Genome-wide analysis identified 17 new loci influencing intraocular pressure in Chinese population

Genetics and Glaucoma: the state of the art

Glaucoma is the second leading cause of irreversible blindness worldwide. Although genetic background contributes differently to rare early-onset glaucoma (before age 40) or common adult-onset glaucoma, it is now considered an important factor in all major forms of the disease. Genetic and genomic studies, including GWAS, are contributing to identifying novel loci associated with glaucoma or to endophenotypes across ancestries to enrich the knowledge about glaucoma genetic susceptibility. Moreover, new high-throughput functional genomics contributes to defining the relevance of genetic results in the biological pathways and processes involved in glaucoma pathogenesis. Such studies are expected to advance significantly our understanding of glaucoma's genetic basis and provide new druggable targets to treat glaucoma. This review gives an overview of the role of genetics in the pathogenesis or risk of glaucoma.

10 Years of GWAS in intraocular pressure

Intraocular pressure (IOP) is the only modifiable risk factor for glaucoma, the leading cause of irreversible blindness worldwide. In this review, we summarize the findings of genome-wide association studies (GWASs) of IOP published in the past 10 years and prior to December 2022. Over 190 genetic loci and candidate genes associated with IOP have been uncovered through GWASs, although most of these studies were conducted in subjects of European and Asian ancestries. We also discuss how these common variants have been used to derive polygenic risk scores for predicting IOP and glaucoma, and to infer causal relationship with other traits and conditions through Mendelian randomization. Additionally, we summarize the findings from a recent large-scale exome-wide association study (ExWAS) that identified rare variants associated with IOP in 40 novel genes, six of which are drug targets for clinical treatment or are being evaluated in clinical trials. Finally, we discuss the need for future genetic studies of IOP to include individuals from understudied populations, including Latinos and Africans, in order to fully characterize the genetic architecture of IOP.

Deep Sc-RNA sequencing decoding the molecular dynamic architecture of the human retina

The human retina serves as a light detector and signals transmission tissue. Advanced insights into retinal disease mechanisms and therapeutic strategies require a deep understanding of healthy retina molecular events. Here, we sequenced the mRNA of over 0.6 million single cells from human retinas across six regions at nine different ages. Sixty cell sub-types have been identified from the human mature retinas with unique markers. We revealed regional and age differences of gene expression profiles within the human retina. Cell-cell interaction analysis indicated a rich synaptic connection within the retinal cells. Gene expression regulon analysis revealed the specific expression of transcription factors and their regulated genes in human retina cell types. Some of the gene's expression, such as DKK3, are elevated in aged retinas. A further functional investigation suggested that over expression of DKK3 could impact mitochondrial stability. Overall, decoding the molecular dynamic architecture of the human retina improves our understanding of the vision system.

Pierre CL, Bimschleger H, Gao J, Cheng R, Mohammadi P, Chen H, Palmer AA, Polesskaya O, Jablonski MM. Genome-wide association study finds multiple loci associated with intraocular pressure in HS rats

Elevated intraocular pressure (IOP) is influenced by environmental and genetic factors. Increased IOP is a major risk factor for most types of glaucoma, including primary open angle glaucoma (POAG). Investigating the genetic basis of IOP may lead to a better understanding of the molecular mechanisms of POAG. The goal of this study was to identify genetic loci involved in regulating IOP using outbred heterogeneous stock (HS) rats. HS rats are a multigenerational outbred population derived from eight inbred strains that have been fully sequenced. This population is ideal for a genome-wide association study (GWAS) owing to the accumulated recombinations among well-defined haplotypes, the relatively high allele frequencies, the accessibility to a large collection of tissue samples, and the large allelic effect size compared to human studies. Both male and female HS rats (N = 1,812) were used in the study. Genotyping-by-sequencing was used to obtain ∼3.5 million single nucleotide polymorphisms (SNP) from each individual. SNP heritability for IOP in HS rats was 0.32, which agrees with other studies. We performed a GWAS for the IOP phenotype using a linear mixed model and used permutation to determine a genome-wide significance threshold. We identified three genome-wide significant loci for IOP on chromosomes 1, 5, and 16. Next, we sequenced the mRNA of 51 whole eye samples to find cis-eQTLs to aid in identification of candidate genes. We report 5 candidate genes within those loci: Tyr, Ctsc, Plekhf2, Ndufaf6 and Angpt2. Tyr, Ndufaf6 and Angpt2 genes have been previously implicated by human GWAS of IOP-related conditions. Ctsc and Plekhf2 genes represent novel findings that may provide new insight into the molecular basis of IOP. This study highlights the efficacy of HS rats for investigating the genetics of elevated IOP and identifying potential candidate genes for future functional testing.

