Performance evaluation of differential splicing analysis methods and splicing analytics platform construction.

A proportion of previously defined benign variants or variants of uncertain significance in humans, which are challenging to identify, may induce an abnormal splicing process. An increasing number of methods have been developed to predict splicing variants, but their performance has not been completely evaluated using independent benchmarks. Here, we manually sourced ∼50 000 positive/negative splicing variants from > 8000 studies and selected the independent splicing variants to evaluate the performance of prediction methods. These methods showed different performances in recognizing splicing variants in donor and acceptor regions, reminiscent of different weight coefficient applications to predict novel splicing variants. Of these methods, 66.67% exhibited higher specificities than sensitivities, suggesting that more moderate cut-off values are necessary to distinguish splicing variants. Moreover, the high correlation and consistent prediction ratio validated the feasibility of integration of the splicing prediction method in identifying splicing variants. We developed a splicing analytics platform called SPCards, which curates splicing variants from publications and predicts splicing scores of variants in genomes. SPCards also offers variant-level and gene-level annotation information, including allele frequency, non-synonymous prediction and comprehensive functional information. SPCards is suitable for high-throughput genetic identification of splicing variants, particularly those located in non-canonical splicing regions.

SLIT2 Rare Sequencing Variants Identified in Idiopathic Hypogonadotropic Hypogonadism.

INTRODUCTION: Idiopathic hypogonadotropic hypogonadism (IHH) is a rare reproductive disorder resulting from gonadotropin-releasing hormone (GnRH) deficiency. However, in only approximately half of patients with IHH is it possible to identify a likely molecular diagnosis. Mice lacking Slit2 have a reduced number or altered patterning of GnRH neurons in the brain. In order to assess the contribution of SLIT2 to IHH, we carried out a candidate gene burden test analysis. METHODS: A total of 196 IHH probands and 2,362 ethic-matched controls were recruited for this study. The IHH probands and controls were subjected to whole-exome sequencing. In the IHH patients with SLIT2 variants and their available family members, detailed phenotyping and segregation analysis were performed. RESULTS: Nine heterozygous SLIT2 rare sequencing variants (RSVs) were identified in 13 probands, with a prevalence of 6.6%. Furthermore, we identified an increased mutational burden for SLIT2 in this cohort (odds ratio = 2.2, p = 0.021). The segregation analysis of available IHH families revealed that the majority of SLIT2 RSVs were inherited from unaffected or partially affected parents. CONCLUSION: Our study suggests SLIT2 as a new IHH-associated gene and expands the clinical and genetic spectrum of IHH. Furthermore, SLIT2 alone does not appear to be sufficient to cause the disorder, and it may interact with other IHH-associated genes to induce a clinical phenotype.

Profiling the Genome-Wide Landscape of Short Tandem Repeats by Long-Read Sequencing.

Background: Short tandem repeats (STRs) are highly variable elements that play a pivotal role in multiple genetic diseases and the regulation of gene expression. Long-read sequencing (LRS) offers a potential solution to genome-wide STR analysis. However, characterizing STRs in human genomes using LRS on a large population scale has not been reported. Methods: We conducted the large LRS-based STR analysis in 193 unrelated samples of the Chinese population and performed genome-wide profiling of STR variation in the human genome. The repeat dynamic index (RDI) was introduced to evaluate the variability of STR. We sourced the expression data from the Genotype-Tissue Expression to explore the tissue specificity of highly variable STRs related genes across tissues. Enrichment analyses were also conducted to identify potential functional roles of the high variable STRs. Results: This study reports the large-scale analysis of human STR variation by LRS and offers a reference STR database based on the LRS dataset. We found that the disease-associated STRs (dSTRs) and STRs associated with the expression of nearby genes (eSTRs) were highly variable in the general population. Moreover, tissue-specific expression analysis showed that those highly variable STRs related genes presented the highest expression level in brain tissues, and enrichment pathways analysis found those STRs are involved in synaptic function-related pathways. Conclusion: Our study profiled the genome-wide landscape of STR using LRS and highlighted the highly variable STRs in the human genome, which provide a valuable resource for studying the role of STRs in human disease and complex traits.

Performance comparison of computational methods for the prediction of the function and pathogenicity of non-coding variants.

