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Supplementary Material for: Multifactorial Analysis of a Biomarker Pool for Alzheimer Disease Risk in a North Indian Population
<p><b><i>Background:</i></b> Alzheimer disease (AD) is a progressive
neurodegenerative disease with a complex multifactorial etiology. Here,
we aim to identify a biomarker pool comprised of genetic variants and
blood biomarkers as predictor of AD risk. <b><i>Methods:</i></b> We
performed a case-control study involving 108 cases and 159 non-demented
healthy controls to examine the association of multiple biomarkers with
AD risk. <b><i>Results:</i></b> The <i>APOE</i> genotyping revealed that ε4 allele frequency was significantly high (<i>p</i> value = 0.0001, OR = 2.66, 95% CI 1.58-4.46) in AD as compared to controls, whereas ε2 (<i>p</i>
= 0.0430, OR = 0.29, CI 0.07-1.10) was overrepresented in controls. In
biochemical assays, significant differences in levels of total copper,
free copper, zinc, copper/zinc ratio, iron, epidermal growth factor
receptor (EGFR), leptin, and albumin were also observed. The AD risk
score (ADRS) as a linear combination of 6 candidate markers involving
age, education status, <i>APOE</i> ε4 allele, levels of iron, Cu/Zn
ratio, and EGFR was created using stepwise linear discriminant analysis.
The area under the ROC curve of the ADRS panel for predicting AD risk
was significantly high (AUC = 0.84, <i>p</i> < 0.0001, 95% CI 0.78-0.89, sensitivity = 70.0%, specificity = 83.8%) compared to individual parameters. <b><i>Conclusion:</i></b>
These findings support the multifactorial etiology of AD and
demonstrate the ability of a panel involving 6 biomarkers to
discriminate AD cases from non-demented healthy controls.</p