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Investigators analyzed data on more than 450,000 participants in the UK Biobank as well as two independent samples of more than 320,000 individuals with and without AD, and more than 260,000 individuals participating in a separate genes and intelligence study.
They estimated lean muscle and fat tissue in the arms and legs and found, in adjusted analyses, over 500 genetic variants associated with lean mass.
On average, higher genetically lean mass was associated with a “modest but statistically robust” reduction in AD risk and with superior performance on cognitive tasks.
“Using human genetic data, we found evidence for a protective effect of lean mass on risk of Alzheimer’s disease,” study investigators Iyas Daghlas, MD, a resident in the department of neurology, University of California, San Francisco, said in an interview.
Although “clinical intervention studies are needed to confirm this effect, this study supports current recommendations to maintain a healthy lifestyle to prevent dementia,” he said.
The study was published online in BMJ Medicine.
Naturally randomized research
Several measures of body composition have been investigated for their potential association with AD. Lean mass – a “proxy for muscle mass, defined as the difference between total mass and fat mass” – has been shown to be reduced in patients with AD compared with controls, the researchers noted.
“Previous research studies have tested the relationship of body mass index with Alzheimer’s disease and did not find evidence for a causal effect,” Dr. Daghlas said. “We wondered whether BMI was an insufficiently granular measure and hypothesized that disaggregating body mass into lean mass and fat mass could reveal novel associations with disease.”
Most studies have used case-control designs, which might be biased by “residual confounding or reverse causality.” Naturally randomized data “may be used as an alternative to conventional observational studies to investigate causal relations between risk factors and diseases,” the researchers wrote.
In particular, the Mendelian randomization (MR) paradigm randomly allocates germline genetic variants and uses them as proxies for a specific risk factor.
MR “is a technique that permits researchers to investigate cause-and-effect relationships using human genetic data,” Dr. Daghlas explained. “In effect, we’re studying the results of a naturally randomized experiment whereby some individuals are genetically allocated to carry more lean mass.”
The current study used MR to investigate the effect of genetically proxied lean mass on the risk of AD and the “related phenotype” of cognitive performance.
Genetic proxy
As genetic proxies for lean mass, the researchers chose single nucleotide polymorphisms (genetic variants) that were associated, in a genome-wide association study (GWAS), with appendicular lean mass.
Appendicular lean mass “more accurately reflects the effects of lean mass than whole body lean mass, which includes smooth and cardiac muscle,” the authors explained.
This GWAS used phenotypic and genetic data from 450,243 participants in the UK Biobank cohort (mean age 57 years). All participants were of European ancestry.
The researchers adjusted for age, sex, and genetic ancestry. They measured appendicular lean mass using bioimpedance – an electric current that flows at different rates through the body, depending on its composition.
In addition to the UK Biobank participants, the researchers drew on an independent sample of 21,982 people with AD; a control group of 41,944 people without AD; a replication sample of 7,329 people with and 252,879 people without AD to validate the findings; and 269,867 people taking part in a genome-wide study of cognitive performance.
The researchers identified 584 variants that met criteria for use as genetic proxies for lean mass. None were located within the APOE gene region. In the aggregate, these variants explained 10.3% of the variance in appendicular lean mass.
Each standard deviation increase in genetically proxied lean mass was associated with a 12% reduction in AD risk (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.82-0.95; P < .001). This finding was replicated in the independent consortium (OR, 0.91; 95% CI, 0.83-0.99; P = .02).
The findings remained “consistent” in sensitivity analyses.
A modifiable risk factor?
Higher appendicular lean mass was associated with higher levels of cognitive performance, with each SD increase in lean mass associated with an SD increase in cognitive performance (OR, 0.09; 95% CI, 0.06-0.11; P = .001).
“Adjusting for potential mediation through performance did not reduce the association between appendicular lean mass and risk of AD,” the authors wrote.
They obtained similar results using genetically proxied trunk and whole-body lean mass, after adjusting for fat mass.
The authors noted several limitations. The bioimpedance measures “only predict, but do not directly measure, lean mass.” Moreover, the approach didn’t examine whether a “critical window of risk factor timing” exists, during which lean mass might play a role in influencing AD risk and after which “interventions would no longer be effective.” Nor could the study determine whether increasing lean mass could reverse AD pathology in patients with preclinical disease or mild cognitive impairment.
