A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes.

BACKGROUND: Long-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing. RESULTS: We demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS. CONCLUSIONS: This study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.

A population-based survey of FBN1 variants in Iceland reveals underdiagnosis of Marfan syndrome.

Marfan syndrome (MFS) is an autosomal dominant condition characterized by aortic aneurysm, skeletal abnormalities, and lens dislocation, and is caused by variants in the FBN1 gene. To explore causes of MFS and the prevalence of the disease in Iceland we collected information from all living individuals with a clinical diagnosis of MFS in Iceland (n = 32) and performed whole-genome sequencing of those who did not have a confirmed genetic diagnosis (27/32). Moreover, to assess a potential underdiagnosis of MFS in Iceland we attempted a genotype-based approach to identify individuals with MFS. We interrogated deCODE genetics' database of 35,712 whole-genome sequenced individuals to search for rare sequence variants in FBN1. Overall, we identified 15 pathogenic or likely pathogenic variants in FBN1 in 44 individuals, only 22 of whom were previously diagnosed with MFS. The most common of these variants, NM_000138.4:c.8038 C > T p.(Arg2680Cys), is present in a multi-generational pedigree, and was found to stem from a single forefather born around 1840. The p.(Arg2680Cys) variant associates with a form of MFS that seems to have an enrichment of abdominal aortic aneurysm, suggesting that this may be a particularly common feature of p.(Arg2680Cys)-associated MFS. Based on these combined genetic and clinical data, we show that MFS prevalence in Iceland could be as high as 1/6,600 in Iceland, compared to 1/10,000 based on clinical diagnosis alone, which indicates underdiagnosis of this actionable genetic disorder.

Actionable Genotypes and Their Association with Life Span in Iceland.

BACKGROUND: In 2021, the American College of Medical Genetics and Genomics (ACMG) recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available. Evaluations of the association of actionable genotypes in these genes with life span are currently lacking. METHODS: We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings, version 3.0 (ACMG SF v3.0), list in the genomes of 57,933 Icelanders. We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database, the frequency of variants, and their associations with disease to create a manually curated set of actionable genotypes (variants). We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers. RESULTS: Through manual curation of 4405 sequence variants in the ACMG SF v3.0 genes, we identified 235 actionable genotypes in 53 genes. Of the 57,933 participants, 2306 (4.0%) carried at least one actionable genotype. We found shorter median survival among persons carrying actionable genotypes than among noncarriers. Specifically, we found that carrying an actionable genotype in a cancer gene was associated with survival that was 3 years shorter than that among noncarriers, with causes of death among carriers attributed primarily to cancer-related conditions. Furthermore, we found evidence of association between carrying an actionable genotype in certain genes in the cardiovascular disease group and a reduced life span. CONCLUSIONS: On the basis of the ACMG SF v3.0 guidelines, we found that approximately 1 in 25 Icelanders carried an actionable genotype and that carrying such a genotype was associated with a reduced life span. (Funded by deCODE Genetics-Amgen.).

Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura.

Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.

Large-scale plasma proteomics comparisons through genetics and disease associations.

High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.

Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events.

Importance: Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain. Objective: To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations. Design, Setting, and Participants: The primary analysis was a retrospective study of primary events among 13 540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals. Exposures: Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling. Main Outcomes and Measures: Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death. Results: In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical risk factor model (C index change, 0.022 [95% CI, 0.007 to 0.038]). Addition of the protein risk score alone to a clinical risk factor model also led to a significantly increased C index (difference, 0.014 [95% CI, 0.002 to 0.028]). Among White individuals in the secondary event population (6307 participants; 432 events; median follow-up, 2.2 years), the protein risk score had an HR of 1.62 per SD (95% CI, 1.48 to 1.79) and significantly increased C index when added to a clinical risk factor model (C index change, 0.026 [95% CI, 0.011 to 0.042]). The protein risk score was significantly associated with major adverse cardiovascular events among individuals of African and Asian ancestries in the secondary event population. Conclusions and Relevance: A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.

Histopathology and levels of proteins in plasma associate with survival after colorectal cancer diagnosis.

