Biology subjects

Williams, N.

Publications and source records attributed to Williams, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Discrete Ricci curvatures capture age-related changes in human brain functional connectivity networks

Geometry-inspired notions of discrete Ricci curvature have been successfully used as markers of disrupted brain connectivity in neuropsychiatric disorders, but their ability to characterize age-related changes in functional connectivity is unexplored. Here, we apply Forman-Ricci curvature and Ollivier-Ricci curvature to compare functional connectivity networks of healthy young and older subjects from the Max Planck Institute Leipzig Study for Mind-Body-Emotion Interactions (MPI-LEMON) dataset (N = 225). We found that both Forman-Ricci curvature and Ollivier-Ricci curvature can capture whole-brain and region-level age-related differences in functional connectivity. Meta-analysis decoding demonstrated that those brain regions with age-related curvature differences were associated with cognitive domains known to manifest age-related changes - movement, affective processing and somatosensory processing. Moreover, the curvature values of some brain regions showing age-related differences exhibited correlations with behavioral scores of affective processing. Finally, we found an overlap between brain regions showing age-related curvature differences and those brain regions whose non-invasive stimulation resulted in improved movement performance in older adults. These results suggest that both Forman-Ricci curvature and Ollivier-Ricci curvature correctly identify brain regions that are known to be functionally or clinically relevant. Our results add to a growing body of evidence demonstrating the sensitivity of discrete Ricci curvature measures to changes in the organisation of functional connectivity networks, both in health and disease.

neuroscience↗

bioRxiv2022

A scoping review on the use of consumer-grade EEG devices for research

BACKGROUNDCommercial electroencephalography (EEG) devices have become increasingly available over the last decade. These devices have been used in a wide variety of fields ranging from engineering to cognitive neuroscience. PURPOSEThe aim of this study was to chart peer-review articles that used currently available consumer-grade EEG devices to collect neural data. We provide an overview of the research conducted with these relatively more affordable and user-friendly devices. We also inform future research by exploring the current and potential scope of consumer-grade EEG. METHODSWe followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following electronic databases: PsycINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, experimental research, validation, signal processing, and clinical) and location of use as indexed by the first authors country. RESULTSWe identified 916 studies that used data recorded with consumer-grade EEG: 531 were reported in journal articles and 385 in conference papers. Emotiv devices were most used, followed by the NeuroSky MindWave, OpenBCI, interaXon Muse, and MyndPlay Mindband. The most common use was for brain-computer interfaces, followed by experimental research, signal processing, validation, and clinical purposes. CONCLUSIONSConsumer-grade EEG has proven to be a useful tool for neuroscientific research and will likely continue to be used well into the future. Our study provides a comprehensive review of their application, as well as future directions for researchers who wish to use these devices.

neuroscience↗

bioRxiv2022

Accurate simultaneous sequencing of genetic and epigenetic bases in DNA

DNA comprises molecular information stored via genetic bases (G, C, T, A) and also epigenetic bases, principally 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Both genetic and epigenetic information are vital to our understanding of biology and disease states. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases typically fail to capture common C-to-T mutations or distinguish 5mC from 5hmC. Here, we present a single-base-resolution sequencing methodology that will simultaneously sequence complete genetics and complete epigenetics in a single workflow. The approach is non-destructive to DNA and provides a digital readout of bases, which we exemplify by simultaneous sequencing of G, C, T, A, 5mC and 5hmC; 6-Letter sequencing. We demonstrate sequencing of human genomic DNA and also cell-free DNA taken from a blood sample of a cancer patient. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. We envisage it will be versatile across many applications in life sciences.

genomics↗

bioRxiv2022

Severe drought events trigger long-term salt marsh dieback in the Southeastern and Gulf of Mexico USA