Nevertheless, the findings suggest “that lean mass might be a possible modifiable protective factor for Alzheimer’s disease,” the authors wrote. “The mechanisms underlying this finding, as well as the clinical and public health implications, warrant further investigation.”
Novel strategies
In a comment, Iva Miljkovic, MD, PhD, associate professor, department of epidemiology, University of Pittsburgh, said the investigators used “very rigorous methodology.”
The finding suggesting that lean mass is associated with better cognitive function is “important, as cognitive impairment can become stable rather than progress to a pathological state; and, in some cases, can even be reversed.”
In those cases, “identifying the underlying cause – e.g., low lean mass – can significantly improve cognitive function,” said Dr. Miljkovic, senior author of a study showing muscle fat as a risk factor for cognitive decline.
More research will enable us to “expand our understanding” of the mechanisms involved and determine whether interventions aimed at preventing muscle loss and/or increasing muscle fat may have a beneficial effect on cognitive function,” she said. “This might lead to novel strategies to prevent AD.”
Dr. Daghlas is supported by the British Heart Foundation Centre of Research Excellence at Imperial College, London, and is employed part-time by Novo Nordisk. Dr. Miljkovic reports no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Investigators analyzed data on more than 450,000 participants in the UK Biobank as well as two independent samples of more than 320,000 individuals with and without AD, and more than 260,000 individuals participating in a separate genes and intelligence study.
They estimated lean muscle and fat tissue in the arms and legs and found, in adjusted analyses, over 500 genetic variants associated with lean mass.
On average, higher genetically lean mass was associated with a “modest but statistically robust” reduction in AD risk and with superior performance on cognitive tasks.
“Using human genetic data, we found evidence for a protective effect of lean mass on risk of Alzheimer’s disease,” study investigators Iyas Daghlas, MD, a resident in the department of neurology, University of California, San Francisco, said in an interview.
Although “clinical intervention studies are needed to confirm this effect, this study supports current recommendations to maintain a healthy lifestyle to prevent dementia,” he said.
The study was published online in BMJ Medicine.
Naturally randomized research
Several measures of body composition have been investigated for their potential association with AD. Lean mass – a “proxy for muscle mass, defined as the difference between total mass and fat mass” – has been shown to be reduced in patients with AD compared with controls, the researchers noted.
“Previous research studies have tested the relationship of body mass index with Alzheimer’s disease and did not find evidence for a causal effect,” Dr. Daghlas said. “We wondered whether BMI was an insufficiently granular measure and hypothesized that disaggregating body mass into lean mass and fat mass could reveal novel associations with disease.”
Most studies have used case-control designs, which might be biased by “residual confounding or reverse causality.” Naturally randomized data “may be used as an alternative to conventional observational studies to investigate causal relations between risk factors and diseases,” the researchers wrote.
In particular, the Mendelian randomization (MR) paradigm randomly allocates germline genetic variants and uses them as proxies for a specific risk factor.
MR “is a technique that permits researchers to investigate cause-and-effect relationships using human genetic data,” Dr. Daghlas explained. “In effect, we’re studying the results of a naturally randomized experiment whereby some individuals are genetically allocated to carry more lean mass.”
The current study used MR to investigate the effect of genetically proxied lean mass on the risk of AD and the “related phenotype” of cognitive performance.
Genetic proxy
As genetic proxies for lean mass, the researchers chose single nucleotide polymorphisms (genetic variants) that were associated, in a genome-wide association study (GWAS), with appendicular lean mass.
Appendicular lean mass “more accurately reflects the effects of lean mass than whole body lean mass, which includes smooth and cardiac muscle,” the authors explained.
This GWAS used phenotypic and genetic data from 450,243 participants in the UK Biobank cohort (mean age 57 years). All participants were of European ancestry.
The researchers adjusted for age, sex, and genetic ancestry. They measured appendicular lean mass using bioimpedance – an electric current that flows at different rates through the body, depending on its composition.
