Aggregation Database Research Articles

Mutation Screening of ATXN1, ATXN2, and ATXN3 in Amyotrophic Lateral Sclerosis.

Emerging evidence suggests potential disease modifying roles of ATXN1, ATXN2, and ATXN3 in amyotrophic lateral sclerosis (ALS). We aimed to provide a comprehensive variants profile of the ATXN1, ATXN2, and ATXN3 genes and examine the association of these variants with the risk and clinical characteristics of ALS. We screened and analyzed the rare variants in a cohort of 2220 ALS patients from Southwest China, using controls from the Genome Aggregation Database (gnomAD) and the China Metabolic Analytics Project (ChinaMAP). The over-representation of rare variants and their association with disease risk in ALS patients were assessed using Fisher's exact test with Bonferroni correction at both allele and gene levels. Kaplan-Meier analysis was employed to explore the relationship between the distribution of variants and survival. A total of 62 eligible rare missense variants were identified, comprising 32 from ATXN1, 21 from ATXN2, and 9 from ATXN3. Allelic association testing revealed a significant enrichment of the ATXN1 (c.2122C > G, p.Leu708Val) variant and the ATXN2 (c.3778C > G, p.Pro1260Ala) variant in ALS. Gene burden analysis indicated that variants in the ATXN1 and ATXN3 genes had a higher burden in ALS. Substantial heterogeneity in survival time was observed among patients carrying different variants within the same gene. However, there were no significant differences in survival between ALS patients grouped by N-terminal or C-terminal distribution. Our results provided a genetic variation profile of ATXN1, ATXN2, and ATXN3 in ALS patients, along with the clinical characteristics of individuals carrying these variations. This information might offer valuable insights for the ongoing ALS disease-modifying treatments.

Aggregating amyloid resources: A comprehensive review of databases on amyloid-like aggregation

Protein aggregation is responsible for several degenerative conditions in humans, and it is also a bottleneck in industrial protein production and storage of biotherapeutics. Bioinformatics tools have been developed to predict and redesign protein solubility more efficiently by understanding the underlying principles behind aggregation. As more experimental data become available, dedicated resources for storing, indexing, classifying and consolidating experimental results have emerged. These resources vary in focus, including aggregation-prone regions, 3D patches or protein stretches capable of forming amyloid fibrils. Some of these resources also consider the experimental conditions that cause protein aggregation and how they affect the process. This review article explores how protein aggregation databases have evolved and surveys state-of-the-art resources. We highlight their applications, complementarity and existing limitations. Moreover, we showcase the existing symbiosis between amyloid-related databases and predictive tools. To increase the usefulness of our review, we supplement it with a comprehensive list of present and past amyloid databases: https://biogenies.info/amyloid-database-list/.

Quantifying constraint in the human mitochondrial genome.

Mitochondrial DNA (mtDNA) has an important yet often overlooked role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection and represent powerful tools for identifying genetic variation that underlies human phenotypes1-4. However, nuclear constraint models are not applicable to mtDNA, owing to its distinct features. Here we describe the development of a mitochondrial genome constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset that reports mtDNA variation across 56,434 human participants5. Specifically, we analyse constraint by comparing the observed variation in gnomAD to that expected under neutrality, which was calculated using a mtDNA mutational model and observed maximum heteroplasmy-level data. Our results highlight strong depletion of expected variation, which suggests that many deleterious mtDNA variants remain undetected. To aid their discovery, we compute constraint metrics for every mitochondrial protein, tRNA and rRNA gene, which revealed a range of intolerance to variation. We further characterize the most constrained regions within genes through regional constraint and identify the most constrained sites within the entire mitochondrial genome through local constraint, which showed enrichment of pathogenic variation. Constraint also clustered in three-dimensional structures, which provided insight into functionally important domains and their disease relevance. Notably, we identify constraint at often overlooked sites, including in rRNA and noncoding regions. Last, we demonstrate that these metrics can improve the discovery of deleterious variation that underlies rare and common phenotypes.

