ADAM12, among CLL patients and normal individuals. We also evaluated the association between methylation of ADAM12 and clinical and demographic characteristics of the participants. Chronic Lymphocytic Leukemia (CLL) is a common leukemia among Caucasians but rare in Asians population. We postulated that aberrant methylation either hypermethylation or partial methylation might be one of the silencing mechanisms that inactivates the tumour suppressor genes in CLL. This study aimed to compare the methylation status of tumour suppressor gene, ADAM12 was determined using Methylation-Specific PCR (MSP); whereas, DNA sequencing method was applied for validation of the MSP results. A total of 25 CLL patients and 25 normal individuals were recruited in this study. The methylation status of ADAM12 and the presence of CLL (p=0.037). Among CLL patients, 12 (48%) were partially methylated and 13 (52%) were unmethylated. Meanwhile, 5 (20%) and 20 (80.6%) of healthy individuals were partially methylated and unmethylated, respectively. There was a statistically significant association between the status of methylation at ADAM12 found in this study using MSP assay may provide new exposure to CLL that may improve the gaps involved in genetic epigenetic study in CLL. The aberrant methylation of  A disintegrin and metalloproteinases (ADAMs) consist of more than 30 proteins of Metzincin family. They are all matrix zinc-dependent proteases enzymes, multifunctional proteins, and principally membrane-bound family of multidomain . In this family, there are forty gene members, and only 21 of them appear in human and is thought to function in human body . ADAMs family members have various roles, including cell signalling , protein processing , adhesion , fertility , and proteolytic shedding of receptor ectodomains . All these diversified multifunctions are reflected in their structures which can be subdivided into head, body, and tail. Head of the proteins consists of pro and catalytic domains. These domains mediate processing of growth factors and cytokines by ectodomain shedding and have been in charge of epidermal growth factor (EGF) and insulin-like growth factor (IGF) receptor signalling. The body of the proteins which consists of disintegrin, cysteine-rich, and EGF-like domains is in contact with the extracellular matrix and other cells through interactions with integrins and syndecans. The tail of the proteins which consists of cytoplasmic domain is in contact with the extracellular matrix and other cells through interactions with integrins and syndecans. The tail is also in interactions with signalling molecules. Furthermore, splice forms lie in some ADAMs, such as ADAM9, ADAM28, and ADAM12, shorter secreted and soluble forms have been discussed . ADAM12 gene is located on chromosome 10q26 in human gene and reported as meltrin α by , a protein involved in myoblast fusion. ADAM12 is up-regulated in bladder , stomach , and liver cancers . Through induction of stromal cell apoptosis, ADAM12 protein can stimulate the progression of breast tumour.ADAM12 is a proteolytic member of the ADAMs family that, as a result of alternate splicing, encodes for two different forms. Membrane-bound form (ADAM12-L) is the first form, which has different types of domains, including pro-domain, metalloproteinase domain, disintegrin domain, cysteine-rich domain, EGF-like domain, transmembrane region, and cytoplasmic tail . Another form is secreted one (ADAM12-S), which has all the aforementioned domains except the transmembrane and cytoplasmic domains . The ADAM12 controlled tumour progression in gene modified mice models . ADAM12 also has been recognized as one of the candidate cancer genes in a comprehensive mutational analysis on human breast cancer. In another study on 122 genes, it was found that this gene was mutated with high frequencies in breast cancers, there was only one ADAM gene, namely ADAM12 and the rest only 14 genes had a higher cancer mutation prevalence score than ADAM12. In the aforementioned study, it was suggested that ADAM12 had a critical function in breast cancer progression considering a high mutation frequency together with a strongly up-regulated expression of ADAM12 . Breast cancer cases are commonly associated with raised levels of ADAM9, ADAM12, ADAM15, ADAM17, and ADAM28 . The current study was attempted to first compare the status of hypermethylation in CLL patients and normal individuals and second to discover any associations between the hypermethylation status and demographic data. ADAM12 is highly expressed in tissues characterised by exaggerate growth, such as human placenta and tumours . Its expression is higher in malignant tumor cells, but lower in most normal adult tissues . It is also associated with the spreading and progression of human cancers . In three different studies, it was shown that Sample size estimationp16INK4a . In CLL patients group,14.3% exposure was based on the results of hypermethylation study on CLL patients in Hong Kong . The sample size required for the study controls to be able to reject the null hypothesis was 8 CLL patients and 8 normal. Our null hypothesis was that the exposure rates for CLL patients and controls were equal with probability (power) 95%. However, we considered CLL patients and controls. Therefore, the total number of participants was 50 in the current study.Sample size was estimated using sample size calculation software (PS software). The sample size for this research was calculated for a dichotomous independent case-control study with a ratio of 1:1 CLL patients and normal controls. Expected frequency of exposure was 89% and 14.3% in control group and CLL patients group, respectively. In control group, 89% exposure was based on the results of a hypermethylation study on blood mononuclear cells showing that 89% of the controls had hypermethylation at Patient selection and sample collectionIn this study, 25 peripheral blood samples were obtained from patients diagnosed with CLL at Universiti Sains Malaysia Hospital  and Ampang Hospital . In addition, twenty five peripheral blood samples were obtained from healthy donors without family history of cancer. All samples were in compliance with consent forms. DNA extraction® DNA Blood Mini kit . Extracted DNA had concentration up to 2000 ng/µl and purity among 1.8 – 2.0. The genomic DNA isolated from peripheral blood of both groups based on standard protocols.High-molecular weight genomic DNA was isolated from peripheral blood samples according to the manufacturer’s specifications of QIAampBisulfite treatment Bisulfite treatment of DNA is a complete deamination process of unmethylated cytosine, but not methylated cytosine to uracil . All original cytosines will be displayed as thymines; meanwhile, methylated cytosines will be remained as cytosines in the final sequence pattern. This treatment was carried out using commercially available kit, CpGenome Modification kit , and according to the manufacturer’s instructions. Briefly, 250 ng of genomic DNA was incubated in mild heated water bath at an alkaline pH. At this time, the DNA bases were first exposed to its single stranded form through denaturing process. After that, incubation was done for 16 hours which led to sulfonation and hydrolytic deamination processes, producing uracil sulfonate intermediate. The resultant DNA was bound to a micro-particulate carrier in the presence of another salt provided in the kit. The conversion was completed after desulfonation and repeated desalting. The DNA was finally eluted from the carrier by heating in 25 μl elution buffer. Methylation–Specific PCR (MSP)ADAM12 were designed using MethPrimer software. Details on the primers’ sequences are shown in 2, 0.2 mM dNTP, 0.5 u/µL AmpliTaq Gold DNA polymerase , 0.2 µM forward and reverse primers, approximately 50 ng of genomic bisulfite treated DNA template, and distilled deionised water (ddH2O). MSP amplification of all genes was done and optimised using the Touchdown PCR protocol and GeneAmp® PCR System 9700  machine under the following cycling conditions: 10 minutes initial denaturation (95°C), 14 cycles of 20 seconds denaturation (94°C), 1 minute annealing (variable temperature), and 1 minute elongation (72°C). Amplification was run for further 32 cycles of 20 seconds denaturation (94°C), 1 minute annealing (57°C), 1 minute elongation (72°C), and final elongation at 72°C for 5 minutes and storage at 10°C. Four µl of PCR products were loaded into 3% agarose gel, stained with Ultra Power DNA Stain , electrophoresed and visualized under UV light, and its picture was captured by a UV Transilluminator . Specific MSP primers for DNA sequencingAmplicon obtained from every MSP was considered as critical sample due to very high concentration and volume are needed prior to the purification and DNA sequencing. The PCR products were sent for DNA sequencing service  to validate the qualitative results observed from MSP assay. Statistical analysisThe statistical analysis was done to discover any associations between patients’ demographic data and clinicopathologic characteristics. The data were analysed using SPSS 21 and running Fisher’s Exact, Pearson Chi-square for categorical variables, and independent T-tests for continuous variables. Patients’ demographic data included in this study were age, gender, and race and patients’ clinicopathological data involved clinical features and current treatments. Demographic characteristics in CLL patients and controlsThe age of CLL patients and controls ranged between 52 to 78 years and 23 to 42 years, respectively.The mean ±SD of age for CLL patients and controls were 65.8 ± 7.8 years and 27.9 ± 4.3 years, respectively. The ratio of male to female among CLL patients was 2.1:1. Therefore, predominant among male was encountered . For clinical data, two categories were assessed, namely clinical features and current treatment. In this regard, characteristics such as lymphadenopathy, hepatomegaly, and splenomegaly were reviewed in CLL patients. Patients undergoing chlorambucil or prednisolone or both treatments were classified under active treatment. The distribution of CLL patients based on clinical features and current treatment is summarised in DNA concentration and genomic integrityThe genomic DNA samples from CLL patients, controls, and cell lines demonstrated a competitive concentration ranging between 20 and 1,400 ng/µL. The purity of the genomic DNA samples were between 1.7 and 2.0 (A260/A280). The genomic DNA samples were also evaluated for their integrity by performing standard gel analysis using 1% agarose gel.Determination of hypermethylation status of ADAM12ADAM12, the size of the amplified amplicon was 159 bp for both unmethylated (UM) and methylated (M) ADAM12. If any samples showed both unmethylated and methylated bands, the sample was partially methylated . Blank is PCR solutions with ddH20 as the replacement of sample. Each batch of MSP analysis was repeated in duplicate. Representative results on MSP analysis of the CLL patients and controls for ADAM12 are shown in All 50 bisulfite treated DNA samples were screened for the hypermethylation status using MSP analysis. For DNA sequencing analysisADAM12 are shown in Patient samples of MSP analysis that gave the most prominent band during gel electrophoresis were subjected to DNA sequencing. The purpose of this DNA sequencing was to validate the methylation status detected by MSP assay. Sequencing results for partially methylated and unmethylated Determining the association between hypermethylation status and demographic and clinical characteristics in CLL patientsThe results on association between the demographic data  and clinical characteristics  and hypermethylation status of CLL patients are displayed in ADAM12 and CLL was detected in this study (p=0.037). In a previous microarray study on CLL disease, Rahmatpanah et al., (2009) found that ADAM12 was methylated in CD38highpatients and high-risk CLL patients showed 31-92% of CD38 expression. Interestingly, they also discovered methylation of ADAM12 in a CLL patient’s cell line. This cell line was initially induced by cytokines and subsequently infected with Epstein-Barr virus. Association between CD38 expression and aggressive clinical behaviour of CLL was confirmed in two other studies . It is commonly accepted that CD38+ patients show poor prognosis, therefore, they usually have