COPD is currently diagnosed by spirometry, but many other individuals (primarily smokers) have respiratory symptoms and/or imaging abnormalities that suggest lung damage. Identifying subjects with pre-obstruction manifestations of COPD could lead to more effective treatment and prevention.

COPD subjects often develop ongoing inflammation that persists long after smoking cessation. It is unknown when this cycle of inflammation begins or what causes it.

Chronic Obstructive Pulmonary Disease (COPD) is a complex heterogeneous syndrome. The current approach of regarding this disease as a single entity has limited the ability to develop effective therapies and prevention. Understanding the major subtypes of COPD could lead to more biologically relevant disease classifications, improved prognostic information, and precision medicine treatment.

The optimal analytical approaches and data types to define complex disease subtypes have not been determined.

Most chronic lung diseases, including COPD, do not have biomarkers that reflect disease pathogenesis accurately. Readily measurable biomarkers, especially in peripheral blood, would be key tools for clinical trials and studies of disease heterogeneity.

The most useful chronic lung disease biomarkers would be proteins, metabolites, or gene expression measurements in peripheral blood. Defining useful peripheral blood biomarkers that reflect lung disease pathogenesis will require validation that the lung disease process can be captured in peripheral blood measurements.

Chest CT scans provide anatomical information on disease pattern and severity that cannot be readily obtained otherwise. These imaging studies could be essential in reclassifying chronic lung diseases more effectively and in assessing disease progression more accurately.

The increasing use of chest CT scans for lung cancer screening will provide a large number of imaging studies that could transform pulmonary research in multiple chronic lung diseases. However, the images will need to be appropriately collected and analyzed.

No single Omics data type is likely to adequately describe the pathogenesis and heterogeneity of chronic lung diseases including COPD, asthma, and IPF. However, integration of these data types using systems biology and network approaches could transform the diagnosis, prognosis, and treatment of these chronic lung diseases.

The availability of multiple Omics data at fairly reasonable costs provides unique opportunities for multiple Omics research.

Better diagnostic criteria as well as biomarkers will allow for efficient targeting of specific therapies for ACOS, such as biologic therapies developed for asthma.

Since ACOS subjects are usually excluded from COPD or asthma trials, this will require identification of study populations that did not exclude ACOS and/or enrollment of ACOS subjects into a new study.

Detailed, high quality epidemiology of the major chronic lung diseases is seriously lacking. Very few cohorts of subjects at risk for or with chronic lung diseases have been established and as a result human data for understanding risk elements that determine disease progression and the development of new treatments for chronic lung diseases is substantially behind other fields. For example, COPD has become the third leading cause of death and is the only leading cause of death and disability that has increased in frequency consistently over the past several decades.

Multiple cohorts of Chronic Lung Diseases need to be established and support maintained for a large portion of the life of the cohort subjects in order to acquire the type of human data needed to address this challenge. An example of this challenge is that we know that GOLD 3 and GOLD 4 subjects have major disability and a markedly increased death rate, yet we know little about the elements that cause or are associated with risk of a GOLD 2 subject to progress to a GOLD 3 or GOLD 4 state.

If we could develop less costly and time consuming cell and animal models of COPD that reflect meaningful subphenotypes, we would be able to not only probe basic mechanism but also have reliable test platforms for candidate therapies.
There is typically a major obstacle between the acquisition of big data from observational disease cohorts, often broad but superficial, and the translation of these findings to basic discovery efforts. The clinical researchers speak a different language than the basic investigators and traversing this chasm with grant enticements might prove helpful.

This would require some suspension of the classic mechanistic, hypothesis driven proposals to develop these research tools.
There would need to be some reconstruction of study sections to permit these combined clinical-basic grants. The translational PPG was in keeping with this but should be reinforced with smaller grant programs such as RO1 level grants.

