The Genome of the Netherlands: design, and project goals

Detection of Genetic Variants in Thai Population by Trio-Based Whole-Genome Sequencing Study

This trio-based whole-genome sequencing (WGS) study enhances the accuracy of variant detection by leveraging parental genotypes, which facilitates the identification of de novo mutations and population-specific variants. Nonetheless, the comprehensive genetic variation data of the Thai population remain limited, posing challenges to advancing personalized medicine and population-based screening strategies. We establish the genetic variation information of a healthy Thai population by analyzing the sequences of 40 trios, yielding 120 whole genomes (excluding offspring). The resulting dataset encompasses 20.2 million variants, including 1.1 million novel and 19.1 million known variants. Within this dataset, we identify 169 pathogenic variants, of which 56 are classified as rare and 87 are absent from the ClinVar database as of version 2023. These pathogenic variants, particularly the rare and de novo mutations, will likely be of significant interest for genetic association studies. Notably, one pathogenic variant linked to a de novo mutation is found in the SF3B2 gene, which is associated with craniofacial microsomia. With its innovative methodology and comprehensive dataset, our trio-based whole-genome sequencing study provides an invaluable representation of the genetic variations in the Thai population. These data provide a critical foundation for further analyses of the pathogenic variants related to human disease phenotypes in genetic association studies.

Validation of the IDseek® OmniSTR™ Global Autosomal STR Profiling kit, reverse complement PCR as an improved tool/method for routine massively parallel sequencing of short tandem repeats

Massively Parallel Sequencing (MPS) has gained interest in the forensic community over the past decade. Most of the published MPS methods focus on specialty applications intended for use in a limited number of samples with protocols that are relatively laborious. Recent developments using Reverse-Complement PCR enable an efficient MPS protocol suited for routine analysis of high numbers of samples. This method is implemented in the IDseek® OmniSTR™ Global Autosomal STR Profiling kit (Nimagen) for sequencing 28 of the most commonly used forensic autosomal STRs, one Y-chromosomal STR and Amelogenin. This study describes the validation of this kit and focuses on sensitivity, inhibitor tolerance, sequence variation detection and performance with mixtures up to 5 contributors. Results are compared to a Capillary Electrophoresis method (the PowerPlex® Fusion 6 C system, Promega) and the first commercial forensic MPS kit (ForenSeq™ DNA Signature prep, Qiagen) and for a concordance study with data from the Powerseq® MPS kit as well. Analysis settings in FDSTools are deduced and discussed, and an almost completely automated analysis is achieved. Using FDSTools noise correction, contributions in a mixture down to a level of 1.5 % of the major allele of a marker can be detected.

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.

Association between ACE (rs4343 and rs1799752), AGTR1 (rs5186), and PAI-1 (rs2227631) polymorphisms in the host and the severity of Covid-19 infection

OBJECTIVE

It is necessary to identify appropriate clinical, biochemical, epidemiological and genetic biomarkers to elucidate the underlying mechanisms of the coronavirus disease-2019 (COVID-19) disease. The study focused on not only the link between disease severity (non-intense unit care (non-ICU) versus intensive unit care (ICU) and genetic susceptibility in COVID-19 patients but also the connection between comorbidity and genetic susceptibility affecting the severity of COVID-19.

SUBJECT AND METHODS

One hundred and sixty-two COVID-19 patients treated in the non-ICU and ICU in Kayseri City Hospital were included. All volunteers underwent a physical examination and biochemical evaluation. Angiotensin-converting enzyme (ACE p.T776T G > A(rs4343) and g.16471_16472delinsALU (also referred to as I/D polymorphism; rs1799752), angiotensin II receptor type-1 (AGTR1) c.*86A > C (also referred to as A1166C; rs5186), and plasminogen activator inhibitor-1 (PAI-1-844 G > A (rs2227631) polymorphisms were analysed as well.

RESULTS

To have ACE "ID" genotype did not change the severity of the disease (OR: 0.92, 95% CI: 0.41-2.1, p = 0.84), but decreased the mortality risk 2.9-fold (OR: 2.9, 95% CI: 1.1-7.0, p = 0.03). In PAI-1-844 G > A, having the "AA" genotype in the "A" recessive model increased the risk of the diabetes mellitus (DM) 2.3-fold (OR: 2.3 95%, CI: 1.16-4.66, p = 0.018). In the "G" recessive model, to have the GG genotype increased the risk of chronic kidney disease (CKD) 4.8-fold (OR:4.8, 95% CI: 1.5-15.5, p = 0.008). "GG" genotype in the DM group had a higher fibrinogen level compared to those with the "AG" genotype (AG:4847.2 mg/L (1704.3) versus GG:6444.67 mg/L (1861.62) p = 0.019) and "AA" genotype in the CKD group had lower platelet levels and those with "GG" had higher platelet levels (AA:149 µL (18-159) versus GG: 228 µL (146-357) p = 0.022).

CONCLUSION

This study was shown that genetic predispositions that causes comorbidities were also likely to affect the prognosis of COVID-19.

Capturing the fusion of two ancestries and kinship structures in Merovingian Flanders

The Merovingian period (5th to 8th cc AD) was a time of demographic, socioeconomic, cultural, and political realignment in Western Europe. Here, we report the whole-genome shotgun sequence data of 30 human skeletal remains from a coastal Late Merovingian site of Koksijde (675 to 750 AD), alongside 18 remains from two Early to Late Medieval sites in present-day Flanders, Belgium. We find two distinct ancestries, one shared with Early Medieval England and the Netherlands, while the other, minor component, reflecting likely continental Gaulish ancestry. Kinship analyses identified no large pedigrees characteristic to elite burials revealing instead a high modularity of distant relationships among individuals of the main ancestry group. In contrast, individuals with >90% Gaulish ancestry had no kinship links among sampled individuals. Evidence for population structure and major differences in the extent of Gaulish ancestry in the main group, including in a mother-daughter pair, suggests ongoing admixture in the community at the time of their burial. The isotopic and genetic evidence combined supports a model by which the burials, representing an established coastal nonelite community, had incorporated migrants from inland populations. The main group of burials at Koksijde shows an abundance of >5 cM long shared allelic intervals with the High Medieval site nearby, implying long-term continuity and suggesting that similarly to Britain, the Early Medieval ancestry shifts left a significant and long-lasting impact on the genetic makeup of the Flemish population. We find substantial allele frequency differences between the two ancestry groups in pigmentation and diet-associated variants, including those linked with lactase persistence, likely reflecting ancestry change rather than local adaptation.