Non-coding variants in the human genome significantly influence human traits and complex diseases via their regulation and modification effects. Hence, an increasing number of computational methods are developed to predict the effects of variants in human non-coding sequences. However, it is difficult for inexperienced users to select appropriate computational methods from dozens of available methods. To solve this issue, we assessed 12 performance metrics of 24 methods on four independent non-coding variant benchmark datasets: (1) rare germline variants from clinical relevant sequence variants (ClinVar), (2) rare somatic variants from catalogue of somatic mutations in cancer (COSMIC), (3) common regulatory variants from curated expression quantitative trait loci (eQTL) data, and (4) disease-associated common variants from curated genome-wide association studies (GWAS). All 24 tested methods performed differently under various conditions, indicating varying strengths and weaknesses under different scenarios. Importantly, the performance of existing methods was acceptable for rare germline variants from ClinVar with the area under the curve (AUC) of 0.4481-0.8033 and poor for rare somatic variants from COSMIC (AUC: 0.4984-0.7131), common regulatory variants from curated eQTL data (AUC: 0.4837-0.6472), and disease-associated common variants from curated GWAS (AUC: 0.4766-0.5188). We also compared the prediction performance of 24 methods for non-coding de novo mutations in autism spectrum disorder and found that the combined annotation-dependent depletion (CADD) and context-dependent tolerance score (CDTS) methods showed better performance. Summarily, we assessed the performance of 24 computational methods under diverse scenarios, providing preliminary advice for proper tool selection, guiding the development of new techniques in interpreting non-coding variants.

Cross-Disorder Analysis of De Novo Mutations in Neuropsychiatric Disorders.

The clinical similarity among different neuropsychiatric disorders (NPDs) suggested a shared genetic basis. We catalogued 23,109 coding de novo mutations (DNMs) from 6511 patients with autism spectrum disorder (ASD), 4,293 undiagnosed developmental disorder (UDD), 933 epileptic encephalopathy (EE), 1022 intellectual disability (ID), 1094 schizophrenia (SCZ), and 3391 controls. We evaluated that putative functional DNMs contribute to 38.11%, 34.40%, 33.31%, 10.98% and 6.91% of patients with ID, EE, UDD, ASD and SCZ, respectively. Consistent with phenotype similarity and heterogeneity in different NPDs, they show different degree of genetic association. Cross-disorder analysis of DNMs prioritized 321 candidate genes (FDR < 0.05) and showed that genes shared in more disorders were more likely to exhibited specific expression pattern, functional pathway, genetic convergence, and genetic intolerance.

Evaluating the role of ARSA in Chinese patients with Parkinson's disease.

Recent studies have suggested ARSA, a gene responsible for metachromatic leukodystrophy, could be a genetic modifier of Parkinson's disease (PD) pathogenesis, acting as a molecular chaperone for α-synuclein. To elucidate the role of ARSA variants in PD, we did a comprehensive analysis of ARSA variants by performing next-generation sequencing on 477 PD families, 1440 sporadic early-onset PD patients and 1962 sporadic late-onset PD patients and 2636 controls from Chinese mainland, as well as the association between ARSA variants and cognitive function of PD patients. We identified 2 familial PD following autosomal dominant inherence carrying rare variants of ARSA, but they had limited clinical significance. We detected a total of 81 coding variants of ARSA in our subjects but none of the identified variants were associated with either susceptibility or cognitive performance of PD, while loss-of-function variants showed slightly increased burden in late-onset PD (0.25% vs. 0%, p = 0.08). Our results suggested ARSA may not play important roles in PD of Chinese population.

Genetic landscape of human mitochondrial genome using whole-genome sequencing.

