Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs

Precision medicine programs to identify clinically relevant genetic variation have been revolutionized by access to increasingly affordable high-throughput sequencing technologies. A decade of continual drops in per-base sequencing costs means it is now feasible to sequence an individual patient genome and interrogate all classes of genetic variation for < $1,000 USD. However, while advances in these technologies have greatly simplified the ability to obtain patient sequence information, the timely analysis and interpretation of variant information remains a challenge for the rollout of large-scale precision medicine programs. This review will examine the challenges and potential solutions that exist in identifying predictive genetic biomarkers and pharmacogenetic variants in a patient and discuss the larger bioinformatic challenges likely to emerge in the future. It will examine how both software and hardware development are aiming to overcome issues in short read mapping, variant detection and variant interpretation. It will discuss the current state of the art for genetic disease and the remaining challenges to overcome for complex disease. Success across all types of disease will require novel statistical models and software in order to ensure precision medicine programs realize their full potential now and into the future

Detecting pathogenic variants in autoimmune diseases using high‐throughput sequencing

Sequencing the first human genome in 2003 took 15 years and cost $2.7 billion. Advances in sequencing technologies have since decreased costs to the point where it is now feasible to resequence a whole human genome for$1000 in a single day. These advances have allowed the generation of huge volumes of high‐quality human sequence data used to construct increasingly large catalogs of both population‐level and disease‐causing variation. The existence of such databases, coupled with a high‐quality human reference genome, means we are able to interrogate and annotate all types of genetic variation and identify pathogenic variants for many diseases. Increasingly, sequencing‐based approaches are being used to elucidate the underlying genetic cause of autoimmune diseases, a group of roughly 80 polygenic diseases characterized by abnormal immune responses where healthy tissue is attacked. Although sequence data generation has become routine and affordable, significant challenges remain with no gold‐standard methodology to identify pathogenic variants currently available. This review examines the latest methodologies used to identify pathogenic variants in autoimmune diseases and considers available sequencing options and subsequent bioinformatic methodologies and strategies. The development of reliable and robust sequencing and analytic workflows to detect pathogenic variants is critical to realize the potential of precision medicine programs where patient variant information is used to inform clinical practice

Efficacy of computational predictions of the functional effect of idiosyncratic pharmacogenetic variants

BACKGROUND: Pharmacogenetic variation is important to drug responses through diverse and complex mechanisms. Predictions of the functional impact of missense pharmacogenetic variants primarily rely on the degree of sequence conservation between species as a primary discriminator. However, idiosyncratic or off-target drug-variant interactions sometimes involve effects that are peripheral or accessory to the central systems in which a gene functions. Given the importance of sequence conservation to functional prediction tools—these idiosyncratic pharmacogenetic variants may violate the assumptions of predictive software commonly used to infer their effect. METHODS: Here we exhaustively assess the effectiveness of eleven missense mutation functional inference tools on all known pharmacogenetic missense variants contained in the Pharmacogenomics Knowledgebase (PharmGKB) repository. We categorize PharmGKB entries into sub-classes to catalog likely off-target interactions, such that we may compare predictions across different variant annotations. RESULTS: As previously demonstrated, functional inference tools perform variably across the complete set of PharmGKB variants, with large numbers of variants incorrectly classified as ‘benign’. However, we find substantial differences amongst PharmGKB variant sub-classes, particularly in variants known to cause off-target, type B adverse drug reactions, that are largely unrelated to the main pharmacological action of the drug. Specifically, variants associated with off-target effects (hence referred to as off-target variants) were most often incorrectly classified as ‘benign’. These results highlight the importance of understanding the underlying mechanism of pharmacogenetic variants and how variants associated with off-target effects will ultimately require new predictive algorithms. CONCLUSION: In this work we demonstrate that functional inference tools perform poorly on pharmacogenetic variants, particularly on subsets enriched for variants causing off-target, type B adverse drug reactions. We describe how to identify variants associated with off-target effects within PharmGKB in order to generate a training set of variants that is needed to develop new algorithms specifically for this class of variant. Development of such tools will lead to more accurate functional predictions and pave the way for the increased wide-spread adoption of pharmacogenetics in clinical practice

Laser-induced fluorescence studies of HfF+ produced by autoionization

Autoionization of Rydberg states of HfF, prepared using the optical-optical double resonance (OODR) technique, holds promise to create HfF+ in a particular Zeeman level of a rovibronic state for an electron electric dipole moment (eEDM) search. We characterize a vibronic band of Rydberg HfF at 54 cm-1 above the lowest ionization threshold and directly probe the state of the ions formed from this vibronic band by performing laser-induced fluorescence (LIF) on the ions. The Rydberg HfF molecules show a propensity to decay into only a few ion rotational states of a given parity and are found to preserve their orientation qualitatively upon autoionization. We show empirically that we can create 30% of the total ion yield in a particular |J+,M+> state and present a simplified model describing autoionization from a given Rydberg state that assumes no angular dynamics.Comment: 8 pages, 5 figure

