research essay on dementia

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Diagnosis and Management of Dementia: A Review

Zoe arvanitakis.

1 Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL.

2 Dept of Neurological Sciences, Rush University Medical Center, Chicago, IL.

Raj C. Shah

3 Dept of Family Medicine, Rush University Medical Center, Chicago, IL.

David A. Bennett

Collection, management, analysis, and interpretation of the data: Dr. Arvanitakis.

Preparation, review, or approval of the manuscript: Drs. Arvanitakis, Shah, and Bennett.

Decision to submit the manuscript for publication: Drs. Arvanitakis and Bennett.

Associated Data

Worldwide, 47 million people live with dementia and, by 2050, the number is expected to increase to 131 million.

Observations

Dementia is an acquired loss of cognition in multiple cognitive domains sufficiently severe to affect social or occupational function. In the US, Alzheimer’s disease (AD) affects 5.8 million people. However, dementia is commonly associated with more than one neuropathology, usually AD with cerebrovascular pathology. Diagnosing dementia requires a history evaluating for cognitive decline and impairment in daily activities, with corroboration from a close friend or family member, in addition to a moderately extended mental status examination by a clinician to delineate impairments in memory, language, attention, visuospatial cognition such as spatial orientation, executive function, and mood. Brief cognitive impairment screening questionnaires can assist in initiating and organizing the cognitive assessment. However, if the assessment is inconclusive (e.g., symptoms present, but normal examination), neuropsychological testing can help with a diagnosis. Physical examination may help identify the etiology of dementia. For example, focal neurologic abnormalities suggest stroke. Brain neuroimaging may demonstrate structural changes including, but not limited to, focal atrophy, infarcts, and tumor, that may not be identified on physical examination. Additional evaluation with cerebrospinal fluid assays or genetic testing should be considered in atypical dementia cases, such as age of onset under 65 years, rapid symptom onset, and/or impairment in multiple cognitive domains but not episodic memory. For treatment, patients benefit from non-pharmacologic approaches, including cognitively engaging activities such as reading, physical exercise such as walking, and socialization such as family gatherings. Pharmacologic approaches can provide modest symptomatic relief. For AD, this includes an acetylcholinesterase inhibitor such as donepezil for mild-to-severe dementia, and memantine (used alone or as an add-on therapy) for moderate-to-severe dementia. Rivastigmine is approved for the symptomatic treatment of Parkinson’s disease dementia.

Conclusions and Relevance

AD currently affects 5.8 million persons in the US, and is a common cause of dementia which is usually accompanied by other neuropathology. Causes of dementia can be diagnosed by medical history, cognitive and physical examination, laboratory testing, and brain imaging. Management should include both non-pharmacologic and pharmacologic approaches.

INTRODUCTION

Dementia is a common public health problem. 1 Worldwide, approximately 47 million people have dementia and this number is expected to increase to 131 million by 2050. 1 Reductions in age-adjusted incidence of dementia have occurred in the United States (US) and other developed countries over the last 20 years, perhaps associated with increasing formal educational attainment. However, without improved treatments or preventive therapy, the adverse consequences of dementia will continue to increase. 2

In the US, the prevalence of dementia is 15% in people older than 68 years. 3 Dementia is most commonly attributed to Alzheimer’s disease (AD), with over five million people currently affected by AD, and 13.8 million are projected to be affected by the year 2050. 4 AD is the 6 th leading cause of death, and the 5 th leading cause among persons older than 65 years. 5 , 6 This review summarizes diagnosis and management of dementia, defined as significant cognitive impairment in two or more cognitive domains.

We conducted a literature search in PubMed, using the search terms “dementia and (diagnosis or management)” in the title field. The following inclusion criteria were applied: a publication date from November 19, 2013 to June 29, 2019; English language; female or male sex; and “aged, 65 + years” (to exclude studies about less common causes of dementia). Original research studies with sample sizes less than 100 persons were excluded.

OBSERVATIONS

The search yielded 200 articles published in the past five and a half years. We excluded 37 studies with fewer than 100 persons, 52 on topics not relevant to this review, 41 about non-US public policy or practice, 20 about caregivers, 7 about pathology, 5 about medical record documentation or coding, and 11 that were not original research. The remaining 27 articles of original research, including 22 observational studies and 5 randomized clinical trials, informed this review.