Increasing evidences suggest that mitochondrial dysfunction is implicated in diseases and aging, and whole-genome sequencing (WGS) is the most unbiased method in analyzing the mitochondrial genome (mtDNA). However, the genetic landscape of mtDNA in the Chinese population has not been fully examined. Here, we described the genetic landscape of mtDNA using WGS data from Chinese individuals (n = 3241). We identified 3892 mtDNA variants, of which 3349 (86%) were rare variants. Interestingly, we observed a trend toward extreme heterogeneity of mtDNA variants. Our study observed a distinct purifying selection on mtDNA, which inhibits the accumulation of harmful heteroplasmies at the individual level: (1) mitochondrial dN/dS ratios were much <1; (2) the dN/dS ratio of heteroplasmies was higher than homoplasmies; (3) heteroplasmies had more indels and predicted deleterious variants than homoplasmies. Furthermore, we found that haplogroup M (20.27%) and D (20.15%) had the highest frequencies in the Chinese population, followed by B (18.51%) and F (16.45%). The number of variants per individual differed across haplogroup groups, with a higher number of homoplasmies for the M lineage. Meanwhile, mtDNA copy number was negatively correlated with age but positively correlated with the female sex. Finally, we developed an mtDNA variation database of Chinese populations called MTCards (http://genemed.tech/mtcards/) to facilitate the query of mtDNA variants in this study. In summary, these findings contribute to different aspects of understanding mtDNA, providing a better understanding of the genetic basis of mitochondrial-related diseases.

Combination Therapy of the Active KRAS-Targeting Antibody inRas37 and a PI3K Inhibitor in Pancreatic Cancer.

KRAS activating mutations, which are present in more than 90% of pancreatic cancers, drive tumor dependency on the RAS/mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/AKT signaling pathways. Therefore, combined targeting of RAS/MAPK and PI3K/AKT signaling pathways may be required for optimal therapeutic effect in pancreatic cancer. However, the therapeutic efficacy of combined MAPK and PI3K/AKT signaling target inhibitors is unsatisfactory in pancreatic cancer treatment, because it is often accompanied by MAPK pathway reactivation by PI3K/AKT inhibitor. Therefore, we developed an inRas37 antibody, which directly targets the intra-cellularly activated GTP-bound form of oncogenic RAS mutation and investigated its synergistic effect in the presence of the PI3K inhibitor BEZ-235 in pancreatic cancer. In this study, inRas37 remarkably increased the drug response of BEZ-235 to pancreatic cancer cells by inhibiting MAPK reactivation. Moreover, the co-treatment synergistically inhibited cell proliferation, migration, and invasion and exhibited synergistic anticancer activity by inhibiting the MAPK and PI3K pathways. The combined administration of inRas37and BEZ-235 significantly inhibited tumor growth in mouse models. Our results demonstrated that inRas37 synergistically increased the antitumor activity of BEZ-235 by inhibiting MAPK reactivation, suggesting that inRas37 and BEZ-235 co-treatment could be a potential treatment approach for pancreatic cancer patients with KRAS mutations.

The Association Between Lysosomal Storage Disorder Genes and Parkinson's Disease: A Large Cohort Study in Chinese Mainland Population.

Background: Recent years have witnessed an increasing number of studies indicating an essential role of the lysosomal dysfunction in Parkinson's disease (PD) at the genetic, biochemical, and cellular pathway levels. In this study, we investigated the association between rare variants in lysosomal storage disorder (LSD) genes and Chinese mainland PD. Methods: We explored the association between rare variants of 69 LSD genes and PD in 3,879 patients and 2,931 controls from Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) using next-generation sequencing, which were analyzed by using the optimized sequence kernel association test. Results: We identified the significant burden of rare putative LSD gene variants in Chinese mainland patients with PD. This association was robust in familial or sporadic early-onset patients after excluding the GBA variants but not in sporadic late-onset patients. The burden analysis of variant sets in genes of LSD subgroups revealed a suggestive significant association between variant sets in genes of sphingolipidosis deficiency disorders and familial or sporadic early-onset patients. In contrast, variant sets in genes of sphingolipidoses, mucopolysaccharidoses, and post-translational modification defect disorders were suggestively associated with sporadic late-onset patients. Then, SMPD1 and other four novel genes (i.e., GUSB, CLN6, PPT1, and SCARB2) were suggestively associated with sporadic early-onset or familial patients, whereas GALNS and NAGA were suggestively associated with late-onset patients. Conclusion: Our findings supported the association between LSD genes and PD and revealed several novel risk genes in Chinese mainland patients with PD, which confirmed the importance of lysosomal mechanisms in PD pathogenesis. Moreover, we identified the genetic heterogeneity in early-onset and late-onset of patients with PD, which may provide valuable suggestions for the treatment.

