Characterization of the Common Genetic Variation in the Spanish Population of Navarre.

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.

Tumor Antigens beyond the Human Exome.

With the advent of immunotherapeutics, a new era in the combat against cancer has begun. Particularly promising are neo-epitope-targeted therapies as the expression of neo-antigens is tumor-specific. In turn, this allows the selective targeting and killing of cancer cells whilst healthy cells remain largely unaffected. So far, many advances have been made in the development of treatment options which are tailored to the individual neo-epitope repertoire. The next big step is the achievement of efficacious "off-the-shelf" immunotherapies. For this, shared neo-epitopes propose an optimal target. Given the tremendous potential, a thorough understanding of the underlying mechanisms which lead to the formation of neo-antigens is of fundamental importance. Here, we review the various processes which result in the formation of neo-epitopes. Broadly, the origin of neo-epitopes can be categorized into three groups: canonical, noncanonical, and viral neo-epitopes. For the canonical neo-antigens that arise in direct consequence of somatic mutations, we summarize past and recent findings. Beyond that, our main focus is put on the discussion of noncanonical and viral neo-epitopes as we believe that targeting those provides an encouraging perspective to shape the future of cancer immunotherapeutics.

Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis.

Human aging is marked by the emergence of a tapestry of clonal expansions in dividing tissues, particularly evident in blood as clonal hematopoiesis (CH). CH, linked to cancer risk and aging-related phenotypes, often stems from somatic mutations in a set of established genes. However, the majority of clones lack known drivers. Here we infer gene-level positive selection in whole blood exomes from 200,618 individuals in UK Biobank. We identify 17 additional genes, ZBTB33, ZNF318, ZNF234, SPRED2, SH2B3, SRCAP, SIK3, SRSF1, CHEK2, CCDC115, CCL22, BAX, YLPM1, MYD88, MTA2, MAGEC3 and IGLL5, under positive selection at a population level, and validate this selection pattern in 10,837 whole genomes from single-cell-derived hematopoietic colonies. Clones with mutations in these genes grow in frequency and size with age, comparable to classical CH drivers. They correlate with heightened risk of infection, death and hematological malignancy, highlighting the significance of these additional genes in the aging process.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension.

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Exome sequencing in four families with neurodevelopmental disorders: genotype-phenotype correlation and identification of novel disease-causing variants in VPS13B and RELN.

Neurodevelopmental disorders (NDDs) are a clinically and genetically heterogeneous group of early-onset pediatric disorders that affect the structure and/or function of the central or peripheral nervous system. Achieving a precise molecular diagnosis for NDDs may be challenging due to the diverse genetic underpinnings and clinical variability. In the current study, we investigated the underlying genetic cause(s) of NDDs in four unrelated Pakistani families. Using exome sequencing (ES) as a diagnostic approach, we identified disease-causing variants in established NDD-associated genes in all families, including one hitherto unreported variant in RELN and three recurrent variants in VPS13B, DEGS1, and SPG11. Overall, our study highlights the potential of ES as a tool for clinical diagnosis.

Multi-omics portrait of ductal carcinoma in situ in young women.

BACKGROUND: Young patients with breast ductal carcinoma in situ (DCIS) often face a poorer prognosis. The genomic intricacies in young-onset DCIS, however, remain underexplored. METHODS: To address this gap, we undertook a comprehensive study encompassing exome, transcriptome, and vmethylome analyses. Our investigation included 20 DCIS samples (including 15 young-onset DCIS) and paired samples of normal breast tissue and blood. RESULTS: Through RNA sequencing, we identified two distinct DCIS subgroups: "immune hot" and "immune cold". The "immune hot" subgroup was characterized by increased infiltration of lymphocytes and macrophages, elevated expression of PDCD1 and CTLA4, and reduced GATA3 expression. This group also exhibited active immunerelated transcriptional regulators. Mutational analysis revealed alterations in TP53 (38%), GATA3 (25%), and TTN (19%), with two cases showing mutations in APC, ERBB2, and SMARCC1. Common genomic alterations, irrespective of immune status, included gains in copy numbers at 1q, 8q, 17q, and 20q, and losses at 11q, 17p, and 22q. Signature analysis highlighted the predominance of signatures 2 and 1, with "immune cold" samples showing a significant presence of signature 8. Our methylome study on 13 DCIS samples identified 328 hyperdifferentially methylated regions (DMRs) and 521 hypo-DMRs, with "immune cold" cases generally showing lower levels of methylation. CONCLUSION: In summary, the molecular characteristics of young-onset DCIS share similarities with invasive breast cancer (IBC), potentially indicating a poor prognosis. Understanding these characteristics, especially the immune microenvironment of DCIS, could be pivotal in identifying new therapeutic targets and preventive strategies for breast cancer.

