https://www.helbiglab.io/blog daily 0.75 2025-06-23 https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j-77pcy-dc9h5-zwxby-wbpp7 monthly 0.5 2021-05-11 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1620754401839-5XDDU3N90VPIAGNJUTAH/HPO_2021-2048x1536.jpeg Blog - Introducing the revised Human Phenotype Ontology (HPO) – a new language for Big Data in the epilepsies https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j-77pcy-dc9h5-zwxby monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616531886183-8CDX9WI56ZB3383TNE58/SCN2A_2021_3-2048x1536.jpeg Blog - SCN2A – a neurodevelopmental disorder digitized through 10,860 phenotypic annotations Figure 1. Overview of SCN2A variants and associated phenotypic features. (a) The NaV1.2 channel (above) and gene (below), highlighting a selection of recurrent variants. (b) The frequency of phenotypic features within categorized phenotypic subgroups: developmental and epileptic encephalopathy (DEE, n = 255), autism (ASD, n = 60), benign familial neonatal–infantile seizures (BFNIS, n = 53), other epilepsy (n = 27), and atypical SCN2A-related phenotypes (n = 18). Boxed frequencies indicate the five most frequent Human Phenotype Ontology (HPO) terms within each respective phenotypic subgroup. CNS central nervous system, EEG electroencephalogram, PTV protein-truncating variant. Adapted from Crawford, Xian et al. under a CC BY 4.0 license (link) https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j-77pcy-dc9h5-zwxby-fc38t monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616531545809-WWN22M8WJVPEBQMJ6X2E/Dataspeak2020.jpeg Blog - Make data speak in rare childhood epilepsies Figure 1. Analyzing standardized outcomes data implemented in the Electronic Medical Record for routine health care. (A) Documented seizure frequencies in >350 patients by age, arrows reflect changes in seizure frequency between encounters, green indicates improvement, red indicates worsening. This type of visualization for seizure frequencies over time has since been abandoned by our lab and replaced by more intuitive ways of making this data more tangible (CNS 2020 poster by Fitzgerald et al.). However, this plot bears some resemblance to one of the most famous historical data visualizations, the Maury train chart as displayed on the cover of Edward Tufte’s book. (B) Non-seizure outcomes data in >800 children with genetic epilepsies, using percentiles for routine scales used in clinical care (AIMS, Beery, BOT2, GMFM, Peabody). This graph emphasizes that many children with genetic epilepsies have relatively low scores on established scales that may not allow for sufficient discrimination. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j-77pcy-dc9h5 monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604076704526-V9ULYB9KPXQAM14STHRZ/Kaplanis2020.jpg Blog - The spectrum of de novo variants in 30,000 individuals with neurodevelopmental disorders Figure 1. Count of de novo variants for the genes with the most common de novo variants identified by Kaplanis et al. Gene-based count was derived from the Supplementary Data provided by the authors, synonymous de novo variants were excluded, and results were grouped by genes. Common epilepsy-associated genes including SCN2A, STXBP1, KCNQ2, SYNGAP1, SCN8A, SCN1A, and GNAO1 are amongst the 50 most common genes. However, the four most common genes (ARID1B, DDX3X, ANKRD11, and KMT2A) do not represent genetic etiologies that are exclusively associated with the epilepsies and represent broader genetic causes for neurodevelopmental disorders. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j-77pcy monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603402363561-5EP8D5O6S75JB9V52A7R/OMIM2020.jpg Blog - OMIM to retire EIEE classification – an important step to overhaul terminology for genetic epilepsies Figure 1. The pace of disease gene discovery as cataloged by the OMIM Morbid Map Scorecard. The current scorecard is available from https://omim.org/statistics/geneMap. The figure is an update provided by OMIM from the figure in Amberger et al., 2018. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb-y2s5j monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603400058564-MXUVZC8DH3YQOE41BS0A/RELA2020.jpg Blog - DNA methylation, somatic mutations, and polymicrogyria Figure 1. Brain mosaicism as new defining feature in a subset of PMG. Performing copy number profiling from DNA methylation data, Kobow and colleagues identified a somatic duplication of the entire long arm of chromosome 1 in surgical brain tissue of a subset of PMG patients. Subsequent FISH analysis identified a mosaic distribution of 1q triploid nuclei in the center of the lesion, but not in adjacent anatomically normal appearing cortical tissue (Figure provided by the authors). https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel-hzxrb monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603398514802-D7L7BZHPGDJ9T7WGQ9T1/RELA2020.jpg Blog - Understanding patient advocacy – the Rare Epilepsy Landscape Analysis (RELA) Figure 1. The landscape of rare epilepsy support organizations in the US (adapted from the Rare Epilepsy Landscape Analysis, Penn Miller 2020) https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3-jcdel monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603397960173-TVK8J21XTZ9G068TWNXB/Niestroj2020.jpg Blog - The SCN1A rs6732655 enigma – a reply Figure 1. A meta-analysis of rs6732655 (SCN1A) in both studies mentioned in my prior blog post. The diamond-shaped symbol at the bottom of the Forest plot describes the overall estimated effect sizes using two different models, which basically result in the same estimate. Overall, the information of the BBJ study changes the estimate of the effect size (OR) only marginally. The joint estimate from both studies still suggests an OR of 1.1. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645-8afd3 monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603398042366-OWQX9V8S6T2O7YQMFFYJ/image-asset.jpeg Blog - Entering the phenotype era – HPO-based similarity, big data, and the genetic epilepsies Figure 2. Phenotypic similarity analysis thrives on heterogeneity. Addition of controls results in increased phenotype-based significance and reduced genotype-based significance (A) On the basis of the initial cohort of 846 individuals with DEE, the subsequent addition of 1,548 population controls sequenced for de novo variants results in a steady increase in the statistical significance of gene-based phenotypic similarity. Inversely, statistical significance based on the frequency of observed de novo variants steadily decreases with the addition of controls. (B and C) With additional simulated controls, significance based on phenotypic similarity eventually exceeds significance based on frequency of de novo variants for CHD2 (B) and GRIN1 (C). The gray line indicates the critical cohort size when phenotypic significance becomes more significant than genotype-based significance. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603397640430-ROYDXGV0NV7S41DTMKI5/Niestroj2020.jpg Blog - Entering the phenotype era – HPO-based similarity, big data, and the genetic epilepsies Figure 1. A re-introduction to SCN1A-related epilepsies. What patterns do we see when we put together all the clinical information in EuroEPINOMICS, Epi4K, and other epilepsy studies and analyze data for patterns that are linked to de novo variants in SCN1A? The clinical features are displayed as a “phenogram,” comparing the frequency in individuals with SCN1A de novo variants (y-axis) to the larger cohort of developmental and epileptic encephalopathies (x-axis), with red dots indicating terms that are significantly different. On the right, the phenotypes listed are shown as a “phenotree,” displaying the connection of phenotypic features associated with SCN1A. Phenograms and phenotrees are some of the tools we developed to visualize large-scale phenotype data in the developmental and epileptic encephalopathies to make it more intuitive. This data, based on >30K single HPO terms, reconstructs the clinical features of Dravet Syndrome even though none of the included individuals have been clinically diagnosed. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records-5a645 monthly 0.5 2021-03-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603397362057-PG3LVJHYWE15VSN8B0T7/Niestroj2020.jpg Blog - Copy Number Variations in the epilepsies – a 2020 update Figure 1. Overview of common recurrent CNVs in >10,000 individuals with epilepsy and >6,500 matched control individuals, sorted by epilepsy type (DEE developmental and epileptic encephalopathies, GGE genetic generalized epilepsy, NAFE non-acquired focal epilepsy, LFE lesional focal epilepsy). Table modified from Table 1 by Niestroj and collaborators. https://www.helbiglab.io/blog/the-natural-history-of-genetic-epilepsies-as-told-by-3200-years-of-electronic-medical-records monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597759620026-GKO7U5ZGH4XU4KRWPLV2/image-asset.jpeg Blog - The natural history of genetic epilepsies as told by 3,200 years of electronic medical records Figure 1. The timescapes of STXBP1 and SCN2A. When assessing clinical features in genetic epilepsies over time, we can assess which clinical terms are associated with a given genetic etiology at specific time points. ‘Timescapes’ are ways to visualize this complex data of 528 possible phenotypic terms across 100 time intervals. The green line at the top “decodes” the association signal of STXBP1 with Infantile Spasms, showing the frequency of Infantile Spasms over time in 22 patients with STXBP1-related disorders compared to 636 individuals in our cohort – the peak at 6 months represents the strongest association signal that is shown in the timescape plot. https://www.helbiglab.io/blog/gnao1-and-13k-genomes-rare-disease-sequencing-on-a-national-level monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597759516947-RE1FJX9RFADX8QSGV31X/Turro2020.jpg Blog - GNAO1 and 13K genomes – rare disease sequencing on a national level Figure 1. Frequency of genetic etiologies in the neurological and developmental disorders (NDD) subgroup of the study by Turro and collaborators, grouped by frequency and listing the genetic etiologies seen twice or more. Disease-causing variants in GNAO1, a rare neurogenetic condition causing a developmental and epileptic encephalopathy (DEE) and/or movement disorder, were the most common single-gene cause for neurological and developmental disorders, followed by SCN1A, STXBP1, and KMT2B. https://www.helbiglab.io/blog/common-genetic-risk-factors-for-epilepsy-in-the-japanese-population monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597759380155-R0346WE1PR8GP3TZ72C9/image-asset.jpeg Blog - Common genetic risk factors for epilepsy in the Japanese population Figure 1. The study by Ishigaki and collaborators examined common genetic risk factors for 42 common diseases in more than 200,000 individuals from the BioBank Japan Project. The authors compared common variants predisposing individuals to epilepsies in their study to variants in the 2014 ILAE GWAS study. Only the rs6732655, in the vicinity of SCN1A, had an effect size that overlapped with what was previously seen in our prior study. https://www.helbiglab.io/blog/understanding-the-genetics-of-fires monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597758958363-CSW5J21SJ7VAZJYQQLS8/image-asset.jpeg Blog - Understanding the genetics of FIRES Figure 1. Candidate genes in FIRES based on exome sequencing in 50 individuals with FIRES. The table includes (a) de novo variants in individuals with FIRES, (b) pathogenic variants in FIRES reported in ClinVar, and (c) variants in epilepsy-related genes absent from the gnomAD database. A de novo variant in DNM1 (indicated by superscript 1) had been previously reported in a study by von Spiczak and collaborators, but this variant is substantially different from the other DNM1 variant based on this location in the dynamin protein. https://www.helbiglab.io/blog/exome-sequencing-in-the-rolandic-epilepsies monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597758852540-3L7G5NULYMNYFAFUWWFQ/BRE_2020.jpg Blog - Exome sequencing in the rolandic epilepsies Figure 1. De novo variants in 57 individuals with epilepsy-aphasia spectrum disorders including typical and atypical rolandic epilepsies. Explanatory de novo variants, either pathogenic, likely pathogenic variants or de novo variants in related neurodevelopmental and/or neurological disorders can be found in roughly 10% of individuals in addition to a large number of candidate de novo variants that may provide further insight into the biology of the epilepsy-aphasias in the future. https://www.helbiglab.io/blog/the-genetics-of-doose-syndrome-or-myoclonic-astatic-epilepsy monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1597758708887-Y1SZ0EV3W7RMNTLXJFN7/doose.jpg Blog - The genetics of Doose Syndrome or Myoclonic Astatic Epilepsy Figure 1. The clinical