Abstract Background As clinical genetics evolves towards the broader field of clinical genomics, the diagnostic approach to rare diseases is undergoing a paradigm shift. This transformation has significantly impacted rare disease diagnostics, increasingly done through gene panels, whole exome and whole genome sequencing. To advance beyond genomics into precision medicine and encompass the breadth of relevant clinical scenarios, a true systems shift is required that challenges conventional barriers and enables the formation of cross-disciplinary, integrated environments. Methods The Genomic Medicine Center Karolinska Rare Diseases (GMCK-RD) has, for the past 10 years, brought together healthcare and academia to enable large-scale genome sequencing in a clinical diagnostics context. Within GMCK-RD, experts from various medical disciplines collaborate closely with clinical geneticists, bioinformaticians, and researchers to integrate genome sequencing into healthcare. Results In total, 15 644 individuals with suspected rare diseases were analyzed using clinical genome sequencing, including pediatric (48%), adult (48%) and fetal (4%) samples. The overall diagnostic yield was 22.6%, providing a diagnosis for 3 538 individuals with variants in 1 570 genes. Moreover, a rare disease analysis tool suite developed and validated in house includes a bioinformatic pipeline allowing for comprehensive data analysis covering a wide range of genetic variants including SNVs, INDELs, repeat expansions, uniparental disomies, balanced and unbalanced structural variants as well as insertions of mobile elements. Results are visualized and interpreted in custom-developed decision support systems functioning as an interpretation portal as well as a knowledge-base to capture the interpretation efforts made in a structured format allowing future secondary use. Conclusions Altogether, GMCK-RD has shifted healthcare in our region towards precision diagnostics. We emphasize the need to transition from traditional clinical genetic diagnostics to a broader clinical genomics approach. Beyond this shift, we advocate integrating genomics with specialized clinical and laboratory medicine, a concept pioneered for inborn errors of metabolism (IEM) with stepwise spread to additional disease groups. In this model, a multidisciplinary unit combines screening, targeted diagnostics, individualized treatment, and long-term patient follow-up. Here we provide a road map and guide for inspiration for centers aiming to implement genome sequencing in rare disease diagnostics.

Introduction:A trio analysis refers to the strategy of exome or genome sequencing of DNA from a patient, as well as parents, in order to identify the genetic cause of a disorder or syndrome. Methods:During the last 10 years, we have successfully applied exome or genome sequencing and performed trio analysis for 1,000 patients. Results:Overall, 39% of the patients were diagnosed, with the detection of causative variant(s). The variants were located in 308 different genes. Autosomal dominant de novo variants were detected in 46% of the solved cases. Detection rates were highest in patients with a syndromic neurodevelopmental disorder (46%) and in patients with known consanguinity (59%). Even for patients previously analyzed as singletons, using a pre-defined gene panel, a consecutive trio analysis resulted in the detection of a causative variant in 30%. Discussion:A major advantage of trio analysis is the immediate identification of de novo variants as well as confirmation of compound heterozygosity. Additionally, inherited variants from a healthy parent can be dismissed as non-disease causing. The trio strategy enables analysis of a high number of genes-or even the whole genome-simultaneously. The strengths of a trio analysis, in combination with analysis of genome sequence data, allows for the detection of a wide range of genetic aberrations. This enables a high diagnostic yield, even in previously analyzed patients. Our current protocol for trio analysis is based on genome sequencing data, which allows for simultaneous detection of single nucleotide variants, insertion/deletions, structural variants, expanded short tandem repeats, as well as a copy number analysis corresponding to an array-CGH, and analysis regarding SMN1 gene copies.