Egypt Genome: Towards an African new genomic era

BACKGROUND

Studying the human genome is crucial to embrace precision medicine through tailoring treatment and prevention strategies to the unique genetic makeup and molecular information of individuals. After human genome project (1990-2003) generated the first full sequence of a human genome, there have been concerns towards Northern bias due to underrepresentation of other populations. Multiple countries have now established national genome projects aiming at the genomic knowledge that can be harnessed from their populations, which in turn can serve as a basis for their health care policies in the near future.

AIM OF REVIEW

The intention is to introduce the recently established Egypt Genome (EG) to delineate the genomics and genetics of both the modern and Ancient Egyptian populations. Leveraging genomic medicine to improve precision medicine strategies while building a solid foundation for large-scale genomic research capacity is the fundamental focus of EG.

KEY SCIENTIFIC CONCEPTS

EG generated genomic knowledge is predicted to enrich the existing human genome and to expand its diversity by studying the underrepresented African/Middle Eastern populations. The insightful impact of EG goes beyond Egypt and Africa as it fills the knowledge gaps in health and disease genomics towards improved and sustainable genomic-driven healthcare systems for better outcomes. Promoting the integration of genomics into clinical practice and spearheading the implementation of genomic-driven healthcare and precision medicine is therefore a key focus of EG. Mining into the wealth of Ancient Egyptian Genomics to delineate the genetic bridge between the contemporary and Ancient Egyptian populations is another excitingly unique area of EG to realize the global vision of human genome.

Molecular analysis of cancer genomes in children with Lynch syndrome: Exploring causal associations

Lynch syndrome (LS) predisposes to cancer in adulthood and is caused by heterozygous germline variants in a mismatch repair (MMR) gene. Recent studies show an increased prevalence of LS among children with cancer, suggesting a causal relationship. For LS-spectrum (LSS) cancers, including high-grade gliomas and colorectal cancer, causality has been supported by typical MMR-related tumor characteristics, but for non-LSS cancers, causality is unclear. We characterized 20 malignant tumors of 18 children with LS, including 16 non-LSS tumors. We investigated second hits, tumor mutational load, mutational signatures and MMR protein expression. In all LSS tumors and three non-LSS tumors, we detected MMR deficiency caused by second hit somatic alterations. Furthermore, these MMR-deficient tumors carried driver variants that likely originated as a consequence of MMR deficiency. However, in 13 non-LSS tumors (81%), a second hit and MMR deficiency were absent, thus a causal link between LS and cancer development in these children is lacking. These findings demonstrate that causality of LS in children with cancer, which can be determined by molecular tumor characterization, seems to be restricted to specific tumor types. Large molecular and epidemiological studies are needed to further refine the tumor spectrum in children with LS.

Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Risk-conferring HLA variants in an epilepsy cohort: benefits of multifaceted use of whole genome sequencing in clinical practice

BACKGROUND

Whole genome sequencing is increasingly used in healthcare, particularly for diagnostics. However, its clinically multifaceted potential for individually customised diagnostic and therapeutic care remains largely unexploited. We used existing whole genome sequencing data to screen for pharmacogenomic risk factors related to antiseizure medication-induced cutaneous adverse drug reactions (cADRs), such as human leucocyte antigen HLA-B*15:02, HLA-A*31:01 variants.

METHODS

Genotyping results, generated from the Genomics England UK 100 000 Genomes Project primarily for identification of disease-causing variants, were used to additionally screen for relevant HLA variants and other pharmacogenomic variants. Medical records were retrospectively reviewed for clinical and cADR phenotypes for HLA variant carriers. Descriptive statistics and the χ2 test were used to analyse phenotype/genotype data for HLA carriers and compare frequencies of additional pharmacogenomic variants between HLA carriers with and without cADRs, respectively.

RESULTS

1043 people with epilepsy were included. Four HLA-B*15:02 and 86 HLA-A*31:01 carriers were identified. One out of the four identified HLA-B*15:02 carriers had suffered antiseizure medication-induced cADRs; the point prevalence of cADRs was 16.9% for HLA-A*31:01 carriers of European origin (n=46) and 14.4% for HLA-A*31:01 carriers irrespective of ancestry (n=83).

CONCLUSIONS

Comprehensive utilisation of genetic data spreads beyond the search for causal variants alone and can be extended to additional clinical benefits such as identifying pharmacogenomic biomarkers, which can guide pharmacotherapy for genetically-susceptible individuals.

Identification of candidate genes for developmental colour agnosia in a single unique family

Colour agnosia is a disorder that impairs colour knowledge (naming, recognition) despite intact colour perception. Previously, we have identified the first and only-known family with hereditary developmental colour agnosia. The aim of the current study was to explore genomic regions and candidate genes that potentially cause this trait in this family. For three family members with developmental colour agnosia and three unaffected family members CGH-array analysis and exome sequencing was performed, and linkage analysis was carried out using DominantMapper, resulting in the identification of 19 cosegregating chromosomal regions. Whole exome sequencing resulted in 11 rare coding variants present in all affected family members with developmental colour agnosia and absent in unaffected members. These variants affected genes that have been implicated in neural processes and functions (CACNA2D4, DDX25, GRINA, MYO15A) or that have an indirect link to brain function, development or disease (MAML2, STAU1, TMED3, RABEPK), and a remaining group lacking brain expression or involved in non-neural traits (DEPDC7, OR1J1, OR8D4). Although this is an explorative study, the small set of candidate genes that could serve as a starting point for unravelling mechanisms of higher level cognitive functions and cortical specialization, and disorders therein such as developmental colour agnosia.

Heterozygosity of ALG9 in Association with Autosomal Dominant Polycystic Liver Disease

α-1,2-mannosyltransferase (ALG9) germline variants are linked to autosomal dominant polycystic kidney disease (ADPKD). Many individuals affected with ADPKD possess polycystic livers as a common extrarenal manifestation. We performed whole exome sequencing in a female with autosomal dominant polycystic liver disease (ADPLD) without kidney cysts and established the presence of a heterozygous missense variant (c.677G>C p.(Gly226Ala)) in ALG9. In silico pathogenicity prediction and 3D protein modeling determined this variant as pathogenic. Loss of heterozygosity is regularly seen in liver cyst walls. Immunohistochemistry indicated the absence of ALG9 in liver tissue from this patient. ALG9 expression was absent in cyst wall lining from ALG9- and PRKCSH-caused ADPLD patients but present in the liver cyst lining derived from an ADPKD patient with a PKD2 variant. Thus, heterozygous pathogenic variants in ALG9 are also associated with ADPLD. Somatic loss of heterozygosity of the ALG9 enzyme was seen in the ALG9 patient but also in ADPLD patients with a different genetic background. This expanded the phenotypic spectrum of ADPLD to ALG9.