a shorter progression-free interval, need earlier and recurrent treatments, and eventually die sooner . In this study, it was revealed that methylation of ADAM12 was associated with aggressive progression of CLL and it can be contributed to the advance symptoms of CLL. ADAM12 has a variety of functions in normal cells, such as multidomain and signaling properties. However, it is excessively expressed in uncontrolled growing cells, such as breast cancer  and other tumours. Despite these findings, studies on ADAM12 in haematological disease are scarce when compared with non-haematological diseases, which makes the role of ADAM12 in CLL patients remains ambiguous. However, the association of ADAM12 methylation with CLL can be supported by the fact that CLL progression is slower than other cancers, suggesting methylation of ADAM12 may contribute to the speed of disease progression. A significant association between hypermethylation status of ADAM12 regulated tumour progression in gene-modified mice models . A combination of high mutation-frequency and a strongly up-regulated expression of ADAM12 in breast cancer suggest that this gene may enhance progression of breast cancer . ADAM12 in breast cancer was among the first of ADAMs shown to have diagnostic potential. Roy et al., (2004) found that urinary levels of ADAM12 were clearly higher in breast cancer patients compared to healthy groups and the proportion of breast cancer patients having high urinary level of ADAM12 was clearly greater than the healthy groups. Follow-up studies reported the same result in patients with putative premalignant lesions of invasive breast cancer, such as atypical hyperplasia and lobular carcinoma in situ and control groups . Apart from that, urinary level of ADAM12 was also found to be elevated in patients with bladder cancer . Among the non-haematological findings on ADAM12 are a table of expression of a disintegrin and metalloproteinases (ADAMs) in human cancers and their possible functions. Therefore, it is suggested that ADAM12 functions as a sheddase, adhesion molecule, and ECM-degrading proteinase, and is involved in cancer progression . ADAM12 is expressed in high amounts in excessively growing cells, including human placenta and tumours; whereas, the opposite happens in normal tissues . Therefore, it is associated with the metastasis of human cancers . It was proven that Bisulfite-based DNA methylation analysis has higher quantitative accuracy, detection sensitivity, and efficiency. It has a wide spectrum for sample analysis when compared with restriction enzymes-based assays . An MSP analysis is a simple method without using costly sequencing reagents and exposure to radioactivity. It does not involve many sub-techniques and requires shorter time to be completed in order to obtain the actual hypermethylation status of samples. Another reliable and sensitive assay for hypermethylation detection is methylation sensitive-high resolution melting (MS-HRM) . In the MS-HRM analysis, samples are bisulfite treated and PCR amplified before they are subjected to MS-HRM assay. MS-HRM compares melting profiles of unknown PCR products to known products which are amplified from both unmethylated and methylated DNAs. Despite these advantages, this study did not utilise MS-HRM as MSP also has the advantages of being rapid and sufficiently sensitive. Besides, it is an economical technique. MSP also has the benefit of being highly sensitive due to its ability to detect single methylated allele among more than 1,000 unmethylated alleles . The fragments selected for MSP amplification are intentionally kept small so as to examine patterns of methylation in limited region and to conduct investigation where amplification of larger fragments is not possible. It requires the regular equipments that can be found easily in any laboratory, which makes the MSP protocol less complex when compared with MS-HRM that requires HRM machine.Compared to Southern analysis, MSP is also significantly more sensitive. It can detect low numbers of methylated alleles from reduced quantity of DNA samples, such as the paraffin-embedded materials. This type of sample could not be analysed previously by Southern analysis . MSP permits analysis of all CpG sites within a whole genome, not just those within short sequences identified by methylation-sensitive restriction enzymes, allowing the fine mapping of methylation patterns throughout CpG-rich regions. MSP also can eliminate the common false positive results due to inherent partial digestion of PCR products by methylation-sensitive restriction. An extra advantage of MSP is its immediate determination of unmethylated and methylated products in a single sample that can be used to verify the integrity of DNA as a template for PCR, thus permitting a semi-quantitative assessment of allele types that are close to the quantitation determined by Southern analysis . MSP also exhibits a higher sensitivity  when compared with mutation and microsatellite analysis for the detection of tumour cells in one thousand normal cells . Other advantage of MSP is that it can determine DNA methylation pattern of double stranded DNA since the bisulfite treated DNAs are no longer self-complementary and the amplification of products can be measured individually . ADAM12 was one of the targets for hypermethylation in CLL. Future studies investigating the epigenetic marker in more heterogenous sample size are warranted to determine whether epigenetic dysregulation occurs in the CLL patients of Asians population or not. In conclusion, this study adds to the abundance findings of CLL and also the methylated genes specific for it. It was also able to fill many literature gaps in the genes studied for CLL. In summary, in this study, it was found that


We describe the clinical implementation of genome-wide DNA methylation analysis in rare disorders across the EpiSign diagnostic laboratory network and the assessment of results and clinical impact in the first subjects tested.We outline the logistics and data flow between an integrated network of clinical diagnostics laboratories in Europe, the United States, and Canada. We describe the clinical validation of EpiSign using 211 specimens and assess the test performance and diagnostic yield in the first 207 subjects tested involving two patient subgroups: the targeted cohort  and the screening cohort .Among the 207 subjects tested, 57 (27.6%) were positive for a diagnostic episignature including 48/136 (35.3%) in the targeted cohort and 8/71 (11.3%) in the screening cohort, with 4/207 (1.9%) remaining inconclusive after EpiSign analysis.This study describes the implementation of diagnostic clinical genomic DNA methylation testing in patients with rare disorders. It provides strong evidence of clinical utility of EpiSign analysis, including the ability to provide conclusive findings in the majority of subjects tested. Despite concerted efforts to standardize guidelines for the interpretation of sequence variants5 and to define the functional evidence for variant classification,6 a large proportion of VUS remain without conclusive clinical interpretation. Also, the understanding of the impact of genetic variation outside of protein-coding DNA sequences is very limited, and as such, the majority of genetic testing in clinical laboratories is focused on exonic and short surrounding intronic sequences. Family variant cosegregation studies, in silico prediction algorithms, and gene-specific functional studies may help resolve VUS findings, but in the majority of cases these are not available, feasible, or conclusive.Evolution of genetic testing from single-nucleotide assessment to clinical exome and genome sequencing, while increasing the diagnostic yield to an average of 36%,7 DNA methylation is an epigenetic modification, resulting in changes in structural and chemical properties of the DNA, impacting molecular mechanisms including chromatin assembly and gene transcription.8 Our group and others have demonstrated that individuals among a growing number of rare disorders exhibit DNA methylation “episignatures” or “EpiSigns” as highly sensitive and specific DNA methylation biomarkers.22 These genome-wide DNA methylation profiles currently include over 40 rare disorders in association with more than 60 genes, and can be gene domain, gene level, as well as protein complex specific. DNA methylation episignatures are detectable in peripheral blood and are highly sensitive and specific for each disorder. As such, they represent effective biomarkers for the testing of patients with a broadening range of neurodevelopmental genetic conditions, as well as a reflex functional test for patients with ambiguous genetic test findings or clinical phenotypes.23One functional consequence of genetic defects in patients with hereditary neurodevelopmental disorders is the disruption of genomic DNA methylation.24 and fragile X syndrome,25 enabling further test consolidation in this patient population. One key technical challenge in the clinical setting is data analysis. This requires the development of large-scale reference DNA methylation databases, including disorder and tissue-specific reference data sets and controls, and sophisticated analytical processes including machine learning algorithms as analytical classifiers. Testing must be performed in a regulated clinically certified environment, with adherence to the required quality management procedures, and clinical quality metrics, all under professional clinical oversight.Genomic DNA methylation analysis is also adaptable to the routine analytical processes in clinical laboratories. Cytosine methylation is a highly stable analyte, and genome-wide DNA methylation data can be generated on a microarray platform. In parallel with episignature screening, genomic DNA methylation analysis enables concurrent and highly sensitive and specific assessment of imprinting disordersIn this study we describe the implementation and validation of EpiSign, a clinical genome-wide DNA methylation test for patients with rare Mendelian disorders, based on the Illumina Infinium methylation array technology and the EpiSign Knowledge Database (EKD). We describe the quality metrics and clinical validation metrics within an integrated network of licensed academic nonprofit clinical laboratories in Europe, Canada, and the United States. We describe the clinical performance and the diagnostic yield in subjects tested between initiation of the service in November 2019 to June 2020. This study demonstrates the clinical utility of genomic DNA methylation testing in patients with Mendelian neurodevelopmental disorders.5 Technical inter and intrarun replicates were assessed for concordance based on methylation variant pathogenicity (MVP) score (within 0.05) and clustering analysis. The clinical testing cohort  and Amsterdam University Medical Center and partner labs . Data from validation and clinical testing specimens (November 2019 and June 2020) were blinded and submitted to the clinical bioinformatics laboratory  through a secure file transfer protocol and housed on the hospital clinical encrypted servers.DNA methylation analysis was performed using the Illumina Infinium EPIC bead chip arrays as previously describedhttps://www.lhsc.on.ca/palm/molecular.html). Individual DNA methylation data for each subject were compared with the EKD using the support vector machine (SVM) based classification algorithm for EpiSign disorders. Methylation variant Pathogenicity (MVP) score is generated ranging between 0 and 1, representing the confidence of prediction for the specific class the SVM was trained to detect. Conversion of SVM decision values to these scores was carried out according to the Platt scaling method.26 Classification for a specific EpiSign disorder included MVP score assessment with a general threshold of >0.5 for positive, <0.1 negative, 0.1–0.5 inconclusive or low confidence, hierarchical clustering and the multidimensional scaling (MDS) of subject’s methylation data relative to the disorder-specific EpiSign probe sets and controls. A detailed description of this analytics protocol was described previously.27Analysis of the DNA methylation array data was performed by the clinical bioinformatics laboratory using Illumina Infinium EPIC arrays. Methylation data for each sample were compared to the established DNA methylation episignatures for the 43 disorders Table  which arDNA methylation analysis results were clinically verified by a board-certified clinical molecular geneticist at the clinical bioinformatics laboratory. Result categories include positive (matching an EpiSign disorder), negative (not matching any EpiSign disorder), and inconclusive (described in detail in results). The report is then reviewed and verified by a board-certified laboratory professional in the clinical testing laboratory, and a clinical report describing the EpiSign results  is issued to the requesting physician.KANSL1 (NM_001193466.1): c.297_307del; p.Gly100Glnfs*6, related to Koolen–de Vries syndrome (KDVS), and another subject  with a previously reported likely pathogenic variant, CREBBP (NM_004380.2):c.4480C>A; p.Pro1494Thr, related to the Rubinstein–Taybi syndrome (RSTS). In the case Val118 with the KANSL1 likely pathogenic variant, and clinical features consistent with KDVS, the MVP score for KDVS was zero. Some individuals carry a duplication harboring part of the KANSL1 gene elsewhere in the genome, which may cause variants in the duplicated region to be erroneously assigned to the KANSL1 gene. However, assessment of exome sequencing data, array comparative genomic hybridization (array CGH), and multiplex ligation-dependent probe amplification (MLPA) analysis showed no evidence of this this duplication. The MVP score in the second case, Val26, with CREBBP(NM_004380.2):c.4480C>A, p.