Causality between plasma lipids and neurodegenerative diseases: a bidirectional two-sample Mendelian randomization analysis_Chinese Journal of Evidence-Based Medicine

Authors：

MENG Liuyang , ZHANG Shuaikang , SONG Chengbin ,  JIANG Deyou

Heilongjiang University of Traditional Chinese Medicine, Harbin 150000, P. R. China;

Corresponding author：

JIANG Deyou, Email: jiangdeyou@126.com

Keywords：

Mendelian randomized analysis; Plasma lipids; Neurodegenerative diseases; Causality

DOI：

10.7507/1672-2531.202403095

Video：

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Objective Observational studies have shown that plasma lipids are associated with the development of neurodegenerative diseases (NDD), but the causal relationship is unclear. This study investigated the causal relationship between 179 liposomes and NDD using a two-sample Mendelian randomization (MR). Methods A two-sample MR method was used to comprehensively analyze the causal relationship between liposomes and major NDD such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS). The two sample software package and Phenoscanner database were used to screen for appropriate instrumental variables(TV). In this study, inverse variance weighting (IVW) was used as the primary measure of MR analysis, and various sensitivity tests were performed. Results MR-IVW results showed that phosphatidylethanolamine (PE) (OR=0.90, 95%CI 0.83 to 0.99, P=0.03), phosphatidylcholine (PC) (OR=0.92, 95%CI 0.85 to 0.99, P=0.02) and phosphatidylinositol (PI) (OR=0.90, 95%CI 0.83 to 0.99, P=0.03) were protective factors for AD. Sterol ester (OR=1.18, 95%CI 1.04 to 1.34, P=0.01) and cholesterol (OR=1.26, 95%CI 1.02 to 1.56, P=0.03) increased the risk of PD. PE (OR=0.79, 95%CI 0.64 to 0.98, P=0.03) and PC (OR=0.83, 95%CI 0.69 to 0.98, P=0.03) reduced the risk of PD. Diacylglycerol (DAG) (OR=1.24, 95%CI 1.01 to 1.54, P=0.04) and sphingomyelin (SM) (OR=1.13, 95%CI 1.08 to 1.58, P=0.01) were the risk factors for MS. PI (OR=0.77, 95%CI 0.62 to 0.95, P=0.02) and PC (OR=0.74, 95%CI 0.88 to 0.95, P=0.02) were protective factors for MS. PI (OR=1.02, 95%CI 1.01 to 1.04, P=0.02) and triglyceride (TG) (OR=1.03, 95%CI 1.01 to 1.05, P=0.02) increased the risk of ALS, PC (OR=0.98, 95%CI 0.97 to 0.99, P=0.03) decreased the risk of ALS. Conclusion There is a causal relationship between sterol ester, cholesterol, PC, PE, PI, DAG, SM, TG and different NDD, which will provide theoretical basis and support for further clinical studies.