Genetic Burden of TNNI3K in Diagnostic Testing of Patients With Dilated Cardiomyopathy and Supraventricular Arrhythmias

BACKGROUND

Genetic variants in TNNI3K (troponin-I interacting kinase) have previously been associated with dilated cardiomyopathy (DCM), cardiac conduction disease, and supraventricular tachycardias. However, the link between TNNI3K variants and these cardiac phenotypes shows a lack of consensus concerning phenotype and protein function.

METHODS

We describe a systematic retrospective study of a cohort of patients undergoing genetic testing for cardiac arrhythmias and cardiomyopathy including TNNI3K. We further performed burden testing of TNNI3K in the UK Biobank. For 2 novel TNNI3K variants, we tested cosegregation. TNNI3K kinase function was estimated by TNNI3K autophosphorylation assays.

RESULTS

We demonstrate enrichment of rare coding TNNI3K variants in DCM patients in the Amsterdam cohort. In the UK Biobank, we observed an association between TNNI3K missense (but not loss-of-function) variants and DCM and atrial fibrillation. Furthermore, we demonstrate genetic segregation for 2 rare variants, TNNI3K-p.Ile512Thr and TNNI3K-p.His592Tyr, with phenotypes consisting of DCM, cardiac conduction disease, and supraventricular tachycardia, together with increased autophosphorylation. In contrast, TNNI3K-p.Arg556_Asn590del, a likely benign variant, demonstrated depleted autophosphorylation.

CONCLUSIONS

Our findings demonstrate an increased burden of rare coding TNNI3K variants in cardiac patients with DCM. Furthermore, we present 2 novel likely pathogenic TNNI3K variants with increased autophosphorylation, suggesting that enhanced autophosphorylation is likely to drive pathogenicity.

Aicardi Syndrome Is a Genetically Heterogeneous Disorder

Aicardi Syndrome (AIC) is a rare neurodevelopmental disorder recognized by the classical triad of agenesis of the corpus callosum, chorioretinal lacunae and infantile epileptic spasms syndrome. The diagnostic criteria of AIC were revised in 2005 to include additional phenotypes that are frequently observed in this patient group. AIC has been traditionally considered as X-linked and male lethal because it almost exclusively affects females. Despite numerous genetic and genomic investigations on AIC, a unifying X-linked cause has not been identified. Here, we performed exome and genome sequencing of 10 females with AIC or suspected AIC based on current criteria. We identified a unique de novo variant, each in different genes: KMT2B, SLF1, SMARCB1, SZT2 and WNT8B, in five of these females. Notably, genomic analyses of coding and non-coding single nucleotide variants, short tandem repeats and structural variation highlighted a distinct lack of X-linked candidate genes. We assessed the likely pathogenicity of our candidate autosomal variants using the TOPflash assay for WNT8B and morpholino knockdown in zebrafish (Danio rerio) embryos for other candidates. We show expression of Wnt8b and Slf1 are restricted to clinically relevant cortical tissues during mouse development. Our findings suggest that AIC is genetically heterogeneous with implicated genes converging on molecular pathways central to cortical development.

Genetic Ancestry Estimates within Dutch Family Units and Across Genotyping Arrays: Insights from Empirical Analysis Using Two Estimation Methods

Accurate inference of genetic ancestry is crucial for population-based association studies, accounting for population heterogeneity and structure. This study analyzes genome-wide SNP data from the Netherlands Twin Register to compare genetic ancestry estimates. The focus is on the comparison of ancestry estimates between family members and individuals genotyped on multiple arrays (Affymetrix 6.0, Affymetrix Axiom, and Illumina GSA). Two conventional methods, principal component analysis and ADMIXTURE, were implemented to estimate ancestry, each serving its specific purpose, rather than for direct comparison. The results reveal that as the degree of genetic relatedness decreases, the Euclidean distances of genetic ancestry estimates between family members significantly increase (empirical p < 0.001), regardless of the estimation method and genotyping array. Ancestry estimates among individuals genotyped on multiple arrays also show statistically significant differences (empirical p < 0.001). Additionally, this study investigates the relationship between the ancestry estimates of non-identical twin offspring with ancestrally diverse parents and those with ancestrally similar parents. The results indicate a statistically significant weak correlation between the variation in ancestry estimates among offspring and differences in ancestry estimates among parents (Spearman's rho: 0.07, p = 0.005). This study highlights the utility of current methods in inferring genetic ancestry, emphasizing the importance of reference population composition in determining ancestry estimates.

Molecular analysis of gene variants in an Iranian family with psychomotor retardation mitochondrial disorder patient

In 1-year-old girl presenting with neurodegenerative mitochondrial disease (Leigh syndrome), mutation analysis was performed by whole exome sequencing. Pathogenic variants were then analyzed in parents and relatives by Sanger sequencing. We identified a point mutation c.G484A in NDUFS8 gene which was homozygous in patient and heterozygous in parents.

An Association Study of Germline Variants in Bladder Cancer-Related Genes with the Prognosis of Non-Muscle Invasive Bladder Cancer

BACKGROUND

Various germline genetic variants are associated with the prognosis of non-muscle invasive bladder cancer (NMIBC). Germline variants in genes frequently somatically mutated in bladder cancer have not been studied thoroughly in relation to risk of recurrence or progression in NMIBC.

OBJECTIVE

To identify germline DNA variants in bladder carcinogenesis-related genes associated with recurrence or progression in NMIBC.

METHODS

We analysed associations between single-nucleotide polymorphisms (SNPs) and NMIBC recurrence and progression using data from the Nijmegen Bladder Cancer Study (NBCS, 1,443 patients). We included 5,053 SNPs within 46 genes known to have mutation, overexpression or amplification in bladder cancer. We included all recurrences in the statistical analysis and performed both single variant analysis and gene-based analysis. SNPs and genes that showed significant or suggestive association (false discovery rate P value < 20%) were followed-up in independent cohorts for replication analysis, through eQTL analysis and tests for association of tumour expression levels with NMIBC recurrence and progression.