Early vascular aging plays a central role in chronic kidney disease (CKD), but its molecular causes remain unclear. Somatic mutations accumulate in various cells with age, yet their functional contribution to aging tissues is not well understood. Here we found progerin, the protein responsible for the premature aging disease Hutchinson-Gilford progeria syndrome, steadily recurring in vascular smooth muscle cells of patients with CKD. Notably, the most common progeria-causing mutation, LMNA c.1824C>T, was identified as a somatic mutation in CKD arteries. Clusters of proliferative progerin-expressing cells in CKD arteries and in vivo lineage-tracing in mice revealed clonal expansion capacity of mutant cells. Mosaic progerin expression contributed to genomic damage, endoplasmic reticulum stress and senescence in CKD arteries and resulted in vascular aging phenotypes in vivo. These findings suggest that certain somatic mutations may be clonally expanded in the arterial wall, contributing to the disease-related functional decline of the tissue.

Background:Heterozygous variants in CTNND2, encoding the brain-specific protein δ-catenin, are associated with a broad spectrum of neurodevelopmental disorders, including dyslexia, attention deficit hyperactivity disorder, intellectual disability, and autism. Despite its clinical significance, the full phenotypic spectrum of CTNND2-associated disorders and the neurodevelopmental role of δ-catenin, a key component of the cadherin-catenin cell adhesion complex, remain poorly defined. Methods:Through international collaboration, we assembled the phenotypic and molecular information for 57 individuals, 42 previously unpublished, carrying heterozygous CTNND2 variants. All individuals were evaluated by local clinicians, and the variants were identified through exome or genome sequencing, clinical microarray, or karyotyping. To investigate the effects of δ-catenin loss on early neurogenesis, we performed neural differentiation and transcriptomic profiling in three patient-derived neural stem cell lines and three CRISPR-Cas9-generated CTNND2 knockout lines. In one patient-derived line, we further analyzed cerebral organoid development and performed pathway modulation to assess phenotypic rescue. Results:The 41 CTNND2 variants included 12 previously reported loss-of-function- and one missense variant, and 28 novel variants comprising 10 missense and 18 predicted loss-of-function changes. Eight of the novel variants occurred de novo, and 12 were inherited from a parent with a neurodevelopmental phenotype. The most common clinical features were developmental delay (90%), intellectual disability (74%), and behavioral abnormalities (79%). Functional studies revealed impaired early neurogenesis in one patient-derived line, characterized by aberrant neural rosette formation. Transcriptome analysis showed dysregulated WNT signaling, and partial rescue of these defects was achieved by modulating the WNT pathway, highlighting δ-catenin's role in early neural development. Conclusions:This study defines the clinical symptoms of CTNND2-related neurodevelopmental disorders, outlining a recognizable yet variable phenotype that overlaps with other forms of intellectual disability and autism. Our findings provide preliminary evidence of genotype-phenotype correlations and highlight δ-catenin's critical role in modulating WNT signaling during early neural development. These insights advance our understanding of CTNND2-associated disorders and support the importance of mechanistic studies to inform personalized diagnostics and therapies.

We aimed to describe the clinical characteristics of families with heritable TP53-related cancer (hTP53rc) syndrome in Sweden with class 4 and 5 germline TP53 variants (gTP53), and to evaluate the genotype-phenotype correlation. These results were also used to evaluate our previously published phenotype prediction model based on TP53 missense variants and their impact on protein conformation. 90 families with hTP53rc were initially identified in Sweden. After variant reclassification using the TP53-specific ACMG criteria, 83 families remained (176 carriers) to harbour a pathogenic (class 5) or likely pathogenic (class 4) variant in TP53. Of these, 112 carriers (64%) had a previous history of cancer, and 35 (31%) had developed more than one primary tumour. 16% of the families met the stricter criteria for Classic Li-Fraumeni syndrome, 45% the updated Chompret criteria, 35% for hereditary breast cancer (HBC), and the remaining 5% were classified as “Others”. We identified 42 different gTP53 variants of which 22 were missense. The most frequently observed variant was the missense c.542 G > A, p.R181H identified in 14/29 (48%) of HBC families. Fifteen of the 20 informative missense variants (75%) were phenotypically predicted correctly using our previously published in silico prediction model. The TP53 p.R181H was identified as a common Swedish variant predominantly associated with an HBC phenotype. Apart from this variant, there were no significant genotype-phenotype correlations. Therefore, due to phenotypic overlap it is still too early to stratify surveillance programme for different TP53-carriers.

