In a recent paper by Perry et al, Stratifying Type 2
Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and
Enrichment for Risk Variants in Lean Compared to Obese Cases, the authors have
performed a genome wide study identifying genes that a prevalent in non-obese
versus obese Type 2 diabetics[1] (T2). We have argued
previously that the predominant number of T2 cases is driven by obesity. The
authors demonstrate non obese T2 and then through a genome wide analysis, GWA,
identify the putative genes.
We summarize their results and we then present several
questions regarding the usefulness of the results.
The authors start by stating:
Individuals with Type 2 diabetes (T2D) can present with
variable clinical characteristics. It is well known that obesity is a major
risk factor for type 2 diabetes, yet patients can vary considerably—there are
many lean diabetes patients and many overweight people without diabetes. We
hypothesized that the genetic predisposition to the disease may be different in
lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2).
Specifically, as lean T2D patients had lower risk than obese patients, they
must have been more genetically susceptible. Using genetic data from multiple
genome-wide association studies, we tested genetic markers across the genome in
2,112 lean type 2 diabetes cases (BMI<25 kg/m2), 4,123 obese
cases (BMI≥30 kg/m2), and 54,412 healthy controls. We confirmed our
results in an additional 2,881 lean cases, 8,702 obese cases, and 18,957
healthy controls.
Using these data we found differences in genetic enrichment
between lean and obese cases, supporting our original hypothesis. We also
searched for genetic variants that may be risk factors only in lean or obese
patients and found two novel gene regions not previously reported in European
individuals. These findings may influence future study design for type 2
diabetes and provide further insight into the biology of the disease.
They then continue:
Genome-wide association (GWA) studies have identified ~50
independent loci robustly associated with type 2 diabetes. These studies have
highlighted new candidate pathways involved in the disease, identified overlap
with monogenic forms of the disease, and provided genetic links with correlated
phenotypes.
The GWA studies of type 2 diabetes have not so far
provided a greatly improved understanding of the clinical heterogeneity of the
disease. Type 2 diabetes cases vary appreciably in their clinical
characteristics, particularly age of diagnosis and body mass index (BMI). There
is also a group of patients who may present with evidence of an autoimmune
component to their diabetes, but who are not insulin dependent. In contrast,
the identification of the genetic component to monogenic forms of diabetes has
often explained the clinical heterogeneity observed.
Previous studies have provided some evidence of genetic
heterogeneity between non-obese and obese type 2 diabetic cases. For example,
the variant with the strongest effect on type 2 diabetes risk, in TCF7L2, has a stronger effect in non-obese cases (odds
ratio = 1.53 [0.37–1.71] compared to obese cases (OR = 1.21 [1.09–1.35]). The
effect of FTO variation on type 2 diabetes risk depends on how
cases and controls are ascertained by BMI status, but this was expected given FTO's known primary effect on BMI. In the most recent
GWA studies of type 2 diabetes, risk variants tended to have stronger effects
in non-obese compared to obese individuals – of 30 loci examined, 23 showed
stronger associations in non-obese compared to obese individuals.
The authors conclude:
In conclusion, we report associations with the LAMA1 and
HMG20A
(not previously associated at genome-wide significance in Europeans)
gene regions with type 2 diabetes risk. We have demonstrated that lean diabetic
cases are enriched for known type 2 diabetes risk alleles compared to obese
cases. This enrichment is consistent with the observation that many of the
variants with the strongest effects on diabetes are associated with reduced
beta cell function [1]. At the opposite end of the spectrum, obese cases presumably
need fewer diabetes risk variants to push them towards diabetes, as they are
already under strain from the physiological impact of obesity and insulin
resistance. These data suggest a disease model where type 2 diabetes cases lie
across a continuous distribution with regards to genetic/environmental risk,
and betacell dysfunction versus insulin resistance aetiologies.
The conclusion is that lean or low BMI Pt with T2 has a
genetic predisposition to the disorder. This is consistent with what we have
been stating in our prior analyses but it fails to demonstrate what percent of
the total population has such a genetic failure.
This report raises several questions:
1. Not apparent is the percent of Type 2 patients who have
low BMI, <25, and the percent who have high, >30. Namely what is the
incidence and prevalence of T2 in those groups? One would suspect based on
generally available data that the percent of high BMI individuals having T2 is
high and those with low BMI have a low percent incidence and prevalence.
2. With the genes identified in the GWA in the low BMI
group, what is their function? Namely the authors should have explored the
intra-cellular and intercellular pathways and their metabolic effects. Just
have a gene present does not mean causality. Causality is an essential element.
Presence is at best correlative.
3. There is the issue of somatic presence versus germline
presence. Namely if the Pt with low BMI and gene variants, were these somatic,
namely did they have this forever and if so why did they come down with T2 at
some point. If not somatic, and germline then what process caused the gene
mutation. What caused the gene variant? This is a key question. Also if somatic
why did it take so long to present?
4. How do we define T2? I suspect the authors do so via an
HbA1c measure. They seem to allude to such by taking measurements of HbA1c as
well as 2 hour glucose as one would do in a classic glucose tolerance test
using a 75g glucose bolus. However, I found it difficult to identify the
specific definition used in the document itself.
5. Notwithstanding, there is the annoying mass balance equation, input-output=net accumulation! How do these genes change this? Do they result in lowered metabolic expenditures? But with low BMI this is not an issue. Thus are we looking at different T2 disease states? The low BMI T2 patient has excess blood glucose due to lower uptake? lower insulin secretion? Why? What do these genes do to achieve that abnormality?
We seem left with more questions than answers. This is often the case with excess data and no paradigms to validate them.
5. Notwithstanding, there is the annoying mass balance equation, input-output=net accumulation! How do these genes change this? Do they result in lowered metabolic expenditures? But with low BMI this is not an issue. Thus are we looking at different T2 disease states? The low BMI T2 patient has excess blood glucose due to lower uptake? lower insulin secretion? Why? What do these genes do to achieve that abnormality?
We seem left with more questions than answers. This is often the case with excess data and no paradigms to validate them.
Reference
Perry, J., et al, Stratifying Type 2 Diabetes Cases by BMI
Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean
Compared to Obese Cases, PLOS Genetics, May 2012 | Volume 8 | Issue 5 |
e1002741.
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