Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

PURPOSE: The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in four siblings. METHODS: We identified five individuals from three unrelated families with biallelic variants in FAM177A1. The physiological function of FAM177A1 was studied in a zebrafish model organism and human cell lines with loss-of-function variants similar to the affected cohort. RESULTS: These individuals share a characteristic phenotype defined by macrocephaly, global developmental delay, intellectual disability, seizures, behavioral abnormalities, hypotonia, and gait disturbance. We show that FAM177A1 localizes to the Golgi complex in mammalian and zebrafish cells. Intersection of the RNA-seq and metabolomic datasets from FAM177A1-deficient human fibroblasts and whole zebrafish larvae demonstrated dysregulation of pathways associated with apoptosis, inflammation, and negative regulation of cell proliferation. CONCLUSION: Our data sheds light on the emerging function of FAM177A1 and defines FAM177A1-related neurodevelopmental disorder as a new clinical entity.

The mitochondrial multi-omic response to exercise training across rat tissues.

Mitochondria have diverse functions critical to whole-body metabolic homeostasis. Endurance training alters mitochondrial activity, but systematic characterization of these adaptations is lacking. Here, the Molecular Transducers of Physical Activity Consortium mapped the temporal, multi-omic changes in mitochondrial analytes across 19 tissues in male and female rats trained for 1, 2, 4, or 8 weeks. Training elicited substantial changes in the adrenal gland, brown adipose, colon, heart, and skeletal muscle. The colon showed non-linear response dynamics, whereas mitochondrial pathways were downregulated in brown adipose and adrenal tissues. Protein acetylation increased in the liver, with a shift in lipid metabolism, whereas oxidative proteins increased in striated muscles. Exercise-upregulated networks were downregulated in human diabetes and cirrhosis. Knockdown of the central network protein 17-beta-hydroxysteroid dehydrogenase 10 (HSD17B10) elevated oxygen consumption, indicative of metabolic stress. We provide a multi-omic, multi-tissue, temporal atlas of the mitochondrial response to exercise training and identify candidates linked to mitochondrial dysfunction.

RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci.

Expansions of tandem repeats (TRs) cause approximately 60 monogenic diseases. We expect that the discovery of additional pathogenic repeat expansions will narrow the diagnostic gap in many diseases. A growing number of TR expansions are being identified, and interpreting them is a challenge. We present RExPRT (Repeat EXpansion Pathogenicity pRediction Tool), a machine learning tool for distinguishing pathogenic from benign TR expansions. Our results demonstrate that an ensemble approach classifies TRs with an average precision of 93% and recall of 83%. RExPRT's high precision will be valuable in large-scale discovery studies, which require prioritization of candidate loci for follow-up studies.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

The mitochondrial multi-omic response to exercise training across tissues.

Mitochondria are adaptable organelles with diverse cellular functions critical to whole-body metabolic homeostasis. While chronic endurance exercise training is known to alter mitochondrial activity, these adaptations have not yet been systematically characterized. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) mapped the longitudinal, multi-omic changes in mitochondrial analytes across 19 tissues in male and female rats endurance trained for 1, 2, 4 or 8 weeks. Training elicited substantial changes in the adrenal gland, brown adipose, colon, heart and skeletal muscle, while we detected mild responses in the brain, lung, small intestine and testes. The colon response was characterized by non-linear dynamics that resulted in upregulation of mitochondrial function that was more prominent in females. Brown adipose and adrenal tissues were characterized by substantial downregulation of mitochondrial pathways. Training induced a previously unrecognized robust upregulation of mitochondrial protein abundance and acetylation in the liver, and a concomitant shift in lipid metabolism. The striated muscles demonstrated a highly coordinated response to increase oxidative capacity, with the majority of changes occurring in protein abundance and post-translational modifications. We identified exercise upregulated networks that are downregulated in human type 2 diabetes and liver cirrhosis. In both cases HSD17B10, a central dehydrogenase in multiple metabolic pathways and mitochondrial tRNA maturation, was the main hub. In summary, we provide a multi-omic, cross-tissue atlas of the mitochondrial response to training and identify candidates for prevention of disease-associated mitochondrial dysfunction.

Beyond the exome: what's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order and emerging technologies, such as optical genome mapping and long-read DNA or RNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to a consortium such as GREGoR, which is focused on elucidating the underlying cause of rare unsolved genetic disorders.

A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network.