Risk factors and Neuropathology

Aging is an important risk factor for all-cause dementia. AD affects 5–10% of people older than 65 years, and 50% of those 85 years old. 7 Non-modifiable risk factors for AD include female sex, Black race, Hispanic ethnicity, and genetic factors such as the apolipoprotein E ( APOE) gene. 8 – 13 Modifiable risk factors for all-cause dementia include hypertension and diabetes, diet, and limited cognitive, physical, and social activities. 14 – 18 Pathologically, “mixed dementia” is the most common form of dementia, found in 46% of persons with clinically diagnosed AD, and most commonly consisting of AD neurodegeneration and cerebrovascular disease. 19 Other neurodegenerative pathologies such as Lewy body disease (pathologically confirmed in 17% of cases) and frontotemporal lobar degeneration (in <5% of cases) are less frequent. 19 – 25

Definition and Characterization

Dementia is defined by chronic, acquired loss of two or more cognitive abilities caused by brain disease or injury ( Box 1 ). This definition has been used in clinical practice for decades, although recent changes in the Diagnostic Statistical Manual, 5 th Edition, have moved away from using the term dementia and have recognized that dementia can be present with impairment in a single domain (i.e. by this definition, a patient with a severe expressive aphasia could be classified as having dementia). 26 , 27 Memory requires the recording, storage, and retrieval of information. The most common clinical presentation of AD is a slow onset and gradually progressive loss of memory, typically with inability to learn new information and particularly autobiographical information, such as recent events in ones’ life. This is because AD preferentially affects brain networks involved in episodic memory. Examples of episodic memory loss include forgetting appointments, to pay bills or to take medication. Typically, a person with AD repeats questions and conversations. The memory loss is often accompanied by subjective memory complaints. Difficulty recalling names which are recalled later, is common in aging but is not a typical early sign of dementia. Mild cognitive impairment (MCI) is defined by performance that is lower than normal on objective neuropsychological testing of cognition, but with maintained daily functions (e.g., maintained abilities to function within society such as for daily activities at work, home, and in social settings, and maintained activities of daily living such as for personal care) and therefore not consistent with dementia ( Box 1 ). 28 MCI can be categorized into “amnestic” MCI, in which reduced performance on memory is the key finding, versus “non-amnestic” MCI, in which reduced cognitive performance is in a non-memory domain such as language. MCI can also be characterized into “single domain” versus “multi-domain” MCI, in which multiple cognitive performance measures are impaired. MCI does not always progress to dementia, and a patient’s cognitive status may become normal or fluctuate between MCI, normal cognition, and dementia. Fluctuations in cognition are also present in some conditions including neurodegenerative diseases (such as in early stages of Lewy body disease), cerebrovascular disease (e.g., intermittent small strokes), and psychiatric conditions (e.g., depression, anxiety), and with medications affecting cognition (e.g., opioids), and variability in cognitive test results.

Dementia is a clinical syndrome with variable manifestations ( Table 1 ), which help attribute the cause of dementia and guide management. While research studies have defined a “preclinical” AD, 27 , 29 in clinical care, AD is not diagnosed before symptom onset. Differentiating AD from other causes of dementia is easiest in the early stage of illness, as dementias in the late stage look similar ( Table 2 ). 30 – 34

Manifestations of dementia *

Clinical and pathologic characteristics differentiating select causes of dementia

Because mixed dementia is common, the evaluation focuses on identifying conditions likely to contribute to dementia ( Box 1 and Table 2 ). Cerebrovascular disease is the most frequent co-morbid condition with AD, and evidence of cerebrovascular disease does not reduce the likelihood of AD. However, approximately five percent of people with dementia show evidence of only cerebrovascular disease. After AD, the most common neurodegenerative dementias are Lewy body disease, characterized by chronic REM behavior disorder with early visuospatial impairment and parkinsonism, 21 , 22 , 32 , 33 and frontotemporal dementia, characterized by a behavioral variant (the most common presentation is disinhibition) or less often, a language impairment variant (such as a semantic dementia, in which the meaning of the patient’s speech is unclear; Table 2 ). 23 , 34

Diagnosis and Management

Clinical evaluations, differential diagnosis, and management of dementia most commonly occur in the primary care setting, with appropriate specialist input as needed.

Clinical Evaluation for Diagnosis

The 2014 US Preventive Services Task Force indicated that there was insufficient evidence to evaluate the balance of benefits and harms for universal screening for cognitive impairment using formal screening instruments in community-dwelling adults age 65 years and older. 35 While the Task Force concluded that adequate evidence existed for some screening tools that have sufficiently high sensitivity and specificity for identifying dementia, there is no published evidence of the effect of screening on decision making or planning by patients, clinicians, or caregivers. 35 However, report of memory complaints 36 – 38 or rapidly-progressive cognitive problems over several months may indicate an underlying medical condition that warrants further evaluation with cognitive, laboratory, and other tests. 39 – 40