(Pro1494Thr), for RSTS was zero. Potential mosaicism of the CREBBP variant was not apparent. The remaining two discordant cases  both had previously identified SMARCC2 pathogenic variants. Fifty-six samples were normal reference controls (NC) and were all concordant. The remaining 12 samples (other controls in Table ARID2 pathogenic variant. There were 10 interrun duplicates (samples processed in different array batches) and 18 intrarun duplicates (replicate samples processed in the same batch), and all were concordant. EpiSign v2 validation included 55 replicates of samples used in v1 validation and all were concordant.The 211 validation specimens are described in Table EpiSign analysis includes genetic conditions that exhibit DNA methylation episignatures as well as the common imprinting disorders and fragile X Table . A totalSMC1A, the causative gene for Cornelia de Lange syndrome (CdLS) type 2, SMC1A:c.598A>C, p.(Lys200Gln) and SMC1A:c.1280A>G, p.(Glu427Gly). The SMC1A:c.598A>C, p.(Lys200Gln) variant was reclassified as likely pathogenic, ACMG category 2, and the SMC1A:c.1280A>G, p.(Glu427Gly) variant did not show evidence of pathogenicity based on the current reference episignatures. Other examples depicted in Fig. NSD1, the causative gene for Sotos syndrome type 1, NSD1:c.4982G>C, p.(Cys1661Ser) and NSD1:c.3331G>T, p.Asp1111Tyr. The NSD1:c.4982G>C, p.(Cys1661Ser) was reclassified to likely pathogenic, ACMG category 2, while NSD1:c.3331G>T, p.Asp1111Tyr, which clusters with controls, showed no evidence of pathogenicity. Similar analysis is performed for all subjects tested with findings summarized in Table Figure ARID2:c.988_1008del, p.(Leu330_Gly336del) VUS. MVP score for BAFopathy using the EpiSign v1 was slightly elevated (0.2) but below the established 0.5 cutoff and above the 0.1 cutoff for reference normal controls. The updated EpiSign v2 reanalysis showed no evidence of the elevated BAFopathy score; however, MRD23 score remained elevated. MDS profile showed clustering between BAFopathy cohort and controls  VUS. The ADNP gene has two distinct EpiSigns11 as a result of truncating variants in two distinct protein domains; the 5’ being defined by the variants ranging from c.56 to c.1287. The MVP score for this subject was 0.03, which is within the normal range, but MVP scores for all other conditions were zero. Due to the strong hypomethylation observed with this episignature, MDS analysis clearly separates the reference from the positive cohort, and this sample plots between the two , negative microarray, and negative exome analysis with the phenotype strongly suggestive of CHARGE syndrome. EpiSign analysis identified a DNA methylation profile specific for CHD7, consistent with the clinical diagnosis  are described in a separate manuscript in preparation. Hence, EpiSign analysis provided the necessary evidence for a more in-depth and focused molecular analysis, ultimately leading to the definitive molecular genetic diagnosis.A similar scenario with a different outcome involves subject Clin6 who was referred for EpiSign analysis as a result of negative molecular sequencing  VUS, maternal; VPS13B:c.1520A>G (p.Asn507Ser) VUS, paternal; LAMC3:c.4415G>A (p.Arg1472Gln), maternal; EZH2:c.2110+6T>G VUS, maternal; and normal findings for: FMR1, MECP2, SNP 6.0 microarray, NSD1 (sequencing and MLPA), extensive biochemical workup, and X-inactivation studies. However, EpiSign analysis showed an episignature associated with DNMT3A, the gene involved in Tatton–Brown–Rahman syndrome . As an infant, the patient met motor and speech milestones but regressed at 18 months, losing speech, attentiveness, and responsiveness to directions. Now at age 17 years, she has overgrowth , limited speech, echolalia, mild intellectual disability, and autism spectrum disorder.Case Clin187 highlights an example where extensive molecular genetic testing was performed without a molecular diagnosis, referred to as a diagnostic odyssey. Findings included exome sequencing with 29 and fragile X syndrome30 have been around for decades, EpiSign enables simultaneous assessment for these, as well as a rapidly expanding number of genetic neurodevelopmental disorders exhibiting DNA methylation episignatures.This paper describes the implementation of genome-wide DNA methylation analysis in clinical testing of individuals with rare genetic disorders. It represents a major milestone in molecular diagnostics as it advances clinical genetic testing beyond assessment of the DNA nucleotide sequence, or genomics, to clinical epigenomics. While targeted molecular assays for assessment of DNA methylation defects of imprinting disorders15 and the assessment of genetically unsolved individuals with suspected hereditary conditions.14 While this clinical utility has been described in a research setting in targeted patient cohorts, this study focuses on the assessment of the impact of genome-wide DNA methylation analysis in a clinical setting in a prospective unselected patient population. The majority of the subjects tested in the clinical cohort  had previously identified genetic VUS, and of these, 134 (98.5%) received a conclusive EpiSign report (positive or negative), of which 48 (35.3%) showed a distinct EpiSign. For the 86 (63.2%) VUS cases with negative EpiSign results, lack of an episignature is considered strong evidence for rule out of these disorders. However, due to the possibility of the existence of additional/alternate yet unmapped episignatures in these genes, as has been demonstrated in ADNP11 and SMARCA2,31 we currently stop short of fully ruling out pathogenicity. Only 2 (1.5%) VUS cases remained unclassified. These findings represent a significant advancement in clinical variant assessment over currently available methodologies. While alternative approaches for classification of VUS exist, including functional and family segregation studies, these are not always available, feasible, or conclusive.32 EpiSign analysis is less susceptible to those limitations as it assesses the same tissue  used for sequence analysis, and it generally does not require assessment of other family members. From a patient, family, and clinical management perspective, providing the patient and care team with a rapid diagnosis relating to the functional impact of the genetic condition, which for a microarray-based test can be achieved within 1–2 weeks, may be most beneficial to decision-making.The primary clinical utility of EpiSign analysis is the assessment and reclassification of VUS in genes with existing episignatures,Of the remaining 71 subjects without the previously identified genetic findings, 8 subjects (11.3%) had a positive EpiSign result, demonstrating evidence for the clinical utility of EpiSign analysis in a broader patient population. Given that these subjects already had varying degrees of targeted genetic investigations completed with no conclusive findings, some of the EpiSign disorders had effectively been ruled out already. These findings taken together suggest there may be a health systems value proposition of instigating use of EpiSign earlier in the diagnostic journey of individuals with rare disorders.34 Similarly, there are now major efforts underway to assess the clinical utility and the health systems impact, and to accelerate the rate of episignature discovery including a national-scale trial , which will compare the impact of DNA methylation analysis as a first-line versus a second-line test in 4,000 individuals with suspected rare disorders while assessing EpiSigns in 100 additional genetic conditions .Application of this technology to the broader patient populations will depend on the rate of discovery of gene and disorder-specific episignatures. As a corollary, implementation of chromosomal microarrays as a first-tier diagnostic test was primarily contingent upon increased diagnostic yield compared with karyotyping (from 5% to 10–15%) resulting from years of research and discovery of novel microdeletion and duplication syndromes, often involving large clinical databases and registries.14 Existence of a specific DNA methylation pattern can guide the molecular assessment, and in some cases resolve complex diagnostic odysseys, which can have a huge impact on patient care and the related health systems costs.36The clinical cases presented in detail highlight some important implications of this technology. One is the sequential use of EpiSign analysis with genetic testing. While using EpiSign to investigate individuals with VUS or related clinical presentations provides demonstrated value, EpiSign can also uncover genetic disorders that were not initially suspected. We have previously demonstrated an incremental diagnostic yield of approximately 3% in patients with prior extensive genomic testing but without a genetic diagnosis.37 The key benefits of this model involve standardization and coordinated quality management and quality assessment procedures, ensuring consistency across the different provider laboratories, which is critical given the inherent nature and complexity of this analysis. This also allows for more rapid expansion of reference DNA methylation databases and facilitates continuous optimization of the underpinning analytical algorithms. As the EKD expands, the reference machine learning–derived algorithms that form the basis of individual EpiSigns become more sensitive and specific,9 enabling regular and documented updates to the analytical software, with the appropriate quality metrics and quality control documentation and version controls.EpiSign testing is performed using an integrated model involving primary labs performing and reporting test results with informatics and databasing centralized in the tertiary clinical bioinformatics laboratory, similar to the field of noninvasive prenatal testing for aneuploidy.39There are a number of challenges related to introducing a diagnostic modality to the clinical laboratory, and EpiSign is not an exception. Unlike DNA sequencing, DNA methylation analysis is limited to peripheral blood where large reference databases are available. Other factors including age, sex, and environmental exposures can also impact the analysis and need to be accounted for in analytical processes.24 and fragile X,25 at levels >20%, but due to normal control variability  may be explained by the variant not actually being pathogenic, or an existence of a yet unmapped episignature in this gene.DNA methylation episignatures can be susceptible to technical variation such as sample processing data batch effects, as well as biological parameters such as mosaicism. The validation cohort included a number of low-level mosaic imprinting disorders that may not be readily detectable by the EpiSign assay. In our previous work we were able to detect mosaicism in imprinting disordersy Figure , this isARID1B, ARID1A, SMARCB1, SMARCA2, and SMARCA4.17 Hence, it is not possible to completely rule out pathogenicity