Prevalence of CYP2C19*2 and CYP2C19*3 Allelic Variants and Clopidogrel Use in Patients with Cardiovascular Disease in Trinidad & Tobago.

INTRODUCTION: Trinidad & Tobago has the highest prevalence of cardiovascular disease (CVD) in the Caribbean and clopidogrel is a ubiquitously used treatment. Yet, the extent of genetically mediated clopidogrel resistance is unknown. To determine this, we investigated whether the association between CYP2C19*2 and CYP2C19*3 genetic variants and clopidogrel resistance holds, and calculated the frequencies of these in the Trinidadian CVD population. METHODS: Demographic data, clinical data, and a saliva sample were collected under informed consent from 22 patients with CVD on dual anti-platelet therapy whose biochemical resistance to clopidogrel is known, and a further 162 patients accessing the main public CVD clinic in Trinidad and who are either currently being treated or are likely to be treated with clopidogrel. A polymerase chain reaction (PCR) and restriction enzyme digestion procedure was used to genotype each patient for the CYP2C19*2 and CYP2C19*3 allelic variants. Genotype was compared to known clopidogrel resistance in the 22 patients, and to disease status and clopidogrel usage in the larger cohort. RESULTS: CYP2C19*2 genotype was concordant with clopidogrel resistance. CYP2C19*2 was detected in 61.1% (99/162) of patients and CYP2C19*3 was undetected. Clopidogrel was the most prescribed antiplatelet therapy (42%). A total of 120 people presented with coronary artery disease (CAD) and 52.5% of these (n = 63/120) are currently prescribed clopidogrel. 63.5% (40/63) of patients with CAD who are prescribed clopidogrel carry the CYP2C19*2 allele; ten homozygous and 30 heterozygous. Indian patients comprised 65% of the cohort and were four times more likely to carry the CYP2C19*2 allele than African patients. CONCLUSIONS: A large proportion of Trinidadian patients with CVD who are prescribed or may be prescribed clopidogrel carry genetic variants associated with clopidogrel resistance. These results emphasize the clinical need for further investigation into whether CYP2C19*2 genotype should guide clopidogrel use for the cardiovascular disease population in Trinidad & Tobago. A slide deck is available for this article.

Correction: Implementation of Genomic Surveillance of SARS-CoV-2 in the Caribbean: Lessons learned for sustainability in resource-limited settings.

[This corrects the article DOI: 10.1371/journal.pgph.0001455.].

Implementation of genomic surveillance of SARS-CoV-2 in the Caribbean: Lessons learned for sustainability in resource-limited settings.

The COVID-19 pandemic highlighted the importance of global genomic surveillance to monitor the emergence and spread of SARS-CoV-2 variants and inform public health decision-making. Until December 2020 there was minimal capacity for viral genomic surveillance in most Caribbean countries. To overcome this constraint, the COVID-19: Infectious disease Molecular epidemiology for PAthogen Control & Tracking (COVID-19 IMPACT) project was implemented to establish rapid SARS-CoV-2 whole genome nanopore sequencing at The University of the West Indies (UWI) in Trinidad and Tobago (T&T) and provide needed SARS-CoV-2 sequencing services for T&T and other Caribbean Public Health Agency Member States (CMS). Using the Oxford Nanopore Technologies MinION sequencing platform and ARTIC network sequencing protocols and bioinformatics pipeline, a total of 3610 SARS-CoV-2 positive RNA samples, received from 17 CMS, were sequenced in-situ during the period December 5th 2020 to December 31st 2021. Ninety-one Pango lineages, including those of five variants of concern (VOC), were identified. Genetic analysis revealed at least 260 introductions to the CMS from other global regions. For each of the 17 CMS, the percentage of reported COVID-19 cases sequenced by the COVID-19 IMPACT laboratory ranged from 0·02% to 3·80% (median = 1·12%). Sequences submitted to GISAID by our study represented 73·3% of all SARS-CoV-2 sequences from the 17 CMS available on the database up to December 31st 2021. Increased staffing, process and infrastructural improvement over the course of the project helped reduce turnaround times for reporting to originating institutions and sequence uploads to GISAID. Insights from our genomic surveillance network in the Caribbean region directly influenced non-pharmaceutical countermeasures in the CMS countries. However, limited availability of associated surveillance and clinical data made it challenging to contextualise the observed SARS-CoV-2 diversity and evolution, highlighting the need for development of infrastructure for collecting and integrating genomic sequencing data and sample-associated metadata.

Factors associated with breast cancer recurrence and survival at Sangre Grande Hospital, Trinidad.