Aging is associated with a progressive decline in tissue function and regenerative capacity, partly due to genomic instability, one of the hallmarks of aging1,2. Genomic instability encompasses DNA damage and the accumulation of somatic mutations in post-zygotic cells, yet the specific impact of these mutations on age-related tissue dysfunction remains poorly understood. To address this, we developed a mouse model in which genomic instability was induced specifically in muscle progenitor cells3 through targeted deletion of the Msh2 (ref. 4) and Blm5 genes. This allowed us to assess how elevated DNA damage and somatic mutations, from single-nucleotide variants (SNVs) to structural variants, affect muscle regeneration following injury. These mice exhibited impaired muscle regeneration, characterized by smaller muscle fibers, reduced muscle mass gain and decreased grip strength. Importantly, similar muscle deficits were observed in a second mouse model where somatic mutations were elevated with less substantial DNA damage. These findings provide evidence that the accumulation of somatic mutations can potentially compromise the function of somatic cells, contributing to the aging phenotype in skeletal muscle.

Genome-wide association studies [GWAS] have identified a limited number of endometrial cancer risk loci by analyzing single nucleotide polymorphisms [SNPs]. We hypothesized that analyzing haplotypes rather than SNPs could provide novel and more detailed information on genetic cancer susceptibility loci. To examine the association of a SNP or haplotype with endometrial cancer risk we performed a two-stage haplotype GWAS. The discovery GWAS included a sub-cohort of 1,116 Swedish endometrial cancer cases and 5,021 controls from previously published GWAS data. A sliding window analysis was employed with window sizes of 1-25 SNPs using a logistic regression model. The Swedish haplotype analysis identified 15 novel candidate risk loci (2q31.1, 4p16.1, 4p15.31, 6q13, 7p21.1, 9p13.3, 10q26.3, 11q21, 12q13.11, 13q12.11, 15q13.3, 16q24.3, 19q13.32, 20p12.3 and 22q13.2) with OR ranging from 1.6 to 3.3 and p-values from 4.25 × 10 −8 to 9.86 × 10 −15 . A second replication haplotype analysis of the Swedish novel loci was performed using two cohorts from Belgium and Germany. In spite of small sample sizes in the replication cohorts, there was still support for most loci with positive ORs. In addition, the findings in the two European cohorts motivates further studies to search for founder haplotypes. These novel findings suggested that endometrial cancer loci, identified through haplotype analysis, conferred a higher risk compared to previous single-variant GWAS.

IntroductionNeuromuscular disorders (NMDs) have a heterogeneous etiology. A genetic diagnosis is key to personalized healthcare and access to targeted treatment for the affected individuals.MethodsIn this study, 861 patients with NMDs were analyzed with genome sequencing and comprehensive variant calling including single nucleotide variants, small insertions/deletions (SNVs/INDELs), and structural variants (SVs) in a panel of 895 NMD genes, as well as short tandem repeat expansions (STRs) at 28 loci. In addition, for unsolved cases with an unspecific clinical presentation, the analysis of a panel with OMIM disease genes was added.ResultsIn the cohort, 27% (232/861) of the patients harbored pathogenic variants, of which STRs and SVs accounted for one-third of the patients (71/232). The variants were found in 107 different NMD genes. Furthermore, 18 pediatric patients harbored pathogenic variants in non-NMD genes.DiscussionOur results highlight that for children with unspecific hypotonia, a genome-wide analysis rather than a disease-based gene panel should be considered as a diagnostic approach. More importantly, our results clearly show that it is crucial to include STR- and SV-analyses in the diagnostics of patients with neuromuscular disorders.