of a variant of another BAF complex gene as for the case with the ARID2 variant. An alternative scenario is highlighted by ADNP, which was the first gene in which the existence of multiple, domain-specific episignatures was described.11 Although majority of the EpiSign genes currently have a single common episignature mapped, assessment of pathogenicity of variants outside the established reference range and variant type warrants caution, as in the inconclusive case Clin203.Other biologically based limitations of EpiSign analysis can be highlighted by the four inconclusive samples from the clinical testing cohort. The current BAFopathy episignature is trained on positive cases with pathogenic variants in 40 Generation of EpiSigns requires cohorts of subjects with gene-specific pathogenic variants, which is currently possible for the more prevalent disorders. Also, as many of the episignatures are mild in scale, the size of the reference cohort is directly correlated to the level of sensitivity of the assay. Hence, occasionally, as in the case Clin120 for example, the results may be inconclusive.An overarching challenge with this technology is the rarity of Mendelian disorders. While the population prevalence of rare diseases is 3.5–5.9%, equating to 263–446 million persons affected globally, given that this number encompasses >5,000 diseases, the prevalence of rare disorders ranges between 1–5 per 10,000 and <1/1,000, 000.6 there are currently no specific guidelines for the clinical interpretation of genomic DNA methylation findings. EpiSign employs the use of DNA methylation data as a surrogate for evidence of the underpinning genetic defects that may or may not be detectable using the current molecular testing modalities. Another challenge is that our current knowledge of the full scope of these genetically associated epiphenotypes is limited. Hence, while on the one hand a confirmation of a related episignature in a patient with a genetic VUS may be considered a molecular diagnosis, a negative result in a patient with or without a known genetic variant is not an absolute rule-out and the analysis would be considered a molecular screen. A more complex challenge is a confirmation of an episignature in absence of a detectable genetic variation, in particular when it is observed in a patient with a matching clinical diagnosis. In this case EpiSign is the standalone molecular diagnosis.While the recommendations for application of the functional evidence in genetic testing now exist,This study describes the implementation of clinical genomic DNA methylation testing in patients with rare disorders. It demonstrates strong evidence of clinical utility, including the ability to provide conclusive diagnoses in a significant proportion of subjects tested. It also highlights the limitations and challenges with implementation and use of this diagnostic modality. As this technology evolves, the number and type of rare disorders with EpiSigns is going to expand, increasing its clinical utility. While the current clinical use of EpiSign focuses on cases with VUS, and very specific clinical presentations, expanding clinical utility of this test may justify its application earlier in the diagnostic journey, in a broader patient population. Larger-scale studies, such as EpiSign-CAN, are necessary to assess the diagnostic yield and health system impact as either a first-line test or in unresolved cases post–genomic assessment. Finally, the development of clinical guidelines for use and application of clinical epigenomic technologies is warranted.Supplementary FiguresTable S1Table S2


In the reservoir, species were more constrained in δ15N and differed more in δ13C, representing a shorter, wider food web. Differences in energetic pathways and resource availability among habitats likely contributed to differences in isotopic niches. Endangered Razorback Sucker (Xyrauchen texanus) aggregate at some reservoir inflows in the Colorado River basin, and this is where we found the highest niche overlap among species. Whether isotopic niche overlap among adult native and nonnative species has negative consequences is unclear, because data on resource availability and use are lacking; however, these observations do indicate the potential for competition. Still, the impacts of diet overlap among trophic generalists, such as Razorback Sucker, are likely low, particularly in habitats with diverse and abundant food bases such as river-reservoir inflows.Instream barriers can constrain dispersal of nonnative fishes, creating opportunities to test their impact on native communities above and below these barriers. Deposition of sediments in a river inflow to Lake Powell, USA resulted in creation of a large waterfall prohibiting upstream movement of fishes from the reservoir allowing us to evaluate the trophic niche of fishes above and below this barrier. We expected niche overlap among native and nonnative species would increase in local assemblages downstream of the barrier where nonnative fish diversity and abundance were higher. Fishes upstream of the barrier had more distinct isotopic niches and species exhibited a wider range in δ Nonnative fishes, for example, can have wide ranging effects4, including altering energetic pathways and changing food web structure6. Gauging the impact of biological invasions is relatively straightforward for top predators that consume native species7, but assessing impacts occurring through indirect effects of competition are more difficult to identify. Evidence from stable isotope analysis suggests that native species often shift their trophic niche in the presence of nonnative species, presumably to less preferred, lower quality resources10. Competitive interactions between species with similar trophic niches occupying the same habitat might lead to exclusion unless species partition resources13, but direct evidence of competition in the wild is difficult to detect15. Still, food web studies can provide important information on potential species interactions and elucidate impacts of nonnative species on native assemblages15.Nonnative species have been widely introduced into freshwater habitats, presenting one of the most significant and persistent threats to native species18, but these gradients are often altered by river regulation20. Construction of dams and reservoirs have transformed riverscapes into a mosaic of lotic and lentic habitats21, frequently leading to changes in fish assemblage composition both downstream and upstream of dams22. Further, water development has resulted in discontinuities in resource gradients25, created new resource gradients26, and facilitated introduction and proliferation of nonnative species27. These alterations have changed natural habitat gradients  and increased the number of potential competitors31. Habitat alterations have also led to reduction and homogenization of niche space resulting from decreased trophic diversity and shortening of food chains in some river systems32, while species introductions have caused lengthening of food chains in others34.Fish assemblage and food web structure can change across habitat and trophic resource gradients that shift longitudinally in rivers36, yet evidence of competition is often missing in research of freshwater systems, partially because of a lack of data on trophic resource use and availability. Moreover, because of their rarity and conservation status, it is often difficult to directly assess the diet of imperiled species39, limiting our understanding of impacts of nonnative species as resource competitors. Non-lethal and less intrusive techniques, such as stable isotope analysis, provide an alternative approach to compare overlap in trophic resource use of fishes40. For instance, δ13C reflects organic matter sources, such as autochthonous versus allochthonous primary production in streams41 or pelagic versus benthic primary production in lakes42, but the δ13C values of these sources can sometimes overlap43. Meanwhile, δ15N can provide an estimate of trophic position45, and several informative analytical metrics have been developed to quantify isotopic niche breadth  and trophic overlap among species in an assemblage48.Our understanding of trophic resource use by some imperiled fishes and their overlap with nonnative fishes is limited. Predation and competition are the most often cited effects of nonnative species49. Novel habitats in the basin, such as large water-storage reservoirs, serve as sources for nonnative species, but some native species also appear to be using river-reservoir inflow habitats51. Previous research identified overlap in resource use between younger life stages of native  and nonnative species  in the upper Colorado basin53, but data on large-river, federally endangered species, such as Colorado Pikeminnow (Ptychocheilus lucius) and Razorback Sucker (Xyrauchen texanus) are more limited, likely because of their rarity in the system.Nonnative species introductions and habitat alteration are the leading hypothesized drivers for native fish imperilment in the Colorado River basin in the American Southwest55. This created a rare opportunity to compare relative positions of species in trophic niche space in the river above this barrier, where the assemblage is dominated by native fishes, and in the river and reservoir below the barrier, where the assemblage is dominated by nonnative fishes. We had three objectives in this study. First, we identified differences in mean isotopic signatures of fishes within habitats, and expected species isotopic niches would reflect differences in resource use. Second, we quantified isotopic niche breadth of species within habitats, and predicted wider isotopic niche breadth for all species in the reservoir, because this habitat consists of areas with both detritus-based and algae-based food webs . Finally, we assessed niche overlap between pairs of native and nonnative fishes within habitats. We predicted trophic niche overlap between native and nonnative species would be greatest in the reservoir, because of the higher diversity and relative abundance of nonnative fish species , and predicted overlap would decrease moving upstream into riverine habitats. We were primarily interested in assessing isotopic niche overlap among X. texanus and other benthic omnivores that might occupy a similar trophic position . We also included data on P. lucius because of its conservation status, and a lack of data on trophic resource use of this species in the wild53. Both species are the focus of conservation and recovery efforts and use riverine and reservoir inflow habitats in the basin50. Tissues from other nonnative species (fishes and quagga mussels Dreissena rostriformis bugensis) were collected, but in only one of the three habitats so we excluded these from analyses and present these data for reference in the Electronic Supplementary Material . The middle habitat began directly below the Piute Farms Waterfall (hereafter river downstream) and included 21 rkm of the San Juan River and Lake Powell inflow. This habitat consisted of lower gradient (0.6 m km−1), slowing velocity, and turbid lotic habitats at the upper end of the reservoir . The last, and most downstream, habitat also occurred in the San Juan River–Lake Powell inflow across 15 rkm, and encompassed gradients of decreasing turbidity and increasing channel width and depth (here after reservoir)51.In 2018 and 2019, we sampled fishes and collected tissues for stable isotope analysis across 135 river kilometers (rkm) of the San Juan River, including the San Juan River arm of Lake Powell in southeastern Utah , and permitting from the U.S. Fish and Wildlife Service (TE067729-6), Navajo Nation , and National Park Service (GLCA-2017-SCI-0003).We collected pectoral fin tissues from the distal end of the fin for isotope analysis from fishes captured in the river upstream and river downstream habitats in March (13–31), April (1–2), June (8–10), and September (22–28) in 2018 using raft electrofishing , and from reservoir fishes in April and May 2019 captured in trammel nets . Fin tissues typically have an isotopic half-life of several months for both δ60, we prepared salt-preserved tissues by rinsing tissues with distilled water and soaking them in distilled water for 4 h. In the laboratory, we dried tissues (60 °C for ~ 8 h), homogenized tissues with a mortar