Prevalence Estimation of the PALB2 Germline Variant in East Asians and Koreans through Population Database Analysis.

PALB2 is a tumor suppressor gene. Heterozygous germline pathogenic variants of PALB2 significantly increase the lifetime risk of breast cancer and moderately increase the risk of ovarian and pancreatic cancers. This study analyzed the estimated prevalence of PALB2 variants globally, focusing on East Asian and Korean populations, where limited data were previously available. We examined 125,748 exomes from the Genome Aggregation Database (gnomAD), including 9197 East Asians, and additional data from 5305 individuals in the Korean Variant Archive and 1722 in the Korean Reference Genome Database. All PALB2 variants were interpreted according to guidelines from the American College of Medical Genetics and Genomics and the Clinical Genome Resource. The global prevalence of PALB2 variants was 0.18%, with the highest prevalence in Finnish populations (0.41%) and the lowest in Ashkenazi Jewish populations (0.04%). East Asians had a prevalence of 0.09%. By combining data from Korean genome databases and gnomAD totaling 8936 individuals, the overall prevalence of PALB2 variants in the Korean population was determined to be 0.13%. This study is the first comprehensive investigation of PALB2 variant prevalence in East Asians and Koreans using gnomAD and Korean genome databases. These findings provide essential reference data for future research and highlight the importance of region-specific genetic studies that will inform genetic counseling and hereditary cancer risk management.

Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework.

Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population diversity on gene expression. Population differentiated variants were estimated by using the allele frequency information from The Genome Aggregation Database. We found that the weights of a variants was the main factor that affected the gene expression predictions, and that ~70% of variants were significantly population differentiated based on proportion tests. To provide insights into this population effect on gene expression levels, we utilized the allele frequency information to develop a gene expression reference panel, Predict Asian-Population (PredictAP), for EAS ancestry. PredictAP can be viewed as an auxiliary tool for PrediXcan when using genotype data from EAS subjects.

Expanding the Russian allele frequency reference via cross-laboratory data integration: insights from 7452 exome samples.

Population allele frequency is crucially important for accurate interpretation of known and novel variants in medical genetics. Recently, several large allele frequency databases, such as the Genome Aggregation Database (gnomAD), have been created to serve as a global reference for such studies. However, frequencies of many rare alleles vary dramatically between populations, and population-specific allele frequency is often more informative than the global one. Many countries and regions, including Russia, remain poorly studied from the genetic perspective. Here, we report the first successful attempt to integrate genetic information between major medical genetic laboratories in Russia. We construct RUSeq, an open, large-scale reference set of genetic variants by analyzing 7452 exome samples collected in two major Russian cities-Moscow and St. Petersburg. An ∼10-fold increase in sample size compared to previous studies allowed us to characterize extensive genetic diversity within the admixed Russian population with contributions from several major ancestral groups. We highlight 51 known pathogenic variants that are overrepresented in Russia compared to other European countries. We also identify several dozen high-impact variants that are present in healthy donors despite being annotated as pathogenic in ClinVar and falling within genes associated with autosomal dominant disorders. The constructed database of genetic variant frequencies in Russia has been made available to the medical genetics community through a variant browser available at http://ruseq.ru.

Lack of a genetic risk continuum between pubertal timing in the general population and idiopathic hypogonadotropic hypogonadism.