INTRODUCTION:Distinguishing paracentric inversions (PAIs) from chromosomal insertions has traditionally relied on fluorescent in situ hybridization (FISH) techniques, but recent advancements in high-throughput sequencing have enabled the use of genome sequencing for such differentiation. In this study, we present a 38-year-old male carrier of a paracentric inversion on chromosome 2q, inv (2)(q31.2q34), whose partner experienced recurrent miscarriages. MATERIAL AND METHODS:FISH analysis confirmed the inversion, and genome sequencing was employed for detailed characterization. RESULTS:Preimplantation genetic testing (PGT) revealed that all assessed embryos were balanced, consistent with the low risk of unbalanced offspring associated with PAIs. While PAI carriers traditionally exhibit low risk of producing unbalanced offspring, exceptions exist due to crossover events within the inversion loop. Although the sample size was limited, the findings align with existing sperm study data, supporting the rare occurrence of unbalanced progeny in PAI carriers. CONCLUSIONS:This study highlights the possibility of characterizing PAIs using genome sequencing to enable correct reproductive counseling and PGT decisions. Detailed characterization of a PAI is crucial for understanding potential outcomes and guiding PGT strategies, as accurate knowledge of the inversion size is essential for appropriate method selection in PGT. Given the very low risk of unbalanced offspring in PAI carriers, routine PGT may not be warranted but should be considered in specific cases with a history of unbalanced progeny or recurrent miscarriages. This study contributes to our understanding of PAI segregation and its implications for reproductive outcomes.

To describe the phenotype of a novel form of autosomal dominant episodic nystagmus and to identify the potential genetic aetiology. We identified several individuals in a large Swedish family affected by episodic nystagmus. In total, 39 family members from five generations were invited to participate in the study, of which 17 were included (12 affected and 5 unaffected). The phenotype of the nystagmus was described based on data collected from family members through questionnaires, interviews, clinical examinations and from video recordings of ongoing episodes of nystagmus. Whole genome sequencing (WGS) and further Sanger sequencing for segregation of the identified candidate variants was performed in eight participants (six affected and two unaffected). The 12 affected participants showed a phenotype with episodic nystagmus of early onset. A vertical jerk nystagmus with variable amplitude and frequency was characterized in the analysed video material. No other eye pathology or other disease that could explain the episodic nystagmus was identified among the family participants. Genetic analysis identified a missense variant (p.Ser375Phe) in the gene FRMD5, which segregated with the disease in the eight individuals analysed, from three generations. We describe a novel autosomal dominant form of early onset episodic nystagmus and suggest the FRMD5 gene as a strong candidate gene for this disorder.

PURPOSE:Individuals with intellectual disability (ID) and/or neurodevelopment disorders (NDDs) are currently investigated with several different approaches in clinical genetic diagnostics.METHODS:We compared the results from 3 diagnostic pipelines in patients with ID/NDD: genome sequencing (GS) first (N = 100), GS as a secondary test (N = 129), or chromosomal microarray (CMA) with or without FMR1 analysis (N = 421).RESULTS:The diagnostic yield was 35% (GS-first), 26% (GS as a secondary test), and 11% (CMA/FMR1). Notably, the age of diagnosis was delayed by 1 year when GS was performed as a secondary test and the cost per diagnosed individual was 36% lower with GS first than with CMA/FMR1. Furthermore, 91% of those with a negative result after CMA/FMR1 analysis (338 individuals) have not yet been referred for additional genetic testing and remain undiagnosed.CONCLUSION:Our findings strongly suggest that genome analysis outperforms other testing strategies and should replace traditional CMA and FMR1 analysis as a first-line genetic test in individuals with ID/NDD. GS is a sensitive, time- and cost-effective method that results in a confirmed molecular diagnosis in 35% of all referred patients.