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7.	De Jager PL, Bennett DA. An inflection point in gene discovery efforts for neurodegenerative diseases: from syndromic diagnoses toward endophenotypes and the epigenome. JAMA Neurol, 2013, 70(6): 719-726.
8.	Mesa-Herrera F, Taoro-González L, Valdés-Baizabal C, et al. Lipid and lipid raft alteration in aging and neurodegenerative diseases: a window for the development of new biomarkers. Int J Mol Sci, 2019, 20(15): 3810.
9.	Chew H, Solomon VA, Fonteh AN. Involvement of lipids in Alzheimer's disease pathology and potential therapies. Front Physiol, 2020, 11: 598.
10.	Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review. Res Synth Methods, 2019, 10(4): 486-496.
11.	Lawlor DA, Harbord RM, Sterne JA, et al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med, 2008, 27(8): 1133-1163.
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13.	Ottensmann L, Tabassum R, Ruotsalainen SE, et al. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat Commun, 2023, 14(1): 6934.
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15.	Zhang Y, Zhang X, Chen D, et al. Causal associations between gut microbiome and cardiovascular disease: a Mendelian randomization study. Front Cardiovasc Med, 2022, 9: 971376.
16.	Burgess S, Davey Smith G, Davies NM, et al. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res, 2023, 4: 186.
17.	Bowden J, Spiller W, Del Greco M F, et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regression. Int J Epidemiol, 2018, 47(6): 2100.
18.	Gronau QF, Wagenmakers EJ. Limitations of Bayesian leave-one-out cross-validation for model selection. Comput Brain Behav, 2019, 2(1): 1-11.
19.	Hemani G, Zheng J, Elsworth B, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife, 2018, 7: e34408.
20.	Alecu I, Bennett SAL. Dysregulated lipid metabolism and its role in α-synucleinopathy in Parkinson's disease. Front Neurosci, 2019, 13: 328.
21.	Gouras GK, Tampellini D, Takahashi RH, et al. Intraneuronal beta-amyloid accumulation and synapse pathology in Alzheimer's disease. Acta Neuropathol, 2010, 119(5): 523-541.
22.	Kurouski D. Elucidating the role of lipids in the aggregation of amyloidogenic proteins. Acc Chem Res, 2023, 56(21): 2898-2906.
23.	Shanks HRC, Onuska KM, Barupal DK, et al. Serum unsaturated phosphatidylcholines predict longitudinal basal forebrain degeneration in Alzheimer's disease. Brain Commun, 2022, 4(6): fcac318.
24.	Batra R, Arnold M, Wörheide MA, et al. The landscape of metabolic brain alterations in Alzheimer's disease. Alzheimers Dement, 2023, 19(3): 980-998.
25.	Bárány M, Chang YC, Arús C, et al. Increased glycerol-3-phosphorylcholine in post-mortem Alzheimer's brain. Lancet, 1985, 1(8427): 517.
26.	Miatto O, Gonzalez RG, Buonanno F, et al. In vitro 31P NMR spectroscopy detects altered phospholipid metabolism in Alzheimer's disease. Can J Neurol Sci, 1986, 13(4 Suppl): 535-539.
27.	Lolicato F, Nickel W, Haucke V, et al. Phosphoinositide switches in cell physiology - from molecular mechanisms to disease. J Biol Chem, 2024, 300(3): 105757.
28.	Balla T. Phosphoinositides: tiny lipids with giant impact on cell regulation. Physiol Rev, 2013, 93(3): 1019-1137.
29.	Gao Y, Ye S, Tang Y, et al. Brain cholesterol homeostasis and its association with neurodegenerative diseases. Neurochem Int, 2023, 171: 105635.
30.	Raju A, Jaisankar P, Borah A, et al. 1-Methyl-4-phenylpyridinium-induced death of differentiated SH-SY5Y neurons is potentiated by cholesterol. Ann Neurosci, 2018, 24(4): 243-251.
