Alternative cell line models though popular for drug testing are not biomimetic – they are not dependent on the microenvironment for survival, growth and treatment response and being derived from relapse samples they do not capture the molecular complexity observed at disease presentation. Here we have developed anin vitro platform to rapidly establish co-cultures of patient-derived leukaemia cells with 3D bone marrow mesenchyme spheroids, BM-MSC-spheroids.  We optimise protocols for developing MSC-spheroid leukaemia co-culture using clinical samples and deliver drug response data within a week. Using three patient samples representing distinct cytogenetics we show that patient-derived-leukaemia cells show enhanced proliferation when co-cultured with MSC-spheroids. In addition, MSC-spheroids provided improved protection against treatment. This makes our spheroids suitable to model treatment resistance – a major hurdle in current day cancer managementPatient derived xenograft (PDX) models are regarded as gold standard preclinical models in leukaemia research, especially in testing new drug combinations where typically 45-50 mice are used per assay. 9000 animal experiments are performed annually in the UK in leukaemia research with these expensive procedures being classed as moderate severity, meaning they cause significant pain, suffering and visible distress to animal’s state. Furthermore, not all clinical leukaemia samples engraft and when they do data turnaround time can be between 6-12 months. Heavy dependence on animal models is because clinical leukaemia samples do not proliferateGiven this 3Rs approach is 12 months faster , is a human cell-based biomimetic model and uses 45-50 fewer animals/drug-response assay the anticipated target end-users would include academia and pharmaceutical industry. This animal replacement prototype would facilitate clinically translatable research to be performed with greater ethical, social and financial sustainability. Research highlightsScientific Benefitex vivo co-culture of patient-derived-leukaemia samples.A 3D spheroid-based approach with improved clinical relevance for3Rs BenefitTo replace animal experiments, including moderate severity animal (mice) procedures in leukaemia research and drug testing.Practical Benefitin vivo counterparts.A 3Rs approach that yields drug response data quickly and is ethically, socially and financially more sustainable than itsCurrent applicationsExploration of leukaemia biology such as stem/progenitor proliferation, stem/progenitor-niche interactions, niche-impacted treatment resistance and to obtain drug response data.Potential applicationsAdapt the approach to include other haematological cancers as well as bone cancers.,–Acute lymphoblastic leukaemia (ALL) management in children is hindered by two chief obstacles: 1. Treatment toxicity–in vitro studies before moving intoin vivo models, neverthelessin vivo models are still used as key models to expand primary samples as vital research resources. This causes heavy reliance on PDX models, where leukaemia cells are engrafted into immunocompromised mice to amplify patient-derived leukaemia cells, to study cancer biology and perform translational studies.,The gold standard preclinical model in leukaemia research is a PDX model.–in vitro cancer models precedingin vivo validation experiments rely on cell lines, which retain cytogenic characteristics of leukaemia. However being derived from patients with relapsed disease these samples do not represent the molecular complexity of disease that is observed at presentation.,in vitro as suspension monocultures, and therefore do not represent cancer within the context of its microenvironment. Therefore, these models show limitedin vivo predictivity, leading to increasein vitro toin vivo drug attrition rates.The pipeline for preclinical testing using mouse PDX models is: 1. Toxicity analysis to determine no observed adverse effect limit (NOAEL)/maximum tolerated dose (MTD): 15-20 mice per drug.ex vivo alludes to the vital role that the BM-niche plays in cancer biology. The leukaemia BM-microenvironment plays a key role in disease, mediating cell-cell signalling and conferring treatment protection to leukaemia cells.,,,in vitro is important. Furthermore, targeting leukaemia-niche interactions may present as promising therapeutic approaches. We have developedin vitro 2D co-culture platforms in previous studies,in vitro toin vivo drug attrition rates and 2. explore the impact of human BM cells in driving ALL biology such as leukaemia proliferation, dormancy and treatment resistance.ex vivo platforms have potential to detect therapeutically exploitable targets that disrupt leukaemia-BM cell interactions conferring treatment resistance to the cancer cells.,in vivo procedures, further mitigating reliance on mouse experiments to perform mechanistic studies. However, standard 2D models, including co-cultures, do not sufficiently portray functional biomimicry and do not recapitulate structural intricacies of the leukemic niche. Nor do such 2D models capture the complex polarity of cell-cell interactionsALL is a disease primarily of the bone marrow (BM), the BM comprises cell types including haematopoietic, mesenchymal stroma cells (MSC), osteoblasts, osteoclasts, endothelia, perivascular and immune cells. Difficulty in culturing patient derived ALL cellsin vitro representations of specific organs.Recent advances in medicine have embraced 3D models as miniatureEthical approval,,Patient leukaemia cells were obtained from the Newcastle Biobank (REC reference number 07/H0906/109+5). All samples were acquired following written informed consent. Animal data shown here reflect unpublished data that were existing from past experiments. These experiments were carried out as per previously published methods.2D BM-MSC-ALL co-culture4 cells/0.5 mL/cm2 in their respective media  was added to desired wells and leukaemia cells were cultured for 5 days. Experiments were repeated to include a total of 3 biological replicates with each replicate including 3 independent experiments.3D Spheroid Calcein AM/Hoechst-33342 staining7cells/ml, to which 10 μl of 1 μM calcein stain was added to final concentration of 0.01 μM. Cells were incubated at 37°C for 20 minutes in the dark. Cells were pelleted and resuspended in pre warmed media and left for 10 minutes to ensure optimal calcein retention before imaging. Samples that were double stained with Hoechst-33342 were stained for calcein as above and following the 10 minute incubation, were stained with Hoechst-33342 at final working concentration of 10 μg/ml in pre warmed media for 20 minutes. Digital Images were captured using Leica Application Suite X (LASX) version 3.5.7.23225.MSC were seeded into Aggrewell plates to obtain a final spheroid size of 200 cells per microwell. Cells were cultured in the Aggrewell format for 3 and 7 days following which resultant spheroids were collected for the staining procedure. The calcein stain was prepared by reconstituting the lyophilized reagent to a 1mM stock in DMSO. From this, 1 μM working solution was prepared by diluting into sterile calcium free PBS. The MSC spheres were resuspended in PBS at a density of approximately 1×10MSC Marker Antibody stainingMSC Spheroids were collected from Aggrewell plates, disrupted to single cells using a trypsin EDTA wash followed by gentle mixing. Remaining cell clumps were removed by passing sample through a 40 μm PluriStrainer. Cells were counted using a trypan blue exclusion assay. 1 million cells were resuspended in PBS to wash before blocking in 10%FBS/PBS. Cells were again spun down and resuspended in 200 μl PBS. 5 μl antibody was added and samples were incubated at room temperature for 1 hour in the dark. Following incubation, 800 μl 10% FBS/PBS was added and cells were spun down again before being resuspended in PBS for running on flow cytometer.Extraction of mRNARNA was purified from cell pellets (viable cells centrifuged at 5000 g X 5 minutes followed by aspiration of supernatant media) using the RNeasy mini kit, and as per manufacturer protocols. The RNA yield and quality was checked using the nanodrop ND-1000 spectrophotometer.cDNA synthesisRevertAidTMH Minus First Strand cDNA Synthesis Kit was used to synthesise cDNA from the RNA isolated. 500 ng RNA was collected and added to RNase/DEPC free water to a final volume of 11 μl. 1 μl (dN)6 (200 mg/l) random hexamers was added, mixed gently by inverting the vial and briefly centrifuged. Using a GeneAmp PCR system 2700 the sample was incubated at 65°C for 5 minutes, after which the sample was immediately placed on ice, 8 μl of the master mix  was addeqRT-PCRUpon receipt, primers were reconstituted in RNase/DNase free water to a final stock concentration of 100 μM. PCR Mix  was loadCostings analysis of in vivo versus in vitro modelsin vitro models were estimated using list prices of media, reagents and other materials associated with developing and using the models for a 2 drug combination dose finding assay. This included 5 biological replicates, 3 experimental repeats with each having 3 technical repeats with a total number of experiments of 45. These costs were divided into the following categories: Production of clinical/patient-derived leukaemia samples;in vitro CRISPR/RNAi organoid generation; Dose/IC50 finding for 2 drug combination; and evaluation of drug combination.Costings ofIn vivo costings were calculated using figures obtained from the Comparative Biology Centre, Newcastle University. This included fixed costs including mouse purchase from an NSG in-house colony, housing and IVIS use. Comparativein vivo equivalents to thein vitro design accounted for: production of PDX engrafted tissue ;in vivo CRISPR/RNAi ; Dose finding for 2 drug combination (3 mice per sex); and evaluation of the combination . All total costings were calculated using Microsoft Excel and figures were created using Microsoft Excel.Data analysisMicroscopy images were analysed using the Windows download bundled with Java 8. Version 1.4.3. Real time qPCR data were captured and analysed using the StepOne Plus Real-Time PCR System  and Software package StepOne Software v23.ex vivo human cell-based co-culture platforms potentially enable 73%  replacement of animals in drug testing experiments. Drug testing experiments are conventionally carried out using PDX-mouse-models, currently regarded as gold standard preclinical leukaemia models . This shows the ability of our 3D co-culture model to screen off false-positive hits derived from 2D models, consequently minimisingin vitro toin vivo attrition rates. We further confirm that when co-cultured with 3D MSC spheres, ALL cells expectedly proliferate in 3D-MSC spheroid-co-cultures, however, fail to increase in cell counts on day five, in the dexamethasone treatment arm  cells from t-positive samples,in vivo predictivity, to replace, reduce and refine animal models in drug testing. This further corroborates the timeliness of prioritising development of transformative human cell-based, non-animal technologies towards preclinical drug testing. Most specifically, a key advantage of our prototype approach would be in medium-high throughput screening of single and combinatorial compounds, particularly as pre-in vivo screens, to prevent “false positive” 2Din vitro hits, such as that observed inin vivo drug efficacy testing.Nevertheless, the U.S. Food and Drug Administration (FDA) has recently announced that new drugs would not be mandated to be tested in animals prior to first-in-human trials, and an FDA-wide program is furthermore prioritising development of human-relevant methods, with highin vivo and patient drug response predictivity. Such sustainableex vivo models will ultimately aim to successfully replace existing moderate severity animal procedures in leukaemia research with clinically relevant human cell-based models that are able to successfully impact positive clinical outcome.A 3D BM-mesenchyme-leukaemia spheroid model will provide researchers with a tractable platform with improved biomimicry, where clinical samples can be cultured within the context of their mesenchymal microenvironment, and patient specific drug testing can be performed within shorter time periods, such as a week. In circumstances where sourcing primary MSC may be a challenge, human induced pluripotent stem cell (iPSC) differentiation into MSC may be an attractive alternative.Here we use primary human MSC, which indeed may be difficult to source, and which may lead to donor variability. Using iPSC derived MSC to co-culture patient-derived leukaemiahttps://doi.org/10.17632/56npmkbpfb.1.Mendeley Data. A human mesenchymal spheroid prototype to replace moderate severity animal procedures in leukaemia drug testing.