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.

Annotation of uORFs in the OMIM genes allows to reveal pathogenic variants in 5'UTRs.

An increasing number of studies emphasize the role of non-coding variants in the development of hereditary diseases. However, the interpretation of such variants in clinical genetic testing still remains a critical challenge due to poor knowledge of their pathogenicity mechanisms. It was previously shown that variants in 5'-untranslated regions (5'UTRs) can lead to hereditary diseases due to disruption of upstream open reading frames (uORFs). Here, we performed a manual annotation of upstream translation initiation sites (TISs) in human disease-associated genes from the OMIM database and revealed ∼4.7 thousand of TISs related to uORFs. We compared our TISs with the previous studies and provided a list of 'high confidence' uORFs. Using a luciferase assay, we experimentally validated the translation of uORFs in the ETFDH, PAX9, MAST1, HTT, TTN,GLI2 and COL2A1 genes, as well as existence of N-terminal CDS extension in the ZIC2 gene. Besides, we created a tool to annotate the effects of genetic variants located in uORFs. We revealed the variants from the HGMD and ClinVar databases that disrupt uORFs and thereby could lead to Mendelian disorders. We also showed that the distribution of uORFs-affecting variants differs between pathogenic and population variants. Finally, drawing on manually curated data, we developed a machine-learning algorithm that allows us to predict the TISs in other human genes.

Gene Expression Analysis of Yeast Strains with a Nonsense Mutation in the eRF3-Coding Gene Highlights Possible Mechanisms of Adaptation.

In yeast Saccharomyces cerevisiae, there are two translation termination factors, eRF1 (Sup45) and eRF3 (Sup35), which are essential for viability. Previous studies have revealed that presence of nonsense mutations in these genes leads to amplification of mutant alleles (sup35-n and sup45-n), which appears to be necessary for the viability of such cells. However, the mechanism of this phenomenon remained unclear. In this study, we used RNA-Seq and proteome analysis to reveal the complete set of gene expression changes that occur during cellular adaptation to the introduction of the sup35-218 nonsense allele. Our analysis demonstrated significant changes in the transcription of genes that control the cell cycle: decreases in the expression of genes of the anaphase promoting complex APC/C (APC9, CDC23) and their activator CDC20, and increases in the expression of the transcription factor FKH1, the main cell cycle kinase CDC28, and cyclins that induce DNA biosynthesis. We propose a model according to which yeast adaptation to nonsense mutations in the translation termination factor genes occurs as a result of a delayed cell cycle progression beyond the G2-M stage, which leads to an extension of the S and G2 phases and an increase in the number of copies of the mutant sup35-n allele.

The Landscape of Point Mutations in Human Protein Coding Genes Leading to Pregnancy Loss.

Pregnancy loss is the most frequent complication of a pregnancy which is devastating for affected families and poses a significant challenge for the health care system. Genetic factors are known to play an important role in the etiology of pregnancy loss; however, despite advances in diagnostics, the causes remain unexplained in more than 30% of cases. In this review, we aggregated the results of the decade-long studies into the genetic risk factors of pregnancy loss (including miscarriage, termination for fetal abnormality, and recurrent pregnancy loss) in euploid pregnancies, focusing on the spectrum of point mutations associated with these conditions. We reviewed the evolution of molecular genetics methods used for the genetic research into causes of pregnancy loss, and collected information about 270 individual genetic variants in 196 unique genes reported as genetic cause of pregnancy loss. Among these, variants in 18 genes have been reported by multiple studies, and two or more variants were reported as causing pregnancy loss for 57 genes. Further analysis of the properties of all known pregnancy loss genes showed that they correspond to broadly expressed, highly evolutionary conserved genes involved in crucial cell differentiation and developmental processes and related signaling pathways. Given the features of known genes, we made an effort to construct a list of candidate genes, variants in which may be expected to contribute to pregnancy loss. We believe that our results may be useful for prediction of pregnancy loss risk in couples, as well as for further investigation and revealing genetic etiology of pregnancy loss.

Plasma microRNA Profiling in Type 2 Diabetes Mellitus: A Pilot Study.

