Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations

Transcription factor 3 is dysregulated in megakaryocytes in myelofibrosis

Transcription factor 3 (TCF3) is a DNA transcription factor that modulates megakaryocyte development. Although abnormal TCF3 expression has been identified in a range of hematological malignancies, to date, it has not been investigated in myelofibrosis (MF). MF is a Philadelphia-negative myeloproliferative neoplasm (MPN) that can arise de novo or progress from essential thrombocythemia [ET] and polycythemia vera [PV] and where dysfunctional megakaryocytes have a role in driving the fibrotic progression. We aimed to examine whether TCF3 is dysregulated in megakaryocytes in MPN, and specifically in MF. We first assessed TCF3 protein expression in megakaryocytes using an immunohistochemical approach analyses and showed that TCF3 was reduced in MF compared with ET and PV. Further, the TCF3-negative megakaryocytes were primarily located near trabecular bone and had the typical "MF-like" morphology as described by the WHO. Genomic analysis of isolated megakaryocytes showed three mutations, all predicted to result in a loss of function, in patients with MF; none were seen in megakaryocytes isolated from ET or PV marrow samples. We then progressed to transcriptomic sequencing of platelets which showed loss of TCF3 in MF. These proteomic, genomic and transcriptomic analyses appear to indicate that TCF3 is downregulated in megakaryocytes in MF. This infers aberrations in megakaryopoiesis occur in this progressive phase of MPN. Further exploration of this pathway could provide insights into TCF3 and the evolution of fibrosis and potentially lead to new preventative therapeutic targets.

Clinical and Genomic Profile of Primary Cranial Neurolymphomatosis

Primary cranial neurolymphomatosis (PCNL) is a rare subtype of primary CNS lymphoma (PCNSL) in which infiltrative lymphomatous involvement is confined to cranial nerves. Here, we report a case of PCNL with successful genomic profiling. A 57-year-old male had a lengthy prediagnostic phase spanning approximately 30 months, characterized by multiple episodes of cranial neuropathies managed by steroids. At the time of diagnosis, the patient had right-sided cranial neuropathies involving cranial nerves (CN) V, VI, and VII. Pathological findings of the right cavernous lesion biopsy were consistent with large B-cell lymphoma-infiltrating nerve fibers. The clinical course was aggressive and refractory, characterized by relentless progression with the development of cervical spinal neurolymphomatosis, cerebrospinal fluid involvement, and ependymal and intraparenchymal cerebral involvement, despite multiple lines of therapy, including chemoimmunotherapy, Bruton's tyrosine kinase inhibitor, radiation, autologous stem cell transplant, chimeric antigen receptor T-cell therapy (CAR-T), and whole-brain radiation. The patient survived for 22 months from the time of the initial diagnosis and 52 months after the first episode of cranial neuropathy. Next-generation sequencing identified mutations (MYD88, CD79b, and PIM1) that are frequently observed in PCNSL. The unusual findings included a total of 22 mutations involving PIM1, indicating a highly active aberrant somatic hypermutation and two missense CXCR4 mutations. CXCR4 mutations have never been described in PCNSL and may have implications for disease biology and therapeutic interventions. We provide a literature review to further elucidate PCNL.

Assessing the Performance of In silico Tools and Molecular Dynamics Simulations for Predicting Pharmacogenetic Variant Impact

The ability of freely available in silico tools to predict the effect of non-synonymous single nucleotide polymorphisms (nsSNPs) in pharmacogenes on protein function is not well defined. We assessed the performance of seven sequence-based (SIFT, PolyPhen2, mutation accessor, FATHMM, PhD-SNP, MutPred2, and SNPs & Go) and five structure-based (mCSM, SDM, DDGun, CupSat, and MAESTROweb) tools in predicting the impact of 118 nsSNPs in the CYP2C19, CYP2C9, CYP2B6, CYP2D6, and DPYD genes with known function (24 normal, one increased, 42 decreased, and 51 no-function). Sequence-based tools had a higher median (IQR) positive predictive value (89% [89-94%] vs. 12% [10-15%], P < 0.001) and lower negative predictive value (30% [24-34%] vs. 90% [80-93%], P < 0.001) than structure-based tools. Accuracy did not significantly differ between sequence-based (59% [37-67%]) and structure-based (34% [23-44%]) tools (P = 0.070). Notably, the no-function CYP2C9*3 allele and decreased function CYP2C9*8 allele were predicted incorrectly as tolerated by 100% of sequenced-based tools and as stabilizing by 60% and 20% of structure-based tools, respectively. As a case study, we performed mutational analysis for the CYP2C9*1, *3 (I359L), and *8 (R150H) proteins through molecular dynamic (MD) simulations using S-warfarin as the substrate. The I359L variant increased the distance of the major metabolic site of S-warfarin to the oxy-ferryl center of CYP2C9, and I359L and R150H caused shifts in the conformation of S-warfarin to a position less favorable for metabolism. These data suggest that MD simulations may better capture the impact of nsSNPs in pharmacogenes than other tools.

Basket Trials: Past, Present, and Future

Large-scale tumor molecular profiling has revealed that diverse cancer histologies are driven by common pathways with unifying biomarkers that can be exploited therapeutically. Disease-agnostic basket trials have been increasingly utilized to test biomarker-driven therapies across cancer types. These trials have led to drug approvals and improved the lives of patients while simultaneously advancing our understanding of cancer biology. This review focuses on the practicalities of implementing basket trials, with an emphasis on molecularly targeted trials. We examine the biologic subtleties of genomic biomarker and patient selection, discuss previous successes in drug development facilitated by basket trials, describe certain novel targets and drugs, and emphasize practical considerations for participant recruitment and study design. This review also highlights strategies for aiding patient access to basket trials. As basket trials become more common, steps to ensure equitable implementation of these studies will be critical for molecularly targeted drug development.

Structural dynamics of the intrinsically disordered linker region of cardiac troponin T

The cardiac troponin complex, composed of troponins I, T, and C, plays a central role in regulating the calcium-dependent interactions between myosin and the thin filament. Mutations in troponin can cause cardiomyopathies; however, it is still a major challenge for the field to connect how changes in sequence affect troponin's function. Recent high-resolution structures of the thin filament revealed critical insights into the structure-function relationship of the troponin complex, but there remain large, unresolved segments of troponin, including the troponin-T linker region that is a hotspot for several cardiomyopathy mutations. This unresolved yet functionally-significant linker region has been proposed to be intrinsically disordered, with behaviors that are not well described by traditional structural approaches; however, this proposal has not been experimentally verified. Here, we used a combination of single-molecule Förster resonance energy transfer (FRET), molecular dynamics simulations, and functional reconstitution assays to investigate the troponin-T linker region. We experimentally and computationally show that in the context of both isolated troponin and the fully regulated troponin complex, the linker behaves as a dynamic, intrinsically disordered region. This region undergoes polyampholyte expansion in the presence of high salt and distinct conformational changes during the assembly of the troponin complex. We also examine the ΔE160 hypertrophic cardiomyopathy mutation in the linker, and we demonstrate that this mutation does not affect the conformational dynamics of the linker, rather it allosterically affects interactions with other subunits of the troponin complex, leading to increased molecular contractility. Taken together, our data clearly demonstrate the importance of disorder within the troponin-T linker and provide new insights into the molecular mechanisms controlling the pathogenesis of cardiomyopathies.

Functional validation of EIF2AK4 (GCN2) missense variants associated with pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a disorder with a large genetic component. Biallelic mutations of EIF2AK4, which encodes the kinase GCN2, are causal in two ultra-rare subtypes of PAH, pulmonary veno-occlusive disease and pulmonary capillary haemangiomatosis. EIF2AK4 variants of unknown significance have also been identified in patients with classical PAH, though their relationship to disease remains unclear. To provide patients with diagnostic information and enable family testing, the functional consequences of such rare variants must be determined, but existing computational methods are imperfect. We applied a suite of bioinformatic and experimental approaches to sixteen EIF2AK4 variants that had been identified in patients. By experimentally testing the functional integrity of the integrated stress response (ISR) downstream of GCN2, we determined that existing computational tools have insufficient sensitivity to reliably predict impaired kinase function. We determined experimentally that several EIF2AK4 variants identified in patients with classical PAH had preserved function and are therefore likely to be non-pathogenic. The dysfunctional variants of GCN2 that we identified could be subclassified into three groups: misfolded, kinase-dead, and hypomorphic. Intriguingly, members of the hypomorphic group were amenable to paradoxical activation by a type-1½ GCN2 kinase inhibitor. This experiment approach may aid in the clinical stratification of EIF2AK4 variants and potentially identify hypomorophic alleles receptive to pharmacological activation.

Clinical and functional characterization of a novel KCNJ11 (c.101G > A, p.R34H) mutation associated with maturity-onset diabetes mellitus of the young type 13

PURPOSE

This study aimed to describe the clinical features, diagnostic and therapeutic course of a patient with MODY13 caused by KCNJ11 (c.101G > A, p.R34H) and how it contributes to the pathogenesis of MODY13, and to explore new therapeutic targets.