BACKGROUND:Prostate cancer is the most prevalent cancer in men worldwide. It is a polygenic disease with a substantial proportion of heritability. Identification of novel candidate biomarkers is crucial for clinical cancer prevention and the development of therapeutic strategies. Here, we describe the analysis of rare and common genetic variants that can predispose to the development of prostate cancer. METHODS:Whole-genome sequencing was performed on germline DNA of five Swedish siblings which were diagnosed with prostate cancer. The high-risk variants were identified setting the minor allele frequency < 0.01, CADD > 10 and if tested in PRACTICAL, OR > 1.5, while the low-risk variants were identified minor allele frequency > 0.01, CADD > 10 and if tested in PRACTICAL, OR > 1.1. RESULTS:We identified 38 candidate high-risk gene variants and 332 candidate low-risk gene variants, where 2 and 14 variants were in coding regions, respectively, that were shared by the brothers with prostate cancer. CONCLUSIONS:This study expanded the knowledge of potential risk factor candidates involved in hereditary and familial prostate cancer. Our findings can be beneficial when applying targeted screening in families with a high risk of developing the disease.

(1) Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility. (2) Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1–25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls. (3) Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 × 10−8), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2–25 and 113 risk haplotypes of window size 50 at p < 5 × 10−8 on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68. (4) Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.

Breast cancer is the most prevalent malignancy among women worldwide and hereditary breast cancer (HBC) accounts for about 5–10% of the cases. Today, the most recurrent genes known are BRCA1 and BRCA2, accounting for around 25% of familial cases. Although thousands of loss-of-function variants in more than twenty predisposing genes have been found, the majority of familial cases of HBC remain unexplained. The aim of this study was to identify new predisposing genes for HBC in three non-BRCA families with autosomal dominant inheritance pattern using whole-exome sequencing and functional prediction tools. No pathogenic variants in known hereditary cancer-related genes could explain the breast cancer susceptibility in these families. Among 2122 exonic variants with maximum minor allele frequency (MMAF) < 0.1%, between 17–35 variants with combined annotation-dependent depletion (CADD) > 20 segregated with disease in the three analyzed families. Selected candidate genes, i.e., UBASH3A, MYH13, UTP11L, and PAX7, were further evaluated using protein expression analysis but no alterations of cancer-related pathways were observed. In conclusion, identification of new high-risk cancer genes using whole-exome sequencing has been more challenging than initially anticipated, in spite of selected families with pronounced family history of breast cancer. A combination of low- and intermediate-genetic-risk variants may instead contribute the breast cancer susceptibility in these families.

Identifying genetic cancer risk factors will lead to improved genetic counseling, cancer prevention and cancer care. Analyzing families with a strong history of breast cancer (BC) has been a successful method to identify genes that contribute to the disease. This has led to discoveries of high-risk genes like the BRCA-genes. Nevertheless, many BC incidences are of unknown causes. In this study, exome sequencing on 59 BC patients from 24 Swedish families with a strong history of BC was performed to identify variants in known and novel BC predisposing genes. First, we screened known BC genes and identified two pathogenic variants in the BRIP1 and PALB2 genes. Secondly, to identify novel BC genes, rare and high impact variants and segregating in families were analyzed to identify 544 variants in novel BC candidate genes. Of those, 22 variants were defined as high-risk variants. Several interesting genes, either previously linked with BC or in pathways that when flawed could contribute to BC, were among the detected genes. The strongest candidates identified are the FANCM gene, involved in DNA double-strand break repair, and the RAD54L gene, involved in DNA recombination. Our study shows identifying pathogenic variants is challenging despite a strong family history of BC. Several interesting candidates were observed here that need to be further studied.

Identifying new candidate colorectal cancer (CRC) genes and mutations are important for clinical cancer prevention as well as in cancer care. Genetic counseling is already implemented for known high-risk variants; however, the majority of CRC are of unknown causes. In our study, 110 CRC patients in 55 Swedish families with a strong history of CRC but unknown genetic causes were analyzed with the aim of identifying novel candidate CRC predisposing genes. Exome sequencing was used to identify rare and high-impact variants enriched in the families. No clear pathogenic variants were found in known CRC predisposing genes; however, potential pathogenic variants in novel CRC predisposing genes were identified. Over 3000 variants with minor allele frequency (MAF) <0.01 and Combined Annotation Dependent Depletion (CADD) > 20 were seen aggregating in the CRC families. Of those, 27 variants with MAF < 0.001 and CADD>25 were considered high-risk mutations. Interestingly, more than half of the high-risk variants were detected in three families, suggesting cumulating contribution of several variants to CRC. In summary, our study shows that despite a strong history of CRC within families, identifying pathogenic variants is challenging. In a small number of families, few rare mutations were shared by affected family members. This could indicate that in the absence of known CRC predisposing genes, a cumulating contribution of mutations leads to CRC observed in these families.