Evaluation of possible dementia requires a brief medical history and a cognitive and neurologic examination ( Box 2 ). The history remains the most important diagnostic tool and should be obtained from both the patient and a close family member or friend. While some patients complain of forgetfulness, others are unable to recall details of their history and in some instances have anosognosia (i.e., lack of insight into one’s disease). One clue that a patient has a memory problem occurs when the person accompanying them provides the medical history. The history should characterize the nature, magnitude, and course of cognitive changes. The nature refers to the cognitive domains affected. Is there loss of episodic memory (e.g., what the patient did that morning, yesterday, and last week), or language abilities (e.g., word finding difficulties with circumlocutions)? The magnitude refers to the severity: does the cognitive loss affect daily functions, such as the patient’s ability to manage her own affairs (e.g., does she get lost while driving, not pay her bills, forget to take medications)? Is the course with an insidious onset and a slow progression (as in neurodegeneration) or a rapid onset and fluctuating and stepwise progression (as in cerebrovascular disease)? The history should focus on medical conditions that could affect cognition including vascular disease risk factors (such as hypertension and diabetes), existing brain conditions (such as stroke, Parkinson’s Disease, head trauma), and use of medications that can impair cognition (e.g., sleep aids and anxiolytics such as benzodiazepines; analgesics such as codeine containing agents; anticholinergics such as tricyclic antidepressants and bladder antimuscarinics). 41 , 42 A family history might identify young-onset dementia (onset in persons younger than 65 years) in first-degree relatives, suggesting one of the rare inherited genetic forms of dementia.

The cognitive examination identifies the presence, severity, and nature of cognitive impairment (e.g., memory versus language), and should consider cultural, linguistic, educational, and other factors such as anxiety and sleep deprivation. One commonly used screening tool is the Montreal Cognitive Assessment (MoCA; range 0–30, follow-up evaluation to screening recommended if score <24/30). The MoCA requires about 10 minutes to administer and is useful in early detection of cognitive impairment, including MCI with executive dysfunction. 43 The Mini-Mental State Exam was developed more than 4 decades ago. It is less sensitive to the presence of MCI and less thoroughly evaluates the domains of executive function, higher-level language skills, and complex visuospatial processing. 43 – 47

The neurologic examination evaluates for objective evidence of neurocognitive problems such as aphasia, apraxia, and agnosia. Unusual behaviors, such as disinhibition with hyperorality or hypersexuality, suggest a frontotemporal dementia, which comprises a group of uncommon conditions associated with neuronal loss beginning in the frontal and/or temporal regions of the brain while other areas are relatively spared. The examination may demonstrate focal neurologic signs or parkinsonism (e.g., as typically seen in the early stages of Lewy body disease). The routine evaluation also includes physical examination to identify systemic vascular disease and systemic signs which may be pertinent to rarer causes of dementia (e.g., golden-brown eye discoloration [Kayser-Fleischer rings] of Wilson’s disease).

The routine work-up typically includes a limited number of blood tests (e.g., B12 and TSH) and neuroimaging to identify cortical and hippocampal atrophy (as seen in AD), or neuropathology including potentially treatable causes of dementia (e.g., resectable tumor, or normal pressure hydrocephalus which may be shunted), using brain imaging with either MRI or CT ( Box 2 ). 48 – 53 Additional evaluation is sometimes warranted. For example, in highly-educated and highly-functioning individuals, a compelling history of cognitive decline (e.g., no longer able to perform a complex task which could easily be done a year ago, such as filling a tax return or working at a cognitively demanding job such as doctor or lawyer), can suggest dementia despite the presence of “normal” function on a brief, screening cognitive test. In this instance, referral for detailed neuropsychological testing should be considered to assess a broader range of cognitive abilities (e.g., memory, executive function, language, attention, visuospatial abilities) with increased levels of difficulty. 54

If the etiology of dementia is unclear after a brief history and examination, additional history and examination, and select blood, neurologic and medical tests should be considered ( Box 2 ).

Recent biomedical advances have led to additional tests that may be helpful in the differential diagnosis of dementia, in particular disease biomarkers which are still commonly used in research. 55 For a patient whose presentation is not consistent with AD (commonly called “atypical dementia”; see Supplemental Materials , eTable 1 ) and for patients in whom diagnostic certainty is low, clinicians may consider specialist referral and additional testing. Functional neuroimaging 56 such as positron emission tomography (PET) 57 can show changes suggestive of AD, usually asymmetric, bilateral temporal-parietal hypometabolism with routine tracers such as fluorodeoxyglucose (FDG) which has a sensitivity of 91% and a specificity of 85% for AD. 58 – 59 FDG PET, covered by health insurance for suspected frontotemporal dementia, may differentiate this etiology from AD, facilitating diagnosis of this less common cause of dementia. For patients with frontotemporal dementia, FDG PET typically shows decreased, asymmetric frontal lobe hypometabolism in the behavioral variant, and anterior temporal lobe hypometabolism in the language (semantic) variant. 60 Amyloid PET can also be used in patients with cognitive impairment who are evaluated for AD or other causes of cognitive decline. 58 – 59 , 61 In a recent observational, multisite, longitudinal study of Medicare beneficiaries, amyloid PET results were associated with change in management plans in more than 60% of patients, compared to pre-PET scan. Change in management plans consisted of change in AD medication or other medication therapy, and changes in counseling about safety and future planning. 62 However, there is no evidence that PET scan changes clinical outcomes. Functional neuroimaging with tau radioligands are only appropriate for research purposes. 63