BACKGROUND: The TNM system is used to assess prognosis after colorectal cancer (CRC) diagnosis. Other prognostic factors reported include histopathological assessments of the tumour, tumour mutations and proteins in the blood. As some of these factors are strongly correlated, it is important to evaluate the independent effects they may have on survival. METHODS: Tumour samples from 2162 CRC patients were visually assessed for amount of tumour stroma, severity of lymphocytic infiltrate at the tumour margins and the presence of lymphoid follicles. Somatic mutations in the tumour were assessed for 2134 individuals. Pre-surgical levels of 4963 plasma proteins were measured in 128 individuals. The associations between these features and prognosis were inspected by a Cox Proportional Hazards Model (CPH). RESULTS: Levels of stroma, lymphocytic infiltration and presence of lymphoid follicles all associate with prognosis, along with high tumour mutation burden, high microsatellite instability and TP53 and BRAF mutations. The somatic mutations are correlated with the histopathology and none of the somatic mutations associate with survival in a multivariate analysis. Amount of stroma and lymphocytic infiltration associate with local invasion of tumours. Elevated levels of two plasma proteins, CA-125 and PPP1R1A, associate with a worse prognosis. CONCLUSIONS: Tumour stroma and lymphocytic infiltration variables are strongly associated with prognosis of CRC and capture the prognostic effects of tumour mutation status. CA-125 and PPP1R1A may be useful prognostic biomarkers in CRC.

DanMAC5: a browser of aggregated sequence variants from 8,671 whole genome sequenced Danish individuals.

OBJECTIVES: Allele counts of sequence variants obtained by whole genome sequencing (WGS) often play a central role in interpreting the results of genetic and genomic research. However, such variant counts are not readily available for individuals in the Danish population. Here, we present a dataset with allele counts for sequence variants (single nucleotide variants (SNVs) and indels) identified from WGS of 8,671 (5,418 females) individuals from the Danish population. The data resource is based on WGS data from three independent research projects aimed at assessing genetic risk factors for cardiovascular, psychiatric, and headache disorders. To enable the sharing of information on sequence variation in Danish individuals, we created summarized statistics on allele counts from anonymized data and made them available through the European Genome-phenome Archive (EGA, https://identifiers.org/ega. DATASET: EGAD00001009756 ) and in a dedicated browser, DanMAC5 (available at www.danmac5.dk ). The summary level data and the DanMAC5 browser provide insight into the allelic spectrum of sequence variants segregating in the Danish population, which is important in variant interpretation. DATA DESCRIPTION: Three WGS datasets with an average coverage of 30x were processed independently using the same quality control pipeline. Subsequently, we summarized, filtered, and merged allele counts to create a high-quality summary level dataset of sequence variants.

The population genomic legacy of the second plague pandemic.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%-40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th-19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Effect of booster vaccination against Delta and Omicron SARS-CoV-2 variants in Iceland.

By the end of July 2021, the majority of the Icelandic population had received vaccination against COVID-19. In mid-July a wave of SARS-CoV-2 infections, dominated by the Delta variant, spread through the population, followed by an Omicron wave in December. A booster vaccination campaign was initiated to curb the spread of the virus. We estimate the risk of infection for different vaccine combinations using vaccination data from 276,028 persons and 963,557 qPCR tests for 277,687 persons. We measure anti-Spike-RBD antibody levels and ACE2-Spike binding inhibitory activity in 371 persons who received one of four recommended vaccination schedules with or without an mRNA vaccine booster. Overall, we find different antibody levels and inhibitory activity in recommended vaccination schedules, reflected in the observed risk of SARS-CoV-2 infections. We observe an increased protection following mRNA boosters, against both Omicron and Delta variant infections, although BNT162b2 boosters provide greater protection against Omicron than mRNA-1273 boosters.

The sequences of 150,119 genomes in the UK Biobank.

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Population-level deficit of homozygosity unveils CPSF3 as an intellectual disability syndrome gene.

Predicting the pathogenicity of biallelic missense variants can be challenging. Here, we use a deficit of observed homozygous carriers of missense variants, versus an expected number in a set of 153,054 chip-genotyped Icelanders, to identify potentially pathogenic genotypes. We follow three missense variants with a complete deficit of homozygosity and find that their pathogenic effect in homozygous state ranges from severe childhood disease to early embryonic lethality. One of these variants is in CPSF3, a gene not previously linked to disease. From a set of clinically sequenced Icelanders, and by sequencing archival samples targeted through the Icelandic genealogy, we find four homozygous carriers. Additionally, we find two homozygous carriers of Mexican descent of another missense variant in CPSF3. All six homozygous carriers of missense variants in CPSF3 show severe intellectual disability, seizures, microcephaly, and abnormal muscle tone. Here, we show how the absence of certain homozygous genotypes from a large population set can elucidate causes of previously unexplained recessive diseases and early miscarriage.

Reconstruction of a large-scale outbreak of SARS-CoV-2 infection in Iceland informs vaccination strategies.