PURPOSE: The aim of this study is to determine the demographic, pathological, and treatment-related factors that predict recurrence and survival in a Trinidadian cohort of breast cancer patients. METHODS: The inclusion criteria for this study were female, over 18 years, and with a primary breast cancer diagnosis confirmed by a biopsy report occurring between 2010 and 2015 at Sangre Grande Hospital, Trinidad. Univariate associations with 5-year recurrence-free survival and 5-year overall survival were calculated using the Kaplan-Meier method for categorical variables and Cox Proportional Hazards for continuous variables. A multivariate model for prediction of recurrence and survival was determined using Cox regression. RESULTS: For the period 2010-2015, 202 records were abstracted. Five-year overall survival and recurrence-free survival rates were found to be 74.3% and 56.4%, respectively. Median times from first suspicious finding to date of biopsy report, date of surgery, and date of chemotherapy were 63 days, 125 days, and 189 days, respectively. In the univariate analysis, age (p = 0.038), stage (p < 0.001), recurrence (p = 0.035), surgery (p = 0.016), ER (p < 0.001) status, PR status (p < 0.001), and subtype (p < 0.001) were significantly associated with survival. Additionally, stage (p = 0.004), N score (p = 0.002), ER (p = 0.028) status, PR (p = 0.018) status, and subtype (p = 0.025) were significantly associated with recurrence. In the Cox multivariate model, Stage 4 was a significant predictor of survival (HR 6.77, 95% CI [0.09-2.49], p = 0.047) and N3 score was a significant predictor of recurrence (HR 4.47, 95% CI [1.29-15.54], p = 0.018). CONCLUSION: This study reports a 5-year breast cancer survival rate of 74.3%, and a recurrence-free survival rate of 56.4% in Trinidad for the period 2010-2015.

Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562.

K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and indels (both corrected for CN in aneuploid regions), loss of heterozygosity, megabase-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs), including small and large-scale complex SVs and nonreference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT Taking aneuploidy into account, we reanalyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.

Whole-genome sequencing analysis of CNV using low-coverage and paired-end strategies is efficient and outperforms array-based CNV analysis.

BACKGROUND: Copy number variation (CNV) analysis is an integral component of the study of human genomes in both research and clinical settings. Array-based CNV analysis is the current first-tier approach in clinical cytogenetics. Decreasing costs in high-throughput sequencing and cloud computing have opened doors for the development of sequencing-based CNV analysis pipelines with fast turnaround times. We carry out a systematic and quantitative comparative analysis for several low-coverage whole-genome sequencing (WGS) strategies to detect CNV in the human genome. METHODS: We compared the CNV detection capabilities of WGS strategies (short insert, 3 kb insert mate pair and 5 kb insert mate pair) each at 1×, 3× and 5× coverages relative to each other and to 17 currently used high-density oligonucleotide arrays. For benchmarking, we used a set of gold standard (GS) CNVs generated for the 1000 Genomes Project CEU subject NA12878. RESULTS: Overall, low-coverage WGS strategies detect drastically more GS CNVs compared with arrays and are accompanied with smaller percentages of CNV calls without validation. Furthermore, we show that WGS (at ≥1× coverage) is able to detect all seven GS deletion CNVs >100 kb in NA12878, whereas only one is detected by most arrays. Lastly, we show that the much larger 15 Mbp Cri du chat deletion can be readily detected with short-insert paired-end WGS at even just 1× coverage. CONCLUSIONS: CNV analysis using low-coverage WGS is efficient and outperforms the array-based analysis that is currently used for clinical cytogenetics.

A situational analysis of breast cancer early detection services in Trinidad and Tobago.

PURPOSE: A situational analysis of breast cancer (BC) early detection services was carried out to investigate whether Trinidad and Tobago (T&T) has the framework for successful organized national screening. METHODS: An online survey was designed to assess the availability, accessibility, quality control and assurance (QC&A), and monitoring and evaluation (M&E) mechanisms for public and private BC early detection. A focus group with local radiologists (n = 3) was held to identify unaddressed challenges and make recommendations for improvement. RESULTS: Major public hospitals offer free detection services with wait times of 1-6 months for an appointment. Private institutions offer mammograms for TTD$240 (USD$37) at minimum with same day service. Both sectors report a lack of trained staff. Using 1.2 mammograms per 10,000 women ≥40 years as sufficient, the public sector's rate of 0.19 mammograms per 10,000 women ≥40 years for screening and diagnosis is inadequate. Program M&E mechanisms, QC&A guidelines for machinery use, delays in receipt of pathology reports, and unreliable drug access are further unaddressed challenges. CONCLUSION: T&T must first strengthen its human and physical resources, implement M&E and QC&A measures, strengthen cancer care, and address other impediments to BC early detection before investing in nationally organized BC screening.

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

BACKGROUND: High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. RESULTS: The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. CONCLUSIONS: High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

Exome sequencing and genome-wide copy number variant mapping reveal novel associations with sensorineural hereditary hearing loss.

BACKGROUND: The genetic diversity of loci and mutations underlying hereditary hearing loss is an active area of investigation. To identify loci associated with predominantly non-syndromic sensorineural hearing loss, we performed exome sequencing of families and of single probands, as well as copy number variation (CNV) mapping in a case-control cohort. RESULTS: Analysis of three distinct families revealed several candidate loci in two families and a single strong candidate gene, MYH7B, for hearing loss in one family. MYH7B encodes a Type II myosin, consistent with a role for cytoskeletal proteins in hearing. High-resolution genome-wide CNV analysis of 150 cases and 157 controls revealed deletions in genes known to be involved in hearing (e.g. GJB6, OTOA, and STRC, encoding connexin 30, otoancorin, and stereocilin, respectively), supporting CNV contributions to hearing loss phenotypes. Additionally, a novel region on chromosome 16 containing part of the PDXDC1 gene was found to be frequently deleted in hearing loss patients (OR=3.91, 95% CI: 1.62-9.40, p=1.45×10(-7)). CONCLUSIONS: We conclude that many known as well as novel loci and distinct types of mutations not typically tested in clinical settings can contribute to the etiology of hearing loss. Our study also demonstrates the challenges of exome sequencing and genome-wide CNV mapping for direct clinical application, and illustrates the need for functional and clinical follow-up as well as curated open-access databases.

