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Biomedical subjects

Jennifer Huffman

Publications and source records attributed to Jennifer Huffman.

2 recordsLinked to original sources

Historical review: more than two decades understanding the genetic architecture of hemostasis and thrombosis.

From the beginning of the millennium and the development of genome-wide analyses, the technical advances and remarkable increase in research sample sizes have led to an escalating number of discoveries revealing genetic determinants of levels of the main factors regulating hemostasis and thrombosis and demonstrating a clear polygenic complex regulation of most coagulation factors. These discoveries have been useful to understand the biology underlying hemostasis regulation and to understand risk of associated thrombotic disease, such as venous thromboembolism, coronary artery disease, and ischemic stroke. In this historical review, we outline the main discoveries in genetic studies of coagulation factors (fibrinogen and its alternatively spliced γ' isoform, D-dimer, factor [F]V, FVII, FVIII, von Willebrand factor, and FXI), the main natural anticoagulants (protein C, protein S, and antithrombin), components of fibrinolysis (tissue plasminogen activator and plasminogen activator inhibitor-1), and global coagulation tests (prothrombin time and activated partial thromboplastin time). We explore the clinical implications of these discoveries and suggest new avenues for future investigation.

Humans

Polygenic scores for obstructive sleep apnoea reveal pathways contributing to cardiovascular disease.

BACKGROUND: Obstructive sleep apnoea (OSA) is a common chronic condition, with obesity its strongest risk factor. Polygenic scores (PGSs) summarise the genetic liability to phenotype and can provide insights into relationships between phenotypes. Recently, large datasets that include genetic data and OSA status became available, providing an opportunity to utilise PGS approaches to study the genetic relationship between OSA and other phenotypes, while differentiating OSA-specific from obesity-specific genetic factors. METHODS: Using race/ethnic diverse samples from over 1.2 million individuals from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger's MyCode, MGB Biobank, and the Human Phenotype Project, we developed and assessed PGSs for OSA, both without (BMIunadjOSA-PGS) and with adjustment for the genetic contributions of BMI (BMIadjOSA-PGS). FINDINGS: Adjusted odds ratios (ORs) for OSA per 1 standard deviation of the PGSs ranged from 1.38 to 2.75. The associations of BMIadjOSA- and BMIunadjOSA-PGSs with CVD outcomes in AoU shared both common and distinct patterns. Only BMIunadjOSA-PGS was associated with type 2 diabetes, heart failure, and coronary artery disease, while both BMIadjOSA- and BMIunadjOSA-PGSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA-PGS association with hypertension was driven by females (OR = 1.1, p-value = 0.002, OR = 1.01 p-value = 0.2 in males). OSA PGSs were also associated with body fat measures with some sex-specific associations. INTERPRETATION: Distinct components of OSA genetic risk are related and independent of obesity. Sex-specific associations with body fat distribution measures may explain differing OSA risks and associations with cardiometabolic morbidities between sexes. FUNDING: R01AG080598.

Humans