The frequency of salt marsh dieback events has increased over the last 25 years with unknown consequences to the resilience of the ecosystem to accelerated sea level rise (SLR). Salt marsh ecosystems impacted by sudden vegetation dieback events were previously thought to recover naturally within a few months to years. In this study, we provide evidence that approximately 14% of total marsh area has not revegetated 10-years after a dieback event in Charleston, SC. Dieback onset coincided with a severe drought in 2012, and a second dieback event occurred in 2016 after a historic flood influenced by Hurricane Joaquin in October of 2015, with unvegetated zones reaching nearly 30% of total marsh area in 2017. Most affected areas were associated with lower elevation zones in the interior of the marsh (midmarsh). During the 2013 dieback event, we estimate that unvegetated midmarsh area expanded by 300%. Grass planting was shown to be an effective restoration practice, with restored plants having greater aboveground biomass than relict sites after two years of transplanting. A positive restoration outcome indicated that the stressors that caused the initial dieback are no longer present. Despite that, many dieback areas have not recovered naturally even as they are located within the typical elevation range of a healthy vegetated marsh. A mechanistic modelling approach was used to assess the effects of vegetation dieback on salt marsh resilience to SLR. Predictions indicate that a highly productive restored marsh (2000 g m-2 y-1) would persist at a moderate SLR rate of 60 cm 100 y-1, whereas a non- restored mudflat would lose all of its elevation capital after 100 years. Thus, rapid restoration of marsh dieback is critical to avoid further degradation. Also, failure to incorporate the increasing frequency and intensity of extreme climatic events which trigger irreversible marsh diebacks underestimates salt marsh vulnerability to climate change. At an elevated SLR rate of 122 cm 100 y-1, most likely an extreme climate change scenario, even highly productive ecosystems augmented by sediment placement would not keep pace with SLR. Thus, climate change mitigation actions are also urgently needed to preserve present-day marsh ecosystems.

ecology↗

bioRxiv2021

Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

While standard graph-theoretic measures have been widely used to characterize atypical resting-state functional connectivity in autism spectrum disorder (ASD), geometry-inspired network measures have not been applied. In this study, we apply Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and typically developing individuals (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We find brain-wide and region-specific ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures, with region-specific differences concentrated in Default Mode, Somatomotor and Ventral Attention networks for Forman-Ricci curvature. We use meta-analysis decoding to demonstrate that brain regions with curvature differences are associated to those cognitive domains known to be impaired in ASD. Further, we show that brain regions with curvature differences overlap with those brain regions whose non-invasive stimulation improves ASD-related symptoms. These results suggest the utility of graph Ricci curvatures in characterizing atypical connectivity of clinically relevant regions in ASD and other neurodevelopmental disorders.

neuroscience↗

bioRxiv2021

Optimizing the live attenuated influenza A vaccine backbone for high-risk patient groups

The live attenuated influenza vaccine (LAIV) is approved for intranasal spray application in 2-49 year-old patients with safety concerns limiting its use in younger children and immunocompromised patients, mainly from the higher incidence of adverse events and the possibility of uncontrolled replication and reversion to a pathogenic strain, respectively. Further attenuation of the LAIV could generally improve its safety profile, which might come at the cost of reduced immunogenicity. To solve this dilemma, we took advantage of a recently defined mechanism of ER stress induction by modifying IAV non-structural protein 1 (NS1). The modified LAIV (AAmut/PR8) showed stronger ER stress activation in vitro and replicated to lower titers in vivo compared to its parental strain, without affecting protection against homo-subtypic or hetero-subtypic IAV strains. AAmut/PR8 could pose as a suitable strategy to attend the gap to the current LAIV recommendation guidelines in susceptible target populations.

