Appendix e-1
Rationale
Given limitations to the MeDi scoring system we used (which nonetheless was validated in several longitudinal studies and remains the most widely used), we performed a sensitivity analysis to test whether: 1) the results would hold after restricting analysis to those in the lower and upper end of the MeDi spectrum; and 2) whether a different MeDi scoring system would influence the results.
Methods
First, we restricted the models to participants who were on the lower (MeDi score 1-3) or upper end (MeDi score 6-9) of the MeDi score distribution. We focused on PiB and FDG SUVR measures extracted from the clusters of voxels reaching peak significance in the longitudinal analysis looking at group by time interaction effects. Cluster
description and corresponding anatomical location is found in Table e-2 and Table e-3.
For each modality, SUVR measures in each cluster were averaged using a volume-of- interest (VOI) approach. We used repeated measures GLM analyses with 2 levels to test for longitudinal VOI differences between those on the higher end (MeDihigh) and those on the lower end (MeDilow) at p<.05. Age, sex, ApoE status, vascular risk factors, and time to follow-up were examined as covariates as in the main analysis.
Secondly, we sought to re-examine MeDi adherence in our participants using the scoring system developed by Sofi et al 35. This system has the advantage of being sample-independent and was developed based on meta-analysis of descriptive data from the literature on over 4 million subjects.
The same average intake data (g/day) for each of the 30 food groups used in the main analysis was used to derive literature-based MeDi scores in our participants. We calculated daily gram intake for nine food categories: dairy, meat, fruit, vegetables, legumes, cereals, fish, olive oil, and alcohol.
Intake of each food group typical of the MeDi (fruit, vegetables, cereals, legumes and fish) was used to define three categories relative to food group-specific cutoffs. We then gave 2 points to the highest category of consumption, 1 point for the middle category and 0 point for the lowest category, per food. Conversely, for food groups not typical of the MeDi (meat and meat products, dairy products) we gave 2 points for the lowest category, 1 point for the middle category and 0 point for the highest category of
consumption. For alcohol, we used the categories related to the alcohol unit (1 alcohol unit=12 g of alcohol), by giving 2 points to the middle category (1–2 alcohol units/d), 1 point to the lowest category (<1 alcohol unit/d) and 0 point to the highest category of consumption (>2 alcohol units/d). For olive oil, we gave 2 points for regular use; 1 point for frequent use; 0 point for occasional use. The final adherence score ranges from 0 point (lowest adherence) to 18 points (highest adherence). Since no relevant
differences for proposed food categories across men and women were obtained, a single score was computed for both sexes 35. These scores were then normalized to a 0-9 point scale by dividing each score by 2, so as to bring the two MeDi score
distributions on the same scale. The mean and median values of the literature-based MeDi scores were the same (score=3.9 and 4, respectively). As such, we dichotomized participants into higher vs. lower adherence using a MeDi score of 4 as the cutoff.
We then conducted a reliability analysis to calculate the percent discordance and compare the two MeDi scores across subjects using Cronbach’s alpha statistics and intra-class correlation coefficients (ICC), at p<.05.
Finally, we used repeated measures GLMs with 2 levels to test for longitudinal VOI differences between the new MeDi- and MeDi+ groups at p<.05. Cluster description and corresponding anatomical location is found in Table e-2 and Table e-3. Age, sex, ApoE status, vascular risk factors, and time to follow-up were examined as covariates.
Results
1. Restricting the models to participants on the lower vs. upper end of the MeDi score distribution.
A total of 22 participants had MeDi scores of 4 and 5. The remaining 48 participants were examined in this analysis, including 26 participants in the MeDilow (MeDi score 1-3) and 22 participants in the MeDihigh group (MeDi score 6-9).
As shown in Table 1, groups were comparable for demographic characteristics. The MeDilow group showed a higher percentage of participants with hypertension, and higher BMI as compared to the MeDihigh group (p<.05)
Table 1. clinical characteristics of MeDilow and MeDihigh groups.
MeDilow MeDihigh
N 26 22
Age, years, range 50(8), 33-60 49(8), 31-60
Gender, % female 54% 64%
Education, y 16(3) 16(2)
Family history of AD, % positive 73% 74%
APOE-4 status, % positive 39% 22%
Ethnicity, % White 88% 79%
Time to follow-up, years, range 2.4(0.4), 2-3 2.6(0.5), 2-3.5
Hypertension, % positive 22% 9%*
BMI 26(6) 19(7)*
QUICKI scores 0.161(0.017) 0.164(0.011)
Values are means (SD) unless otherwise specified; *p<.05
For PiB measures, none of the confounds were significant predictors of change in PiB uptake. With and without adjusting for confounds, significant time by MeDi group interaction effects were observed at p<.001, with the MeDilow group showing higher rates of PiB deposition than the the MeDihigh group (Figure 1A). Quantitatively, PiB uptake increased by an average of 0.020 SUVR per year (SE=0.027) in the MeDilow
group, corresponding to an average increase from baseline of 3.9%. PiB uptake did not show significant increases in the MeDihigh group, with an average change of 0.002 SUVR per year (SE=0.028), corresponding to <1% increase from baseline.
Figure 1. Longitudinal PiB and FDG effects in MeDilow vs. MeDihigh groups.
A) PiB changes in MeDilow vs. MeDihigh groups: fully adjusted measures. SUVR = standardized uptake value ratios to cerebellar uptake (unitless).
