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. 2024 Mar 27;15(1):2576.
doi: 10.1038/s41467-024-46344-2.

The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease

Affiliations

The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease

Jordi Manuello et al. Nat Commun. .

Abstract

We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer's disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer's and Parkinson's disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide - a proxy for traffic-related air pollution - and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Vulnerable ‘last in, first out’ (LIFO) network of higher-order brain regions that degenerate earlier and faster than the rest of the brain.
Top left, spatial map of the LIFO network (in red-yellow, thresholded at Z > 4 for visualisation) used to extract the loadings from every scanned participant from UK Biobank (n = 39,676). Top right, these LIFO loadings (in arbitrary units) show a strong quadratic association with age in the UK Biobank cohort, i.e. grey matter volume decreases quadratically with older age in these specific regions (R2 = 0.30, P < 2.23 × 10−308; inset: residual scatterplot). Bottom, the vulnerable network appears to encompass areas mainly involved in execution, working memory, and attention (using the BrainMap taxonomy, and with the LIFO brain network thresholded at both Z = 4 and Z = 10, see Supplementary Information).
Fig. 2
Fig. 2. Manhattan plot and regional autosomal association plots for the variants significantly associated genome-wide with the vulnerable ‘last in, first out’ (LIFO) brain network.
Top row, Manhattan plot showing the 7 significant genetic clusters associated with the LIFO brain network (–log10(P) > 7.5). Second and third rows, regional association plots of the top variants for each of the 5 autosomal genetic clusters: rs6540873 on chromosome (Chr) 1 (KCNK2), rs13107325 on Chr4 (SLC39A8), rs2677109 on Chr6 (RUNX2) (as a proxy in high LD R2 = 0.86 with indel 6:45442860_TA_T), rs12146713 on Chr12 (NUAK1), and rs2532395 on Chr17 (MAPT, KANSL1)(highest variant after tri-allelic rs2693333; see Supplementary Data 4 for a complete list of significant variants in this 5th MAPT genetic cluster). Bottom row, regional association plots of the top variants for the two genetic clusters in the pseudo-autosomal region PAR1 of the X chromosome: rs312238 (XG, CD99) and rs2857316 (XG)(UK Biobank has no genotyped variants on the 3’ side). Based on Human Genome build hg19. P-values are derived from a two-sided linear association test.

References

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