A meta-analysis of genome-wide association studies identifies new genetic loci associated with all-cause and vascular dementia

Abstract

Dementia is multifactorial with Alzheimer (AD) and vascular (VaD) pathologies making the largest contributions. Genome-wide association studies (GWAS) have identified over 70 genetic risk loci for AD but the genomic determinants of other dementias, including VaD remain understudied. We hypothesize that common forms of dementia will share genetic risk factors and conducted the largest GWAS to date of "all-cause dementia" (ACD) and examined the genetic overlap with VaD. Our dataset includes 809,299 individuals from European, African, Asian, and Hispanic ancestries with 46,902 and 8,702 cases of ACD and VaD, respectively. We replicated known AD loci at genome-wide significance for both ACD and VaD and conducted bioinformatic analyses in prioritizing genes that are functionally relevant and shared with closely related traits and risk factors. For ACD, novel loci were associated with energy transport throughout the brain (SEMA4D), neuronal excitability (ANO3), amyloid plaques deposition in the brain (RBFOX1), and MRI markers of small vessel disease (HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). In addition to the genetic overlap with neurodegenerative processes, genetic risk loci for ACD exhibited overlap with vascular risk factors (Type-II diabetes, blood pressure, lipid levels) and MRI markers of cerebral small vessel disease (cSVD). Our study identified genetic risk loci underlying ACD and VaD that point to the involvement of specific biological pathways and highlights their genetic overlap with vascular risk factors and MRI markers of cSVD. These novel insights could lead to new prevention and treatment strategies.

The ABC's of Alzheimer risk gene ABCA7

“…In East-Asian populations, also associations with AD have been detected for SNPs rs3764650 and rs4147929. 45 Finally, for both rs3764650 and rs12151021, significant association has been detected in a mixed ancestry study of all cause dementia 46 and AD, respectively. 47 Differences in association signals between ethnicities could be due to discrepancies in genetic architecture such as LD structure and allele frequencies.…”

Artificial intelligence for dementia genetics and omics

“…There is currently a marked lack of diversity within dementia genetics studies, with GWAS discovery being largely confined to the genetics of AD in non‐Hispanic White adults of European ancestry. Although some small GWAS have been conducted in non‐European samples, 20,21–23 have measured non‐AD dementias, 6,9,10 and incorporated dementia‐related intermediate quantitative phenotypes or endophenotypes (such as amyloid‐beta and cerebral small vessel disease), 24–26 these studies are largely underpowered. Certain ancestries remain understudied, for example, South Asians despite representing around a quarter of the total global population.…”

“…Although some small GWAS have been conducted in non-European samples, 20,[21][22][23] have measured non-AD dementias, 6,9,10 and incorporated dementia-related intermediate quantitative phenotypes or endophenotypes (such as amyloid-beta and cerebral small vessel disease), [24][25][26] The study of both coding and non-coding rare/structural variants associated with dementia risk needs to be further pursued through short-and long-read sequencing technologies, which are thought to be important contributors to missing heritability in dementia. 27 Under the hood, long-read sequencing is powered by DL, using GPUpowered alignment algorithms to better characterize the genome.…”

“…2 Genomewide association studies (GWAS) have led to the identification of an increasing number of genetic loci associated with the risk of dementias and related neurodegenerative diseases in older adults, primarily of European ancestry. [3][4][5][6][7][8][9][10] However, even with established bonafide associations, the task of characterizing variants and genes in the context of complex disease molecular pathophysiology, as well as its interacting genes and pathways, remains a daunting challenge. 11 Recent progress in cutting-edge genetic and omics technologies, such as epigenomics, transcriptomics, proteomics, and metabolomics, which refer to the comprehensive assessment of a set of specific types of biological molecules, allied with emerging computational methods, hold promise of faster discoveries.…”

“…The number of people living with dementia worldwide is around 45 million and, as life expectancy increases and populations age, this number is expected to increase 2 . Genome‐wide association studies (GWAS) have led to the identification of an increasing number of genetic loci associated with the risk of dementias and related neurodegenerative diseases in older adults, primarily of European ancestry 3–10 . However, even with established bonafide associations, the task of characterizing variants and genes in the context of complex disease molecular pathophysiology, as well as its interacting genes and pathways, remains a daunting challenge 11 …”