•- 3D spheres.tif•- 3D Sphere.tif•- drug combination.xlsx•-in vivo Vsin vitro costs.xlsx•- Raw Figure Data.xlsxThis project contains the following underlying data:Creative Commons Attribution 4.0 International license (CC-BY 4.0).Data are available under the terms of the The authors have addressed all the comments and included the additional data requested.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Stem cells, leukaemia modelling, signalling, pre-clinical drug testing.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Many thanks for accommodating my recommendations.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?PartlyAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Leukaemia biology, disease modelling, stem cells, epigenetics, preclinical drug testing.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. et al. provides a convincing argument for the requirement of additional in vitro models to improve drug testing in acute lymphocytic leukaemia (ALL) and reduce the reliance on Xenograft mouse models. Preliminary data is presented supporting the use of 3D human mesenchymal stroma cell (MSC) spheroid/primary ALL co-cultures for the use in preclinical testing of drugs. Proof of principle data is provided showing that simple 2D co-culture on MSCs gives a similar range of drug responses to dexamethasone and the BCL2 mimetic drug ABT199 as observed in in vivo studies for 2 primary ALL patient samples. The authors then show optimisation data using Aggrewell plates, demonstrating uniform spheroid formation and a corresponding increase in spheroid diameter when cell seeding density is increased. The final figure then compares primary ALL cell proliferation in 2D and 3D culture and drug responses to dexamethasone. Using 3 independent patient samples they show that MSC spheroids support cell proliferation over a 5 day time frame and provide protection to dexamethasone. These are important observations and support the introduction of a more physiologically relevant humanised system for drug screening prior to conducting in vivo studies. Another potential advantage would be if the authors had data demonstrating that the system supports patients' samples which do not engraft, as there is a high engraftment failure rate in Xenograft models with not all patient samples being successful. This could potentially lead to more robust data on patient’s responses. Given patient heterogeneity mouse models may be biasing certain traits/genetics due to the engraftment limitations observed.The manuscript by Wilson Overall, the system if adopted by other researchers could potentially reduce animal numbers and suffering, reduce the cost and select the most promising drugs for additional testing. It would therefore have impact on replacement and reduction of mouse experiments.+105+73+34-45- are key markers demonstrating stemness. The culture conditions using FCS can also lead to changes in the MSCs so it would be good to include passage number. Figure 3 live/dead staining of the spheroids especially for the size used in the drug treatment assays in Figure 4 would be important to include.The MSC are characterised by gene expression, it would be good to include flow cytometry data; CD90Data showing that dexamethasone and ABT199 do not detrimentally affect the MSC monoculture and MSC spheroids would also be important to include.Figure 4 looks at proliferation, apoptosis assays would be good to include to show whether cell death was occurring.Data showing similar results in ALL patient samples known to fail to engraft in vivo would strengthen the rationale for adopting the 3D system.Although the potential costs and animal savings presented are feasible, the system is quite simplistic and is more likely to be incorporated as an additional test rather than be adopted as a replacement. It would be more attractive if the time frame could be extended and more details on the application for high throughput screening development was discussed. Also, in vivo toxicity testing of novel compounds will still be required in order for regulatory approval for any Phase 1 clinical trial in humans to be progressed.Minor corrections: However, there are some limitations in the results shown that would be strengthened by additional experiments:Research highlights - blasts would only be appropriate for certain types of leukaemia, either need to define it’s ALL specifically or change to stem/progenitor.Scientific benefit: A 3D spheroid-based approach with improved clinical relevance for ex vivo co-culture of primary patient leukaemia samples for further investigation into cancer biology such as stem/progenitor cell-niche interactions, stem/progenitor cell proliferation and treatment resistance.3Rs benefit: To replace moderate severity animal (mice) procedures in leukaemia research and early pre-clinical drug testing.Current applications: Exploration of leukaemia biology such as stem/progenitor cell proliferation, stem/progenitor cell -niche interactions, niche-impacted treatment resistance and obtain drug response data.Introduction:Need to define at the start that you are talking about ALL as it reads like a general overview which means some of the % incidence rates etc. are not correct. It would be good to mention what type of ALL as well, is it B-ALL, T-ALL, childhood, adult?Paragraph 3 page 3: Most research groups would use primary patient samples in vitro prior to moving to in vivo models. This should be included.Paragraph 2 Page 4: Remove blasts and replace with LSCs also include disease type chronic myeloid leukaemia.Page 11 ‘such spheroid biobanks’: do they actually exist? Or are you planning on constructing a biobank?‘MSC spheroids provide superior protection to leukaemia cells against dexamethasone treatment. are appropriate in modelling treatment resistance which remains a major clinical challenge in cancer management’. Is this statement correct, not really looking at resistance, just reduced sensitivity to the drugs at that dose when in 3D rather than 2D culture. Need to amend and extend to include how you would look at resistance i.e. relapsed patients and the potential to interrogate resistance mechanisms.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Stem cells, leukaemia modelling, signalling, pre-clinical drug testing.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. This manuscript by Wilson et al provides a rationale, methodological details and pilot data supporting the use of 3D human mesenchymal stroma cell (MSC) spheroid co-cultures in the preclinical testing of drugs for acute leukaemia. The authors provide a detailed rationale for the potential benefits of this system, including: i) reduction in animal use/suffering; ii) reduced costs; and iii) the ability to model the protective impact of bone marrow micro-environmental influences in abrogating drug efficacy in vitro, reducing the number “false positive” drug hits taken forward to in vivo model systems. The authors provide data showing the equivalence of 2D in vitro drug sensitivity with PDX models (n=2) and compare 2D vs 3D co-culture of human leukaemias (n=3) in proliferation and dexamethasone sensitivity assays, showing consistently enhanced proliferation and reduced dexamethasone sensitivity in the 3D system. They also present methodological data on the establishment of MSC spheroids as well as modelling on the potential reduction in animal use and costs based on local experience. Overall, the rationale to develop more physiologically relevant in vitro co-culture systems is a very worthwhile endeavour with clear potential benefits for animal welfare, costs and in streamlining drug development. It also has the potential advantage of being used in the study of leukaemias that do not engraft in current immunosuppressed mouse models. In my opinion the work has three major limitations that would benefit from either additional data or acknowledgement in the discussion.Whilst this work demonstrates the feasibility of the approach, it is not possible from the data presented to conclude that 3D systems perform better than either 2D co-culture or PDX systems. Specifically, the data presented uses a small number of patient samples (n=2 or 3) and drugs (Dexamethasone ± ABT199). The three systems are not directly compared and no example of an in vitro drug hit that proves “false-positive” when tested in vivo is tested in parallel 2D/3D co-culture.There are a number of potential technical limitations of the co-culture approach that are not acknowledged: i) the requirement for access to a source of MSCs which are not readily available to most labs; ii) certain drugs (notably cytotoxic chemotherapy) are likely to have direct toxicity to the MSCs themselves; iii) the lack of a vascular component to this system might result in artificially high levels of physical protection from drug exposure by the 3D niche .The potential costs and animal savings presented are feasible, but likely at the upper end of the spectrum and will differ between institutions. For example, the time to generate a novel PDX is indeed many months, but once established PDX models in ALL engraft much more quickly and reproducibly and established PDX material is readily available. In vivo toxicity testing is not needed for established drugs being re-purposed; conversely novel chemical agents will still need some in vivo toxicity data prior to regulatory approval for first-in-human studies.  In the introduction it would be helpful to specify the precise leukaemia being studied and at which age. In particular, relapse rates in adult B-ALL are much higher than those presented, which are indicative of the paediatric setting.In the 2D co-culture methods, please provide a reference on how to process MSCs and specify the final volume of media per well used to plate the leukaemia cells.For the response data presented in figures 1 and 4, please clarify in the legend or methods the nature of the readouts and timepoints used. Minor points:Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?PartlyAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Leukaemia biology, disease modelling, stem cells, epigenetics, preclinical drug testing.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.