features of Doose Syndrome (epilepsy with myoclonic atonic seizures or Myoclonic Astatic Epilepsy [MAE]). The table is adapted from our recent publication by Tang et al., 2020 and compares the clinical features in the large cohorts of Doose Syndrome that have been reported since the initial description in 1970. Doose Syndrome (MAE) is a rare epilepsy syndrome, but is a recognizable clinical entity. However, in contrast to Dravet Syndrome where >90% of individuals have disease-causing variants in SCN1A, Doose Syndrome is genetically heterogeneous. https://www.helbiglab.io/blog/scn3a-a-sodium-channel-in-epilepsy-and-brain-malformations monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1593005463669-EP9V6RLASW3ITXCRCR1Y/scn3a.jpeg Blog - SCN3A – a sodium channel in epilepsy and brain malformations Figure 1. SCN3A in epilepsies and malformations of cortical development. Many variants cluster in the S4 segment or S4/S5 linker region and result in a gain-of-function effect of the Nav1.3 protein, the ion channel encoded by the SCN3A gene (figure modified from a prior version of Zaman et al., 2020). https://www.helbiglab.io/blog/blog-post-four-sm239 monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1591919811899-LBSY2TWBH8YMH14A6XMA/download.jpeg Blog - Ten steps ahead while six feet apart – telemedicine in child neurology Figure 1. Analyzing 2,589 Child Neurology Telehealth Encounters Necessitated by the COVID-19 Pandemic. We used a novel health care analytics framework to assess patient demographics, age distribution, and diagnoses in 14,780 in- person encounters and 2,589 telehealth encounters. We found that telemedicine in child neurology is feasible and effective, covering the full age and diagnostic range typically seen in an outpatient child neurology clinic. https://www.helbiglab.io/blog/blog-post-three-tyje8 monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1591920086765-NNCS4BT6TXYZZ7K0MKMT/Epi25_2019.jpg Blog - Epi25 – redefining epilepsy genetics through exomes of 17,000 individuals Figure 1. Burden analysis for the three phenotypic subgroups in the Epi25 study, including developmental and epileptic encephalopathies (DEE), generalized genetic epilepsies (GGE), and non-acquired focal epilepsy (NAFE). In brief, a burden analysis assesses the frequency (“burden”) of rare variants in cases and controls and assesses whether this difference is significant. The current graph (qq plot) indicates genes that deviate from the expected p-value (red line), hinting at a role in disease causation. While no single gene reached exome-wide significance, several genes are suggestive, most prominently SCN1A in DEE. Several other genes, including genes that were previously not implicated in the epilepsies, were found to carry more ultrarare variants than expected, such as COBLL1 for DEE, UNC79 for GGE, and TRIM3 for NAFE [modified from Figure 3 of the corrected proof (link) with permissions by the publisher] https://www.helbiglab.io/blog/blog-post-two-m5jxa monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1591920676279-6Y44OPSUR9J64S9A9DNR/image-asset.png Blog - How common is rare? A population-based study into genetic childhood epilepsies The genetics of childhood epilepsy in Scotland. All genetic diagnoses in a population-based cohort of 333 patients presenting with seizures under 36 months collected over a three-year period. This chart provides the answer to the most common genetic epilepsy identified in this study. Incidence estimates are provided for individual genes, where such estimates were possible. https://www.helbiglab.io/blog/blog-post-one-mjntb monthly 0.5 2020-11-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1591920970400-8BSKQZRWXLO154XZYM0X/Helbig2019.jpg Blog - Deciphering the phenotypic code – AP2M1 in epileptic encephalopathies Figure 1. When comparing more than 3,000 phenotypic terms in 314 individuals with developmental and epileptic encephalopathies, we find that patients with similar genetic epilepsies cluster. This is true for known genetic epilepsies such as DNM1 and SCN8A, but also for the previously unknown AP2M1 gene. The phenotypic similarity between individuals can then be quantified and compared to the remainder of the cohort. The AP2M1 signal was so prominent that it stood out from the remainder of the cohort, making AP2M1 the first epilepsy gene to be identified through a computational phenotyping approach. https://www.helbiglab.io/blog/tag/RES monthly 0.5 https://www.helbiglab.io/blog/tag/epilepsy+panel monthly 0.5 https://www.helbiglab.io/blog/tag/GWAS monthly 0.5 https://www.helbiglab.io/blog/tag/electronic+medical+records monthly 0.5 https://www.helbiglab.io/blog/tag/ClinGen monthly 0.5 https://www.helbiglab.io/blog/tag/outcome+measures monthly 0.5 https://www.helbiglab.io/blog/tag/diagnositc+exome+sequencing monthly 0.5 https://www.helbiglab.io/blog/tag/SLC2A1 monthly 0.5 https://www.helbiglab.io/blog/tag/SLC6A1 monthly 0.5 https://www.helbiglab.io/blog/tag/epileptic+encephalopathy monthly 0.5 https://www.helbiglab.io/blog/tag/COVID-19 monthly 0.5 https://www.helbiglab.io/blog/tag/exome+sequencing monthly 0.5 https://www.helbiglab.io/blog/tag/KCNT1 monthly 0.5 https://www.helbiglab.io/blog/tag/Epi4K monthly 0.5 https://www.helbiglab.io/blog/tag/computational+phenotyping monthly 0.5 https://www.helbiglab.io/blog/tag/15q13.3+microdeletion monthly 0.5 https://www.helbiglab.io/blog/tag/AP2M1 monthly 0.5 https://www.helbiglab.io/blog/tag/SCN1A monthly 0.5 https://www.helbiglab.io/blog/tag/FIRES monthly 0.5 https://www.helbiglab.io/blog/tag/natural+history+study monthly 0.5 https://www.helbiglab.io/blog/tag/DDD+study monthly 0.5 https://www.helbiglab.io/blog/tag/GEE monthly 0.5 https://www.helbiglab.io/blog/tag/OMIM monthly 0.5 https://www.helbiglab.io/blog/tag/HLA+sequencing monthly 0.5 https://www.helbiglab.io/blog/tag/whole+genome+sequencing monthly 0.5 https://www.helbiglab.io/blog/tag/NORSE monthly 0.5 https://www.helbiglab.io/blog/tag/KCNQ2 monthly 0.5 https://www.helbiglab.io/blog/tag/healthcare+analytics monthly 0.5 https://www.helbiglab.io/blog/tag/polymicrogyria monthly 0.5 https://www.helbiglab.io/blog/tag/Epi25 monthly 0.5 https://www.helbiglab.io/blog/tag/loss-of-function monthly 0.5 https://www.helbiglab.io/blog/tag/STXBP1 monthly 0.5 https://www.helbiglab.io/blog/tag/HPO monthly 0.5 https://www.helbiglab.io/blog/tag/16p13.11+microdeletion monthly 0.5 https://www.helbiglab.io/blog/tag/Rare+Epilepsy+Network monthly 0.5 https://www.helbiglab.io/blog/tag/CNV monthly 0.5 