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease characterized by insulin resistance and ß-cell dysfunction and leading to many micro- and macrovascular complications. In this study we analyzed the circulating miRNA expression profiles in plasma samples from 44 patients with T2D and 22 healthy individuals using next generation sequencing and detected 229 differentially expressed miRNAs. An increased level of miR-5588-5p, miR-125b-2-3p, miR-1284, and a reduced level of miR-496 in T2D patients was verified. We also compared the expression landscapes in the same group of patients depending on body mass index and identified differential expression of miR-144-3p and miR-99a-5p in obese individuals. Identification and functional analysis of putative target genes was performed for miR-5588-5p, miR-125b-2-3p, miR-1284, and miR-496, showing chromatin modifying enzymes and apoptotic genes being among the significantly enriched pathways.

Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery.

BACKGROUND: Accurate variant detection in the coding regions of the human genome is a key requirement for molecular diagnostics of Mendelian disorders. Efficiency of variant discovery from next-generation sequencing (NGS) data depends on multiple factors, including reproducible coverage biases of NGS methods and the performance of read alignment and variant calling software. Although variant caller benchmarks are published constantly, no previous publications have leveraged the full extent of available gold standard whole-genome (WGS) and whole-exome (WES) sequencing datasets. RESULTS: In this work, we systematically evaluated the performance of 4 popular short read aligners (Bowtie2, BWA, Isaac, and Novoalign) and 9 novel and well-established variant calling and filtering methods (Clair3, DeepVariant, Octopus, GATK, FreeBayes, and Strelka2) using a set of 14 "gold standard" WES and WGS datasets available from Genome In A Bottle (GIAB) consortium. Additionally, we have indirectly evaluated each pipeline's performance using a set of 6 non-GIAB samples of African and Russian ethnicity. In our benchmark, Bowtie2 performed significantly worse than other aligners, suggesting it should not be used for medical variant calling. When other aligners were considered, the accuracy of variant discovery mostly depended on the variant caller and not the read aligner. Among the tested variant callers, DeepVariant consistently showed the best performance and the highest robustness. Other actively developed tools, such as Clair3, Octopus, and Strelka2, also performed well, although their efficiency had greater dependence on the quality and type of the input data. We have also compared the consistency of variant calls in GIAB and non-GIAB samples. With few important caveats, best-performing tools have shown little evidence of overfitting. CONCLUSIONS: The results show surprisingly large differences in the performance of cutting-edge tools even in high confidence regions of the coding genome. This highlights the importance of regular benchmarking of quickly evolving tools and pipelines. We also discuss the need for a more diverse set of gold standard genomes that would include samples of African, Hispanic, or mixed ancestry. Additionally, there is also a need for better variant caller assessment in the repetitive regions of the coding genome.

Structure and Polymorphism of Amyloid and Amyloid-Like Aggregates.

Amyloids are protein aggregates with the cross-ß structure. The interest in amyloids is explained, on the one hand, by their role in the development of socially significant human neurodegenerative diseases, and on the other hand, by the discovery of functional amyloids, whose formation is an integral part of cellular processes. To date, more than a hundred proteins with the amyloid or amyloid-like properties have been identified. Studying the structure of amyloid aggregates has revealed a wide variety of protein conformations. In the review, we discuss the diversity of protein folds in the amyloid-like aggregates and the characteristic features of amyloid aggregates that determine their unusual properties, including stability and interaction with amyloid-specific dyes. The review also describes the diversity of amyloid aggregates and its significance for living organisms.

Direct proof of the amyloid nature of yeast prions [PSI+] and [PIN+] by the method of immunoprecipitation of native fibrils.

Prions are proteins that can exist in several structurally and functionally distinct states, one or more of which is transmissible. Yeast proteins Sup35 and Rnq1 in prion state ([PSI+] and [PIN+], respectively) form oligomers and aggregates, which are transmitted from parents to offspring in a series of generations. Several pieces of indirect evidence indicate that these aggregates also possess amyloid properties, but their binding to amyloid-specific dyes has not been shown in vivo. Meanwhile, it is the specific binding to the Congo Red dye and birefringence in polarized light after such staining that is considered the gold standard for proving the amyloid properties of a protein. Here, we used immunoprecipitation to extract native fibrils of the Sup35 and Rnq1 proteins from yeast strains with different prion status. These fibrils are detected by electron microscopy, stained with Congo Red and exhibit yellow-green birefringence after such staining. All these data show that the Sup35 and Rnq1 proteins in prion state form amyloid fibrils in vivo. The technology of fibrils extraction in combination with standard cytological methods can be used to identify new pathological and functional amyloids in any organism and to analyze the structural features of native amyloid fibrils.