ANGPTL4 accelerates KRASG12D-Induced acinar to ductal metaplasia and pancreatic carcinogenesis.

Oncogenic KRASG12D induces neoplastic transformation of pancreatic acinar cells through acinar-to-ductal metaplasia (ADM) and pancreatic intraepithelial neoplasia (PanIN), and drives pancreatic ductal adenocarcinoma (PDAC). Angiopoietin-like 4 (ANGPTL4) is known to be involved in the regulation of cancer growth and metastasis. However, whether ANGPTL4 affects KRASG12D-mediated ADM and early PDAC intervention remains unknown. In the current study, we investigated the role of ANGPTL4 in KRASG12D-induced ADM, PanIN formation, and PDAC maintenance. We found that ANGPTL4 was highly expressed in human and mouse ADM lesions and contributed to the promotion of KRASG12D-driven ADM in mice. Consistently, ANGPTL4 rapidly induced ADM in three-dimensional culture of acinar cells with KRAS mutation and formed ductal cysts that silenced acinar genes and activated ductal genes, which are characteristic of in vivo ADM/PanIN lesions. We also found that periostin works as a downstream regulator of ANGPTL4-mediated ADM/PDAC. Genetic ablation of periostin diminished the ADM/PanIN phenotype induced by ANGPTL4. A high correlation between ANGPTL4 and periostin was confirmed in human samples. These results demonstrate that ANGPTL4 is critical for ADM/PanIN initiation and PDAC progression through the regulation of periostin. Thus, the ANGPTL4/periostin axis is considered a potential target for ADM-derived PDAC.

Gene4PD: A Comprehensive Genetic Database of Parkinson's Disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is no database that integrate different type of genetic data, and support analyzing of PD-associated genes (PAGs). By systematic review and curation of multiple lines of public studies, we integrate multiple layers of genetic data (rare variants and copy-number variants identified from patients with PD, associated variants identified from genome-wide association studies, differentially expressed genes, and differential DNA methylation genes) and age at onset in PD. We integrated five layers of genetic data (8302 terms) with different levels of evidences from more than 3,000 studies and prioritized 124 PAGs with strong or suggestive evidences. These PAGs were identified to be significantly interacted with each other and formed an interconnected functional network enriched in several functional pathways involved in PD, suggesting these genes may contribute to the pathogenesis of PD. Furthermore, we identified 10 genes were associated with a juvenile-onset (age ≤ 30 years), 11 genes were associated with an early-onset (age of 30-50 years), whereas another 10 genes were associated with a late-onset (age > 50 years). Notably, the AAOs of patients with loss of function variants in five genes were significantly lower than that of patients with deleterious missense variants, while patients with VPS13C (P = 0.01) was opposite. Finally, we developed an online database named Gene4PD (http://genemed.tech/gene4pd) which integrated published genetic data in PD, the PAGs, and 63 popular genomic data sources, as well as an online pipeline for prioritize risk variants in PD. In conclusion, Gene4PD provides researchers and clinicians comprehensive genetic knowledge and analytic platform for PD, and would also improve the understanding of pathogenesis in PD.

Characterizing the Expression Patterns of Parkinson's Disease Associated Genes.

BACKGROUND: The expression pattern represents a quantitative phenotype that provides an in-depth view of the molecular mechanism in Parkinson's disease (PD); however, the expression patterns of PD-associated genes (PAGs) and their relation to age at onset (AAO) remain unclear. METHODS: The known PD-causing genes and PD-risk genes, which were collected from latest published authoritative meta-analysis, were integrated as PAGs. The expression data from Genotype-Tissue Expression database, Allen Brian Map database, and BrainSpan database, were extracted to characterize the tissue specificity, inhibitory-excitatory neuron expression profile, and spatio-temporal expression pattern of PAGs, respectively. The AAO information of PD-causing gene was download from Gene4PD and MDSgene database. RESULTS: We prioritized 107 PAGs and found that the PAGs were more likely to be expressed in brain-related tissues than non-brain tissues and that more PAGs had higher expression levels in excitatory neurons than inhibitory neurons. In addition, we identified two spatio-temporal expression modules of PAGs in human brain: the first module showed a higher expression level in the adult period than in the prenatal period, and the second module showed the opposite features. It showed that more PAGs belong to the first module that the second module. Furthermore, we found that the median AAO of patients with mutations in PD-causing genes of the first module was lower than that of the second module. CONCLUSION: In conclusion, this study provided comprehensive landscape of expression patterns, AAO features and their relationship for the first time, improving the understanding of pathogenesis, and precision medicine in PD.