https://www.helbiglab.io/blog/tag/focal+epilepsy monthly 0.5 https://www.helbiglab.io/blog/tag/Benign+Rolandic+Epilepsy monthly 0.5 https://www.helbiglab.io/blog/tag/neurodevelopmental+disorders monthly 0.5 https://www.helbiglab.io/blog/tag/IGE%2FGEE monthly 0.5 https://www.helbiglab.io/blog/tag/epidemiology monthly 0.5 https://www.helbiglab.io/blog/tag/EMR+genomics monthly 0.5 https://www.helbiglab.io/blog/tag/epilepstic+encephalopathy monthly 0.5 https://www.helbiglab.io/blog/tag/data+science monthly 0.5 https://www.helbiglab.io/blog/tag/Epilepsy+Foundation monthly 0.5 https://www.helbiglab.io/blog/tag/gain-of-function monthly 0.5 https://www.helbiglab.io/blog/tag/DNA+methylation monthly 0.5 https://www.helbiglab.io/blog/tag/semantic+similarity+analysis monthly 0.5 https://www.helbiglab.io/blog/tag/Myoclonic+Astatic+Epilepsy monthly 0.5 https://www.helbiglab.io/blog/tag/SCN3A monthly 0.5 https://www.helbiglab.io/blog/tag/trio+exome+sequencing monthly 0.5 https://www.helbiglab.io/blog/tag/population+genetics monthly 0.5 https://www.helbiglab.io/blog/tag/telemedicine monthly 0.5 https://www.helbiglab.io/blog/tag/EuroEPINOMICS monthly 0.5 https://www.helbiglab.io/blog/tag/BETCS monthly 0.5 https://www.helbiglab.io/blog/tag/PRRT2 monthly 0.5 https://www.helbiglab.io/blog/tag/EIEE monthly 0.5 https://www.helbiglab.io/blog/tag/rs6732655 monthly 0.5 https://www.helbiglab.io/blog/tag/DEE monthly 0.5 https://www.helbiglab.io/blog/tag/KCNB1 monthly 0.5 https://www.helbiglab.io/blog/tag/IGE monthly 0.5 https://www.helbiglab.io/blog/tag/15q11.2+microdeletion monthly 0.5 https://www.helbiglab.io/blog/tag/brain+malformation monthly 0.5 https://www.helbiglab.io/blog/tag/autism monthly 0.5 https://www.helbiglab.io/blog/tag/GNAO1 monthly 0.5 https://www.helbiglab.io/blog/tag/Brain+malformations monthly 0.5 https://www.helbiglab.io/blog/tag/genome monthly 0.5 https://www.helbiglab.io/blog/tag/exome monthly 0.5 https://www.helbiglab.io/blog/tag/genome-wide+association+study monthly 0.5 https://www.helbiglab.io/blog/tag/BFNIS monthly 0.5 https://www.helbiglab.io/blog/tag/Doose+Syndrome monthly 0.5 https://www.helbiglab.io/blog/tag/child+neurology monthly 0.5 https://www.helbiglab.io/blog/tag/Epilepsy+with+Myoclonic-Atonic+Seizures monthly 0.5 https://www.helbiglab.io/blog/tag/SCN2A monthly 0.5 https://www.helbiglab.io/blog/tag/NINDS+Curing+the+Epilepsies+Conference monthly 0.5 https://www.helbiglab.io/blog/tag/Human+Phenotype+Ontology monthly 0.5 https://www.helbiglab.io/home daily 1.0 2021-02-18 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1613670154647-8MJB5JC5LCGTAARNI24Z/artificial-neural-network-3501528_1920.jpg Home - Our Projects https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1613670186888-QALZCYKOBDZXZK06M0L0/Helbig_lab_spring_group_photo.jpg Home - Our Team https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1613670378605-D4GHSRFHVENLC18E212Q/Channelopathis.jpg Home - The Channelopathist https://www.helbiglab.io/mission daily 0.75 2020-11-25 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1606333523539-MD0JKO0JLHIFHI9APAXN/dna-4478127_1920.jpg Mission - Make data speak in rare childhood epilepsies We want to understand how to better identify and treat childhood brain disorders. Gene discovery has already transformed the way we understand rare neurological disorders in children. However, while genetic studies can be performed at scale, the analysis of clinical data often needs to be performed manually. Our goal is to expand the data science approaches established for analyzing genomic data and clinical information so that we can leverage large-scale data to better understand natural histories and treatment responses. https://www.helbiglab.io/our-team daily 0.75 2022-05-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1617114020782-H254H37KOR875I6WPO2O/gonzalez.jpg Our Team - Alexander K. Gonzalez, MS, MBA https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/bf6f85e5-4a27-495e-a228-a5a8affa03a1/Parthasarathy.jpg Our Team - Shridhar Parthasarathy https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/08631456-3274-40f2-9c46-28ab7ce8c879/Vikram.jpg Our Team - Vikram Mukherjee, MS https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/587263c7-2776-4562-b6d0-340f51dc6818/Ruggiero.jpg Our Team - Sarah Ruggiero, MS, LCGC https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/5b339119-c95a-41cd-adf3-eae5bb99a569/priya.jpg Our Team - Priya Vaidiswaran https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615697730-CSK42ZMU91XLALO4RA1B/portrait%2Batlanticare.jpg Our Team - Laina Lusk, MMSc, LCGC https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615474543-04UVCEMKXCHK3Y434Q64/ColinEllisPhoto.jpg Our Team - Colin Ellis, MD https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1594830088268-PYA8PEECJ7D495DV81KC/Screen%252BShot%252B2020-07-14%252Bat%252B10.56.50%252BAM.jpg Our Team - David Lewis-Smith, MA, MB BChir, MClinRes, MRCP https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1599163532753-1XLO9LHRLA6FZAH0LV8P/Fitch%2C+Eryn+Headshot.jpg Our Team - Eryn Fitch https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/2f66dfe1-5eba-4bd1-9a76-b796c22ef920/mckee.jpg Our Team - Jillian McKee, MD, PhD https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615576288-92MJYBJNOE0XAIY0KKUE/Ganesan_ShivaRGB-19.jpg Our Team - Shiva Ganesan, MS https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615558178-2GVJ59P21O59LOZONZ2J/Galer_Peter%252BRGB-19.jpg Our Team - Peter Galer, MSc https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/31730b97-d553-4bee-b5dc-3cf245033926/Kaufman.jpg Our Team - Michael Kaufman, MS https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1600113468956-S0P7TRF1TC9M91LUS81S/DSC_0953.JPG Our Team - Margaret O’Brien https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615644733-5NNI3J4OF1TBDVRAV3RD/Helbig%252C%2BKatherineRGB-17.jpg Our Team - Katherine Helbig, MS, LCGC https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/ea902944-36d7-404c-8302-6de12669b19c/Cosico.jpg Our Team - Mahgenn Cosico https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615771279-BWGY8DOHNR0VXER7Y6OS/6845netz.jpg Our Team - Manuela Pendziwiat https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/f8e7bf39-d320-4422-bf91-129b0b89f281/helbig.jpg Our Team - Ingo Helbig, MD https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1616615831670-1N6JO8AFHW5F8EST2WRQ/olivia.jpg Our Team - Olivia Wilmarth https://www.helbiglab.io/publications daily 0.75 2021-10-20 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603741645017-U5IBU17Q1VQQ8WC5O7KR/galerp2020.jpg Publications - Semantic Similarity Analysis Reveals Robust Gene-Disease Relationships in Developmental and Epileptic Encephalopathies (October, 2020) In the past, lack of a consistent framework has prevented the analysis of heterogenous clinical data in conjunction with genetic etiologies. This study synthesizes genetic findings with clinical features on a large scale, using the Human Phenotype Ontology (HPO) in order to assess clinical features and phenotypic relatedness for individuals with de novo variants in the same gene. This demonstrates that phenotype data, when made uniform, can provide statistical evidence in gene-disease relationships and reveal patterns from sparse clinical data. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603382709903-0Y6F7PUV2WIVKZQVTH51/image-asset.png Publications - Whole‐exome and HLA sequencing in Febrile infection‐related epilepsy syndrome (July, 2020) While recent decades have brought new information and understanding to once poorly understood epilepsy syndromes, the cause of Febrile infection‐related epilepsy syndrome (FIRES) remains up for debate, due in part to its rarity. This study aimed to identify candidate variants related to FIRES. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603462090203-Q3FXXIEY3AU99A42WHZ5/Screen%2BShot%2B2020-10-23%2Bat%2B10.06.10%2BAM.jpg Publications - A longitudinal footprint of genetic epilepsies using automated electronic medical record interpretation (August, 2020) Childhood epilepsies have a strong genetic contribution, but the disease trajectory for many genetic etiologies remains unknown. Electronic medical record (EMR) data has the potential to allow for the analysis of longitudinal clinical information. Using tools to mine EMRs to assess individual disease histories, we can better understand and follow age-related patterns leading to a better understanding of genetic epilepsies. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603383347983-HYFL59SQYDU857FSYG1H/image-asset.png Publications - Analyzing 2,589 child neurology telehealth encounters necessitated by the COVID-19 pandemic (June 2020) A new healthcare analytics pipeline that we built in response to the challenges of the telemedicine transition at the onset of the COVID-19 pandemic in March 2020 brought new opportunities to assess the rapid implementation of child neurology telehealth outpatient care. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603383463672-GVFOJEQC8JM2BNYC3SRS/Screen+Shot+2020-10-22+at+12.17.13+PM.png Publications - A Recurrent Missense Variant in AP2M1 Impairs Clathrin-Mediated Endocytosis and Causes Developmental and Epileptic Encephalopathy (May 2019) The developmental and epileptic encephalopathies (DEEs) are heterogeneous disorders with a strong genetic contribution, but the underlying genetic etiology remains unknown in a significant proportion of individuals. Pathogenic variants in single genes do not often provide a full picture when it comes to diagnosis. We analyzed whole-exome sequencing data for potential de novo variants in the same gene across individuals and then compared phenotypic similarities by using Human Phenotype Ontology (HPO) terms in 314 individuals with DEEs. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603462854205-GJP7J6HWNEAHPEV4K892/Picture1.png Publications - DNM1 encephalopathy: A new disease of vesicle fission (June 2017) Mutations in DNM1 are associated with childhood epilepsies. Here, we evaluate the phenotypic spectrum caused by mutations in dynamin 1 (DNM1), encoding the presynaptic protein DNM1. We investigate possible genotype-phenotype correlations and predicted functional consequences based on structural modeling to look for potentially homogeneous phenotypes amongst individuals with mutations in DNM1. https://www.helbiglab.io/contact-us daily 0.75 2020-11-04 https://www.helbiglab.io/our-team/alexander-k-gonzalez daily 0.75 2025-06-24 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/252f2074-4ff2-47d8-b1ac-2490fed372d0/Alexander+K.+Gonzalez.png Alexander K. Gonzalez Alexander leads the DBHi Translational Research Informatics Group (TRiG), a team of data integration analysts and data scientists specializing in data integration solutions designed to manage complex rare disease data in biomedical research. His team partners with the Helbig lab to create integrated data pipelines. https://www.helbiglab.io/our-team/priya-vaidiswaran daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/0775ebf4-6075-43e8-acf1-7a48cf0766d2/priya.jpg Priya Vaidiswaran Priya has been a member of the Helbig Lab for a little more than a year now. She has a Master in Chemistry and previously served as a lab researcher. She has wonderful interpersonal skills which make her a very successful research coordinator. She enjoys meeting new people and has enrolled numerous participants into our research protocol. Her passion for genetics and understanding for wet bench techniques makes her skillset quite unique. She is a mom of 2 rowdy kids – almost 7 and 4 years old, and yes, she is a multitasker who loves challenges. https://www.helbiglab.io/our-team/sarah-ruggiero daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/cc2cc5cf-d2dd-4e8c-910c-60bfee43245a/Ruggiero.jpg Sarah Ruggiero Sarah is a Genetic Counselor who specializes in the genetics of epilepsy and related neurodevelopmental disorders. She has a long-standing interest in neurodevelopmental disorders, and worked as a research scientist within multiple laboratories exploring the pathobiology of neurodevelopmental disorders before becoming a Genetic Counselor. Within the Helbig laboratory, she serves as a link between the clinical and research efforts of the Epilepsy Genetics Research Project. One particular area of focus is her work on the gene STXBP1, specifically, better methods to characterize STXBP1-related disorders. She has an MS in Genetic Counseling from Arcadia University, as well as a BS in Neuroscience and BA in English from the University of Delaware. https://www.helbiglab.io/our-team/david-lewis-smith daily 0.75 2020-11-04 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1596548338789-S9DWUI0A097LD5M8UIFP/Screen%252BShot%252B2020-07-15%252Bat%252B12.17.49%252BPM.jpg David Lewis-Smith David Lewis-Smith is a Wellcome Trust Clinical PhD Fellow based at Newcastle University (UK), where he is supervised by Dr Rhys Thomas (Epileptology), Prof. Heather