A literature review of dispersal pathways of Aedes albopictus across different spatial scales: implications for vector surveillance

Background: Aedes albopictus is a highly invasive species and an important vector of dengue and chikungunya viruses. Indigenous to Southeast Asia, Ae. albopictus has successfully invaded every inhabited continent, except Antarctica, in the past 80 years. Vector surveillance and control at points of entry (PoE) is the most critical front line of defence against the introduction of Ae. albopictus to new areas. Identifying the pathways by which Ae. albopictus are introduced is the key to implementing effective vector surveillance to rapidly detect introductions and to eliminate them. Methods: A literature review was conducted to identify studies and data sources reporting the known and suspected dispersal pathways of human-mediated Ae. albopictus dispersal between 1940-2020. Studies and data sources reporting the first introduction of Ae. albopictus in a new country were selected for data extraction and analyses. Results: Between 1940-2020, Ae. albopictus was reported via various dispersal pathways into 86 new countries. Two main dispersal pathways were identified: (1) at global and continental spatial scales, maritime sea transport was the main dispersal pathway for Ae. albopictus into new countries in the middle to late 20th Century, with ships carrying used tyres of particular importance during the 1980s and 1990s, and (2) at continental and national spatial scales, the passive transportation of Ae. albopictus in ground vehicles and to a lesser extent the trade of used tyres and maritime sea transport appear to be the major drivers of Ae. albopictus dispersal into new countries, especially in Europe. Finally, the dispersal pathways for the introduction and spread of Ae. albopictus in numerous countries remains unknown, especially from the 1990s onwards. Conclusions: This review identified the main known and suspected dispersal pathways of human-mediated Ae. albopictus dispersal leading to the first introduction of Ae. albopictus into new countries and highlighted gaps in our understanding of Ae. albopictus dispersal pathways. Relevant advances in vector surveillance and genomic tracking techniques are presented and discussed in the context of improving vector surveillance

Genetic bias, diversity indices, physiochemical properties and CDR3 motifs divide auto-reactive from allo-reactive T-Cell repertoires

The distinct properties of allo-reactive T-cell repertoires are not well understood. To investigate whether auto-reactive and allo-reactive T-cell repertoires encoded distinct properties, we used dextramer enumeration, enrichment, single-cell T-cell receptor (TCR) sequencing and multiparameter analysis. We found auto-reactive and allo-reactive T-cells differed in mean ex vivo frequency which was antigen dependent. Allo-reactive T-cells showed clear differences in TCR architecture, with enriched usage of specific T-cell receptor variable (TRBJ) genes and broader use of T-cell receptor variable joining (TRBJ) genes. Auto-reactive T-cell repertoires exhibited complementary determining regions three (CDR3) lengths using a Gaussian distribution whereas allo-reactive T-cell repertoires exhibited distorted patterns in CDR3 length. CDR3 loops from allo-reactive T-cells showed distinct physical-chemical properties, tending to encode loops that were more acidic in charge. Allo-reactive T-cell repertoires differed in diversity metrics, tending to show increased overall diversity and increased homogeneity between repertoires. Motif analysis of CDR3 loops showed allo-reactive T-cell repertoires differed in motif preference which included broader motif use. Collectively, these data conclude that allo-reactive T-cell repertoires are indeed different to auto-reactive repertoires and provide tangible metrics for further investigations and validation. Given that the antigens studied here are overexpressed on multiple cancers and that allo-reactive TCRs often show increased ligand affinity, this new TCR bank also has translational potential for adoptive cell therapy, soluble TCR-based therapy and rational TCR design