GPCards: An integrated database of genotype-phenotype correlations in human genetic diseases.

Genotype-phenotype correlations are the basis of precision medicine of human genetic diseases. However, it remains a challenge for clinicians and researchers to conveniently access detailed individual-level clinical phenotypic features of patients with various genetic variants. To address this urgent need, we manually searched for genetic studies in PubMed and catalogued 8,309 genetic variants in 1,288 genes from 17,738 patients with detailed clinical phenotypic features from 1,855 publications. Based on genotype-phenotype correlations in this dataset, we developed an user-friendly online database called GPCards (http://genemed.tech/gpcards/), which not only provided the association between genetic diseases and disease genes, but also the prevalence of various clinical phenotypes related to disease genes and the patient-level mapping between these clinical phenotypes and genetic variants. To accelerate the interpretation of genetic variants, we integrated 62 well-known variant-level and gene-level genomic data sources, including functional predictions, allele frequencies in different populations, and disease-related information. Furthermore, GPCards enables automatic analyses of users' own genetic data, comprehensive annotation, prioritization of candidate functional variants, and identification of genotype-phenotype correlations using custom parameters. In conclusion, GPCards is expected to accelerate the interpretation of genotype-phenotype correlations, subtype classification, and candidate gene prioritisation in human genetic diseases.

De novo mutations in folate-related genes associated with common developmental disorders.

Folate deficiency is an environmental risk factor for several developmental disorders. De novo mutations (DNMs) also play important etiological roles in various developmental disorders. However, it remains unclear whether DNMs in folate-related genes (FRGs) contribute to developmental disorders. We obtained a list of 1,821 FRGs from folate metabolism pathways and the Comparative Toxicogenomics Database, along with data concerning DNMs in 15,404 cases and 3,391 controls from the Gene4Denovo database. We used a TADA-Denovo model to prioritize candidate disease-associated FRGs, and characterized these genes in terms of genic intolerance, functional networks, and expression patterns. Compared with the controls, FRGs were significantly enriched in likely damaging DNMs (ldDNMs) in patients with developmental disorders (1.54 ≤ odds ratio ≤ 3.39, P adj ≤ 0.0075). Furthermore, FRGs with ldDNMs rather than with likely non-damaging DNMs (lndDNMs) overlapped significantly among the five developmental disorders included in the datasets. The TADA-Denovo model prioritized 96 candidate disease-associated FRGs, which were intolerant to genetic variants. Their functional networks mainly involved pathways associated with chromatin modification, organ development, and signal transduction pathways. DNMT3A, KMT2B, KMT2C, and YY1 emerged as hub FRGs from the protein-protein interaction network. These candidate disease-associated FRGs are preferentially expressed in the excitatory neurones during embryonic development, and in the cortex, cerebellum, striatum, and amygdala during foetal development. Overall, these findings show that DNMs in FRGs are associated with the risk of developmental disorders. Further research on these DNMs may facilitate the discovery of developmental disorder biomarkers and therapeutic targets, enabling detailed, personalized, and precise folate treatment plan.

Intracellular KRAS-specific antibody enhances the anti-tumor efficacy of gemcitabine in pancreatic cancer by inducing endosomal escape.

