TY - JOUR
T1 - Shared genetic loci between Alzheimer's disease and multiple sclerosis
T2 - Crossroads between neurodegeneration and immune system
AU - Fominykh, Vera
AU - Shadrin, Alexey A.
AU - Jaholkowski, Piotr P.
AU - Bahrami, Shahram
AU - Athanasiu, Lavinia
AU - Wightman, Douglas P.
AU - Uffelmann, Emil
AU - Posthuma, Danielle
AU - Selbæk, Geir
AU - Dale, Anders M.
AU - Djurovic, Srdjan
AU - Frei, Oleksandr
AU - Andreassen, Ole A.
N1 - Funding Information: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 847776 and 964874 , and EEA grants ( EEA-RO-NO-2018-0535 , EEA-RO-NO-2018-0573 ). This work was partly performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo and operated and developed by the TSD service group at the University of Oslo, IT Department (USIT). Computations were also performed on resources provided by the National Infrastructure for High-Performance Computing and Data Storage in Norway. DP received funding from NWO Gravitation: BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (Grant No. 024.004.012 , to D.P. and D.P.W.), and a European Research Council advanced grant (Grant No, ERC-2018-AdG GWAS2FUNC 834057 , to D.P.). Funding Information: All GWAS investigated in the present study were approved by the local ethics committees, and informed consent was obtained from all participants. The authors thank the researchers of the IMSGC, PGC and ADGC consortia for access to data, and for all participants who provided samples. We gratefully acknowledge support from the American National Institutes of Health ( NS057198 , EB00790 ), the Research Council of Norway (# 229129 , 213837 , 324252 , 326813 , 300309 , 273291 , 223273 , 248980 , 296030 ), the South-East Norway Regional Health Authority ( 2022-073 ), KG Jebsen Stiftelsen ( SKGJ-MED-021 ), Norwegian Health Association ("Nasjonalforeningen for folkehelsen", # 22731 ). Funding Information: All GWAS investigated in the present study were approved by the local ethics committees, and informed consent was obtained from all participants. The authors thank the researchers of the IMSGC, PGC and ADGC consortia for access to data, and for all participants who provided samples. We gratefully acknowledge support from the American National Institutes of Health (NS057198, EB00790), the Research Council of Norway (#229129, 213837, 324252, 326813, 300309, 273291, 223273, 248980, 296030), the South-East Norway Regional Health Authority (2022-073), KG Jebsen Stiftelsen (SKGJ-MED-021), Norwegian Health Association ("Nasjonalforeningen for folkehelsen", #22731). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 847776 and 964874, and EEA grants (EEA-RO-NO-2018-0535, EEA-RO-NO-2018-0573). This work was partly performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo and operated and developed by the TSD service group at the University of Oslo, IT Department (USIT). Computations were also performed on resources provided by the National Infrastructure for High-Performance Computing and Data Storage in Norway. DP received funding from NWO Gravitation: BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (Grant No. 024.004.012, to D.P. and D.P.W.), and a European Research Council advanced grant (Grant No, ERC-2018-AdG GWAS2FUNC 834057, to D.P.). Publisher Copyright: © 2023 The Authors
PY - 2023/7/1
Y1 - 2023/7/1
N2 - Background: Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. Methods: We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. Results: MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. Conclusions: Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.
AB - Background: Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. Methods: We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. Results: MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. Conclusions: Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.
KW - Alzheimer's disease
KW - Dementia
KW - Genetic overlap
KW - Multiple sclerosis
KW - Neurodegeneration
KW - Neuroinflammation
KW - Pleiotropy
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U2 - https://doi.org/10.1016/j.nbd.2023.106174
DO - https://doi.org/10.1016/j.nbd.2023.106174
M3 - Article
C2 - 37286172
SN - 0969-9961
VL - 183
SP - 1
EP - 12
JO - Neurobiology of Disease
JF - Neurobiology of Disease
M1 - 106174
ER -