Polymorphisms in brain cholesterol homeostasis pathway as biomarkers for Alzheimer's Disease: meta‐analyses of clinical evidences

TL;DR

This study identifies genetic variations in cholesterol-related genes that are linked to Alzheimer's disease risk, suggesting potential biomarkers for early detection.

Contribution

The study provides new evidence linking specific SNPs in cholesterol homeostasis genes to Alzheimer's disease risk through meta-analysis.

Findings

SNP rs3846662 (HMGCR) showed increased AD risk with an OR of 1.16.

SNP rs11136000 (CLU) was associated with AD risk (OR = 1.15) with low heterogeneity.

SNP rs754203 (CYP46A1) and rs3851179 (PICALM) showed significant associations with AD risk.

Abstract

Alzheimer's disease (AD) is a neurodegenerative condition marked by memory loss, cognitive decline, and eventually motor and behavioural dysfunction. Most AD drug trials have failed due to the lack of early intervention, which is crucial for treatment effectiveness. Though early diagnosis remains challenging owing to blood‐brain barrier, blood‐based biomarkers are being explored due to their non‐invasive nature. Genes involved in cholesterol and lipid metabolism, such as APOE, APOJ, ABCA7, and SORL1, have also been observed to increase AD risk.

Clinical studies of polymorphisms in cholesterol homeostasis pathway involving participants clinically diagnosed with Alzheimer's Disease of any form as per set criteria of diagnosis for AD were included after comprehensive search across PubMed, Embase, Scopus and Web of Science. Independent reviewers extracted data from the included studies which included information like general information, participants, study methods, polymorphisms studied, outcomes, results, conclusion, etc. Any discrepancies or doubts was resolved by a third reviewer.

A total of 1870 studies were identified based on the designed search strategy, which reduced to 216 after removal of duplicates, with 45 studies considered suitable for the final meta‐analyses. The risk of AD was significantly associated in random effect model for SNP rs3846662 (HMGCR; OR = 1.16, 95% CI = 0.99, 1.35, I2 = 59%, p = 0.06), rs11136000 (CLU; OR = 1.15, 95% CI = 1.08, 1.22, I2 = 0%, p = 0.83), rs754203 (CYP46A1; OR = 1.10, 95% CI = 0.92, 1.33, I2 = 87%, p < 0.01), and rs3851179 (PICALM; OR = 1.18, 95% CI = 1.05, 1.33, I2 = 77%, p < 0.01).

The selected SNPs were found to be significantly associated with the risk of AD, with risk alleles for rs3846662, rs11136000, rs754203, and rs3851179 being G, C, T, C alleles respectively with an OR of 1.16, 1.15, 1.10, and 1.18 respectively. Therefore, these can be considered to be AD biomarkers.

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