Cerebrospinal fluid (CSF) testing may be considered to obtain evidence of AD (low amyloid and high tau levels), other neurodegenerative disease (e.g., elevated protein 14–3-3 for Creutzfeldt-Jakob disease) or other etiologies (e.g., positive cultures in infection, oligoclonal bands in demyelination; improved gait after high volume CSF removal in normal pressure hydrocephalus). 64 – 68 Genetic testing may be reasonable, usually for young patients with a history of first-degree relatives with young-onset dementia (e.g., parents or siblings with dementia in their fourth or fifth decade of life). Rare autosomal dominant forms of dementia (e.g., presenilin gene mutations) warrant genetic counseling to determine whether other family members need to be screened. 69 Assessment for the APOE genotype is not recommended for routine evaluation of AD because most people with AD dementia do not have either the protective ε2 allele or the ε4 allele (associated with increased risk) and, more importantly, because currently, medical management would not be altered by the test results. 8 Additional neurologic work-up, such as for amyotrophic lateral sclerosis and medical work-up, such as for cardiac, metabolic, and other etiologies, may be considered with particular attention to ruling out reversible causes of cognitive impairment such as psychiatric disorders (depression) and thyroid dysfunction (see Supplemental Materials , eTable 2 ). 70

The overall goals are to reduce suffering caused by the cognitive and accompanying symptoms (e.g., in mood and behavior), while delaying progressive cognitive decline. Both non-pharmacologic and pharmacologic approaches are used to achieve the overall goals.

Non-pharmacologic management

For complex manifestations of dementia, referrals to specialists, such as clinician managers (e.g., geriatric nurse practitioners), social workers, occupational or speech therapists, and others may be helpful. Evidence primarily from observational studies and a few randomized controlled trials suggest potential benefits of select non-pharmacologic approaches in dementia ( Box 3 ). Although data demonstrating benefit are limited, they are inexpensive and generally safe. Cognitive training and activities such as reading and playing cognitively engaging games (e.g., chess, bridge) may help maintain cognition and function, as shown in randomized trials. 71 – 73 However, frustration and stress from challenging tasks should be avoided. Music or art therapy, and other experiential approaches, may help maintain cognition or improve quality of life. 74 Because old memories of childhood are preserved the longest, reminiscence therapy, consisting of psychotherapy using the personal history of an individuals’ early-life stories and events, may improve psychological well-being. 75

Physical exercise, both aerobic (e.g., walking, swimming) and non-aerobic/conditioning (e.g., weights), improves cardiovascular health through benefits on blood pressure and stroke risk, and randomized trials suggest these interventions may positively affect cognitive and physical function. 76 – 78 But, not all randomized trials have shown benefits from exercise for cognition. 79 – 80 In a randomized clinical trial, a comprehensive sleep education training program reduced night-time awakenings, total time awake at night, and depressive symptoms over 6 months. 81 Social activities may be beneficial, including participating in birthday parties, holidays, support groups with cognitively impaired individuals, and interacting with trained pets (e.g., dog therapy). Eating a brain-healthy diet (e.g., nuts, berries, leafy greens, fish) or a Mediterranean diet is also suggested. 82 – 85 A randomized clinical trial found that a combined diet, exercise, cognitive training, and vascular risk monitoring intervention improved cognition in people at-risk for cognitive decline. 86 However, patients with moderate-to-severe dementia have difficulty participating in cognitive, physical, and social activities, and activities should be limited when patients can no longer participate safely and productively.

Day care centers and assisted living facilities may also be helpful for either the patient or caregiver, but may not delay nursing home admission. 87 A randomized trial of staff and persons in residential care facilities showed that a clinical protocol for behavioral and psychological symptoms of dementia used by staff, improved patients’ behavioral symptoms and staff stress. 86 In the terminal phase of dementia, palliative care may be helpful.