Mutations in NGLY1 cause an inherited disorder of the endoplasmic reticulum-associated degradation pathway.

PURPOSE: The endoplasmic reticulum-associated degradation pathway is responsible for the translocation of misfolded proteins across the endoplasmic reticulum membrane into the cytosol for subsequent degradation by the proteasome. To define the phenotype associated with a novel inherited disorder of cytosolic endoplasmic reticulum-associated degradation pathway dysfunction, we studied a series of eight patients with deficiency of N-glycanase 1. METHODS: Whole-genome, whole-exome, or standard Sanger sequencing techniques were employed. Retrospective chart reviews were performed in order to obtain clinical data. RESULTS: All patients had global developmental delay, a movement disorder, and hypotonia. Other common findings included hypolacrima or alacrima (7/8), elevated liver transaminases (6/7), microcephaly (6/8), diminished reflexes (6/8), hepatocyte cytoplasmic storage material or vacuolization (5/6), and seizures (4/8). The nonsense mutation c.1201A>T (p.R401X) was the most common deleterious allele. CONCLUSION: NGLY1 deficiency is a novel autosomal recessive disorder of the endoplasmic reticulum-associated degradation pathway associated with neurological dysfunction, abnormal tear production, and liver disease. The majority of patients detected to date carry a specific nonsense mutation that appears to be associated with severe disease. The phenotypic spectrum is likely to enlarge as cases with a broader range of mutations are detected.

Impacts of variation in the human genome on gene regulation.

Recent advances in fast and inexpensive DNA sequencing have enabled the extensive study of genomic and transcriptomic variation in humans. Human genomic variation is composed of sequence and structural changes including single-nucleotide and multinucleotide variants, short insertions or deletions (indels), larger copy number variants, and similarly sized copy neutral inversions and translocations. It is now well established that any two genomes differ extensively and that structural changes constitute a prominent source of this variation. There have also been major technological advances in RNA sequencing to globally quantify and describe diversity in transcripts. Large consortia such as the 1000 Genomes Project and the ENCODE (ENCyclopedia Of DNA Elements) Project are producing increasingly comprehensive maps outlining the regions of the human genome containing variants and functional elements, respectively. Integration of genetic variation data and extensive annotation of functional genomic elements, along with the ability to measure global transcription, allow the impacts of genetic variants on gene expression to be resolved. There are several well-established models by which genetic variants affect gene regulation depending on the type, nature, and position of the variant with respect to the affected genes. These effects can be manifested in two ways: changes to transcript sequences and isoforms by coding variants, and changes to transcript abundance by dosage or regulatory variants. Here, we review the current state of how genetic variations impact gene regulation locally and globally in the human genome.

Computational and bioinformatics frameworks for next-generation whole exome and genome sequencing.

It has become increasingly apparent that one of the major hurdles in the genomic age will be the bioinformatics challenges of next-generation sequencing. We provide an overview of a general framework of bioinformatics analysis. For each of the three stages of (1) alignment, (2) variant calling, and (3) filtering and annotation, we describe the analysis required and survey the different software packages that are used. Furthermore, we discuss possible future developments as data sources grow and highlight opportunities for new bioinformatics tools to be developed.

Child development and structural variation in the human genome.

Structural variation of the human genome sequence is the insertion, deletion, or rearrangement of stretches of DNA sequence sized from around 1,000 to millions of base pairs. Over the past few years, structural variation has been shown to be far more common in human genomes than previously thought. Very little is currently known about the effects of structural variation on normal child development, but such effects could be of considerable significance. This review provides an overview of the phenomenon of structural variation in the human genome sequence, describing the novel genomics technologies that are revolutionizing the way structural variation is studied and giving examples of genomic structural variations that affect child development.

Personal omics profiling reveals dynamic molecular and medical phenotypes.

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Personalizing rare disease research: how genomics is revolutionizing the diagnosis and treatment of rare disease.

A decade after the complete sequencing of the human genome, combined with recent advances in throughput and sequencing costs, the genetics of rare diseases has entered a new era. There has now been an explosion in the identification and mapping of rare diseases, with over 10,000 exomes having been sequenced to date. This article surveys the progress and development of technologies to understand rare disease; it provides a historical overview of traditional techniques such as karyotyping and homozygosity mapping, reviews current methods of whole-exome and -genome sequencing, and provides a future perspective on upcoming developments such as targeted drugs and gene therapy. This article will discuss the implications of these methods for rare disease research, along with a discussion of the success stories that provide great hope and optimism for patients and scientists alike.

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms.

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.