objective

To estimate the contributions of genetically predicted blood lipid levels on the extent of coronary atherosclerosis.

Design, Setting, and Participants

This genetic study included Icelandic adults who had undergone coronary angiography or assessment of coronary artery calcium using cardiac computed tomography. The study incorporates data collected from January 1987 to December 2017 in Iceland in the Swedish Coronary Angiography and Angioplasty Registry and 2 registries of individuals who had undergone percutaneous coronary interventions and coronary artery bypass grafting. For each participant, genetic scores were calculated for levels of non-high-density lipoprotein cholesterol (non-HDL-C), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides, based on reported effect sizes of 345 independent, lipid-associated variants. The genetic scores' predictive ability for lipid levels was assessed in more than 87 000 Icelandic adults. A mendelian randomization approach was used to estimate the contribution of each lipid trait.

Exposures

Genetic scores for levels of non-HDL-C, LDL-C, HDL-C, and triglycerides.

Main Outcomes and Measures

The extent of angiographic CAD and coronary artery calcium quantity.

Results

A total of 12 460 adults (mean [SD] age, 65.1 [10.7] years; 8383 men [67.3%]) underwent coronary angiography, and 4837 had coronary artery calcium assessed by computed tomography. A genetically predicted increase in non-HDL-C levels by 1 SD (38 mg/dL [to convert to millimoles per liter, multiply by 0.0259]) was associated with greater odds of obstructive CAD (odds ratio [OR], 1.83 [95% CI, 1.63-2.07]; P = 2.8 × 10-23). Among patients with obstructive CAD, there were significant associations with multivessel disease (OR, 1.26 [95% CI, 1.11-1.44]; P = 4.1 × 10-4) and 3-vessel disease (OR, 1.47 [95% CI, 1.26-1.72]; P = 9.2 × 10-7). There were also significant associations with the presence of coronary artery calcium (OR, 2.04 [95% CI, 1.70-2.44]; P = 5.3 × 10-15) and loge-transformed coronary artery calcium (effect, 0.70 [95% CI, 0.53-0.87]; P = 1.0 × 10-15). Genetically predicted levels of non-HDL-C remained associated with obstructive CAD and coronary artery calcium extent even after accounting for the association with LDL-C. Genetically predicted levels of HDL-C and triglycerides were associated individually with the extent of coronary atherosclerosis, but not after accounting for the association with non-HDL cholesterol.

Conclusions and Relevance

In this study, genetically predicted levels of non-HDL-C were associated with the extent of coronary atherosclerosis as estimated by 2 different methods. The association was stronger than for genetically predicted levels of LDL-C. These findings further support the notion that non-HDL-C may be a better marker of the overall burden of atherogenic lipoproteins than LDL-C.

Variants in ELL2 influencing immunoglobulin levels associate with multiple myeloma

Multiple myeloma (MM) is characterized by an uninhibited, clonal growth of plasma cells. While first-degree relatives of patients with MM show an increased risk of MM, the genetic basis of inherited MM susceptibility is incompletely understood. Here we report a genome-wide association study in the Nordic region identifying a novel MM risk locus at ELL2 (rs56219066T; odds ratio (OR)=1.25; P=9.6 × 10(-10)). This gene encodes a stoichiometrically limiting component of the super-elongation complex that drives secretory-specific immunoglobulin mRNA production and transcriptional regulation in plasma cells. We find that the MM risk allele harbours a Thr298Ala missense variant in an ELL2 domain required for transcription elongation. Consistent with a hypomorphic effect, we find that the MM risk allele also associates with reduced levels of immunoglobulin A (IgA) and G (IgG) in healthy subjects (P=8.6 × 10(-9) and P=6.4 × 10(-3), respectively) and, potentially, with an increased risk of bacterial meningitis (OR=1.30; P=0.0024).

Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the ‘missing heritability’. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10⁻⁴ (95% confidence interval [9.6×10⁻⁵–3.1×10⁻⁴]); accounts overall for 0.5% [0.19%–0.82%] of severe childhood obesity cases (P = 3.8×10⁻¹⁰; odds ratio = 25.0 [9.9–60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m⁻² [1.8–10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

A statistical approach to identify ancient template DNA

One of the key problems in the study of ancient DNA is that of authenticating sequences obtained from PCR amplifications of highly degraded samples. Contamination of ancient samples and postmortem damage to endogenous DNA templates are the major obstacles facing researchers in this task. In particular, the authentication of sequences obtained from ancient human remains is thought by many to be rather challenging. We propose a novel approach, based on the c statistic, that can be employed to help identify the sequence motif of an endogenous template, based on a sample of sequences that reflect the nucleotide composition of individual template molecules obtained from ancient tissues (such as cloned products from a PCR amplification). The c statistic exploits as information the most common form of postmortem damage observed among clone sequences in ancient DNA studies, namely, lesion-induced substitutions caused by cytosine deamination events. Analyses of simulated sets of templates with miscoding lesions and real sets of clone sequences from the literature indicate that the c-based approach is highly effective in identifying endogenous sequence motifs, even when they are not present among the sampled clones. The proposed approach is likely to be of general use to researchers working with DNA from ancient tissues, particularly from human remains, where authentication of results has been most challenging.