B) FDG changes in MeDilow vs. MeDihigh groups: sex- and ApoE-adjusted measures. SUVR = standardized uptake value ratios to global activity (unitless).
For FDG measures, sex and ApoE status were associated with change in FDG uptake (p<.05). Women showed higher rates of CMRglc decline vs. men (p=0.04), and so did ApoE4 carriers vs. non-carriers (p=0.02). None of the other confounds showed
significant associations with CMRglc changes. Adjusting for sex and ApoE, time by MeDi group interaction effects were observed (p=.035), with the MeDilow group showing higher rates of CMRglc declines than the MeDihigh group (Figure 1B). CMRglc declined by an average of 0.028 SUVR per year (SE=0.049) in the MeDilow group, corresponding to an average CMRglc decline from baseline of 3.83% per year. CMRglc did not show significant declines in the MeDihigh group, with an average change of 0.018 SUVR per year (SE=0.054), corresponding to <1% change per year from baseline.
2. Assessing the reliability of the MeDi scoring system.
Using a literature-based MeDi scoring system (normalized to a 0-9 point scale), 15%
participants scored <3, 13% scored 3, 33% scored 3.1-4, 34% scored 4.1-5, 13%
scored 5.1-6, and 3% scored >6.1. The mean score was 3.9, the median score was 4, SD=1.1.
As compared to the original MeDi scoring system, literature-based MeDi scores yielded an increased percentage of MeDi- participants. Of the 70 participants examined, 43
were classified as MeDi- (61%) and 27 (49%) were classified as MeDi+. This was due to the fact that 14 participants (20%) were classified differently using the two systems, including 10 MeDi+ subjects that were reclassified as MeDi- using literature-based scores, and 4 MeDi- subjects that were reclassified as MeDi+ (Figure 2).The two methods were consistent in classifying the remaining 56 subjects (80%).
Figure 2. Comparison of the two MeDi scoring systems.
Scatterplots of MeDi scores obtained with our original system and with a literature-based scoring system displayed on the same 0-9 points scale.
As evident in Figure 2, across subjects, the MeDi scores were well correlated (r=0.501) and showed good reliability with ICC=0.583 (95% confidence interval=.329-.741) and p<.001. Likewise, the MeDi groups obtained with different methods were well correlated (r=0.580) and showed good reliability with ICC=0.734 (95% confidence interval=.573- .835) and p<.001.
Therefore, we repeated all longitudinal analyses after removing the 14 subjects with conflicting MeDi classifications. The remaining 56 participants were examined in this analysis, including 33 participants in the MeDi- group and 23 participants in the MeDi- group.
As shown in Table 2, groups were comparable for demographic characteristics. The MeDilow group showed non-significant trends towards a higher percentage of
participants with hypertension, and towards higher BMI as compared to the MeDihigh
group (p<.14).
Table 2. clinical characteristics of MeDi- and MeDi+ groups.
MeDi- MeDi+
N 33 23
Age, years, range 52(6), 40-60 50(8), 31-60
Gender, % female 67% 70%
Education, y 16(2) 17(2)
Family history of AD, % positive 70% 65%
APOE-4 status, % positive 42% 39%
Ethnicity, % White 85% 78%
Time to follow-up, years, range 2.5(0.4), 2-3 2.6(0.5), 2-3.5
Hypertension, % positive 17% 7%
BMI 26(5) 20(5)
QUICKI scores 0.168(0.020) 0.162(0.014)
Values are mean (SD) unless otherwise specified; *p<.05
For PiB measures, none of the confounds were significant predictors of change in PiB uptake. With and without adjusting for confounds, time by MeDi group interaction effects were observed at p<.001, with the MeDi- group showing higher rates of PiB deposition than the MeDi+ group (Figure 3A). Quantitatively, PiB uptake increased by an average of 0.034 SUVR per year (SE=0.034) in the MeDi- group, corresponding to an average increase from baseline of 6.9%. PiB uptake did not show significant increases in the MeDi+ group, with an average change of 0.005 SUVR per year (SE=0.033),
corresponding to <1% increase from baseline.
Figure 3. Longitudinal PiB and FDG effects in MeDi- vs. MeDi+ groups after removing the 14 participants with discordant MeDi classification vs. literature-based scores.
A) PiB changes in MeDi- vs. MeDi+ groups: fully adjusted measures. SUVR = standardized uptake value ratios to cerebellar uptake (unitless).
B) FDG changes in MeDi- vs. MeDi+ groups: fully adjusted measures. SUVR = standardized uptake value ratios to global activity (unitless).
For FDG measures, none of the confounds were significant predictors of change in FDG uptake. With and without adjusting for confounds, time by MeDi group interaction effects were observed (p<.017), with the MeDi- group showing higher rates of CMRglc declines than the MeDi+ group (Figure 3B). CMRglc declined by an average of 0.058 SUVR per year (SE=0.050) in the MeDilow group, corresponding to an average CMRglc decline from baseline of 7.4%. CMRglc did not show significant declines in the MeDihigh group, with an average change of 0.018 SUVR per year (SE=0.054), corresponding to an average decline of 1.3% from baseline.
Overall, albeit limited by the smaller sample size, these results indicate that the longitudinal effects reported in the main analysis still hold after restricting analysis to participants in the lower and upper end of the MeDi score distribution; and after restricting analysis to those with consistent literature-based classifications.
