Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.

INTRODUCTION: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS: Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models. RESULTS: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. HIGHLIGHTS: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups.

INTRODUCTION: Existing blood-based biomarkers for Alzheimer's disease (AD) mainly focus on its pathological features. However, studies on blood-based biomarkers associated with other biological processes for a comprehensive evaluation of AD status are limited. METHODS: We developed a blood-based, multiplex biomarker assay for AD that measures the levels of 21 proteins involved in multiple biological pathways. We evaluated the assay's performance for classifying AD and indicating AD-related endophenotypes in three independent cohorts from Chinese or European-descent populations. RESULTS: The 21-protein assay accurately classified AD (area under the receiver operating characteristic curve [AUC] = 0.9407 to 0.9867) and mild cognitive impairment (MCI; AUC = 0.8434 to 0.8945) while also indicating brain amyloid pathology. Moreover, the assay simultaneously evaluated the changes of five biological processes in individuals and revealed the ethnic-specific dysregulations of biological processes upon AD progression. DISCUSSION: This study demonstrated the utility of a blood-based, multi-pathway biomarker assay for early screening and staging of AD, providing insights for patient stratification and precision medicine. HIGHLIGHTS: The authors developed a blood-based biomarker assay for Alzheimer's disease. The 21-protein assay classifies AD/MCI and indicates brain amyloid pathology. The 21-protein assay can simultaneously assess activities of five biological processes. Ethnic-specific dysregulations of biological processes in AD were revealed.

Neuronal γ-secretase regulates synaptic functions via cholesterol homeostasis.

In this issue of Neuron, Essayan-Perez and Südhof1 demonstrate roles for γ-secretase in the regulation of synaptic functions in human neurons. Chronic attenuation of γ-secretase activity increases synapse formation but decreases neurotransmission (i.e., the probability of presynaptic release), likely due to impairment of cholesterol metabolism.

The VCAM1-ApoE pathway directs microglial chemotaxis and alleviates Alzheimer's disease pathology.

In Alzheimer's disease (AD), sensome receptor dysfunction impairs microglial danger-associated molecular pattern (DAMP) clearance and exacerbates disease pathology. Although extrinsic signals, including interleukin-33 (IL-33), can restore microglial DAMP clearance, it remains largely unclear how the sensome receptor is regulated and interacts with DAMP during phagocytic clearance. Here, we show that IL-33 induces VCAM1 in microglia, which promotes microglial chemotaxis toward amyloid-beta (Aß) plaque-associated ApoE, and leads to Aß clearance. We show that IL-33 stimulates a chemotactic state in microglia, characterized by Aß-directed migration. Functional screening identified that VCAM1 directs microglial Aß chemotaxis by sensing Aß plaque-associated ApoE. Moreover, we found that disrupting VCAM1-ApoE interaction abolishes microglial Aß chemotaxis, resulting in decreased microglial clearance of Aß. In patients with AD, higher cerebrospinal fluid levels of soluble VCAM1 were correlated with impaired microglial Aß chemotaxis. Together, our findings demonstrate that promoting VCAM1-ApoE-dependent microglial functions ameliorates AD pathology.

Receptor-ligand interaction controls microglial chemotaxis and amelioration of Alzheimer's disease pathology.