KRAS mutation is associated with the progression and growth of pancreatic cancer and contributes to chemo-resistance, which poses a significant clinical challenge in pancreatic cancer. Here, we developed a RT22-ep59 antibody (Ab) that directly targets the intracellularly activated GTP-bound form of oncogenic KRAS mutants after it is internalized into cytosol by endocytosis through tumor-associated receptor of extracellular epithelial cell adhesion molecule (EpCAM) and investigated its synergistic anticancer effects in the presence of gemcitabine in pancreatic cancer. We first observed that RT22-ep59 specifically recognized tumor-associated EpCAM and reached the cytosol by endosomal escape. In addition, the anticancer effect of RT22-ep59 was observed in the high-EpCAM-expressing pancreatic cancer cells and gemcitabine-resistant pancreatic cancer cells, but it had little effect on the low-EpCAM-expressing pancreatic cancer cells. Additionally, co-treatment with RT22-ep59 and gemcitabine synergistically inhibited cell viability, migration, and invasion in 3D-cultures and exhibited synergistic anticancer activity by inhibiting the RAF/ERK or PI3K/AKT pathways in cells with high-EpCAM expression. In an orthotopic mouse model, combined administration of RT22-ep59 and gemcitabine significantly inhibited tumor growth. Furthermore, the co-treatment suppressed cancer metastasis by blocking EMT signaling in vitro and in vivo. Our results demonstrated that RT22-ep59 synergistically increased the antitumor activity of gemcitabine by inhibiting RAS signaling by specifically targeting KRAS. This indicates that co-treatment with RT22-ep59 and gemcitabine might be considered a potential therapeutic strategy for pancreatic cancer patients harboring KRAS mutation.

No relationship between SRY variants and risk of Parkinson's disease in Chinese population.

Parkinson's disease (PD) is a common neurodegenerative disease with inherent sex differences, and sex-determining region Y (SRY) is a gene located in the Y chromosome which encodes a transcription factor involving the regulation of the dopamine system. In this study, we investigated whether SRY variants were associated with PD in Chinese population. A total of 2058 male patients with PD and 1650 male control participants were recruited, and variants in SRY transcript and flanking regions were genotyped by whole-exome sequencing or whole-genome sequencing. Analysis of rare variants by the optimal sequence kernel association test showed no difference in variant burden of coding, 5'-noncoding and 3'-noncoding between the case and control group. In addition, of the 6 common variants identified, none showed a significant effect in altering PD risk in our population using logistic regression. Our results suggested SRY variants were not associated with the risk of PD in Chinese population.

Functional relationships between recessive inherited genes and genes with de novo variants in autism spectrum disorder.

BACKGROUND: Both de novo variants and recessive inherited variants were associated with autism spectrum disorder (ASD). This study aimed to use exome data to prioritize recessive inherited genes (RIGs) with biallelically inherited variants in autosomes or X-linked inherited variants in males and investigate the functional relationships between RIGs and genes with de novo variants (DNGs). METHODS: We used a bioinformatics pipeline to analyze whole-exome sequencing data from 1799 ASD quads (containing one proband, one unaffected sibling, and their parents) from the Simons Simplex Collection and prioritize candidate RIGs with rare biallelically inherited variants in autosomes or X-linked inherited variants in males. The relationships between RIGs and DNGs were characterized based on different genetic perspectives, including genetic variants, functional networks, and brain expression patterns. RESULTS: Among the biallelically or hemizygous constrained genes that were expressed in the brain, ASD probands carried significantly more biallelically inherited protein-truncating variants (PTVs) in autosomes (p = 0.038) and X-linked inherited PTVs in males (p = 0.026) than those in unaffected siblings. We prioritized eight autosomal, and 13 X-linked candidate RIGs, including 11 genes already associated with neurodevelopmental disorders. In total, we detected biallelically inherited variants or X-linked inherited variants of these 21 candidate RIGs in 26 (1.4%) of 1799 probands. We then integrated previously reported known or candidate genes in ASD, ultimately obtaining 70 RIGs and 87 DNGs for analysis. We found that RIGs were less likely to carry multiple recessive inherited variants than DNGs were to carry multiple de novo variants. Additionally, RIGs and DNGs were significantly co-expressed and interacted with each other, forming a network enriched in known functional ASD clusters, although RIGs were less likely to be enriched in these functional clusters compared with DNGs. Furthermore, although RIGs and DNGs presented comparable expression patterns in the human brain, RIGs were less likely to be associated with prenatal brain regions, the middle cortical layers, and excitatory neurons than DNGs. LIMITATIONS: The RIGs analyzed in this study require functional validation, and the results should be replicated in more patients with ASD. CONCLUSIONS: ASD RIGs were functionally associated with DNGs; however, they exhibited higher heterogeneity than DNGs.