Biodegradation of Crude Oil and Corexit 9500 in Arctic Seawater

The need to understand the biodegradation of oil and chemical dispersants in Arctic marine environments is increasing alongside growth in oil exploration and transport in the region. We chemically quantified biodegradation and abiotic losses of crude oil and Corexit 9500, when present separately, in incubations of Arctic seawater and identified microorganisms potentially involved in biodegradation of these substrates based on shifts in bacterial community structure (16S rRNA genes) and abundance of biodegradation genes (GeoChip 5.0 microarray). Incubations were performed over 28-day time courses using surface seawater collected from near-shore and offshore locations in the Chukchi Sea. Within 28 days, the indigenous microbial community biodegraded 36% (k = 0.010 day-1) and 41% (k = 0.014 day-1) of oil and biodegraded 77% and 33% (k = 0.015 day-1) of the Corexit 9500 component dioctyl sodium sulfosuccinate (DOSS) in respective near-shore and offshore incubations. Non-ionic surfactants (Span 80, Tween 80, and Tween 85) present in Corexit 9500 were non-detectable by 28 days due to a combination of abiotic losses and biodegradation. Microorganisms utilized oil and Corexit 9500 as growth substrates during the incubation, with the Corexit 9500 stimulating more extensive growth than oil within 28 days. Taxa known to include oil-degrading bacteria (e.g., Oleispira, Polaribacter, and Colwellia) and some oil biodegradation genes (e.g., alkB, nagG, and pchCF) increased in relative abundance in response to both oil and Corexit 9500. These results increase our understanding of oil and dispersant biodegradation in the Arctic and suggest that some bacteria may be capable of biodegrading both oil and Corexit 9500

Colchicine Does Not Reduce Abdominal Aortic Aneurysm Growth in a Mouse Model

Background and Aims. The nacht domain, leucine-rich repeat, and pyrin domain-containing protein 3 (NLRP3) inflammasome is upregulated in human abdominal aortic aneurysm (AAA), but its pathogenic role is unclear. The aims of this study were firstly to examine whether the inflammasome was upregulated in a mouse model of AAA and secondly to test whether the inflammasome inhibitor colchicine limited AAA growth. Methods. AAA was induced in eight-week-old male C57BL6/J mice with topical application of elastase to the infrarenal aorta and oral 3-aminopropionitrile (E-BAPN). For aim one, inflammasome activation, abdominal aortic diameter, and rupture were compared between mice with AAA and sham controls. For aim two, 3 weeks after AAA induction, mice were randomly allocated to receive colchicine (n=28, 0.2 mg/kg/d) or vehicle control (n=29). The primary outcome was the rate of maximum aortic diameter increase measured by ultrasound over 13 weeks. Results. There was upregulation of NLRP3 markers interleukin- (IL-) 1 beta (median, IQR; 15.67, 7.11-22.60 pg/mg protein versus 6.87, 4.54-11.60 pg/mg protein, p=.048) and caspase-1 (109, 83-155 relative luminosity units (RLU) versus 45, 38-65 RLU, p <.001) in AAA samples compared to controls. Aortic diameter increase over 80 days (mean difference, MD, 4.3 mm, 95% CI 3.3, 5.3, p <.001) was significantly greater in mice in which aneurysms were induced compared to sham controls. Colchicine did not significantly limit aortic diameter increase over 80 days (MD -0.1 mm, 95% CI -1.1, 0.86, p=.922). Conclusions. The inflammasome was activated in this mouse model of AAA; however, daily oral administration of colchicine did not limit AAA growth

Characterisation of tetraspanins from Schistosoma haematobium and evaluation of their potential as novel diagnostic markers

Schistosoma haematobium is the leading cause of urogenital schistosomiasis and it is recognised as a class 1 carcinogen due to the robust association of infection with bladder cancer. In schistosomes, tetraspanins (TSPs) are abundantly present in different parasite proteomes and could be potential diagnostic candidates due to their accessibility to the host immune system. The large extracellular loops of six TSPs from the secretome (including the soluble excretory/secretory products, tegument and extracellular vesicles) of S. haematobium (Sh-TSP-2, Sh-TSP-4, Sh-TSP-5, Sh-TSP-6, Sh-TSP-18 and Sh-TSP-23) were expressed in a bacterial expression system and polyclonal antibodies were raised to the recombinant proteins to confirm the anatomical sites of expression within the parasite. Sh-TSP-2, and Sh-TSP-18 were identified on the tegument, whereas Sh-TSP-4, Sh-TSP-5, Sh-TSP-6 and Sh-TSP-23 were identified both on the tegument and internal tissues of adult parasites. The mRNAs encoding these TSPs were differentially expressed throughout all schistosome developmental stages tested. The potential diagnostic value of three of these Sh-TSPs was assessed using the urine of individuals (stratified by infection intensity) from an endemic area of Zimbabwe. The three Sh-TSPs were the targets of urine IgG responses in all cohorts, including individuals with very low levels of infection (those positive for circulating anodic antigen but negative for eggs by microscopy). This study provides new antigen candidates to immunologically diagnose S. haematobium infection, and the work presented here provides compelling evidence for the use of a biomarker signature to enhance the diagnostic capability of these tetraspanins