and pestle, and packed samples into tin capsules, and weighed to the nearest 0.1 mg. We analyzed tissues for carbon and nitrogen stable isotope ratios. Tissues collected from the reservoir were analyzed at the Stable Isotope Mass Spectrometry Laboratory, Kansas State University, Manhattan, Kansas by continuous-flow, direct combustion, and mass spectrometry using an Elementar Vario Cube elemental analyzer coupled to an Elementar Vision mass spectrometer . Tissues collected from the river upstream and river downstream habitats were analyzed at the Utah State University Department of Geology Stable Isotope Laboratory, using a Thermo Scientific Gasbench II or Costech ECS4010 elemental analyzer  coupled to a Thermo Scientific Delta V Advantage IRMS . We report data on a per mille basis (‰) in delta (δ) notation. We calculated delta values as:R is equal to 13C/12C and 15N/14N. We used laboratory standards calibrated against international standards: Pee Dee Belemnite was the standard for carbon and atmospheric molecular nitrogen was the standard for nitrogen. Measurement error on routine analysis of laboratory standards was less than 0.50‰ for both δ13C and δ15N. For comparison, we also ran duplicate samples (n = 4) at both stable isotope laboratories and these differed on average by 1.4‰ (CV = 0.4) for δ13C and 0.58‰ (CV = 0.08) for δ15N.We either air-dried tissues or preserved them in table salt in the field. Following−1), and then calculated relative abundance as the catch per unit effort of native species divided by the total catch per unit effort. Both capture techniques tend to target large-bodied fishes and are biased against smaller fishes61; therefore, we removed Red Shiner (Cyprinella lutrensis) and Western Mosquitofish (Gambusia affinis), two small-bodied species, from the dataset before calculating relative abundance. We tested for differences in native species relative abundance among habitats using a linear mixed effect model using the lme4 package62. We logit transformed proportional data prior to fitting the model, and included reach as a fixed factor and a random intercept of month nested within year. We used likelihood ratio tests with the car package63 to estimate statistical significance (α = 0.05).To assess fish assemblage composition across our study area, we quantified variation in relative abundance of native species across our three habitats. We used species relative abundance because sampling methods differed between the river (raft electrofishing) and reservoir (trammel netting) habitats. We first transformed catch data into catch per unit effort . Finally, using the piecewiseSEM package64, we calculated variance explained by fixed factors using marginal R2 and fixed and random factors together using conditional R265.We tested for differences in species isotopic niche positions within habitats by separately comparing values of δ13C and δ15N as a measure of isotopic niche breadth of each species in each reach. We calculated standard ellipse areas corrected for sample sizes (SEAc) using the SIBER package47. Standard ellipses represent the core trophic niche of a species and encompass roughly 40% of the samples in a group regardless of the sample size47. To estimate niche overlap between native and nonnative species pairs in each reach we used the nicheROVER package66. This analysis uses a Monte Carlo resampling routine  to randomly draw from the sampled population and calculates a mean and 95% credible interval of niche overlap probabilities. These values are directional in that they represent the estimated probability a randomly drawn individual of one species overlaps with the niche of another species in δ13C and δ15N bivariate space48. All analyses were conducted using the R statistical language version 3.5.367.We used standard ellipse area of δF2,112.87 = 21.37, P < 0.001; Fig. C. carpio was 4× greater in the river downstream than the river upstream. The one exception was Channel Catfish , which was 20× more abundant upstream of the waterfall relative to the river downstream in late March and early April.Fish assemblage composition changed distinctly along our study area. As expected, nonnative species were more dominant towards the reservoir and relative abundance of native species declined from upstream to downstream . δ15N values, on average, differed significantly among some species in all habitats  compared to the reservoir . Conversely, the fixed effect of species contributed to a relatively low proportion of the explained variation in δ15N in the reservoir  compared to the river upstream  and river downstream  and C. carpio (325%) was still larger compared to the river upstream, but SEAc was 20% and 30% lower relative to the river downstream, respectively. The SEAc of Gizzard Shad (Dorosoma cepedianum) increased by 56% from the river downstream to the reservoir. Relative to all other species X. texanus had the most consistent niche breadth across habitats ranging from 7.96 in the river upstream to 6.46 in the river downstream to 7.39 in the reservoir .Variation in species overlap in isotopic space was apparent along the river-reservoir inflow gradient that coincided with changes in fish assemblage composition and likely variation in diversity of energetic pathways moving from lotic to lentic habitats. Along with increases in dominance of nonnative fishes, we observed increased isotopic niche overlap in the river and reservoir downstream of the waterfall compared to the river upstream where we observed lower nonnative fish relative abundance and occurrence. The Piute Farms Waterfall is a complete barrier to upstream fish movement71. The two native suckers demonstrated the highest probability of overlap with other species across all habitats, likely due to a more generalist feeding strategy. In contrast, P. lucius, a presumed piscivore72, exhibited a relatively small probability of overlap with other species, but this was dependent on the habitat. Some nonnative species, such as I. punctatus, are hypothesized to limit populations of native fish in the Colorado River basin through predation74. Our results suggest relatively little overlap between P. lucius, the species with the highest δ15N in the river upstream and I. punctatus, and supports other observations of limited piscivory by I. punctatus in the San Juan River74. Although we observed more overlap among species in the two habitats downstream of the waterfall, we do not expect competition is a strong driver of assemblage dynamics as river-reservoir inflows are not likely resource-limited76. Because native fishes in the Colorado River basin tend to be trophic generalists77, they might be less susceptible to competitive exclusion by nonnative species despite overlap in isotopic niche space. Fishes in the Colorado River basin likely evolved to capitalize on resource availability that varied across space and time, including across lotic-lentic habitat gradients such as the Colorado River Delta79, expansive reaches of river impounded by lava dams80, and lentic habitats created by high water events81.We observed changes in the amount of isotopic overlap between species, and particularly, native and nonnative species among the three habitats. Overlap of species in isotopic niche space can be an indication of potential competition for food resources13C of filter-feeding quagga mussels in the reservoir was more depleted in samples collected farther in-reservoir . Catostomus latipinnis was the only species that appeared to obtain resources from a mix of river and reservoir resources based on the intermediate δ13C values in the river downstream of the barrier. Some fish species could be partitioning habitat and garnering energy from more littoral or pelagic resources in the reservoir42. For instance, D. cepedianum and X. texanus might forage more in the littoral zone or shallower in the water column where food resources are less depleted86, which matches patterns observed in other food web and habitat use studies from Lake Powell88. The δ13C signature of X. texanus captured in the river downstream of the waterfall align more with that from the reservoir than the river upstream, which was not surprising since this species moves in the river for only a few weeks or months , spending most of their time in the reservoir87.We only had data on baseline trophic levels from the reservoir, which limited our ability to isolate the cause of observed shifts in isotopic niches, which could be due to changes in baseline isotopic signatures, diet, or habitat use. The δ15N45. For instance, the δ15N of filter-feeding quagga mussels collected from the reservoir reach during our study had a δ15N of 6.3 ± 1.1 (mean ± SE) and much more variable δ13C (-33.1 ± 2.3). Previous research on isotopic niches of native fishes in the Colorado River basin have mainly used smaller-bodied individuals relative to those we used here , limiting our ability to make direct comparisons of isotopic signatures. Whereas trophic position of fish tends to increase with size89; the random effect of fish length explained relatively little variation in our models. Nonetheless, our δ15N values for P. lucius , I. punctatus, and C. latipinnis are comparable to those reported previously from the San Juan River (range: 100–350 mm TL)90, although body sizes were not reported for the latter two species.Many native fishes in the Colorado River Basin, as well as the nonnative species we assessed, are considered trophic generalists. All fishes, native and nonnative, appeared to be feeding on primary consumers and higher trophic levels  rather than feeding directly on phytoplankton or benthic algae in the reservoir, assuming trophic fractionation of 3.4 ‰ in δ91. Somewhat surprisingly, on average, native fishes demonstrated consistent trophic niche breadth (based on SEAc) among the three habitats. All native fishes demonstrated substantially wider niches in the river upstream relative to nonnative fishes, and although the niche breadth of some nonnative species increased moving downstream towards the reservoir , X. texanus maintained a relatively wide niche breadth across habitats. In all three habitats, niche breadth was generally influenced more by variation in δ13C among individuals within species , potentially due to variation in basal resource (only measured in the reservoir) or habitat use. Only C. carpio in the river upstream and downstream and I. punctatus in the river downstream appeared to have niche breadth dually influenced by variation in δ13C and δ15N . Overall, species exhibited shifts towards more depleted carbon isotope sources moving from the river upstream  to the reservoir (− 27.5 ± 3.5), but the amount of overlap in isotopic niche space among species varied across habitats.Niche breadth varied spatially among the three habitats for native and nonnative species, presumably as the major resource base shifted from allochthonous to autochthonous92, and native and nonnative species co-occur in these habitats93, with nonnative species often thriving in more modified habitat95. In the Colorado River basin, native fish assemblages have endured habitat loss and degradation alongside the introduction and establishment of nonnative species, but recovery efforts are hindered by a full accounting of limiting factors, particularly the importance of biotic interactions. Although we observed greater niche overlap between native and nonnative fishes in habitats with a greater relative abundance of nonnative fishes , it remains unclear whether this overlap has negative impacts on native populations. It is difficult to assess the importance of overlap between native fish and potential nonnative competitors because data on resource availability are lacking across the basin. This study adds to a growing body of research suggesting adult native fishes may be able to coexist with some nonnative fishes that also have an opportunistic feeding strategy. In addition, we demonstrate some native fishes might be able to successfully utilize highly modified river-reservoir inflow and reservoir habitat96, habitats similar to lotic-lentic habitats that have been present across their evolutionary history.Human transformation of riverscapes has restructured fish assemblages with consequences for the conservation of native species. Artificial habitats, such as reservoirs and isolated river fragments, are now commonSupplementary Information.