RESULTS

Single variant analysis showed no statistically significant associations with recurrence or progression. In gene-based analysis, the aggregate effect of the 25 SNPs in the Cyclin D1 gene (CCND1) was statistically significantly associated with NMIBC recurrence (Punadj = 0.001, PFDR = 0.046), but not with progression (Punadj = 0.17, PFDR = 0.54). Validation analysis in independent cohorts did not confirm the association of CCND1 with NMIBC recurrence.

CONCLUSIONS

We could not identify reproducible associations between common germline variants in bladder carcinogenesis-related genes and NMIBC recurrence or progression.

Reclassification of a likely pathogenic Dutch founder variant in KCNH2; implications of reduced penetrance

BACKGROUND

Variants in KCNH2, encoding the human ether a-go-go (hERG) channel that is responsible for the rapid component of the cardiac delayed rectifier K+ current (IKr), are causal to long QT syndrome type 2 (LQTS2). We identified eight index patients with a new variant of unknown significance (VUS), KCNH2:c.2717C > T:p.(Ser906Leu). We aimed to elucidate the biophysiological effect of this variant, to enable reclassification and consequent clinical decision-making.

METHODS

A genotype-phenotype overview of the patients and relatives was created. The biophysiological effects were assessed independently by manual-, and automated calibrated patch clamp. HEK293a cells expressing (i) wild-type (WT) KCNH2, (ii) KCNH2-p.S906L alone (homozygous, Hm) or (iii) KCNH2-p.S906L in combination with WT (1:1) (heterozygous, Hz) were used for manual patching. Automated patch clamp measured the variants function against known benign and pathogenic variants, using Flp-In T-rex HEK293 KCNH2-variant cell lines.

RESULTS

Incomplete penetrance of LQTS2 in KCNH2:p.(Ser906Leu) carriers was observed. In addition, some patients were heterozygous for other VUSs in CACNA1C, PKP2, RYR2 or AKAP9. The phenotype of carriers of KCNH2:p.(Ser906Leu) ranged from asymptomatic to life-threatening arrhythmic events. Manual patch clamp showed a reduced current density by 69.8 and 60.4% in KCNH2-p.S906L-Hm and KCNH2-p.S906L-Hz, respectively. The time constant of activation was significantly increased with 80.1% in KCNH2-p.S906L-Hm compared with KCNH2-WT. Assessment of KCNH2-p.S906L-Hz by calibrated automatic patch clamp assay showed a reduction in current density by 35.6%.

CONCLUSION

The reduced current density in the KCNH2-p.S906L-Hz indicates a moderate loss-of-function. Combined with the reduced penetrance and variable phenotype, we conclude that KCNH2:p.(Ser906Leu) is a low penetrant likely pathogenic variant for LQTS2.

The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study

Introduction

Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer.

Methods

Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS).

Results

We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers.

Discussion

Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.

WGS Data Collections: How Do Genomic Databases Transform Medicine?

As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and may play an important regulatory function. The first WGS-based datasets have already been released including underrepresented populations. Although many databases contain pooled data from several cohorts, recently the importance of local databases has been highlighted. Genomic databases are not only collecting data but may also contribute to better diagnostics and therapies. They may find applications in population studies, rare diseases, oncology, pharmacogenetics, and infectious and inflammatory diseases. Further data may be analysed with Al technologies and in the context of other omics data. To exemplify their utility, we put a highlight on the Polish genome database and its practical application.

LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes

BACKGROUND

Loss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. The association of LoF variants with complex diseases and traits may lead to the discovery and validation of novel therapeutic targets. Current approaches predict high-confidence LoF variants without identifying the specific genes or the number of copies they affect. Moreover, there is a lack of methods for detecting knockout genes caused by compound heterozygous (CH) LoF variants.

RESULTS

We have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from genotyped, imputed and sequenced genomes. LoFTK enables the identification of genes that are inactive in one or two copies and provides summary statistics for downstream analyses. LoFTK can identify CH LoF variants, which result in LoF genes with two copies lost. Using data from parents and offspring we show that 96% of CH LoF genes predicted by LoFTK in the offspring have the respective alleles donated by each parent.

CONCLUSIONS

LoFTK is a command-line based tool that provides a reliable computational workflow for predicting LoF variants from genotyped and sequenced genomes, identifying genes that are inactive in 1 or 2 copies. LoFTK is an open software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK .

Longitudinal Epigenome-Wide Analysis of Kidney Transplant Recipients Pretransplant and Posttransplant

Introduction

Kidney transplantation remains the gold standard of treatment for end-stage renal disease (ESRD), with improved patient outcomes compared with dialysis. Epigenome-Wide Association Analysis (EWAS) of DNA methylation may identify markers that contribute to an individual's risk of adverse transplant outcomes, yet only a limited number of EWAS have been conducted in kidney transplant recipients. This EWAS aimed to interrogate the methylation profile of a kidney transplant recipient cohort with minimal posttransplant complications, exploring differences in samples pretransplant and posttransplant.

Methods

We compared differentially methylated cytosine-phosphate-guanine sites (dmCpGs) in samples derived from peripheral blood mononuclear cells of the same kidney transplant recipients, collected both pretransplant and posttransplant (N = 154), using the Infinium MethylationEPIC microarray (Illumina, San Diego, CA). Recipients received kidneys from deceased donors and had a mean of 17 years of follow-up.

Results

Five top-ranked dmCpGs were significantly different at false discovery rate (FDR) adjusted P ≤ 9 × 10-8; cg23597162 within JAZF1, cg25187293 within BTNL8, cg17944885, located between ZNF788P and ZNF625-ZNF20, cg14655917 located between ASB4 and PDK4 and cg09839120 located between GIMAP6 and EIF2AP3.