Clinical attention for the caregiver, often a close relative, is important. While efforts continue to effectively deliver primary care for dementia, 88 caregiver education and interventions may improve outcomes for patients with dementia, and inexpensive and useful information is available (See Supplemental Materials , eTable 3 ). Safety, including for the patient’s mental, physical, and financial well-being, should be monitored by the caregiver, with attention to home safety, such as risk of kitchen fires which may be associated with patient burns. 89 Other home safety measures include controlling medication intake, limiting access to firearms and other weapons, and monitoring for elder abuse. Safety outside the home includes at work, where the caregiver may facilitate the patient cutting back or stopping work, for instance if managing machinery or making decisions regarding a company’s finances. Also, driving may need to be modified, including limiting driving to neighborhood and daytime driving to prevent getting lost. While no single test is associated with better driving safety, driving ability should be re-assessed periodically and cessation recommended based on dementia severity, to prevent accidents and injuries. 90 The caregiver can assist in planning for health care and finances as soon as possible in the course of the illness, to determine advanced directives before late-stage dementia. 91 Educating the family on effective communication with a person with dementia, who eventually develop aphasia, is important. Similarly, family should be educated on promoting psychological health and socially adaptive behaviors (e.g., simple and clear instructions to encourage cooperation with activities to address physical and mental health needs, without inciting agitation or aggression).

Behavioral problems, such as physical aggression, are a main cause of emergency room visits and institutionalization, and are associated with poor outcomes for patients (e.g., psychological and medical complications) and families. 92 , 93 Caregiver interventions may prevent patient institutionalization. For example, the family can learn to recognize fear, frustration, and anger (e.g., yelling, lashing out), and address signs of aggression (e.g., by redirecting the patients’ attention to something they enjoy), potentially preventing negative outcomes. 94

An important consideration for families with a member who has dementia, is the high burden of caregiving. 95 This burden may be physical/medical (e.g., neglect of caregiver’s own health, with potential medical complications), emotional and psychological (stress, burnout, depression), and/or financial. Prevention, early recognition, and treatment of these issues (e.g., referrals to social work for additional support), are integral to an effective management plan. A randomized trial demonstrated that delivering caregiver assistance in-person versus by telephone only, both improved care quality and without differences in effectiveness. 96

Pharmacologic management

Table 3 shows the Food and Drug Administration (FDA) approved drugs for AD dementia. Five drugs, four of which are currently available for prescription, yield modest symptomatic benefit for cognitive symptoms. Acetylcholinesterase inhibitors were the first drugs approved in the US for AD. These drugs inhibit the brain acetylcholinesterase enzyme, thereby promoting relative increases in acetylcholine abundance at the synaptic cleft for cholinergic neurotransmission. In a meta-analysis review of 10 randomized, double blind, placebo controlled trials each with a six month duration of drug exposure, acetylcholinesterase inhibitors were associated with 2.4 points slower decline (95%CI −2.7 to −2.0; p<0.00001) in a research measure of cognition spanning 70 points. 97 This is equivalent to about 6 months of decline from natural history studies of AD dementia, but the magnitude of the clinically relevant benefit is uncertain. 35 Also, modest improvements were observed in activities of daily living and behaviors. The efficacy of anticholinesterase inhibitors is similar among the individual drugs (donepezil, rivastigmine, galantamine). 96 Given the modest benefits and known risks, clinicians should engage in shared decision making regarding the initiation of an acetylcholinesterase inhibitor for the symptomatic treatment of AD dementia. 90

Approved * pharmacologic treatments for dementia attributed to AD

Each drug shown in Table 3 is available for use orally, and one is also available for transdermal use (rivastigmine). A slow titration dosing regimen over 4–8 weeks is recommended to reach the target dose and minimize adverse effects for all of the drugs. Some drugs are used at different maintenance doses depending on effects/adverse effects. For example, donepezil maintenance can be at 5 mg (e.g., if higher dose is associated with poor tolerability), 10mg (typical target), or 23 mg (rarely used), once daily. Despite a slow titration, adverse effects, such as gastrointestinal (e.g., nausea, vomiting, and diarrhea; in about 5 percent of users) may occur ( Table 3 ). Adverse effects may be higher than previously recognized. 98 If encountered, dosage may be lowered (e.g., from 10 mg of donepezil to 5 mg), either temporarily (e.g., days to weeks) before re-escalating more slowly and monitoring for recurrence of adverse effects (family instructed to call clinician if adverse effects). Alternatively, the drug can be discontinued and a different drug can be prescribed even in the same class (another acetylcholinesterase inhibitor), given that adverse effects vary among same-class drugs. 99 Approximately 5 percent of patients discontinue the drug due to adverse effects. If tolerated, annual brief assessments using the history (e.g., progression of cognitive problems, new cognitive problems, functional status) and a brief cognitive test can be used in the absence of new problems. Often, clinicians cannot appreciate a benefit and must rely on caregiver reports. A good response to a drug would result in the caregiver noticing a slight improvement in day-to-day life (e.g., improved ability to function at home). Routine cognitive tests such as the MoCA, 43 can be used to monitor disease course on treatment, and to identify unexpected trends such as rapid decline which would prompt consideration for a medical evaluation (e.g., for systemic infection). However, benefits are typically not seen on such routine tests. Monitoring requires periodic re-evaluation of cognition, function, neuropsychiatric and behavioral symptoms, and medication reconciliation. 100 – 103