Microglia maintain brain homeostasis through their ability to survey and phagocytose danger-associated molecular patterns (DAMPs). In Alzheimer's disease (AD), microglial phagocytic clearance regulates the turnover of neurotoxic DAMPs including amyloid beta (Aß) and hyperphosphorylated tau. To mediate DAMP clearance, microglia express a repertoire of surface receptors to sense DAMPs; the activation of these receptors subsequently triggers a chemotaxis-to-phagocytosis functional transition in microglia. Therefore, the interaction between microglial receptors and DAMPs plays a critical role in controlling microglial DAMP clearance and AD pathogenesis. However, there is no comprehensive overview on how microglial sensome receptors interact with DAMPs and regulate various microglial functions, including chemotaxis and phagocytosis. In this review, we discuss the important axes of receptor-ligand interaction that control different microglial functions and their roles in AD pathogenesis. First, we summarize how the accumulation and structural changes of DAMPs trigger microglial functional impairment, including impaired DAMP clearance and aberrant synaptic pruning, in AD. Then, we discuss the important receptor-ligand axes that restore microglial DAMP clearance in AD and aging. These findings suggest that targeting microglial chemotaxis-the first critical step of the microglial chemotaxis-to-phagocytosis state transition-can promote microglial DAMP clearance in AD. Thus, our review highlights the importance of microglial chemotaxis in promoting microglial clearance activity in AD. Further detailed investigations are essential to identify the molecular machinery that controls microglial chemotaxis in AD.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Polygenic diseases, such as Alzheimer's disease (AD), are those caused by the interplay between multiple genetic risk factors. Statistical models can be used to predict disease risk based on a person's genetic profile. However, there are limitations to existing methods, while emerging methods such as deep learning may improve risk prediction. Deep learning involves computer-based software learning from patterns in data to perform a certain task, e.g. predict disease risk. Here, we test whether deep learning models can help to predict AD risk. Our models not only outperformed existing methods in modeling AD risk, they also allow us to estimate an individual's risk of AD and determine the biological processes that may be involved in AD. With further testing and optimization, deep learning may be a useful tool to help accurately predict risk of AD and other diseases.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology.

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aß+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aß- and 90 Aß+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aß-, 5 Aß+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Demographics and Medication Use of Patients with Late-Onset Alzheimer's Disease in Hong Kong.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking. OBJECTIVE: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally. METHODS: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017. RESULTS: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for > 1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression. CONCLUSION: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases.

Association of SPI1 Haplotypes with Altered SPI1 Gene Expression and Alzheimer's Disease Risk.

BACKGROUND: Genetic studies reveal that single-nucleotide polymorphisms (SNPs) of SPI1 are associated with Alzheimer's disease (AD), while their effects in the Chinese population remain unclear. OBJECTIVE: We aimed to examine the AD-association of SPI1 SNPs in the Chinese population and investigate the underlying mechanisms of these SNPs in modulating AD risk. METHODS: We conducted a genetic analysis of three SPI1 SNPs (i.e., rs1057233, rs3740688, and rs78245530) in a Chinese cohort (n = 333 patients with AD, n = 721 normal controls). We also probed public European-descent AD cohorts and gene expression datasets to investigate the putative functions of those SNPs. RESULTS: We showed that SPI1 SNP rs3740688 is significantly associated with AD in the Chinese population (odds ratio [OR] = 0.72 [0.58-0.89]) and identified AD-protective SPI1 haplotypes ß (tagged by rs1057233 and rs3740688) and γ (tagged by rs3740688 and rs78245530). Specifically, haplotypes ß and γ are associated with decreased SPI1 gene expression level in the blood and brain tissues, respectively. The regulatory roles of these haplotypes are potentially mediated by changes in miRNA binding and the epigenetic landscape. Our results suggest that the AD-protective SPI1 haplotypes regulate pathways involved in immune and neuronal functions. CONCLUSION: This study is the first to report a significant association of SPI1 with AD in the Chinese population. It also identifies SPI1 haplotypes that are associated with SPI1 gene expression and decreased AD risk.

Brain-wide Cas9-mediated cleavage of a gene causing familial Alzheimer's disease alleviates amyloid-related pathologies in mice.

The pathology of familial Alzheimer's disease, which is caused by dominant mutations in the gene that encodes amyloid-beta precursor protein (APP) and in those that encode presenilin 1 and presenilin 2, is characterized by extracellular amyloid plaques and intracellular neurofibrillary tangles in multiple brain regions. Here we show that the brain-wide selective disruption of a mutated APP allele in transgenic mouse models carrying the human APP Swedish mutation alleviates amyloid-beta-associated pathologies for at least six months after a single intrahippocampal administration of an adeno-associated virus that encodes both Cas9 and a single-guide RNA that targets the mutation. We also show that the deposition of amyloid-beta, as well as microgliosis, neurite dystrophy and the impairment of cognitive performance, can all be ameliorated when the CRISPR-Cas9 construct is delivered intravenously via a modified adeno-associated virus that can cross the blood-brain barrier. Brain-wide disease-modifying genome editing could represent a viable strategy for the treatment of familial Alzheimer's disease and other monogenic diseases that affect multiple brain regions.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging.

INTRODUCTION: Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. METHODS: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. RESULTS: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 "hub proteins" representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690-0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. DISCUSSION: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging.

