Abstract
Metformin, a diabetes drug with anti-aging cellular responses, has complex actions that may alter dementia onset. Mixed results are emerging from prior observational studies. To address this complexity, we deploy a causal inference approach accounting for the competing risk of death in emulated clinical trials using two distinct electronic health record systems. In intention-to-treat analyses, metformin use associates with lower hazard of all-cause mortality and lower cause-specific hazard of dementia onset, after accounting for prolonged survival, relative to sulfonylureas. In parallel systems pharmacology studies, the expression of two AD-related proteins, APOE and SPP1, was suppressed by pharmacologic concentrations of metformin in differentiated human neural cells, relative to a sulfonylurea. Together, our findings suggest that metformin might reduce the risk of dementia in diabetes patients through mechanisms beyond glycemic control, and that SPP1 is a candidate biomarker for metformin’s action in the brain.
| Original language | English |
|---|---|
| Article number | 7652 |
| Pages (from-to) | 7652 |
| Journal | Nature Communications |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - 10 Dec 2022 |
Bibliographical note
Funding Information:We thank Alexander Soukas, Victor Castro, and Peter K. Sorger for helpful discussions. The authors thank Shawn Murphy, Henry Chueh, and the Partners Health Care Research Patient Data Registry group for facilitating use of their database. This study is based in part on data from the Clinical Practice Research Datalink database obtained under license from the UK Medicines and Healthcare products Regulatory Agency. However, the interpretation and conclusions contained in this article are those of the authors alone and not necessarily those of the NHS, the NIHR, or the Department of Health. The results published here are in part based on data obtained from the AMP-AD Knowledge Portal (doi:10.7303/syn2580853). These data were generated from postmortem brain tissue collected through the Mount Sinai VA Medical Center Brain Bank, led by Dr. Eric Schadt from Mount Sinai School of Medicine, by the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, and by the following sources: The Mayo Clinic Alzheimer’s Disease Genetic Studies, led by Dr. Nilufer Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, FL using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer’s Disease Research Center, and the Mayo Clinic Brain Bank. We thank the NIH R01 AG058063 (awarded to M.W.A.), P30 AG062421 (awarded to B.T.H.), P30 AG066512 (awarded to R.A.B.), a CART grant (awarded to M.W.A.), an administrative supplement to U54 CA22508 (awarded to M.W.A.), IBM Research (awarded to R.E.W. and S.N.F.), the Abdul Latif Jameel Clinic for Machine Learning in Health grant (awarded to R.E.W. and S.N.F.), the UK Dementia Research Institute which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council (awarded to I.T.), the Alzheimer’s Society and Alzheimer’s Research UK, support by the British Heart Foundation Centre for Research Excellence at Imperial College (awarded to I.T.), the Hellenic Foundation for Research and Innovation (HFRI) (awarded to I.T.), and the General Secretariat for Research and Technology (GSRT) (awarded to I.T.) for support.
Funding Information:
We thank Alexander Soukas, Victor Castro, and Peter K. Sorger for helpful discussions. The authors thank Shawn Murphy, Henry Chueh, and the Partners Health Care Research Patient Data Registry group for facilitating use of their database. This study is based in part on data from the Clinical Practice Research Datalink database obtained under license from the UK Medicines and Healthcare products Regulatory Agency. However, the interpretation and conclusions contained in this article are those of the authors alone and not necessarily those of the NHS, the NIHR, or the Department of Health. The results published here are in part based on data obtained from the AMP-AD Knowledge Portal (doi:10.7303/syn2580853). These data were generated from postmortem brain tissue collected through the Mount Sinai VA Medical Center Brain Bank, led by Dr. Eric Schadt from Mount Sinai School of Medicine, by the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, and by the following sources: The Mayo Clinic Alzheimer’s Disease Genetic Studies, led by Dr. Nilufer Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, FL using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer’s Disease Research Center, and the Mayo Clinic Brain Bank. We thank the NIH R01 AG058063 (awarded to M.W.A.), P30 AG062421 (awarded to B.T.H.), P30 AG066512 (awarded to R.A.B.), a CART grant (awarded to M.W.A.), an administrative supplement to U54 CA22508 (awarded to M.W.A.), IBM Research (awarded to R.E.W. and S.N.F.), the Abdul Latif Jameel Clinic for Machine Learning in Health grant (awarded to R.E.W. and S.N.F.), the UK Dementia Research Institute which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council (awarded to I.T.), the Alzheimer’s Society and Alzheimer’s Research UK, support by the British Heart Foundation Centre for Research Excellence at Imperial College (awarded to I.T.), the Hellenic Foundation for Research and Innovation (HFRI) (awarded to I.T.), and the General Secretariat for Research and Technology (GSRT) (awarded to I.T.) for support.
Publisher Copyright:
© 2022, The Author(s).
ASJC Scopus subject areas
- Chemistry (all)
- Biochemistry, Genetics and Molecular Biology (all)
- General
- Physics and Astronomy (all)
