Greater Muscle Strength Means Better Cognitive Function for Older People

Summary: A new study reports greater muscle strength is associated with better cognitive function in older adults. However, handgrip strength was not associated with improved cognitive function.

Source: University of Eastern Finland.

Greater muscle strength is associated with better cognitive function in ageing men and women, according to a new Finnish study. The association of extensively measured upper and lower body muscle strength with cognitive function was observed, but handgrip strength was not associated with cognitive function. Cognition refers to brain functions relating to receiving, storing, processing and using information. The findings were published in European Geriatric Medicine.

The study population comprised 338 men and women with an average age of 66 years. Their muscle strength was measured utilising handgrip strength, three lower body exercises such as leg extension, leg flexion and leg press and two upper body exercises such as chest press and seated row. Sum scores to depict lower body and upper body muscle strength were calculated separately, and cognitive function was assessed using the CERAD neuropsychological test battery with calculated total score.

Handgrip strength is relatively easy and fast to measure, and it has been widely used as a measure of muscle strength in various studies. However, this new study could not demonstrate an association between muscle strength and cognitive function when using a model based on mere handgrip strength and age. Instead, an association between muscle strength and cognitive function was observed only when sum scores depicting upper or lower body muscle strength were included in the model.

“The findings suggest that it may be justified to go beyond the handgrip and to include the upper and lower body when measuring muscle strength, as this may better reflect the association between muscle strength and cognition,” says Early Stage Researcher Heikki Pentikäinen, the first author of the article, who is currently preparing a PhD thesis on the topic for the University of Eastern Finland.

Image shows a brain.

Exercise is known to have various health benefits, and strength training is a way for practically everyone to increase muscle mass and enhance muscle strength. However, the association of muscle strength with various aspects of cognitive function is a relatively under-researched area. The study provided new insight into the methodology of measuring muscle strength and into the role of muscle strength in cognitive function. The study constituted part of the extensive, population-based DR’s EXTRA study, which was a four-year randomised and controlled intervention study analysing the effects of exercise and nutrition on endothelial function, atherosclerosis and cognition. The study was carried out at Kuopio Research Institute of Exercise Medicine in 2005-2011 and it involved more than 1,400 men and women living in the eastern part of Finland.

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Source: Heikki Pentikäinen – University of Eastern Finland
Image Source: NeuroscienceNews.com image is in the public domain.
Original Research: Abstract for “Muscle strength and cognition in ageing men and women: The DR’s EXTRA study” by H. Pentikäinen, K. Savonen, P. Komulainen, V. Kiviniemi, T. Paajanen, M. Kivipelto, H. Soininen, and R. Rauramaa in European Geriatric Medicine. Published online May 11 2017 doi:10.1016/j.eurger.2017.04.004

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Abstract

Muscle strength and cognition in ageing men and women: The DR’s EXTRA study

Handgrip strength (HS) has been widely used as a measure of muscle strength in prospective studies examining the association between strength and cognitive impairment. Lower HS has been independently associated with deeper decline in cognition over time but contradictory results also exist. HS is simple and quick to measure but caution is required when generalising HS as a predictor of the global muscle strength.

“Muscle strength and cognition in ageing men and women: The DR’s EXTRA study” by H. Pentikäinen, K. Savonen, P. Komulainen, V. Kiviniemi, T. Paajanen, M. Kivipelto, H. Soininen, and R. Rauramaa in European Geriatric Medicine. Published online May 11 2017 doi:10.1016/j.eurger.2017.04.004

Neuromuscular disease

Neuromuscular disease is a very broad term that encompasses many diseases and ailments that impair the functioning of the muscles, either directly, being pathologies of the voluntary muscle, or indirectly, being pathologies of nerves or neuromuscular junctions.[1][2]

Neuromuscular diseases are those that affect the muscles and/or their direct nervous system control, problems with central nervous control can cause either spasticity or some degree of paralysis (from both lower and upper motor neuron disorders), depending on the location and the nature of the problem. Some examples of central disorders include cerebrovascular accident, Parkinson’s disease, multiple sclerosis, Huntington’s disease and Creutzfeldt–Jakob disease. Spinal muscular atrophies are disorders of lower motor neuron while amyotrophic lateral sclerosis is a mixed upper and lower motor neuron condition.[medical citation needed]

Symptoms/signs

Symptoms of neuromuscular disease may include the following:[1][3]

Causes

Neuromuscular disease can be caused by autoimmune disorders,[4] genetic/hereditary disorders [1] and some forms of the collagen disorder Ehlers–Danlos Syndrome,[5] exposure to environmental chemicals and poisoning which includes heavy metal poisoning.[6] The failure of the electrical insulation surrounding nerves, the myelin, is seen in certain deficiency diseases, such as the failure of the body’s system for absorbing vitamin B-12[6]