Pubertal timing is a highly heritable trait in the general population. Recently, a large-scale exome-wide association study has implicated rare variants in six genes (KDM4C, MC3R, MKRN3, PDE10A, TACR3, and ZNF483) as genetic determinants of pubertal timing within the general population. Two of the genes (TACR3, MKRN3) are already implicated in extreme disorders of pubertal timing. This observation suggests that there may be a pervasive "genetic risk continuum" wherein genes that govern pubertal timing in the general population, by extension, may also be causal for rare Mendelian disorders of pubertal timing. Hence, we hypothesized that the four novel genes linked to pubertal timing in the population will also contribute to idiopathic hypogonadotropic hypogonadism (IHH), a genetic disorder characterized by absent puberty. Exome sequencing data from 1322 unrelated IHH probands were reviewed for rare sequence variants (RSVs) (minor allele frequency bins: <1%; <0.1%; <0.01%) in the six genes linked to puberty in the general population. A gene-based rare variant association testing (RVAT) was performed between the IHH cohort and a reference public genomic sequences repository-the Genome Aggregation Database (gnomAD). As expected, RVAT analysis showed that RSVs in TACR3, a known IHH gene, were significantly enriched in the IHH cohort compared to gnomAD cohort across all three MAF bins. However, RVAT analysis of the remaining five genes failed to show any RSV enrichment in the IHH cohort across all MAF bins. Our findings argue strongly against a pervasive genetic risk continuum between pubertal timing in the general population and extreme pubertal phenotypes. The biologic basis of such distinct genetic architectures' merits further evaluation.

A local community on a global collective intelligence platform: A case study of individual preferences and collective bias in ecological citizen science.

The collective intelligence of crowds could potentially be harnessed to address global challenges, such as biodiversity loss and species' extinction. For wisdom to emerge from the crowd, certain conditions are required. Importantly, the crowd should be diverse and people's contributions should be independent of one another. Here we investigate a global citizen-science platform-iNaturalist-on which citizens report on wildlife observations, collectively producing maps of species' spatiotemporal distribution. The organization of global platforms such as iNaturalist around local projects compromises the assumption of diversity and independence, and thus raises concerns regarding the quality of such collectively-generated data. We spent four years closely immersing ourselves in a local community of citizen scientists who reported their wildlife sightings on iNaturalist. Our ethnographic study involved the use of questionnaires, interviews, and analysis of archival materials. Our analysis revealed observers' nuanced considerations as they chose where, when, and what type of species to monitor, and which observations to report. Following a thematic analysis of the data, we organized observers' preferences and constraints into four main categories: recordability, community value, personal preferences, and convenience. We show that while some individual partialities can "cancel each other out", others are commonly shared among members of the community, potentially biasing the aggregate database of observations. Our discussion draws attention to the way in which widely-shared individual preferences might manifest as spatial, temporal, and crucially, taxonomic biases in the collectively-created database. We offer avenues for continued research that will help better understand-and tackle-individual preferences, with the goal of attenuating collective bias in data, and facilitating the generation of reliable state-of-nature reports. Finally, we offer insights into the broader literature on biases in collective intelligence systems.

MYO5B and the Polygenic Landscape of Very Early-Onset Inflammatory Bowel Disease in an Ethnically Diverse Population.

Genetic discovery in very early-onset inflammatory bowel disease (VEO-IBD) can elucidate not only the origins of VEO-IBD, but also later-onset inflammatory bowel disease. We aimed to investigate the polygenic origins of VEO-IBD in a cohort with a high proportion of Hispanic patients. Patients with VEO-IBD who underwent whole exome sequencing at our center were included. Genes were categorized as genes of interest (GOIs) (129 genes previously described to be associated with VEO-IBD) or non-GOIs. VEO-IBD "susceptibility" single nucleotide variants (SNVs) were identified through enrichment compared with gnomAD (Genome Aggregation Database) and ALFA (Allele Frequency Aggregator) and were scored by Combined Annotation Dependent Depletion for deleteriousness. Gene networks carrying susceptibility SNVs were created. Myosin 5b immunofluorescence was also studied. Fifty-six patients met inclusion criteria, and 32.1% identified as Hispanic. Monogenic disease was infrequent (8.9%). Significant enrichment of GOI susceptibility SNVs was observed, notably in MYO5B, especially in Hispanics. MEFV, TNFAIP3, SH3TC2, and NCF2 were also central participants in the GOI networks. Myosin 5b immunofluorescence in colonic mucosa was significantly reduced in those with MYO5B susceptibility SNVs compared with control subjects. Seven genes (ESRRA, HLA-DQ1, RETSAT, PABPC1, PARP4, CCDC102A, and SUSD2) were central participants in the non-GOI networks. Our results support the polygenic nature of VEO-IBD, in which key participants, like MYO5B, were identified through network analytics. Rare variant load within susceptibility genes may be relevant not only for the genetic origins of inflammatory bowel disease, but also for the age of disease onset. Our findings could guide future work in precision medicine.