Quantitative assessment of chaperone binding to amyloid aggregates identifies specificity of Hsp40 interaction with yeast prion fibrils.

Yeast self-perpetuating protein aggregates (yeast prions) provide a framework to investigate the interaction of misfolded proteins with the protein quality control machinery. The major component of this system that facilitates propagation of all known yeast amyloid prions is the Hsp104 chaperone that catalyzes fibril fragmentation. Overproduction of Hsp104 cures some yeast prions via a fragmentation-independent mechanism. Importantly, major cytosolic chaperones of the Hsp40 group, Sis1 and Ydj1, oppositely affect yeast prion propagation, and are capable of stimulating different activities of Hsp104. In this work, we developed a quantitative method to investigate the Hsp40 binding to amyloid aggregates. We demonstrate that Sis1 binds fibrils formed by the Sup35NM protein with higher affinity compared to Ydj1. Moreover, the interaction of Sis1 with the fibrils formed by the other yeast prion protein, Rnq1, is orders of magnitude weaker. We show that the deletion of the dimerization domain of Sis1 (crucial for the curing of [PSI+] by excess Hsp104) decreases its affinity to both Sup35NM and Rnq1 fibrils. Taken together, these results suggest that tight binding of Hsp40 to the amyloid fibrils is likely to enhance aggregate malpartition instead of fibril fragmentation.

A Data-Driven Review of the Genetic Factors of Pregnancy Complications.

Over the recent years, many advances have been made in the research of the genetic factors of pregnancy complications. In this work, we use publicly available data repositories, such as the National Human Genome Research Institute GWAS Catalog, HuGE Navigator, and the UK Biobank genetic and phenotypic dataset to gain insights into molecular pathways and individual genes behind a set of pregnancy-related traits, including the most studied ones-preeclampsia, gestational diabetes, preterm birth, and placental abruption. Using both HuGE and GWAS Catalog data, we confirm that immune system and, in particular, T-cell related pathways are one of the most important drivers of pregnancy-related traits. Pathway analysis of the data reveals that cell adhesion and matrisome-related genes are also commonly involved in pregnancy pathologies. We also find a large role of metabolic factors that affect not only gestational diabetes, but also the other traits. These shared metabolic genes include IGF2, PPARG, and NOS3. We further discover that the published genetic associations are poorly replicated in the independent UK Biobank cohort. Nevertheless, we find novel genome-wide associations with pregnancy-related traits for the FBLN7, STK32B, and ACTR3B genes, and replicate the effects of the KAZN and TLE1 genes, with the latter being the only gene identified across all data resources. Overall, our analysis highlights central molecular pathways for pregnancy-related traits, and suggests a need to use more accurate and sophisticated association analysis strategies to robustly identify genetic risk factors for pregnancy complications.

To CURe or not to CURe? Differential effects of the chaperone sorting factor Cur1 on yeast prions are mediated by the chaperone Sis1.

Yeast self-perpetuating protein aggregates (prions) provide a convenient model for studying various components of the cellular protein quality control system. Molecular chaperones and chaperone-sorting factors, such as yeast Cur1 protein, play key role in proteostasis via tight control of partitioning and recycling of misfolded proteins. In this study, we show that, despite the previously described ability of Cur1 to antagonize the yeast prion [URE3], it enhances propagation and phenotypic manifestation of another prion, [PSI+ ]. We demonstrate that both curing of [URE3] and enhancement of [PSI+ ] in the presence of excess Cur1 are counteracted by the cochaperone Hsp40-Sis1 in a dosage-dependent manner, and show that the effect of Cur1 on prions parallels effects of the attachment of nuclear localization signal to Sis1, indicating that Cur1 acts on prions via its previously reported ability to relocalize Sis1 from the cytoplasm to nucleus. This shows that the direction in which Cur1 influences a prion depends on how this specific prion responds to relocalization of Sis1.

Differential effects of chaperones on yeast prions: CURrent view.