Cordell (Statistical Genetics), and Prof. Marcus Kaiser (Neuroinformatics). He has published original research on movement disorders, peripheral nervous system, and complex neurological phenotypes. His current research focusses on the computational association of clinical neurological phenotypes with genetic variants in epilepsy, in the hope that this will facilitate more precise medicine for people with epilepsies. He is an adult neurologist by training and has a particular interest in the clinical features of genetically defined epilepsies in adulthood. He has been leading the ILAE Epilepsiome Task Force’s contributions to the Human Phenotype Ontology, primarily a seizure subontology based on contemporary ILAE Classifications. He is an active member of the ILAE SNOMED Task Force and Vice-chair of the Young Epilepsy Section of the British Branch of the ILAE. David completed his undergraduate training at Trinity Hall (University of Cambridge, 2004-2010) before moving to Newcastle for an NIHR Academic Clinical Fellowship in neurogenetics supervised by Prof. Patrick Chinnery (2010-2014) and higher specialty training in adult neurology thereafter. He is a proud father, frustrated musician and cyclist. https://www.helbiglab.io/our-team/julie-xian daily 0.75 2022-05-07 https://www.helbiglab.io/our-team/katherine-helbig daily 0.75 2020-10-27 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603807644702-GVX7SNDHRQ9TXB91GHIN/Helbig%2C+KatherineRGB-17.jpg Katherine Helbig Katherine Helbig, MS, LCGC, is a senior genetic counselor in the Division of Neurology at Children’s Hospital of Philadelphia and Co-Director of the Epilepsy Neurogenetics Initiative. She provides genetic counseling to families in the Epilepsy Neurogenetics Clinic. She has a research interest in identifying new genetic causes of infantile and childhood onset epilepsies and understanding how genetic variation leads to seizure disorders. She has led gene-discovery efforts in the epilepsies and related neurological disorders and has particular expertise in genomic analysis and variant interpretation in the epilepsies. An additional area of clinical and research interest is improving access to genetic services for people with epilepsy and understanding how genetics can improve health outcomes. She is an active member of the epilepsy genetics research community, including the Epi25 Collaborative and the EuroEPINOMICS Consortium, and is a founding member and co-chair of EpiGC, the consortium of epilepsy genetic counselors. https://www.helbiglab.io/our-team/colin-ellis daily 0.75 2020-10-26 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603739411814-2L4F8AE3VN2KRIYJHZY8/ColinEllisPhoto.jpg Colin Ellis Colin Ellis, MD, is an Assistant Professor of Neurology at the University of Pennsylvania and an Attending Physician at the Children's Hospital of Philadelphia. He completed clinical training in Neurology and Epilepsy at the University of Pennsylvania, and research fellowship in Epilepsy and Genetics at the University of Melbourne, Australia. His research focuses on epilepsy genetics, familial epilepsies, and complex non-Mendelian inheritance of epilepsy in families. An additional focus is the use of electronic medical data to improve research and clinical care in epilepsy. Dr. Ellis is a member of the Epi4K Consortium and the Epi25 Collaborative, international research consortiums focused on understanding the genetic basis of epilepsy, and the ClinGen Gene Curation Expert Panel on Epilepsy. He is a member of the American Neurological Association, the American Epilepsy Society, and the American Academy of Neurology. https://www.helbiglab.io/our-team/margaret-o-brien daily 0.75 2020-11-04 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1600113572229-HBWXRLVF3Q36J3HCMG7S/DSC_0953.jpg Margaret O' Brien Margaret O'Brien is a research student in the Helbig Lab. She currently attends Lewis Katz School of Medicine at Temple University. She has been working with the Helbig Lab since 2016 when she began as Dr. Helbig's Research Coordinator. Now in medical school, she has since transitioned from a coordinator role to a research role. Her current project involves analyzing admission and readmission rates for children with genetic epilepsies. This research is important to her because prior to going to medical school she met many of Dr. Helbig's patients in Neurogenetics Clinic at CHOP. She hopes that her research will help provide better care for kids with genetic epilepsies and continue to educate clinicians about this diverse population. Margaret grew up right outside of Philadelphia and when she is not studying, she enjoys planning activities and cooking. She continues to be inspired by the members of the Helbig team and the research they are doing. https://www.helbiglab.io/our-team/ingo-helbig daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/d7992d46-8707-4f25-86af-bfcd23968a9a/helbig.jpg Ingo Helbig Ingo Helbig, MD, is a pediatric neurologist in the Division of Neurology at Children's Hospital of Philadelphia. Dr. Helbig went to medical school in Heidelberg and Mannheim, Germany, and Lexington, Kentucky, USA. He trained at the Epilepsy Research Centre, Melbourne, Australia, and was Assistant Professor at the Department of Neuropediatics, Kiel, Germany. Between 2011 and 2015, he co-headed the EuroEPINOMICS-RES Consortium, the European counterpart of the NIH-funded Epi4K consortium involved in collaborative genomic studies to identify genes for human epilepsies. He was part of the Genetics Commission of the International League Against Epilepsy (ILAE) from 2014-2017 and currently leads the Epilepsiome Task Force of the ILAE Genetics Commission, which aims at increasing genetic literacy in the epilepsy community. After heading the epilepsy genetics group at the University of Kiel, Germany, he transferred to the Children’s Hospital of Philadelphia (CHOP) in 2014 and became faculty in the Division of Neurology in July 2017. The main focus of his prior work was to understand how genetic changes lead to severe epilepsies in both children and adults, contributing to several new gene findings in the field in the last seven years including GRIN2A, CHD2, KCNA2, HCN1, and DNM1. Dr. Helbig uses clinical and research expertise to curate epilepsy-related genes in variants within his leadership role of the Epilepsy Clinical Domain Working Group. https://www.helbiglab.io/our-team/michael-kaufman daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/588fdf2a-a817-4aa8-af9b-ef4792c68899/Kaufman.jpg