METHODS

Whole-exome sequencing was used to screen prediagnosed individuals and family members with clinically suspected KCNJ11 mutations. Real-time fluorescence quantitative PCR, western blotting, thallium flux of potassium channels, glucose-stimulated insulin secretion (GSIS), and immunofluorescence assays were used to analyze the regulation of insulin secretion by the KCNJ11 mutant in MIN6 cells. Daily blood glucose levels were continuously monitored for 14 days in the proband using the ambulatory blood glucose meter (SIBIONICS).

RESULTS

Mutation screening of the entire exon of the gene identified a heterozygous KCNJ11 (c.101G > A, p.R34H) mutation in the proband and his mother. Cell-based GSIS assays after transfection of MIN6 using wild-type and mutant plasmids revealed that this mutation impaired insulin secretory function. Furthermore, we found that this impaired secretory function is associated with reduced functional activity of the mutant KCNJ11 protein and reduced expression of the insulin secretion-associated exocytosis proteins STXBP1 and SNAP25.

CONCLUSION

For the first time, we revealed the pathogenic mechanism of KCNJ11 (c.101G > A, p.R34H) associated with MODY13. This mutant can cause alterations in KATP channel activity, reduce sensitivity to glucose stimulation, and impair pancreatic β-cell secretory function by downregulating insulin secretion-associated exocytosis proteins. Therefore, oral sulfonylurea drugs can lower blood glucose levels through pro-insulinotropic effects and are more favorable for patients with this mutation.

PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context

Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenicity classification, but the functional impact of missense variants is multi-dimensional. Pathogenic missense variants in the same gene may act through different modes of action (i.e., gain/loss-of-function) by affecting different aspects of protein function. They may result in distinct clinical conditions that require different treatments. We developed a new method, PreMode, to perform gene-specific mode-of-action predictions. PreMode models effects of coding sequence variants using SE(3)-equivariant graph neural networks on protein sequences and structures. Using the largest-to-date set of missense variants with known modes of action, we showed that PreMode reached state-of-the-art performance in multiple types of mode-of-action predictions by efficient transfer-learning. Additionally, PreMode's prediction of G/LoF variants in a kinase is consistent with inactive-active conformation transition energy changes. Finally, we show that PreMode enables efficient study design of deep mutational scans and optimization in protein engineering.

Molecular Dynamics Simulation of Kir6.2 Variants Reveals Potential Association with Diabetes Mellitus

Diabetes mellitus (DM) represents a problem for the healthcare system worldwide. DM has very serious complications such as blindness, kidney failure, and cardiovascular disease. In addition to the very bad socioeconomic impacts, it influences patients and their families and communities. The global costs of DM and its complications are huge and expected to rise by the year 2030. DM is caused by genetic and environmental risk factors. Genetic testing will aid in early diagnosis and identification of susceptible individuals or populations using ATP-sensitive potassium (KATP) channels present in different tissues such as the pancreas, myocardium, myocytes, and nervous tissues. The channels respond to different concentrations of blood sugar, stimulation by hormones, or ischemic conditions. In pancreatic cells, they regulate the secretion of insulin and glucagon. Mutations in the KCNJ11 gene that encodes the Kir6.2 protein (a major constituent of KATP channels) were reported to be associated with Type 2 DM, neonatal diabetes mellitus (NDM), and maturity-onset diabetes of the young (MODY). Kir6.2 harbors binding sites for ATP and phosphatidylinositol 4,5-diphosphate (PIP2). The ATP inhibits the KATP channel, while the (PIP2) activates it. A Kir6.2 mutation at tyrosine330 (Y330) was demonstrated to reduce ATP inhibition and predisposes to NDM. In this study, we examined the effect of mutations on the Kir6.2 structure using bioinformatics tools and molecular dynamic simulations (SIFT, PolyPhen, SNAP2, PANTHER, PhD&SNP, SNP&Go, I-Mutant, MuPro, MutPred, ConSurf, HOPE, and GROMACS). Our results indicated that M199R, R201H, R206H, and Y330H mutations influence Kir6.2 structure and function and therefore may cause DM. We conclude that MD simulations are useful techniques to predict the effects of mutations on protein structure. In addition, the M199R, R201H, R206H, and Y330H variant in the Kir6.2 protein may be associated with DM. These results require further verification in protein-protein interactions, Kir6.2 function, and case-control studies.

Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa

Mutations leading to a reduced or loss of function in genes of the leptin-melanocortin system confer a risk for monogenic forms of obesity. Yet, gain of function variants in the melanocortin-4-receptor (MC4R) gene predispose to a lower BMI. In individuals with reduced body weight, we thus expected mutations leading to an enhanced function in the respective genes, like leptin (LEP) and MC4R. Therefore, we have Sanger sequenced the coding regions of LEP and MC4R in 462 female patients with anorexia nervosa (AN), and 445 healthy-lean controls. In total, we have observed four and eight variants in LEP and MC4R, respectively. Previous studies showed different functional in vitro effects for the detected frameshift and non-synonymous variants: (1) LEP: reduced/loss of function (p.Val94Met), (2) MC4R: gain of function (p.Val103Ile, p.Ile251Leu), reduced or loss of function (p.Thr112Met, p.Ser127Leu, p.Leu211fsX) and without functional in vitro data (p.Val50Leut). In LEP, the variant p.Val94Met was detected in one patient with AN. For MC4R variants, one patient with AN carried the frameshift variant p.Leu211fsX. One patient with AN was heterozygous for two variants at the MC4R (p.Val103Ile and p.Ser127Leu). All other functionally relevant variants were detected in similar frequencies in patients with AN and lean individuals.

The pathogenic mutations of APOA5 in Chinese patients with hyperlipidemic acute pancreatitis

BACKGROUND AND AIMS

To study the role of gene mutations in the development of severe hypertriglyceridemia (HTG) in patients with hyperlipidemic acute pancreatitis (HLAP), especially different apolipoprotein A5 (APOA5) mutations.

METHODS

Whole-exome sequencing was performed on 163 patients with HLAP and 30 patients with biliary acute pancreatitis (BAP). The pathogenicity of mutations was then assessed by combining clinical information, predictions of bioinformatics programs, information from multiple gene databases, and residue location and conservation. The pathogenic mutations of APOA5 were visualized using the software.

RESULTS

1. Compared with BAP patients, pathogenic mutations of APOA5 were frequent in HLAP patients; among them, the heterozygous mutation of p.G185C was the most common. 2. All six pathogenic mutations of APOA5 identified in this study (p.S35N, p.D167V, p.G185C, p.K188I, p.R223C, and p.H182fs) were positively correlated with severe HTG; they were all in the important domains of apolipoprotein A-V (apoA-V). Residue 223 is strictly conserved in multiple mammals and is located in the lipoprotein lipase (LPL)-binding domain (Pro215-Phe261). When Arg 223 is mutated to Cys 223, the positive charge of this residue is reduced, which is potentially destructive to the binding function of apoA-V to LPL. 3. Four new APOA5 mutations were identified, namely c.563A > T, c.667C > T, c.788G > A, and c.544_545 insGGTGC.

CONCLUSIONS

The pathogenic mutations of APOA5 were specific to the patients with HLAP and severe HTG in China, and identifying such mutations had clinical significance in elucidating the etiology and subsequent treatment.

Extreme acute radiation-induced toxicity in a patient with polymorphous low-grade adenocarcinoma of the nasopharynx and rare variants in DNA repair genes

BACKGROUND

Polymorphous low-grade adenocarcinoma (PLGA) is an extremely rare finding in the nasopharynx. There are no guidelines for the treatment of PLGA in this localization. Radiotherapy may be administered to treat this malignancy; however, in radiosensitive individuals, it is associated with a risk of severe radiotherapy-induced toxicity.

METHODS

We present a case of a 73-year-old woman with locally advanced polymorphous low-grade adenocarcinoma of the nasopharynx who developed a severe adverse acute reaction to radiotherapy leading to treatment discontinuation. Despite intensive treatment, the patient died 40 days after RT initiation. Whole genome sequencing was performed using DNA from peripheral blood mononuclear cells in the search for variants that could explain such extreme toxicity.

RESULTS

We identified a combination of pathogenic variants that may have contributed to the patient's reaction to radiation therapy, including predisposing variants in XRCC1, XRCC3, and LIG4. We also identified candidate variants, not previously described in this context, which could be associated with radiation toxicity based on plausible mechanisms. We discuss previous reports of this rare tumor from the literature and known contributors to radiation-induced toxicity.

CONCLUSIONS

Genetic causes should be considered in cases of extreme radiosensitivity, especially when is not explained by clinical factors.

Identification of novel candidate genes associated with non-syndromic tooth agenesis in Mongolian families

OBJECTIVES

This study aimed to identify genetic variants associated with non-syndromic tooth agenesis (TA) in nine families from Mongolia using whole-exome sequencing (WES) and bioinformatics analysis.

MATERIAL AND METHODS

The study enrolled 41 participants, including three inherited and six non-inherited families. WES analysis was performed on 14 saliva samples from individuals with non-syndromic TA. The potential candidate genes were identified through variant filtering and segregation analysis. The filtered variants were then analyzed in silico mutation impact analysis.

