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Two Studies Uncover Risk Loci for Age-Associated Neurodegenerative Disorders

NEW YORK – Two new studies have uncovered genetic risk loci for the age-associated neurodegenerative disorders Alzheimer's disease and Lewy body dementia that hint at genes that influence dementia risk.

Dementia affects some 5 million people in the US. While previous studies have tied dozens of genetic loci to Alzheimer's disease, the most common form of dementia, a Wellcome Sanger Institute team turned to a genome-wide association study by proxy (GWAX) and meta-analysis approach to boost power to identify additional risk loci. Meanwhile, a National Institute of Neurological Disorders and Stroke-led team delved into genetic risk loci linked to the less-studied Lewy body dementia, finding further evidence of its overlap with Alzheimer's disease and Parkinson's disease.

For their GWAX, researchers led by Sanger's Andrew Bassett analyzed 53,042 individuals either diagnosed themselves or with a parent or sibling with Alzheimer's disease and 355,900 controls from the UK Biobank. They identified 13 loci linked to risk of Alzheimer's disease, including three new loci, as they reported Monday in Nature Genetics. A further fixed-effect meta-analysis of the GWAX results uncovered 34 risk loci, four of which were new, and three loci with suggestive significance. Such an approach, Bassett noted in an email, enables an increased sample size and sensitivity to detect novel genomic risk loci.

By applying three different fine-mapping approaches, the researchers identified 21 SNPs that could be causal for Alzheimer's disease risk, including ones near known Alzheimer's disease risk genes. They additionally conducted a co-localization analysis to identify genes whose expression might be affected by the risk variants. This implicated genes like PTK2B, BIN1, and TREM2, which have previously been associated with Alzheimer's disease risk. 

They bundled this data into a quantitative score aimed at highlighting potentially causal genes. Among the high-confidence prioritized genes were APH1B and TSPAN14, which have roles in APP processing and ADAM10 localization, respectively. Other prioritized genes included RIN3, HS3ST1, and FCER1G.

Bassett and his colleagues are now following up on the candidate genes this analysis uncovered. In particular, they are using iPSC-derived microglia to examine their roles in cellular function.

In a separate paper also appearing in Nature Genetics, an international team of researchers led by NINDS's Sonja Scholz sought to identify genetic risk loci for Lewy body dementia, a form of dementia that includes features of both Alzheimer's disease and Parkinson's disease. They sequenced 2,981 people diagnosed with Lewy body dementia and 4,391 controls. Through a subsequent genome-wide association study, the researchers uncovered five genetic loci linked to Lewy body dementia risk. Three of those loci were at known Lewy body dementia risk loci in the genes GBA, APOE, and SNCA. The two other loci were new and were in BIN1 and TMEM175, which have been tied to Alzheimer's disease and Parkinson's disease, respectively.

The researchers also examined similarities between the risk profiles for Lewy body dementia, Alzheimer's disease, and Parkinson's disease. Individuals diagnosed with Lewy body dementia had a higher genetic risk of developing both Alzheimer's disease, and Parkinson's disease. In addition, they noted overlap between pathways involved in Lewy body dementia and in Alzheimer's disease and Parkinson's disease, such as amyloid-beta formation and the regulation of endocytosis. 

These findings suggested to the researchers that the genetic architecture of Lewy body dementia is complex and overlaps with that of Alzheimer's disease and Parkinson's disease. Further, Scholz noted in an email, these shared molecular alterations suggest that "drugs developed for Parkinson's disease or Alzheimer's disease should be tested as candidate drugs for LBD."

She added that there is more work to be done to better understand Lewy body dementia, including studying a greater number and greater diversity of patients as well as exploring the effect of the risk loci in model systems. "The hope is that this knowledge will ultimately pave the way for the development of disease-modifying therapeutic interventions," she said.