Genetic constraint at single amino acid resolution in protein domains improves missense variant prioritisation and gene discovery

BackgroundOne of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as “genetic constraint”. Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes.MethodsWe aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues.ResultsWe identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism.ConclusionsGrouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

Global prevalence of hereditary thrombotic thrombocytopenic purpura determined by genetic analysis

AbstractHereditary thrombotic thrombocytopenic purpura (hTTP) is a rare autosomal recessive, life-threatening disorder caused by a severe deficiency of the plasma enzyme, ADAMTS13. The current estimated prevalence of hTTP in different regions of the world, 0.5 to 2.0 patients per million, is determined by the frequency of diagnosed patients. To evaluate more accurately the worldwide prevalence of hTTP, and also the prevalence within distinct ethnic groups, we used data available in exome and genome sequencing of 807 162 (730 947 exomes, 76 215 genomes) subjects reported recently by the Genome Aggregation Database (gnomAD-v4.1). Among 1 614 324 analyzed alleles in the gnomAD population we identified 6321 distinct ADAMTS13 variants. Of these, 758 were defined as pathogenic; 140 (18%) variants had been previously reported and 618 (82%) were novel (predicted as pathogenic). In total 10 154 alleles (0.6%) were carrying the reported or predicted pathogenic variants; 7759 (77%) with previously reported variants. Considering all 758 pathogenic variants and also only the 140 previously reported variants, we estimated a global hTTP prevalence of 40 and 23 cases per 106, respectively. Considering only the 140 previously reported variants, the highest estimated prevalence was in East Asians (42 per 106). The estimated prevalences of other populations were: Finnish, 32 per 106; non-Finnish Europeans, 28 per 106; Admixed Americans, 19 per 106; Africans/African Americans, 6 per 106; and South Asians, 4 per 106. The lowest prevalences were Middle Eastern, 1 per 106 and Ashkenazi Jews, 0.7 per 106. This population-based genetic epidemiology study reports that hTTP prevalence is substantially higher than the currently estimated prevalence based on diagnosed patients. Many patients with hTTP may not be diagnosed or may have died during the neonatal period.

Clinical and genetic characteristics of ALS patients with variants in genes regulating DNA methylation.

Aberrant DNA methylation alterations are implicated in amyotrophic lateral sclerosis (ALS). Nevertheless, the influence of genetic variants in genes regulating DNA methylation on ALS patients is not well understood. Therefore, we aim to provide a comprehensive variant profile of genes related to DNA methylation (DNMT1, DNMT3A, DNMT3B, DNMT3L) and demethylation (TET1, TET2, TET3, TDG) and to investigate the association of these variants with ALS. Variants were screened in a cohort of 2240 ALS patients from Southwest China, using controls from the Genome Aggregation Database (n = 9976) and the China Metabolic Analytics Project (n = 10,588). The over-representation of rare variants and their association with ALS risk were evaluated using Fisher's exact test with Bonferroni correction at both allele and gene levels. Kaplan-Meier analysis and Cox regression analysis were employed to explore the relationship between variants and survival. A total of 210 variants meeting the criteria were identified. Gene-based burden analysis identified a significant increase in ALS risk associated with rare variants in the TET2 gene (OR = 1.95, 95% CI = 1.29-2.88, P = 0.001). Survival analysis demonstrated that patients carrying variants in demethylation-related genes had a higher risk of death compared to those with methylation-related gene variants (HR = 1.29, 95% CI = 1.03-1.86, P = 0.039). This study provides a genetic variant profile of genes involved in DNA methylation and demethylation regulation, along with the clinical characteristics of ALS patients carrying these variants. The findings offer genetic evidence implicating disrupted DNA methylation dynamics in ALS.