Endogenous yeast amyloids that control heritable traits and are frequently used as models for human amyloid diseases are termed yeast prions. Yeast prions, including the best studied ones ([PSI +] and [URE3]), propagate via intimate interactions with molecular chaperones. Different yeast prions exhibit differential responses to changes in levels, functionality or localization of the components of chaperone machinery. Here, we provide additional data confirming differential effects of chaperones (and specifically, Hsp40s) on yeast prions and summarize current knowledge of the mechanisms underlying chaperone specificities. Contrary to frequent statements in literature, overproduction of the Hsp104 chaperone antagonizes both [PSI +] and [URE3] prions, while overproduction of the Hsp70-Ssa1 chaperone antagonizes [URE3] prion only in some, but not in all strains. Recently, we demonstrated that the relocalization of a fraction of the Hsp40 chaperone Sis1 from the cytosol to the nucleus by the chaperone-sorting factor Cur1 exhibits opposite effects on [PSI +] and [URE3] prions. We suggest that the response of prions to changes in Sis1 localization represents a combination of the effects of Sis1 shortage on fragmentation of prion aggregates and on malpartition of prion aggregates during a cell division. Differences in sensitivity of prion fragmentation to Sis1 and in relative inputs of fragmentation and malpartition in prion propagation result in opposite effects of Sis1 relocalization on [PSI +] and [URE3].

Catching hidden variation: systematic correction of reference minor allele annotation in clinical variant calling.

PurposeWe comprehensively assessed the influence of reference minor alleles (RMAs), one of the inherent problems of the human reference genome sequence.MethodsThe variant call format (VCF) files provided by the 1000 Genomes and Exome Aggregation Consortium (ExAC) consortia were used to identify RMA sites. All coding RMA sites were checked for concordance with UniProt and the presence of same codon variants. RMA-corrected predictions of functional effect were obtained with SIFT, PolyPhen-2, and PROVEAN standalone tools and compared with dbNSFP v2.9 for consistency.ResultsWe systematically characterized the problem of RMAs and identified several possible ways in which RMA could interfere with accurate variant discovery and annotation. We have discovered a systematic bias in the automated variant effect prediction at the RMA loci, as well as widespread switching of functional consequences for variants located in the same codon as the RMA. As a convenient way to address the problem of RMAs we have developed a simple bioinformatic tool that identifies variation at RMA sites and provides correct annotations for all such substitutions. The tool is available free of charge at http://rmahunter.bioinf.me.ConclusionCorrection of RMA annotation enhances the accuracy of next-generation sequencing-based methods in clinical practice.

SFP1-mediated prion-dependent lethality is caused by increased Sup35 aggregation and alleviated by Sis1.

[PSI+ ] is the prion form of the translation termination factor Sup35 (eRF3); [PSI+ ] strains display nonsense suppression. Another prion-like element, [ISP+ ], is linked to antisuppression in a specific background. Transcriptional regulator Sfp1 was shown to be responsible for [ISP+ ] propagation. In this work, we identified SFP1 as a multicopy inducer of [PSI+ ]-dependent lethality. Sfp1 is likely to up-regulate transcription of genes encoding release factors; however, its overproduction increases Sup35, but not Sup45 protein level. Using the synthetic lethality test, we compared the effects of SFP1 and SUP35 over-expression on the viability of [PSI+ ] strains. Together with an observation that Sfp1 overproduction leads to an increased accumulation of Sup35 in [PSI+ ] aggregates, we suggest that excess Sfp1 causes [PSI+ ] toxicity. Even though SUP45 over-expression is known to compensate for the [PSI+ ]-dependent lethality, it fails to do so when the lethality is caused by SFP1 over-expression. We discovered that the increased levels of Hsp40 chaperone Sis1 alleviate prion toxicity caused by either SFP1 or SUP35 over-expression and revert back to normal distribution of Sup35 between monomers and aggregate fractions. Finally, we showed that Sfp1 partially colocalizes with Sup35 aggregates, which may contribute to another mechanism of Sfp1-derived [PSI+ ] prion toxicity.

Exome sequencing in extreme altitude mountaineers identifies pathogenic variants in RTEL1 and COL6A1 previously associated with respiratory failure.