iPSCs-Based Therapy for Trabecular Meshwork

The trabecular meshwork (TM) of the eye serves as an essential tissue in controlling aqueous humor (AH) outflow and intraocular pressure (IOP) homeostasis. However, dysfunctional TM cells and/or decreased TM cellularity is become a critical pathogenic cause for primary open-angle glaucoma (POAG). Consequently, it is particularly valuable to investigate TM characteristics, which, in turn, facilitates the development of new treatments for POAG. Since 2006, the advancement in induced pluripotent stem cells (iPSCs) provides a new tool to (1) model the TM in vitro and (2) regenerate degenerative TM in POAG. In this context, we first summarize the current approaches to induce the differentiation of TM-like cells from iPSCs and compare iPSC-derived TM models to the conventional in vitro TM models. The efficacy of iPSC-derived TM cells for TM regeneration in POAG models is also discussed. Through these approaches, iPSCs are becoming essential tools in glaucoma modeling and for developing personalized treatments for TM regeneration.

A correlation-based feature analysis of physical examination indicators can help predict the overall underlying health status using machine learning

As a systematic investigation of the correlations between physical examination indicators (PEIs) is lacking, most PEIs are currently independently used for disease warning. This results in the general physical examination having limited diagnostic values. Here, we systematically analyzed the correlations in 221 PEIs between healthy and 34 unhealthy statuses in 803,614 individuals in China. Specifically, the study population included 711,928 healthy participants, 51,341 patients with hypertension, 12,878 patients with diabetes, and 34,997 patients with other unhealthy statuses. We found rich relevance between PEIs in the healthy physical status (7662 significant correlations, 31.5%). However, in the disease conditions, the PEI correlations changed. We focused on the difference in PEIs between healthy and 35 unhealthy physical statuses and found 1239 significant PEI differences, suggesting that they could be candidate disease markers. Finally, we established machine learning algorithms to predict health status using 15-16% of the PEIs through feature extraction, reaching a 66-99% accurate prediction, depending on the physical status. This new reference of the PEI correlation provides rich information for chronic disease diagnosis. The developed machine learning algorithms can fundamentally affect the practice of general physical examinations.

Asian Race and Primary Open-Angle Glaucoma: Where Do We Stand?

Primary open-angle glaucoma (POAG) is an optic neuropathy characterized by irreversible retinal ganglion cell damage and visual field loss. The global POAG prevalence is estimated to be 3.05%, and near term is expected to significantly rise, especially within aging Asian populations. Primary angle-closure glaucoma disproportionately affects Asians, with up to four times greater prevalence of normal-tension glaucoma reported compared with high-tension glaucoma. Estimates for overall POAG prevalence in Asian populations vary, with Chinese and Indian populations representing the majority of future cases. Structural characteristics associated with glaucoma progression including the optic nerve head, retina, and cornea are distinct in Asians, serving as intermediates between African and European descent populations. Patterns in IOP suggest some similarities between races, with a significant inverse relationship between age and IOP only in Asian populations. Genetic differences have been suggested to play a role in these differences, however, a clear genetic pattern is yet to be established. POAG pathogenesis differs between Asians and other ethnicities, and it may differ within the broad classification of the Asian race. Greater awareness and further research are needed to improve treatment plans and outcomes for the increasingly high prevalence of normal tension glaucoma within aging Asian populations.

