Publications by authors named "E M Litkowski"
We performed ancestry and sex specific Phenome Wide Association Studies (PheWAS) to explore disease related outcomes associated with genetically predicted height. This is the largest PheWAS on genetically predicted height involving up to 840,000 individuals of diverse ancestry. We explored European, African, East Asian ancestries and Hispanic population groups.
View Article and Find Full Text PDFAims/hypothesis: This is the first study to examine the association between variants of the glucagon-like-peptide-1 receptor gene (GLP-1R) and metabolic characteristics among youth. We explored separate associations of three GLP-1R polymorphisms (rs10305420, rs6923761, and rs1042044) with BMI trajectories and markers of glucose-insulin homeostasis.
Methods: Mixed models examined associations between GLP-1R polymorphisms and trajectories of BMI.
Article Synopsis
- Researchers investigated blood protein networks in chronic obstructive pulmonary disease (COPD) using data from over 3,000 participants to better understand complex interconnections rather than just individual biomarker changes.
- They applied advanced techniques to analyze 4,776 proteins, identifying significant networks linked to factors like smoking status and emphysema.
- The study found both known and new proteins associated with COPD, highlighting the importance of these networks in understanding the disease across different ethnic groups, with some results replicating in another study cohort.
Objective: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates.
Research Design And Methods: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%).
Results: T1D characteristics increased progressively with higher genetic risk (P < 0.
Background: Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.
Methods: Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.