Science and Law
15th September 2016

The Future of Asbestos Litigation – Linking Genomic Science with Rigorous Exposure Assessment

We have been highly focused on the importance of genomic data related to MM and other lung disease in the context of asbestos exposure. Indeed, as we discussed in a recent post, we believe that genomic data is likely to transform the landscape related to toxic torts generally, and related to asbestos litigation specifically. Specifically, genomic techniques may help litigators determine when lung disease is related to a particular exposure or not.

The Future of Asbestos Litigation – Linking Genomic Science with Rigorous Exposure Assessment

The vast majority of malignant mesothelioma (MM) cases are asbestos related, yet the majority of individuals exposed to asbestos (even relatively high doses of amphibole asbestos fibers) do not develop MM. Many have concluded from this observation that there may be some genetic factor or factors that make some individuals more prone to mesothelioma than others — perhaps even predestined to developing MM, even in the absence of asbestos exposure.

We have been highly focused on the importance of genomic data related to MM and other lung disease in the context of asbestos exposure. Indeed, as we discussed in a recent post, we believe that genomic data is likely to transform the landscape related to toxic torts generally, and related to asbestos litigation specifically. Specifically, genomic techniques may help litigators determine when lung disease is related to a particular exposure or not.

However, good genomic data is only part of the answer. The only way to reliably and effectively relate genomic factors to the role of asbestos in lung disease is to couple the collection of good genomic data with rigorous exposure assessment. The literature in this regard is disturbingly lacking.

In our view, the relevant literature appears to cluster into the following three categories:

  1. Rigorous Genomic Assessment with Limited or Poor Exposure Assessment;
  2. Rigorous Exposure Assessment with No Genomic Analysis
  3. Poor Exposure Assessment Studies

We describe below a representative sampling of recent studies in these categories.

Rigorous Genomic Assessment with Limited or Poor Exposure Assessment

Some of the best studies rigorously assessing the role of genomics in relationship to MM and lung cancer are genome-wide association studies (GWAS). There are five basic steps to a GWAS:

  1. Recruit large numbers of subjects from at least 2 groups: people with disease and people without disease
  2. Scan genetic markers across complete sets of DNA (genomes) of large number of subjects
  3. Identify genetic variations in two or more groups of participants (disease and controls)
  4. Explore genetic associations between the disease state and/or exposure parameters using complex statistical techniques
  5. Predict regions of the human genome where the disease-causing problem resides

Because GWAS’ are, by their very nature correlational, the associated variants themselves may not directly cause the disease. Rather, the studies assess associations between various genomic factors and disease states. Additional experimental studies (e.g., knock-out mouse studies) can then be designed to test whether the associations are causal.

To date, we are aware of 4 GWAS’ assessing asbestos-related disease: 3 examined MM and one examined lung cancer. These studies are summarized in the chart below.

Author, YearArticle TitleDisease Examined
Cadby, 2013A genome-wide association study for malignant mesothelioma riskMesothelioma
Matullo, 2013Genetic variants associated with increased risk of malignant pleural mesothelioma: a genome-wide association studyMesothelioma
Tunesi, 2015Gene–asbestos interaction in malignant pleural mesothelioma susceptibilityMesothelioma
Liu, 2015Genome-wide Gene–Asbestos Exposure Interaction Association Study Identifies a Common Susceptibility Variant on 22q13.31 Associated with Lung Cancer RiskLung Cancer

 

These studies provide critical information about the role of genetic patterns and specific mutations (including BAP1) that could be related to the risk of asbestos-induced MM and asbestos-induced lung cancer.

Importantly, however, none of these studies performed a rigorous assessment of asbestos exposure. Specifically, some studies relied on self-report techniques while others relied on anecdotal, unsubstantiated methods to estimate exposure. Such methods cannot provide accurate or reliable conclusions about the role of specific genomic patterns in asbestos-induced lung disease. Such information may have been possible had rigorous exposure assessment tools been utilized (see below).

Rigorous Exposure Assessment with No Genomic Analysis

In late 2015, Gilhman and colleagues published a study that calculated lifetime MM risk in individuals with different levels of exposure to different forms of asbestos. These investigators utilized transmission electron microscopy (TEM) analysis to assess fiber types and counting of asbestos fibers. This method provides rigorous exposure assessment and allows for a reliable analysis of the relationship between fiber burden and risk of MM and lung cancer. Importantly, Gilham and colleagues make a point in their discussion of discussing the importance of generating estimates of “spontaneous mesothelioma unrelated to asbestos,” which they argue is ignored in their modeling.

Similar to the Gilham study, Victor Roggli’s group recently performed lung fiber burden analysis from a series of MM cases (Kraynie et al., 2016; and de Ridder at al., 2016). They used a rigorous methodology for fiber analysis, which included both scanning electron microscopy (SEM) for fiber characterization and energy dispersive x-ray analysis (EDXA) for fiber type analysis. They reported on the patient characteristics for their asbestos-related and their non-asbestos-related cases, showing important differences between the two groups.

All three of these recent investigations made important observations about the asbestos fiber burden in their various cases as well as observations about the rate of spontaneous (background) MM rates. However, none of these studies performed any testing for genomic patterns. This is unfortunate because such testing might have allowed them to find important genetic correlates of individuals with little to no asbestos fiber burden – i.e., background or spontaneous MM rates.

Poor Exposure Assessment

Finally, there are other studies that attempt to draw conclusions about the importance of environmental asbestos exposure without any proper exposure assessment. One recent example is a study by Ferrante and colleagues that attempted to generate information related to whether individuals were occupationally or non-occupational exposure to asbestos using a case control design. However, these investigators estimated asbestos exposure using occupational matrices and so-called “experienced raters.” No objective SEM or EDXA techniques were used to estimate asbestos exposure.

Thus, in this study, not only were genomic data absent from the analysis, but exposure assessments were performed using extremely subjective and unreliable techniques.

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