Oncorhynchus kisutch) are a culturally and economically important species that return from multiyear ocean migrations to spawn in rivers that flow to the Northern Pacific Ocean. Southern stocks of coho salmon in Canada and the United States have significantly declined over the past quarter century, and unfortunately, conservation efforts have not reversed this trend. To assist in stock management and conservation efforts, we generated a chromosome-level genome assembly. We also resequenced the genomes of 83 coho salmon across the North American range to identify nucleotide variants and understand the demographic histories of these salmon by modeling effective population size from genome-wide data. From demographic history modeling, we observed reductions in effective population sizes between 3,750 and 8,000 years ago for several northern sampling sites, which may correspond to bottleneck events during recolonization after glacial retreat.Coho salmon ( Oncorhynchus keta), pink (O. gorbuscha), and sockeye salmon (O. nerka) increased throughout the North Pacific after 1977, the opposite was true for coho and Chinook salmon (O. tshawytscha). These declines became particularly acute after 1989 when marine survival for these species began a downward spiral that has yet to be reversed  were harvested . Howeverreversed . A severreversed . ImproveIn a large-scale population structure analyses of coho salmon sampled from 318 localities, in 38 different regional groups in North America and Russia , 17 microsatellite loci showed that salmon clustered geographically and regions could be delineated along a north—south gradient, with reduced variation to the north and isolated inland populations  [see FigSalvelinus alpinus) are thought to have persisted in refugia north of the North American ice sheets  generate a high-quality chromosome-level reference genome assembly and (2) estimate the timing of coho salmon recolonization of northern streams. Our method to construct a high-quality genome assembly was to use multiple sequencing technologies and techniques to complement each other. Our method to estimate the timing of recolonization was to resequence the genomes of 83 coho salmon and model effective population size from a comprehensive inventory of SNPs. This was done to identify genetic bottlenecks after the last glacial maximum corresponding to founding events during recolonization.All animals were reared in compliance with the Canadian Council on Animal Care Guidelines, under permit from the Fisheries and Oceans Canada Pacific Region Animal Care Committee (under Ex.7.1). Using Inch Creek coho salmon  was applied 6 hours post-fertilization (10°C) to coho salmon eggs that had been fertilized with UV-inactivated Atlantic salmon sperm . SurviviDNA for Illumina sequencing was extracted from frozen muscle tissue using a Phenol:Chloroform extraction [adapted from  was ground into a powder with a mortar and pestle with liquid nitrogen. The powder was transferred to a 5 ml LoBind Eppendorf tube, along with 3600 ul buffer ATL (Qiagen), 400 ul proteinase K solution (Qiagen) and 40 ul RNAse A solution (Qiagen). The sample was digested at 56°C for 3 hours, with rotation at ∼4 rpm. A phenol-chlorform-isoamyl alcohol (25:24:1) purification was performed 3 times, followed by 1 round of chloroform-isoamyl alcohol (24:1). At each stage, 1 volume of organic was mixed with 1 volume of aqueous, inverted slowly for 3 minutes to mix thoroughly, spun for 15 minutes at 5000 g to separate the layers, and the aqueous top layer was transferred very slowly to a new tube using a 1000 ul pipette and wide bore tip. RNAse A solution  was added and incubated at room temperature for 1 hr, followed by 5 ul Proteinase K (20 mg/ml) overnight at 4°C. Approximately 750 ul was obtained from each tube after the final stage. This volume was transferred to a Spectra/Por Float-A-Lyzer G2 1000 kD (pink) dialysis device, and dialysis was performed in 1 L of 10 mM Tris-Cl, pH 8.5 at 4°C with gentle mixing for 1 week, changing buffer 5 times. DNA quantity was determined by Qubit and quality by 0.6% agarose gel at 60 Volts.Library preparation and sequencing details for the various sequencing technologies and samples can be found under the following NCBI submissions: 10× Chromium , Hi-C (SRX5975810), PacBio Sequel (SRX5975835–SRX5975836), PacBio RS II (SRX2338326–SRX2338334), Illumina mate-pair , and Illumina overlapping paired-end (SRX2333080—SRX2333081).All PacBio data was assembled using Canu v1.8 (Arrow v 2.2.2 from SMRTlink 6.0.0.47841 (PacBio) was used to polish the assembly with PacBio data with the ArrowGrid wrapper program  (https://github.com/lh3/bioawk) was used to remove any remaining scaffolds smaller than 1001 bp .A custom gap-closing script was run to attempt to fill newly scaffolded gaps with error-corrected PacBio data, for full details see , and a mAfter the Tigment pipeline, Hi-C data was aligned to the genome with Juicer 1.5.6  was used to generate the NCBI AGP files. After manual editing to rename linkage groups based on prior assemblies and the northern pike linkage map  or a MagMAX DNA Multi-Sample Ultra Kit with a KingFisher (ThermoFisher Scientific). Following DNA extraction, samples were quantified by Qubit BR DNA assay (ThermoFisher) and integrity validated by agarose gel electrophoresis. At McGill University and Genome Québec Innovation Centre , individual Illumina libraries were constructed with Illumina TruSeq LT sample preparation kits, and each individual was sequenced either on an Illumina HiSeq2500 (PE125) or a HiSeqXTen (PE150), targeting approximately 15–30× coverage. Resequenced genomes were submitted to the NCBI under BioProjects: PRJNA401427 and PRJNA808051 .github.com/broadinstitute/picard) AddOrReplaceReadGroups program was used to add read group IDs, and the MarkDuplicates program was used to mark duplicates (default settings). GATK v3.8 . Private allele counts per river (river is used instead of sampling site throughout the rest of the text) were tallied using the populations module in Stacks  was performed using PLINK . The contig N50 of the assembly was 1,159 kb and the percent of complete BUSCOs was 99%, which is comparable to the human genome assembly also at 99% (NCBI accession: GCF_000001405.39) .i.e. ≤ 91% identity, The coho salmon genome has extensive signatures of chromosomal duplication , which hThe coho salmon genome also has a high retention of repetitive elements ; Table 3P-value = 0.068). In this study, we had fewer sampling sites and fewer samples in general than previous studies that did find a significant correlation of genetic distance and geographic distance  and observed heterozygosity  in the upper Columbia River that similarly appear divergent from all other populations of sockeye salmon and kokanee   occurring in this population around 4,000 years ago. We only collected samples from one tributary of the Thompson River (a part of a much larger basin) and can only suggest that a plausible hypothesis from this data is that recolonization of the Salmon River from a small founding population took place after glaciers receded. We did not account for the influence of hatcheries, which could also influence some of the metrics discussed above. Also, we did not incorporate linked selection in demographic modeling as the type of analysis that we used was not amenable. Without linked selection accounted for, there could be biases in times and effective population sizes from our estimates  to between 3,750–8,000 years ago. These values are based on assumptions of a mutation rate of 8e–9 bp/generation and a generation time of 3 years. Linked selection may also bias our time and effective population estimates (While it is important to remember that time and population estimates are influenced by many factors when inferring demographic histories from sequence data, multiple lines of evidence can be used to strengthen these inferences or put them in a more realistic context. Radiometric evidence supports that the Cordilleran Ice Sheet maximum occurred between 19,000 and 20,000 years ago (The overall trend we observed from modeling demographic histories was major drops in effective population size at each transition from glaciation to inter-glaciation period with increases for nearly all populations after the penultimate glaciation period and uncommon increases for specific rivers after the most recent glaciation period. At a species level, these transitional drops in effective population size likely influence multiple aspects of coho salmon biology since genetic variability can contribute to many characteristics of a species.In this study, we generated a high-quality reference genome assembly as a tool for conservation and management of coho salmon. Additionally, we resequenced the genomes of a wide distribution of coho salmon from rivers along North America to identify nucleotide variants that will have significant utility for other analyses of coho salmon genetics. We modeled demographic histories of the coho salmon with this data and estimated recolonization occurred between 3,750–8,000 years ago for some northern streams, and observed that major reductions in effective population size were related to changes between glacial and inter-glacial periods. This coho salmon genome assembly will facilitate research to better understand coho salmon biology in the future and will enhance management of this culturally and economically important species.jkad033_Supplementary_DataClick here for additional data file.


