Whole-genome sequencing in prenatally detected congenital malformations: prospective cohort study in clinical setting.

OBJECTIVE: To investigate the diagnostic yield of trio whole-genome sequencing (WGS) in fetuses with various congenital malformations referred to a tertiary center for prenatal diagnosis. METHODS: In this prospective study, 50 pregnancies with different congenital malformations, negative for trisomies and causative copy-number variants, were analyzed further with fetal-parental trio WGS analysis. Parents were eligible for inclusion if they accepted further investigation following the detection of isolated or multiple malformations on prenatal ultrasound. Cases with isolated increased nuchal translucency, gamete donation or multiple pregnancy were excluded. WGS with the Illumina Inc. 30× polymerase-chain-reaction-free short-read sequencing included analysis of single-nucleotide variants, insertions and deletions, structural variants, short tandem repeats and copy-number identification of SMN1 and SMN2 genes. RESULTS: A molecular diagnosis was achieved in 13/50 (26%) cases. Causative sequence variants were identified in 12 genes: FGFR3 (n = 2), ACTA1 (n = 1), CDH2 (n = 1), COL1A2 (n = 1), DHCR7 (n = 1), EYA1 (n = 1), FBXO11 (n = 1), FRAS1 (n = 1), L1CAM (n = 1), OFD1 (n = 1), PDHA1 (n = 1) and SOX9 (n = 1). The phenotypes of the cases were divided into different groups, with the following diagnostic yields: skeletal malformation (4/9 (44%)), multisystem malformation (3/7 (43%)), central nervous system malformation (5/15 (33%)) and thoracic malformation (1/10 (10%)). Additionally, two cases carried variants that were considered potentially clinically relevant, even though they were assessed as variants of uncertain significance, according to the guidelines provided by the American College of Medical Genetics and Genomics. Overall, we identified a causative or potentially clinically relevant variant in 15/50 (30%) cases. CONCLUSIONS: We demonstrate a diagnostic yield of 26% with clinical WGS in prenatally detected congenital malformations. This study emphasizes the benefits that WGS can bring to the diagnosis of fetal structural anomalies. It is important to note that causative chromosomal aberrations were excluded from our cohort before WGS. As chromosomal aberrations are a well-known cause of prenatally detected congenital malformations, future studies using WGS as a primary diagnostic test, including assessment of chromosomal aberrations, may show that the detection rate exceeds the diagnostic yield of this study. WGS can add clinically relevant information, explaining the underlying cause of the fetal anomaly, which will provide information concerning the specific prognosis of the condition, as well as estimate the risk of recurrence. A genetic diagnosis can also provide more reproductive choice for future pregnancies. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants.

Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base pairs) of uncertain significance are the genetic cause of a portion of these unresolved cases. As sequencing methods using long or linked reads become more accessible and SV detection algorithms improve, clinicians and researchers are gaining access to thousands of reliable SVs of unknown disease relevance. Methods to predict the pathogenicity of these SVs are required to realize the full diagnostic potential of long-read sequencing. To address this emerging need, we developed StrVCTVRE to distinguish pathogenic SVs from benign SVs that overlap exons. In a random forest classifier, we integrated features that capture gene importance, coding region, conservation, expression, and exon structure. We found that features such as expression and conservation are important but are absent from SV classification guidelines. We leveraged multiple resources to construct a size-matched training set of rare, putatively benign and pathogenic SVs. StrVCTVRE performs accurately across a wide SV size range on independent test sets, which will allow clinicians and researchers to eliminate about half of SVs from consideration while retaining a 90% sensitivity. We anticipate clinicians and researchers will use StrVCTVRE to prioritize SVs in probands where no SV is immediately compelling, empowering deeper investigation into novel SVs to resolve cases and understand new mechanisms of disease. StrVCTVRE runs rapidly and is publicly available.

ScalpelSig Designs Targeted Genomic Panels from Data to Detect Activity of Mutational Signatures.

Over the past decade, a promising line of cancer research has utilized machine learning to mine statistical patterns of mutations in cancer genomes for information. Recent work shows that these statistical patterns, commonly referred to as "mutational signatures," have diverse therapeutic potential as biomarkers for cancer therapies. However, translating this potential into reality is hindered by limited access to sequencing in the clinic. Almost all methods for mutational signature analysis (MSA) rely on whole genome or whole exome sequencing data, while sequencing in the clinic is typically limited to small gene panels. To improve clinical access to MSA, we considered the question of whether targeted panels could be designed for the purpose of mutational signature detection. Here we present ScalpelSig, to our knowledge the first algorithm that automatically designs genomic panels optimized for detection of a given mutational signature. The algorithm learns from data to identify genome regions that are particularly indicative of signature activity. Using a cohort of breast cancer genomes as training data, we show that ScalpelSig panels substantially improve accuracy of signature detection compared to baselines. We find that some ScalpelSig panels even approach the performance of whole exome sequencing, which observes over 10 × as much genomic material. We test our algorithm under a variety of conditions, showing that its performance generalizes to another dataset of breast cancers, to smaller panel sizes, and to lesser amounts of training data.

Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking.

BACKGROUND: Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). RESULTS: We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the "immunosuppression" pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. CONCLUSIONS: In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.

Germline Sequencing Improves Tumor-Only Sequencing Interpretation in a Precision Genomic Study of Patients With Pediatric Solid Tumor.

PURPOSE: Molecular tumor profiling is becoming a routine part of clinical cancer care, typically involving tumor-only panel testing without matched germline. We hypothesized that integrated germline sequencing could improve clinical interpretation and enhance the identification of germline variants with significant hereditary risks. MATERIALS AND METHODS: Tumors from pediatric patients with high-risk, extracranial solid malignancies were sequenced with a targeted panel of cancer-associated genes. Later, germline DNA was analyzed for a subset of these genes. We performed a post hoc analysis to identify how an integrated analysis of tumor and germline data would improve clinical interpretation. RESULTS: One hundred sixty participants with both tumor-only and germline sequencing reports were eligible for this analysis. Germline sequencing identified 38 pathogenic or likely pathogenic variants among 35 (22%) patients. Twenty-five (66%) of these were included in the tumor sequencing report. The remaining germline pathogenic or likely pathogenic variants were single-nucleotide variants filtered out of tumor-only analysis because of population frequency or copy-number variation masked by additional copy-number changes in the tumor. In tumor-only sequencing, 308 of 434 (71%) single-nucleotide variants reported were present in the germline, including 31% with suggested clinical utility. Finally, we provide further evidence that the variant allele fraction from tumor-only sequencing is insufficient to differentiate somatic from germline events. CONCLUSION: A paired approach to analyzing tumor and germline sequencing data would be expected to improve the efficiency and accuracy of distinguishing somatic mutations and germline variants, thereby facilitating the process of variant curation and therapeutic interpretation for somatic reports, as well as the identification of variants associated with germline cancer predisposition.

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinson's disease.

BACKGROUND: Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinson's disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD. RESULTS: Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered. CONCLUSIONS: Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.

SpecHap: a diploid phasing algorithm based on spectral graph theory.

Haplotype phasing plays an important role in understanding the genetic data of diploid eukaryotic organisms. Different sequencing technologies (such as next-generation sequencing or third-generation sequencing) produce various genetic data that require haplotype assembly. Although multiple diploid haplotype phasing algorithms exist, only a few will work equally well across all sequencing technologies. In this work, we propose SpecHap, a novel haplotype assembly tool that leverages spectral graph theory. On both in silico and whole-genome sequencing datasets, SpecHap consumed less memory and required less CPU time, yet achieved comparable accuracy with state-of-art methods across all the test instances, which comprises sequencing data from next-generation sequencing, linked-reads, high-throughput chromosome conformation capture, PacBio single-molecule real-time, and Oxford Nanopore long-reads. Furthermore, SpecHap successfully phased an individual Ambystoma mexicanum, a species with gigantic diploid genomes, within 6 CPU hours and 945MB peak memory usage, while other tools failed to yield results either due to memory overflow (40GB) or time limit exceeded (5 days). Our results demonstrated that SpecHap is scalable, efficient, and accurate for diploid phasing across many sequencing platforms.

Prevalence of Germline Alterations on Targeted Tumor-Normal Sequencing of Esophagogastric Cancer.