Instructive roles of astrocytes in hippocampal synaptic plasticity: neuronal activity-dependent regulatory mechanisms.

In the adult hippocampus, synaptic plasticity is important for information processing, learning, and memory encoding. Astrocytes, the most common glial cells, play a pivotal role in the regulation of hippocampal synaptic plasticity. While astrocytes were initially described as a homogenous cell population, emerging evidence indicates that in the adult hippocampus, astrocytes are highly heterogeneous and can differentially respond to changes in neuronal activity in a subregion-dependent manner to actively modulate synaptic plasticity. In this review, we summarize how local neuronal activity changes regulate the interactions between astrocytes and synapses, either by modulating the secretion of gliotransmitters and synaptogenic proteins or via contact-mediated signaling pathways. In turn, these specific responses induced in astrocytes mediate the interactions between astrocytes and neurons, thus shaping synaptic communication in the adult hippocampus. Importantly, the activation of astrocytic signaling is required for memory performance including memory acquisition and recall. Meanwhile, the dysregulation of this signaling can cause hippocampal circuit dysfunction in pathological conditions, resulting in cognitive impairment and neurodegeneration. Indeed, reactive astrocytes, which have dysregulated signaling associated with memory, are induced in the brains of patients with Alzheimer's disease (AD) and transgenic mouse model of AD. Emerging technologies that can precisely manipulate and monitor astrocytic signaling in vivo enable the examination of the specific actions of astrocytes in response to neuronal activity changes as well as how they modulate synaptic connections and circuit activity. Such findings will clarify the roles of astrocytes in hippocampal synaptic plasticity and memory in health and disease.

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aß) pathology through the modulation of microglial activation and Aß clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

Rhynchophylline Administration Ameliorates Amyloid-ß Pathology and Inflammation in an Alzheimer's Disease Transgenic Mouse Model.

Alzheimer's disease (AD), the most common neurodegenerative disease, has limited treatment options. As such, extensive studies have been conducted to identify novel therapeutic approaches. We previously reported that rhynchophylline (Rhy), a small molecule EphA4 inhibitor, rescues impaired hippocampal synaptic plasticity and cognitive dysfunctions in APP/PS1 mice, an AD transgenic mouse model. To assess whether Rhy can be developed as an alternative treatment for AD, it is important to examine its pharmacokinetics and effects on other disease-associated pathologies. Here, we show that Rhy ameliorates amyloid plaque burden and reduces inflammation in APP/PS1 mice. Transcriptome analysis revealed that Rhy regulates various molecular pathways in APP/PS1 mouse brains associated with amyloid metabolism and inflammation, specifically the ubiquitin proteasome system, angiogenesis, and microglial functional states. These results show that Rhy, which is blood-brain barrier permeable, is beneficial to amyloid pathology and regulates multiple molecular pathways.

IL-33/ST2 Signaling Regulates Synaptic Plasticity and Homeostasis in the Adult Hippocampal Circuitry.

In response to neuronal activity changes, the adult hippocampal circuits undergo continuous synaptic remodeling, which is essential for information processing, learning, and memory encoding. Glial cells, including astrocytes and microglia, actively regulate hippocampal synaptic plasticity by coordinating the neuronal activity-induced synaptic changes at the circuit level. Emerging evidence suggests that the crosstalk between neurons and glia in the adult hippocampus is region specific and that the mechanisms controlling this process are critically dependent on secreted factors. Interleukin-33 (IL-33), a cytokine of the IL-1 family, is a key factor that modulates such glia-driven neuromodulations in two distinct hippocampal circuits. The activation of IL-33 and its receptor complex is important for maintaining the excitatory synaptic activity in the cornu ammonis 1 subregion and the remodeling of dentate gyrus synapses through activity-dependent astrocyte-synapse and microglia-synapse interactions, respectively. Meanwhile, the dysregulation of this signaling is implicated in multiple neurological disorders, especially Alzheimer's disease. Further investigations of how IL-33/ST2 signaling is regulated in a region-specific manner as well as its diverse functions in glia-synapse communications in the adult hippocampal circuitry will provide insights into the nature of hippocampal synaptic plasticity and homeostasis in health and disease.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications.

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

Cytokine signaling convergence regulates the microglial state transition in Alzheimer's disease.