Conclusion

Five dmCpGs were identified at the generally accepted EWAS critical significance level of FDR adjusted P (P FDRadj) ≤ 9 × 10-8, including cg23597162 (within JAZF1) and cg17944885, which have prior associations with chronic kidney disease (CKD). Comparing individuals with no evidence of posttransplant complications (N = 105) demonstrated that 693,555 CpGs (89.57%) did not display any significant difference in methylation (P FDRadj ≥ 0.05), thereby this study establishes an important reference for future epigenetic studies that seek to identify markers of posttransplant complications.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

de novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units-based workflow. We applied our workflow to whole-genome sequencing data from three parent-child sequenced cohorts including the Simons Simplex Collection (SSC), Simons Foundation Powering Autism Research (SPARK), and the 1000 Genomes Project (1000G) that were sequenced using DNA from blood, saliva, and lymphoblastoid cell lines (LCLs), respectively. The SSC and SPARK DNV callsets were within expectations for number of DNVs, percent at CpG sites, phasing to the paternal chromosome of origin, and average allele balance. However, the 1000G DNV callset was not within expectations and contained excessive DNVs that are likely cell line artifacts. Mutation signature analysis revealed 30% of 1000G DNV signatures matched B-cell lymphoma. Furthermore, we found variants in DNA repair genes and at Clinvar pathogenic or likely-pathogenic sites and significant excess of protein-coding DNVs in IGLL5; a gene known to be involved in B-cell lymphomas. Our study provides a new rapid DNV caller for the field and elucidates important implications of using sequencing data from LCLs for reference building and disease-related projects.

A Genome-Wide Association Study into the Aetiology of Congenital Solitary Functioning Kidney

Congenital solitary functioning kidney (CSFK) is a birth defect that occurs in 1:1500 children and predisposes them to kidney injury. Its aetiology is likely multifactorial. In addition to known monogenic causes and environmental risk factors, common genetic variation may contribute to susceptibility to CSFK. We performed a genome-wide association study among 452 patients with CSFK and two control groups of 669 healthy children and 5363 unaffected adults. Variants in two loci reached the genome-wide significance threshold of 5 × 10-8, and variants in 30 loci reached the suggestive significance threshold of 1 × 10-5. Of these, an identified locus with lead single nucleotide variant (SNV) rs140804918 (odds ratio 3.1, p-value = 1.4 × 10-8) on chromosome 7 was most promising due to its close proximity to HGF, a gene known to be involved in kidney development. Based on their known molecular functions, both KCTD20 and STK38 could explain the suggestive significant association with lead SNV rs148413365 on chromosome 6. Our findings need replication in an independent cohort of CSFK patients before they can be established definitively. However, our analysis suggests that common variants play a role in CSFK aetiology. Future research could enhance our understanding of the molecular mechanisms involved.

Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome

The levels of the thousands of metabolites in the human plasma metabolome are strongly influenced by an individual's genetics and the composition of their diet and gut microbiome. Here, by assessing 1,183 plasma metabolites in 1,368 extensively phenotyped individuals from the Lifelines DEEP and Genome of the Netherlands cohorts, we quantified the proportion of inter-individual variation in the plasma metabolome explained by different factors, characterizing 610, 85 and 38 metabolites as dominantly associated with diet, the gut microbiome and genetics, respectively. Moreover, a diet quality score derived from metabolite levels was significantly associated with diet quality, as assessed by a detailed food frequency questionnaire. Through Mendelian randomization and mediation analyses, we revealed putative causal relationships between diet, the gut microbiome and metabolites. For example, Mendelian randomization analyses support a potential causal effect of Eubacterium rectale in decreasing plasma levels of hydrogen sulfite-a toxin that affects cardiovascular function. Lastly, based on analysis of the plasma metabolome of 311 individuals at two time points separated by 4 years, we observed a positive correlation between the stability of metabolite levels and the amount of variance in the levels of that metabolite that could be explained in our analysis. Altogether, characterization of factors that explain inter-individual variation in the plasma metabolome can help design approaches for modulating diet or the gut microbiome to shape a healthy metabolome.

Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease

INTRODUCTION

A few copy number variations (CNVs) have been reported for Alzheimer's disease (AD). However, there is a lack of a systematic investigation of CNVs in AD based on whole genome sequencing (WGS) data.

METHODS

We used four methods to identify consensus CNVs from the WGS data of 1,411 individuals and further investigated their functional roles in AD using the matched transcriptomic and clinicopathological data.

RESULTS

We identified 3,012 rare AD-specific CNVs whose residing genes are enriched for cellular glucuronidation and neuron projection pathways. Genes whose mRNA expressions are significantly correlated with common CNVs are involved in major histocompatibility complex class II receptor activity. Integration of CNVs, gene expression, and clinical and pathological traits further pinpoints a key CNV that potentially regulates immune response in AD.

DISCUSSION

We identify CNVs as potential genetic regulators of immune response in AD. The identified CNVs and their downstream gene networks reveal novel pathways and targets for AD.

Limited evidence for blood eQTLs in human sexual dimorphism

BACKGROUND

The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits.

METHODS

To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs.

RESULTS

Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection.

CONCLUSIONS

Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.

CMDB: the comprehensive population genome variation database of China

A high-quality genome variation database derived from a large-scale population is one of the most important infrastructures for genomics, clinical and translational medicine research. Here, we developed the Chinese Millionome Database (CMDB), a database that contains 9.04 million single nucleotide variants (SNV) with allele frequency information derived from low-coverage (0.06×-0.1×) whole-genome sequencing (WGS) data of 141 431 unrelated healthy Chinese individuals. These individuals were recruited from 31 out of the 34 administrative divisions in China, covering Han and 36 other ethnic minorities. CMDB, housing the WGS data of a multi-ethnic Chinese population featuring wide geographical distribution, has become the most representative and comprehensive Chinese population genome database to date. Researchers can quickly search for variant, gene or genomic regions to obtain the variant information, including mutation basic information, allele frequency, genic annotation and overview of frequencies in global populations. Furthermore, the CMDB also provides information on the association of the variants with a range of phenotypes, including height, BMI, maternal age and twin pregnancy. Based on these data, researchers can conduct meta-analysis of related phenotypes. CMDB is freely available at https://db.cngb.org/cmdb/.