Diseases of the motor end plate include myasthenia gravis, a form of muscle weakness due to antibodies against acetylcholine receptor,[7] and its related condition Lambert-Eaton myasthenic syndrome (LEMS).[8] Tetanus and botulism are bacterial infections in which bacterial toxins cause increased or decreased muscle tone, respectively.[9]Muscular dystrophies, including Duchenne’s and Becker’s, are a large group of diseases, many of them hereditary or resulting from genetic mutations, where the muscle integrity is disrupted, they lead to progressive loss of strength and decreased life span.[10]

Further causes of neuromuscular diseases are :

Polymyositis

Inflammatory muscle disorders

Tumors

Mechanism

In terms of the mechanism of neurological diseases, it depends on which one—whether it is amyotrophic lateral sclerosis, myasthenia gravis or some other NMD.[1]One finds that in muscular dystrophy (Duchenne), gene therapy might have promise as a treatment, since the mutation in a nonessential exon, can be improved via exon-skipping.[16]

Diagnosis

Nerve conduction velocity (study)

Diagnostic procedures that may reveal muscular disorders include direct clinical observations. This usually starts with the observation of bulk, possible atrophy or loss of muscle tone. Neuromuscular disease can also be diagnosed by testing the levels of various chemicals and antigens in the blood, and using electrodiagnostic medicine tests[17] including electromyography[18] (measuring electrical activity in muscles) and nerve conduction studies.[19]

In neuromuscular disease evaluation, it is important to perform musculoskeletal and neurologic examinations. Genetic testing is an important part of diagnosing inherited neuromuscular conditions.

Source: wiki

Mitochondrial function between the heart and skeletal muscles and biomarkers of Heart Failure

Heart failure (HF) is a chronic and devastating illness becoming an increasingly important burden on the health care system. Reduced exercise tolerance is an independent predictor of hospital readmission and mortality in patients with HF [1], and is thought to be a therapeutic target [2]. Although central factors such as ejection fraction (EF) or cardiac output do play a role, peripheral factors which include reduced skeletal muscle, an alteration in fiber type to one with less oxidative properties, and decreased ATP production, are mainly responsible for the reduction in exercise capacity [3]. From these findings, mitochondrial function is thought to be an important factor in the skeletal muscle in HF patients.

We recently reported that the retention of Technetium-99m sestamibi (99mTc-MIBI) correlated inversely with mitochondrial function in vivo and ex vivo in various organs [4]. 99mTc-MIBI is a lipophilic cation used for the clinical diagnosis of coronary artery disease. 99mTc-MIBI is transported to the myocardium via coronary blood flow, where it is rapidly incorporated into myocardial cells by diffusion, and binds to mitochondria [[4], [5]]. In clinical settings, the MIBI washout rate increased if mitochondrial dysfunction was present in HF patients [6]. Moreover, we and other groups demonstrated that mitochondrial functional assessment by 99mTc-MIBI was not organ-specific including the skeletal muscle [[4], [7], [8]].

To gain insight into the mechanisms underlying exercise intolerance in HF, we analyzed 99mTc-MIBI washout of the heart and leg muscles along with other clinical and cardiopulmonary exercise (CPX) parameters.

We studied 45 consecutive hospitalized patients with CHF treated for acute decompensation. CHF was defined by the Framingham criteria. Written informed consent was obtained from all patients, and the study conformed to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Institutional Review Board of Kitano Hospital. The exclusion criteria consisted of Killip class IV HF at the time of the study, acute myocardial infarction, and no consent. Echocardiographic data, levels of brain natriuretic peptide (BNP), the estimated glomerular filtration rate, C-reactive protein levels, and medical history were analyzed. A dose of 740 MBq (20 mCi) of 99mTc-MIBI was administered intravenously under resting conditions after an overnight fast. Planar images followed by single photon emission computed tomography images were obtained 20 min and 3 h after the injection for the calculation of the washout rate (Supplementary materials) [6].

All data are expressed as the mean ± standard deviation (SD). Differences between groups were compared using the Mann–Whitney U-test. The correlation analysis was carried out using the Pearson’s product-moment. A multiple general linear model in Poisson distribution by the likelihood-ratio chi-square test was used when the determinants of parameters were analyzed. In all tests, a value of p < 0.05 was considered significant.

Patient characteristics were as follows: 62% were male; 37% had dilated cardiomyopathy; 55% had hypertension; 24% had diabetes; the mean age was 68 years; the mean EF was 41%; the mean BNP level was 370 pg/mL; and the mean washout rate of the heart and the leg muscles was 46% and 30%, respectively. See details in Supplementary Table 1.