Evaluating the Performance of In silico Tools for PRRT2 Missense Variants.

Variants in the PRRT2 gene are associated with paroxysmal kinesigenic dyskinesia and other episodic disorders. With the employment of variant screening in patients with episodic dyskinesia, many PRRT2 variants have been discovered. Bioinformatics tools are becoming increasingly important for predicting the functional significance of variants. This study aimed to evaluate the performance of six in silico tools for PRRT2 missense variants. Pathogenic PRRT2 variants were retrieved from the Human Gene Mutation Database (HGMD) and literature from the PubMed database. The benign set of non-deleterious variants was retrieved from the Genome Aggregation Database (gnomAD). The overall accuracy, sensitivity, specificity, positive predictive values, and negative predictive values of SIFT, PolyPhen2, MutationTaster, CADD, Fathmm, and Provean were analyzed. The MCC score and ROC curve were calculated. The GraphPad Prism 8.0 software was used to plot ROC curves for the six bioinformatics software. A total of 45 missense variants with confirmed pathogenicity were used as a positive set, and 222 missense variants were used as a negative set. The top three tools in accuracy are Fathmm, Provean, and MutationTaster. The top three predictors in sensitivity are SIFT, PolyPhen2, and CADD. Regarding specificity, the top three tools were Provean, Fathmm, and MutationTaster. In terms of the MCC and F-score, the highest degree was observed in Fathmm. Fathmm also had the highest AUC score. The cutoff values of Fathmm, CADD, PolyPhen2, and Provean were between the median prediction scores of the positive and negative sets. In contrast, the cutoff value of SIFT was below the median prediction score of the positive and negative sets. Fathmm had the highest accuracy. The prediction performance of six in silico tools differed among the parameters. Fathmm had the best prediction performance, with the highest accuracy and MCC/F-score for PRRT2 missense variants.

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database.

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

Allele frequency of pathogenic variants causing acid sphingomyelinase deficiency and Gaucher disease in the general Japanese population

Acid sphingomyelinase deficiency (ASMD) and Gaucher disease (GD) are lysosomal storage disorders associated with hepatosplenomegaly and thrombocytopenia. The incidences of ASMD and GD are known to be particularly high in the Ashkenazi Jewish population. Conversely, the number of reported patients with these diseases has been limited in Asian countries, including Japan. Here, we reviewed the allele frequencies of pathogenic variants causing ASMD and GD in the Japanese population and populations with various ancestry backgrounds using the Japanese Multi-Omics Reference Panel 54KJPN and the Genome Aggregation Database v4.0.0. The estimated carrier frequencies of ASMD- and GD-related variants were 1/180 and 1/154 in Japanese individuals, equivalent to disease occurrence frequencies of 1/128,191 and 1/94,791 individuals, respectively. These frequencies are much higher than previously expected. Our data also suggest that there are more patients with a milder form of ASMD and nonspecific clinical findings who have not yet been diagnosed.

Landscape of potential germline pathogenic variants in select cancer susceptibility genes in patients with adult-type ovarian granulosa cell tumors.

