April 13, 2024

Genetic and lifestyle factors linked to brain network aging, study reveals

In a recent study published in the journal Nature Communications, researchers determined genetic influences and the impact of modifiable risk factors (MRFs) on a brain network vulnerable to aging, schizophrenia, and Alzheimer’s disease in approximately 40,000 United Kingdom (UK) Biobank participants.

Study: The effects of genetic and modifiable risk factors on brain regions vulnerable to aging and disease. Image credit: Kittyfly/Shutterstock

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Developing strategies to modify risk factors can pave the way for healthy aging, reducing the incidence of dementia. This approach examines a range of factors, including cerebrovascular issues such as high blood pressure, diabetes and obesity, protective actions such as exercise, and lifestyle choices such as alcohol intake. A collective assessment of MRF, including lifestyle and environmental pollution, highlights their potential to influence 40% of global dementia cases. Despite the fixed nature of genetic factors linked to diseases such as Alzheimer’s disease and Parkinson’s disease, brain imaging reveals that certain regions are especially vulnerable to aging and neurodegenerative diseases. More research is crucial to clarify the intricate relationships between genetic predispositions and modifiable lifestyle factors in brain health and the progression of neurodegenerative diseases.

About the study

In the current study, using the UK Biobank imaging cohort, researchers included data from 39,676 participants who underwent T1-weighted structural brain scans. These scans were processed to map gray matter, focusing on identifying a network of brain regions labeled “last in, first out” (LIFO), previously determined to be particularly sensitive to aging. This network, characterized mainly by higher-order brain regions, was analyzed for its unique contribution to brain structure, differentiating it from other regions.

The study followed ethical guidelines, with UK Biobank obtaining the necessary approvals and consent from participants. The researchers investigated 161 MRFs across 15 categories, including those identified by the Lancet Commission as linked to the risk of dementia other than traumatic brain injury. This comprehensive selection aimed to understand the impact of these MRFs on the LIFO network without reducing data complexity.

Statistical analysis began with a genome-wide association study (GWAS) to explore genetic influences, followed by assessment of each MRF’s association with the LIFO network. By adjusting for confounders such as age and sex, the study aimed to identify the specific effects of these MRFs. Additional analysis included a combined model of all significant MRFs to comprehensively assess their unique contributions.

Post hoc analyzes further explored genetic factors, including assessing causality within genetic clusters and performing enrichment analyzes for gene functions. Furthermore, mediation analysis investigated the relationship between the Alzheimer’s disease-associated Microtubule-Associated Protein (MAPT) Tau gene variant and the LIFO network. The study also investigated the genetic overlap between MRFs and the LIFO phenotype, providing insights into potential common genetic pathways.

Study results

In the study, the LIFO brain network, known for its susceptibility to aging, showed a significant quadratic relationship with age, revealing an accelerated decline in gray matter volume in higher-order regions associated with cognitive functions such as execution, working memory and attention. .

Top left, spatial map of the LIFO network (in red-yellow, with threshold of Z > 4 for visualization) used to extract the payloads of each participant scanned from the UK Biobank (n = 39,676).  In the top right, these LIFO loads (in arbitrary units) show a strong quadratic association with age in the UK Biobank cohort, i.e. gray matter volume decreases quadratically with advancing age in these specific regions (R2 = 0.30 , P < 2,23 × 10−308 ; inserção: gráfico de dispersão residual).  No fundo, a rede vulnerável parece abranger áreas envolvidas principalmente na execução, memória de trabalho e atenção (usando a taxonomia BrainMap e com a rede cerebral LIFO com limite em Z = 4 e Z = 10Top left, spatial map of the LIFO network (in red-yellow, with threshold of Z > 4 for visualization) used to extract the payloads of each participant scanned from the UK Biobank (n = 39,676). In the top right, these LIFO loads (in arbitrary units) show a strong quadratic association with age in the UK Biobank cohort, i.e., gray matter volume decreases quadratically with advancing age in these specific regions (Rtwo= 0.30, P < 2.23 × 10−308; inset: residual scatterplot). At bottom, the vulnerable network appears to encompass areas primarily involved in execution, working memory, and attention (using the BrainMap taxonomy and with the LIFO brain network capped at Z = 4 and Z = 10

The study identified genomic associations between the LIFO network and seven genetic clusters, with associations replicated across all clusters. These genetic influences include clusters near genes such as Potassium Two Pore Domain Channel Subfamily K Member 2 (KCNK2), which is involved in neuroprotection and control of inflammation, and Solute Carrier Family 39 Member 8/Zinc Iron Regulator Protein 8 (SLC39A8/ZIP8). , known for its wide range of associations with markers of health and disease. Other notable discoveries include a close variant of Runt-related transcription factor 2 (RUNX2), linked to neurogenesis and Alzheimer’s disease, and a variant of the NUAK family Kinase 1 (NUAK1) associated with schizophrenia and depressive disorders. The MAPT region, implicated in several neurodegenerative diseases, also showed a significant association.

Two genetic clusters on the X chromosome, particularly in the pseudoautosomal region, were also identified. These clusters are related to XG blood group antigens and show associations with several health outcomes, including nitrogen dioxide air pollution, highlighting environmental influences on brain health.

The study further examined MRFs, using a two-step analysis to determine their impact on the LIFO network. Initial findings identified significant associations across 12 MRF categories, with pollution, diabetes and alcohol consumption emerging as notable risk factors affecting the LIFO network. This comprehensive model, which takes into account confounding factors such as age and sex, underscores the multifaceted nature of brain health, merging genetic predispositions with environmental and lifestyle factors.

The heritability of the LIFO network was confirmed, although genetic coheritability with Alzheimer’s disease or schizophrenia did not show statistical significance. This finding suggests a complex interplay of factors contributing to brain network vulnerability.

Conclusions

In short, in the study, researchers discovered significant genetic and lifestyle factors that influence a brain network prone to premature aging, known as the LIFO network. They identified seven genetic clusters, including new ones on sex chromosomes, and highlighted diabetes, air pollution and alcohol as key modifiable risks. These findings reveal a complex interplay between genetics and environment in brain health, highlighting the vulnerability of the LIFO network to aging and diseases such as Alzheimer’s disease and schizophrenia. The study also opens new avenues for investigating the genetic influences of the XG blood group on brain aging.

Diary reference:

  • Manuello, J., Min, J., McCarthy, P. et al. The effects of genetic and modifiable risk factors on brain regions vulnerable to aging and disease. Nat Commun (2024), DOI-10.1038/s41467-024-46344-2, https://www.nature.com/articles/s41467-024-46344-2

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