RESULTS

WES analysis identified 21 variants associated with TA, and 5 of these variants met all filtering criteria. These variants were located in the exome region of MAST4, ITGA6, PITX2, CACNA1S, and CDON genes. The variant in PITX2 was found in eight participants from inherited and non-inherited families, while the MAST4 variant was identified in 6 participants from inherited families.

CONCLUSIONS

The study identified various genetic variant candidates associated with TA in different family groups, with PITX2 being the most commonly identified. Our findings suggest that MAST4 may also be a novel candidate gene for TA due to its association with the Wnt signaling pathway. Additionally, we found that five candidate genes related to focal adhesion and calcium channel complex were significant and essential in tooth development.

CLINICAL RELEVANCE

Identifying new pathogenic genes associated with TA can improve our understanding of the molecular mechanisms underlying the disease, leading to better diagnosis, prevention, and treatment. Early detection of TA based on biomarkers can improve dental management and facilitate orthodontic and prosthetic treatment.

Characterization of terminal flowering cowpea (Vigna unguiculata (L.) Walp.) mutants obtained by induced mutagenesis digs out the loss-of-function of phosphatidylethanolamine-binding protein

Cowpea (Vigna unguiculata (L.) Walp) is one of the major food legume crops grown extensively in arid and semi-arid regions of the world. The determinate habit of cowpea has many advantages over the indeterminate and is well adapted to modern farming systems. Mutation breeding is an active research area to develop the determinate habit of cowpea. The present study aimed to develop new determinate habit mutants with terminal flowering (TFL) in locally well-adapted genetic backgrounds. Consequently, the seeds of popular cowpea cv P152 were irradiated with doses of gamma rays (200, 250, and, 300 Gy), and the M1 populations were grown. The M2 populations were produced from the M1 progenies and selected determinate mutants (TFLCM-1 and TFLCM-2) from the M2 generation (200 Gy) were forwarded up to the M5 generation to characterize the mutants and simultaneously they were crossed with P152 to develop a MutMap population. In the M5 generation, determinate mutants (80-81 days) were characterized by evaluating the TFL growth habit, longer peduncles (30.75-31.45 cm), erect pods (160°- 200°), number of pods per cluster (4-5 nos.), and early maturity. Further, sequencing analysis of the VuTFL1 gene in the determinate mutants and MutMap population revealed a single nucleotide transversion (A-T at 1196 bp) in the fourth exon and asparagine (N) to tyrosine (Y) amino acid change at the 143rd position of phosphatidylethanolamine-binding protein (PEBP). Notably, the loss of function PEPB with a higher confidence level modification of anti-parallel beta-sheets and destabilization of the protein secondary structure was observed in the mutant lines. Quantitative real-time PCR (qRT-PCR) analysis showed that the VuTFL1 gene was downregulated at the flowering stage in TFL mutants. Collectively, the insights garnered from this study affirm the effectiveness of induced mutation in modifying the plant's ideotype. The TFL mutants developed during this investigation have the potential to serve as a valuable resource for fostering determinate traits in future cowpea breeding programs and pave the way for mechanical harvesting.

Does Background Matter? A Comparative Characterization of Mouse Models of Autosomal Retinitis Pigmentosa rd1 and Pde6b-KO

Many retinal degenerative diseases result in vision impairment or permanent blindness due to photoreceptor loss or dysfunction. It has been observed that Pde6brd1 mice (rd1), which carry a spontaneous nonsense mutation in the pde6b gene, have a strong phenotypic similarity to patients suffering from autosomal recessive retinitis pigmentosa. In this study, we present a novel mouse model of retinitis pigmentosa generated through pde6b gene knockout using CRISPR/Cas9 technology. We compare this Pde6b-KO mouse model to the rd1 mouse model to gain insights into the progression of retinal degeneration. The functional assessment of the mouse retina and the tracking of degeneration dynamics were performed using electrophysiological methods, while retinal morphology was analyzed through histology techniques. Interestingly, the Pde6b-KO mouse model demonstrated a higher amplitude of photoresponse than the rd1 model of the same age. At postnatal day 12, the thickness of the photoreceptor layer in both mouse models did not significantly differ from that of control animals; however, by day 15, a substantial reduction was observed. Notably, the decline in the number of photoreceptors in the rd1 model occurred at a significantly faster rate. These findings suggest that the C3H background may play a significant role in the early stages of retinal degeneration.

Genetic preservation of SLC22A3 in the Admixed and Xhosa populations living in the Western Cape

BACKGROUND

Amphiphilic solute facilitator organic cation transporters mediate the movement of various endogenous and exogenous organic cations, including crucial drugs like metformin, oxaliplatin, and lamivudine. These transporters are now seen as a potential explanation for inter-individual differences in drug effectiveness, contributing to 15-30% of such variability due to genetic factors.The aim of this study was to determine the baseline minor allele frequency distribution of 18 known coding SNPs in the SLC22A3 gene of 278 Cape Admixed (130) and Xhosa (148) individuals residing in Cape Town, South Africa.

METHODS

A convenience sampling method was used for sample collection. DNA extraction and subsequent amplification of target sites was carried out according to standard established methodologies. All genotyping was performed using the SNaPshot™ mini-seuqencing platform.

RESULTS

This study found no genetic polymorphisms in the coding region of the SLC22A3 gene of both the Xhosa and Cape Admixed individuals investigated.

CONCLUSION

This study has shown that SLC22A3 coding SNPs observed in other populations are absent in the sample of both Cape Admixed and Xhosa individuals studied. The lack of protein sequence variation was consistent with other studies and may reflect the significant physiological role of human organic cation transporter 3 in maintaining cellular and organismal homeostasis.

Biochemical Activity of 17 Cancer-Associated Variants of DNA Polymerase Kappa Predicted by Electrostatic Properties

DNA damage and repair have been widely studied in relation to cancer and therapeutics. Y-family DNA polymerases can bypass DNA lesions, which may result from external or internal DNA damaging agents, including some chemotherapy agents. Overexpression of the Y-family polymerase human pol kappa can result in tumorigenesis and drug resistance in cancer. This report describes the use of computational tools to predict the effects of single nucleotide polymorphism variants on pol kappa activity. Partial Order Optimum Likelihood (POOL), a machine learning method that uses input features from Theoretical Microscopic Titration Curve Shapes (THEMATICS), was used to identify amino acid residues most likely involved in catalytic activity. The μ4 value, a metric obtained from POOL and THEMATICS that serves as a measure of the degree of coupling between one ionizable amino acid and its neighbors, was then used to identify which protein mutations are likely to impact the biochemical activity. Bioinformatic tools SIFT, PolyPhen-2, and FATHMM predicted most of these variants to be deleterious to function. Along with computational and bioinformatic predictions, we characterized the catalytic activity and stability of 17 cancer-associated DNA pol kappa variants. We identified pol kappa variants R48I, H105Y, G147D, G154E, V177L, R298C, E362V, and R470C as having lower activity relative to wild-type pol kappa; the pol kappa variants T102A, H142Y, R175Q, E210K, Y221C, N330D, N338S, K353T, and L383F were identified as being similar in catalytic efficiency to WT pol kappa. We observed that POOL predictions can be used to predict which variants have decreased activity. Predictions from bioinformatic tools like SIFT, PolyPhen-2, and FATHMM are based on sequence comparisons and therefore are complementary to POOL but are less capable of predicting biochemical activity. These bioinformatic and computational tools can be used to identify SNP variants with deleterious effects and altered biochemical activity from a large data set.

Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies

PURPOSE OF REVIEW

Familial hypercholesterolemia (FH) is a hereditary condition characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C), which increases the risk of cardiovascular disease if left untreated. This review aims to discuss the role of bioinformatics tools in evaluating the pathogenicity of missense variants associated with FH. Specifically, it highlights the use of predictive models based on protein sequence, structure, evolutionary conservation, and other relevant features in identifying genetic variants within LDLR, APOB, and PCSK9 genes that contribute to FH.

RECENT FINDINGS

In recent years, various bioinformatics tools have emerged as valuable resources for analyzing missense variants in FH-related genes. Tools such as REVEL, Varity, and CADD use diverse computational approaches to predict the impact of genetic variants on protein function. These tools consider factors such as sequence conservation, structural alterations, and receptor binding to aid in interpreting the pathogenicity of identified missense variants. While these predictive models offer valuable insights, the accuracy of predictions can vary, especially for proteins with unique characteristics that might not be well represented in the databases used for training. This review emphasizes the significance of utilizing bioinformatics tools for assessing the pathogenicity of FH-associated missense variants. Despite their contributions, a definitive diagnosis of a genetic variant necessitates functional validation through in vitro characterization or cascade screening. This step ensures the precise identification of FH-related variants, leading to more accurate diagnoses. Integrating genetic data with reliable bioinformatics predictions and functional validation can enhance our understanding of the genetic basis of FH, enabling improved diagnosis, risk stratification, and personalized treatment for affected individuals. The comprehensive approach outlined in this review promises to advance the management of this inherited disorder, potentially leading to better health outcomes for those affected by FH.

