Madhuri Hegde, PhD, FACMG

Adjunct Professor

Office: Rm 221 ext 8-8589

Lab: Clinical: Rm 221 Phone: 404-778-8589; Research: Office: 305M Phone: 404-727-3875

Phone: 404-727-3863


Research Interests

Muscular Dystrophy:  Understanding the functional intricacy and the effect of mutation on the protein expression is critical to making the right choice of therapeutic approach for Congenital Muscular Dystrophy (CMD) and Limb Girdle Muscular Dystrophy (LGMD). We are using an integrated approach using next generation genotyping, sequencing and microarray tools, to identify new gene and create a comprehensive map of the CMD and LGMD muscle exome, transcriptome and proteome, which may aid in choosing the most appropriate and focused personalized therapeutic approach.

Newborn screening: Duchenne muscular dystrophy (DMD) is an inherited form of muscular dystrophy which occurs in about 1 out of every 3,600 male infants. In spite of the high frequency of disease, newborn screening (NBS) for DMD is not in practice except in a few countries worldwide. Though, creatine kinase (CK) level testing has been attempted as a NBS method, the high false positive rate and the need for follow-up re-testing have rendered the test unacceptable for NBS. Based on the promising reports from a recent study that introduced a two-tier screening system using dried blood spots from birthing process, we are validating and implementing a comprehensive and low cost next generation sequencing (NGS) approach to detect all types (deletions, duplications and point mutations) in the DMD gene.

Dysferlinopathies: DYSF is a large gene comprising 55 exons and spanning a genomic region of >150 kb. Although mutation detection provides the most definitive diagnosis, it does not provide information about protein expression. We are using a modified monocyte assay method to identify dysferlin deficient patients and compare the dysferlin expression data with the genotype data to define the correlation of protein expression and disease severity. This data will useful in monitoring patients entering gene therapy trials for dysferlin. We have also implemented this strategy in India.

Clinical Sequence Variant Classification and EMR integration: Current technology allows clinical laboratories to rapidly translate research discoveries from small patient cohorts into clinical genetic tests; therefore, a potentially large proportion of sequence variants identified in individuals with clinical features of a genetic disorder remain unpublished.  Clinical laboratories willing to share this data face technological and practical barriers perpetuating a current problem: inconsistent interpretation of sequence variants from clinical laboratories working with different information.   We have developed an in-house data management system, which is a highly-curated clinical grade variant database with a data structure designed to facilitate sharing of variants identified at EGL. This system also tracks changes in variant classifications, generating notifications for the laboratory about which cases are in need of a review and possible report update. The second component, EmVClass, is a web-based tool that allows any user to view and request a review of variants classified at EGL. These software tools provide a solution to two pressing problems in clinical genetic testing:  how to make sequence variants identified in a clinical laboratory freely available to the community and how to communicate changes in variant classification to healthcare providers.

Medical Exome: Next generation sequencing (NGS) technologies are increasingly gaining acceptance in clinical laboratories in the form of targeted gene panels and exome sequencing. These targeted tests are used extensively in the testing for Mendelian diseases with locus and allelic heterogeneity and cancer. While their moderate size allows for high coverage, technical sensitivity and the ability to generate data for every interrogated base, their clinical sensitivity is usually suboptimal. In contrast, exome sequencing offers enhanced detection rates but does not return data for the entire target region, thereby limiting its clinical utility. To address these challenges, in collaboration with Dr. Birgit Funke (Harvard) and Dr. Avni Santani (CHOP) we are performing an in-depth and iterative curation of all genes that are currently known to be medically relevant. We are also  developing a clinically validated enhanced exome assay where coverage of medically relevant genes is optimized. The assay design will be shared with the genetic testing community to promote standardization of medical sequencing. This information will be critical for clinical laboratories, physicians, and researchers that interpret data within the context of a patient's clinical findings and are rapidly adopting exome and genome wide sequencing, where access to curated knowledge is critical to analyze the large number of variants returned.

Areas of Specialization

  • Muscular Dystrophy
Novel and high throughput methodologies to detect sequence variation


  • BSc, University of Bombay, India,
  • MSc, University of Bombay, India,
  • PhD, University of Auckland, New Zealand,
  • Postdoctoral Fellowship, Baylor College of Medicine,

Board Certifications

  • FACMG (Clinical Molecular Genetics)


Robert C. Green, MD, MPH, Jonathan S. Berg, MD, PhD, Leslie Biesecker, MD, David Dimmock, MD, James P. Evans, MD, PhD, Wayne W. Grody, MD, PhD, Madhuri Hegde, PhD, Sarah Kalia, ScM, Bruce R. Korf, MD, PhD, Ian Krantz, PhD, Amy L. McGuire, JD, PhD, David Miller, MD, PhD, Mike Murray, MD, Robert Nussbaum, MD, PhD, Sharon Plon, MD, Heidi L. Rehm, PhD, FACMG, Howard J. Jacob, PhD. Expert Concordance and Discordance for Return of Incidental Findings from Whole Genome Sequencing. Genetics in Medicine. Genet Med. 2012 Apr 14 (4): 405-10.