microbiology↗

bioRxiv2021

Clonal dynamics of haematopoiesis across the human lifespan

Age-related change in human haematopoiesis causes reduced regenerative capacity1, cytopenias2, immune dysfunction3 and increased risk of blood cancer. The cellular alterations that underpin the abruptness of this functional decline after the age of 70 years remain elusive. We sequenced 3579 genomes from single-cell-derived colonies of haematopoietic stem cell/multipotent progenitors (HSC/MPPs) across 10 haematologically normal subjects aged 0-81 years. HSC/MPPs accumulated 17 mutations/year after birth and lost 30bp/year of telomere length. Haematopoiesis in adults aged <65 was massively polyclonal, with high indices of clonal diversity and a stable population of 20,000-200,000 HSC/MPPs contributing evenly to blood production. In contrast, haematopoiesis in individuals aged >75 showed profoundly decreased clonal diversity. In each elderly subject, 30-60% of haematopoiesis was accounted for by 12-18 independent clones, each contributing 1-34% of blood production. Most clones had begun their expansion before age 40, but only 22% had known driver mutations. Genome-wide selection analysis estimated that 1/34 to 1/12 non-synonymous mutations were drivers, occurring at a constant rate throughout life, affecting a wider pool of genes than identified in blood cancers. Loss of Y chromosome conferred selective benefits on HSC/MPPs in males. Simulations from a simple model of haematopoiesis, with constant HSC population size and constant acquisition of driver mutations conferring moderate fitness benefits, entirely explained the abrupt change in clonal structure in the elderly. Rapidly decreasing clonal diversity is a universal feature of haematopoiesis in aged humans, underpinned by pervasive positive selection acting on many more genes than currently identified.

genomics↗

bioRxiv2021

The longitudinal dynamics and natural history of clonal haematopoiesis

Human cells acquire somatic mutations throughout life, some of which can drive clonal expansion. Such expansions are frequent in the haematopoietic system of healthy individuals and have been termed clonal haematopoiesis (CH). While CH predisposes to myeloid neoplasia and other diseases, we have limited understanding of how and when CH develops, what factors govern its behaviour, how it interacts with ageing and how these variables relate to malignant progression. Here, we track 697 CH clones from 385 individuals aged 55 or older over a median of 13 years. We find that 92.4% of clones expanded at a stable exponential rate over the study period, with different mutations driving substantially different growth rates, ranging from 5% (DNMT3A, TP53) to over 50%/yr (SRSF2-P95H). Growth rates of clones with the same mutation differed by approximately +/-5%/yr, proportionately impacting "slow" drivers more substantially. By combining our time-series data with phylogenetic analysis of 1,731 whole genome-sequenced haematopoietic colonies from 7 older individuals, we reveal distinct patterns of lifelong clonal behaviour. DNMT3A-mutant clones preferentially expanded early in life and displayed slower growth in old age, in the context of an increasingly competitive oligoclonal landscape. By contrast, splicing gene mutations only drove expansion later in life, while growth of TET2-mutant clones showed minimal age-dependency. Finally, we show that mutations driving faster clonal growth carry a higher risk of malignant progression. Our findings characterise the lifelong natural history of CH and give fundamental insights into the interactions between somatic mutation, ageing and clonal selection.

cancer biology↗

bioRxiv2021

Biophysical network models of phase-synchronization in MEG resting-state

Magnetoencephalography (MEG) is used extensively to study functional connectivity (FC) networks of phase-synchronization, but the relationship of these networks to their biophysical substrates is poorly understood. Biophysical Network Models (BNMs) have been used to produce networks corresponding to MEG-derived networks of phase-synchronization, but the roles of inter-regional conduction delays, the structural connectome and dynamics of model of individual brain regions, in obtaining this correspondence remain unknown. In this study, we investigated the roles of conduction delays, the structural connectome, and dynamics of models of individual regions, in obtaining a correspondence between model-generated and MEG-derived networks between left-hemispheric regions. To do this, we compared three BNMs, respectively comprising Wilson-Cowan oscillators interacting with diffusion Magnetic Resonance Imaging (MRI)-based patterns of structural connections through zero delays, constant delays and distance-dependent delays respectively. For the BNM whose networks corresponded most closely to the MEG-derived network, we used comparisons against null models to identify specific features of each model component, e.g. the pattern of connections in the structure connectome, that contributed to the observed correspondence. The Wilson-Cowan zero delays model produced networks with a closer correspondence to the MEG-derived network than those produced by the constant delays model, and the same as those produced by the distance-dependent delays model. Hence, there is no evidence that including conduction delays improves the correspondence between model-generated and MEG-derived networks. Given this, we chose the Wilson-Cowan zero delays model for further investigation. Comparing the Wilson-Cowan zero delays model against null models revealed that both the pattern of structural connections and Wilson-Cowan oscillatory dynamics contribute to the correspondence between model-generated and MEG-derived networks. Our investigations yield insight into the roles of conduction delays, the structural connectome and dynamics of models of individual brain regions, in obtaining a correspondence between model-generated and MEG-derived networks. These findings result in a parsimonious BNM that produces networks corresponding closely to MEG-derived networks of phase-synchronization. HighlightsO_LISimple biophysical model produces close match ({rho}=0.49) between model and MEG networks C_LIO_LINo evidence for conduction delays improving match between model and MEG networks C_LIO_LIPattern of structural connections contributes to match between model and MEG networks C_LIO_LIWilson-Cowan oscillatory dynamics contribute to match between model and MEG networks C_LI