As neurodegeneration in AD progresses, further cognitive and functional decline invariably occur, and consideration should be given in the moderate-to-severe stages of dementia for adding memantine ( Table 3 ). Memantine can also be used as a first-line drug, for instance when a patient with moderate dementia presents for a first evaluation but is not taking any medication for cognition. Another use is for patients who cannot tolerate an acetylcholinesterase inhibitor. Adverse effects of memantine include headaches and constipation.

Aside from AD, few other dementia etiologies have approved pharmacologic treatments for cognitive symptoms, and no disease specific treatments exist for Lewy body disease or frontotemporal dementia. In addition to AD, rivastigmine has also received approval for Parkinson disease dementia. There are currently no FDA-approved drugs for MCI, 104 and studies of acetylcholinesterase inhibitors failed to show benefit in this population. 105 At this time, more than 100 drugs are being investigated for dementia and cognition, and include potential disease modifying agents. 106 – 107

Medical management should address common causes of cognitive impairment and dementia, including polypharmacy which affects a third of persons older than 60 years. 108 – 109 Special considerations may be appropriate for patients with medical comorbidities (e.g., kidney dysfunction). Another approach in dementia management is reducing brain ischemia and stroke risk by treating vascular risk factors (hypertension, diabetes, hyperlipidemia) and consideration of the risk-benefit ratio for anti-thrombotics and anticoagulants (if prior stroke or atrial fibrillation are present). A recent randomized clinical trial of dementia prevention showed that intensive blood pressure lowering in persons with hypertension (comparing a target systolic blood pressure below 120mmHg, to a pressure between 120–140mmHg) did not reduce risk of dementia, but did reduce the combined rate of MCI or probable dementia in a post-hoc analysis. 110

Dementia is often accompanied by neuropsychiatric and behavioral problems. About 95% of patients have at least mild symptoms, most commonly apathy (83%) and depression (63%). 111 Approved treatments do not exist for these non-cognitive manifestations in the setting of dementia. For depression, a low dose antidepressant can be tried such as with a selective serotonin-reuptake inhibitor (e.g., escitalopram). Management of agitation and aggression can be challenging. Conventional antipsychotics such as haloperidol, should be avoided. 112 Newer generation “atypical” antipsychotics such as risperidone and quetiapine fumarate, should be avoided if possible, given their association with serious risks, especially in older patients. 113 Specifically, death, cardiac effects such as heart failure, and stroke, have resulted in a black box warning. Therefore, antipsychotics should only be used in controlled environments (e.g., under close medical supervision) and for a limited time only (e.g., a few weeks) when all other non-pharmacologic approaches have failed or the patient’s behavior poses a substantial threat to themselves or others. 112

CONCLUSIONS

AD currently affects 5.8 million persons in the US, and is a common cause of dementia which is usually accompanied by other neuropathology. The cause of dementia can be diagnosed by medical history, cognitive and physical examination, laboratory testing, and brain imaging. Management should include both non-pharmacologic approaches with cognitive, physical, and social activities, and pharmacologic approaches such as with an acetylcholinesterase inhibitor for AD, although efficacy of treatments remains limited.

Supplementary Material

Supplemental material, acknowledgements.

This study was supported by the National Institutes of Health, grant numbers P30 AG010161, R01 AG040039, R01 NS084965, and RF1 AG059621; the Health Resources and Services Administration for HRSA-15-057; and the Illinois Department of Public Health. The study funders had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript, or decision to submit the manuscript for publication.

• Open access
• Published: 07 June 2024

Effects of intensive lifestyle changes on the progression of mild cognitive impairment or early dementia due to Alzheimer’s disease: a randomized, controlled clinical trial

• Dean Ornish 1 , 2 ,
• Catherine Madison 1 , 3 ,
• Miia Kivipelto 4 , 5 , 6 , 7 ,
• Colleen Kemp 8 ,
• Charles E. McCulloch 9 ,
• Douglas Galasko 10 ,
• Jon Artz 11 , 12 ,
• Dorene Rentz 13 , 14 , 15 ,
• Jue Lin 16 ,
• Kim Norman 17 ,
• Anne Ornish 1 ,
• Sarah Tranter 8 ,
• Nancy DeLamarter 1 ,
• Noel Wingers 1 ,
• Carra Richling 1 ,
• Rima Kaddurah-Daouk 18 ,
• Rob Knight 19 ,
• Daniel McDonald 20 ,
• Lucas Patel 21 ,
• Eric Verdin 22 , 23 ,
• Rudolph E. Tanzi 13 , 24 , 25 , 26 &
• Steven E. Arnold 13 , 27  

Alzheimer's Research & Therapy volume  16 , Article number:  122 ( 2024 ) Cite this article

Metrics details

Evidence links lifestyle factors with Alzheimer’s disease (AD). We report the first randomized, controlled clinical trial to determine if intensive lifestyle changes may beneficially affect the progression of mild cognitive impairment (MCI) or early dementia due to AD.