31.	Galvagnion C. The role of lipids interacting with α-synuclein in the pathogenesis of Parkinson's disease. J Parkinsons Dis, 2017, 7(3): 433-450.
32.	Wang S, Zhang S, Liou LC, et al. Phosphatidylethanolamine deficiency disrupts α-synuclein homeostasis in yeast and worm models of Parkinson disease. Proc Natl Acad Sci USA, 2014, 111(38): E3976-E3985.
33.	Manyam BV, Ferraro TN, Hare TA. Cerebrospinal fluid amino compounds in Parkinson's disease. Alterations due to carbidopa/levodopa. Arch Neurol, 1988, 45(1): 48-50.
34.	Lattau SSJ, Borsch LM, Auf dem Brinke K, et al. Plasma lipidomic profiling using mass spectrometry for multiple sclerosis diagnosis and disease activity stratification (lipidMS). Int J Mol Sci, 2024, 25(5): 2483.
35.	Cui H, Huang Y, Wu Y, et al. The expression of diacylglycerol kinase isoforms α and ζ correlates with the progression of experimental autoimmune encephalomyelitis in rats. Histochem Cell Biol, 2021, 156(5): 437-448.
36.	Walter S, Gulbins E, Halmer R, et al. Pharmacological inhibition of acid sphingomyelinase ameliorates experimental autoimmune encephalomyelitis. Neurosignals, 2019, 27(S1): 20-31.
37.	Roy P, Tomassoni D, Nittari G, et al. Effects of choline containing phospholipids on the neurovascular unit: a review. Front Cell Neurosci, 2022, 16: 988759.
38.	Sun M, Gong P, Yuan B, et al. AXL-induced autophagy mitigates experimental autoimmune encephalomyelitis by suppressing microglial inflammation via the PI3K/AKT/mTOR signaling pathway. Mol Immunol, 2023, 159: 15-27.
39.	Vaage AM, Benth JŠ, Meyer HE, et al. Premorbid lipid levels and long-term risk of ALS-a population-based cohort study. Amyotroph Lateral Scler Frontotemporal Degener, 2024, 25(3-4): 358-366.
40.	Phan K, He Y, Bhatia S, et al. Multiple pathways of lipid dysregulation in amyotrophic lateral sclerosis. Brain Commun, 2022, 5(1): fcac340.
41.	Wagey R, Pelech SL, Duronio V, et al. Phosphatidylinositol 3-kinase: increased activity and protein level in amyotrophic lateral sclerosis. J Neurochem, 1998, 71(2): 716-722.
42.	Wilson C, Venditti R, De Matteis MA. Deregulation of phosphatidylinositol-4-phosphate in the development of amyotrophic lateral sclerosis 8. Adv Biol Regul, 2021, 79: 100779.
43.	Arima H, Omura T, Hayasaka T, et al. Reductions of docosahexaenoic acid-containing phosphatidylcholine levels in the anterior horn of an ALS mouse model. Neuroscience, 2015, 297: 127-136.
44.	Ikeda K, Kinoshita M, Iwasaki Y, et al. Lecithinized superoxide dismutase retards wobbler mouse motoneuron disease. Neuromuscul Disord, 1995, 5(5): 383-390.
45.	Chen S, Wang L, Hu Y, et al. High drug capacity of nano-levodopa-liposomes: preparation, in vitro release and brain-targeted research. Appl Biochem Biotechnol, 2024, 196(6): 3317-3330.
46.	De La Torre AL, Huynh TN, Chang CCY, et al. Stealth liposomes encapsulating a potent ACAT1/SOAT1 inhibitor F12511: pharmacokinetic, biodistribution, and toxicity studies in wild-type mice and efficacy studies in triple transgenic Alzheimer's disease mice. Int J Mol Sci, 2023, 24(13): 11013.
47.	Zhou Y, Zhu F, Liu Y, et al. Blood-brain barrier-penetrating siRNA nanomedicine for Alzheimer's disease therapy. Sci Adv, 2020, 6(41): eabc7031.
48.	Seo MW, Park TE. Recent advances with liposomes as drug carriers for treatment of neurodegenerative diseases. Biomed Eng Lett, 2021, 11(3): 211-216.
49.	Teixeira MI, Lopes CM, Amaral MH, et al. Current insights on lipid nanocarrier-assisted drug delivery in the treatment of neurodegenerative diseases. Eur J Pharm Biopharm, 2020, 149: 192-217.