Breast cancer represents the most frequently diagnosed malignancy among women with 10%–20% of all cases involving the deadliest of all subtypes, triple-negative breast cancer (TNBC).,Molecular Therapies – Nucleic Acids, establishes multifunctional 3WJ RNA nanoparticles to target TNBC tumors through aptamer-mediated guidance that enhances the delivery of therapeutics to hinder tumor progression. The reported findings are not only significant to the field of nucleic acid therapies but also contribute to advancements in TNBC management and targeted treatments.In the current work, the international team led by Peixuan Guo, Li-Ching Chen, and Yuan-Soon Ho utilizes a robust RNA nanotechnology framework for the development of modular platforms crafted for targeted delivery of therapies to TNBC. This platform employs thermodynamically and chemically stable RNA three-way junctions (3WJs), which are RNA motifs efficiently self-assembled from three concise strands. The integration of these strands, each individually functionalized with therapeutic nucleic acids, an RNA aptamer selected to target This research represents a novel demonstration of the potential of combining targeting, imaging, and therapeutic moieties within a single RNA nanoparticle for combination therapy in cancer treatment.in vivo studies involving mice with TNBC xenografts were conducted. Following injection by tail vein, a higher signal of 3WJ-in vivo targeting due to the inclusion of in vivo studies are crucial for assessing the biodistribution and biological interactions of the newly developed 3WJ-in vitro cell studies.To further evaluate the TNBC tumor targeting efficacy of the 3WJ- Following confirmation of tumor targeting and uptake in mouse models, 3WJ-in cellulo was followed by tumor growth inhibition studies in vivo using the TNBC xenograft mouse models. Mice injected with 3WJ-The effective repression of TNBC cell growth by 3WJ-,While the reported technology holds promise for the future of TNBC management and offers potential for expanding therapeutic applications of nucleic acid nanotechnology, it is important to recognize that some additional studies may be necessary to address certain potential limitations. Depending on their composition and architectural parameters, RNA nanoparticles are known to activate various immune responses and thereby may cause adverse reactionsIn summary, this study presents stable functional RNA nanoparticles able to target


SERPINA1 sequencing would identify undiagnosed AATD. We performed a retrospective cohort study in a deidentified Electronic Health Record (EHR)-linked DNA biobank with 72,027 individuals genotyped for the M, Z, and S alleles in SERPINA1. We investigated liver transplantation frequency by genotype group and compared with hepatitis C infection. We performed SERPINA1 sequencing in carriers of pathogenic AATD alleles who underwent liver transplantation. Liver transplantation was associated with the Z allele  and with hepatitis C . For liver transplantation, there was a significant interaction between genotype and hepatitis C . Sequencing uncovered a second, rare, pathogenic SERPINA1 variant in six of 133 individuals with liver transplants and without hepatitis C. Liver transplantation was more common in individuals with AATD risk alleles (including heterozygotes), and AATD and hepatitis C demonstrated evidence of a gene-environment interaction in relation to liver transplantation. The current AATD screening strategy may miss diagnoses whereas SERPINA1 sequencing may increase diagnostic yield for AATD, stratify risk for liver disease, and inform clinical management for individuals with AATD risk alleles and liver disease risk factors.Alpha-1 antitrypsin deficiency (AATD), a relatively common autosomal recessive genetic disorder, is underdiagnosed in symptomatic individuals. We sought to compare the risk of liver transplantation associated with hepatitis C infection with AATD heterozygotes and homozygotes and determine if  SERPINA1. Decreased functional A1A exposes host tissues to non-specific neutrophil proteases leading to tissue damage; this loss of function is the primary mechanism of lung disease in AATD [Alpha-1 antitrypsin deficiency (AATD) is an autosomal recessive Mendelian genetic disorder caused by reduced abundance or dysfunction of the alpha-1 antitrypsin (A1A) protein, encoded by  in AATD . Accumul in AATD , 3. Tiss in AATD .SERPINA1 gene. Screening for AATD consists of quantifying A1A in the blood and, if the level of A1A is low, gel-electrophoresis-based protease inhibitor (PI) typing determines which SERPINA1 alleles are present. The reference allele in the SERPINA1 gene is referred to as “M”; the most common pathogenic alleles are “Z” (more severe) and “S” (more common but milder AATD) [There are a variety of pathogenic alleles in the er AATD) . Within er AATD) .Estimations of AATD prevalence in European ancestry populations are between 1:2000–7000 –8 while Beyond the marginal benefit provided by enzyme replacement therapy, providing an AATD diagnosis can alter the disease course , 12. TheSERPINA1 whose symptoms overlap with AATD but lack a formal diagnosis, at times despite having been clinically tested.We sought to identify undiagnosed cases of AATD among individuals who had undergone liver transplantation. We compared the frequency of liver transplantation between AATD risk alleles and a non-genetic cause of liver failure, hepatitis C infection. Additionally, we hypothesized that the current screening strategy that consists of A1A levels with reflex PI typing will miss rare cases of AATD. Here, we confirmed that individuals homozygous and heterozygous for AATD risk alleles both have increased rates of liver transplantation, demonstrated that there is a gene-environment interaction between AATD-risk alleles and hepatitis C infection in the context of need for liver transplantation, and identified individuals who are compound heterozygous for rare pathogenic variants in SERPINA1. We hypothesized that frequency of liver transplantation would correlate with AATD-related genetic risk and sought to determine how that risk compared to the risk of transplantation with hepatitis C infection. We hypothesized that AATD would be over-represented in individuals who had undergone liver transplantation and that those individuals could provide the opportunity to identify undiagnosed AATD through SERPINA1 sequencing.This is a retrospective cohort study utilizing an Electronic Health Record (EHR)-linked DNA biobank. Deidentified EHR data were collected over a 31-year period at our tertiary care center institutional biobank and included 72,027 European ancestry individuals genotyped for the M, Z, and S alleles in This study was reviewed and the need for ethical approval was waived by the Vanderbilt Institutional Review Board (IRB) and deemed as non-human subject research. Individuals with DNA specimens and linked, de-identified electronic health record (EHR) data were obtained from BioVU, Vanderbilt’s DNA biobank . As this® Expanded Multi-Ethnic Genotyping Array plus custom content (VUMC BioVU MEGAEX). After Illumina’s GenomeStudio Genotyping Module, rigorous QC measures were conducted in which data were filtered by both sample and SNP call rates > = 95% and minor allele frequency >1%; gender mismatch was reviewed and discrepancies resolved, if possible, and data removed if unresolvable; concordances of genotype with HapMap and duplicated samples and concordance of allele frequency with gnomAD database were checked. Admixture 1.3 software [SERPINA1 were collected and included the reference “M” allele and the most common pathogenic alleles, “Z” and “S.”Genotype data were obtained from DNA specimens in BioVU , 32. Incsoftware  was usedWe identified individuals who had undergone liver transplantation and those who had evidence of hepatitis C infection in their EHR. Hepatitis C was chosen as a relatively common environmental exposure that increases risk for liver failure requiring transplantation. The presence or absence of an ICD code for hepatitis C infection was more readily ascertainable than exposures like tobacco or alcohol which change in quantity and frequency over time and are inconsistently reported in EHR data.SERPINA1 that were rarer than the most common, known pathogenic allele . Literature review was used to determine if the rare sequence variants identified were known to be previously reported pathogenic variants in AATD.MS or MZ heterozygotes genotype groups who underwent liver transplantation were chosen for whole exome sequencing (WES) to determine if there were other pathogenic alleles that were not captured on the genotyping array; 140 of those individuals had sufficient quantity and quality of DNA for sequencing. WES reads were processed via Illumina dynamic read analysis for genomics (DRAGEN), a GATK-based germline short variant discovery pipeline in Illumina BaseSpace Sequencing Hub. DRAGEN’s “hard filter” and SNPs call rate >90% were applied to remove low quality variants. WES analysis focused on variants in SERPINA1 and seven individuals who underwent liver transplantation, were heterozygous for a variant in SERPINA1, and had evidence of hepatitis C infection. Chart review investigated the sex, age, BMI, alcohol- and tobacco-use history, COPD status, and A1A level measurements and PI typing, if available, and included full access to de-identified content of the EHRs.Chart review was performed on the six compound heterozygotes for rare variants in Data analyses were conducted in R Version 3.6.1 . Means of continuous variables were compared with a Wilcoxon rank sum test. Confidence intervals for percentages were calculated using the “BinomCI” function and the Wilson continuity correction. P-values were calculated with Fisher’s exact test  to compare discrete count data. They were not corrected for multiple comparisons. Linear and logistic regressions were performed with the “glm” function and were corrected for age, sex, and number of years of EHR data available.There were 72,027 individuals of European ancestry for whom both EHR and genotype data were available . 56% werSERPINA1 genotype groups (We assessed the rates of liver transplantation across e groups . When coe groups .