GLIS1 regulates trabecular meshwork function and intraocular pressure and is associated with glaucoma in humans

Chronically elevated intraocular pressure (IOP) is the major risk factor of primary open-angle glaucoma, a leading cause of blindness. Dysfunction of the trabecular meshwork (TM), which controls the outflow of aqueous humor (AqH) from the anterior chamber, is the major cause of elevated IOP. Here, we demonstrate that mice deficient in the Krüppel-like zinc finger transcriptional factor GLI-similar-1 (GLIS1) develop chronically elevated IOP. Magnetic resonance imaging and histopathological analysis reveal that deficiency in GLIS1 expression induces progressive degeneration of the TM, leading to inefficient AqH drainage from the anterior chamber and elevated IOP. Transcriptome and cistrome analyses identified several glaucoma- and extracellular matrix-associated genes as direct transcriptional targets of GLIS1. We also identified a significant association between GLIS1 variant rs941125 and glaucoma in humans (P = 4.73 × 10-6), further supporting a role for GLIS1 into glaucoma etiology. Our study identifies GLIS1 as a critical regulator of TM function and maintenance, AqH dynamics, and IOP.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Mendelian randomization analysis identified genes pleiotropically associated with central corneal thickness

OBJECTIVE

To prioritize genes that were pleiotropically or potentially causally associated with central corneal thickness (CCT).

METHODS

We applied the summary data-based Mendelian randomization (SMR) method integrating summarized data of genome-wide association study (GWAS) on CCT and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with CCT. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analyses were done for participants of European and East Asian ancestries, separately.

RESULTS

We identified multiple genes showing pleiotropic association with CCT in the participants of European ancestry. CLIC3 (ILMN_1796423; PSMR = 4.15 × 10- 12), PTGDS (ILMN_1664464; PSMR = 6.88 × 10- 9) and C9orf142 (ILMN_1761138; PSMR = 8.09 × 10- 9) were the top three genes using the CAGE eQTL data, and RP11-458F8.4 (ENSG00000273142.1; PSMR = 5.89 × 10- 9), LCNL1 (ENSG00000214402.6; PSMR = 5.67 × 10- 8), and PTGDS (ENSG00000107317.7; PSMR = 1.92 × 10- 7) were the top three genes using the GTEx eQTL data. No genes showed significantly pleiotropic association with CCT in the participants of East Asian ancestry after correction for multiple testing.

CONCLUSION

We identified several genes pleiotropically associated with CCT, some of which represented novel genes influencing CCT. Our findings provided important leads to a better understanding of the genetic factors influencing CCT, and revealed potential therapeutic targets for the treatment of primary open-angle glaucoma and keratoconus.

Investigating Genetic Factors Contributing to Variable Expressivity of Class I 17p13.3 Microduplication

17p13.3 microduplications are rare copy number variations (CNVs) associated with variable phenotypes, including facial dysmorphism, developmental delay, intellectual disability, and autism. Typically, when a recognized pathogenic CNV is identified, other genetic factors are not considered. We investigated via whole-exome sequencing the presence of additional variants in four carriers of class I 17p13.3 microduplications. A 730 kb 17p13.3 microduplication was identified in two half-brothers with intellectual disability, but not in a third affected half-brother or blood cells from their normal mother (Family A), thus leading to the hypothesis of maternal germline mosaicism. No additional pathogenic variants were detected in Family A. Two affected siblings carried maternally inherited 450 kb 17p13.3 microduplication (Family B); the three carriers of the microduplication exhibited microcephaly and learning disability/speech impairment of variable degrees. Exome analysis revealed a variant of uncertain significance in RORA, a gene already linked to autism, in the autistic boy; his sister was heterozygous for a CYP1B1 pathogenic variant that could be related to her congenital glaucoma. Besides, both siblings carried a loss-of-function variant in DIP2B, a candidate gene for intellectual disability, which was inherited from their father, who also exhibited learning disability in childhood. In conclusion, additional pathogenic variants were revealed in two affected carriers of class I 17p13.3 microduplication (Family B), probably adding to their phenotypes. These results provided new evidence regarding the contribution of RORA and DIP2B to neurocognitive deficits, and highlighted the importance of full genetic investigation in carriers of CNV syndromes with variable expressivity. Finally, we suggest that microcephaly may be a rare clinical feature also related to the presence of the class I 17p13.3 microduplication.

