Dr. Weinshilboum's research program is focused on pharmacogenomics, the study of the role of inheritance in variation among patients in drug response phenotypes — phenotypes that can vary from severe life-threatening adverse drug reactions at one end of the spectrum to lack of the desired therapeutic drug effect at the other. Over the years, pharmacogenetics has evolved into pharmacogenomics and, recently, into pharmaco-omics with the integration of genomics with transcriptomics, proteomics and metabolomics. Each of these studies can involve millions or even billions of data points requiring significant computational analysis.
Dr. Weinshilboum's laboratory pursues pharmacogenomic studies related to drug therapies for:
- Cancers, including:
- Childhood leukemia
- Breast cancer
- Psychiatric diseases, including:
- Major depressive disorder (depression), the most common of all psychiatric diseases
- Alcohol use disorder (alcoholism)
These projects combine drug therapy, genomics, molecular biology and — for the analyses — machine learning and artificial intelligence.
Acute lymphoblastic leukemia (ALL) is the most common cancer in children. It is now possible to cure over 90% of these children with drug therapy. One of the key drugs for the treatment of childhood ALL is mercaptopurine, but occasionally this important drug will destroy a child's bone marrow, resulting in a life-threatening adverse drug reaction.
Dr. Weinshilboum's laboratory discovered that this severe drug reaction is due to genetic variation in a gene encoding the enzyme thiopurine methyltransferase (TPMT), which the body uses to inactivate mercaptopurine. That discovery made TPMT genetic polymorphisms one of the earliest and most widely used clinical pharmacogenomic biomarkers, which made it possible to avoid an adverse drug reaction.
Dr. Weinshilboum's program has applied a similar approach to drugs used to treat breast cancer to understand both drug response and underlying mechanisms responsible for variation in the efficacy of antineoplastic drugs, especially those used to treat estrogen receptor positive breast cancer.
Major depressive disorder (MDD, depression) pharmacogenomics
MDD is a major cause of medical disability worldwide and — because of the risk of suicide — it is also a major cause of mortality. Selective serotonin reuptake inhibitors (SSRIs) are the standard of care for the drug therapy of MDD. However, one-third to one-half of patients with MDD do not achieve adequate relief of symptoms from SSRI therapy.
Dr. Weinshilboum's research program has used genome-wide association studies (GWAS) to scan the genome and identify genes associated with variation in SSRI clinical response. In addition, by employing pharmaco-omics, he has used metabolomics data to "inform" GWAS to make it possible to identify novel genes associated with variation in SSRI clinical response, such as ERICH3 and TSPAN5. Then using single nucleotide polymorphisms (SNPs) in those genes — combined with clinical data and machine learning techniques — he has developed algorithms to predict who will and who will not respond to SSRI therapy. Dr. Weinshilboum is taking a similar approach to study variation in response to drugs that are used to treat patients who have alcohol use disorder (AUD, alcoholism).
The pharmacogenomics research program of this laboratory uses genomics, transcriptomics, proteomics and metabolomics to identify genes associated with variation in response to drugs used to treat cancer and neuropsychiatric disease and then to pursue the underlying biological mechanisms responsible for those variations in order to design better drugs and more accurately predict variation in drug response.