-16) (-16), MZ (p = 2.16e-13), and SS (p = 2.98e-02) genotype groups but not significant in the SZ (p = 0.11) and ZZ (p = 0.21) groups (-16). The interaction between non-reference SERPINA1 genotypes and hepatitis C for the outcome of liver transplantation was significant for all groups  . With bo) groups . There w) groups . The assSERPINA1 exons were examined in both S and Z heterozygotes to identify any rare pathogenic variants not captured through genotyping. Of the 140 individuals sequenced, seven had hepatitis C infection; none of those individuals had a second pathogenic variant identified  underwent liver transplantation compared with 8.76% of individuals with two pathogenic AATD alleles and the absence of hepatitis C infection. Similarly, 24.7% of heterozygotes for either the S or Z allele underwent liver transplantation when they had hepatitis C infection compared to 1.54% without hepatitis C infection. Other environmental exposures, such as alcohol or obesity, or other unmeasured genetic factors likely contributed to increased risk of liver transplantation for individuals who were either heterozygous or homozygous for AATD risk alleles.SERPINA1 sequencing facilitated identification of six individuals who are compound heterozygous for pathogenic variants. Only one of these individuals had evidence of an AATD diagnosis after full-text review of their medical records, indicating that some or all of these individuals may represent missed AATD diagnoses while acknowledging the presence of other liver disease risk factors such as obesity in these individuals likely makes their need for transplantation multifactorial. Correlation of A1A level and SERPINA1 genotype revealed individuals with two pathogenic alleles who have normal A1A levels. There one individual with a ZZ genotype, normal A1A levels, and who was not on A1A augmentation therapy in this work  diabetes , 25, butdiabetes ; the preSERPINA1 identified in sequencing. While other environmental exposures like obesity and alcohol use could additionally contribute to the liver dysfunction in these patients ,function , 50. Thefunction  which coSERPINA1 sequencing into routine AATD screening may be higher in general populations with liver failure. Except for the 140 individuals that underwent SERPINA1 sequencing, we have no ability to determine the proportion of M alleles are truly functional/reference alleles and how many are dysfunctional M variant alleles. ICD codes for hepatitis C infection do not capture whether individuals were viremic and the temporal relationship between hepatitis C infection diagnosis and liver transplantation. Finally, this is a retrospective study. A randomized controlled trial comparing the current A1A measurement with reflex PI typing screening strategy with SERPINA1 sequencing would more conclusively demonstrate superiority of sequencing over the standard measurement of A1A level with reflex PI typing for AATD screening.This study has several limitations. Use of ICD codes and phecodes can miscategorize individuals; this was the case for the individual who lacked an ICD code for AATD but had evidence of this diagnosis in manual chart review. Additionally, this study was limited to individuals of European descent. While AATD is most common in this ancestry, work should be done to investigate its applicability to other demographics. AATD is likely overrepresented and more frequently tested in this population who were seen at a quaternary-care facility that performs liver transplantation. However, the potential benefit of incorporating SERPINA1 sequencing into the AATD screening process to capture those individuals who may not present with a low A1A level or a detectable pathogenic allele on PI typing. This work providers further support that carriers for AATD have an increased risk of liver failure, especially in the context of other environmental risk factors , and more inclusive screening measures may help mitigate AATD-related end-organ damage through lifestyle modifications and new pharmacologic interventions.In summary, increasing consideration should be given to the incorporation of


We couple halidevapor phase epitaxy (HVPE) growth of III–Vmaterials with liftoff from an ultrathin carbon release layer to addresstwo significant cost components in III–V device - epitaxialgrowth and substrate reusability. We investigate nucleation and growthof GaAs layers by HVPE on a thin amorphous carbon layer that can bemechanically exfoliated, leaving the substrate available for reuse.We study nucleation as a function of carbon layer thickness and growthrate and find island-like nucleation. We then study various GaAs growthconditions, including V/III ratio, growth temperature, and growthrate in an effort to minimize film roughness. High growth rates andthicker films lead to drastically smoother surfaces with reduced threadingdislocation density. Finally, we grow an initial photovoltaic deviceon a carbon release layer that has an efficiency of 7.2%. The findingsof this work show that HVPE growth is compatible with a carbon releaselayer and presents a path toward lowering the cost of photovoltaicswith high throughput growth and substrate reuse. Growth of III-Vs using halide vaporphase epitaxy (HVPE) may significantly reduce the cost of semiconductorgrowth due to its high source material utilization, use of elementalgroup III precursors, and ultrafast growth rates beyond 500 μm/h.15 Material quality is still maintained at these high growth rates,and HVPE growth of binary, ternary, and quaternary III–V materialswith high-quality heterointerfaces results in photovoltaic devicesthat perform as well as those grown by traditional OMVPE techniques.22 HVPE growth of III-Vs commonly employs a hydrogen carrier gas, whichis likely incompatible with carbon-based interlayers because highflow rates of H2 selectively etch graphene.23 Studies on graphene interlayers show that exposureto hydrogen process gas results in poor interfaces affecting the qualityof the overgrown layer.24 Instead, the use of a nitrogencarrier gas is another option for HVPE growth that overcomes the 2Dlayer degradation challenge.9 The use ofnitrogen may also be an advantage for cost reduction because growthrates of up to 528 μm/h have been reported for GaAs grown byHVPE using a nitrogen carrier gas15 andreduce operating cost due to its inert properties.Organometallicvapor phase epitaxy (OMVPE) growth of GaAs-on-GaAsthrough a thin amorphous carbon interlayer was demonstrated,Here, westudy nucleation and growth conditions for GaAs filmsgrown on a thin, amorphous carbon (aC) interlayer, combining the benefitsof rapid HVPE growth under nitrogen with efficient substrate reuse.We demonstrate full exfoliation of up to 10 × 10 mm GaAs films,indicating that the underlying aC layer remains sufficiently intactafter the HVPE growth process. The grown layer is (001)-oriented andthus maintains a registry to the underlying substrate. We also investigatehow growth temperature, growth rate, and V/III ratio affect the resultingmorphology of GaAs films grown by HVPE through an aC interlayer anddetermine planarization conditions that result in smoother films withlower defect densities. Finally, we demonstrate initial photovoltaicdevices grown on aC interlayers. The union of HVPE growth and substratereuse using a weakly bonded interlayer thus presents a pathway towardlower-cost, high-quality optoelectronics.1.12 environment before transferto the HVPE reactor and the sample in 2 dry box environment for one week. Due to the locationof the reactors, we were unable to explore samples with less than2 days of exposure after carbon growth. The sample grown on the moreexposed carbon layer is significantly rougher and more faceted. Wenote that a general trend of very rough or nonplanarized films onolder substrates remained constant over many growth attempts, butthis work was not able to explore exact chemical changes to the carboninterlayer or sources of degradation. Unless otherwise noted, allsamples described in this manuscript are grown within 2 days of carbonsubstrate growth to minimize these effects as much as possible.We firststudied the effects of environmental exposure on the surface of thecarbon substrate. The carbon interlayer is grown by an OMVPE and thenpackaged in an inert atmosphere to transfer for HVPE growth. 12 Previousstudies on graphene interlayers show GaAs quality to be sensitiveto the thickness of the 2D interlayer; an overly thick layer suppressesregistry with the underlying III–V substrate and an overlythin layer results in incomplete coverage of the substrate and leadsto direct bonding between the substrate and film such that the filmcannot be exfoliated.10With an initial understanding of sample transfereffects on thecarbon substrate, we then studied the effects of aC layer thicknesson the nucleation of HVPE-grown GaAs layers. Two different aC layerthicknesses were prepared by varying aC growth time, where the thinnerlayer was deposited for 5 min and the thicker layer was depositedfor 13 min. In both cases, aC layers are deposited on III–Vsubstrates, as described in the Methods. We were not able to determinethe exact thickness of the aC layers investigated here due to challengesin measuring layer thicknesses approaching the monolayer limit, butinitial studies suggest that the average thickness of aC is arounda monolayer for the thinner sample.252 for thinner and thicker aC interlayers, respectively. Thickinterlayers may shield remote interactions between the substrate andthe growing layer,12 so increased nucleationdensity on the thinner aC layer is likely a result of a sufficientlythin interlayer capable of enabling remote epitaxy. Increased islanddensity could also result from nucleation through pinholes of an uncoalescedcarbon layer; however, as discussed later and demonstrated in Figure SI.1, coalesced films are fully exfoliatedfor both aC interlayer thicknesses, leaving intact substrates andfilms. Spalling marks indicative of pinhole-based selective epitaxywere not observed in this work.27We also find a growthrate dependence on the film coalescence.Films deposited at 0.30 μm/min, as shown in 1.22 process gas is used to offset the potentialfor etching of the aC interlayer by H2; however, hydride-basedprecursors are still used as part of the HVPE process and may leadto etching of the aC layer. An incomplete aC interlayer will impactthe ability to exfoliate layers from the parent substrate. As such,we test exfoliation of a fully coalesced GaAs film to determine ifthe carbon layer remains intact after film growth. 9A primary goalof this work is to demonstrate HVPE as a viable III–Vgrowth method on carbon interlayers for substrate reuse. As discussedbefore, a N11 EBSD results are almost uniformly(001)-oriented and more closely resemble the results for growth ona monolayer of graphene than growth on a bilayer.11 This further suggests that the aC interlayer is sufficientlythin to allow interaction between the substrate and growing layeras a thick, uninterrupted layer of carbon results in polycrystallinegrowth.9 While a demonstration of regrowthand thus substrate reuse was outside the scope of this work, examplesof substrate reuse through an exfoliated GaAs-on-aC interlayer areshown in a previous study.12The structure is investigated at the front andback surfaces ofthe film to determine the registry of the grown layer with the substrate.X-ray diffraction, shown in 1.328 further optimization of growth conditions was thus required to minimizethis parameter. We consider the effect of the V/III ratio, temperature,and growth rate on films with an approximate thickness of 500 nm.The inset of 2 scan areaas a function of growth rate, growth temperature, and V/III ratio,respectively. All films are single crystals, fully coalesced, and(001) oriented with no detectable competition from other crystallographicorientations . We notethat all samples studied here were (001)-oriented GaAs like that ofthe sample demonstrated in 19Initial measurementsof films show a high surface roughness unlikelyto accommodate high-quality device growth;ions see SI.2. We ions see SI.2. We ions see SI.2. We 29 The conditions usedhere are consistent with planarization conditions optimized in recentwork studying HVPE growth on roughened substrates under hydrogen gas.29 This work shows that similar planarization resultsoccur under nitrogen.We used the findings of the parametric studiesto optimize thegrowth of a GaAs layer on aC. We achieved a further reduction of filmroughness from the films demonstrated above using a low V/III of 5,a growth temperature of 650 °C and a growth rate of about 4 μm/min,which has been increased via an increased flow of nitrogen throughthe center tube to 4000 sccm. 8 cm–2 for measurementsaveraged over five 250 μm2 regions. This defect densityis a significant improvement from the dislocation density in the unoptimizedfilms from 8 cm–2 and thus abovethe detector threshold) but is high enough to adversely impact deviceperformance. These dislocations possibly derive from the merging ofislands after nucleation, but further investigation is warranted.30 Another potential route for improvement is inthe quality of the amorphous carbon layer. Our observations in 9 and we, therefore, suspect that further optimization ofthe aC surface could reduce the defect density of our GaAs layersby promoting more uniform film growth.Low dislocation density is critical for achievinghigh-performancedevices because dislocations serve as recombination sites for thegenerated carriers. 