Genetic testing and diagnostic strategies of fetal skeletal dysplasia: a preliminary study in Wuhan, China

BACKGROUND

Fetal skeletal dysplasia is a diverse group of degenerative diseases of bone and cartilage disorders that can lead to movement disorder and even death. This study aims to evaluate the diagnostic yield of sonographic examination and genetic testing for fetal skeletal dysplasia.

METHODS

From September 2015 to April 2021, the study investigated 24 cases with suspected short-limb fetuses, which were obtained from Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology. To identify the causative gene, multiple approaches (including karyotype analysis, copy number variations and whole exome sequencing) were performed on these fetuses. And further segregation analysis of the candidate variant was performed in parents by using Sanger sequencing.

RESULTS

① Out of 24 cases, likely pathogenic variants in FGFR3, FBN2, COL1A2, CUL7 and DYNC2H1 were detected in 6 cases; pathogenic variants in FGFR3, IMPAD1 and GORAB were identified in other 6 cases; and variants in WNT1, FBN1, OBSL1, COL1A1, DYNC2H1 and NEK1, known as Variant of Undetermined Significance, were found in 4 cases. There were no variants detected in the rest 8 cases by the whole exome sequencing. ② Of 24 cases, 12 (50%) were found to carry variants (pathogenic or likely pathogenic) in seven genes with 12 variants. Four fetuses (16.7%) had variants of uncertain significance.

CONCLUSION

Genetic testing combining with ultrasound scanning enhances the accurate diagnosis of fatal skeletal dysplasia in utero, and then provides appropriate genetic counseling.

In-silico prediction of TGF-β1 non-synonymous variants and their impact on binding affinity to Fresolimumab

TGF-β1 is a potent immunoregulatory cytokine that plays diverse roles in development, bone healing, fibrosis, and cancer. However, characterizing TGF-β1 gene variants is challenging because the structural and functional consequences of these variants are still undetermined. In this study, we aimed to perform an in-silico analysis of TGF-β1 non-synonymous variants and their pathogenic effects on the TGF-β1 protein. A total of 10,252 TGF-β1 SNPs were collected from the NCBI dbSNP database and in-silico tools (SIFT, PROVEAN, Mutation Taster, ClinVar, PolyPhen-2, CScape, MutPred, and ConSurf) were used. The in-silico predicted potential variants were further investigated for their binding to the TGF-β1 targeting drug "Fresolimumab". Molecular docking was performed using HADDOCK and confirmed by PRODIGY and PDBsum. The in-silico analysis predicted four potential TGF-β1 nsSNPs: E47G in the LAP domain of the propeptide and I22T, L28F, and E35D in the mature TGF-β1 peptide. HADDOCK and molecular dynamics simulations revealed that the I22T and E35D variants have higher binding affinity for Fresolimumab as compared to the wild type and L28F variants. Molecular dynamics simulations (100 ns) and principal component analysis showed that TGF-β1 variants influenced the protein structure and caused variations in the internal dynamics of protein complexes with the antibody. Among them, the E35D variant significantly destabilized the TGF-β1 protein structure, resulting in rearrangement in the binding site and affecting the interactions with the Fresolimumab. This study identified four variants that can affect the TGF-β1 protein structure and result in functional consequences such as impaired response to Fresolimumab.Communicated by Ramaswamy H. Sarma.

In-silico identification and prioritization of therapeutic targets of asthma

Asthma is a "common chronic disorder that affects the lungs causing variable and recurring symptoms like repeated episodes of wheezing, breathlessness, chest tightness and underlying inflammation. The interaction of these features of asthma determines the clinical manifestations and severity of asthma and the response to treatment" [cited from: National Heart, Lung, and Blood Institute. Expert Panel 3 Report. Guidelines for the Diagnosis and Management of Asthma 2007 (EPR-3). Available at: https://www.ncbi.nlm.nih.gov/books/NBK7232/ (accessed on January 3, 2023)]. As per the WHO, 262 million people were affected by asthma in 2019 that leads to 455,000 deaths ( https://www.who.int/news-room/fact-sheets/detail/asthma ). In this current study, our aim was to evaluate thousands of scientific documents and asthma associated omics datasets to identify the most crucial therapeutic target for experimental validation. We leveraged the proprietary tool Ontosight® Discover to annotate asthma associated genes and proteins. Additionally, we also collected and evaluated asthma related patient datasets through bioinformatics and machine learning based approaches to identify most suitable targets. Identified targets were further evaluated based on the various biological parameters to scrutinize their candidature for the ideal therapeutic target. We identified 7237 molecular targets from published scientific documents, 2932 targets from genomic structured databases and 7690 dysregulated genes from the transcriptomics and 560 targets from genomics mutational analysis. In total, 18,419 targets from all the desperate sources were analyzed and evaluated though our approach to identify most promising targets in asthma. Our study revealed IL-13 as one of the most important targets for asthma with approved drugs on the market currently. TNF, VEGFA and IL-18 were the other top targets identified to be explored for therapeutic benefit in asthma but need further clinical testing. HMOX1, ITGAM, DDX58, SFTPD and ADAM17 were the top novel targets identified for asthma which needs to be validated experimentally.

Spatial Distribution of Missense Variants within Complement Proteins Associates with Age Related Macular Degeneration

Purpose

Genetic variants in complement genes are associated with age-related macular degeneration (AMD). However, many rare variants have been identified in these genes, but have an unknown significance, and their impact on protein function and structure is still unknown. We set out to address this issue by evaluating the spatial placement and impact on protein structureof these variants by developing an analytical pipeline and applying it to the International AMD Genomics Consortium (IAMDGC) dataset (16,144 AMD cases, 17,832 controls).

Methods

The IAMDGC dataset was imputed using the Haplotype Reference Consortium (HRC), leading to an improvement of over 30% more imputed variants, over the original 1000 Genomes imputation. Variants were extracted for the CFH , CFI , CFB , C9 , and C3 genes, and filtered for missense variants in solved protein structures. We evaluated these variants as to their placement in the three-dimensional structure of the protein (i.e. spatial proximity in the protein), as well as AMD association. We applied several pipelines to a) calculate spatial proximity to known AMD variants versus gnomAD variants, b) assess a variant's likelihood of causing protein destabilization via calculation of predicted free energy change (ddG) using Rosetta, and c) whole gene-based testing to test for statistical associations. Gene-based testing using seqMeta was performed using a) all variants b) variants near known AMD variants or c) with a ddG >|2|. Further, we applied a structural kernel adaptation of SKAT testing (POKEMON) to confirm the association of spatial distributions of missense variants to AMD. Finally, we used logistic regression on known AMD variants in CFI to identify variants leading to >50% reduction in protein expression from known AMD patient carriers of CFI variants compared to wild type (as determined by in vitro experiments) to determine the pipeline's robustness in identifying AMD-relevant variants. These results were compared to functional impact scores, ie CADD values > 10, which indicate if a variant may have a large functional impact genomewide, to determine if our metrics have better discriminative power than existing variant assessment methods. Once our pipeline had been validated, we then performed a priori selection of variants using this pipeline methodology, and tested AMD patient cell lines that carried those selected variants from the EUGENDA cohort (n=34). We investigated complement pathway protein expression in vitro , looking at multiple components of the complement factor pathway in patient carriers of bioinformatically identified variants.

Results

Multiple variants were found with a ddG>|2| in each complement gene investigated. Gene-based tests using known and novel missense variants identified significant associations of the C3 , C9 , CFB , and CFH genes with AMD risk after controlling for age and sex (P=3.22×10 -5 ;7.58×10 -6 ;2.1×10 -3 ;1.2×10 -31 ). ddG filtering and SKAT-O tests indicate that missense variants that are predicted to destabilize the protein, in both CFI and CFH, are associated with AMD (P=CFH:0.05, CFI:0.01, threshold of 0.05 significance). Our structural kernel approach identified spatial associations for AMD risk within the protein structures for C3, C9, CFB, CFH, and CFI at a nominal p-value of 0.05. Both ddG and CADD scores were predictive of reduced CFI protein expression, with ROC curve analyses indicating ddG is a better predictor (AUCs of 0.76 and 0.69, respectively). A priori in vitro analysis of variants in all complement factor genes indicated that several variants identified via bioinformatics programs PathProx/POKEMON in our pipeline via in vitro experiments caused significant change in complement protein expression (P=0.04) in actual patient carriers of those variants, via ELISA testing of proteins in the complement factor pathway, and were previously unknown to contribute to AMD pathogenesis.

Conclusion

We demonstrate for the first time that missense variants in complement genes cluster together spatially and are associated with AMD case/control status. Using this method, we can identify CFI and CFH variants of previously unknown significance that are predicted to destabilize the proteins. These variants, both in and outside spatial clusters, can predict in-vitro tested CFI protein expression changes, and we hypothesize the same is true for CFH . A priori identification of variants that impact gene expression allow for classification for previously classified as VUS. Further investigation is needed to validate the models for additional variants and to be applied to all AMD-associated genes.

