Implementing food-based dietary guidelines for - United Nations ...

Setting upper levels for nutrient risk assessment
not been fully validated, there is probably a need for
research to develop and validate markers appropriate
for this nutrient risk assessment strategy.
A continuum as a basis for identifying adverse health
effects for this strategy in nutrient hazard identification
and characterization is illustrated in figure 3 [16].
Steps 4–7 in the figure reflect the increasing severity
of adverse health effects; the workshop [1] agreed that
phenomena occurring at level 3, namely, at levels of
intake that were assumed to be not far in excess of the
homeostatic range, could indeed be surrogates, or predictive
markers, of adverse health effects. Furthermore,
it concluded that
when data are available, the optimal endpoint for use
in setting a UL would be an effect at step 3 and possibly
step 2, with steps 4–7 reflective of clinical phenomena.
Step 2 may be applicable in some cases in which sufficient
information is available to suggest that changes
outside the homeostatic range that occur without known
sequelae would be relevant as surrogates for an adverse
health effect [1].
This is emphasized in figure 3 by showing, against
the background of the ranked effects, a hypothetical
cascade of markers or effects arising from exceeding
a safe level, or conceptual UL, of intake. These figures
show how a critical control point analytical approach
to available information could be used in nutrient
hazard identification and characterization; it provides
a strategic structure for an evidence-based systematic
review and categorization of the data and potential
markers and for the determination of gaps in insight
of the pathophysiology and uncertainty.
The use of such markers would be an important
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FIG. 3. The range and cascade of effects and of markers:
opportunities for identifying critical markers of adverse
health effects. Each circle represents a hypothetical marker,
and the dark circle represents the marker at a critical point
for the subsequent cascade of adverse health effects. The
spectrum of health effects is from Renwick et al. [16]
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innovation in nutrient risk assessment. Their introduction
would be amenable to the NOAEL, BMD, and
categorical regression approaches to hazard characterization.
Using markers of earlier effects of excess intakes
would be expected to increase the size of the database
for hazard identification and characterization. They
probably will not improve the quality of the database.
In particular, the use of markers at steps 2 and 3 of
figure 3 needs to be backed by confidence in their
validity and quality.
With these issues in mind, the workshop emphasized
that biomarkers comprised two classes: “factors” that
represent “an event…directly involved in the process
of interest and are causally associated with the adverse
health effect”[1] and “indicators” that represent correlated
or associated effects and events that have not been
shown to be part of the causal pathway. Thus, a biomarker
that is part of the causal pathway can be regarded as
being “predictive” of an adverse health effect; however,
some “predictive” biomarkers might not be causal. In
this regard, the workshop appreciated that biomarkers
can be diagnostic in that they indicate adverse
health effects relevant to nutrient risk assessment, for
example, liver damage, but as such these could still be
categorized as factors or indicators according to their
perceived role in the pathogeneses involved. Thus,
nutrient risk assessors may have available a portfolio of
biomarkers that could be used as surrogates for adverse
health effects, in that such markers can be typified as
being causally associated with the adverse health effect;
diagnostic of the adverse health effect; and predictive
of, but not causally associated with, the adverse health
effect [1].
Overall markers, whether they are functional, chemical,
or morphological, would need to meet the quality
criteria of being biologically valid and reproducible, of
known specificity and sensitivity, and methodologically
or analytically valid and reproducible. A recent
consideration of the use of markers as surrogate endpoints
in the justification of claims of reduced risk of
disease is particularly relevant to these issues [17] and
emphasizes the need for markers to be ethically and
practically feasible if they are to be used in systematic
studies in populations. The workshop appreciated that
these criteria provided a basis for characterizing the
uncertainty and variability associated with markers at
any stage in the above ranking, but particularly those
at stages 2 and 3, where the best chances of improving
the database through human research exist.
Theoretically, a biologically based or metabolic dose–
response model would be applicable to all nutrients
and should or could derive from the compilation and
acquisition of new data on absorption, distribution,
metabolism, and excretion as the basis of information
on biokinetics and biodynamics. In essence, this
resembles the use and derivation of chemical-specific
adjustment factors (CSAFs) to improve the specificity