Bobby G. Ng, Karl Hackmann, Melanie A. Jones, Alexey M. Eroshkin, Ping He, Roy Wiliams, Shruti Bhide, Vincent Cantagrel, Joseph G. Gleeson, Amy S. Paller, Rhonda E. Schnur, Sigrid Tinschert, Janice Zunich, Madhuri R. Hegde, Hudson H. Freeze. Mutations in the glycosylphosphatidylinositol biosynthesis gene PIG-L cause CHIME syndrome. Am J Hum Genetics. Am J Hum Genet. 2012 Apr 6; 90(4): 685-8. Epub 2012 Mar 22.

Amy Gargis, Lisa Kalman, Meredith Berry, David Bick, David Dimmock, Tina Hambuch, Fei Lu, Elaine Lyon, Karl Voelkerding, Barbara Zehnbauer, Richa Agarwala, Sarah Bennett, Bin Chen, Ephrem Chin, John Compton, Soma Das, Dan Farkas, Matt Ferber, Adam Felsenfeld, Birgit Funke, Manohar Furtado, Lilia Ganova-Raeva, Ute Geigenmuller, Sandra Gunselman, Madhuri Hegde, Philip Johnson, Andrew Kasarskis, Shashikant Kulkarni, Thomas Lenk, Jonathan Liu, Megan Manion, Teri Manolio, Elizabeth Mansfield, Elaine Mardis, Jason Merker, Mangalathu Rajeevan, Martin Reese, Heidi Rehm, Brigitte Simen, Joanne Yeakley, Justin Zook, Ira Lubin. Next Generation Sequencing in medical genetics: Approaches to Quality Assurance and Compliance with Regulatory and Professional Standards. Nat Biotechnol. 2012 Nov; 30(11):1033-6.

Martinez A, Chin E, Hegde M. Clinical next generation sequencing panel for Congenital muscular dystrophy.  PLoS One. 2013;8(1): e53083.

Ankala, A, Kohn, J. N, Khadilkar, S. V, Gaitonde P, Dastur R, Hegde, M. R. Ancestral founder mutations in calpain-3 in the Indian Agarwal community: Historical, clinical, and molecular perspective. Muscle and Nerve. Muscle Nerve. 2013 Jun;47(6):931-937

Michael F. Wangler, Rishikesh Chavan, M. John Hicks, Jed.G. Nuchter, Madhuri Hegde, Sharon E. Plon, Patrick A. Thompson. Unusually early presentation of small-bowel adenocarcinoma in a patient with Peutz-Jeghers syndrome. J Pediatr Hematol Oncol. 2013 May; 35(4):323-8.

Ephrem L.H. Chin, Cristina da Silva, Madhuri Hegde. Assessment of clinical analytical sensitivity and specificity of next generation sequencing for detection of simple and complex mutations. BMC Genet. 2013 Feb 19;14:6.

Lisa Kalman, Jack Tarleton, Monica Hitch, Madhuri Hegde, Nick Hjelm, Elizabeth Berry-Kravis, Lili Zhou,James Hilbert, Richard Moxley III, Elizabeth Luebbe, Lorraine Toji. Quality Assurance for Myotonic Dystrophy type 1 (DM1) Genetic Testing: Development of a Genomic DNA Reference Material Panel. Journal of Molecular Diagnostics. J Mol Diagn. 2013 May 13. doi:pii: S1525-1578

Sandhya Iyer, Arunkanth Ankala, Rekha Singh, Madhuri Hegde. Determination of common genetic variants in cytidine deaminase (CDA) gene in Indian ethnic population. Gene. 2013 Jul 15; 524(1): 35-9.

Rong Fu, Madhuri Hegde, H. A. Jinnah. Genotype-Phenotype Correlations in Lesch-Nyhan Disease and its Attenuated Variants. Brain. Accepted

Jones M, Rhodenizer D, Da Silva C, Bean LJB, Coffee B, Tanner A, Collins C, Hedge M. Molecular Diagnostic Testing For Congenital Disorders Of Glycosylation (CDG): Detection Rate For Single Gene Testing And Next Generation Sequencing Panel Testing. Mol Genet Metab. Mol Genet Metab. 2013 May 28. S1096-7192(13) 00178-9.

Lora J. H. Bean, Stuart W. Tinker, Cristina da Silva, Madhuri R. Hegde. Free the Data: One Laboratory's Approach to Knowledge-based Genomic Variant Classification and Preparation for EMR Integration of Genomic Data. Human Mutation. Hum Mutat. 2013 Jun 11. doi: 10.1002/humu.22364

Heidi L. Rehm, Sherri J. Bale, Pinar Bayrak-Toydemir, Jonathan S. Berg, Kerry K. Brown, Joshua L. Deignan, Michael J. Friez, Birgit H. Funke, Madhuri R. Hegde and Elaine Lyon; A Working Group of the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee. ACMG clinical laboratory standards for next-generation sequencing. Genetics in Medicine. In press.

Madhuri Hegde. Marching towards personalized genomic medicine. J Pediatr. 2013 Jan; 162 (1):10-1.

Eli Williams, Madhuri Hegde. Implementing genomic medicine in Pathology. Advances in Anatomic Pathology. Adv Anat Pathol. 2013 Jul;20(4):238-44