Whole-exome and targeted gene sequencing of large-cell lung carcinoma reveals recurrent mutations in the PI3K pathway

BACKGROUND

Large cell lung carcinoma (LCLC) is an exceptionally aggressive disease with a poor prognosis. At present, little is known about the molecular pathology of LCLC.

METHODS

Ultra-deep sequencing of cancer-related genes and exome sequencing were used to detect the LCLC mutational in 118 tumor-normal pairs. The cell function test was employed to confirm the potential carcinogenic mutation of PI3K pathway.

RESULTS

The mutation pattern is determined by the predominance of A > C mutations. Genes with a significant non-silent mutation frequency (FDR) < 0.05) include TP53 (47.5%), EGFR (13.6%) and PTEN (12.1%). Moreover, PI3K signaling (including EGFR, FGRG4, ITGA1, ITGA5, and ITGA2B) is the most mutated pathway, influencing 61.9% (73/118) of the LCLC samples. The cell function test confirmed that the potential carcinogenic mutation of PI3K pathway had a more malignant cell function phenotype. Multivariate analysis further revealed that patients with the PI3K signaling pathway mutations have a poor prognosis (P = 0.007).

CONCLUSIONS

These results initially identified frequent mutation of PI3K signaling pathways in LCLC and indicate potential targets for the treatment of this fatal type of LCLC.

Myocilin misfolding and glaucoma: A 20-year update

Mutations in the gene MYOC account for approximately 5% of cases of primary open angle glaucoma (POAG). MYOC encodes for the protein myocilin, a multimeric secreted glycoprotein composed of N-terminal coiled-coil (CC) and leucine zipper (LZ) domains that are connected via a disordered linker to a 30 kDa olfactomedin (OLF) domain. More than 90% of glaucoma-causing mutations are localized to the OLF domain. While myocilin is expressed in numerous tissues, mutant myocilin is only associated with disease in the anterior segment of the eye, in the trabecular meshwork. The prevailing pathogenic mechanism involves a gain of toxic function whereby mutant myocilin aggregates intracellularly instead of being secreted, which causes cell stress and an early timeline for TM cell death, elevated intraocular pressure, and subsequent glaucoma-associated retinal degeneration. In this review, we focus on the work our lab has conducted over the past ∼15 years to enhance our molecular understanding of myocilin-associated glaucoma, which includes details of the molecular structure and the nature of the aggregates formed by mutant myocilin. We conclude by discussing open questions, such as predicting phenotype from genotype alone, the elusive native function of myocilin, and translational directions enabled by our work.

Use of whole genome sequencing to determine the genetic basis of visceral myopathies including Prune Belly syndrome

Objectives/aims

The visceral myopathies (VM) are a group of disorders characterised by poorly contractile or acontractile smooth muscle. They manifest in both the GI and GU tracts, ranging from megacystis to Prune Belly syndrome. We aimed to apply a bespoke virtual genetic panel and describe novel variants associated with this condition using whole genome sequencing data within the Genomics England 100,000 Genomes Project.

Methods

We screened the Genomics England 100,000 Genomes Project rare diseases database for patients with VM-related phenotypes. These patients were screened for sequence variants and copy number variants (CNV) in ACTG2, ACTA2, MYH11, MYLK, LMOD1, CHRM3, MYL9, FLNA and KNCMA1 by analysing whole genome sequencing data. The identified variants were analysed using variant effect predictor online tool, and any possible segregation in other family members and novel missense mutations was modelled using in silico tools. The VM cohort was also used to perform a genome-wide variant burden test in order to identify confirm gene associations in this cohort.

Results

We identified 76 patients with phenotypes consistent with a diagnosis of VM. The range of presentations included megacystis/microcolon hypoperistalsis syndrome, Prune Belly syndrome and chronic intestinal pseudo-obstruction. Of the patients in whom we identified heterozygous ACTG2 variants, 7 had likely pathogenic variants including 1 novel likely pathogenic allele. There were 4 patients in whom we identified a heterozygous MYH11 variant of uncertain significance which leads to a frameshift and a predicted protein elongation. We identified one family in whom we found a heterozygous variant of uncertain significance in KCNMA1 which in silico models predicted to be disease causing and may explain the VM phenotype seen. We did not find any CNV changes in known genes leading to VM-related disease phenotypes. In this phenotype selected cohort, ACTG2 is the largest monogenic cause of VM-related disease accounting for 9% of the cohort, supported by a variant burden test approach, which identified ACTG2 variants as the largest contributor to VM-related phenotypes.

Conclusions

VM are a group of disorders that are not easily classified and may be given different diagnostic labels depending on their phenotype. Molecular genetic analysis of these patients is valuable as it allows precise diagnosis and aids understanding of the underlying disease manifestations. We identified ACTG2 as the most frequent genetic cause of VM. We recommend a nomenclature change to 'autosomal dominant ACTG2 visceral myopathy' for patients with pathogenic variants in ACTG2 and associated VM phenotypes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44162-023-00012-z.

Prioritization of genes associated with type 2 diabetes mellitus for functional studies

Existing therapies for type 2 diabetes mellitus (T2DM) show limited efficacy or have adverse effects. Numerous genetic variants associated with T2DM have been identified, but progress in translating these findings into potential drug targets has been limited. Here, we describe the tools and platforms available to identify effector genes from T2DM-associated coding and non-coding variants and prioritize them for functional studies. We discuss QSER1 and SLC12A8 as examples of genes that have been identified as possible T2DM candidate genes using these tools and platforms. We suggest further approaches, including the use of sequencing data with increased sample size and ethnic diversity, single-cell omics data for analyses, glycaemic trait associations to predict gene function and, potentially, human induced pluripotent stem cell 'village' cultures, to strengthen current gene functionalization workflows. Effective prioritization of T2DM-associated genes for experimental validation could expedite our understanding of the genetic mechanisms responsible for T2DM to facilitate the use of precision medicine in its treatment.

Evaluation and analysis of novel germline variants in ethanol metabolism pathway genes predisposition to liver disease

The pathogenetic events of liver disease are seemingly determined by factors linked to ethanol metabolism. The variations in genes encoding enzymes of the ethanol metabolic pathway can influence exposure to alcohol and thus may act as risk factors for the development of liver disease. The present study aimed to understand the genetic aspect of germline variations in ethanol metabolic pathway genes in two major categories of liver disease i.e. ALD and NAFLD. Targeted Re-sequencing was performed in the two disease categories along with healthy control followed by an assessment and evaluation of the variants in a case vs control manner. The pathogenicity prediction was evaluated using SIFT, PolyPhen, PROVEN, LRT, CADD, FATHMM, EIGEN, REVEL and VarSome, while MD simulation of a novel significant variant was performed using the GROMACS 5.1.4 package. The annotation of targeted re-sequencing results revealed 2172 variants in different locations of the genes. Upon recurrent assessment predominantly focusing on exonic missense variants from these genes of the alcohol metabolism pathway, the ALDH1L2 [c.337C>G, p.Pro113Ala, (rs199841702)] variant was found highly significant with comprehensive results. The amino acid substitution tool that predicted protein stability due to a point mutation showed a decrease in stability. The genotyping distribution of the identified novel variant in the population revealed that heterozygosity is significantly distributed in ALD patients. However, the predominant association between the inherited variant and the cause of developing disease needs further robust study.

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification

Functional classification of genetic variants is a key for their clinical applications in patient care. However, abundant variant data generated by the next-generation DNA sequencing technologies limit the use of experimental methods for their classification. Here, we developed a protein structure and deep learning (DL)-based system for genetic variant classification, DL-RP-MDS, which comprises two principles: 1) Extracting protein structural and thermodynamics information using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, 2) combining those data with an unsupervised learning model of auto-encoder and a neural network classifier to identify the statistical significance patterns of the structural changes. We observed that DL-RP-MDS provided higher specificity than over 20 widely used in silico methods in classifying the variants of three DNA damage repair genes: TP53, MLH1, and MSH2. DL-RP-MDS offers a powerful platform for high-throughput genetic variant classification. The software and online application are available at https://genemutation.fhs.um.edu.mo/DL-RP-MDS/.

Variant Landscape of 15 Genes Involved in Corneal Dystrophies: Report of 30 Families and Comprehensive Analysis of the Literature

Corneal dystrophies (CDs) represent a group of inherited diseases characterized by the progressive deposit of abnormal materials in the cornea. This study aimed to describe the variant landscape of 15 genes responsible for CDs based on a cohort of Chinese families and a comparative analysis of literature reports. Families with CDs were recruited from our eye clinic. Their genomic DNA was analyzed using exome sequencing. The detected variants were filtered using multi-step bioinformatics and confirmed using Sanger sequencing. Previously reported variants in the literature were summarized and evaluated based on the gnomAD database and in-house exome data. In 30 of 37 families with CDs, 17 pathogenic or likely pathogenic variants were detected in 4 of the 15 genes, including TGFBI, CHST6, SLC4A11, and ZEB1. A comparative analysis of large datasets revealed that 12 of the 586 reported variants are unlikely causative of CDs in monogenic mode, accounting for 61 of 2933 families in the literature. Of the 15 genes, the gene most frequently implicated in CDs was TGFBI (1823/2902, 62.82% of families), followed by CHST6 (483/2902, 16.64%) and SLC4A11 (201/2902, 6.93%). This study presents, for the first time, the landscape of pathogenic and likely pathogenic variants in the 15 genes responsible for CDs. Awareness of frequently misinterpreted variants, such as c.1501C>A, p.(Pro501Thr) in TGFBI, is crucial in the era of genomic medicine.