βII spectrin (SPTBN1): biological function and clinical potential in cancer and other diseases

βII spectrin, the most common isoform of non-erythrocyte spectrin, is a cytoskeleton protein present in all nucleated cells. Interestingly, βII spectrin is essential for the development of various organs such as nerve, epithelium, inner ear, liver and heart. The functions of βII spectrin include not only establishing and maintaining the cell structure but also regulating a variety of cellular functions, such as cell apoptosis, cell adhesion, cell spreading and cell cycle regulation. Notably, βII spectrin dysfunction is associated with embryonic lethality and the DNA damage response. More recently, the detection of altered βII spectrin expression in tumors indicated that βII spectrin might be involved in the development and progression of cancer. Its mutations and disorders could result in developmental disabilities and various diseases. The versatile roles of βII spectrin in disease have been examined in an increasing number of studies; nonetheless, the exact mechanisms of βII spectrin are still poorly understood. Thus, we summarize the structural features and biological roles of βII spectrin and discuss its molecular mechanisms and functions in development, homeostasis, regeneration and differentiation. This review highlight the potential effects of βII spectrin dysfunction in cancer and other diseases, outstanding questions for the future investigation of therapeutic targets. The investigation of the regulatory mechanism of βII spectrin signal inactivation and recovery may bring hope for future therapy of related diseases.

Metagenomic analysis of gut microbiota in non-treated plaque psoriasis patients stratified by disease severity: development of a new Psoriasis-Microbiome Index

Psoriasis is an immune-mediated skin disorder. Imbalance of gut microbial populations has been implicated in many diseases. We aimed to investigate whether there were differences in gut microbiota in psoriasis patients vs non-psoriasis controls and between psoriasis severity groups. 55 psoriasis patients and 27 controls were included. V3–V4 regions of the 16S rRNA gene of fecal samples were analyzed using Illumina MiSeq. Bioinformatic analysis was performed. We found changes in gut microbiome composition depending on their psoriasis status as determined by weighted unifrac (p < 0.05), in particular an increase in Firmicutes and depletion of Bacteroidetes in psoriasis patients. Additionally, the Faecalibacterium and Blautia genus were higher in psoriasis patients while Bacteroides and Paraprevotella in non-psoriasis controls (p < 0.05, LDA score > 2). Moderate-to-severe psoriasis patients had lower biodiversity than mild psoriatic patients (p = 0.049). No differences for beta-diversity were found. We developed a Psoriasis-Microbiota Index (PMI), which discriminated among psoriasis patients and controls with sensitivity: 0.78 and specificity: 0.79. Furthermore, we performed a meta-analysis with published data to validate this index. We demonstrated gut dysbiosis in psoriasis patients, suggesting a role in psoriasis pathophysiology. Furthermore, we developed a PMI with the potential to discriminate between psoriasis patients and controls across different populations, which could be used as a biomarker in the clinical practice.

Genetics of primary open-angle glaucoma and its endophenotypes

Glaucoma is a neurodegenerative disorder characterized by the loss of retinal ganglion cells and optic nerve fibers, resulting in the loss of visual field. Primary open-angle glaucoma (POAG) is the most prevalent subtype of glaucoma. Recent genome-wide association studies (GWASs) identified more than 100 variants associated with POAG and multiple loci associated with endophenotypes including the disc area, vertical cup-to-disc ratio (VCDR), and intraocular pressure (IOP). Especially, several GWASs reported the association between VCDR and variants near CDKN2B/CDKN2B-AS1, ATOH7, and CHEK2, and between IOP and variants near TMCO1, CAV1/CAV2, GAS7, and ARHGEF12. However, the effect of each variant on endophenotypes is modest; therefore, it is useful to construct a genetic risk score (GRS) based on the effect on endophenotypes by combining susceptible genetic variants. Several studies demonstrated that higher GRS was closely associated with endophenotypes including the VCDR, IOP, and age of diagnosis. Henceforth, by quantifying GRS, identification of high risk group before the disease onset, prediction of visual prognosis and early intervention may be possible.