1.4JSC) and open circuit voltage (VOC) in solarcells. The carbon interlayer cell has an efficiency reduction relativeto the control that suggests the presence of TDD on the order of 108 cm–2 based on previous studies of defectivecells, in agreement with our ECCI results.30We grewan upright, rear heterojunction GaAs solar cell on a GaAs substratewith an aC interlayer to show an initial demonstration of device performance. Figure SI.3 shows the same cell structure grownby HVPE on an OMVPE-grown buffer wherein no break in vacuum occurredbetween the growth of the aC layer and the buffer layer. This comparisonprovides a picture of what is possible for an HVPE-grown cell on thesereusable templates; other explanations of cell performance indicatedby this comparison are the subject of a future study. At this time,we are unable to determine if improved performance is due to superiornucleation by OMVPE, reduced carbon layer degradation, or some combination;further study is needed.Unfortunately,these cells were unable to be grown immediatelyafter the growth of the aC substrates, so this study is unable todecouple the detrimental effects of coalescence and carbon degradation.In the ideal case, the carbon layer and subsequent device would begrown either in-line or without breaking vacuum. As an example, 2Thisstudy presents the successful nucleation of GaAs on III–Vsubstrates through a thin carbon interlayer. The interlayer materialhere is amenable to wafer-scale deposition; the exfoliation methodis relatively rapid, and the growth method described here is capableof producing III–V devices at high throughput. We show singlecrystal films that fully exfoliate from the substrate, demonstratingthat these techniques are possible in tandem. We further investigatethe effect of varied growth conditions on film quality, namely, filmroughness and defect density, and find that film quality is significantlyimproved for growth conditions with low V/III ratios and high growthrates at or above around 0.75 μm/min. Planarization techniquesdrive film morphologies toward smooth surfaces better suited for devicegrowth. Initial device growth yields a cell efficiency of 7.2% (withoutantireflection coating) for HVPE-grown single junction upright GaAscells; device quality can likely improve by limiting air exposureto the carbon layer prior to transfer to the HVPE reactor.33.1Approximately 500 nm thick AlGaAs layers weredeposited by OMVPEon a GaAs substrate with a 6° offcut toward (111)A. AlGaAs werechosen as they are more thermally robust than GaAs and are thus amore suitable candidate for the subsequent carbon deposition process.An amorphous carbon layer was then deposited at MIT on the AlGaAssubstrate by an OMVPE after heating to around 700 °C; flowingtoluene and nitrogen are used as a carbon precursor and a carriergas, respectively. More details on the substrate preparation processcan be found in ref . After g3.215 Boats containing elemental group III precursors were held at a constanttemperature of 800 °C and the growth zone temperature was variedbetween 575 and 750 °C as noted in the text. Thickness calibrationsamples were prepared on epi-ready GaAs substrates with a 6°offcut toward the (111)A face using growth conditions identical tothose used for growth on aC interlayers. Growth rates were variedby modulating the flow of the nitrogen carrier gas that delivers uncrackedhydrides to the substrate surface as described in previous studies.20 For devices, the n-type dopant is selenium and is provided by aflow of H2Se; the p-type dopant is zinc and is providedby a diethylzinc source.GaAs films were grown in a customtwo-growth-chamber HVPE reactorusing a nitrogen process gas described in detail elsewhere.3.312The GaAs filmgrown on aC was exfoliated by using the following process. First,a 35 nm-thick Ti layer is deposited by electron-beam evaporation asan adhesion layer. Next, a high-stress Ni stressor layer is depositedby DC sputtering with a thickness of 3–7 μm. A thermallyreleasable tape is then attached on the Ni, and the entire stack oftape/Ni/Ti/GaAs layers is manually exfoliated at the aC interfaceby mechanical peeling. This method is described in more detail inReference.3.4Nucleationdensities for GaAs islands were calculated from optical profiles capturedby a Keyence profilometer. Data processing was performed in ImageJusing the MorphoLibJ package. X-ray diffraction was collected usinga Panalytical X’Pert Pro instrument in a symmetric scan mode.The growth rate was calibrated by first growing a GaInP layer on anepi-ready GaAs substrate and then growing a GaAs layer under the samegrowth conditions as those used on aC; the top GaAs layer was partiallymasked and selectively etched, and layer height was determined bycontact profilometry.2 scan area with 3 s of collection time per line.Average roughness was characterized by using instrument software analysisover the full scan area following background correction. Electronchanneling contrast imaging (ECCI) was conducted on an FEI Nova NanoSEM630 operating at 25 kV accelerating voltage and 3.2 nA beam currentand defect densities were calculated by counting the number of defectswithin a total imaging area of approximately 1250 μm2. SEM was performed on the same instrument operating at a 3 kV acceleratingvoltage and 0.64 nA beam current.Electron backscatter diffraction (EBSD)patterns are collected using a Zeiss Merlin high-resolution scanningelectron microscopy (SEM). A beam acceleration voltage of 15 kV anda current of 3 nA are used for the EBSD mapping. Atomic force microscopy(AFM) was collected using a Nanosurf EasyScan 2 collected over a 100μm3.5Devices are processedusing standard photolithography techniques, and Au metal is electroplatedfor both front and rear contacts. Light and dark current density asa function of voltage (J-V) is collected on an XT-10 continuous wavesolar simulator with a xenon arc lamp under a simulated AM1.5G spectrum.Light intensity is calibrated against a GaAs reference cell to simulate1-sun conditions. Quantum efficiency was measured using a home-builtsystem that contains a reflectance diode; reflectance spectra wereused to determine the layer thickness. Cells measured here do nothave an anti-reflective coating and have not been certified by anindependent laboratory.


We included 25 patients with a maximum five years of disease duration and 25 controls, and isolated four immune cell populations from each fresh blood sample. Epigenome-wide DNA methylation profiles were generated from 186 samples using the Illumina MethylationEpic array and association with disease status was tested using linear regression models. We identified six differentially methylated CpGs in CD14+ monocytes and one in CD8 + T cells. Four differentially methylated regions were identified in monocytes, including a region upstream of RAB32, a gene that has been linked to LRRK2. Methylation upstream of RAB32 correlated negatively with mRNA expression, and RAB32 expression was upregulated in Parkinson’s disease both in our samples and in summary statistics from a previous study. Our epigenome-wide association study of early Parkinson’s disease provides evidence for methylation changes across different peripheral immune cell types, highlighting monocytes and the RAB32 locus. The findings were predominantly cell-type-specific, demonstrating the value of isolating purified cell populations for genomic studies.Understanding the contribution of immune mechanisms to Parkinson’s disease pathogenesis is an important challenge, potentially of major therapeutic implications. To further elucidate the involvement of peripheral immune cells, we studied epigenome-wide DNA methylation in isolated populations of CD14 The prospect of immunomodulation is currently one of the most promising strategies for disease modification in PD3, and an improved understanding of the contribution of different classes of leukocytes may be pivotal for further progress.Parkinson’s disease (PD) is a progressive neurodegenerative disorder, for which there is currently no effective disease-modifying therapy. Over the last decades, a growing body of evidence has demonstrated the important role of the immune system in PD pathogenesis, yet the specific mechanisms involved and the interrelations between microglial and peripheral immune processes are incompletely understood5 and recognize peptides of the neuropathological hallmark protein α-synuclein presented by human leukocyte antigen (HLA) class II proteins6. Levels of α-synuclein autoantibodies have also been studied with mixed results7, and genome-wide association studies (GWAS) have consistently reported a significant PD risk signal in the HLA region on chromosome 69. However, studies integrating genetic association statistics with cell-specific data have primarily linked genetic PD risk to innate immunity and the myeloid lineage13, a finding that is also mirrored in Alzheimer’s disease (AD)14. In line with these observations, a recent transcriptomic study of CD14+ monocytes reported widespread alterations in PD15.Highlighting the relevance of the adaptive immune system, T cells have been shown to infiltrate the substantia nigra16. A growing body of evidence implicates epigenetic mechanisms in neurodegeneration and PD pathogenesis19. DNA methylation at CpG dinucleotides is the most studied epigenetic modification in the context of complex disease. Hypothesis-free epigenome-wide association studies (EWAS) have been performed in a small series of post-mortem human brain tissue comparing PD to control brains22 and a larger study of bulk cortical tissue from our group investigated Lewy body pathology as outcome, including donors with both PD and dementia with Lewy bodies23. Two PD EWAS have studied isolated cortical neurons using either flow cytometry24 or magnetic-activated cell separation25. A number of PD studies have investigated differential methylation in whole blood30. Sample sizes of whole blood PD EWAS have been gradually increasing, and the largest study to date included more than 2000 participants and reported a hypermethylated CpG site in PD near SLC7A11, a gene involved in glutamate signaling30. Methylation analyses in blood may be particularly interesting as a tool to characterize immune mechanisms in PD, and a recent EWAS study highlighted immune dysregulation both in PD generally and specifically in patients with depression29. These are promising findings, yet the use of whole blood for differential methylation analyses entails major caveats. Whole-blood EWAS typically applies an algorithm to adjust for estimated cell-type composition, but essentially measures the noisy, joint effect of methylation across all cell types in the sample, limiting both the power to detect cell-type-specific signals and the interpretation of positive findings. Furthermore, most studies have included patients many years from PD diagnosis, when downstream effects of the disease and its treatment may have a major impact on methylation.Epigenetics influence complex disease by mechanisms of gene regulation that are partially