Fig. 1A and B show multiple scatter plots and correlation coefficient, respectively, of the variables. The 99mTc-MIBI washout of the heart and BNP and the washout of the heart and leg muscles were focused in Fig. 1C and D, respectively. A higher washout rate represents mitochondrial dysfunction. The washout rate of the heart inversely correlated to BNP level increase (Fig. 1C). 99mTc-MIBI washout rate of the heart positively correlated with the washout rate of the leg muscles (Fig. 1D), but not with left ventricular EF (Fig. 1A, pink circle). In multivariate regression analyses (Supplementary Table 2), the 99mTc-MIBI washout rate of the leg muscle and BNP levels were the factors that determined the washout rate of the heart.

Thumbnail image of Fig. 1. Opens large image

Fig. 1

Association between the MIBI washout rate of the heart and leg muscles (A). Multiple scatter plots of the variables. A red circle focused in panel C. A purple circle focused in panel D. A pink circle indicated the relationship between 99mTc-MIBI washout rate of the heart and left ventricular ejection fraction. (B) Pearson’s correlation coefficient. (C) BNP levels and 99mTc-MIBI washout rate of the heart and (D) 99mTc-MIBI washout rate of the heart and leg muscles. Line, linear correlation with standard deviation.

We analyzed data obtained from 22 patients who underwent CPX. Patients who underwent CPX were younger, but the other parameters were not significantly different from those who did not undergo CPX (Supplementary Fig. 2 and Table 3). PeakVO2 was negatively correlated with the 99mTc-MIBI washout of the leg muscles and weakly positively correlated with the length of the circumflex of the thigh (Fig. 2A ). Fig. 2B shows the relationship between peak oxygen consumption and 99mTc-MIBI washout of the leg muscles. Determinants of peak oxygen consumption in the subgroup were the 99mTc-MIBI washout of the leg and EF. Multi-collinearity was observed between the 99mTc-MIBI washout of the heart and leg muscles and the length of the circumflex of the thigh (Supplementary Table 4).

Thumbnail image of Fig. 2. Opens large image

Fig. 2

Association between the CPX parameters and the MIBI washout rate of the heart and leg muscles (A). Multiple scatter plots of the variables. (B) Peak oxygen consumption and 99mTc-MIBI washout rate of the leg muscles. Line, linear correlation with standard deviation.

The factors linking the heart and the leg muscle are currently unknown. Mechanisms involving sympathetic neural activation; cellular metabolism in the cardiac and skeletal muscles; inter-organ relationships such as anemia, chronic kidney disease, liver congestion, and depression; and inflammatory cytokines may contribute to the linkage between mitochondrial function of the heart and peripheral muscles in HF patients [9]. Brain-derived neurotrophic factor is involved in depression and is decreased in HF patients. It regulates skeletal muscle energy metabolism and is one of the linking factor candidates [10].

Muscle mass (i.e., circumflex of the thigh), in addition to the mitochondrial function of the legs, is the deciding factor for exercise capacity. In fact, a reduction in mitochondrial function and the inability to utilize oxygen delivered, i.e. low peripheral O2 extraction may contribute to the reduction in oxidative capacity. Thus, possible targets for exercise interventions to improve exercise intolerance in HF are not only the muscle’s mass but also the quality of the skeletal muscle [3].

There are several limitations. First, CPX was not done in all patients, and there were no CPX values in healthy controls. Second, we could not assess other markers of mitochondrial function or morphology of the heart and skeletal muscles as such analysis requires biopsy samples, which is beyond the scope of the study.

In summary, we demonstrated a clear correlation of mitochondrial function between the heart and skeletal muscles and biomarkers of HF.

Our results indicate that mitochondrial function of the leg muscle, along with the muscle volume, may limit exercise capacity in patients with CHF.

Alzheimer’s Disease Risk Factor Formula

ad genes.JPGAlzheimer’s Risk Factor, formula by Connie Dello Buono , ©12Sept2016

Assumption: Female, over 60yrs of age, on western diet, lives in Northern hemisphere, have families with cancer, diabetes and dementia, prone to allergies (lack zinc), digestive disorders, high dairy and sugar consumption (low magnesium and calcium,iron) and had used some medications in the past

Alzheimer’s Disease (AD) Factor = Blood sugar (0.2) + Blood Pressure (0.2) + Hard cheese and pork consumption (0.1) + Exercise and sun exposure (0.1) + number of medications (0.1) + stress level and brain concussions (0.1) + exposure to copper,fungus,molds,toxins (0.1) + genes (0.1)

  • AD Factor =1.0 (High)
  • AD Factor = <0.8 (Medium)
  • AD Factor = <0.5 (Low)

Please email your entries to motherhealth@gmail.com to create a database and get health data insights about Alzheimer’s disease. The link below contains the table in Microsoft Word. This data will also be used to track cancer, diabetes, lung disease, depression, mental health and heart disease.