New Drug Development and Clinical Trial Design by Applying Genomic Information Management

Depending on the patients' genotype, the same drug may have different efficacies or side effects. With the cost of genomic analysis decreasing and reliability of analysis methods improving, vast amount of genomic information has been made available. Several studies in pharmacology have been based on genomic information to select the optimal drug, determine the dose, predict efficacy, and prevent side effects. This paper reviews the tissue specificity and genomic information of cancer. If the tissue specificity of cancer is low, cancer is induced in various organs based on a single gene mutation. Basket trials can be performed for carcinomas with low tissue specificity, confirming the efficacy of one drug for a single gene mutation in various carcinomas. Conversely, if the tissue specificity of cancer is high, cancer is induced in only one organ based on a single gene mutation. An umbrella trial can be performed for carcinomas with a high tissue specificity. Some drugs are effective for patients with a specific genotype. A companion diagnostic strategy that prescribes a specific drug for patients selected with a specific genotype is also reviewed. Genomic information is used in pharmacometrics to identify the relationship among pharmacokinetics, pharmacodynamics, and biomarkers of disease treatment effects. Utilizing genomic information, sophisticated clinical trials can be designed that will be better suited to the patients of specific genotypes. Genomic information also provides prospects for innovative drug development. Through proper genomic information management, factors relating to drug response and effects can be determined by selecting the appropriate data for analysis and by understanding the structure of the data. Selecting pre-processing and appropriate machine-learning libraries for use as machine-learning input features is also necessary. Professional curation of the output result is also required. Personalized medicine can be realized using a genome-based customized clinical trial design.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

DPYD*7 as a Predictor of Severe Fluoropyrimidine-Related Adverse Events

PURPOSE

Around 20%-30% of patients treated with fluoropyrimidines develop severe treatment-related adverse events (AEs). These are mainly caused by deficiency of dihydropyrimidine dehydrogenase, its main metabolizing enzyme. The DPYD*7 variant allele contains a frameshift mutation that leads to absence of dihydropyrimidine dehydrogenase. Clinical studies on this variant in patients treated with fluoropyrimidines are lacking because of its low minor allelic frequency. However, the DPYD*7 minor allelic frequency is 56-times higher in the Dutch compared with the global population. This allowed us to evaluate fluoropyrimidine tolerability in DPYD*7 variant allele carriers.

MATERIALS AND METHODS

Patients treated with standard-of-care fluoropyrimidine who were pretreatment DPYD genotyped for DPYD*2A, *13, 2846A>T, and 1236G>A single-nucleotide polymorphisms were included for analyses. Patients were additionally screened for the DPYD*7 allele (rs72549309, 295-298delTCAT). AEs were graded if they worsened from baseline, according to Common Terminology Criteria for Adverse Events version 5.0. AEs ≥ grade 3 were considered severe.

RESULTS

From 3,748 patients, we found 13 patients carrying heterozygous DPYD*7. Relevant clinical data were available for 11 patients. All patients developed fluoropyrimidine-related AEs, of which five patients developed severe AEs (46%). From these five patients, three patients were started with 65% or 50% of standard dose, but apparently still developed severe toxicity. Because of severe AEs, three patients discontinued treatment prematurely (one patient already started with 50% of standard dose) and one patient who started with 50% of standard dose was further reduced to 35% of standard dose.

CONCLUSION

In this study, the clinical consequences of carrying the DPYD*7 variant allele were confirmed as 46% of the patients developed severe AEs, even in the presence of initial dose reductions. This underlines the need for prospective studies investigating the required fluoropyrimidine dose for DPYD*7 carriers.

Genetic pain loss disorders

Genetic pain loss includes congenital insensitivity to pain (CIP), hereditary sensory neuropathies and, if autonomic nerves are involved, hereditary sensory and autonomic neuropathy (HSAN). This heterogeneous group of disorders highlights the essential role of nociception in protecting against tissue damage. Patients with genetic pain loss have recurrent injuries, burns and poorly healing wounds as disease hallmarks. CIP and HSAN are caused by pathogenic genetic variants in >20 genes that lead to developmental defects, neurodegeneration or altered neuronal excitability of peripheral damage-sensing neurons. These genetic variants lead to hyperactivity of sodium channels, disturbed haem metabolism, altered clathrin-mediated transport and impaired gene regulatory mechanisms affecting epigenetic marks, long non-coding RNAs and repetitive elements. Therapies for pain loss disorders are mainly symptomatic but the first targeted therapies are being tested. Conversely, chronic pain remains one of the greatest unresolved medical challenges, and the genes and mechanisms associated with pain loss offer new targets for analgesics. Given the progress that has been made, the coming years are promising both in terms of targeted treatments for pain loss disorders and the development of innovative pain medicines based on knowledge of these genetic diseases.

The Thousand Polish Genomes-A Database of Polish Variant Allele Frequencies

Although Slavic populations account for over 4.5% of world inhabitants, no centralised, open-source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for clinical genetics, biomedical research, as well as archeological and historical studies. The Polish population, which is homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a genetic reference for the Slavic nations. In this study, we analysed whole genomes of 1222 Poles to identify and genotype a wide spectrum of genomic variation, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups, and de novo variants. Common variant analyses showed that the Polish cohort is highly homogenous and shares ancestry with other European populations. In rare variant analyses, we identified 32 autosomal-recessive genes with significantly different frequencies of pathogenic alleles in the Polish population as compared to the non-Finish Europeans, including C2, TGM5, NUP93, C19orf12, and PROP1. The allele frequencies for small and structural variants, calculated for 1076 unrelated individuals, are released publicly as The Thousand Polish Genomes database, and will contribute to the worldwide genomic resources available to researchers and clinicians.

National Genome Initiatives in Europe and the United Kingdom in the Era of Whole-Genome Sequencing: A Comprehensive Review

Identification of genomic variability in population plays an important role in the clinical diagnostics of human genetic diseases. Thanks to rapid technological development in the field of massive parallel sequencing technologies, also known as next-generation sequencing (NGS), complex genomic analyses are now easier and cheaper than ever before, which consequently leads to more effective utilization of these techniques in clinical practice. However, interpretation of data from NGS is still challenging due to several issues caused by natural variability of DNA sequences in human populations. Therefore, development and realization of projects focused on description of genetic variability of local population (often called "national or digital genome") with a NGS technique is one of the best approaches to address this problem. The next step of the process is to share such data via publicly available databases. Such databases are important for the interpretation of variants with unknown significance or (likely) pathogenic variants in rare diseases or cancer or generally for identification of pathological variants in a patient's genome. In this paper, we have compiled an overview of published results of local genome sequencing projects from United Kingdom and Europe together with future plans and perspectives for newly announced ones.

