L‐carnitine for cognition in healthy subjects
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
The objective of this review is to assess the efficacy and safety of l‐carnitine to improve cognitive function or prevent cognitive decline in healthy subjects.
Background
Description of the condition
Cognitive functions, such as attention, perception, memory, and language, are affected by aging. Decline may be seen not only in patients with dementia and mild cognitive impairment (MCI), but also in older adults experiencing cognitive impairment that measurably exceeds their peers, and even in healthy people as they age. Although there is as yet no treatment that can delay or stop the deterioration of brain cells in dementia, there is evidence that some cases of MCI might be reversible, and prevention of dementia may be possible. Safe interventions which could improve cognitive function in older people or which could delay or prevent the onset of MCI or dementia would be very valuable.
Description of the intervention
L‐carnitine (the racemic form of carnitine) is an endogenous molecule, a quaternary ammonium compound synthesized from lysine or methionine. It is an important contributor to cellular energy metabolism. Although discovered in 1905, the crucial role of L‐carnitine in metabolism was not elucidated until 1955, and its deficiency was not described until 1972. The most significant source of L‐carnitine in human nutrition is meat, and humans also can synthesize L‐carnitine from dietary amino acids. It is produced by the body in the liver and kidneys and stored mainly in the most active metabolic tissue such as the skeletal muscles, heart, brain, and sperm. Although L‐carnitine is supplied exogenously and can be synthesized endogenously, both primary and secondary deficiencies do occur. Carnitine deficiency can be acquired or can be a result of inborn errors of metabolism (Stanley 2004). Pre‐term infants are at risk for carnitine deficiency due to impaired synthesis and insufficient renal tubular resorption (Evangeliou 2003). Secondary carnitine deficiency is not as rare and is most commonly associated with dialysis in chronic renal failure, although it can also be induced by intestinal resection, severe infection, and liver disease. Oral supplementation of L‐carnitine in individual dosages greater than 2 g appears to offer no advantage, since the mucosal absorption of carnitine appears to be saturated at about a 2‐g dose (Harper 1988). Maximum blood concentration is reached approximately 3.5 hours after an oral dose and slowly decreases, with a half‐life of about 15 hours (Bach 1983). Elimination of carnitine occurs primarily through the kidneys (Bach 1983). Carnitine and its bioavailable forms (l‐carnitine, acetyl‐l‐carnitine, propionyl‐l‐carnitine) have been proposed as a treatment, or as an adjunct to conventional medicine, for many conditions, including stable angina, intermittent claudication, diabetic neuropathy, kidney disease and dialysis, hyperthyroidism, male infertility, erectile dysfunction, chronic fatigue syndrome, as well as Alzheimer's disease and memory impairment.
How the intervention might work
1) L‐carnitine is involved in energy production.
L‐carnitine is a cofactor required for transformation of free long‐chain fatty acids into acylcarnitines, and for their subsequent transport into the mitochondrial matrix, where they undergo beta‐oxidation for cellular energy production. In the elderly, variations are found in the plasma concentration of L‐carnitine for unknown reasons. The concentration of carnitine actually increases with age until nearly 70 years old, subsequently tending to diminish in parallel with the reduction in body mass index and muscle mass (Malaguarnera 1999). Increasing L‐carnitine content might increase the rate of fatty acid oxidation, permitting a reduction of glucose utilization, preserving muscle glycogen content, and ensuring maximal rates of oxidative ATP production (Brass 1994a; Brass 1994b; Brass 1994c).
2) Improvement of cognitive function may be connected to processes influenced by the brain’s energy production.
In brain tissue, the L‐carnitine shuttle mediates translocation of the acetyl moiety from mitochondria into the cytosol and thus contributes to the synthesis of acetylcholine and of acetylcarnitine (Montgomery 2003; Nalecz 1996). Acetylcarnitine can modulate brain energy, phospholipid metabolism, synaptic morphology, and synaptic transmission, and can enhance the synthesis and release of cellular macromolecules (such as neurotrophic factors, neurohormones and multiple neurotransmitters) (Benton 2004; Pettegrew 2000; Virmani 2004), which may be helpful to improve cognitive function.