In addition to the UK Biobank participants, the researchers drew on an independent sample of 21,982 people with AD; a control group of 41,944 people without AD; a replication sample of 7,329 people with and 252,879 people without AD to validate the findings; and 269,867 people taking part in a genome-wide study of cognitive performance.
The researchers identified 584 variants that met criteria for use as genetic proxies for lean mass. None were located within the APOE gene region. In the aggregate, these variants explained 10.3% of the variance in appendicular lean mass.
Each standard deviation increase in genetically proxied lean mass was associated with a 12% reduction in AD risk (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.82-0.95; P < .001). This finding was replicated in the independent consortium (OR, 0.91; 95% CI, 0.83-0.99; P = .02).
The findings remained “consistent” in sensitivity analyses.
A modifiable risk factor?
Higher appendicular lean mass was associated with higher levels of cognitive performance, with each SD increase in lean mass associated with an SD increase in cognitive performance (OR, 0.09; 95% CI, 0.06-0.11; P = .001).
“Adjusting for potential mediation through performance did not reduce the association between appendicular lean mass and risk of AD,” the authors wrote.
They obtained similar results using genetically proxied trunk and whole-body lean mass, after adjusting for fat mass.
The authors noted several limitations. The bioimpedance measures “only predict, but do not directly measure, lean mass.” Moreover, the approach didn’t examine whether a “critical window of risk factor timing” exists, during which lean mass might play a role in influencing AD risk and after which “interventions would no longer be effective.” Nor could the study determine whether increasing lean mass could reverse AD pathology in patients with preclinical disease or mild cognitive impairment.
Nevertheless, the findings suggest “that lean mass might be a possible modifiable protective factor for Alzheimer’s disease,” the authors wrote. “The mechanisms underlying this finding, as well as the clinical and public health implications, warrant further investigation.”
Novel strategies
In a comment, Iva Miljkovic, MD, PhD, associate professor, department of epidemiology, University of Pittsburgh, said the investigators used “very rigorous methodology.”
The finding suggesting that lean mass is associated with better cognitive function is “important, as cognitive impairment can become stable rather than progress to a pathological state; and, in some cases, can even be reversed.”
In those cases, “identifying the underlying cause – e.g., low lean mass – can significantly improve cognitive function,” said Dr. Miljkovic, senior author of a study showing muscle fat as a risk factor for cognitive decline.
More research will enable us to “expand our understanding” of the mechanisms involved and determine whether interventions aimed at preventing muscle loss and/or increasing muscle fat may have a beneficial effect on cognitive function,” she said. “This might lead to novel strategies to prevent AD.”
Dr. Daghlas is supported by the British Heart Foundation Centre of Research Excellence at Imperial College, London, and is employed part-time by Novo Nordisk. Dr. Miljkovic reports no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Investigators analyzed data on more than 450,000 participants in the UK Biobank as well as two independent samples of more than 320,000 individuals with and without AD, and more than 260,000 individuals participating in a separate genes and intelligence study.
They estimated lean muscle and fat tissue in the arms and legs and found, in adjusted analyses, over 500 genetic variants associated with lean mass.
On average, higher genetically lean mass was associated with a “modest but statistically robust” reduction in AD risk and with superior performance on cognitive tasks.
“Using human genetic data, we found evidence for a protective effect of lean mass on risk of Alzheimer’s disease,” study investigators Iyas Daghlas, MD, a resident in the department of neurology, University of California, San Francisco, said in an interview.
Although “clinical intervention studies are needed to confirm this effect, this study supports current recommendations to maintain a healthy lifestyle to prevent dementia,” he said.
The study was published online in BMJ Medicine.
Naturally randomized research
Several measures of body composition have been investigated for their potential association with AD. Lean mass – a “proxy for muscle mass, defined as the difference between total mass and fat mass” – has been shown to be reduced in patients with AD compared with controls, the researchers noted.
“Previous research studies have tested the relationship of body mass index with Alzheimer’s disease and did not find evidence for a causal effect,” Dr. Daghlas said. “We wondered whether BMI was an insufficiently granular measure and hypothesized that disaggregating body mass into lean mass and fat mass could reveal novel associations with disease.”