1. Haider ZF, von Stumm S. Predicting educational and social-emotional outcomes in emerging adulthood from intelligence, personality, and socioeconomic status. J Pers Soc Psychol, 2022, 123(6): 1386-1406.
2. Li D, Zhou L, Cao Z, et al. Associations of environmental factors with neurodegeneration: an exposome-wide mendelian randomization investigation. Ageing Res Rev, 2024, 95: 102254.
3. Estes RE, Lin B, Khera A, et al. Lipid metabolism influence on neurodegenerative disease progression: is the vehicle as important as the cargo. Front Mol Neurosci, 2021, 14: 788695.
4. Quehenberger O, Dennis EA. The human plasma lipidome. N Engl J Med, 2011, 365(19): 1812-1823.
5. O'Donnell VB, Ekroos K, Liebisch G, et al. Lipidomics: current state of the art in a fast moving field. Wiley Interdiscip Rev Syst Biol Med, 2020, 12(1): e1466.
6. Stephenson DJ, Hoeferlin LA, Chalfant CE. Lipidomics in translational research and the clinical significance of lipid-based biomarkers. Transl Res, 2017, 189: 13-29.
7. De Jager PL, Bennett DA. An inflection point in gene discovery efforts for neurodegenerative diseases: from syndromic diagnoses toward endophenotypes and the epigenome. JAMA Neurol, 2013, 70(6): 719-726.
8. Mesa-Herrera F, Taoro-González L, Valdés-Baizabal C, et al. Lipid and lipid raft alteration in aging and neurodegenerative diseases: a window for the development of new biomarkers. Int J Mol Sci, 2019, 20(15): 3810.
9. Chew H, Solomon VA, Fonteh AN. Involvement of lipids in Alzheimer's disease pathology and potential therapies. Front Physiol, 2020, 11: 598.
10. Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review. Res Synth Methods, 2019, 10(4): 486-496.
11. Lawlor DA, Harbord RM, Sterne JA, et al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med, 2008, 27(8): 1133-1163.
12. Glymour MM, Tchetgen Tchetgen EJ, Robins JM. Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions. Am J Epidemiol, 2012, 175(4): 332-339.
13. Ottensmann L, Tabassum R, Ruotsalainen SE, et al. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat Commun, 2023, 14(1): 6934.
14. Machiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics, 2015, 31(21): 3555-3557.
15. Zhang Y, Zhang X, Chen D, et al. Causal associations between gut microbiome and cardiovascular disease: a Mendelian randomization study. Front Cardiovasc Med, 2022, 9: 971376.
16. Burgess S, Davey Smith G, Davies NM, et al. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res, 2023, 4: 186.
17. Bowden J, Spiller W, Del Greco M F, et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regression. Int J Epidemiol, 2018, 47(6): 2100.
18. Gronau QF, Wagenmakers EJ. Limitations of Bayesian leave-one-out cross-validation for model selection. Comput Brain Behav, 2019, 2(1): 1-11.
19. Hemani G, Zheng J, Elsworth B, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife, 2018, 7: e34408.
20. Alecu I, Bennett SAL. Dysregulated lipid metabolism and its role in α-synucleinopathy in Parkinson's disease. Front Neurosci, 2019, 13: 328.
21. Gouras GK, Tampellini D, Takahashi RH, et al. Intraneuronal beta-amyloid accumulation and synapse pathology in Alzheimer's disease. Acta Neuropathol, 2010, 119(5): 523-541.
22. Kurouski D. Elucidating the role of lipids in the aggregation of amyloidogenic proteins. Acc Chem Res, 2023, 56(21): 2898-2906.
23. Shanks HRC, Onuska KM, Barupal DK, et al. Serum unsaturated phosphatidylcholines predict longitudinal basal forebrain degeneration in Alzheimer's disease. Brain Commun, 2022, 4(6): fcac318.
24. Batra R, Arnold M, Wörheide MA, et al. The landscape of metabolic brain alterations in Alzheimer's disease. Alzheimers Dement, 2023, 19(3): 980-998.
25. Bárány M, Chang YC, Arús C, et al. Increased glycerol-3-phosphorylcholine in post-mortem Alzheimer's brain. Lancet, 1985, 1(8427): 517.
26. Miatto O, Gonzalez RG, Buonanno F, et al. In vitro 31P NMR spectroscopy detects altered phospholipid metabolism in Alzheimer's disease. Can J Neurol Sci, 1986, 13(4 Suppl): 535-539.
27. Lolicato F, Nickel W, Haucke V, et al. Phosphoinositide switches in cell physiology - from molecular mechanisms to disease. J Biol Chem, 2024, 300(3): 105757.