Importance: Among patients with esophagogastric cancers, only individuals who present with known features of heritable cancer syndromes are referred for genetic testing. Broader testing might identify additional patients with germline alterations. Objectives: To examine the prevalence of likely pathogenic or pathogenic (LP/P) germline alterations among patients with esophagogastric cancer and to assess associations between germline variant prevalence and demographic and clinicopathologic features. Design, Setting, and Participants: This cross-sectional study was performed at a tertiary referral cancer center from January 1, 2014, to December 31, 2019, in 515 patients with esophagogastric cancer who consented to tumor and blood sequencing. Main Outcomes and Measures: Presence or absence of LP/P variants in up to 88 genes associated with cancer predisposition syndromes as identified by targeted sequencing (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets). Results: Among 515 patients (median age, 59 years; range, 18-87 years; 368 [71.5%] male; 398 [77.3%] White), 243 (47.2%) had gastric cancer, 111 (21.6%) had gastroesophageal junction (GEJ) cancer, and 161 (31.3%) had esophageal cancer. A total of 48 patients with gastric cancer (19.8%), 16 (14.4%) with GEJ cancer, and 17 (10.6%) with esophageal cancer had LP/P germline variants. The number of LP/P variants in high- and moderate-penetrance genes was significantly higher in patients with gastric cancer (29 [11.9%]; 95% CI, 8.1%-16.7%) vs patients with esophageal cancer (8 [5.0%]; 95% CI, 2.2%-9.6%; P = .03), and the difference was greater for high-penetrance germline alterations in patients with gastric cancer (25 [10.3%]; 95% CI, 6.8%-14.8%) vs in patients with esophageal cancer (3 [1.9%]; 95% CI, 0.38%-5.3%; P = .001). The most frequent high- and moderate-penetrance LP/P alterations were in BRCA1/2 (14 [2.7%]), ATM (11 [2.1%]), CDH1 (6 [1.2%]), and MSH2 (4 [0.8%]). Those with early-onset disease (≤50 years of age at diagnosis) were more likely to harbor an LP/P germline variant (29 [21.0%]; 95% CI, 14.5%-28.8%) vs those with late-onset disease (patients >50 years of age at diagnosis) (52 [13.8%]; 95% CI, 10.5%-17.7%; P = .046). ATM LP/P variants occurred in 6 patients (4.3%; 95% CI, 1.6%-9.1%) with early-onset esophagogastric cancer vs 5 (1.3%; 95% CI, 0.4%-3.1%; P = .08) of those with late-onset esophagogastric cancer. Conclusions and Relevance: These results suggest that pathogenic germline variants are enriched in gastric and early-onset esophagogastric cancer and that germline testing should be considered in these populations. The role of ATM alterations in esophagogastric cancer risk warrants further investigation.

Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program.

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.

A study of elective genome sequencing and pharmacogenetic testing in an unselected population.

BACKGROUND: Genome sequencing (GS) of individuals without a medical indication, known as elective GS, is now available at a number of centers around the United States. Here we report the results of elective GS and pharmacogenetic panel testing in 52 individuals at a private genomics clinic in Alabama. METHODS: Individuals seeking elective genomic testing and pharmacogenetic testing were recruited through a private genomics clinic in Huntsville, AL. Individuals underwent clinical genome sequencing with a separate pharmacogenetic testing panel. RESULTS: Six participants (11.5%) had pathogenic or likely pathogenic variants that may explain one or more aspects of their medical history. Ten participants (19%) had variants that altered the risk of disease in the future, including two individuals with clonal hematopoiesis of indeterminate potential. Forty-four participants (85%) were carriers of a recessive or X-linked disorder. All individuals with pharmacogenetic testing had variants that affected current and/or future medications. CONCLUSION: Our study highlights the importance of collecting detailed phenotype information to interpret results in elective GS.

Risk of hospitalisation associated with infection with SARS-CoV-2 lineage B.1.1.7 in Denmark: an observational cohort study.

BACKGROUND: The more infectious SARS-CoV-2 lineage B.1.1.7 rapidly spread in Europe after December, 2020, and a concern that B.1.1.7 could cause more severe disease has been raised. Taking advantage of Denmark's high RT-PCR testing and whole genome sequencing capacities, we used national health register data to assess the risk of COVID-19 hospitalisation in individuals infected with B.1.1.7 compared with those with other SARS-CoV-2 lineages. METHODS: We did an observational cohort study of all SARS-CoV-2-positive cases confirmed by RT-PCR in Denmark, sampled between Jan 1 and March 24, 2021, with 14 days of follow-up for COVID-19 hospitalisation. Cases were identified in the national COVID-19 surveillance system database, which includes data from the Danish Microbiology Database (RT-PCR test results), the Danish COVID-19 Genome Consortium, the National Patient Registry, the Civil Registration System, as well as other nationwide registers. Among all cases, COVID-19 hospitalisation was defined as first admission lasting longer than 12 h within 14 days of a sample with a positive RT-PCR result. The study population and main analysis were restricted to the proportion of cases with viral genome data. We calculated the risk ratio (RR) of admission according to infection with B.1.1.7 versus other co-existing lineages with a Poisson regression model with robust SEs, adjusted a priori for sex, age, calendar time, region, and comorbidities. The contribution of each covariate to confounding of the crude RR was evaluated afterwards by a stepwise forward inclusion. FINDINGS: Between Jan 1 and March 24, 2021, 50 958 individuals with a positive SARS-CoV-2 test and at least 14 days of follow-up for hospitalisation were identified; 30 572 (60·0%) had genome data, of whom 10 544 (34·5%) were infected with B.1.1.7. 1944 (6·4%) individuals had a COVID-19 hospitalisation and of these, 571 (29·4%) had a B.1.1.7 infection and 1373 (70·6%) had an infection with other SARS-CoV-2 lineages. Although the overall number of hospitalisations decreased during the study period, the proportion of individuals infected with B.1.1.7 increased from 3·5% to 92·1% per week. B.1.1.7 was associated with a crude RR of hospital admission of 0·79 (95% CI 0·72-0·87; p<0·0001) and an adjusted RR of 1·42 (95% CI 1·25-1·60; p<0·0001). The adjusted RR was increased in all strata of age and calendar period-the two covariates with the largest contribution to confounding of the crude RR. INTERPRETATION: Infection with SARS-CoV-2 lineage B.1.1.7 was associated with an increased risk of hospitalisation compared with that of other lineages in an analysis adjusted for covariates. The overall effect on hospitalisations in Denmark was lessened due to a strict lockdown, but our findings could support hospital preparedness and modelling of the projected impact of the epidemic in countries with uncontrolled spread of B.1.1.7. FUNDING: None.

