A multigenerational study on phenotypic consequences of the most common causal variant of HNF1A-MODY

Aims/hypothesis Systematic studies on the phenotypic consequences of variants causal of HNF1A-MODY are rare. Our aim was to assess the phenotype of carriers of a single HNF1A variant and genetic and clinical factors affecting the clinical spectrum. Methods We conducted a family-based multigenerational study by comparing heterozygous carriers of the HNF1A p.(Gly292fs) variant with the non-carrier relatives irrespective of diabetes status. During more than two decades, 145 carriers and 131 non-carriers from 12 families participated in the study, and 208 underwent an OGTT at least once. We assessed the polygenic risk score for type 2 diabetes, age at onset of diabetes and measures of body composition, as well as plasma glucose, serum insulin, proinsulin, C-peptide, glucagon and NEFA response during the OGTT. Results Half of the carriers remained free of diabetes at 23 years, one-third at 33 years and 13% even at 50 years. The median age at diagnosis was 21 years (IQR 17–35). We could not identify clinical factors affecting the age at conversion; sex, BMI, insulin sensitivity or parental carrier status had no significant effect. However, for 1 SD unit increase of a polygenic risk score for type 2 diabetes, the predicted age at diagnosis decreased by 3.2 years. During the OGTT, the carriers had higher levels of plasma glucose and lower levels of serum insulin and C-peptide than the non-carriers. The carriers were also leaner than the non-carriers (by 5.0 kg, p=0.012, and by 2.1 kg/m2 units of BMI, p=2.2 × 10−4, using the first adult measurements) and, possibly as a result of insulin deficiency, demonstrated higher lipolytic activity (with medians of NEFA at fasting 621 vs 441 μmol/l, p=0.0039; at 120 min during an OGTT 117 vs 64 μmol/l, p=3.1 × 10−5). Conclusions/interpretation The most common causal variant of HNF1A-MODY, p.(Gly292fs), presents not only with hyperglycaemia and insulin deficiency, but also with increased lipolysis and markedly lower adult BMI. Serum insulin was more discriminative than C-peptide between carriers and non-carriers. A considerable proportion of carriers develop diabetes after young adulthood. Even among individuals with a monogenic form of diabetes, polygenic risk of diabetes modifies the age at onset of diabetes. Graphical abstract

Effect sizes of causal variants for gene expression and complex traits differ between populations

Despite the growing number of genome-wide association studies (GWAS) for complex traits, it remains unclear whether effect sizes of causal genetic variants differ between populations. In principle, effect sizes of causal variants could differ between populations due to gene-by-gene or gene-by-environment interactions. However, comparing causal variant effect sizes is challenging: it is difficult to know which variants are causal, and comparisons of variant effect sizes are confounded by differences in linkage disequilibrium (LD) structure between ancestries. Here, we develop a method to assess causal variant effect size differences that overcomes these limitations. Specifically, we leverage the fact that segments of European ancestry shared between European-American and admixed African-American individuals have similar LD structure, allowing for unbiased comparisons of variant effect sizes in European ancestry segments. We apply our method to two types of traits: gene expression and low-density lipoprotein cholesterol (LDL-C). We find that causal variant effect sizes for gene expression are significantly different between European-Americans and African-Americans; for LDL-C, we observe a similar point estimate although this is not significant, likely due to lower statistical power. Cross-population differences in variant effect sizes highlight the role of genetic interactions in trait architecture and will contribute to the poor portability of polygenic scores across populations, reinforcing the importance of conducting GWAS on individuals of diverse ancestries and environments.

Identification of Drug Transporter Genomic Variants and Inhibitors that Protect Against Doxorubicin-Induced Cardiotoxicity