Why it is important to do this review
L‐carnitine has been reported to improve cognitive function in healthy subjects, but the evidence has not as yet been systematically reviewed. This systematic review of efficacy and safety aims to guide clinical practice.
Objectives
The objective of this review is to assess the efficacy and safety of l‐carnitine to improve cognitive function or prevent cognitive decline in healthy subjects.
Methods
Criteria for considering studies for this review
Types of studies
All relevant randomized controlled trials (RCTs), parallel‐group or crossover, will be eligible for inclusion without language restrictions.
Types of participants
Cognitively healthy subjects of any age and either gender.
We will exclude patients with a diagnosis of MCI or dementia or other significant illnesses associated with cognitive impairment (such as depression or schizophrenia).
Types of interventions
L‐carnitine and its derivative, acetyl‐l‐carnitine or propionyl‐l‐carnitine, at any dose and for any length of treatment versus placebo or no treatment.
We will investigate the following treatment comparisons.
(1) L‐carnitine (acetyl‐l‐carnitine, propionyl‐l‐carnitine) alone compared with placebo.
(2) L‐carnitine (acetyl‐l‐carnitine, propionyl‐l‐carnitine) alone compared with no treatment.
Types of outcome measures
Primary outcomes
(1) Incidence of MCI or dementia.
(2) Cognitive function (e.g. memory, concentration, immediate recall, calculation, speed of processing) as measured by psychometric tests such as Mini‐Mental State Examination (MMSE), Randt Memory Test (RMT), Cognitive Subsection of the Alzheimer's disease Scale (ADAS‐Cog) or other single domain or global cognitive scales.
Secondary outcomes
Quality of life measured with a validated scale.
Incidence and severity of adverse effects.
Search methods for identification of studies
We will search for all RCTs of l‐carnitine for cognition, irrespective of any language restrictions.
Electronic searches
We will search ALOIS (www.medicine.ox.ac.uk/alois) ‐ the Cochrane Dementia and Cognitive Improvement Group’s Specialized Register. The search terms used will be: "l‐carnitine" or "acetyl‐l‐carnitine" or "propionyl‐l‐carnitine" or "ALC" or "PLC" or "ALCAR" or ''ALPAR"
ALOIS is maintained by the Trials Search Co‐ordinator and contains dementia and cognitive improvement studies identified from:
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Monthly searches of a number of major healthcare databases: MEDLINE, EMBASE, CINAHL, PsycINFO and LILACS
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Monthly searches of a number of trial registers: meta Register of Controlled Trials; Umin Japan Trial Register; WHO portal (which covers ClinicalTrials.gov; ISRCTN; Chinese Clinical Trials Register; German Clinical Trials Register; Iranian Registry of Clinical Trials and the Netherlands National Trials Register, plus others)
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Quarterly search of The Cochrane Library’s Central Register of Controlled trials (CENTRAL)
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Monthly searches of a number of grey literature sources: ISI Web of knowledge Conference Proceedings; Index to Theses; Australasian Digital Theses
To view a list of all sources searched for ALOIS see About ALOIS on the ALOIS website.
We will run additional separate searches in many of the above sources to ensure that the most up‐to‐date results are retrieved. We have included the search strategy that we will use for the retrieval of reports of trials from MEDLINE (via the Ovid SP platform) in Appendix 1.
Searching other resources
We will check the references of published studies to identify additional trials.We will also review the bibliographies of the RCTs identified, contact the authors and known experts in the field and pharmaceutical companies to identify additional published or unpublished data.
Data collection and analysis
Selection of studies
Two review authors (Mi Yang and Muke Zhou) will independently scrutinize titles and abstracts identified from the register. The two authors will obtain the full text of all potentially relevant studies for independent assessment, and will then decide which trials fit the inclusion criteria. When there are disagreements about inclusion criteria, the two authors will discuss the discrepancy carefully. A third review author (Li He) will help to arbitrate if there is a failure in resolving disagreement.