Whole-exome-based single nucleotide variants and copy number analysis for prenatal diagnosis of compound heterozygosity of SMPD4.

BACKGROUND: Biallelic loss-of-function variants in SMPD4 cause a rare and severe neurodevelopmental disorder. These variants have been identified in a group of children with neurodevelopmental disorders with microcephaly, arthrogryposis, and structural brain anomalies. SMPD4 encodes a sphingomyelinase that hydrolyzes sphingomyelin into ceramide at neutral pH and can thereby affect membrane lipid homeostasis. SMPD4 localizes to the membranes of the endoplasmic reticulum and nuclear envelope and interacts with nuclear pore complexes. MATERIALS AND METHODS: For the efficient prenatal diagnosis of rare and undiagnosed diseases, the parallel detection of copy number variants (CNVs) and single nucleotide variants using whole-exome analysis is required. A physical examination of the parents was performed. Karyotype and whole-exome analysis were performed for the fetus and the parents. RESULTS: A fetus with microcephaly and arthrogryposis; biallelic null variants (c.387-1G>A; Chr2[GRCh38]: g.130142742_130202459del) were detected by whole-exome sequencing (WES). We have reported for the first time the biallelic loss-of-function mutations in SMPD4 in patients born to unrelated parents in China. CONCLUSION: WES could replace chromosomal microarray analysis and copy number variation sequencing as a more cost-effective genetic test for detecting CNVs and diagnosing highly heterogeneous conditions.

Exome sequencing reveals genetic heterogeneity and clinically actionable findings in children with cerebral palsy.

Cerebral palsy (CP) is the most common motor disability in children. To ascertain the role of major genetic variants in the etiology of CP, we conducted exome sequencing on a large-scale cohort with clinical manifestations of CP. The study cohort comprised 505 girls and 1,073 boys. Utilizing the current gold standard in genetic diagnostics, 387 of these 1,578 children (24.5%) received genetic diagnoses. We identified 412 pathogenic and likely pathogenic (P/LP) variants across 219 genes associated with neurodevelopmental disorders, and 59 P/LP copy number variants. The genetic diagnostic rate of children with CP labeled at birth with perinatal asphyxia was higher than the rate in children without asphyxia (P = 0.0033). Also, 33 children with CP manifestations (8.5%, 33 of 387) had findings that were clinically actionable. These results highlight the need for early genetic testing in children with CP, especially those with risk factors like perinatal asphyxia, to enable evidence-based medical decision-making.

Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank.

The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.

Diagnostic yield of exome and genome sequencing after non-diagnostic multi-gene panels in patients with single-system diseases.

BACKGROUND: Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. RESULTS: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). CONCLUSION: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates.

Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults.

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Phenotype-Genotype Correlation Applying a Cocktail Approach and an Exome Chip Analysis Reveals Further Variants Contributing to Variation of Drug Metabolism.

Although great progress has been made in the fine-tuning of diplotypes, there is still a need to further improve the predictability of individual phenotypes of pharmacogenetically relevant enzymes. The aim of this study was to analyze the additional contribution of sex and variants identified by exome chip analysis to the metabolic ratio of five probe drugs. A cocktail study applying dextromethorphan, losartan, omeprazole, midazolam, and caffeine was conducted on 200 healthy volunteers. CYP2D6, 2C9, 2C19, 3A4/5, and 1A2 genotypes were analyzed and correlated with metabolic ratios. In addition, an exome chip analysis was performed. These SNPs correlating with metabolic ratios were confirmed by individual genotyping. The contribution of various factors to metabolic ratios was assessed by multiple regression analysis. Genotypically predicted phenotypes defined by CPIC discriminated very well the log metabolic ratios with the exception of caffeine. There were minor sex differences in the activity of CYP2C9, 2C19, 1A2, and CYP3A4/5. For dextromethorphan (CYP2D6), IP6K2 (rs61740999) and TCF20 (rs5758651) affected metabolic ratios, but only IP6K2 remained significant after multiple regression analysis. For losartan (CYP2C9), FBXW12 (rs17080138), ZNF703 (rs79707182), and SLC17A4 (rs11754288) together with CYP diplotypes, and sex explained 50% of interindividual variability. For omeprazole (CYP2C19), no significant influence of CYP2C:TG haplotypes was observed, but CYP2C19 rs12777823 improved the predictability. The comprehensive genetic analysis and inclusion of sex in a multiple regression model significantly improved the explanation of variability of metabolic ratios, resulting in further improvement of algorithms for the prediction of individual phenotypes of drug-metabolizing enzymes.