Adaptation of humans to challenging environmental conditions, such as extreme temperature, malnutrition, or hypoxia, is an interesting phenomenon for both basic and applied research. Identification of the genetic factors contributing to human adaptation to these conditions enhances our understanding of the underlying molecular and physiological mechanisms. In our study, we analyzed the exomes of 22 high altitude mountaineers to uncover genetic variants contributing to hypoxic adaptation. To our surprise, we identified two putative loss-of-function variants, rs1385101139 in RTEL1 and rs1002726737 in COL6A1 in two extremely high altitude (personal record of more than 8500 m) professional climbers. Both variants can be interpreted as pathogenic according to medical geneticists' guidelines, and are linked to inherited conditions involving respiratory failure (late-onset pulmonary fibrosis and severe Ullrich muscular dystrophy for rs1385101139 and rs1002726737, respectively). Our results suggest that a loss of gene function may act as an important factor of human adaptation, which is corroborated by previous reports in other human subjects.

Current Status and Prospects of the Single-Cell Sequencing Technologies for Revealing the Pathogenesis of Pregnancy-Associated Disorders.

Single-cell RNA sequencing (scRNA-seq) is a method that focuses on the analysis of gene expression profile in individual cells. This method has been successfully applied to answer the challenging questions of the pathogenesis of multifactorial diseases and open up new possibilities in the prognosis and prevention of reproductive diseases. In this article, we have reviewed the application of scRNA-seq to the analysis of the various cell types and their gene expression changes in normal pregnancy and pregnancy complications. The main principle, advantages, and limitations of single-cell technologies and data analysis methods are described. We discuss the possibilities of using the scRNA-seq method for solving the fundamental and applied tasks related to various pregnancy-associated disorders. Finally, we provide an overview of the scRNA-seq findings for the common pregnancy-associated conditions, such as hyperglycemia in pregnancy, recurrent pregnancy loss, preterm labor, polycystic ovary syndrome, and pre-eclampsia.

bioGWAS: A Simple and Flexible Tool for Simulating GWAS Datasets.

Genome-wide association studies (GWAS) have proven to be a powerful tool for the identification of genetic susceptibility loci affecting human complex traits. In addition to pinpointing individual genes involved in a particular trait, GWAS results can be used to discover relevant biological processes for these traits. The development of new tools for extracting such information from GWAS results requires large-scale datasets with known biological ground truth. Simulation of GWAS results is a powerful method that may provide such datasets and facilitate the development of new methods. In this work, we developed bioGWAS, a simple and flexible pipeline for the simulation of genotypes, phenotypes, and GWAS summary statistics. Unlike existing methods, bioGWAS can be used to generate GWAS results for simulated quantitative and binary traits with a predefined set of causal genetic variants and/or molecular pathways. We demonstrate that the proposed method can recapitulate complete GWAS datasets using a set of reported genome-wide associations. We also used our method to benchmark several tools for gene set enrichment analysis for GWAS data. Taken together, our results suggest that bioGWAS provides an important set of functionalities that would aid the development of new methods for downstream processing of GWAS results.

Statistical Dissection of the Genetic Determinants of Phenotypic Heterogeneity in Genes with Multiple Associated Rare Diseases.

Phenotypicheterogeneity is a phenomenon in which distinct phenotypes can develop in individuals bearing pathogenic variants in the same gene. Genetic factors, gene interactions, and environmental factors are usually considered the key mechanisms of this phenomenon. Phenotypic heterogeneity may impact the prognosis of the disease severity and symptoms. In our work, we used publicly available data on the association between genetic variants and Mendelian disease to investigate the genetic factors (such as the intragenic localization and type of a variant) driving the heterogeneity of gene-disease relationships. First, we showed that genes linked to multiple rare diseases (GMDs) are more constrained and tend to encode more transcripts with high levels of expression across tissues. Next, we assessed the role of variant localization and variant types in specifying the exact phenotype for GMD variants. We discovered that none of these factors is sufficient to explain the phenomenon of such heterogeneous gene-disease relationships. In total, we identified only 38 genes with a weak trend towards significant differences in variant localization and 30 genes with nominal significant differences in variant type for the two associated disorders. Remarkably, four of these genes showed significant differences in both tests. At the same time, our analysis suggests that variant localization and type are more important for genes linked to autosomal dominant disease. Taken together, our results emphasize the gene-level factors dissecting distinct Mendelian diseases linked to one common gene based on open-access genetic data and highlight the importance of exploring other factors that contributed to phenotypic heterogeneity.

