The overarching goal of the Genetic Epidemiology of Heart, Lung, and Blood (HLB) Traits Training Grant (GenHLB, T32HL129982) is to foster the next generation of interdisciplinary HLB genetic epidemiologists. GenHLB fellows will receive multidisciplinary and individualized instruction focusing on HLB genetic epidemiology and a complementary training dimension (computation/methods; culture, diversity, diversity, and disparities; or OMICs). These four training dimension reflect programmatic strengths and our beliefs about the multidisciplinary research training necessary to develop the next generation of HLB genetic epidemiology research leaders. We also offer faculty with expertise in wide-ranging diseases and phenotypes relevant to the National Heart, Lung, and Blood Institute (NHLBI, e.g. bleeding disorders, coagulation, pulmonary hypertension, cystic fibrosis, chronic obstructive pulmonary disease, ciliopathies, asthma, pulmonary function, obesity, cardiovascular disease, preeclampsia, metabolism, cardiac conduction, and eating disorders) as well as tailored career development resources. Our multidisciplinary approach to training will enable GenHLB fellows to conduct innovative independent investigator-initiated research that traverse traditional substantive boundaries to advance understanding of the genomic basis of HLB traits and diseases in the most-burdened populations.
HLB genetic epidemiology is the core training dimension that unites the three complementary training dimensions and provides the research framework and formal didactics to necessary to fulfill GenHLB core competencies. Designating HLB genetic epidemiology as the core training dimension also reflects our belief that understanding the genetic and non-genetic underpinnings of HLB phenotypes is essential to designing and conducting effective clinical and public health studies that prevent disease and promote health.
Computation/methods. ‘OMICs technologies have brought about the rise of “discovery-based” science, prompted by the size and complexity of ‘OMICs datasets that require sophisticated statistical methods to obtain proper conclusions and discern subtle, but important signals. In parallel, increasing interests in causal inference and integrative association analysis, among other opportunities, necessitate advanced training in statistics, bioinformatics, and computational biology. Inclusion of a computation/methods dimension directly responds to these contemporary opportunities.
Culture, diversity, and disparities. The distribution and impact of HLB phenotypes differ markedly among populations and often disproportionally affect U.S. minorities. Despite these long-standing disparities, the majority (>80%) of participants included in array based, large-scale genetic epidemiological studies to-date are of European descent. Culture, diversity, and disparities was included as a complementary training dimension because HLB genetic epidemiology research will not reach its full clinical impact unless all populations benefit equally.
OMICs. OMICs are a diverse class of biomarkers that are rapidly evolving in both application and measurement and include genomics, transcriptomics, epigenetics and metabolomics. Recent technological advances have exponentially expanded the breadth of available OMICs data, enabling the evaluation of scientific questions that until this time were impossible to evaluate in large-scale human studies. At the same time, it has been increasingly recognized that few individual OMICs measures can fully capture the intricacy of complex molecular phenotypes and their disease manifestations. Inclusion of an OMICs training dimension allows us to ensure that the next generation of HLB genetic epidemiologists are well-equipped to leverage these biological molecules for discovering novel risk factors and characterizing biologic mechanisms.