neuroscience↗

bioRxiv2021

Huntington's disease age at motor onset is modified by the tandem hexamer repeat in TCERG1

BackgroundHuntingtons disease is caused by an expanded CAG tract in HTT. The length of the CAG tract accounts for over half the variance in age at onset of disease, and is influenced by other genetic factors, mostly implicating the DNA maintenance machinery. We examined a single nucleotide variant, rs79727797, on chromosome 5 in the TCERG1 gene, previously reported to be associated with Huntingtons disease and a quasi-tandem repeat (QTR) hexamer in exon 4 of TCERG1 with a central pure repeat. MethodsWe developed a novel method for calling perfect and imperfect repeats from exome sequencing data, and tested association between the QTR in TCERG1 and residual age at motor onset (after correcting for the effects of CAG length in the HTT gene) in 610 individuals with Huntingtons disease via regression analysis. ResultsWe found a significant association between age at onset and the sum of the repeat lengths from both alleles of the QTR (p = 2.1x10-9), with each added repeat hexamer reducing age at onset by one year (95% confidence interval [0.7, 1.4]). This association explained that previously observed with rs79727797. ConclusionsThe association with age at onset in the genome-wide association study is due to a QTR hexamer in TCERG1, translated to a glutamine/alanine tract in the protein. We could not distinguish whether this was due to cis-effects of the hexamer repeat on gene expression or of the encoded glutamine/alanine tract in the protein. These results motivate further study of the mechanisms by which TCERG1 modifies onset of HD.

genetics↗

bioRxiv2021

Modules in connectomes of phase-synchronization comprise anatomically contiguous, spatially related regions

Modules in brain functional connectomes are essential to balancing segregation and integration of neuronal activity. Connectomes are the complete set of pairwise connections between brain regions. Non-invasive Electroencephalography (EEG) and Magnetoencephalography (MEG) have been used to identify modules in connectomes of phase-synchronization. However, their resolution is suboptimal because of spurious phase-synchronization due to EEG volume conduction or MEG field spread. Here, we used invasive, intracerebral recordings from stereo-electroencephalography (SEEG, N = 67), to identify modules in connectomes of phase-synchronization. To generate SEEG-based group-level connectomes affected only minimally by volume conduction, we used submillimeter accurate localization of SEEG contacts and referenced electrode contacts in cortical grey matter to their closest contacts in white matter. Combining community detection methods with consensus clustering, we found that the connectomes of phase-synchronization were characterized by distinct and stable modules at multiple spatial scales, across frequencies from 3 to 320 Hz. These modules were highly similar within canonical frequency bands. Unlike the distributed brain systems identified with functional Magnetic Resonance Imaging (fMRI), modules up to the high-gamma frequency band comprised only anatomically contiguous regions. Notably, the identified modules comprised cortical regions involved in shared repertoires of sensorimotor and cognitive functions including memory, language and attention. These results suggest that the identified modules represent functionally specialised brain systems, which only partially overlap with the brain systems reported with fMRI. Hence, these modules might regulate the balance between functional segregation and functional integration through phase-synchronization. HighlightsO_LILarge-cohort SEEG used for phase-synchronization connectomics C_LIO_LIConnectomes of phase-synchronization possess distinct and stable modules C_LIO_LIModules in connectomes are highly similar within canonical frequency bands C_LIO_LIModules in connectomes comprise anatomically contiguous regions C_LIO_LIModules in connectomes comprise functionally related regions C_LI

neuroscience↗

bioRxiv2020

Phylogenetic reconstruction of myeloproliferative neoplasm reveals very early origins and lifelong evolution

Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 448,553 somatic mutations from whole-genome sequencing of 843 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 10 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation in these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition ranging between 4.1 months and 11.4 years across 5 patients. DNMT3A mutations, which are associated with age-related clonal haematopoiesis, were also acquired in utero or childhood, by 7.9 weeks of gestation to 7.8 years across 4 patients. Subsequent driver mutation acquisition was separated by decades. The mean latency between JAK2V617F acquisition and clinical presentation was 31 years (range 12-54 years). Rates of clonal expansion varied substantially (<10% to >200% expansion/year), were affected by additional driver mutations, and predicted latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition very early in life with life-long growth and evolution drive adult blood cancer, providing opportunities for early detection and intervention, and a new paradigm for cancer development.

cancer biology↗

bioRxiv2020

10 Years of EPOC: A scoping review of Emotiv's portable EEG device

BACKGROUNDCommercially-made low-cost electroencephalography (EEG) devices have become increasingly available over the last decade. One of these devices, Emotiv EPOC, is currently used in a wide variety of settings, including brain-computer interface (BCI) and cognitive neuroscience research. PURPOSEThe aim of this study was to chart peer-reviewed reports of Emotiv EPOC projects to provide an informed summary on the use of this device for scientific purposes. METHODSWe followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following electronic databases: PsychINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, clinical, signal processing, experimental research, and validation) and location of use (as indexed by the first authors address). RESULTSWe identified 382 relevant studies. The top five publishing countries were the United States (n = 35), India (n = 25), China (n = 20), Poland (n = 17), and Pakistan (n = 17). The top five publishing cities were Islamabad (n = 11), Singapore (n = 10), Cairo, Sydney, and Bandung (n = 7 each). Most of these studies used Emotiv EPOC for BCI purposes (n = 277), followed by experimental research (n = 51). Thirty-one studies were aimed at validating EPOC as an EEG device and a handful of studies used EPOC for improving EEG signal processing (n = 12) or for clinical purposes (n = 11). CONCLUSIONSIn its first 10 years, Emotiv EPOC has been used around the world in diverse applications, from control of robotic limbs and wheelchairs to user authentication in security systems to identification of emotional states. Given the widespread use and breadth of applications, it is clear that researchers are embracing this technology.

neuroscience↗

bioRxiv2020

Lineage tracing of human embryonic development and foetal haematopoiesis through somatic mutations

To date, ontogeny of the human haematopoietic system during foetal development has been characterized mainly through careful microscopic observations. Here we used whole-genome sequencing (WGS) of 511 single-cell derived haematopoietic colonies from healthy human foetuses of 8 and 18 post-conception weeks (pcw) coupled with deep targeted sequencing of tissues of known embryonic origin to reconstruct a phylogenetic tree of blood development. We found that in healthy foetuses, individual haematopoietic progenitors acquire tens of somatic mutations by 18 pcw. Using these mutations as barcodes, we timed the divergence of embryonic and extra-embryonic tissues during development and estimated the number of blood antecedents at different stages of embryonic development. Our analysis has shown that ectoderm originates from a smaller set of blood antecedents compared to endoderm and mesoderm. Finally, our data support a hypoblast origin of the extra-embryonic mesoderm and primitive blood in humans.

genomics↗

bioRxiv2020

A single cell atlas reveals distinct immune landscapes in transplant and primary tumors that determine response or resistance to immunotherapy