Quantitative differentiation of benign and misfolded glaucoma-causing myocilin variants on the basis of protein thermal stability

Accurate predictions of the pathogenicity of mutations associated with genetic diseases are key to the success of precision medicine. Inherited missense mutations in the myocilin (MYOC) gene, within its olfactomedin (OLF) domain, constitute the strongest genetic link to primary open-angle glaucoma via a toxic gain of function, and thus MYOC is an attractive precision-medicine target. However, not all mutations in MYOC cause glaucoma, and common variants are expected to be neutral polymorphisms. The Genome Aggregation Database (gnomAD) lists ∼100 missense variants documented within OLF, all of which are relatively rare (allele frequency <0.001%) and nearly all are of unknown pathogenicity. To distinguish disease-causing OLF variants from benign OLF variants, we first characterized the most prevalent population-based variants using a suite of cellular and biophysical assays, and identified two variants with features of aggregation-prone familial disease variants. Next, we considered all available biochemical and clinical data to demonstrate that pathogenic and benign variants can be differentiated statistically based on a single metric: the thermal stability of OLF. Our results motivate genotyping MYOC in patients for clinical monitoring of this widespread, painless and irreversible ocular disease.

Extensive set of African ancestry-informative markers (AIMs) to study ancestry and population health

Introduction: Human populations are often highly structured due to differences in genetic ancestry among groups, posing difficulties in associating genes with diseases. Ancestry-informative markers (AIMs) aid in the detection of population stratification and provide an alternative approach to map population-specific alleles to disease. Here, we identify and characterize a novel set of African AIMs that separate populations of African ancestry from other global populations including those of European ancestry. Methods: Using data from the 1000 Genomes Project, highly informative SNP markers from five African subpopulations were selected based on estimates of informativeness (In) and compared against the European population to generate a final set of 46,737 African ancestry-informative markers (AIMs). The AIMs identified were validated using an independent set and functionally annotated using tools like SIFT, PolyPhen. They were also investigated for representation of commonly used SNP arrays. Results: This set of African AIMs effectively separates populations of African ancestry from other global populations and further identifies substructure between populations of African ancestry. When a subset of these AIMs was studied in an independent dataset, they differentiated people who self-identify as African American or Black from those who identify their ancestry as primarily European. Most of the AIMs were found to be in their intergenic and intronic regions with only 0.6% in the coding regions of the genome. Most of the commonly used SNP array investigated contained less than 10% of the AIMs. Discussion: While several functional annotations of both coding and non-coding African AIMs are supported by the literature and linked these high-frequency African alleles to diseases in African populations, more effort is needed to map genes to diseases in these genetically diverse subpopulations. The relative dearth of these African AIMs on current genotyping platforms (the array with the highest fraction, llumina's Omni 5, harbors less than a quarter of AIMs), further demonstrates a greater need to better represent historically understudied populations.

Frequencies of variants in genes associated with dyslipidemias identified in Costa Rican genomes

Dyslipidemias are risk factors in diseases of significant importance to public health, such as atherosclerosis, a condition that contributes to the development of cardiovascular disease. Unhealthy lifestyles, the pre-existence of diseases, and the accumulation of genetic variants in some loci contribute to the development of dyslipidemia. The genetic causality behind these diseases has been studied primarily on populations with extensive European ancestry. Only some studies have explored this topic in Costa Rica, and none have focused on identifying variants that can alter blood lipid levels and quantifying their frequency. To fill this gap, this study focused on identifying variants in 69 genes involved in lipid metabolism using genomes from two studies in Costa Rica. We contrasted the allelic frequencies with those of groups reported in the 1000 Genomes Project and gnomAD and identified potential variants that could influence the development of dyslipidemias. In total, we detected 2,600 variants in the evaluated regions. However, after various filtering steps, we obtained 18 variants that have the potential to alter the function of 16 genes, nine variants have pharmacogenomic or protective implications, eight have high risk in Variant Effect Predictor, and eight were found in other Latin American genetic studies of lipid alterations and the development of dyslipidemia. Some of these variants have been linked to changes in blood lipid levels in other global studies and databases. In future studies, we propose to confirm at least 40 variants of interest from 23 genes in a larger cohort from Costa Rica and Latin American populations to determine their relevance regarding the genetic burden for dyslipidemia. Additionally, more complex studies should arise that include diverse clinical, environmental, and genetic data from patients and controls and functional validation of the variants.

Computational analyses reveal fundamental properties of the AT structure related to thrombosis

Summary

Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, antithrombin (AT), encoded by the SERPINC1 gene is a key player regulating the clotting activity and ensuring that it stops at the right time. In this sense, mutations to this factor often result in thrombosis-the excessive coagulation that leads to the potentially fatal formation of blood clots that obstruct veins. Although this process is well known, it is still unclear why even single residue substitutions to AT lead to drastically different phenotypes. In this study, to understand the effect of mutations throughout the AT structure, we created a detailed network map of this protein, where each node is an amino acid, and two amino acids are connected if they are in close proximity in the three-dimensional structure. With this simple and intuitive representation and a machine-learning framework trained using genetic information from more than 130 patients, we found that different types of thrombosis have emerging patterns that are readily identifiable. Together, these results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance the diagnosis and treatment of coagulation disorders.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Clinical features and genetic spectrum of NMNAT1-associated retinal degeneration

OBJECTIVES

To systematically analyse the NMNAT1 variant spectrum and frequency, the associated phenotypic characteristics, and potential genotype-phenotype correlations based on our data and literature review.

METHODS

Biallelic potential pathogenic variants (PPV) in NMNAT1 were collected from our in-house exome sequencing data. Whole-genome sequencing was conducted subsequently for patients with only one heterozygous PPV detected in NMNAT1. The clinical data were reviewed and evaluated in detail. Furthermore, the literature was reviewed for reports of NMNAT1 variants and their associated phenotypes.

RESULTS

Eleven NMNAT1 variants, including two novel variants, were detected in 8 families from our cohort. All of the 9 available patients showed generalized tapetoretinal dystrophy at an early age (88.9% in the first decade), and disciform macular atrophy was identified in six patients from five unrelated families. Among a total of 125 patients from 8 families of our cohort and 91 families reported by the available literature, 92.9% patients showed onset of disease in the first year after birth, and 89.0% patients showed visual acuity of 0.05 or lower. All of the 39 patients with fundus photos available presented disciform macular atrophy with generalized tapetoretinal dystrophy. Most (54/80, 67.5%) of causative NMNAT1 variants were missense. The most frequent variants in Caucasian and Asian population are p.E257K and p.R237C, respectively.

CONCLUSIONS

Early-onset age, disciform macular atrophy with generalized tapetoretinal dystrophy, and poor visual acuity are the typical features of NMNAT1-associated retinal degeneration. Different variant hot spots of NMNAT1 were observed in different populations.

Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory

Background

The widespread clinical application of genome-wide sequencing has resulted in many new diagnoses for rare genetic conditions, but testing regularly identifies variants of uncertain significance (VUS). The remarkable rise in the amount of genomic data has been paralleled by a rise in the number of protein structures that are now publicly available, which may have clinical utility for the interpretation of missense and in-frame insertions or deletions.

Methods

Within a UK National Health Service genomic medicine diagnostic laboratory, we investigated the number of VUS over a 5-year period that were evaluated using protein structural analysis and how often this analysis aided variant classification.

Results

We found 99 novel missense and in-frame variants across 67 genes that were initially classified as VUS by our diagnostic laboratory using standard variant classification guidelines and for which further analysis of protein structure was requested. Evidence from protein structural analysis was used in the re-assessment of 64 variants, of which 47 were subsequently reclassified as pathogenic or likely pathogenic and 17 remained as VUS. We identified several case studies where protein structural analysis aided variant interpretation by predicting disease mechanisms that were consistent with the observed phenotypes, including loss-of-function through thermodynamic destabilisation or disruption of ligand binding, and gain-of-function through de-repression or escape from proteasomal degradation.

Conclusions

We have shown that using in silico protein structural analysis can aid classification of VUS and give insights into the mechanisms of pathogenicity. Based on our experience, we propose a generic evidence-based workflow for incorporating protein structural information into diagnostic practice to facilitate variant classification.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01082-2.

Using reported pathogenic variants to identify therapeutic opportunities for genetic diseases

PURPOSE

Drug development strategies for genetic diseases depend critically on accurate knowledge of how pathogenic variants cause disease. For some well-studied genes, the direct effects of pathogenic variants are well documented as loss-of-function, gain-of-function or hypermorphic, or a combination of the two. For many genes, however, even the direction of effect of variants remains unclear. Classification of Mendelian disease genes in terms of whether pathogenic variants are loss- or gain-of-function would directly inform drug development strategies.