Genetic analyses have revealed the pivotal contribution of microglial dysfunctions to the pathogenesis of Alzheimer's disease (AD). Along AD progression, the accumulation of danger-associated molecular patterns (DAMPs) including beta-amyloid and hyperphosphorylated tau continuously stimulates microglia, which results in their chronic activation. Chronically activated microglia secrete excessive pro-inflammatory cytokines, which further regulate microglial responses towards DAMPs. This has spurred longstanding interest in targeting cytokine-induced microglial responses for AD therapeutic development. However, the cytokine-induced microglial state transition is not comprehensively understood. Cytokines are assumed to induce microglial state transition from a resting state to an activated state. However, recent evidence indicate that this microglial state transition involves multiple sequential functional states. Moreover, the mechanisms by which different functional states within the cytokine-induced microglial state transition regulate AD pathology remain unclear. In this review, we summarize how different cytokine signaling pathways, including those of IL-33 (interleukin-33), NLRP3 inflammasome-IL-1ß, IL-10, and IL-12/IL-23, regulate microglial functions in AD. Furthermore, we discuss how the modulation of these cytokine signaling pathways can result in beneficial outcomes in AD. Finally, we describe a stepwise functional state transition of microglia induced by cytokine signaling that can provide insights into the molecular basis of the beneficial effects of cytokine modulation in AD and potentially aid therapeutic development.

Melanocortin receptor activation alleviates amyloid pathology and glial reactivity in an Alzheimer's disease transgenic mouse model.

Alzheimer's disease (AD) is a devastating neurodegenerative disorder with no disease-modifying treatment. AD progression is characterized by cognitive decline, neuroinflammation, and accumulation of amyloid-beta (Aß) and neurofibrillary tangles in the brain, leading to neuronal and glial dysfunctions. Neuropeptides govern diverse pathophysiological processes and represent key players in AD pathogenesis, regulating synaptic plasticity, glial cell functions and amyloid pathology. Activation of the pro-opiomelanocortin (POMC)-derived neuropeptide and its receptor from the melanocortin receptor (MCR) family have previously been shown to rescue the impairment in hippocampus-dependent synaptic plasticity in the APP/PS1 mouse model of AD. However, the functional roles of MCR signaling in AD conditions, particularly in glial functions, are largely unknown. In this study, we investigated the potential benefits of MCR activation in AD. In APP/PS1 transgenic mice, we demonstrate that MCR activation mediated by the central administration of its agonist D-Tyr MTII substantially reduces Aß accumulation, while alleviating global inflammation and astrocytic activation, particularly in the hippocampus. MCR activation prominently reduces the A1 subtype of reactive astrocytes, which is considered a key source of astrocytic neurotoxicity in AD. Concordantly, MCR activation suppresses microglial activation, while enhancing their association with amyloid plaques. The blunted activation of microglia may contribute to the reduction in the neurotoxic phenotypes of astrocytes. Importantly, transcriptome analysis reveals that MCR activation restores the impaired homeostatic processes and microglial reactivity in the hippocampus in APP/PS1 mice. Collectively, our findings demonstrate the potential of MCR signaling as therapeutic target for AD.

Efficient manipulation of gene dosage in human iPSCs using CRISPR/Cas9 nickases.

The dysregulation of gene dosage due to duplication or haploinsufficiency is a major cause of autosomal dominant diseases such as Alzheimer's disease. However, there is currently no rapid and efficient method for manipulating gene dosage in a human model system such as human induced pluripotent stem cells (iPSCs). Here, we demonstrate a simple and precise method to simultaneously generate iPSC lines with different gene dosages using paired Cas9 nickases. We first generate a Cas9 nickase variant with broader protospacer-adjacent motif specificity to expand the targetability of double-nicking-mediated genome editing. As a proof-of-concept study, we examine the gene dosage effects on an Alzheimer's disease patient-derived iPSC line that carries three copies of APP (amyloid precursor protein). This method enables the rapid and simultaneous generation of iPSC lines with monoallelic, biallelic, or triallelic knockout of APP. The cortical neurons generated from isogenically corrected iPSCs exhibit gene dosage-dependent correction of disease-associated phenotypes of amyloid-beta secretion and Tau hyperphosphorylation. Thus, the rapid generation of iPSCs with different gene dosages using our method described herein can be a useful model system for investigating disease mechanisms and therapeutic development.