Despite impressive responses in some patients, immunotherapy fails to cure most cancer patients. Preclinical studies indicate that radiotherapy synergizes with immunotherapy, promoting radiation-induced antitumor immunity. Nearly all preclinical immunotherapy studies utilize transplant tumor models, but cure rates of transplant tumor models treated with immunotherapy often overestimate patient responses. Here, we show that transplant tumors are cured by PD-1 blockade and radiotherapy, but identical treatment fails in autochthonous tumors. We generated a single-cell atlas of tumor-infiltrating immune cells from transplant and primary tumors treated with radiation and immunotherapy, which reveals striking differences in their immune landscapes. Although radiotherapy remodels myeloid cell phenotypes in primary and transplant tumors, only transplant tumors are enriched for CD8+ T cells that mediate tumor clearance while mice with primary sarcomas demonstrate tumor-specific tolerance. These results identify distinct microenvironments in tumors that coevolve with the immune system, which promote tolerance that must be overcome for immune-mediated cancer cures.

cancer biology↗

bioRxiv2019

Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

neuroscience↗

bioRxiv2019

Analysis of DNM3 and VAMP4 as genetic modifiers of LRRK2 Parkinsons disease

ObjectiveTo assess genetic modifiers of Parkinsons disease (PD) age at onset (AAO) penetrance in individuals carrying common and rare LRRK2 risk alleles\n\nMethodsWe analysed reported genetic modifier DNM3 rs2421947 in 724 LRRK2 p.G2019S heterozygotes using linear regression of AAO. We meta-analysed our data with previously published data (n=754). VAMP4 is in close proximity to DNM3 and is associated with PD. We analysed the effect of the rs11578699 VAMP4 variant on pG2019S penetrance in 786 LRRK2 p.G2019S heterozygotes. We also evaluated the impact of VAMP4 variants using AAO regression in 4882 patients with PD carrying a common LRRK2 risk variant (rs10878226).\n\nResultsThere was no evidence for linkage disequilibrium between DNM3 rs2421947 and VAMP4 rs11578699. Our linear regression AAO of 724 p.G2019S carriers showed no relationship between DNM3 rs2421947 and AAO (beta = -1.19, p = 0.55, n =708). Meta-analysis with previously published data did not indicate a significant effect on AAO (beta = -2.21, p = 0.083, n = 1304), but there was significant heterogeneity in the analyses of new and previously published data. VAMP4 rs11578699 was nominally associated with AAO in patients dichotomized by the common LRRK2 risk variant rs10878226 (beta=1.68, se=0.81 p=0.037).\n\nInterpretationAnalysis of DNM3 in previously unpublished data does not show an interaction between DNM3 and LRRK2 G2019S for AAO, however the inter-study heterogeneity may indicate ethnic-specific effects of DNM3 rs2421947. Analysis of sporadic PD patients stratified by the PD risk variant rs10878226 indicates a possible interaction between LRRK2 and VAMP4.

genetics↗

bioRxiv2019

Universal continuous severity traits underlying hundreds of Parkinson’s disease clinical features

The generation of deeply phenotyped patient cohorts offers an enormous potential to identify disease subtypes but are currently limited by the cohort size and the heterogeneity of the clinical assessments collected across different cohorts. Identifying the universal axes of clinal severity and progression is key to accelerating our understanding of how disease manifests and progresses. These universal axes would accelerate our understanding of how Parkinsons disease (PD) manifests and progresses through which patients may be appropriately compared appropriately stratified, and personalised therapeutic strategies and treatments can be developed and targeted. We developed a Bayesian multiple phenotype mixed model incorporating the genetic relationships between individuals which is able to reduce a wide-array of different clinical measurements into a smaller number of continuous underlying factors named phenotypic axis. We identify three principal axes of PD patient phenotypic variation which are reproducibly found across three independent, deeply and diversely phenotyped cohorts. Together they explain over 75% of the observed clinical variation and remain robustly captured with a fraction of the clinically-recorded features. The most influential axis was associated with the genetic risk of Alzheimers disease (AD) and involves genetic pathways associated with neuroinflammation. Our results suggest PD patients with a high genetic risk for AD are more likely to develop a more aggressive form of PD including, but not limited to, dementia.

neuroscience↗