Gliomas are the most severe brain tumours with a poor prognosis. Although surgery, postoperative radiotherapy and chemotherapy can improve the survival rate of glioma patients, the prognosis of most glioma patients is still poor. In recent years, the influence of gene-targeted therapy on gliomas has been gradually discovered, and intervening the occurrence and development of brain gliomas from the perspective of the gene will significantly improve treatment prognosis. Protein Kinase C and Casein Kinase Substrate in Neurons 1 (PACSIN1) is a member of the conserved peripheral membrane protein family in eukaryotes. Improper expression of PACSIN1 can lead to neurological diseases such as Huntington’s disease and schizophrenia. However, its relationship with tumours or even gliomas has not been explored. The study aims to explore PACSIN1 as a prognostic factor that can predict overall survival (OS) for gliomas. We collected the data from CGGA, TCGA, GEO databases and the pathological glioma tissue specimens from 15 clinical glioma patients surgically resected. The differential expression of PACSIN1 in various clinical indicators, the genes related to PACSIN1 expression, the prognostic value of PACSIN1 and the functional annotations and pathway analysis of differently expressed genes (DEGs) were analysed. The results revealed that PACSIN1 had low expression levels in grade IV, IDH1 wild-type and 1p/19q non-codel group gliomas, and PACSIN1 was considered a mesenchymal molecular subtype marker. PACSIN1 expression is positively correlated with OS in all gliomas and it was found that PACSIN1 influenced the occurrence and development of gliomas through synaptic transmission. The PACSIN1 expression is negatively correlated with the malignant degree of gliomas and positively associated with the OS, indicating that PACSIN1 would play an essential role in the occurrence and development of gliomas and might be a potential new biomarker and targeted therapy site for gliomas. Glioma is a primary tumour developed by glial cells of the brain or central nervous system, accounting for 24% of the total number of primary brain and central nervous system tumours . Among tHigh grades, Isocitrate dehydrogenase 1 (IDH1) wide-type, 1p/19q non-codel gliomas represent poor prognosis . At presProtein Kinase C and Casein Kinase Substrate in Neurons 1 (PACSIN1), also known as SYNDAPIN1, is a member of the PACSIN family. Studies have demonstrated that the PACSIN protein family is a conservative peripheral membrane protein family in eukaryotes and plays an essential role in the synaptic vesicle transport cycle and receptor-mediated endocytosis . MeanwhiOur study collected and extracted data of clinical indicators and gene expression of gliomas from Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) databases and clinical samples, gradually analyzed the influence of PACSIN1 expression on the related clinical indicators of gliomas, studied its clinical significance and explored the mechanism of PACSIN1 affecting gliomas, so as to provide the experimental basis for the diagnosis, prognosis, development and treatment of gliomas.http://www.cgga.org.cn/). And we also downloaded 702 clinical and gene expression data of gliomas from TCGA  and the data of Platform and Series matrix of 684 patients in three datasets  of glioma samples from GEO (https://www.ncbi.nlm.nih.gov/geo/). The RStudio (version4.0.1) and Perl software (version5.30.2.1) were used to collate CGGA, TCGA and GEO datasets, including annotation, merge, the complement of missing values, background correction, and data standardization of raw data.The clinical and gene expression data were downloaded from the mRNAseq_325 and mRNA sequencing samples (non-glioma as control) in CGGA  to build a protein-protein interaction (PPI) network . Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) performed the functional annotations of the DEGs and analyzed gene signaling pathways using clusterProfiler, org. Hs.eg.db and pathview packages of R language. Then, PACSIN1 and DEGs were uploaded to the STRING website  were randomly selected from The Affiliated Suzhou Hospital of Nanjing Medical University. We took the specimen of the patient’s surgically resected pathological glioma tissues. Inclusion criteria: ①All patients were diagnosed as glioma by definite examination, which followed surgical treatment indications; ②All patients underwent a single glioma resection. ③All patients volunteered to participate in this study and signed the informed consents. Exclusion criteria: ①Patients with a history of the tumour; ② Patients with concurrent multiple tumours; ③Patients with other operations during glioma resection. ④Patients whose postoperative pathology cannot make an exact diagnosis. This study was approved by the Ethics Committee of Nanjing Medical UniversityThe tumor sample of patients with glioma were made into paraffin sections, dewaxed with xylene, rehydrated with gradient alcohol, and boiled in the citrate antigen solution. After washed with PBS, the sections were incubated with 10% sheep serum and PACSIN1 antibody  at 4°C overnight. After that, the sections were incubated with HRP-conjugated secondary antibody , set at room temperature for 1 h, incubated with DAB (BOSTER Cat# AR1000) for 10 min, soaked in hematoxylin for 3 min, washed with PBS, and then sealed. The staining results were put under a microscope  to find the expression differences of cancer tissues. At least three tumour sections were analysed for each patient.p < 0.05.Kruskal-Wallis rank sum test was performed to detect the expression difference of PACSIN1 among patients with different glioma grades and different molecular subtypes defined by the TCGA network . WilcoxoIn order to search for targeted molecular markers related to brain gliomas and evaluate their potential as molecular markers, we collected gene data of 325 tumour tissue samples and 20 normal tissue samples in CGGA and 157 tumour tissue samples and 23 normal tissue samples in GSE4290 dataset of GEO in the early stage. Softwares such as Rstudio and Perl were used to annotate the data, supplement the missing values, correct the background, and standardize the data. We detected and analyzed the DEGs in the tumour group and the normal group from the total gene expression profile perspective. Among these DEGs, PACSIN1, one member of the conservative peripheral membrane brain protein family in eukaryotes, caught our attention. The expression of PACSIN1 is lower in gliomas compared with normal group by analyzing CGGA and GSE4290 datasets .p < 0.0001) and was significantly lower in the grade IV group (p < 0.0001). The higher the glioma grade, the lower the PACSIN1 protein expression (p < 0.0001). The results indicated that PACSIN1 plays a vital role in the progression of gliomas.The PACSIN1 expression in glioma grades was extracted from CGGA mRNAseq_325 samples. After data collation, Kruskal-Wallis rank sum test was conducted to detect the expression difference of PACSIN1 among patients with different glioma grades. The results showed that the mRNA expression of PACSIN1 was negatively correlated with glioma grades (IV group . The resIV group . In ordepression . The PACp < 0.001). Compared with the same pathological type of patients without defect, patients with 1p/19q codel have higher sensitivity to chemotherapy and longer survival time (p < 0.0001). The results were verified in TCGA and 228 samples from GSE58218 dataset  defined by the TCGA network . The resp < 0.0001). Similar results were obtained in the TCGA dataset (p < 0.0001). Then, to determine whether PACSIN1 expression could act as an independent prognostic factor, univariate and multivariate Cox regression analyses of CGGA dataset were performed (p < 0.0001), with all clinical indicators including age (p < 0.0001), IDH1 mutation status (p < 0.0001), 1P/19q codeletion status (p < 0.0001), and grade (p < 0.0001) could be used as a predictor of OS of gliomas at all grades. Hazard ratio (HR) is an expression of the hazard or chance of events occurring in the treatment arm as a ratio of the hazard of the events occurring in the control arm. Hazard ratios are commonly used in survival analysis to allow hypothesis testing  in the evaluation of age (p = 0.047), IDH1 mutation status (p = 0.940), 1P/19q codeletion status (p < 0.0001), and grade (p < 0.0001). The results suggested that PACSIN1 could be used as an independent prognostic factor.In the results of multivariate regression analysis, PACSIN1 showed significant results  were significantly correlated with the PACSIN1 expression . Next, GIn order to build a PPI network, we uploaded PACSIN1 and 224 DEGs to the STRING website, and set the interaction score as 0.7. Then, the obtained analysis results were imported into Cytoscape v3.8.0 software to construct an image with 84 nodes plus 223 edges . We alsoGlioma, the most common subtype of primary brain tumour, is a highly invasive and neurodestructive tumour, and is considered one of the most lethal cancers in humans . AccordiIn order to further explore the relationship between PACSIN1 and gliomas, we retrospectively analyzed a total of 1,546 glioma patients from CGGA, TCGA, GSE16011, GSE58218 datasets and 15 glioma samples. First, we investigated the relationship between PACSIN1 and clinical indicators of gliomas . In 201Finally, in order to explore the mechanism of PACSIN1 inhibiting the occurrence and development of gliomas, total 224 DEGs were screened out through correlation analysis, and functional annotation and pathway analysis were conducted. Then we constructed the PPI network and found the main gene cluster, and we also analyzed these genes with functional annotation and pathway analysis. Finally, it was found that PACSIN1 mainly affects the occurrence and development of gliomas through synaptic transmission –8.Many studies have proved that synaptic transmission influences the development of gliomas. In particular, in 2019, Nature published three studies simultaneously, revealing a remarkable discovery: the formation of synaptic structures between gliomas and neurons will promote tumour growth. The results of Michelle Monje’s research group show that both AMPA receptor-dependent excitatory post-synaptic current and gap junction targeting mechanisms can significantly slow down the proliferation of gliomas . Thomas Meanwhile, genes such as CAMK2A, NCS1, NPTX1, RAB3A and SYT1 have been found to affect synaptic transmission. Studies have shown that CAMK2A mutations affect dendritic morphology, lead to synaptic defects, and thus affect behavioural changes associated with ASD . NCS1 biIn this study, PACSIN1 was combined with gliomas for the first time. Through the correlation study between gene expression changes and clinical indicators, it was found that PACSIN1 can be used as an independent prognostic molecule of gliomas, and can predict the prognosis and development of patients’ disease to a certain extent, which will be a potential new site for targeted therapy of gliomas. The shortcoming of this study is that we only conducted a preliminary analysis and discussion at the glioma level, but did not deeply explore the tumour types caused by the differentiation of gliomas in the cell morphology. In addition, we did not carry out relevant animal and cell experiments, but only collected human tissue samples for data analysis. The above studies on the correlation between PACSIN1 and gliomas and the relevant mechanism still need to be further investigated in clinical samples. We will further explore the function of this gene, focusing on its role in other cancer and neurological diseases.This study provides a basis for the following clinical studies on PACSIN1 in gliomas, and offers new ideas for targeted therapy of gliomas. If the PACSIN1 expression can be interfered in the body, so as to regulate the synaptic transmission pathway, it will make an outstanding contribution to the inhibition of the occurrence and development of gliomas, which is of great significance for glioma patients.