28. Balla T. Phosphoinositides: tiny lipids with giant impact on cell regulation. Physiol Rev, 2013, 93(3): 1019-1137.
29. Gao Y, Ye S, Tang Y, et al. Brain cholesterol homeostasis and its association with neurodegenerative diseases. Neurochem Int, 2023, 171: 105635.
30. Raju A, Jaisankar P, Borah A, et al. 1-Methyl-4-phenylpyridinium-induced death of differentiated SH-SY5Y neurons is potentiated by cholesterol. Ann Neurosci, 2018, 24(4): 243-251.
31. Galvagnion C. The role of lipids interacting with α-synuclein in the pathogenesis of Parkinson's disease. J Parkinsons Dis, 2017, 7(3): 433-450.
32. Wang S, Zhang S, Liou LC, et al. Phosphatidylethanolamine deficiency disrupts α-synuclein homeostasis in yeast and worm models of Parkinson disease. Proc Natl Acad Sci USA, 2014, 111(38): E3976-E3985.
33. Manyam BV, Ferraro TN, Hare TA. Cerebrospinal fluid amino compounds in Parkinson's disease. Alterations due to carbidopa/levodopa. Arch Neurol, 1988, 45(1): 48-50.
34. Lattau SSJ, Borsch LM, Auf dem Brinke K, et al. Plasma lipidomic profiling using mass spectrometry for multiple sclerosis diagnosis and disease activity stratification (lipidMS). Int J Mol Sci, 2024, 25(5): 2483.
35. Cui H, Huang Y, Wu Y, et al. The expression of diacylglycerol kinase isoforms α and ζ correlates with the progression of experimental autoimmune encephalomyelitis in rats. Histochem Cell Biol, 2021, 156(5): 437-448.
36. Walter S, Gulbins E, Halmer R, et al. Pharmacological inhibition of acid sphingomyelinase ameliorates experimental autoimmune encephalomyelitis. Neurosignals, 2019, 27(S1): 20-31.
37. Roy P, Tomassoni D, Nittari G, et al. Effects of choline containing phospholipids on the neurovascular unit: a review. Front Cell Neurosci, 2022, 16: 988759.
38. Sun M, Gong P, Yuan B, et al. AXL-induced autophagy mitigates experimental autoimmune encephalomyelitis by suppressing microglial inflammation via the PI3K/AKT/mTOR signaling pathway. Mol Immunol, 2023, 159: 15-27.
39. Vaage AM, Benth JŠ, Meyer HE, et al. Premorbid lipid levels and long-term risk of ALS-a population-based cohort study. Amyotroph Lateral Scler Frontotemporal Degener, 2024, 25(3-4): 358-366.
40. Phan K, He Y, Bhatia S, et al. Multiple pathways of lipid dysregulation in amyotrophic lateral sclerosis. Brain Commun, 2022, 5(1): fcac340.
41. Wagey R, Pelech SL, Duronio V, et al. Phosphatidylinositol 3-kinase: increased activity and protein level in amyotrophic lateral sclerosis. J Neurochem, 1998, 71(2): 716-722.
42. Wilson C, Venditti R, De Matteis MA. Deregulation of phosphatidylinositol-4-phosphate in the development of amyotrophic lateral sclerosis 8. Adv Biol Regul, 2021, 79: 100779.
43. Arima H, Omura T, Hayasaka T, et al. Reductions of docosahexaenoic acid-containing phosphatidylcholine levels in the anterior horn of an ALS mouse model. Neuroscience, 2015, 297: 127-136.
44. Ikeda K, Kinoshita M, Iwasaki Y, et al. Lecithinized superoxide dismutase retards wobbler mouse motoneuron disease. Neuromuscul Disord, 1995, 5(5): 383-390.
45. Chen S, Wang L, Hu Y, et al. High drug capacity of nano-levodopa-liposomes: preparation, in vitro release and brain-targeted research. Appl Biochem Biotechnol, 2024, 196(6): 3317-3330.
46. De La Torre AL, Huynh TN, Chang CCY, et al. Stealth liposomes encapsulating a potent ACAT1/SOAT1 inhibitor F12511: pharmacokinetic, biodistribution, and toxicity studies in wild-type mice and efficacy studies in triple transgenic Alzheimer's disease mice. Int J Mol Sci, 2023, 24(13): 11013.
47. Zhou Y, Zhu F, Liu Y, et al. Blood-brain barrier-penetrating siRNA nanomedicine for Alzheimer's disease therapy. Sci Adv, 2020, 6(41): eabc7031.
48. Seo MW, Park TE. Recent advances with liposomes as drug carriers for treatment of neurodegenerative diseases. Biomed Eng Lett, 2021, 11(3): 211-216.
49. Teixeira MI, Lopes CM, Amaral MH, et al. Current insights on lipid nanocarrier-assisted drug delivery in the treatment of neurodegenerative diseases. Eur J Pharm Biopharm, 2020, 149: 192-217.

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Latest ArticlesCausality between plasma lipids and neurodegenerative diseases: a bidirectional two-sample Mendelian randomization analysis

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