PURPOSE: Next-generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultrarare conditions. However, diagnosis rates differ between analytical pipelines. In the National Institutes of Health-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice. METHODS: A retrospective review was performed at 2 UDN clinical sites to compare the variants and diagnoses/candidate genes identified with the dual analyses of the NGS data. RESULTS: In total, 95 individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, whereas the clinical sites prioritized more research variants/candidate genes (P < .001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the 2 pipelines were more often because of variant prioritization disparities than variant detection. CONCLUSION: The unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provided a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome.

Rare diseases affect 30 million people in the USA and more than 300-400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25-35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.

Genetic counselor roles in the undiagnosed diseases network research study: Clinical care, collaboration, and curation.

Genetic counselors (GCs) are increasingly filling important positions on research study teams, but there is limited literature describing the roles of GCs in these settings. GCs on the Undiagnosed Diseases Network (UDN) study team serve in a variety of roles across the research network and provide an opportunity to better understand genetic counselor roles in research. To quantitatively characterize the tasks regularly performed and professional fulfillment derived from these tasks, two surveys were administered to UDN GCs in a stepwise fashion. Responses from the first, free-response survey elicited the scope of tasks which informed development of a second structured, multiple-select survey. In survey 2, respondents were asked to select which roles they performed. Across 19 respondents, roles in survey 2 received a total of 947 selections averaging approximately 10 selections per role. When asked to indicate what roles they performed, respondent selected a mean of 50 roles (range 22-70). Survey 2 data were analyzed via thematic coding of responses and hierarchical cluster analysis to identify patterns in responses. From the thematic analysis, 20 non-overlapping codes emerged in seven categories: clinical interaction and care, communication, curation, leadership, participant management, research, and team management. Three themes emerged from the categories that represented the roles of GCs in the UDN: clinical care, collaboration, and curation. Cluster analyses showed that responses were more similar among individuals at the same institution than between institutions. This study highlights the ways GCs apply their unique skill set in the context of a clinical translational research network. Additionally, findings from this study reinforce the wide applicability of core skills that are part of genetic counseling training. Clinical literacy, genomics expertise and analysis, interpersonal, psychosocial and counseling skills, education, professional practice skills, and an understanding of research processes make genetic counselors well suited for such roles and poised to positively impact research experiences and outcomes for participants.

Compound heterozygous KCTD7 variants in progressive myoclonus epilepsy.

KCTD7 is a member of the potassium channel tetramerization domain-containing protein family and has been associated with progressive myoclonic epilepsy (PME), characterized by myoclonus, epilepsy, and neurological deterioration. Here we report four affected individuals from two unrelated families in which we identified KCTD7 compound heterozygous single nucleotide variants through exome sequencing. RNAseq was used to detect a non-annotated splicing junction created by a synonymous variant in the second family. Whole-cell patch-clamp analysis of neuroblastoma cells overexpressing the patients' variant alleles demonstrated aberrant potassium regulation. While all four patients experienced many of the common clinical features of PME, they also showed variable phenotypes not previously reported, including dysautonomia, brain pathology findings including a significantly reduced thalamus, and the lack of myoclonic seizures. To gain further insight into the pathogenesis of the disorder, zinc finger nucleases were used to generate kctd7 knockout zebrafish. Kctd7 homozygous mutants showed global dysregulation of gene expression and increased transcription of c-fos, which has previously been correlated with seizure activity in animal models. Together these findings expand the known phenotypic spectrum of KCTD7-associated PME, report a new animal model for future studies, and contribute valuable insights into the disease.

Functional and structural analysis of cytokine-selective IL6ST defects that cause recessive hyper-IgE syndrome.

BACKGROUND: Biallelic variants in IL6ST, encoding GP130, cause a recessive form of hyper-IgE syndrome (HIES) characterized by high IgE level, eosinophilia, defective acute phase response, susceptibility to bacterial infections, and skeletal abnormalities due to cytokine-selective loss of function in GP130, with defective IL-6 and IL-11 and variable oncostatin M (OSM) and IL-27 levels but sparing leukemia inhibitory factor (LIF) signaling. OBJECTIVE: Our aim was to understand the functional and structural impact of recessive HIES-associated IL6ST variants. METHODS: We investigated a patient with HIES by using exome, genome, and RNA sequencing. Functional assays assessed IL-6, IL-11, IL-27, OSM, LIF, CT-1, CLC, and CNTF signaling. Molecular dynamics simulations and structural modeling of GP130 cytokine receptor complexes were performed. RESULTS: We identified a patient with compound heterozygous novel missense variants in IL6ST (p.Ala517Pro and the exon-skipping null variant p.Gly484_Pro518delinsArg). The p.Ala517Pro variant resulted in a more profound IL-6- and IL-11-dominated signaling defect than did the previously identified recessive HIES IL6ST variants p.Asn404Tyr and p.Pro498Leu. Molecular dynamics simulations suggested that the p.Ala517Pro and p.Asn404Tyr variants result in increased flexibility of the extracellular membrane-proximal domains of GP130. We propose a structural model that explains the cytokine selectivity of pathogenic IL6ST variants that result in recessive HIES. The variants destabilized the conformation of the hexameric cytokine receptor complexes, whereas the trimeric LIF-GP130-LIFR complex remained stable through an additional membrane-proximal interaction. Deletion of this membrane-proximal interaction site in GP130 consequently caused additional defective LIF signaling and Stüve-Wiedemann syndrome. CONCLUSION: Our data provide a structural basis to understand clinical phenotypes in patients with IL6ST variants.

Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases.

PURPOSE: Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful. METHODS: We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols. RESULTS: We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases. CONCLUSION: The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

Impact of Single Sign-on Adoption in an Assessment Triage Unit: A Hospital's Journey to Higher Efficiency.

BACKGROUND: Clinician time is a valuable and costly resource. In an age where computer and clinical application usage is increasing, the need for providers to remember multiple usernames and passwords is increasingly inefficient. Further complexity is added to clinical workflows if clinicians must log into smart devices frequently without a simple solution for access and data security. OBJECTIVE: The purpose of this study was to measure the average time required and time savings when taking vital sign measurements using the Single Sign-On (SSO) (badge scan and go) on the electronic medical record-connected vital sign monitors versus using 2-factor authentication (entry of username and password). In addition, user satisfaction, system usability, workflow preference, and efficacy of the deployment of Network Connectivity Engine, that is, the host middleware for SSO, were evaluated through surveys. METHODS: A preimplementation and postimplementation study was performed in the unit piloting the initiative before hospital-wide deployment. Clinician usability and workflow preference surveys were conducted postimplementation. RESULTS: Analysis showed significance in time savings by adopting SSO. CONCLUSION: SSO had a positive impact on staff efficiency and was the preferred method versus the 2-factor log-in.

Yield of whole exome sequencing in undiagnosed patients facing insurance coverage barriers to genetic testing.

BACKGROUND: Despite growing evidence of diagnostic yield and clinical utility of whole exome sequencing (WES) in patients with undiagnosed diseases, there remain significant cost and reimbursement barriers limiting access to such testing. The diagnostic yield and resulting clinical actions of WES for patients who previously faced insurance coverage barriers have not yet been explored. METHODS: We performed a retrospective descriptive analysis of clinical WES outcomes for patients facing insurance coverage barriers prior to clinical WES and who subsequently enrolled in the Undiagnosed Diseases Network (UDN). Clinical WES was completed as a result of participation in the UDN. Payer type, molecular diagnostic yield, and resulting clinical actions were evaluated. RESULTS: Sixty-six patients in the UDN faced insurance coverage barriers to WES at the time of enrollment (67% public payer, 26% private payer). Forty-two of 66 (64%) received insurance denial for clinician-ordered WES, 19/66 (29%) had health insurance through a payer known not to cover WES, and 5/66 (8%) had previous payer denial of other genetic tests. Clinical WES results yielded a molecular diagnosis in 23 of 66 patients (35% [78% pediatric, 65% neurologic indication]). Molecular diagnosis resulted in clinical actions in 14 of 23 patients (61%). CONCLUSIONS: These data demonstrate that a substantial proportion of patients who encountered insurance coverage barriers to WES had a clinically actionable molecular diagnosis, supporting the notion that WES has value as a covered benefit for patients who remain undiagnosed despite objective clinical findings.

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts.

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2-5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6-8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

A Patient with Sjogren's Syndrome and Subsequent Diagnosis of Inclusion Body Myositis and Light-Chain Amyloidosis.

We discuss a challenging case of a 58-year-old Vietnamese-American woman who presented to her new primary care provider with an 8-year history of slowly progressive dysphagia, hoarseness, muscle weakness with associated frequent falls, and weight loss. She eventually reported dry eyes and dry mouth, and she was diagnosed with Sjogren's syndrome. Subsequently, she was additionally diagnosed with inclusion body myositis and gastric light-chain (AL) amyloidosis. Although inclusion body myositis has been previously associated with Sjogren's syndrome, inclusion body myositis is rare in non-Caucasians, and the trio of Sjogren's syndrome, inclusion body myositis, and AL amyloidosis has not been previously reported. Sjogren's syndrome is a systemic autoimmune condition characterized by ocular and oral dryness. It is one of the most common rheumatologic disorders in the USA and worldwide. Early diagnosis of Sjogren's is particularly important given the frequency and variety of associated autoimmune diseases and extraglandular manifestations. Furthermore, although inclusion body myositis has a low prevalence, it is the most common inflammatory myopathy in older adults and is unfortunately associated with long delays in diagnosis, so knowledge of this disorder is also crucial for practicing internists.