Pullets (16 weeks old: n = 1386) were then transferred to nine identical pens within rearing treatments, with outdoor range access from 25 to 65 weeks. Video cameras recorded the pullet pens, adult indoor pens, and outside range. During rearing, observations of play behavior in chicks at 2, 4 and 6 weeks showed no overall effect of rearing treatment. At 11 and 14 weeks only the novelty hens were observed to increase their foraging across age with no differences between treatments in dust bathing. Observations of adult hens at 26, 31, 41, 50, 60 and 64 weeks showed that the structural hens exhibited more dust bathing and foraging overall than the control hens, but that both novelty and/or structural hens showed small increases relative to control hens depending on the behavior and location. Across age, adult hens differed in the degree of dust bathing performed inside or outside and foraging outside but not inside. For litter-reared pullets, additional enrichments may result in some long-term increases in positive behaviors. Enrichment during the indoor rearing of young laying hens (pullets) destined for free-range systems may improve pullet development and increase motivated natural behaviors (termed ‘positive behaviors’) such as foraging, dust bathing and chick play. Hy-Line Brown® chicks (n = 1700) were floor-reared indoors across 16 weeks with three enrichment treatments (n = 3 pens/treatment): (1) standard control, (2) weekly novel objects—‘novelty’, (3) perching/navigation structures—‘structural’. At 16 weeks, pullets (n = 1386) were transferred to nine identical pens within rearing treatments with outdoor range access from 25 to 65 weeks. Video cameras recorded the pullet pens, adult indoor pens, and outside range. During rearing, observations of play behavior  in chicks at 2, 4 and 6 weeks  showed no overall effect of rearing treatment (p = 0.16). At 11 and 14 weeks only the ‘novelty’ hens were observed to increase their foraging across age  . Observations of adult hens at 26, 31, 41, 50, 60 and 64 weeks showed that the structural hens exhibited overall more dust bathing and foraging than the control hens (both p < 0.04) but both novelty and/or structural hens showed small increases depending on the behavior and location . Across age, adult hens differed in the degree of dust bathing performed inside or outside (both p ≤ 0.001) and foraging outside (p < 0.001) but not inside (p = 0.15). For litter-reared pullets, additional enrichments may result in some long-term increases in positive behaviors. Enrichment during the indoor rearing of pullets destined for free-range systems may optimize pullet development including increasing motivated natural behaviors (termed ‘positive behaviors’) including foraging, dust bathing and chick play. Hy-Line Brown® chicks ( Free-range laying hen production systems are prevalent within Australia due to their popularity with consumers . Across One of the potential benefits of free-range systems is the increased space and outdoor environment that provides more freedom to exhibit behaviors that are viewed as part of a positive behavioral repertoire for hens . These pWhile behaviors of dust bathing and foraging are innate and are performed even in the absence of suitable substrates ,17, apprPlay behavior is performed across many animal species and may be associated with better preparing animals for the unexpected later in life . Play maPullets destined for free-range systems in Australia (and elsewhere) are typically reared indoors before being transferred to a laying facility with outdoor access. The discrepancies between the rearing and laying housing systems may impact how the adult hens adapt to their new housing. With outdoor access for pullets being logistically difficult, enriching the rearing environment may be a strategy to optimize pullet development, improving welfare and adaptability. A rearing enrichment trial was designed to measure the impacts of different types of rearing environments on the behavior, health, production, and welfare of a flock of free-range hens in an experimental setting and showed long-term effects of the type of environment the pullets were reared in across multiple measures ,33,34. TAll research was approved by the University of New England Animal Ethics Committee (AEC17-092).® Brown layers that were first reared indoors for 16 weeks in the Rob Cumming Poultry Innovation Centre of the University of New England, Armidale, Australia, before transfer to the Laureldale free-range facility of the University of New England, where they remained until the conclusion of the trial at 65 weeks of age. The housing set-up for the birds has been described previously . Temperature and lighting schedules followed the Hy-Line® Brown alternative management guidelines [This study used 1700 Hy-Liney e.g., ,34). In . In ® Bry . Each pen contained nest boxes, perches, feeders, and water nipples to meet or exceed requirements of the Australian Model Code of Practice for the Welfare of Animals-Domestic Poultry [At 16 weeks of age, 1386 pullets were transferred to nine identical, visually isolated pens within a single shed at the Laureldale free-range facility of the University of New England with rearing treatments balanced for location across the shed. Additional pullets, surplus to the space restrictions of the layer shed, were rehomed including those birds that were either heavier or lighter than the mean body weight, and then some additional randomly selected pullets to reach the desired quota. Pullets were socially remixed within pen replicates of their rearing treatments (three pen replicates per rearing treatment) to simulate the social remixing that occurs commercially. However, pullets were placed into three pens containing only birds from the same rearing treatment. Bird density was approximately 9 birds/m Poultry . Pen spaEach indoor pen was connected to an outdoor range area accessible via two pop-hole openings (18 cm W × 36 cm H). The nine range areas were visually isolated from each other via shade cloth on the wire fences. The pop-holes first opened at 25 weeks of age (May 2018) and provided daytime range access on an automated schedule from 09:15 until after sunset resulting in approximately 9 h of available ranging time across winter and approximately 11 h of available ranging time daylight saving time onward (October 2018). The range area comprised of a 1.2 m length concrete path, followed by 3.6 m length of river rock and then a 26.2 m length of grassed area with no trees or artificial shelters. Monthly photos of the range areas allowed visual estimation of vegetation coverage. Initially the range areas were 90% covered in grass, which was destroyed by hens or seasonal die-off after 8 weeks of range access. Six months after first range access (hen age: 48 weeks), there was some spring grass regrowth with up to 40% coverage in some pens  but by summer (8 months after first range access: hen age: 56 weeks) the ranges were only bare dirt with some scattered hen-resistant weeds.Hikvision Network cameras  were installed to capture the indoor rearing pens during light hours at 2, 3, 4, 6, 8, 11 and 14 weeks of age. The same cameras were installed to capture the indoor pens and range area of each pen at the layer facility at 26, 31, 41, 50, 60 and 64 weeks of age. Across the ranging period there was typically little rain due to severe drought in the region. Due to camera angles, across all pens equally, approximately 0.5 m in front of the pop-holes inside and approximately 1.2 m in front of the pop holes outside was unavoidably excluded from video capture. Video recordings were later decoded by observers who were blind to rearing treatment or blind to the aims of the trial where rearing enrichments were visible in the video. The observers were all trained by a single researcher who simultaneously did sections of video with the trainee to ensure the correct behaviors were being identified. For instances where two observers were collecting data on the same behavior, both observers watched one identical section of video first independently (one day of observations across one pen). If inter-observer reliability was initially below 90% as assessed by correlation in Microsoft Excel , the two observers then discussed the section of video to reach 100% agreement in the identification of birds performing each behavior at each time point the observers previously showed discrepancies on before proceeding with their independent observation days. Where two observers watched one behavior, the allocation of pens and treatments to observe were balanced to minimize any potential observer bias per a specific rearing treatment.The observers collected data as follows:1. Rearing—Enrichment interactions: counts of birds using/interacting with enrichments in the rearing pens at 3, 6, 8, 11 and 14 weeks of age. These data were collected by one observer to document the use of the enrichments during rearing with no intended comparison between treatment groups. At each age point a single day of video per enriched pen  was observed with point counts made every 30 min from 08:00 until 17:30 . Days were selected to be at least 2 days after the new novel objects had been added but also at least 2 days after other/disturbances interventions such as body weight assessment as part of a separate dataset  and vacc2. Rearing—Play behavior of chicks: counts of chicks exhibiting play behavior were observed in each pen across one day at 2, 4, and 6 weeks of age. Ages were selected based on previous literature on broiler chickens ,32 of wh3. Rearing—Pullet foraging and dust bathing: at 11 and 14 weeks of age, all pullet pens were observed by a single observer across two days per age point to count the number of birds dust bathing or foraging  across 30 s every 30 min from 09:30 until 17:30 . This definition of foraging has been used in previous studies  although4. Free-range facility—Hen foraging and dust bathing: at each age, approximately one week of video was recorded with the specific days of observation within the week selected based on a full set of recordings with no missing video due to technical issues, and predominantly dry weather. Across two days each at 26, 31, 41, 50, 60 and 64 weeks of age, the number of hens dust bathing or foraging inside were counted by two observers across a 30 s period every 30 min from 09:30 (pop-holes opened at 09:15) until 17:30 (just before sunset) or until 19:30 from 50 weeks onwards following daylight saving time change . At each observation point, the corresponding observations of hens’ dust bathing or foraging were made outside on the range (n = 2052 observations each for dust bathing and foraging outside) by a different two observers. Selected days within age points had one full day between them that