A comprehensive map of disease networks and molecular drug discoveries for glaucoma

Glaucoma is the leading cause of irreversible blindness worldwide. The molecular etiology of glaucoma is complex and unclear. At present, there are few drugs available for glaucoma treatment. The aim of the present study was to perform a systematic analysis of glaucoma candidate drugs/chemicals based on glaucoma genes, including genetic factors and differentially expressed (DE) genes. In total, 401 genes from the genetic databases and 1656 genes from the DE gene analysis were included in further analyses. In terms of glaucoma-related genetic factors, 54 pathways were significantly enriched (FDR < 0.05), and 96 pathways for DE genes were significantly enriched (FDR < 0.05). A search of the PheWAS database for diseases associated with glaucoma-related genes returned 1,289 diseases, and a search for diseases associated with DE glaucoma-related genes returned 1,356 diseases. Cardiovascular diseases, neurodegenerative diseases, cancer, and ophthalmic diseases were highly related to glaucoma genes. A search of the DGIdb, KEGG, and CLUE databases revealed a set of drugs/chemicals targeting glaucoma genes. A subsequent analysis of the electronic medical records (EMRs) of 136,128 patients treated in Sichuan Provincial People’s Hospital for candidate drug usage and the onset of glaucoma revealed nine candidate drugs. Among these drugs, individuals treated with nicardipine had the lowest incidence of glaucoma. Taken together with the information from the drug databases, the 40 most likely candidate drugs for glaucoma treatment were highlighted. Based on these findings, we concluded that the molecular mechanism of glaucoma is complex and may be a reflection of systemic diseases. A set of ready-to-use candidate drugs targeting glaucoma genes may be developed for glaucoma clinical drug treatments. Our results provide a systematic interpretation of glaucoma genes, interactions with other systemic diseases, and candidate drugs/chemicals.

BDNF improves axon transportation and rescues visual function in a rodent model of acute elevation of intraocular pressure

Optic neuropathies lead to blindness; the common pathology is the degeneration of axons of the retinal ganglion cells. In this study, we used a rat model of retinal ischemia-reperfusion and a one-time intravitreal brain-derived neurotrophic factor (BDNF) injection; then we examined axon transportation function, continuity, physical presence of axons in different part of the optic nerve, and the expression level of proteins involved in axon transportation. We found that in the disease model, axon transportation was the most severely affected, followed by axon continuity, then the number of axons in the distal and proximal optic nerve. BDNF treatment relieved all reductions and significantly restored function. The molecular changes were more minor, probably due to massive gliosis of the optic nerve, so interpretation of protein expression data should be done with some caution. The process in this acute model resembles a fast-forward of changes in the chronic model of glaucoma. Therefore, impairment in axon transportation appears to be a common early process underlying different optic neuropathies. This research on effective intervention can be used to develop interventions for all optic neuropathies targeting axon transportation.

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression

Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10^-6). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups.

Mutant RAMP2 causes primary open-angle glaucoma via the CRLR-cAMP axis

PURPOSE

Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness worldwide and mutations in known genes can only explain 5-6% of POAG. This study was conducted to identify novel POAG-causing genes and explore the pathogenesis of this disease.

METHODS

Exome sequencing was performed in a Han Chinese cohort comprising 398 sporadic cases with POAG and 2010 controls, followed by replication studies by Sanger sequencing. A heterozygous Ramp2 knockout mouse model was generated for in vivo functional study.

RESULTS

Using exome sequencing analysis and replication studies, we identified pathogenic variants in receptor activity-modifying protein 2 (RAMP2) within three genetically diverse populations (Han Chinese, German, and Indian). Six heterozygous RAMP2 pathogenic variants (Glu39Asp, Glu54Lys, Phe103Ser, Asn113Lysfs*10, Glu143Lys, and Ser171Arg) were identified among 16 of 4763 POAG patients, whereas no variants were detected in any exon of RAMP2 in 10,953 control individuals. Mutant RAMP2s aggregated in transfected cells and resulted in damage to the AM-RAMP2/CRLR-cAMP signaling pathway. Ablation of one Ramp2 allele led to cAMP reduction and retinal ganglion cell death in mice.

CONCLUSION

This study demonstrated that disruption of RAMP2/CRLR-cAMP axis could cause POAG and identified a potential therapeutic intervention for POAG.