Abnormalities of signal transduction networks in chronic schizophrenia.

Schizophrenia is a serious neuropsychiatric disorder characterized by disruptions of brain cell metabolism, microstructure, and neurotransmission. All of these processes require coordination of multiple kinase-mediated signaling events. We hypothesize that imbalances in kinase activity propagate through an interconnected network of intracellular signaling with potential to simultaneously contribute to many or all of the observed deficits in schizophrenia. We established a workflow distinguishing schizophrenia-altered kinases in anterior cingulate cortex using a previously published kinome array data set. We compared schizophrenia-altered kinases to haloperidol-altered kinases, and identified systems, functions, and regulators predicted using pathway analyses. We used kinase inhibitors with the kinome array to test hypotheses about imbalance in signaling and conducted preliminary studies of kinase proteins, phosphoproteins, and activity for kinases of interest. We investigated schizophrenia-associated single nucleotide polymorphisms in one of these kinases, AKT, for genotype-dependent changes in AKT protein or activity. Kinome analyses identified new kinases as well as some previously implicated in schizophrenia. These results were not explained by chronic antipsychotic treatment. Kinases identified in our analyses aligned with cytoskeletal arrangement and molecular trafficking. Of the kinases we investigated further, AKT and (unexpectedly) JNK, showed the most dysregulation in the anterior cingulate cortex of schizophrenia subjects. Changes in kinase activity did not correspond to protein or phosphoprotein levels. We also show that AKT single nucleotide polymorphism rs1130214, previously associated with schizophrenia, influenced enzyme activity but not protein or phosphoprotein levels. Our data indicate subtle changes in kinase activity and regulation across an interlinked kinase network, suggesting signaling imbalances underlie the core symptoms of schizophrenia. DISEASE MECHANISMS: A SIGNALING IMBALANCE: A study by US scientists indicates that changes in the activity of key signaling proteins may underlie core symptoms of schizophrenia. Protein kinases mediate the activation of intracellular signaling events and analyses of the kinome, the complete set of protein kinases encoded in the genome, previously revealed significant changes in phosphorylation patterns in postmortem brain tissue from patients with schizophrenia. Based on these findings, Jennifer McGuire at the University of Cincinnati and colleagues investigated the upstream regulation of these proteins. They identified both established and novel proteins associated with schizophrenia in the anterior cingulate cortex, with JNK and AKT activity being the most disrupted in schizophrenia patients. Their findings highlight how subtle changes in the activity of a small number of signaling proteins can propagate and have major consequences for mental health.

Crosstalks between cytokines and Sonic Hedgehog in Helicobacter pylori infection: a mathematical model.

Helicobacter pylori infection of gastric tissue results in an immune response dominated by Th1 cytokines and has also been linked with dysregulation of Sonic Hedgehog (SHH) signaling pathway in gastric tissue. However, since interactions between the cytokines and SHH during H. pylori infection are not well understood, any mechanistic understanding achieved through interpretation of the statistical analysis of experimental results in the context of currently known circuit must be carefully scrutinized. Here, we use mathematical modeling aided by restraints of experimental data to evaluate the consistency between experimental results and temporal behavior of H. pylori activated cytokine circuit model. Statistical analysis of qPCR data from uninfected and H. pylori infected wild-type and parietal cell-specific SHH knockout (PC-SHHKO) mice for day 7 and 180 indicate significant changes that suggest role of SHH in cytokine regulation. The experimentally observed changes are further investigated using a mathematical model that examines dynamic crosstalks among pro-inflammatory (IL1ß, IL-12, IFNγ, MIP-2) cytokines, anti-inflammatory (IL-10) cytokines and SHH during H. pylori infection. Response analysis of the resulting model demonstrates that circuitry, as currently known, is inadequate for explaining of the experimental observations; suggesting the need for additional specific regulatory interactions. A key advantage of a computational model is the ability to propose putative circuit models for in-silico experimentation. We use this approach to propose a parsimonious model that incorporates crosstalks between NFĸB, SHH, IL-1ß and IL-10, resulting in a feedback loop capable of exhibiting cyclic behavior. Separately, we show that analysis of an independent time-series GEO microarray data for IL-1ß, IFNγ and IL-10 in mock and H. pylori infected mice further supports the proposed hypothesis that these cytokines may follow a cyclic trend. Predictions from the in-silico model provide useful insights for generating new hypothesis and design of subsequent experimental studies.