Kathleen Fisch
· Ph.D.University of California, San Diego · Medical Genetics
Active 2009–2024
About
Kathleen Fisch, Ph.D., is an Assistant Professor in the Department of Obstetrics, Gynecology and Reproductive Sciences at UC San Diego, within the Division of Maternal-Fetal Medicine. She serves as the Faculty Director of the ACTRI Center for Computational Biology & Bioinformatics (CCBB), Co-Director of the UC San Diego Center for Perinatal Discovery, and is a member of the ACTRI Executive Committee. Her research focuses on understanding the molecular mechanisms underlying pregnancy disorders and exposures to improve maternal and child health throughout the lifespan. Her active research areas include exploring the role of somatic mutations in placental dysfunction, identifying non-invasive biomarkers of placental disorders, and investigating the relationship between prenatal exposures and pregnancy outcomes. Dr. Fisch has a background in Integrative Biology from UC Berkeley and Ecology with an emphasis in population genetics from UC Davis. She completed postdoctoral training in population genomics and modeling at the San Diego Zoo Institute for Conservation Research, followed by computational genomics and bioinformatics training at Scripps Research.
Research topics
- Biology
- Computational biology
- Computer Science
- Data Mining
- Genetics
- Bioinformatics
- Medicine
- Environmental engineering
- Psychology
- Physical therapy
- Data science
- Cell biology
- Physiology
- Neuroscience
- Intensive care medicine
- Virology
- Anatomy
- Psychiatry
- Engineering
- Environmental science
Selected publications
Pain · 2023 · 101 citations
- Medicine
- Bioinformatics
- Intensive care medicine
ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.
Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)
Nature Cell Biology · 2023 · 170 citations
- Computational biology
- Cell biology
- Biology
Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission
Nature · 2022 · 517 citations
- Computer Science
- Biology
- Computational biology
. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.
NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data
iScience · 2021 · 49 citations
- Computer Science
- Data Mining
- Computer Science
With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.
Cell · 2020 · 384 citations
- Biology
- Computational biology
- Bioinformatics
Recent grants
Omics Data Generation Center (ODGC) for the Acute to Chronic Pain Signatures (A2CPS) Program
NIH · $8.7M · 2019–2026
Frequent coauthors
- 59 shared
Joseph A. Califano
University of California, San Diego
- 58 shared
Theresa Guo
Moores Cancer Center
- 56 shared
Shuling Ren
Capital Medical University
- 50 shared
Sayed Sadat
- 42 shared
Guorong Xu
- 32 shared
Chanond A. Nasamran
University of California, San Diego
- 29 shared
Akihiro Sakai
Hiroshima Red Cross Hospital & Atomic-bomb Survivors Hospital
- 28 shared
Mizuo Ando
Education
- 2010
Ph.D., Reproductive Sciences
University of California, San Diego
- 2006
M.S., Reproductive Sciences
University of California, San Diego
- 2004
B.S., Biology
University of California, San Diego
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