Data extraction and management
Two authors (Mi Yang and Muke Zhou) will independently extract data from the trials to fill in a data extraction form. It should include the study name, type of design, study population size, duration, number of participant withdrawals, participants analyzed in the different treatment groups, inclusion and exclusion criteria, intervention (route and dosage), and outcomes. One author (Mi Yang) will enter data into Review Manager (RevMan 5) and a second author (Muke Zhou) will check the data entry.
Assessment of risk of bias in included studies
The assessment of risk of bias will take into account the security of randomization, allocation concealment, blinding, completeness of outcome data, selective outcome reporting, and any other potential sources of bias. Two authors (N Chen and M Yang) will assess these items independently according to The Cochrane Collaboration's standard scheme (Higgins 2008). Then we will judge all trials for each item and subdivide into the following three categories.
A. Low risk of bias for all key domains: low risk of bias.
B. Unclear risk of bias for one or more key domains: unclear risk of bias.
C. High risk of bias for one or more key domains: high risk of bias.
According to the method of assessing risk of bias in cross‐over trials (Higgins 2008), we intend to evaluate the following items for included cross‐over trials: (i) whether the cross‐over design is suitable; (ii) whether there is a carry‐over effect; (iii) whether only first period data are available; (iv) incorrect analysis; and (v) comparability of results with those from parallel‐group trials.
Measures of treatment effect
We will undertake the task of analyzing the data by using Cochrane RevMan 5 software (RevMan 2008). We will calculate a weighted treatment effect using a fixed‐effect model across trials unless there is substantial heterogeneity, in which case we will use a random‐effects approach. We will express results as risk ratios (RRs) with 95% confidence intervals (CIs) for dichotomous outcomes and as mean differences (MDs) for continuous outcomes. If studies use differing follow‐up periods, we will define different periods of follow‐up and perform separate analyses.
Unit of analysis issues
We will include only studies randomizing individuals. We may include crossover trials as long as either first‐period data or data taking account of the crossover design are available. If a study includes repeated measures of the same outcome, then we will define several outcomes based on different periods of follow‐up and perform separate analyses (Higgins 2008). If studies compare more than two intervention groups, then we will select the most relevant pair of intervention groups to include in the analyses.
Dealing with missing data
1. We will contact the original investigators to request missing data whenever possible.
2. When we can assume data to be missing at random, we will analyze only the available data; when we cannot assume that data are missing at random, we will impute the missing data with replacement values to last observation carried forward if sufficient data are available for analyses.
3. We will perform sensitivity analyses to assess how sensitive results are to reasonable changes in the assumptions that are made.
4. We will address the potential impact of missing data on the findings of the review in the Discussion section.
Assessment of heterogeneity
We will assess heterogeneity amongst trials by using the Chi2 test with a 10% level of statistical significance (P < 0.1) and I2 > 50% (Higgins 2002; Higgins 2003). If significant heterogeneity is present, we will perform a cause analysis, and then undertake subgroup and sensitivity analyses. If there is still unexplained heterogeneity, we will combine the study results using a random‐effects model. For trials that are clinically heterogeneous or present insufficient information for pooling, we will perform a descriptive analysis (Higgins 2008).
Assessment of reporting biases
We will use a funnel plot to investigate the possibility of publication bias if there are sufficient numbers of included studies. Then we will evaluate and express the possible reporting biases.
Data synthesis
We will perform meta‐analyses of the studies, reported on the efficacy of l‐carnitine for cognition, in which the results will be displayed as a forest plot. We will include only trials that provided a measure of effect size. We will also undertake descriptive analyses of other included trials.
Subgroup analysis and investigation of heterogeneity
We will carry out subgroup analyses to explore different derivative form of l‐carnitine, as l‐carnitine, acetyl‐l‐carnitine and propionyl‐l‐carnitine.
Sensitivity analysis
We will also undertake a sensitivity analysis on the basis of methodological quality by repeating the calculation after omitting the trials with low scores on individual quality items (i.e. excluding trials at high risk of bias as defined above). We will perform sensitivity analysis to assess how sensitive results are to reasonable changes in the assumptions made for imputing missing data too.