was not observed .5. Free-range facility—Time budgets of hens: across two days at 50 weeks of age, a 10 m length portion of the range area for each pen was selected for time budget observations by a single observer . This age point was selected as foraging and dust bathing on the range were observed at higher levels and daylight hours were extended for more observations. Scan sampling was applied every 30 min from 09:30 until 19:00 with hens in the designated area first counted and then a behavior allocated per hen based on the ethogram in All analyses were conducted in JMP 14.0.0  with α = 0.05. All proportions were calculated taking cumulative mortality into account. All data were checked for normality and transformed where necessary for parametric tests. The studentized residuals were visually inspected to ensure homoscedascity. Non-parametric tests were conducted where transformations could not make the data normally distributed.n = 27: 3 × daily means × 9 pens) and were logit transformed. A constant of 0.001 was added to the sparring proportions only prior to transformation to account for zero values. A General Linear Mixed Model (GLMM) was applied to each behavior  with rearing treatment, age and their interaction as fixed effects, including pen nested within treatment as a random effect. Where significant differences were present, post-hoc Tukey’s tests were applied to the least squares means.The count data for interaction with enrichments were converted to proportion of birds within the pen at each time point and visually displayed. No statistical analyses were conducted on these data as there were no specific comparisons to be made among treatment groups. The counts of chicks exhibiting play behaviors  were converted to proportions of chicks within each pen performing each behavior at each age point. Observations across the day were summed into a daily mean per pen per age point (n = 36: 4 daily means × 9 pens). A General Linear Mixed Model (GLMM) was applied with rearing treatment, age, and their interaction as fixed effects including pen nested within treatment and observation day as random effects. Where significant differences were present, post-hoc Tukey’s tests were applied to the least squares means.The counts of pullets dust bathing and foraging were converted to proportions of pullets performing the behaviors, logit transformed and mean daily values were calculated per pen for each behavior (n = 108 per behavior: 2 days × 6 age points × 9 pens). The proportions were logit transformed but were not normally distributed and were analyzed for an effect of rearing treatment using separate Kruskal-Wallis tests, including blocking for the effect of age . Where significant differences were present, post-hoc tests were conducted between all pairs using the Steel-Dwass method. The proportions of hens dust bathing or foraging inside the shed or outside on the range were then analyzed separately for an effect of rearing treatment using separate Kruskal-Wallis tests that included blocking for the effect of age. A constant of 0.001 was added to these data prior to logit transformation to account for values of zero. Finally, effect of age for dust bathing or foraging in indoor and outdoor locations was analyzed using separate Kruskal-Wallis tests blocking for effects of rearing treatment. The counts of hens dust bathing or foraging inside and outside were converted to proportions of all hens in the pen and summed across the two locations. The conversion to proportions of all hens in the pen rather than proportions of hens specifically inside or outside was to display the proportions of the total group that were exhibiting each behavior in each location . The original dataset (2052 observations per behavior) was summarized to include one mean value per pen per day each for dust bathing and foraging . The behaviors of jumping/flying, piling, pecking other chickens and fighting occurred too infrequently (~ 1% of the hens’ time budget combined) and were not included in any further analyses. The proportions of comfort behaviors, dust bathing, foraging, pecking, running, standing and walking were analyzed for an effect of rearing treatment using separate non-parametric Kruskal-Wallis tests. Observations of the proportions of pullets utilizing enrichment in the two enriched rearing treatments showed that the birds were interacting with the provided enrichment across the rearing period with approximately 10% of pullets using them at any single point in time  = 5.28, p = 0.02), with the enriched chicks showing less running at four weeks of age compared with the control chicks  = 2.57, p = 0.16), but running decreased linearly across age  = 59.38, p < 0.0001,  = 5.76, p = 0.02) with less frolicking at six weeks  = 2.81, p = 0.14), or interaction between age and rearing treatment  = 0.44, p = 0.78). There was a significant effect of rearing treatment on the proportion of chicks showing wing-flapping  = 9.50, p = 0.01) with the structural chicks showing less than control and novelty chicks  = 4.67, p = 0.03) with less wing-flapping at two weeks of age compared with six weeks of age  = 0.57, p = 0.69). There was a significant interaction between age and rearing treatment on the proportion of chicks sparring  = 3.29, p = 0.048), with the control chicks only showing more sparring at six weeks relative to two weeks of age. There was a significant effect of age  = 5.44, p = 0.02) with more sparring at four weeks than at two weeks, but no overall effect of rearing treatment  = 0.25, p = 0.79). When all play behaviors were combined, there was only a significant effect of age  = 29.05, p < 0.0001) with play linearly decreasing across age. There was no effect of rearing treatment  = 2.94, p = 0.13) and no interaction between rearing treatment and age  = 1.22, p = 0.35). Running was the most frequently observed play behavior but was still observed in less than 10% of the chicks during observations, with sparring only observed in a few chicks  = 1.06, p = 0.40), but the proportions decreased from 11 to 14 weeks  = 332.18, p = 0.003) with no interaction between treatment and age  = 2.40, p = 0.11,  = 5.67, p = 0.01) with the pullets from the novelty treatment increasing their foraging with age, but the control and structural pullets remained at similar levels between 11 and 14 weeks  and foraging  with the structural hens showing more dust bathing and foraging than the control hens only  with both the novelty and structural groups showing more dust bathing than the control hens  with the structural hens showing more dust bathing than the novelty hens only (p = 0.002), 2 = 8.39, df = 2, p = 0.02) with the novelty hens showing more foraging than the control hens only  with the structural hens showing more foraging than the control hens only  and outside  and significant differences across age for hens foraging outside , but not across age for hens foraging inside  including foraging and dust bathing for pullets and adult hens across their production cycle as well as play behavior in chicks. Providing novel objects or perching/navigation structures to pullets raised on floor litter had some effects on play behavior but most play behaviors were observed in low frequencies equally among treatments. The novel objects increased the foraging behavior of pullets across age during the rearing treatment phase to a greater degree relative to the control and structural treatment groups. In the adult hens, the perching/navigation structure enrichments increased overall foraging and dust bathing relative to the control hens but there were treatment effects of both enrichment types, dependent on the location and behavior observed. Hens differed in the amount of foraging and dust bathing performed inside the shed versus outside on the range across age. These results demonstrate that for pullets reared on litter, additional enrichments can still result in some increases in these species-specific positive behaviors in the adult hens. These beneficial effects of rearing enrichments may become more apparent in the longer term as the adult birds are exposed to a new environment, come into lay and likely encounter various stressors across the production cycle. Rearing enrichments resulted in a greater drop in running behavior relative to the control chicks from 2 to 4 weeks of age but when all play behaviors were combined, there was no effect of the rearing treatments indicating enrichments resulted in minimal impacts on play behaviors. It is possible that a different observation method such as extended continuous observations across fewer periods  may haveAll birds in this study were raised on litter, which is important for the development of foraging behavior and reductions of feather pecking ,22, althIncreases in foraging only were shown in the novelty pullets across age which may have been a result of changes in the degree of engagement with the varying enrichments in their pens across time. Once hens moved into the laying system and had a choice of engaging in these behaviors both inside the shed in the floor litter, or outside the shed in the dirt, there were differences between rearing treatments for both dust bathing and foraging, but these differences were in part dependent on the location being observed. Overall, the structural hens did show the most foraging and dust bathing, and this in part may have been related to differences in ranging behavior. Through individual range-use tracking using radio-frequency identification technology, the structural hens spent the longest daily time outside on the range, with the novelty and structural hens showing the longest times for individual visits relative to the control birds . This inThe increase in foraging behavior may have had other welfare benefits across the trial, although confirmation of a causal relationship in this study is limited. The control hens overall showed less foraging relative to the structural hens, and they also exhibited the most plumage damage across time . ForaginThis research demonstrates some long-term benefits of rearing enrichments in the form of novel objects or perching/navigation structures for pullets destined for a free-range environment, where additional complexity in litter-based environments may optimize behavioral development of the pullets and increase performance of positive species-specific behaviors. The effects were most prominent in the pullets reared with the perching/navigation structures throughout development, although the increases were small. Future research should seek to further understand mechanisms behind these effects to design rearing environments that will facilitate desirable behaviors across the laying cycle. Benefits may be seen for laying hens in loose-housed systems with or without range access.