Michael Kaufman Michael joined the Helbig lab as a Data Scientist in April of 2020. He brings with him a background from his previous work experience in marketing and data analysis. Michael has a BA in Cognitive Science from Vassar College and an MS in Data Science from Drexel University. Michael is passionate about data and how it can be used to understand and improve the world. At the Lab, Michael has worked on a variety of projects including those related to telemedicine, EMR genomics and phenotypic analysis. In his spare time, Michael enjoys baking, writing music and weight-lifting (to work off all the baked goods). https://www.helbiglab.io/our-team/manuela-pendziwiat daily 0.75 2020-11-11 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1605113655297-KF0PYODY4K2YSI9BDEWT/6845netz.jpg Manuela Pendziwiat Manuela Pendziwiat is a Biochemist and the Project Manager maintaining our German research studies in UKSH. She received her degree in biochemistry from University of Leipzig and a vocational training as skilled administrative assistant. She specializes in genetics and neurodevelopmental disorders and works as a research scientist. https://www.helbiglab.io/our-team/mahgenn-cosico daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/79743cbb-f277-421b-bd79-f466f2243186/Cosico.jpg Mahgenn Cosico Mahgenn is a clinical research coordinator with the Division of Neurology at the Children’s Hospital of Philadelphia. She received her Bachelor’s in Science with The University of Saint Peter’s in northern New Jersey. Using her academic and professional skills she helps manage various projects focusing on pediatric epilepsy genetics and neurodevelopmental disorders. Mahgenn, also helps significantly increase project recruitment numbers and increase study efficiency. She also has a passion advocating for the children and families she meets and has a family of her own with her loving husband and 3 beautiful children. In her spare time, she loves being around her family and friends. https://www.helbiglab.io/our-team/peter-galer daily 0.75 2020-10-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1599576869494-EMIUA516SPJJ2VTQ285O/Galer_Peter+RGB-19.jpg Peter Galer Peter has been with the Helbig Lab at CHOP since 2017 working first as a Research Technician and in 2020 as a Bioengineering PhD student at University of Pennsylvania working jointly with the Litt Lab. Prior to joining the Lab he received his MSc in Cognitive Science from the School of Informatics at the University of Edinburgh and his BA from Vassar College with a major in Cognitive Science and a minor in History. His work has been focused on the development of algorithms which incorporate computational phenotypes, electronic health records, and genomic data and hopes to expand into other areas such as Natural Language Processing and neural interface devices. https://www.helbiglab.io/our-team/eryn-fitch daily 0.75 2020-10-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1599163572998-ZSWYECHTEP7F7HYX2UTS/Screen%252BShot%252B2020-07-15%252Bat%252B11.41.33%252BAM.jpg Eryn Fitch Eryn Fitch completed her B.S. in Biology, Genetics and Development option, from the Pennsylvania State University in May 2019. For the past year, she has been working as a Genetic Counseling Assistant with the Neurology Department at CHOP. Starting in July 2020, she is a working full-time in Dr. Helbig’s lab as a Clinical Research Assistant focused on participant research enrollment and variant interpretation/curation efforts within ENGIN’s variant curation core and the U54 Channelopathy-associated Epilepsy Research Center. Outside of work, she enjoys traveling, watching bad reality television, trying out new restaurants, and doing anything involving Penn State. https://www.helbiglab.io/our-team/shiva-ganesan daily 0.75 2025-06-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/679772cb-8943-4ff5-af6b-45fdcfee2a17/shiva_headshot-1.jpg Shiva Ganesan Shiva is a Bioinformatician with experience in epilepsy and neurodevelopmental disorders. His main research interests involve computational phenotypes and genomics. In the Helbig lab, he works on data production pipelines for genome/exome sequencing (NGS) data after serving as a Data Science Intern at CHOP. Shiva has a Master of Science in Operations Research and is pursuing his PhD in Biomedical Science from Drexel University. https://www.helbiglab.io/our-team/laina-lusk daily 0.75 2020-10-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1596558329909-NKXJMSIKQUYUNTK2HEY6/portrait%2Batlanticare.jpg Laina Lusk Laina is a genetic counselor in the division of neurology at the Children’s Hospital of Philadelphia, with a research interest in understanding the genetic mechanisms and clinical phenotypes of childhood epilepsy and related neurodevelopmental disorders. She received her BS in neuroscience from Bucknell University and her MMSc in human genetics and genetic counseling from Emory University. Laina has prior clinical experience working as a cancer genetic counselor, and prior research experience in the field of neurodevelopmental disorders. In the Helbig Lab, she serves as a clinical liaison and assists with phenotyping projects. https://www.helbiglab.io/our-team/olivia-wilmarth daily 0.75 2020-10-23 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1596550816278-K9U2LC9DJU3NZZX647TY/olivia.png Olivia Wilmarth Olivia Wilmarth is a Genetic Counseling Assistant supporting CHOP's Division of Neurology. She is a recent graduate of Georgetown University, where she majored in Global Health and minored in Disability Studies. Her capstone research paper focused on the need for implementing clinical genetics services in low-income countries and the barriers toward effective implementation. Olivia has been interested in genetics since high school and hopes to attend graduate school for Genetic Counseling in the near future. She is excited to learn about clinical genetics research as a new member of the Helbig Lab team. https://www.helbiglab.io/projects daily 0.75 2020-11-09 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603805750324-GTWUZLRQ5VRW4K3WCSG7/Ganesan2020.jpg Projects EMR Genomics Collating medical records and genomics to make new discoveries. When studying genes, we must take a holistic approach. Using medical records in combination with genetic analysis, we are able to get a more complete and longitudinal picture of each individual’s background to come to comprehensive conclusions about the trajectory of a disease. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604074286510-Z3XA6DR15Z1RVX7JVRIL/Galer2020.jpg Projects Human Phenotype Ontology Understanding the new language of phenotypes. As of 2017, the cost of a phenome has eclipsed the cost of a genome. This is largely due to the diversity of clinical data. We are involved in the ongoing curation of the Human Phenotypic Ontology (HPO) and we develop methods to make sparse and heterogeneous clinical data comparable. See our blog post on how we try to have algorithms do what Dr. Rett did more than 60 years ago https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603805219090-WUW2BADS55A71C2DFBUS/EGI2019.jpg Projects Epilepsy Gene Discovery Determining the genetic causes of pediatric epilepsy. Genetic testing is integral to the work we do. This testing allows us to not only gain insights into causes of difficult to treat epilepsies in individuals, but will assist in the discovery of new and wider patterns of the genetic components of epilepsies. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603805850986-A45I642HNNOAL36ZP67W/Telemed2020.jpeg Projects Telemedicine Analytics It’s not just how we treat patients, but where. Location can be essential to a child’s development, and treatment location is no exception. Several of our projects investigate the potential differences in treatment that may occur between in-person and telemedicine outpatient appointments. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604932535726-TWIC9HRXC7SV3MNV5G33/Humboldt2018.jpg Projects The FENICS project Harmonization of functional data in the epilepsies. We have a standardized language for genetics and increasingly for clinical features, but what about the functional results in genetic epilepsies? Electrophysiological studies are increasingly performed at scale and we are developing controlled dictionaries as part of our involvement in the Epilepsy Center Without Walls (CWOW) for epilepsy-related ion channel disorders. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1603805541635-ELOFNPRWDC5UR87B65TB/image-asset.jpeg Projects Epilepsy Precision Medicine Where research becomes treatment. At the Helbig Lab, we do more than research genetic epilepsies. By connecting clinical care directly to our research, not only can we discover causes of genetic epilepsy, but we can help develop new gene-specific treatments. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604074912689-8QA8YV50UE50PIR3OHO0/Epilepsiome2018.jpg Projects The Epilepsiome Beyond the Ion Channel. For the last decade, we have blogged about the genetics of the epilepsies at epilepsygenetics.net, which has become the official blog of the Genetics Commission of the International League Against Epilepsy (ILAE). The Channelopathist is a frequently used resource that keeps the community informed about current trends and studies in the field of genetic epilepsies. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604074509975-4EJ7DAQN5GJQ7MU47YVE/OMIM2020.jpg Projects ClinGen Gene Curation The guardians of the epilepsy genes. We are leaders in the Epilepsy Clinical Domain Working Group of the NIH-funded ClinGen consortium and our role is to evaluate whether suggested genetic causes for the epilepsies are valid. Make no mistake, in our role as the guardian of the epilepsy genes, we have already sent several alleged epilepsy genes into early retirement. Epilepsy gene curation is a critical link between the epilepsy sphere and the concepts and frameworks used in laboratory medicine. https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1604073708026-5SJMUG17N381EEVPTXEM/Trilateral2014_final-1024x768.jpg Projects Epilepsy Family Studies Discovering how epilepsy runs in families. Before the exome era, most epilepsy genes were discovered through family studies. However, the art of family studies in the epilepsies has largely been forgotten. We are involved in large-scale projects for gene discovery in family epilepsies and lead a major project connecting researchers from Germany, Israel, and Palestine. https://www.helbiglab.io/hpo-guidance daily 0.75 2021-06-11 https://www.helbiglab.io/resources daily 0.75 2021-06-14 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/1623442669278-6CWMMSWRHGZW4Q0G23T3/HPO-logo-black_small.png Resources - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.helbiglab.io/our-team/vikram-mukherjee daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/03568014-9bba-4e93-8c7f-3ca37cca8b68/Vikram.jpg Vikram Mukherjee Vikram is a clinical research coordinator at the Division of Neurology, within the ENGIN Program. After completing his undergraduate degree at the University of Pittsburgh ('20) in neuroscience and Spanish, he pursued a master's in biomedical science at Rutgers School of Graduate Studies ('21). His research interests include creating faster MRI Acquisition methods for pediatric patients and expanding on the Social Determinants of Health (SDOH) model specifically within the LatinX and South Asian Communities. Vikram aspires to apply to medical school and to eventually become a pediatric neurologist to improve medical care and research within underserved communities. Outside of his academic pursuits, Vikram enjoys playing the Tabla, cooking, and exercising. https://www.helbiglab.io/our-team/jillian-mckee daily 0.75 2022-05-12 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/f09c87ea-2042-4348-9889-6f848341cb1f/mckee.jpg Jillian McKee Jillian McKee, MD, PhD is an epilepsy neurogenetics fellow at the Children’s Hospital of Philadelphia. She completed her undergraduate studies at McGill University in physiology, before moving to the University of Chicago for her medical education and graduate studies in computational neuroscience. She completed residency in pediatrics and child neurology at the Children’s Hospital of Philadelphia and the University of Pennsylvania. Dr. McKee’s research interests include applying machine learning techniques to electronic medical data to delineate novel disease trajectories and develop seizure prediction models to guide the care of neonates and children with epilepsy. Additional clinical and research interests include SYNGAP1-related neurodevelopmental disorder and data-driven approaches to identifying candidates for epilepsy surgery. https://www.helbiglab.io/shridhar-parthasarathy daily 0.75 2022-05-10 https://images.squarespace-cdn.com/content/v1/5e1f8961725933600ed50e69/02b6b6e4-f437-48e5-9313-375ec9356e62/Parthasarathy.jpg Shridhar Parthasarathy