To search for colorectal cancer (CRC) risk loci, Swedish samples were used for a genome‐wide haplotype analysis. A logistic regression model was employed in 2663 CRC cases and 1642 controls in the discovery analysis. Three analyses were done, on all, familial‐, and nonfamilial CRC samples and only results with odds ratio (OR) > 1 were analyzed. single nucleotide polymorphism (SNP) analysis did not generate any statistically significant results. Haplotype analysis suggested novel loci, on chromosome 2q36.1 (OR = 1.71, p value = 5.6924 × 10−8) in all CRC samples, chromosome 1q43 (OR = 4.04 p value = 3.24 × 10−8) in familial CRC samples, and two hits in nonfamilial CRC samples, chromosomes 2q36.1 (OR = 1.71 p value = 5.69 × 10−8) and 3p24.3 (OR = 1.62 p value = 6.21 × 10−9). Moreover, one locus on chromosome 20q13.33 was suggested in analyses of all samples, and five more novel loci were suggested on chromosomes 10q25.3, 15q,22.31, 17p11.2, 1p34.2, and 3q24. The haplotypes from the analysis of all samples were replicated in a second study of CRC cases and controls from the same part of Sweden. In summary, using haplotype analysis in Swedish CRC samples, the best hits were novel loci and the locus on chromosomes 2q36.1 and 20q13.33 suggested in the analysis of all samples were confirmed in a second cohort. The ORs were often higher than ORs from published genome‐wide association study (GWAS). The study suggested it was possible that a risk locus could involve more than one gene, and that haplotypes could give information on the gene or genes possibly involved in the risk at specific locus.

Abstract Background and Aims The genome of every cell accumulates somatic mutations while aging. Somatic mutation data can be used to track a cell´s exposure to mutagens, thereby allowing the discovery of cell types that are more susceptible to mutate and become cancer and the underling mechanisms. Method To detect somatic mutations in healthy, human kidney, we set up a protocol for whole genome DNA sequencing of single non-cancer cells. The protocol requires in vitro clonal expansion prior to sequencing, a step that restricts the analysis to cells able to proliferate in vitro (progenitors), but allows a gene expression analysis in addition to genome sequencing. Cells were obtained from six living kidney donors undergoing surgery. In addition to the kidney cortex biopsy, multiple control tissues (skin, subcutaneous fata and visceral fat) were obtained from each donor, allowing a well-controlled comparison of mutation landscapes in different cell types. Donors´ age spanned from 30 to 69. Results Somatic mutation and gene expression data showed that we were able to culture two different populations of CD133/CD24 positive, tubular cells. One population showed a low amount of somatic mutations and a mutation profile similar to progenitors from other tissues (fat, skeletal muscle and blood), consistent with a lack of exposure to mutagens. Conversely, the other population showed high mutation burden and a unique mutation landscape, characterized by mutation enrichment in active chromatin, regulatory, and transcribed regions. Accumulation of potential, cancer-driver mutations was 6-fold faster in these compared to control cells. The mutation profile was similar to that of the most common kidney cancer subtypes (clear cell- and papillary cell-carcinoma) and indicated that these cells originated from the proximal tubule, in agreement with gene expression data. Conclusion Our somatic mutation data from single genomes support the existence of two different populations of proliferating tubule cells in healthy, human kidney. One is protected from mutagen exposure, similar to stem cells from other organs. The other population is derived from damaged proximal tubule cells and shows a high mutation rate between 30 and 70 years of age. Mutations are enriched in transcribed genes and regulatory regions, thus enhancing the chances of tumorigenic transformation and suggesting conditions that predispose to cancer in the kidney proximal tubule.