Background: Multiple pharmacogenomic studies have identified the synonymous genomic variant rs7853758 (G>A, L461L) and the intronic variant rs885004 in SLC28A3 as statistically associated with a lower incidence of anthracycline-induced cardiotoxicity (AIC). However, the true causal variant(s), the cardioprotective mechanism of this locus, the role of SLC28A3 and other solute carrier (SLC) transporters in AIC, and the suitability of SLC transporters as targets for cardioprotective drugs has not been investigated. Methods: Six well-phenotyped, doxorubicin-treated pediatric patients from the original association study cohort were re-recruited and human induced pluripotent stem cell-derived cardiomyocytes were generated. Patient-specific doxorubicin-induced cardiotoxicity (DIC) was then characterized using assays of cell viability, activated caspase 3/7, and doxorubicin uptake. The role of SLC28A3 in DIC was then queried using overexpression and knockout of SLC28A3 in isogenic hiPSCs using a CRISPR/Cas9. Fine−mapping of the SLC28A3 locus was then completed after SLC28A3 resequencing and an extended in silico haplotype and functional analysis. Genome editing of potential causal variant was done using cytosine base editor. SLC28A3−AS1 overexpression was done using a lentiviral plasmid-based transduction and was validated using stranded RNA-Seq after ribosomal RNA depletion. Drug screening was done using the Prestwick drug library ( n = 1200) followed by in vivo validation in mice. The effect of desipramine on DOX cytotoxicity was also investigated in eight cancer cell lines. Results: Here, using the most commonly used anthracycline, doxorubicin, we demonstrate that patient-derived cardiomyocytes recapitulate the cardioprotective effect of the SLC28A3 locus and that SLC28A3 expression influences the severity of DIC. Using Nanopore¬-based fine-mapping and base editing we identify a novel cardioprotective SNP rs11140490 in the SLC28A3 locus which exerts its effect by regulating an antisense long noncoding-RNA ( SLC28A3-AS1 ) that overlaps with SLC28A3 . Using high-throughput drug screening in patient-derived cardiomyocytes and whole organism validation in mice, we identify the SLC competitive inhibitor desipramine as protective against DIC. Conclusions: This work demonstrates the power of the human induced pluripotent stem cell model to take a SNP from a statistical association through to drug discovery, providing human cell-tested data for clinical trials to attenuate DIC.

A Missense Variant in the Bardet-Biedl Syndrome 2 Gene (BBS2) Leads to a Novel Syndromic Retinal Degeneration in the Shetland Sheepdog

Canine progressive retinal atrophy (PRA) describes a group of hereditary diseases characterized by photoreceptor cell death in the retina, leading to visual impairment. Despite the identification of multiple PRA-causing variants, extensive heterogeneity of PRA is observed across and within dog breeds, with many still genetically unsolved. This study sought to elucidate the causal variant for a distinct form of PRA in the Shetland sheepdog, using a whole-genome sequencing approach. Filtering variants from a single PRA-affected Shetland sheepdog genome compared to 176 genomes of other breeds identified a single nucleotide variant in exon 11 of the Bardet–Biedl syndrome-2 gene (BBS2) (c.1222G>C; p.Ala408Pro). Genotyping 1386 canids of 155 dog breeds, 15 cross breeds and 8 wolves indicated the c.1222G>C variant was only segregated within Shetland sheepdogs. Out of 505 Shetland sheepdogs, seven were homozygous for the variant. Clinical history and photographs for three homozygotes indicated the presence of a novel phenotype. In addition to PRA, additional clinical features in homozygous dogs support the discovery of a novel syndromic PRA in the breed. The development and utilization of a diagnostic DNA test aim to prevent the mutation from becoming more prevalent in the breed.

seqr: a web-based analysis and collaboration tool for rare disease genomics

Exome and genome sequencing have become the tools of choice for rare disease diagnosis, leading to large amounts of data available for analyses. To identify causal variants in these datasets, powerful filtering and decision support tools that can be efficiently used by clinicians and researchers are required. To address this need, we developed seqr - an open source, web-based tool for family-based monogenic disease analysis that allows researchers to work collaboratively to search and annotate genomic callsets. To date, seqr is being used in several research pipelines and one clinical diagnostic lab. In our own experience through the Broad Institute Center for Mendelian Genomics, seqr has enabled analyses of over 10,000 families, supporting the diagnosis of more than 3,800 individuals with rare disease and discovery of over 300 novel disease genes. Here we describe a framework for genomic analysis in rare disease that leverages seqr's capabilities for variant filtration, annotation, and causal variant identification, as well as support for research collaboration and data sharing. The seqr platform is available as open source software, allowing low-cost participation in rare disease research, and a community effort to support diagnosis and gene discovery in rare disease.

Chronic Pancreatitis: The True Pathogenic Culprit within the SPINK1 N34S-Containing Haplotype Is No Longer at Large

A diverse range of loss-of-function variants in the SPINK1 gene (encoding pancreatic secretory trypsin inhibitor) has been identified in patients with chronic pancreatitis (CP). The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser or N34S) variant (rs17107315:T>C) is one of the most important heritable risk factors for CP as a consequence of its relatively high prevalence worldwide (population allele frequency ≈ 1%) and its considerable effect size (odds ratio ≈ 11). The causal variant responsible for this haplotype has been intensively investigated over the past two decades. The different hypotheses tested addressed whether the N34S missense variant has a direct impact on enzyme structure and function, whether c.101A>G could affect pre-mRNA splicing or mRNA stability, and whether another variant in linkage disequilibrium with c.101A>G might be responsible for the observed association with CP. Having reviewed the currently available genetic and experimental data, we conclude that c.-4141G>T (rs142703147:C>A), which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L cis-regulatory module located ∼4 kb upstream of the SPINK1 promoter, can be designated as the causal variant beyond reasonable doubt. This case illustrates the difficulties inherent in determining the identity of the causal variant underlying an initially identified disease association.