A 1:1 multicenter randomized controlled phase 2 trial, ages 45-90 with MCI or early dementia due to AD and a Montreal Cognitive Assessment (MoCA) score of 18 or higher. The primary outcome measures were changes in cognition and function tests: Clinical Global Impression of Change (CGIC), Alzheimer’s Disease Assessment Scale (ADAS-Cog), Clinical Dementia Rating–Sum of Boxes (CDR-SB), and Clinical Dementia Rating Global (CDR-G) after 20 weeks of an intensive multidomain lifestyle intervention compared to a wait-list usual care control group. ADAS-Cog, CDR-SB, and CDR-Global scales were compared using a Mann-Whitney-Wilcoxon rank-sum test, and CGIC was compared using Fisher’s exact test. Secondary outcomes included plasma Aβ42/40 ratio, other biomarkers, and correlating lifestyle with the degree of change in these measures.

Fifty-one AD patients enrolled, mean age 73.5. No significant differences in any measures at baseline. Only two patients withdrew. All patients had plasma Aβ42/40 ratios <0.0672 at baseline, strongly supporting AD diagnosis. After 20 weeks, significant between-group differences in the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and borderline significance in the ADAS-Cog test ( p = 0.053). CGIC, CDR Global, and ADAS-Cog showed improvement in cognition and function and CDR-SB showed significantly less progression, compared to the control group which worsened in all four measures. Aβ42/40 ratio increased in the intervention group and decreased in the control group ( p = 0.003). There was a significant correlation between lifestyle and both cognitive function and the plasma Aβ42/40 ratio. The microbiome improved only in the intervention group ( p <0.0001).

Conclusions

Comprehensive lifestyle changes may significantly improve cognition and function after 20 weeks in many patients with MCI or early dementia due to AD.

Trial registration

Approved by Western Institutional Review Board on 12/31/2017 (#20172897) and by Institutional Review Boards of all sites. This study was registered retrospectively with clinicaltrials.gov on October 8, 2020 (NCT04606420, ID: 20172897).

Increasing evidence links lifestyle factors with the onset and progression of dementia, including AD. These include unhealthful diets, being sedentary, emotional stress, and social isolation.

For example, a Lancet commission on dementia prevention, intervention, and care listed 12 potentially modifiable risk factors that together account for an estimated 40% of the global burden of dementia [ 1 ]. Many of these factors (e.g., hypertension, smoking, depression, type 2 diabetes, obesity, physical inactivity, and social isolation) are also risk factors for coronary heart disease and other chronic illnesses because they share many of the same underlying biological mechanisms. These include chronic inflammation, oxidative stress, insulin resistance, telomere shortening, sympathetic nervous system hyperactivity, and others [ 2 ]. A recent study reported that the association of lifestyle with cognition is mostly independent of brain pathology, though a part, estimated to be only 12%, was through β-amyloid [ 3 ].

In one large prospective study of adults 65 or older in Chicago, the risk of developing AD was 38% lower in those eating high vs low amounts of vegetables and 60% lower in those consuming omega-3 fatty acids at least once/week, [ 4 ] whereas consuming saturated fat and trans fats more than doubled the risk of developing AD [ 5 ].A systematic review and meta-analysis of 243 observational prospective studies and 153 randomized controlled trials found a similar relationship between these and similar risk factors and the onset of AD [ 6 ].

The multifactorial etiology and heterogeneity of AD suggest that multidomain lifestyle interventions may be more effective than single-domain ones for reducing the risk of dementia, and that more intensive multimodal lifestyle interventions may be more efficacious than moderate ones at preventing dementia [ 7 ].

For example, in the Finnish Geriatric Intervention Study (FINGER) study, a RCT of men and women 60-77 in age with Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk scores of at least 6 points and cognition at mean or slightly lower, a multimodal intervention of diet, exercise, cognitive training, vascular risk monitoring maintained cognitive function after 2 years in older adults at increased risk of dementia [ 8 ]. After 24 months, global cognition in the FINGER intervention group was 25% higher than in the control group which declined. Moreover, the FINGER intervention was equally beneficial regardless of several demographic and socioeconomic risk factors [ 9 ] and apolipoprotein E (APOE) ε4 status [ 10 ].