Modest sized efficacy trials demonstrate substantial health benefits, that wane as Pulmonary rehabilitation is discontinued. We need to test the health and resource implications of "chronic" (e.g., 12 or 24 mos) pulmonary rehabilitation. Such information will benefit health systems seeking to implement care models for high-risk, costly, patients - patients with COPD are of increasing interest to health systems. Such a comparative effectiveness trial should also involve behavioral interventions to promote self-management and involve caregivers.

Funding of core facilities that could both provide support for researchers wishing to study COPD, and the development of efficient research models as well as models of chronic bronchitis would be a major advance for screening for treatments of COPD.

Current technology is well established for exposure of small animals to combustible tobacco smoker. However there remains to be developed standardized exposures to e-Cigarettes and Biomass fuels.

Prevention programs in COPD either target smoking or those with established disease. Better understanding the factors that lead to the development of COPD (both in ever and never smokers) is critical to improved disease prevention.

We need to revisit long term studies in novel ways- and look at new cohorts. Better biomarkers need to be developed.

It is entirely possible and actually likely that several diseases manifesting in different organ systems may have shared pathobiological mechanisms. This could be the case of systemic inflammation or abnormal repair, precipitated by interaction with external agents such as pollution or smoking. This would manifest as different diseases affecting different organ systems (as could be the case of COPD and Lung Cancer) using today's taxonomy.
As it stands (taking the COPD Lung Cancer example) each is treated differently and actually strategically and clinically, they are handled as separate entitites. In all reality, if we can identify the diseases that share common pathogenetic mechanism, it is likely that we can develop common biomarker profiles that will detect disease predisposition so that early intervention can be planned.
In addition and equally important, once common co-morbidities can be grouped by pathobiology, plans can be developed by the medical establishment including health authorities to develop common approaches rather than the disjointed separate specialties that today handle each of the different organ systems.
Finally, the potential of aggregation of diseases into common pathobiological fields can reduce health care cost by integrating fields and voiding dispersion of resources.

It is entirely possible to use large throughput data analysis such as system network analysis to determine in a hypothesis free environment, what is the relationship amongst diseases. This analysis, that can be facilitated by the availability of electronic medical records can provide a first glance evidence of commonality amongst certain diseases.
This can be validated in other cohorts and a plan for profiling a representative sample of those cohorts in order to determine their proteomic and metabolomics profile. This will provide insight into the mechanisms responsible for the expression of the diseases and can lead to translational research aimed at identifying the mechanisms for the generation of the syndrome and potential therapeutic targets.
Once proven correct, it will be possible to identify and treat several diseases simultaneously with targeted therapy once appropriate trials have been completed.
The project here presented is already feasible and likely to offer new roads leading to a better taxonomy, identification and treatment of what now represents a puzzle of different pieces poorly interlocked.
Given the magnitude of the population that is and will be even more affected by multiple chronic diseases, this is a field that is ready for prime research efforts.

COPD is chronic and presently incurable. Although it sickens and disables nearly 30 million Americans, and kills 140,000 of them each year, the only "cure" is a lung transplant. Due to the scarcity of organ donors and the requirements that lungs be removed from the donor in a hospital setting, only about 1,400 lung transplants are performed in the Unites States each year. Unfortunately, transplants are fraught with complications, side effects, and potential rejections, and on the average, add only about 5 years to the life of the recipient. The best potential solution lies with the stem cell and lung regeneration research that is presently occurring at a few centers around the country. Ideally, the re-engineered lungs would be composed of the patient's own stem cells, eliminating a great many of the current transplant issues.

Research is presently in process on construction or reconstruction of human organs. There has been success in creating some of the simpler organs, such as the esophagus and bladder, and a Medical Center in Galveston has implanted re-engineered lung is a pig. As of my latest conversation with the lead Doctor on the project, results so far are promising.
There is general agreement among the researchers with whom I have communicated that we are between 5 and 20 years away from human trials of re-generated lungs using the patient's own stem cells, but more funding means more research which means more possibilities of the saving of lives.