Modified Alzheimer’s disease risk factor

Sex
Male = 0.05
Female =0.1
Age > 55yrs=0.1
< 55yrs = 0.05
Blood sugar
Normal/low =0

High = 0.1
Med =0.05

Blood Pressure
Normal/low=0
High = 0.1
Med =0.05
Exposure to copper,fungus,molds,toxins, smoking,alcohol,narcotics, aluminum, air pollution, medications > 5
(H,M,L)  0.2 = H,M = 0.1
Metabolic and diet:
Diabetes 0.1
Exercise and sun exposure, 3x per week = 0
No exercise = 0.1
Genes:
0.1 (combo of these genes) –
Aβ42 ;  presenilin 1 & 2 ; APP ;  CASS4  CELF1  FERMT2
HLA-DRB5, INPP5D,
MEF2C, NME8, PTK2B,
SORL1, ZCWPW1,SlC24A4,
CLU, PICALM, CR1, BIN1,
MS4A, ABCA7,
EPHA1, and CD2AP
Weak immune and metabolic system:
Infection and allergy 0.1

 

Stress level and brain concussions (H,M,L)
H = 0.1
L=0

alzheimer-factor

ad-factor

 

Join 25,000 people in helping redefine health with health concierge and precision medicine.

https://clubalthea.com/2016/10/14/your-complete-dna-sequence-will-help-shape-the-future-of-medicine/

 

 

Muscle health is brain health

Electrical impedance myography, or EIM, is a non-invasive technique for the assessment of muscle health that is based on the measurement of the electrical impedance characteristics of individual muscles or groups of muscles. The technique has been used for the purpose of evaluating neuromuscular diseases both for their diagnosis and for their ongoing assessment of progression or with therapeutic intervention. Muscle composition and microscopic structure change with disease, and EIM measures alterations in impedance that occur as a result of disease pathology.

EIM has been specifically recognized for its potential as an ALS biomarker (also known as a biological correlate or surrogate endpoint) by Prize4Life, a 501(c)(3) nonprofit organization dedicated to accelerating the discovery of treatments and cures for ALS. The $1M ALS Biomarker Challenge focused on identifying a biomarker precise and reliable enough to cut Phase II drug trials in half.

The prize was awarded to Dr. Seward Rutkove, chief, Division of Neuromuscular Disease, in the Department of Neurology at Beth Israel Deaconess Medical Center and Professor of Neurology at Harvard Medical School, for his work in developing the technique of EIM and its specific application to ALS. It is hoped that EIM as a biomarker will result in the more rapid and efficient identification of new treatments for ALS. EIM has shown sensitivity to disease status in a variety of neuromuscular conditions, includingradiculopathy,[4] inflammatory myopathy,[5] Duchenne muscular dystrophy,[6] and spinal muscular atrophy.[7]

In addition to the assessment of neuromuscular disease, EIM also has the prospect of serving as a convenient and sensitive measure of muscle condition. Work in aging populations[8] and individuals with orthopedic injuries[9] indicates that EIM is very sensitive to muscle atrophy and disuse and is conversely likely sensitive to muscle conditioning and hypertrophy.[10] Work on mouse and rats models, including a study of mice on board the final Space Shuttle mission (STS-135),[11] has helped to confirm this potential value.

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ALS

Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease and motor neurone disease (MND), is a specific disorder that involves the death of neurons that control voluntary muscles.[1][2][3][4] Some also use motor neuron disease for a group of five conditions of which ALS is the most common.[5] ALS is characterized by stiff muscles, muscle twitching, and gradually worsening weakness due to muscles decreasing in size.[6] This results in difficulty in speaking, swallowing, and eventually breathing.

Brawn and Brains

The scientists focused on the twins’ muscles rather than their exercise habits largely because the power measures were objective, unlike people’s notoriously unreliable recollections of how much they have worked out. (There was a correlation, though, between more self-reported exercise and sturdier legs.)

The scientists then asked the twins to visit a laboratory and repeat the cognitive tests.

Twenty of the identical twin pairs also completed brain-imaging scans.

Then the researchers compared leg power 10 years earlier with changes in brain function over the same time period.

They found that of the 324 twins, those who had had the sturdiest legs a decade ago showed the least fall-off in thinking skills, even when the scientists controlled for such factors as fatty diets, high blood pressure and shaky blood-sugar control.

The differences in thinking skills were particularly striking within twin pairs. If one twin had been more powerful than the other 10 years before, she tended to be a much better thinker now.

In fact, on average, a muscularly powerful twin now performed about 18 percent better on memory and other cognitive tests than her weaker sister.

Similarly, in the brain imaging of the identical twins, if one genetically identical twin had had sturdier legs than the other at the start of the study, she now displayed significantly more brain volume and fewer “empty spaces in the brain” than her weaker sister, Dr. Steves said.

Over all, among both the identical and fraternal twins, fitter legs were strongly linked, 10 years later, to fitter brains.