METHODS

We leveraged the recent dramatic increase in reported pathogenic variants to provide a novel approach to inferring the direction of effect of pathogenic variants. Specifically, we quantify the ratio of reported pathogenic variants that are missense compared to loss-of-function.

RESULTS

We first show that for many genes that cause dominant Mendelian disease, the ratio of reported pathogenic missense variants is diagnostic of whether the gene causes disease through loss- or gain-of-function, or a combination. Second, we identify a set of genes that appear to cause disease largely or entirely through gain-of-function or hypermorphic pathogenic variants.

CONCLUSIONS

We suggest a set of 16 genes suitable for drug developmental efforts utilizing direct inhibition.

A haplotype-resolved genome assembly of the Nile rat facilitates exploration of the genetic basis of diabetes

Background

The Nile rat (Avicanthis niloticus) is an important animal model because of its robust diurnal rhythm, a cone-rich retina, and a propensity to develop diet-induced diabetes without chemical or genetic modifications. A closer similarity to humans in these aspects, compared to the widely used Mus musculus and Rattus norvegicus models, holds the promise of better translation of research findings to the clinic.

Results

We report a 2.5 Gb, chromosome-level reference genome assembly with fully resolved parental haplotypes, generated with the Vertebrate Genomes Project (VGP). The assembly is highly contiguous, with contig N50 of 11.1 Mb, scaffold N50 of 83 Mb, and 95.2% of the sequence assigned to chromosomes. We used a novel workflow to identify 3613 segmental duplications and quantify duplicated genes. Comparative analyses revealed unique genomic features of the Nile rat, including some that affect genes associated with type 2 diabetes and metabolic dysfunctions. We discuss 14 genes that are heterozygous in the Nile rat or highly diverged from the house mouse.

Conclusions

Our findings reflect the exceptional level of genomic resolution present in this assembly, which will greatly expand the potential of the Nile rat as a model organism.

The ClinGen Brain Malformation Variant Curation Expert Panel: Rules for somatic variants in AKT3, MTOR, PIK3CA, and PIK3R2

PURPOSE

Postzygotic (somatic) variants in the mTOR pathway genes cause a spectrum of distinct developmental abnormalities. Accurate classification of somatic variants in this group of disorders is crucial for affected individuals and their families.

METHODS

The ClinGen Brain Malformation Variant Curation Expert Panel was formed to curate somatic variants associated with developmental brain malformations. We selected the genes AKT3, MTOR, PIK3CA, and PIK3R2 as the first set of genes to provide additional specifications to the 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) sequence variant interpretation guidelines, which currently focus solely on germline variants.

RESULTS

A total of 24 of the original 28 ACMG/AMP criteria required modification. Several modifications used could be applied to other genes and disorders in which somatic variants play a role: 1) using variant allele fraction differences as evidence that somatic mutagenesis occurred as a proxy for de novo variation, 2) incorporating both somatic and germline evidence, and 3) delineating phenotype on the basis of variable tissue expression.

CONCLUSION

We have established a framework for rigorous interpretation of somatic mosaic variants, addressing issues unique to somatic variants that will be applicable to many genes and conditions.

Mutations in GCK May Lead to MODY2 by Reducing Glycogen Synthesis

Dysfunction of glucokinase (GCK) caused by mutations in the GCK gene is the main cause of maturity-onset diabetes of the young type-2 (MODY2, also known as GCK-MODY), which is usually present in adolescence or young adulthood. MODY2 is characterized by mild, stable fasting hyperglycemia that presents at birth, usually 5.4-8.3 mmol L^-1 , and rarely develops complications from diabetes. The treatment of MODY2 prefers a manageable diet rather than the use of insulin. Previous studies have identified GCK mutations only by online software prediction or enzyme kinetic analysis and thermolability assays which are complicated to be conducted. In this study, six mutations in the GCK gene, including four novel mutations and two mutations that are previously reported, are identified. All the six locations are highly conserved according to the sequencing alignment. Moreover, missense mutations are strongly predicted to be pathogenic using online programs. Functional studies show that mutations in GCK mutation do not affect insulin secretion but affect glycogen synthesis. These findings demonstrate that GCK mutations decrease glycogen synthesis, which leads to hyperglycemia in MODY2. Meanwhile, this study provides a new perspective and methods for identifying pathogenic mutations in GCK.

Structural and Functional Impact of Damaging Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) on Human VPS35 Protein Using Computational Approaches

Parkinson's disease is the second most common progressive neurodegenerative movement disorder. Mutations in retromer complex subunit and VPS35 represent the second most common cause of late-onset familial Parkinson's disease. The mutation in VPS35 can disrupt the normal protein functions resulting in Parkinson's disease. The aim of this study was the identification of deleterious missense Single Nucleotide Polymorphisms (nsSNPs) and their structural and functional impact on the VPS35 protein. In this study, several insilico tools were used to identify deleterious and disease-associated nsSNPs. 3D structure of VPS35 protein was constructed through MODELLER 9.2, normalized using FOLDX, and evaluated through RAMPAGE and ERRAT whereas, FOLDX was used for mutagenesis. 25 ligands were obtained from literature and docked using PyRx 0.8 software. Based on the binding affinity, five ligands i.e., PG4, MSE, GOL, EDO, and CAF were further analyzed. Molecular Dynamic simulation analysis was performed using GROMACS 5.1.4, where temperature, pressure, density, RMSD, RMSF, Rg, and SASA graphs were analyzed. The results showed that the mutations Y67H, R524W, and D620N had a structural and functional impact on the VPS35 protein. The current findings will help in appropriate drug design against the disease caused by these mutations in a large population using in-vitro study.

Anterior Umbilication of Lens in a Family with Congenital Cataracts Associated with a Missense Mutation of MIP Gene

Congenital cataracts (CCs) have significant genotypic and phenotypic heterogeneity. The major intrinsic protein (MIP) gene, one of the causative genes of CCs, plays a vital role in maintaining the homeostasis and transparency of the lens. In this study, we identified a unique phenotype of anterior umbilication of the lens in a four-generation pedigree with CCs. All patients in the observed family had nystagmus, nuclear cataracts, and elongated axial lengths compared with their healthy counterparts except for patient I:2, whose axial length was unavailable, and patientII:4, who had total cataracts. We confirmed, using Sanger sequencing based on whole-exon sequencing (WES) data, that all patients carried a heterozygous variant NM_012064.4:c.97C > T (NP_036196.1:p.R33C) in their MIP gene. To our knowledge, 29 variants of the human MIP gene and the relative phenotypes associated with CCs have been identified. Nevertheless, this is the first report on the anterior umbilication of the lens with nuclear or total opacity caused by the c.97C > T (p.R33C) variant in the MIP gene. These results also provide evidence that the elongated axial length might be associated with this variant. This study further confirms the phenotypic heterogeneity of CCs.

DNA Repair Mechanisms, Protein Interactions and Therapeutic Targeting of the MRN Complex

Repair of a DNA double-strand break relies upon a pathway of proteins to identify damage, regulate cell cycle checkpoints, and repair the damage. This process is initiated by a sensor protein complex, the MRN complex, comprised of three proteins-MRE11, RAD50, and NBS1. After a double-stranded break, the MRN complex recruits and activates ATM, in-turn activating other proteins such as BRCA1/2, ATR, CHEK1/2, PALB2 and RAD51. These proteins have been the focus of many studies for their individual roles in hereditary cancer syndromes and are included on several genetic testing panels. These panels have enabled us to acquire large amounts of genetic data, much of which remains a challenge to interpret due to the presence of variants of uncertain significance (VUS). While the primary aim of clinical testing is to accurately and confidently classify variants in order to inform medical management, the presence of VUSs has led to ambiguity in genetic counseling. Pathogenic variants within MRN complex genes have been implicated in breast, ovarian, prostate, colon cancers and gliomas; however, the hundreds of VUSs within MRE11, RAD50, and NBS1 precludes the application of these data in genetic guidance of carriers. In this review, we discuss the MRN complex's role in DNA double-strand break repair, its interactions with other cancer predisposing genes, the variants that can be found within the three MRN complex genes, and the MRN complex's potential as an anti-cancer therapeutic target.