dynamic over time, cell-type-specific, and shaped by both genetic and environmental factors+ monocytes, CD19+ B cells, CD4+ T helper cells and CD8+ cytotoxic T cells in 25 patients with early PD and 25 healthy controls. We nominate differentially methylated CpGs and regions, with monocytes showing the highest number of significant findings.To further elucidate the contribution of different classes of immune cells and identify cell-type-specific alterations in gene regulation, we performed epigenome-wide DNA methylation profiling of purified cell populations representing major peripheral cell types of the innate and adaptive immune system, namely CD1431 and had a maximum disease duration of five years from motor onset at the time of blood draw. Eight out of 25 PD patients were included at the time of diagnosis and had not used any medication for PD. Mean disease duration from the time of PD diagnosis was 1.2 years and mean age at diagnosis was 55. Controls had no immunological nor neurological disease and no parkinsonism in first-degree family members. Demographics are presented in Table Patients were diagnosed based on Movement Disorders Society criteria+ monocytes from the three classes of lymphocytes , with a slight overabundance of low P values also in CD8 + T cells.Following association testing in each cell type by linear regression, including sex, age, and the first surrogate variable as covariates (see “Methods”), we assessed the distribution of P value distributions which could indicate poor modeling of data33. Previous EWAS studies in both PD25 and Alzheimer’s disease34 have reported striking sex differences, arguing for sex-stratified analysis of methylation data rather than merely inclusion of sex as a covariate in linear regression. We considered our sample size too small to attempt the identification of specific differentially methylated CpGs in sex-stratified analyses, yet we performed linear regression split by sex to evaluate P value distributions. Interestingly, sex-stratified regression improved the pattern of P value distributions for both CD8 + T cells and CD19 + B cells, but not for CD14+ monocytes or CD4 + T cells. This may indicate that sex-stratified analysis is warranted for specific cell types and should be explored in future larger studies.In particular CD4 + T cells showed skewed P < 2.25 × 10-8  identified a total of seven signals passing a Bonferroni-corrected significance threshold of P < 0.05) was seen in at least one other cell type for four out of the seven probes, but no probe showed association at P < 0.05 across all cell types. Associations in additional cell types were generally much weaker than the top cell type, and only one passed a Bonferroni-corrected threshold for a total of 21 candidate tests . Figure 35 and peripheral blood mononuclear cells (PBMCs)36, yet blood sampling in our study was performed prior to the COVID-19 pandemic.To further assess whether these association signals were cell-type-specific or shared, we extracted summary statistics from the seven significant probes for all cell types , both with direction of effect consistent with the whole-blood study  associated with cg14704780, cg20636526 or rs112485576 in whole blood using the ARIES mQTL database37, but found no data to support a significant association between the GWAS SNP and differential methylation at these particular CpGs.We further compared the genomic location of the seven significant probes to the top signals reported in the largest PD GWAS to dateP value histograms and individual CpG association results clearly suggested that our experiment had the best potential to detect true signals in CD14+ monocytes, and we prioritized this cell type for analysis of differentially methylated regions. The DMRcate package estimates a smoothed test statistic across probes within a given window and compares this to the expected statistic, using the Benjamini–Hochberg false discovery rate method for calling individually associated probes. A more liberal significance threshold for this initial step than the Bonferroni correction used in the individual CpG association analysis has been recommended38, as the method requires multiple associated probes in the same region, which is also more likely to be biologically relevant than single associated probes. The method identified four differentially methylated regions at P < 0.05 based on Fisher’s multiple comparison statistic, all in CD14+ monocytes  identified by DMRcate. The next region at chr6: 146,863,357–146,863,680 is located upstream of RAB32 and includes three hypomethylated probes that did not reach individual significance at the Bonferroni-corrected threshold. Gene ontology pathway analysis using gometh (see “Methods”) did not identify any significantly enriched GO or KEGG pathways, which was not unexpected given the limited number of significant probes identified for each cell type.15. Comparison with our results is not straightforward, as differential methylation analysis identifies regulatory genomic loci rather than genes. Mindful of this caveat, we performed a lookup of the closest gene to each of the differentially methylated probes and regions in monocytes  in the summary statistics from differential gene expression provided by Navarro et al. Applying Bonferroni correction for ten independent tests, RAB32 was the only differentially expressed gene , upregulated in PD. We also compared the genes proximal to differentially methylated loci in monocytes to 29 genes previously highlighted in a transcriptome-wide association study (TWAS) using gene expression models from peripheral monocytes but found no overlap with our ten monocyte signals39.A predominance of significant findings in monocytes is in line with previous research implicating the myeloid lineage in PD. A recent study investigated monocyte gene expression in 135 PD patients and 95 controls and identified 300 differentially expressed genesRAB32 was also reflected on the mRNA level in our monocyte samples, we performed qPCR (see “Methods”). In line with the results from Navarro et al., we found that RAB32 was upregulated in PD compared to controls  = 0.93 (0.28)). We further observed a strong negative correlation between methylation and RAB32 expression   variable. No association passed adjustment for multiple testing, but we observed P value < 0.05 for the probe in the TSBP1 locus of hypomethylation with dopaminergic treatment (coefficient = −0.60 (0.20), P value = 0.0062 for association between cg14704780 and treatment). Interestingly, this indicates that methylation levels differed more from controls in treatment-naïve patients than in patients receiving medication, a pattern also reported previously for SNCA promoter methylation in whole blood40. We note however, that the level of motor symptoms as assessed by the Unified Parkinson’s Disease Rating Scale (UPDRS) III was significantly higher in the patients who had not yet started PD treatment . The association between 14704780 and dopaminergic treatment was weakened by including UPDRS III in the model, but not eliminated .DNA methylation may be altered by medical treatment, and previous work has indicated that this may be relevant in PD+ monocytes, and one in CD8+ T cells. Our findings indicate dysregulation of immune cells in PD, showing cell-type-specific changes that would not be readily detectable by whole-blood methylation analyses. We included PD patients with less than five years disease duration from diagnosis, 1.2 years on average, indicating that these methylation changes are present early in the disease course. Of the four different immune cell types studied, CD14+ monocytes showed by far the strongest evidence of differential methylation, both as individually significant probes and differentially methylated regions identified by DMRcate. An overrepresentation of low P values at the tail of an otherwise uniform distribution was seen only in CD14+ monocytes, which might potentially reflect more true disease-associated methylation changes in this cell type. These observations are in line with an increasing body of evidence implicating the myeloid lineage in neurodegeneration generally11, as well as in PD specifically39.There is an urgent need to elucidate the immune mechanisms that contribute to PD pathogenesis. We performed a hypothesis-free methylome-wide association study of purified immune cell populations in early PD, identifying differential methylation across ten different genomic loci in CD14LINC03062, alternative name UNQ6494, on chromosome 9. This transcript has been linked to immune infiltration in endometrial carcinoma41 and survival in lung adenocarcinoma42, but potential roles in neuroinflammation are unknown. The region is located ~50 kb downstream of its closest coding gene, GADD45G, which has functions related to DNA damage response and cellular stress signaling43.A differentially methylated region with three individually significant probes was identified in monocyte data near the long noncoding RNA RAB32 and found by qPCR that RAB32 monocyte expression both correlated negatively with methylation in this region and was increased in PD patients relative to controls. Independent evidence supporting a role for this gene was found in summary statistics from a recently published transcriptomic study, also indicating increased expression in PD monocytes15. Interestingly, RAB32 encodes a small Rab GTPase that has been demonstrated to directly interact with and regulate leucine-rich repeat kinase 2, LRRK246. Coding mutations in LRRK2 cause autosomal dominant PD48 and noncoding common variants in the same locus are associated with sporadic PD in GWAS9. Several lines of evidence link the pathogenic mechanisms of LRRK2 to cells of the myeloid lineage, potentially involving both microglia50 and monocytes51. Our findings thus provide further support for RAB32 as implicated in PD pathogenesis through interaction with LRRK2 in myeloid cells.We also identified a hypomethylated region in monocytes upstream of 30. It is well established that PD patients have increased levels of granulocytes and decreased levels of lymphocytes compared to healthy controls53, and although algorithms for cell-type deconvolution are used, there is always the risk that cell composition may be affecting the results. Even if the adjustment for cell composition is accurate, the methylation measured in whole blood will be a mixture reflecting all cell types, quantitatively dominated by granulocytes. Our findings indicate that isolation of homogenous cell populations is essential to identify disease-relevant methylation changes in less abundant cell types. Fluorescence-activated cell sorting (FACS) is an alternative to isolation with magnetic beads used here, and we acknowledge that processing a subset of samples with both methods would have allowed for further methodological validation of this step. Of note, RNA sequencing is increasingly being applied at single-cell resolution, yet this methodology is generally not yet available for DNA methylation analysis.Comparing the methylation patterns of significant probes across all cell types revealed that the differential methylation was largely cell-type-specific. Furthermore, we observed very limited overlap between our own findings and results from recent PD EWAS of whole blood15, RAB32 was the only gene passing an adjusted significance threshold. This strengthens our report of hypomethylation upstream of RAB32 yet limits the interpretability of other signals. It is worth noting however, that simple one-to-one relationships between methylation and gene expression are not