Personalized genetic counseling for Stargardt disease: Offspring risk estimates based on variant severity

Recurrence risk calculations in autosomal recessive diseases are complicated when the effect of genetic variants and their population frequencies and penetrances are unknown. An example of this is Stargardt disease (STGD1), a frequent recessive retinal disease caused by bi-allelic pathogenic variants in ABCA4. In this cross-sectional study, 1,619 ABCA4 variants from 5,579 individuals with STGD1 were collected and categorized by (1) severity based on statistical comparisons of their frequencies in STGD1-affected individuals versus the general population, (2) their observed versus expected homozygous occurrence in STGD1-affected individuals, (3) their occurrence in combination with established mild alleles in STGD1-affected individuals, and (4) previous functional and clinical studies. We used the sum allele frequencies of these severity categories to estimate recurrence risks for offspring of STGD1-affected individuals and carriers of pathogenic ABCA4 variants. The risk for offspring of an STGD1-affected individual with the "severe|severe" genotype or a "severe|mild with complete penetrance" genotype to develop STGD1 at some moment in life was estimated at 2.8%-3.1% (1 in 36-32 individuals) and 1.6%-1.8% (1 in 62-57 individuals), respectively. The risk to develop STGD1 in childhood was estimated to be 2- to 4-fold lower: 0.68%-0.79% (1 in 148-126) and 0.34%-0.39% (1 in 296-252), respectively. In conclusion, we established personalized recurrence risk calculations for STGD1-affected individuals with different combinations of variants. We thus propose an expanded genotype-based personalized counseling to appreciate the variable recurrence risks for STGD1-affected individuals. This represents a conceptual breakthrough because risk calculations for STGD1 may be exemplary for many other inherited diseases.

Qatar Genome: Insights on Genomics from the Middle East

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is under-represented in the human genome variation databases. Here we describe insights from phase 1 of the Qatar Genome Program with whole genome sequenced 6,047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighbouring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history and genetic contributions to health and diseases in diverse populations. This article is protected by copyright. All rights reserved.

Detection of sexually antagonistic transmission distortions in trio datasets

Sexual dimorphisms are widespread in animals and plants, for morphological as well as physiological traits. Understanding the genetic basis of sexual dimorphism and its evolution is crucial for understanding biological differences between the sexes. Genetic variants with sex‐antagonistic effects on fitness are expected to segregate in populations at the early phases of sexual dimorphism emergence. Detecting such variants is notoriously difficult, and the few genome‐scan methods employed so far have limited power and little specificity. Here, we propose a new framework to detect a signature of sexually antagonistic (SA) selection. We rely on trio datasets where sex‐biased transmission distortions can be directly tracked from parents to offspring, and identify signals of SA transmission distortions in genomic regions. We report the genomic location of six candidate regions detected in human populations as potentially under sexually antagonist selection. We find an enrichment of genes associated with embryonic development within these regions. Last, we highlight two candidate regions for SA selection in humans.

Identifying the Steps Required to Effectively Implement Next-Generation Sequencing in Oncology at a National Level in Europe

Next-generation sequencing (NGS) may enable more focused and highly personalized cancer treatment, with the National Comprehensive Cancer Network and European Society for Medical Oncology guidelines now recommending NGS for daily clinical practice for several tumor types. However, NGS implementation, and therefore patient access, varies across Europe; a multi-stakeholder collaboration is needed to establish the conditions required to improve this discrepancy. In that regard, we set up European Alliance for Personalised Medicine (EAPM)-led expert panels during the first half of 2021, including key stakeholders from across 10 European countries covering medical, economic, patient, industry, and governmental expertise. We describe the outcomes of these panels in order to define and explore the necessary conditions for NGS implementation into routine clinical care to enable patient access, identify specific challenges in achieving them, and make short- and long-term recommendations. The main challenges identified relate to the demand for NGS tests (governance, clinical standardization, and awareness and education) and supply of tests (equitable reimbursement, infrastructure for conducting and validating tests, and testing access driven by evidence generation). Recommendations made to resolve each of these challenges should aid multi-stakeholder collaboration between national and European initiatives, to complement, support, and mutually reinforce efforts to improve patient care.

Accurate Prediction of Protein Sequences for Proteogenomics Data Integration

This book chapter discusses proteogenomics data integration and provides an overview into the different omics layer involved in defining the proteome of a living organism. Various aspects of genome variability affecting either the sequence or abundance level of proteins are discussed in this book chapter, such as the effect of single-nucleotide variants or larger genomic structural variants on the proteome. Next, various sequencing technologies are introduced and discussed from a proteogenomics data integration perspective such as those providing short- and long-read sequencing and listing their respective advantages and shortcomings for accurate protein variant prediction using genomic/transcriptomics sequencing data. Finally, the various bioinformatics tools used to process and analyze DNA/RNA sequencing data are discussed with the ultimate goal of obtaining accurately predicted sample-specific protein sequences that can be used as a drop-in replacement in existing approaches for peptide and protein identification using popular database search engines such as MSFragger, SearchGUI/PeptideShaker.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

Identical twins carry a persistent epigenetic signature of early genome programming

Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.

Revisiting genetic artifacts on DNA methylation microarrays exposes novel biological implications

BACKGROUND

Illumina DNA methylation microarrays enable epigenome-wide analysis vastly used for the discovery of novel DNA methylation variation in health and disease. However, the microarrays' probe design cannot fully consider the vast human genetic diversity, leading to genetic artifacts. Distinguishing genuine from artifactual genetic influence is of particular relevance in the study of DNA methylation heritability and methylation quantitative trait loci. But despite its importance, current strategies to account for genetic artifacts are lagging due to a limited mechanistic understanding on how such artifacts operate.

RESULTS

To address this, we develop and benchmark UMtools, an R-package containing novel methods for the quantification and qualification of genetic artifacts based on fluorescence intensity signals. With our approach, we model and validate known SNPs/indels on a genetically controlled dataset of monozygotic twins, and we estimate minor allele frequency from DNA methylation data and empirically detect variants not included in dbSNP. Moreover, we identify examples where genetic artifacts interact with each other or with imprinting, X-inactivation, or tissue-specific regulation. Finally, we propose a novel strategy based on co-methylation that can discern between genetic artifacts and genuine genomic influence.

CONCLUSIONS

We provide an atlas to navigate through the huge diversity of genetic artifacts encountered on DNA methylation microarrays. Overall, our study sets the ground for a paradigm shift in the study of the genetic component of epigenetic variation in DNA methylation microarrays.

The first insight into the genetic structure of the population of modern Serbia

The complete understanding of the genomic contribution to complex traits, diseases, and response to treatments, as well as genomic medicine application to the well-being of all humans will be achieved through the global variome that encompasses fine-scale genetic diversity. Despite significant efforts in recent years, uneven representation still characterizes genomic resources and among the underrepresented European populations are the Western Balkans including the Serbian population. Our research addresses this gap and presents the first ever targeted sequencing dataset of variants in clinically relevant genes. By measuring population differentiation and applying the Principal Component and Admixture analysis we demonstrated that the Serbian population differs little from other European populations, yet we identified several novel and more frequent variants that appear as its unique genetic determinants. We explored thoroughly the functional impact of frequent variants and its correlation with the health burden of the population of Serbia based on a sample of 144 individuals. Our variants catalogue improves the understanding of genetics of modern Serbia, contributes to research on ancestry, and aids in improvements of well-being and health equity. In addition, this resource may also be applicable in neighboring regions and valuable in worldwide functional analyses of genetic variants in individuals of European descent.

Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.

Next-Generation HLA Sequence Analysis Uncovers Shared Risk Alleles Between Clinically Distinct Forms of Childhood Uveitis

Purpose

Classical alleles of the human leukocyte antigen (HLA) complex have been linked to specific entities of pediatric noninfectious uveitis, yet genetic predisposition encoded by the HLA super-locus across the patient population remains understudied.

Methods

We performed next-generation full-length sequencing of HLA-A, HLA-B, HLA-C, HLA-DPB1, HLA-DQB1, and HLA-DRB1 in 280 cases. Dense genotype data from 499 Dutch controls from Genome of the Netherlands were imputed using an HLA-specific reference panel (n = 5225 samples from European ancestry). Cases and controls were compared using logistic regression models adjusting for sex.

Results

In total, 179 common and rare alleles were detected. Considering all cases and controls, HLA-DQB1*04:02 and HLA-DRB1*08:01 were identified as the principal HLA association, which was mainly driven by 92 cases with juvenile idiopathic arthritis-associated uveitis (JIA-U). The HLA-DQB1*04:02-HLA-DRB1*08:01 haplotype was also the primary association for the phenotypically similar idiopathic chronic anterior uveitis without arthritis (CAU). Also, HLA-DQB1*05:03 was an independent risk allele for CAU, but not in JIA-U. Analysis of 185 cases with other forms of uveitis revealed HLA-wide associations (P < 2.79 × 10⁻⁴) for HLA-DRB1*01:02, HLA-DRB1*04:03, and HLA-DQB1*05:03, which could be primarily attributed to cases with panuveitis. Finally, amino acid substitution modeling revealed that aspartic acid at position 57 that distinguishes the risk allele HLA-DQB1*05:03 (for CAU and panuveitis) from nonrisk alleles, significantly increased the binding capacity of naturally presented ligands to HLA-DQ.

Conclusions

These results uncovered novel shared HLA associations among clinically distinct phenotypes of pediatric uveitis and highlight genetic predisposition affecting the antigen presentation pathway.

Familial Occurrence of Adult Granulosa Cell Tumors: Analysis of Whole-Genome Germline Variants

Simple Summary

Although granulosa cell tumors can occur in rare syndromes and one familial case of a granulosa cell tumor has been described, a genetic predisposition for granulosa cell tumors has not been identified. Through our collaborations with patients, we identified four families in which two women of each family were diagnosed with an adult granulosa cell tumor. Although predicted deleterious variants in PIK3C2G, BMP5, and LRP2 were found, we could not identify an overlapping genetic variant or affected locus that may explain a genetic predisposition for granulosa cell tumors. The age of onset in the familial patients was significantly lower (median 38 years, range from 17 to 60) than in sporadic patients (median between 50 and 55 years). Furthermore, breast cancer, polycystic ovary syndrome, and subfertility were seen in these families.

Abstract

Adult granulosa cell tumor (AGCT) is a rare ovarian cancer subtype, with a peak incidence around 50–55 years. Although AGCT can occur in specific syndromes, a genetic predisposition for AGCT has not been identified. The aim of this study is to identify a genetic variant in families with AGCT patients, potentially contributing to tumor evolution. We identified four families, each including two women diagnosed with AGCT. Whole-genome sequencing was performed to identify overlapping germline variants or affected genes. Familial relationship was evaluated using genealogy and genomic analyses. Patient characteristics, medical (family) history, and pedigrees were collected. Findings were compared to a reference group of 33 unrelated AGCT patients. Mean age at diagnosis was 38 years (range from 17 to 60) versus 51 years in the reference group, and seven of eight patients were premenopausal. In two families, three first degree relatives were diagnosed with breast cancer. Furthermore, polycystic ovary syndrome (PCOS) and subfertility was reported in three families. Predicted deleterious variants in PIK3C2G, BMP5, and LRP2 were identified. In conclusion, AGCTs occur in families and could potentially be hereditary. In these families, the age of AGCT diagnosis is lower and cases of breast cancer, PCOS, and subfertility are present. We could not identify an overlapping genetic variant or affected locus that may explain a genetic predisposition for AGCT.

Genetic evidence for a large overlap and potential bidirectional causal effects between resilience and well-being

Resilience and well-being are strongly related. People with higher levels of well-being are more resilient after stressful life events or trauma and vice versa. Less is known about the underlying sources of overlap and causality between the constructs. In a sample of 11.304 twins and 2.572 siblings from the Netherlands Twin Register, we investigated the overlap and possible direction of causation between resilience (i.e. the absence of psychiatric symptoms despite negative life events) and well-being (i.e. satisfaction with life) using polygenic score (PGS) prediction, twin-sibling modelling, and the Mendelian Randomization Direction of Causality (MR-DoC) model. Longitudinal twin-sibling models showed significant phenotypic correlations between resilience and well-being (.41/.51 at time 1 and 2). Well-being PGS were predictive for both well-being and resilience, indicating that genetic factors influencing well-being also predict resilience. Twin-sibling modeling confirmed this genetic correlation (0.71) and showed a strong environmental correlation (0.93). In line with causality, both genetic (51%) and environmental (49%) factors contributed significantly to the covariance between resilience and well-being. Furthermore, the results of within-subject and MZ twin differences analyses were in line with bidirectional causality. Additionally, we used the MR-DoC model combining both molecular and twin data to test causality, while correcting for pleiotropy. We confirmed the causal effect from well-being to resilience, with the direct effect of well-being explaining 11% (T1) and 20% (T2) of the variance in resilience. Data limitations prevented us to test the directional effect from resilience to well-being with the MR-DoC model. To conclude, we showed a strong relation between well-being and resilience. A first attempt to quantify the direction of this relationship points towards a bidirectional causal effect. If replicated, the potential mutual effects can have implications for interventions to lower psychopathology vulnerability, as resilience and well-being are both negatively related to psychopathology.

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

BACKGROUND

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.

RESULTS

Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.

CONCLUSIONS

Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.