The objective of this study was to assess the frequency of potential germline pathogenic variants that may contribute to risk of development of adult granulosa cell tumors (AGCT) given the paucity of germline testing guidelines for these patients. This was a retrospective cross-sectional study analyzing comprehensive genomic profiling (CGP) results of AGCT with the FOXL2 p.C134W mutation submitted to Foundation Medicine between 2012 and 2022. Cases with a potential germline pathogenic variant were identified by filtering single nucleotide variants and short indels by variant allele frequency (VAF) and presence in ClinVar for select cancer susceptibility genes. Odds ratios for AGCT risk were calculated compared to a healthy population. Prior to analysis, 595 patients were screened and 516 with a somatic FOXL2 p.C134W mutation were included. Potential germline pathogenic variants in a DNA repair-related gene (ATM, BRCA1, BRCA2, CHEK2, PALB2, PMS2, RAD51C, or RAD51D) were found in 6.6% of FOXL2-mutated AGCT. Potential germline pathogenic CHEK2 variants were found in 3.5% (18/516) of AGCT patients, a rate that was 2.8-fold higher than Genome Aggregation Database non-cancer subjects (95% CI 1.8-4.6, p < 0.001). The founder variants p.I157T (38.9%, 7/18) and p.T367fs*15 (c.1100delC; 27.8%, 5/18) were most commonly observed. CHEK2 VAF indicated frequent loss of the wildtype copy of the gene. These results support ongoing utilization of genomic tumor profiling and confirmatory germline testing for potential germline pathogenic variants. Further prospective investigation into the biology of germline variants in this population is warranted.

A case report of classic galactosemia with a GALT gene variant and a literature review

BackgroundGalactosemia is an autosomal recessive disorder resulting from an enzyme defect in the galactose metabolic pathway. The most severe manifestation of classic galactosemia is caused by galactose-1-phosphate uridylyltransferase (GALT) deficiency, and this condition can be fatal during infancy if left untreated. It also may result in long-term complications in affected individuals.Case presentationThis report describes a patient whose initial clinical symptoms were jaundice and liver dysfunction. The patient’s liver and coagulation functions did not improve after multiple admissions and treatment with antibiotics, hepatoprotective and choleretic agents and blood transfusion. Genetic analysis revealed the presence of two variants in the GALT gene in the compound heterozygous state: c.377 + 2dup and c.368G > C (p.Arg123Pro). Currently, the variant locus (c.377 + 2dup) in the GALT gene has not been reported in the Human Gene Mutation Database (HGMD), while c.368G > C (p.Arg123Pro) has not been reported in the Genome Aggregation Database (GnomAD) nor the HGMD in East Asian population. We postulated that the two variants may contribute to the development of classical galactosemia.ConclusionsApplications of whole-exome sequencing to detect the two variants can improve the detection and early diagnosis of classical galactosemia and, more specifically, may identify individuals who are compound heterozygous with variants in the GALT gene. Variants in the GALT gene have a potential therapeutic significance for classical galactosemia.

Genetic background of primary and familial HLH in Qatar: registry data and population study.

Familial hemophagocytic lymphohistiocytosis (FHLH) is an inherited life-threatening disease. Five types are identified, with the addition of congenital immunodeficiency syndromes in which HLH is a typical manifestation. The literature on this disease is very scarce in the Middle East, with only a few scattered reports. We report detailed demographic, clinical, and genomic data from 28 patients diagnosed with primary and familial HLH over the last decade in Qatar. An evaluation was performed of allele frequencies of deleterious variants from 12 primary and familial HLH causative genes on the Qatar Genome Programme (QGP) cohort of 14,669 Qatari individuals. The genetic diagnosis was obtained in 15 patients, and four novel mutations in Perforin 1 (PRF1), UNC13D, LYST, and RAB27A genes were found. We identified 22,945 low/high/moderate/modifier impact variants significantly enriched in the QGP in those 12 genes. The variants rs1271079313 in PRF1 and rs753966933 in RAB27A found in our patient cohort were significantly more prevalent in the QGP compared to the Genome Aggregation Database (gnomAD) database, with a high carrier frequency in the Qatari population. We established the first primary and familial HLH Registry in the Gulf Region and identified novel possibly pathogenic variants present at higher frequency in the Qatari population, which could be used for screening purposes. Raising awareness about primary and familial HLH and implementing screening activities in the Qatari highly inbred population could stem into more comprehensive premarital and prenatal evaluations and faster diagnosis.

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.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.