the rule in analyses incorporating both types of data54.Our study has several limitations. Most importantly, there is a lack of independent replication of the results. The findings must therefore be interpreted with caution until they can be corroborated by similar methylation analyses from other cohorts. In our attempt to find independent support for 11 genes nominated in monocytes by comparison with summary statistics from a monocyte differential expression analysis reported in a recent PD studyTSBP1, which were also located close to the established PD GWAS signal in the HLA region, but where treatment seemed to associate with a normalization of methylation values.DNA methylation studies cannot differentiate between disease causes and downstream effects, the latter being less relevant for translational research aiming toward novel disease-modifying therapies. We included patients in an early phase of the disease, including nearly one-third de novo patients who had not started medication for PD. Nevertheless, we cannot exclude that treatment effects or other disease-related effects without causal relevance may have contributed to the observed methylation changes. We observed a trend towards association with medication for probes annotated to 55.Importantly, a wide range of lifestyle and environmental factors may differ across groups of PD patients and healthy controls, potentially influencing DNA methylation. Such exposure-driven methylation differences may be mediators of PD risk, but could also be by-products of risk-associated exposures with no causal role or downstream effects of living with PD. Our study did not include the rich exposure data that would be required to dissect these complex relationships. This limitation is a major general caveat for most current complex disease EWAS, however. As highlighted in a recent review, improved integration of exposure variables is highly warranted in future epigenetic studies of PDP value histograms suggested that the data would have been better modeled in sex-stratified analysis for CD8+ T cells and CD19+ B cells, yet our study was too small to identify significant signals using this design. Power was also limited for pathway analyses, and larger studies are needed to further characterize methylation changes across the studied cell types. Furthermore, this study was performed in an ethnically homogeneous European population. This is a strength with respect to the marginal statistical power, yet do not know to what degree disease-associated methylation changes tend to be population-specific. As with genetic association studies, we acknowledge that more research in underrepresented populations is urgently needed.The included number of participants (25 patients and 25 controls) was modest, although we analyzed a total of 186 methylomes across four cell types. Power analysis indicated that our design was underpowered for smaller effect sizes, which we recognize as a major limitation of our study. + monocyte, CD19+ B cell, CD4+ T-cell and CD8+ T-cell populations in PD, identifying differential methylation predominantly in CD14+ monocytes, highlighting the RAB32 locus in particular. Our findings shed further light on immune mechanisms in PD and warrant further studies of these cell types in order to clarify their role in pathogenesis and identify potential targets of immune-modifying therapy.In conclusion, we performed a methylome-wide association study of purified CD1431, yet levodopa response was not required for inclusion of treatment-naïve patients. Subjects with immunological disorders were excluded, and a clinical blood screen was performed to confirm no gross abnormalities in leukocyte counts at the time of blood draw.The project was approved by the Regional Committee for Medical and Health Research Ethics, Norway. Participants were recruited at the Department of Neurology, Oslo University Hospital and gave written informed consent. A diagnosis of PD was made based on the Movement Disorder Society criteria+, CD14+ and CD19+ cells were isolated by positive selection with EasySepTM Human CD8/CD14/CD19 Positive Selection Kit II . CD4+ cells were isolated by negative selection with EasySepTM Human CD4 Isolation Kit . All procedures followed the standard protocol from the kit manufacturer. Flow cytometry was performed as a quality control the next day to ensure a purity of >90% for each isolated cell population.Peripheral blood mononuclear cells (PBMC) were isolated from whole blood immediately after venipuncture by Lymphoprep  and density gradient centrifugation. Next, CD832. The number of CpGs tested was set to 500,000, target CpGs to 50 and false discovery rate to 0.05. Based on these parameters, a study of 25 patients and 25 controls was estimated to have 80% power to detect a differential methylation corresponding to 0.1 SD. Assuming a replication scenario where 10 candidate CpGs are tested, out of which 5 are truly associated, the required effect size for 80% power was 0.028 SD.We estimated power using the online tool pwrEWAS+ samples, 50 CD19+ samples, 49 CD8+ samples, and 38 CD4+ samples. Insufficient DNA yield occurred primarily for CD4+ T cells, at a similar rate in patients (5/25) and controls (7/25). 500ng DNA from each sample was bisulfite treated and assessed using the Illumina Infinium MethylationEPIC BeadChip . Samples of different disease status and cell type were deliberately intermixed on plates and arrays in a balanced design. From four of the samples, we included an identical technical DNA replicate in the experiment for quality check purposes. The MethylationEPIC array targets ~850,000 CpGs across the regulatory human genome, including both promoter regions and distal enhancers.DNA from the four cell types was isolated with QiAamp DNA Mini Kit  using the standard protocol from the manufacturer. DNA isolation yield varied across samples. From a total of 50 participants, a sufficient amount of DNA was available for 49 CD1456 and wateRmelon57 R packages. Quality control, normalization and evaluation of potential batch effects were performed jointly on the full experiment dataset including all cell types. One sample where >1% of sites had a detection P value greater than 0.05 was filtered out using the pfilter function in the wateRmelon package. CpG sites with a beadcount <3 in 5% of samples or detection P value > 0.05 in 1% of samples were also filtered out. Sex chromosome CpGs were used to estimate sample sex and one sample failing sex check was removed. All remaining data were of high quality as evaluated by inspection of bisulfite conversion and other control probe metrics, outlier detection by the wateRmelon outlyx function and assessment of median signal intensities as evaluated by the minfi getQC function. From a broad range of available normalization methods, we chose functional normalization (funnorm) implemented in the minfi package, as this method is recommended when large differences in methylation patterns are expected, including data from different cell types58. We note that although assessment of differential methylation within each cell type was the main aim of the study, appropriate evaluation of potential batch effects required reliable comparison also across the different cell types.Data processing was performed using R 4.0.3. Raw signal intensity data were imported into R before applying a series of quality checks and filtering steps implemented in the minfiMethylSet data object was mapped to the genome and probes on sex-chromosomes, probe sequences overlapping with known SNPs in the MethylationEPIC annotation and previously reported cross-reactive probes59 were filtered out. Taking advantage of the technical replicates we used the CpGFilter package to compute the intra-class correlation coefficient (ICC), which characterizes the relative contribution of the biological variability to the total variability for each probe60. Probes with low ICC have large measurement errors, making them unsuitable for statistical association testing in complex disorders, and a considerable proportion of probes may thus be filtered out, reducing the multiple testing burden. We filtered out probes with ICC < 0.2. Furthermore, we filtered out constitutively methylated or unmethylated probes with mean beta values < 0.025 or >0.975. The wateRmelon pwod function was used separately on data from each cell type to filter out outlier values lying more than four times the interquartile range from the mean, assumed to result from rare SNP artifacts.The normalized + monocytes using the RNeasy Mini Kit , with adequate yield for 23 PD and 20 control samples, followed by cDNA synthesis using SuperScript IV VILO Master Mix with ezDNase . Quantitative PCR (qPCR) was performed using TaqMan gene expression assays on a ViiA7 instrument  with standard settings as recommended by the manufacturer. Based on previous literature62, we evaluated ACTB, RPL37A and B2M as reference genes and selected RPL37A and B2M as the most suitable based on a strong pairwise correlation  compatible with stable expression. The geometric mean of the cycle threshold (CT) value for these genes was used as normalization factor to estimate the relative expression of RAB32 using the comparative CT method63.RNA was extracted from CD1464. We applied the “Leek” method to determine the number of SVs to include in the model65, which identified 1 SV as appropriate. Methylation beta values were logit transformed into M values. To identify differentially methylated sites (CpGs), linear regression was performed using the limma package66, using the makeContrasts function to define the contrast of interest between PD and control samples of each cell type. We included sex, age, and the first SV as covariates in the model: M ~ disease status + age + sex + SV1. We used the Bonferroni-corrected significance threshold recommended by Mansell et al.67 (P < 9 × 10–8) divided by four cell types (P < 2.25 × 10–8) to adjust for multiple testing. To assess differentially methylated regions, we used the contrast matrix generated for linear regression as input for the R package DMRcate with default parameters68. Finally, we assessed gene ontology enrichment of significant CpGs using the gometh function implemented in the missMethyl R package69. In CD14+ monocytes we tested both Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways for CpGs passing significance thresholds of P value < 10–7, as well as a more liberal threshold of P value < 10–4. We explored the association between significant probes and dopaminergic treatment using linear regression, comparing treated (N = 17) to untreated (N = 8) patients with sex, age and one the first surrogate variable as covariates.Methylation array experiments are prone to technical batch effects. We evaluated experiment plate and chip position as potential covariates but found that these showed no association with top five principal components. To adjust for potentially unknown batch effects, we estimated surrogate variables (SVs) using the sva packageRAB32 expression and adjacent CpGs was investigated using Pearson’s product-moment correlation. Linear regression with sex and age as covariates was used to assess the association between RAB32 expression and disease status. After the identification of differentially methylated CpGs and regions, we assessed the potential association of these probes with PD medication and clinical outcomes using linear or logistic regression models as appropriate, with sex and age as covariates.The correlation between Further information on research design is available in the Suppmental materialReporting Summary