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Clustering of anti-GBM disease: clues to an environmental trigger?
Dr Stephen P McAdoo & Prof Charles D Pusey
Renal and Vascular Inflammation Section, Department of Medicine, Imperial College London, London
UK; Vasculitis Clinic, Hammersmith Hospital, Imperial College Healthcare National Health Service
Trust, London UK.
Correspondence: Dr Stephen P. McAdoo, Renal and Vascular Inflammation Section, Department of
Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W112
0NN. Email: [email protected]
Running Title: Clustering of anti-GBM disease
Keywords: Anti-GBM disease; Goodpasture’s syndrome; ANCA; epidemiology and outcomes
Words: 1604; References: 28
Disclosures: The authors declare no financial conflicts of interest related to this work.
Acknowledgements: SPM is in receipt of a National Institute for Health Research (NIHR) Clinical
Lectureship. We acknowledge support of the Imperial NIHR Biomedical Research Centre.
The classical paradigm of autoimmune disease pathogenesis describes the role of an environmental
insult, to a genetically predisposed individual, that results in miscommunication between the innate and
adaptive immune systems, breakdown of tolerance, and the recognition of self-antigens as the target of
a damaging immunological response. This paradigm is perhaps best exemplified by the interaction of
HLA genotype and smoking, in the development of autoantibodies to citrullinated peptides and the
onset of rheumatoid arthritis1. It is assumed that similar pathogenic mechanisms are involved in other
autoimmune diseases, though few are so well delineated as in this example. In anti-GBM disease, the
components of the aberrant adaptive immune response that are involved in disease pathogenesis are
clearly described, such as pathogenic auto-antibodies, directed to a well-defined auto-antigen, supported
by a population of auto-reactive T cells2,3. The putative environmental triggers, however, and how they
interact with the known genetic determinants of disease susceptibility, to initiate this aberrant response,
are not fully understood.
These genetic determinants of anti-GBM disease are increasingly well described. Whilst there has not
been an undirected genetic survey, such as a genome wide association study, perhaps reflecting the
overall rarity of anti-GBM disease, targeted genetic analysis has been informative. Polymorphisms in
certain non-HLA genes, such as those encoding Fcγ receptors, are associated with disease
susceptibility4,5, consistent with the contribution of pathogenic autoantibodies in mediating organ
damage, whereas polymorphisms in COL4A, the gene encoding the target auto-antigen, have been
excluded from playing a significant role6. Better characterised are the HLA associations of anti-GBM
disease, with 80% of patients inheriting an HLA-DR2 haplotype. Genotyping studies have identified a
hierarchy of associations with particular DRB1 alleles: DRB1*1501, DRB1*03 and DRB1*04 are
positively associated with disease, whereas DRB1*01 and DRB1*07 appear to confer a dominantnegative protective effect7. These susceptibility alleles, however, are associated with other autoimmune
diseases (such as multiple sclerosis and Sjogren’s syndrome) and they are common in most populations,
whilst anti-GBM disease remains exceptionally rare, highlighting the importance of other factors,
including environmental exposures, in the development of this specific condition. Previous reports of
‘clustering’ or ‘outbreaks’ of anti-GBM disease8, and of seasonal variations in disease incidence9,
support a role for environmental factors, such as infection, in triggering disease onset, though they are
limited to anecdotal observation. The report of Canney and colleagues in this edition of CJASN is the
first to assess geographical or temporal clustering using formal statistical methods, in a national cohort
of patients10.
In this well-designed study, the authors have systematically identified all anti-GBM disease cases in
Ireland over an 11 year period by screening results from referral immunology laboratories and
interrogating a national renal histopathology database. This has allowed them to define, for the first
time, a national incidence rate for this rare condition. This rate is higher than previous estimates in other
European populations, which, as discussed by the authors, most likely reflects the methodological
inadequacies of previous studies that were prone to ascertainment bias and the inability to accurately
define at-risk populations. It might also reflect the moderate over-representation of the DR2 haplotype
and DRB1 risk alleles in the Irish population11, or perhaps a genuine increase in the frequency of antiGBM disease in recent years compared to historical cohorts.
The study, in addition, has employed variable-window scan-statistic and Bayesian spatial modelling
methods to identify both temporal and geographical clustering of cases, respectively. These formal
statistical methods confirm the prior anecdotal experience of many other authors. Notably, some
differences in disease phenotype were observed in the two clusters. It is striking, for example, that the
temporal cluster had a very high prevalence of positivity for anti-neutrophil cytoplasm antibodies
(ANCA), found in over 70% of patients, particularly in view of the strict diagnostic criteria used by the
investigators that excluded patients who had overt clinical features of vasculitis. Double-positivity for
ANCA and anti-GBM antibodies is a well-recognised phenomenon, with previous studies estimating
that approximately 30% of patients with anti-GBM disease have a concurrent ANCA12, consistent with
overall prevalence reported in the entire Irish cohort. That the temporal cluster had an overrepresentation of ANCA suggests that a different disease mechanism may be acting in these patients,
or as the authors suggest, that the disease may present variably in different sub-populations. This is
perhaps in keeping with other recent reports that have identified ‘atypical’ presentations of anti-GBM
disease, such as those associated with IgG4 anti-GBM antibodies13, or with what might be termed
‘idiopathic linear immunoglobulin deposition’14, and illustrates the challenges in reliably characterising
the full phenotypic spectrum of a very rare disorder.