Application of Full-Spectrum Rapid Clinical Genome Sequencing Improves Diagnostic Rate and Clinical Outcomes in Critically Ill Infants in the China Neonatal Genomes Project.

OBJECTIVES: To determine the diagnostic and clinical utility of trio-rapid genome sequencing in critically ill infants. DESIGN: In this prospective study, samples from critically ill infants were analyzed using both proband-only clinical exome sequencing and trio-rapid genome sequencing (proband and biological parents). The study occurred between April 2019 and December 2019. SETTING: Thirteen member hospitals of the China Neonatal Genomes Project spanning 10 provinces were involved. PARTICIPANTS: Critically ill infants (n = 202), from birth up until 13 months of life were enrolled based on eligibility criteria (e.g., CNS anomaly, complex congenital heart disease, evidence of metabolic disease, recurrent severe infection, suspected immune deficiency, and multiple malformations). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 202 participants, neuromuscular (45%), respiratory (22%), and immunologic/infectious (18%) were the most commonly observed phenotypes. The diagnostic yield of trio-rapid genome sequencing was higher than that of proband-only clinical exome sequencing (36.6% [95% CI, 30.1-43.7%] vs 20.3% [95% CI, 15.1-26.6%], respectively; p = 0.0004), and the average turnaround time for trio-rapid genome sequencing (median: 7 d) was faster than that of proband-only clinical exome sequencing (median: 20 d) (p < 2.2 × 10-16). The metagenomic analysis identified pathogenic or likely pathogenic microbes in six infants with symptoms of sepsis, and these results guided the antibiotic treatment strategy. Sixteen infants (21.6%) experienced a change in clinical management following trio-rapid genome sequencing diagnosis, and 24 infants (32.4%) were referred to a new subspecialist. CONCLUSIONS: Trio-rapid genome sequencing provided higher diagnostic yield in a shorter period of time in this cohort of critically ill infants compared with proband-only clinical exome sequencing. Precise and fast molecular diagnosis can alter medical management and positively impact patient outcomes.

Whole-genome sequencing analysis of semi-supercentenarians.

Extreme longevity is the paradigm of healthy aging as individuals who reached the extreme decades of human life avoided or largely postponed all major age-related diseases. In this study, we sequenced at high coverage (90X) the whole genome of 81 semi-supercentenarians and supercentenarians [105+/110+] (mean age: 106.6 ± 1.6) and of 36 healthy unrelated geographically matched controls (mean age 68.0 ± 5.9) recruited in Italy. The results showed that 105+/110+ are characterized by a peculiar genetic background associated with efficient DNA repair mechanisms, as evidenced by both germline data (common and rare variants) and somatic mutations patterns (lower mutation load if compared to younger healthy controls). Results were replicated in a second independent cohort of 333 Italian centenarians and 358 geographically matched controls. The genetics of 105+/110+ identified DNA repair and clonal haematopoiesis as crucial players for healthy aging and for the protection from cardiovascular events.

Fine-scale population structure in five rural populations from the Spanish Eastern Pyrenees using high-coverage whole-genome sequence data.