The flashfm approach for fine-mapping multiple quantitative traits

Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.

Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits

The number of variants that have a non-zero effect on a trait (i.e. polygenicity) is a fundamental parameter in the study of the genetic architecture of a complex trait. Although many previous studies have investigated polygenicity at a genome-wide scale, a detailed understanding of how polygenicity varies across genomic regions is currently lacking. In this work, we propose an accurate and scalable statistical framework to estimate regional polygenicity for a complex trait. We show that our approach yields approximately unbiased estimates of regional polygenicity in simulations across a wide-range of various genetic architectures. We then partition the polygenicity of anthropometric and blood pressure traits across 6-Mb genomic regions (N = 290K, UK Biobank) and observe that all analyzed traits are highly polygenic: over one-third of regions harbor at least one causal variant for each of the traits analyzed. Additionally, we observe wide variation in regional polygenicity: on average across all traits, 48.9% of regions contain at least 5 causal SNPs, 5.44% of regions contain at least 50 causal SNPs. Finally, we find that heritability is proportional to polygenicity at the regional level, which is consistent with the hypothesis that heritability enrichments are largely driven by the variation in the number of causal SNPs.

Lethal variants in humans: lessons learned from a large molecular autopsy cohort

Background Molecular autopsy refers to DNA-based identification of the cause of death. Despite recent attempts to broaden its scope, the term remains typically reserved to sudden unexplained death in young adults. In this study, we aim to showcase the utility of molecular autopsy in defining lethal variants in humans. Methods We describe our experience with a cohort of 481 cases in whom the cause of premature death was investigated using DNA from the index or relatives (molecular autopsy by proxy). Molecular autopsy tool was typically exome sequencing although some were investigated using targeted approaches in the earlier stages of the study; these include positional mapping, targeted gene sequencing, chromosomal microarray, and gene panels. Results The study includes 449 cases from consanguineous families and 141 lacked family history (simplex). The age range was embryos to 18 years. A likely causal variant (pathogenic/likely pathogenic) was identified in 63.8% (307/481), a much higher yield compared to the general diagnostic yield (43%) from the same population. The predominance of recessive lethal alleles allowed us to implement molecular autopsy by proxy in 55 couples, and the yield was similarly high (63.6%). We also note the occurrence of biallelic lethal forms of typically non-lethal dominant disorders, sometimes representing a novel bona fide biallelic recessive disease trait. Forty-six disease genes with no OMIM phenotype were identified in the course of this study. The presented data support the candidacy of two other previously reported novel disease genes (FAAH2 and MSN). The focus on lethal phenotypes revealed many examples of interesting phenotypic expansion as well as remarkable variability in clinical presentation. Furthermore, important insights into population genetics and variant interpretation are highlighted based on the results. Conclusions Molecular autopsy, broadly defined, proved to be a helpful clinical approach that provides unique insights into lethal variants and the clinical annotation of the human genome.

Transmission event of SARS-CoV-2 delta variant reveals multiple vaccine breakthrough infections

Background This study aims to identify the causative strain of SARS-CoV-2 in a cluster of vaccine breakthroughs. Vaccine breakthrough by a highly transmissible SARS-CoV-2 strain is a risk to global public health. Methods Nasopharyngeal swabs from suspected vaccine breakthrough cases were tested for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) by qPCR (quantitative polymerase chain reaction) for Wuhan-Hu1 and alpha variant. Positive samples were then sequenced by Swift Normalase Amplicon Panels to determine the causal variant. GATK (genome analysis toolkit) variants were filtered with allele fraction ≥80 and min read depth 30x. Results Viral sequencing revealed an infection cluster of 6 vaccinated patients infected with the delta (B.1.617.2) SARS-CoV-2 variant. With no history of vaccine breakthrough, this suggests the delta variant may possess immune evasion in patients that received the Pfizer BNT162b2, Moderna mRNA-1273, and Covaxin BBV152. Conclusions Delta variant may pose the highest risk out of any currently circulating SARS-CoV-2 variants, with previously described increased transmissibility over alpha variant and now, possible vaccine breakthrough. Funding Parts of this work was supported by the National Institute of Allergy and Infectious Diseases (1U19AI144297) and Baylor College of Medicine internal funding.