OBJECTIVES: The spread of SARS-CoV-2 is dependent on several factors, both biological and behavioural. The effectiveness of nonpharmaceutical interventions can be attributed largely to changes in human behaviour, but quantifying this effect remains challenging. Reconstructing the transmission tree of the third wave of SARS-CoV-2 infections in Iceland using contact tracing and viral sequence data from 2522 cases enables us to directly compare the infectiousness of distinct groups of persons. METHODS: The transmission tree enables us to model the effect that a given population prevalence of vaccination would have had on the third wave had one of three different vaccination strategies been implemented before that time. This allows us to compare the effectiveness of the strategies in terms of minimizing the number of cases, deaths, critical cases, and severe cases. RESULTS: We found that people diagnosed outside of quarantine (Rˆ=1.31) were 89% more infectious than those diagnosed while in quarantine (Rˆ=0.70) and that infectiousness decreased as a function of time spent in quarantine before diagnosis, with people diagnosed outside of quarantine being 144% more infectious than those diagnosed after ≥3 days in quarantine (Rˆ=0.54). People of working age, 16 to 66 years (Rˆ=1.08), were 46% more infectious than those outside of that age range (Rˆ=0.74). DISCUSSION: We found that vaccinating the population in order of ascending age or uniformly at random would have prevented more infections per vaccination than vaccinating in order of descending age, without significantly affecting the expected number of deaths, critical cases, or severe cases.

Functional dissection of inherited non-coding variation influencing multiple myeloma risk.

Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy.

Large-scale integration of the plasma proteome with genetics and disease.

The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF) < 1%). We tested plasma protein levels for association with 373 diseases and other traits and identified 257,490 associations. We integrated pQTL and genetic associations with diseases and other traits and found that 12% of 45,334 lead associations in the GWAS Catalog are with variants in high linkage disequilibrium with pQTL. We identified 938 genes encoding potential drug targets with variants that influence levels of possible biomarkers. Combining proteomics, genomics and transcriptomics, we provide a valuable resource that can be used to improve understanding of disease pathogenesis and to assist with drug discovery and development.

Sequence variants in malignant hyperthermia genes in Iceland: classification and actionable findings in a population database.

Malignant hyperthermia (MH) susceptibility is a rare life-threatening disorder that occurs upon exposure to a triggering agent. MH is commonly due to protein-altering variants in RYR1 and CACNA1S. The American College of Medical Genetics and Genomics recommends that when pathogenic and likely pathogenic variants in RYR1 and CACNA1S are incidentally found, they should be reported to the carriers. The detection of actionable variants allows the avoidance of exposure to triggering agents during anesthesia. First, we report a 10-year-old Icelandic proband with a suspected MH event, harboring a heterozygous missense variant NM_000540.2:c.6710G>A r.(6710g>a) p.(Cys2237Tyr) in the RYR1 gene that is likely pathogenic. The variant is private to four individuals within a three-generation family and absent from 62,240 whole-genome sequenced (WGS) Icelanders. Haplotype sharing and WGS revealed that the variant occurred as a somatic mosaicism also present in germline of the proband's paternal grandmother. Second, using a set of 62,240 Icelanders with WGS, we assessed the carrier frequency of actionable pathogenic and likely pathogenic variants in RYR1 and CACNA1S. We observed 13 actionable variants in RYR1, based on ClinVar classifications, carried by 43 Icelanders, and no actionable variant in CACNA1S. One in 1450 Icelanders carries an actionable variant for MH. Extensive sequencing allows for better classification and precise dating of variants, and WGS of a large fraction of the population has led to incidental findings of actionable MH genotypes.

Molecular benchmarks of a SARS-CoV-2 epidemic.

A pressing concern in the SARS-CoV-2 epidemic and other viral outbreaks, is the extent to which the containment measures are halting the viral spread. A straightforward way to assess this is to tally the active cases and the recovered ones throughout the epidemic. Here, we show how epidemic control can be assessed with molecular information during a well characterized epidemic in Iceland. We demonstrate how the viral concentration decreased in those newly diagnosed as the epidemic transitioned from exponential growth phase to containment phase. The viral concentration in the cases identified in population screening decreased faster than in those symptomatic and considered at high risk and that were targeted by the healthcare system. The viral concentration persists in recovering individuals as we found that half of the cases are still positive after two weeks. We demonstrate that accumulation of mutations in SARS-CoV-2 genome can be exploited to track the rate of new viral generations throughout the different phases of the epidemic, where the accumulation of mutations decreases as the transmission rate decreases in the containment phase. Overall, the molecular signatures of SARS-CoV-2 infections contain valuable epidemiological information that can be used to assess the effectiveness of containment measures.

Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits.

Long-read sequencing (LRS) promises to improve the characterization of structural variants (SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions). We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association of a rare deletion in PCSK9 with lower low-density lipoprotein (LDL) cholesterol levels, compared to the population average. We also discovered an association of a multiallelic SV in ACAN with height; we found 11 alleles that differed in the number of a 57-bp-motif repeat and observed a linear relationship between the number of repeats carried and height. These results show that SVs can be accurately characterized at the population scale using LRS data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.