Most studies have used case-control designs, which might be biased by “residual confounding or reverse causality.” Naturally randomized data “may be used as an alternative to conventional observational studies to investigate causal relations between risk factors and diseases,” the researchers wrote.
In particular, the Mendelian randomization (MR) paradigm randomly allocates germline genetic variants and uses them as proxies for a specific risk factor.
MR “is a technique that permits researchers to investigate cause-and-effect relationships using human genetic data,” Dr. Daghlas explained. “In effect, we’re studying the results of a naturally randomized experiment whereby some individuals are genetically allocated to carry more lean mass.”
The current study used MR to investigate the effect of genetically proxied lean mass on the risk of AD and the “related phenotype” of cognitive performance.
Genetic proxy
As genetic proxies for lean mass, the researchers chose single nucleotide polymorphisms (genetic variants) that were associated, in a genome-wide association study (GWAS), with appendicular lean mass.
Appendicular lean mass “more accurately reflects the effects of lean mass than whole body lean mass, which includes smooth and cardiac muscle,” the authors explained.
This GWAS used phenotypic and genetic data from 450,243 participants in the UK Biobank cohort (mean age 57 years). All participants were of European ancestry.
The researchers adjusted for age, sex, and genetic ancestry. They measured appendicular lean mass using bioimpedance – an electric current that flows at different rates through the body, depending on its composition.
In addition to the UK Biobank participants, the researchers drew on an independent sample of 21,982 people with AD; a control group of 41,944 people without AD; a replication sample of 7,329 people with and 252,879 people without AD to validate the findings; and 269,867 people taking part in a genome-wide study of cognitive performance.
The researchers identified 584 variants that met criteria for use as genetic proxies for lean mass. None were located within the APOE gene region. In the aggregate, these variants explained 10.3% of the variance in appendicular lean mass.
Each standard deviation increase in genetically proxied lean mass was associated with a 12% reduction in AD risk (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.82-0.95; P < .001). This finding was replicated in the independent consortium (OR, 0.91; 95% CI, 0.83-0.99; P = .02).
The findings remained “consistent” in sensitivity analyses.
A modifiable risk factor?
Higher appendicular lean mass was associated with higher levels of cognitive performance, with each SD increase in lean mass associated with an SD increase in cognitive performance (OR, 0.09; 95% CI, 0.06-0.11; P = .001).
“Adjusting for potential mediation through performance did not reduce the association between appendicular lean mass and risk of AD,” the authors wrote.
They obtained similar results using genetically proxied trunk and whole-body lean mass, after adjusting for fat mass.
The authors noted several limitations. The bioimpedance measures “only predict, but do not directly measure, lean mass.” Moreover, the approach didn’t examine whether a “critical window of risk factor timing” exists, during which lean mass might play a role in influencing AD risk and after which “interventions would no longer be effective.” Nor could the study determine whether increasing lean mass could reverse AD pathology in patients with preclinical disease or mild cognitive impairment.
Nevertheless, the findings suggest “that lean mass might be a possible modifiable protective factor for Alzheimer’s disease,” the authors wrote. “The mechanisms underlying this finding, as well as the clinical and public health implications, warrant further investigation.”
Novel strategies
In a comment, Iva Miljkovic, MD, PhD, associate professor, department of epidemiology, University of Pittsburgh, said the investigators used “very rigorous methodology.”
The finding suggesting that lean mass is associated with better cognitive function is “important, as cognitive impairment can become stable rather than progress to a pathological state; and, in some cases, can even be reversed.”
In those cases, “identifying the underlying cause – e.g., low lean mass – can significantly improve cognitive function,” said Dr. Miljkovic, senior author of a study showing muscle fat as a risk factor for cognitive decline.
More research will enable us to “expand our understanding” of the mechanisms involved and determine whether interventions aimed at preventing muscle loss and/or increasing muscle fat may have a beneficial effect on cognitive function,” she said. “This might lead to novel strategies to prevent AD.”
Dr. Daghlas is supported by the British Heart Foundation Centre of Research Excellence at Imperial College, London, and is employed part-time by Novo Nordisk. Dr. Miljkovic reports no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM BMJ MEDICINE