A novel germline HAVCR2 (TIM-3) compound heterozygous mutation is related to hemophagocytic lymphohistiocytic syndrome in EBV-positive peripheral T-cell lymphoma (NOS) with down-regulated TIM-3 signaling

Recently, it have been reported that Hepatitis A Virus-Cellular Receptor 2(HAVCR2,encoding T-cell immunoglobulin and Mucin-Containing Protein 3[TIM3]) mutations are associated with severe hemophagocytic syndrome(HLH) in subcutaneous panniculitis-like T-cell lymphoma(SPTCL),and there are also frequent mutations in sporadic SPTCL, suggesting the individuals harboring HAVCR2(TIM-3) germline mutations are highly susceptible to familial or sporadic SPTCL. Here, we identify a novel germline compound heterozygous mutation of TIM-3 gene,c.245A>G (p.Tyr82Cys) and c.265C>T(p.Arg89Cys) variations in a single familial case with EBV-positive peripheral T-cell lymphoma(NOS),accompanied HLH;we also detected Tyr82Cys germline mutation in TIM-3 gene in one sporadic patient with cutaneous T cell lymphoma. We screened the distributive frequencies for TIM-3 mutations in healthy controls(n=87), B-(n=79) or T-cell lymphoma(n=25) not SPTCL, and the results showed that the mutation was found in two out of 25 patients with T-cell lymphoma but was not detected in 79 patients with B-cell lymphoma nor in a group of 87 controls. The mRNA expression of TIM-3 on primary cells and transfected HEK293 cells reduced significantly, indicating Tyr82Cys and Arg89Cys mutations is a loss-of function mutations on TIM-3,resulting in a weakened TIM-3 signaling. Our results suggest Tyr82Cys TIM-3 germline mutations are not only limited in SPTCL, and also occurred in other types of T-cell lymphoma, especially complicated HLH. TIM-3 mutations may be an predisposing factor for T-cell lymphoma and molecular marker for auxiliary diagnosis in T cell lymphoma,especially complicated with HLH.

Prevalence estimates of putatively pathogenic leptin variants in the gnomAD database

Homozygosity for pathogenic variants in the leptin gene leads to congenital leptin deficiency causing severe early-onset obesity. This monogenic form of obesity has mainly been detected in patients from consanguineous families. Prevalence estimates for the general population using the Exome Aggregation Consortium (ExAC) database reported a low frequency of leptin mutations. One in approximately 15 million individuals will be homozygous for a deleterious leptin variant. With the present study, we aimed to extend these findings utilizing the augmented Genome Aggregation Database (gnomAD) v2.1.1 including more than 140,000 samples. In total, 68 non-synonymous and 7 loss-of-function leptin variants were deposited in gnomAD. By predicting functional implications with the help of in silico tools, like SIFT, PolyPhen2 and MutationTaster2021, the prevalence of hetero- and homozygosity for putatively pathogenic variants (n = 32; pathogenic prediction by at least two tools) in the leptin gene were calculated. Across all populations, the estimated prevalence for heterozygosity for functionally relevant variants was approximately 1:2,100 and 1:17,830,000 for homozygosity. This prevalence deviated between the individual populations. Accordingly, people from East Asia and individuals of mixed ethnicities (‘Others’) were at greater risk to carry a possibly damaging leptin variant. Generally, this study emphasises the scarcity of pathogenic leptin variants in the general population with varying prevalence for distinct study groups.

Cell-based analysis of CLIC5A and SLC12A2 variants associated with hearing impairment in two African families

We have previously reported CLIC5A and SLC12A2 variants in two families from Cameroon and Ghana, segregating non-syndromic hearing impairment (NSHI). In this study, biological assays were performed to further functionally investigate the pathogenicity of CLIC5 [c.224T>C; p.(L75P)] and SCL12A2 [c.2935G>A: p.(E979K)] variants. Ectopic expression of the proteins in a cell model shows that compared to wild-type, both the CLIC5A and SLC12A2 variants were overexpressed. The mutant CLIC5A protein appears as aggregated perinuclear bodies while the wild-type protein was evenly distributed in the cytoplasm. Furthermore, cells transfected with the wild-type CLIC5A formed thin membrane filopodia-like protrusions which were absent in the CLIC5A mutant expressing and control cells. On the other hand, the wild-type SLC12A2 expressing cells had an axon-like morphology which was not observed in the mutant expressing and control cells. A network analysis revealed that CLIC5A can interact with at least eight proteins at the base of the stereocilia. This study has generated novel biological data associated with the pathogenicity of targeted variants in CLIC5A and SLC12A2, found in two African families, and therefore expands our understanding of their pathobiology in hearing impairment.

Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure

Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Taking protein structure into account has therefore provided great insight into the molecular mechanisms underlying human genetic disease. While there has been much focus on how mutations can disrupt protein structure and thus cause a loss of function (LOF), alternative mechanisms, specifically dominant-negative (DN) and gain-of-function (GOF) effects, are less understood. Here, we investigate the protein-level effects of pathogenic missense mutations associated with different molecular mechanisms. We observe striking differences between recessive vs dominant, and LOF vs non-LOF mutations, with dominant, non-LOF disease mutations having much milder effects on protein structure, and DN mutations being highly enriched at protein interfaces. We also find that nearly all computational variant effect predictors, even those based solely on sequence conservation, underperform on non-LOF mutations. However, we do show that non-LOF mutations could potentially be identified by their tendency to cluster in three-dimensional space. Overall, our work suggests that many pathogenic mutations that act via DN and GOF mechanisms are likely being missed by current variant prioritisation strategies, but that there is considerable scope to improve computational predictions through consideration of molecular disease mechanisms.

Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Here the authors analyse the locations of thousands of human disease mutations and their predicted effects on protein structure and show that,while loss-of-function mutations tend to be highly disruptive, non-loss-of-function mutations are in general much milder at a protein structural level.

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

Rare Variants in Novel Candidate Genes Associated With Nonsyndromic Patent Ductus Arteriosus Identified With Whole-Exome Sequencing

Background: Patent ductus arteriosus (PDA) is one of the most common congenital heart defects causing pulmonary hypertension, infective endocarditis, and even death. The important role of genetics in determining spontaneous ductal closure has been well-established. However, as many of the identified variants are rare, thorough identification of the associated genetic factors is necessary to further explore the genetic etiology of PDA.

Methods: We performed whole-exome sequencing (WES) on 39 isolated nonsyndromic PDA patients and 100 healthy controls. Rare variants and novel genes were identified through bioinformatic filtering strategies. The expression patterns of candidate genes were explored in human embryo heart samples.

Results: Eighteen rare damaging variants of six novel PDA-associated genes (SOX8, NES, CDH2, ANK3, EIF4G1, and HIPK1) were newly identified, which were highly expressed in human embryo hearts.

Conclusions: WES is an efficient diagnostic tool for exploring the genetic pathogenesis of PDA. These findings contribute new insights into the molecular basis of PDA and may inform further studies on genetic risk factors for congenital heart defects.

Whole-exome Sequencing Identifies SLC52A1 and ZNF106 Variants as Novel Genetic Risk Factors for (Early) Multiple-organ Failure in Acute Pancreatitis

OBJECTIVE

The aim of this study was to identify genetic variants associated with early multiple organ failure (MOF) in acute pancreatitis.

SUMMARY BACKGROUND DATA

MOF is a life-threatening complication of acute pancreatitis, and risk factors are largely unknown, especially in early persistent MOF. Genetic risk factors are thought to enhance severity in complex diseases such as acute pancreatitis.

METHODS

A 2-phase study design was conducted. First, we exome sequenced 9 acute pancreatitis patients with early persistent MOF and 9 case-matched patients with mild edematous pancreatitis (phenotypic extremes) from our initial Dutch cohort of 387 patients. Secondly, 48 candidate variants that were overrepresented in MOF patients and 10 additional variants known from literature were genotyped in a replication cohort of 286 Dutch and German patients.

RESULTS

Exome sequencing resulted in 161,696 genetic variants, of which the 38,333 non-synonymous variants were selected for downstream analyses. Of these, 153 variants were overrepresented in patients with multiple-organ failure, as compared with patients with mild acute pancreatitis. In total, 58 candidate variants were genotyped in the joined Dutch and German replication cohort. We found the rs12440118 variant of ZNF106 to be overrepresented in patients with MOF (minor allele frequency 20.4% vs 11.6%, Padj=0.026). Additionally, SLC52A1 rs346821 was found to be overrepresented (minor allele frequency 48.0% vs 42.4%, Padj= 0.003) in early MOF. None of the variants known from literature were associated.Conclusions: This study indicates that SLC52A1, a riboflavin plasma membrane transporter, and ZNF106, a zinc finger protein, may be involved in disease progression toward (early) MOF in acute pancreatitis.

Interpreting protein variant effects with computational predictors and deep mutational scanning

Computational predictors of genetic variant effect have advanced rapidly in recent years. These programs provide clinical and research laboratories with a rapid and scalable method to assess the likely impacts of novel variants. However, it can be difficult to know to what extent we can trust their results. To benchmark their performance, predictors are often tested against large datasets of known pathogenic and benign variants. These benchmarking data may overlap with the data used to train some supervised predictors, which leads to data re-use or circularity, resulting in inflated performance estimates for those predictors. Furthermore, new predictors are usually found by their authors to be superior to all previous predictors, which suggests some degree of computational bias in their benchmarking. Large-scale functional assays known as deep mutational scans provide one possible solution to this problem, providing independent datasets of variant effect measurements. In this Review, we discuss some of the key advances in predictor methodology, current benchmarking strategies and how data derived from deep mutational scans can be used to overcome the issue of data circularity. We also discuss the ability of such functional assays to directly predict clinical impacts of mutations and how this might affect the future need for variant effect predictors.