Systematic reanalysis of copy number losses of uncertain clinical significance.

BACKGROUND: Reanalysis of exome/genome data improves diagnostic yield. However, the value of reanalysis of clinical array comparative genomic hybridisation (aCGH) data has never been investigated. Case-by-case reanalysis can be challenging in busy diagnostic laboratories. METHODS AND RESULTS: We harmonised historical postnatal clinical aCGH results from ~16 000 patients tested via our diagnostic laboratory over ~7 years with current clinical guidance. This led to identification of 37 009 copy number losses (CNLs) including 33 857 benign, 2173 of uncertain significance and 979 pathogenic. We found benign CNLs to be significantly less likely to encompass haploinsufficient genes compared with the pathogenic or CNLs of uncertain significance in our database. Based on this observation, we developed a reanalysis pipeline using up-to-date disease association data and haploinsufficiency scores and shortlisted 207 CNLs of uncertain significance encompassing at least one autosomal dominant disease-gene associated with haploinsufficiency or loss-of-function mechanism. Clinical scientist reviews led to reclassification of 15 CNLs of uncertain significance as pathogenic or likely pathogenic. This was ~0.7% of the starting cohort of 2173 CNLs of uncertain significance and 7.2% of 207 shortlisted CNLs. The reclassified CNLs included first cases of CNV-mediated disease for some genes where all previously described cases involved only point variants. Interestingly, some CNLs could not be reclassified because the phenotypes of patients with CNLs seemed distinct from the known clinical features resulting from point variants, thus raising questions about accepted underlying disease mechanisms. CONCLUSIONS: Reanalysis of clinical aCGH data increases diagnostic yield.

Exome sequencing of 1190 non-syndromic clubfoot cases reveals HOXD12 as a novel disease gene.

BACKGROUND: Clubfoot, presenting as a rigid inward and downward turning of the foot, is one of the most common congenital musculoskeletal anomalies. The aetiology of clubfoot is poorly understood and variants in known clubfoot disease genes account for only a small portion of the heritability. METHODS: Exome sequence data were generated from 1190 non-syndromic clubfoot cases and their family members from multiple ethnicities. Ultra-rare variant burden analysis was performed comparing 857 unrelated clubfoot cases with European ancestry with two independent ethnicity-matched control groups (1043 in-house and 56 885 gnomAD controls). Additional variants in prioritised genes were identified in a larger cohort, including probands with non-European ancestry. Segregation analysis was performed in multiplex families when available. RESULTS: Rare variants in 29 genes were enriched in clubfoot cases, including PITX1 (a known clubfoot disease gene), HOXD12, COL12A1, COL9A3 and LMX1B. In addition, rare variants in posterior HOX genes (HOX9-13) were enriched overall in clubfoot cases. In total, variants in these genes were present in 8.4% (100/1190) of clubfoot cases with both European and non-European ancestry. Among these, 3 are de novo and 22 show variable penetrance, including 4 HOXD12 variants that segregate with clubfoot. CONCLUSION: We report HOXD12 as a novel clubfoot disease gene and demonstrate a phenotypic expansion of known disease genes (myopathy gene COL12A1, Ehlers-Danlos syndrome gene COL9A3 and nail-patella syndrome gene LMX1B) to include isolated clubfoot.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system.

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Focused Exome Sequencing Gives a High Diagnostic Yield in the Indian Subcontinent.

The genetically isolated yet heterogeneous and highly consanguineous Indian population has shown a higher prevalence of rare genetic disorders. However, there is a significant socioeconomic burden for genetic testing to be accessible to the general population. In the current study, we analyzed next-generation sequencing data generated through focused exome sequencing from individuals with different phenotypic manifestations referred for genetic testing to achieve a molecular diagnosis. Pathogenic or likely pathogenic variants are reported in 280 of 833 cases with a diagnostic yield of 33.6%. Homozygous sequence and copy number variants were found as positive diagnostic findings in 131 cases (15.7%) because of the high consanguinity in the Indian population. No relevant findings related to reported phenotype were identified in 6.2% of the cases. Patients referred for testing due to metabolic disorder and neuromuscular disorder had higher diagnostic yields. Carrier testing of asymptomatic individuals with a family history of the disease, through focused exome sequencing, achieved positive diagnosis in 54 of 118 cases tested. Copy number variants were also found in trans with single-nucleotide variants and mitochondrial variants in a few of the cases. The diagnostic yield and the findings from this study signify that a focused exome test is a good lower-cost alternative for whole-exome and whole-genome sequencing and as a first-tier approach to genetic testing.