The area of the Spanish Pyrenees is particularly interesting for studying the demographic dynamics of European rural areas given its orography, the main traditional rural condition of its population and the reported higher patterns of consanguinity of the region. Previous genetic studies suggest a gradient of genetic continuity of the area in the West to East axis. However, it has been shown that micro-population substructure can be detected when considering high-quality NGS data and using spatial explicit methods. In this work, we have analyzed the genome of 30 individuals sequenced at 40× from five different valleys in the Spanish Eastern Pyrenees (SEP) separated by less than 140 km along a west to east axis. Using haplotype-based methods and spatial analyses, we have been able to detect micro-population substructure within SEP not seen in previous studies. Linkage disequilibrium and autozygosity analyses suggest that the SEP populations show diverse demographic histories. In agreement with these results, demographic modeling by means of ABC-DL identify heterogeneity in their effective population sizes despite of their close geographic proximity, and suggests that the population substructure within SEP could have appeared around 2500 years ago. Overall, these results suggest that each rural population of the Pyrenees could represent a unique entity.

mSphere of Influence: Whole-Genome Sequencing, a Vital Tool for the Interruption of Nosocomial Transmission.

Ahmed Babiker's work focuses on the clinical and genomic epidemiology of multidrug-resistant health care-associated pathogens and other high-consequence pathogens. In this mSphere of Influence article, he reflects on how the paper "Tracking a Hospital Outbreak of Carbapenem-Resistant Klebsiella pneumoniae with Whole-Genome Sequencing" by Evan S. Snitkin et al. (Sci Transl Med 4:148ra116, 2012, https://doi.org/10.1126/scitranslmed.3004129) impacted his thinking on the use of whole-genome sequencing for nosocomial transmission investigation.

Natural human knockouts and Mendelian disorders: deep phenotyping in Italian isolates.

Whole genome sequencing (WGS) allows the identification of human knockouts (HKOs), individuals in whom loss of function (LoF) variants disrupt both alleles of a given gene. HKOs are a valuable model for understanding the consequences of genes function loss. Naturally occurring biallelic LoF variants tend to be significantly enriched in "genetic isolates," making these populations specifically suited for HKO studies. In this work, a meticulous WGS data analysis combined with an in-depth phenotypic assessment of 947 individuals from three Italian genetic isolates led to the identification of ten biallelic LoF variants in ten OMIM genes associated with known autosomal recessive diseases. Notably, only a minority of the identified HKOs (C7, F12, and GPR68 genes) displayed the expected phenotype. For most of the genes, instead, (ACADSB, FANCL, GRK1, LGI4, MPO, PGAM2, and RP1L1), the carriers showed none or few of the signs and symptoms typically associated with the related diseases. Of particular interest is a case presenting with a FANCL biallelic LoF variant and a positive diepoxybutane test but lacking a full Fanconi anemia phenotypic spectrum. Identifying KO subjects displaying expected phenotypes suggests that the lack of correct genetic diagnoses may lead to inappropriate and delayed treatment. In contrast, the presence of HKOs with phenotypes deviating from the expected patterns underlines how LoF variants may be responsible for broader phenotypic spectra. Overall, these results highlight the importance of in-depth phenotypical characterization to understand the role of LoF variants and the advantage of studying these variants in genetic isolates.

No evidence of EMAST in whole genome sequencing data from 248 colorectal cancers.

Microsatellite instability (MSI) is caused by defective DNA mismatch repair (MMR), and manifests as accumulation of small insertions and deletions (indels) in short tandem repeats of the genome. Another form of repeat instability, elevated microsatellite alterations at selected tetranucleotide repeats (EMAST), has been suggested to occur in 50% to 60% of colorectal cancer (CRC), of which approximately one quarter are accounted for by MSI. Unlike for MSI, the criteria for defining EMAST is not consensual. EMAST CRCs have been suggested to form a distinct subset of CRCs that has been linked to a higher tumor stage, chronic inflammation, and poor prognosis. EMAST CRCs not exhibiting MSI have been proposed to show instability of di- and trinucleotide repeats in addition to tetranucleotide repeats, but lack instability of mononucleotide repeats. However, previous studies on EMAST have been based on targeted analysis of small sets of marker repeats, often in relatively few samples. To gain insight into tetranucleotide instability on a genome-wide level, we utilized whole genome sequencing data from 227 microsatellite stable (MSS) CRCs, 18 MSI CRCs, 3 POLE-mutated CRCs, and their corresponding normal samples. As expected, we observed tetranucleotide instability in all MSI CRCs, accompanied by instability of mono-, di-, and trinucleotide repeats. Among MSS CRCs, some tumors displayed more microsatellite mutations than others as a continuum, and no distinct subset of tumors with the previously proposed molecular characters of EMAST could be observed. Our results suggest that tetranucleotide repeat mutations in non-MSI CRCs represent stochastic mutation events rather than define a distinct CRC subclass.