Of greater significance, the identification of these disease clusters also supports a role for an
environmental trigger in anti-GBM disease. A number of such environmental triggers have been
suggested previously. Perhaps best known is the association of cigarette smoking with the development
of lung haemorrhage15. Inhalation of hydrocarbons has also been associated with anti-GBM disease16,
and an interesting report of identical twins who both developed anti-GBM disease following
hydrocarbon exposure supports a link between genetics and environmental factors17. It is hypothesised
that localised airway inflammation induced by smoking or inhaled hydrocarbons may disrupt the
architecture of the alveolar basement membrane, revealing usually sequestered epitopes in type IV
collagen, and thus permitting access to pathogenic autoantibodies. Whether these factors have a role in
the initiation of the autoimmune response per se, however, is not so clear. A similar process of
‘conformational transition’ of the auto-antigen within the kidney has been suggested to account for the
association of anti-GBM disease with other glomerular lesions (such as ANCA-associated
glomerulonephritis and membranous nephropathy) and lithotripsy for renal stones, that may disrupt the
quaternary structure of glomerular basement membrane18.
These associations with smoking and other specific diseases, however, are not likely to account for the
clustering of diseases that has been confirmed in this study. Some of the early series reported a seasonal
variation in disease incidence, with peaks in spring and early summer which, in the absence of any
reported association with atopy, suggest an infectious trigger9. It is of historical interest that Ernest
Goodpasture’s original description of glomerulonephritis associated with alveolar haemorrhage was in
the context of the influenza outbreak of 1919, though it is not clear whether his patient had genuine
anti-GBM disease19. There are somewhat more recent reports of disease outbreaks associated with
influenza virus, such a series of four cases presenting during an influenza A2 epidemic in the early
1970s, though in these cases confirmatory virologic or serologic evidence of infection was not
demonstrated20. There are a small number of additional, isolated cases where influenza infection was
serologically confirmed, reported in the same era21,22. Other specific infectious associations with antiGBM disease, however, have not been reported, and the precise mechanisms via which infection might
initiate disease are not defined. It is conceivable that non-specific inflammation at the time of respiratory
or systemic infection may result in the release of sequestered epitopes in the lung or kidney, akin to the
mechanisms implicated for smoking in the induction of disease. Alternatively, T or B lymphocytes that
are auto-reactive to GBM antigens (the presence of which are confirmed in healthy individuals23-25) may
undergo ‘bystander activation’ at the time of intercurrent infection, thus initiating anti-GBM disease.
More specific molecular mechanisms may also be at work, and observations in a commoner form of
crescentic glomerulonephritis - that associated with ANCA - may be informative. A variant ANCA
type, directed against LAMP2, a human protein that bears a high degree of homology to FimH, a protein
expressed in fimbriated gram negative bacilli, has been identified in human patients with AAV, and is
purported to arise via a process of molecular mimicry following bacterial infection 26. It has also been
shown that certain Staphylococcus aureus peptides bear high homology to complementary PR3, and it
is thus suggested that anti-PR3 antibodies may arise via a process of idiotype-anti-idiotype interactions
following Staphylococcal infection27. Whilst there are no specific mechanisms suggested for the
infectious induction of anti-GBM antibodies, it is notable that comparable idiotype-anti-idiotype
interactions have recently been described in the induction of experimental anti-GBM disease in a rodent
model28.
The authors of the present study do not comment on the potential infective, occupational or other
environmental exposures that may have initiated disease in their cohort, and exploring these features in
more detail may be informative in the future. In addition, analysis of concurrent patterns of infectious
disease, such as influenza, in the general population during the study period might be considered. It
may also be of interest to determine the pattern of disease in the adjacent six counties of Northern
Ireland, particularly in view of the shared border with the spatial cohort of cases they have described in
Donegal, as this may identify additional cases in the same region, and further opportunity to identify
shared exposures in a larger cohort of cases.
This study is notable for being the first to accurately determine the frequency of anti-GBM disease in
any country, and the authors are to be commended on their collaborative approach, that enabled capture
of systematically identified and strictly defined cases at a national level, and their thoughtful use of
statistical methodology to identify disease clusters over time and by geographical region. The challenge
now is to determine how these data can be utilised to identify putative environmental factors that trigger
disease and may account for these clusters, and how these factors interact with known (or yet to be
identified) genetic determinants to initiate disease. This might then allow the development of early
detection, preventative or more targeted treatment strategies for this rare but potentially devastating
condition, and other comparable renal and autoimmune disorders with a presumed environmental
trigger.
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