Russian Regional Differences in Allele Frequencies of CFTR Gene Variants: Genetic Monitoring of Infertile Couples.

A male factor, commonly associated with poor semen quality, is revealed in about 50% of infertile couples. CFTR gene (Cystic Fibrosis Transmembrane Conduction Regulator) variants are one of the common genetic causes of azoospermia-related male infertility. Notably, the spectrum and frequency of pathogenic CFTR variants vary between populations and geographical regions. In this work, we made an attempt to evaluate the allele frequency (AF) of 12 common CFTR variants in infertile Russian men and healthy individuals from different districts of Russia. Because of the limited number of population-based studies on Russian individuals, we characterized the population AFs based on data from the Registry of Russian cystic fibrosis (CF) patients. In addition to the CF patient registry, we estimated the local frequencies of the same set of variants based on the results of genotyping of CF patients in local biocollections (from St. Petersburg and Yugra regions). AFs of common CFTR variants calculated based on registry and biocollection data showed good concordance with directly measured population AFs. The estimated region-specific frequencies of CFTR variants allowed us to uncover statistically significant regional differences in the frequencies of the F508del (c.1521_1523del; p.Phe508del) and CFTRdele2,3(21kb) (c.54-5940_273+10250del21kb; p.Ser18ArgfsX) variants. The data from population-based studies confirmed previous observations that F508del, CFTRdele2,3(21kb), and L138ins (c.413_415dup; p.Leu138dup)variants are the most abundant among infertile patients, and their frequencies are significantly lower in healthy individuals and should be taken into account during genetic monitoring of the reproductive health of Russian individuals.

Altered Sphingolipid Hydrolase Activities and Alpha-Synuclein Level in Late-Onset Schizophrenia.

Recent data described that patients with lysosomal storage disorders (LSDs) may have clinical schizophrenia (SCZ) features. Disruption of lipid metabolism in SCZ pathogenesis was found. Clinical features of schizophrenia (SCZ) have been demonstrated in patients with several lysosomal storage disorders (LSDs). Taking into account the critical role of lysosomal function for neuronal cells' lysosomal dysfunction could be proposed in SCZ pathogenesis. The current study analyzed lysosomal enzyme activities and the alpha-synuclein level in the blood of patients with late-onset SCZ. In total, 52 SCZ patients with late-onset SCZ, 180 sporadic Parkinson's disease (sPD) patients, and 176 controls were recruited. The enzymatic activity of enzymes associated with mucopolysaccharidosis (alpha-L-Iduronidase (IDUA)), glycogenosis (acid alpha-glucosidase (GAA)) and sphingolipidosis (galactosylceramidase (GALC), glucocerebrosidase (GCase), alpha-galactosidase (GLA), acid sphingomyelinase (ASMase)) and concentration of lysosphingolipids (hexosylsphingosine (HexSph), globotriaosylsphingosine (LysoGb3), and lysosphingomyelin (LysoSM)) were measured using LC-MS/MS. The alpha-synuclein level was estimated in magnetically separated CD45+ blood cells using the enzyme-linked immunosorbent assay (ELISA). Additionally, NGS analysis of 11 LSDs genes was conducted in 21 early-onset SCZ patients and 23 controls using the gene panel PGRNseq-NDD. Decreased ASMase, increased GLA activities, and increased HexSpn, LysoGb3, and LysoSM concentrations along with an accumulation of the alpha-synuclein level were observed in late-onset SCZ patients in comparison to the controls (p < 0.05). Four rare deleterious variants among LSDs genes causing mucopolysaccharidosis type I (IDUA (rs532731688, rs74385837) and type III (HGSNAT (rs766835582)) and sphingolipidosis (metachromatic leukodystrophy (ARSA (rs201251634)) were identified in five patients from the group of early-onset SCZ patients but not in the controls. Our findings supported the role of sphingolipid metabolism in SCZ pathogenesis. Aberrant enzyme activities and compounds of sphingolipids associated with ceramide metabolism may lead to accumulation of alpha-synuclein and may be critical in SCZ pathogenesis.