The FINGER lifestyle intervention also resulted in a 13-20% reduction in rates of cardiovascular disease events (stroke, transient ischemic attack, or coronary), providing more evidence that “what’s good for the heart is good for the brain”(and vice versa) [ 11 ]. Other large-scale multidomain intervention studies to determine if this intervention can help prevent dementia are being conducted or planned in over 60 countries worldwide, as part of the World-Wide FINGERS network, including the POINTER study in the U.S. [ 12 , 13 ].

More recently, a similar dementia prevention-oriented RCT showed that a 2-year personalized multidomain intervention led to modest improvements in cognition and dementia risk factors in those at risk for (but not diagnosed with) dementia and AD [ 14 ].

All these studies showed that lifestyle changes may help prevent dementia. The study we are reporting here is the first randomized, controlled clinical trial to test whether intensive lifestyle changes may beneficially affect those already diagnosed with mild cognitive impairment (MCI) or early dementia due to AD.

In two earlier RCTs, we found that the same multimodal lifestyle intervention described in this article resulted in regression of coronary atherosclerosis as measured by quantitative coronary arteriography [ 15 ] and ventricular function, [ 16 ] improvements in myocardial perfusion as measured by cardiac PET scans, and 2.5 times fewer cardiac events after five years, all of which were statistically significant [ 17 ]. Until then, it was believed that coronary heart disease progression could only be slowed, not stopped or reversed, similar to how MCI or early dementia due to AD are viewed today.

Since AD and coronary heart disease share many of the same risk factors and biological mechanisms, and since moderate multimodal lifestyle changes may help prevent AD, [ 18 ] we hypothesized that a more intensive multimodal intervention proven to often reverse the progression of coronary heart disease and some other chronic diseases may also beneficially affect the progression of MCI or early dementia due to AD.

We report here results of a randomized controlled trial to determine if the progression of MCI or early dementia due to AD may be slowed, stopped, or perhaps even reversed by a comprehensive, multimodal, intensive lifestyle intervention after 20 weeks when compared to a usual-care randomized control group. This lifestyle intervention includes (1) a whole foods, minimally processed plant-based diet low in harmful fats and low in refined carbohydrates and sweeteners with selected supplements; (2) moderate exercise; (3) stress management techniques; and (4) support groups.

This intensive multimodal lifestyle modification RCT sought to address the following questions:

Can the specified multimodal intensive lifestyle changes beneficially affect the progression of MCI or early dementia due to AD as measured by the AD Assessment Scale–Cognitive Subscale (ADAS-Cog), CGIC (Clinical Global Impression of Change), CDR-SB (Clinical Dementia Rating Sum of Boxes), and CDR-G (Clinical Dementia Rating Global) testing?

Is there a significant correlation between the degree of lifestyle change and the degree of change in these measures of cognition and function?

Is there a significant correlation between the degree of lifestyle change and the degree of change in selected biomarkers (e.g., the plasma Aβ42/40 ratio)?

Participants and methods

This study was a 1:1 multi-center RCT during the first 20 weeks of the study, and these findings are reported here. Patients who met the clinical trial inclusion criteria were enrolled between September 2018 and June 2022.

Participants were enrolled who met the following inclusion criteria:

Male or female, ages 45 to 90

Current diagnosis of MCI or early dementia due to AD process, with a MoCA score of 18 or higher (National Institute on Aging–Alzheimer’s Association McKhann and Albert 2011 criteria) [ 19 , 20 ]

Physician shared this diagnosis with the patient and approved their participation in this clinical trial

Willingness and ability to participate in all aspects of the intervention

Availability of spouse or caregiver to provide collateral information and assist with study adherence

Patients were excluded if they had any of the following:

Moderate or severe dementia

Physical disability that precludes regular exercise

Evidence for other primary causes of neurodegeneration or dementia, e.g., significant cerebrovascular disease (whose primary cause of dementia was vascular in origin), Lewy Body disease, Parkinson's disease, FTD

Significant ongoing psychiatric or substance abuse problems

Fifty-one participants with MCI or early-stage dementia due to AD who met these inclusion criteria were enrolled between September 2018 and June 2022 and underwent baseline testing. 26 of the enrolled participants were randomly assigned to an intervention group that received the multimodal lifestyle intervention for 20 weeks and 25 participants were randomly assigned to a usual habits and care control group that was asked not to make any lifestyle changes for 20 weeks, after which they would be offered the intervention. Patients in both groups received standard of care treatment managed by their own neurologist.

The intervention group received the lifestyle program for 20 weeks (initially in person, then via synchronous Zoom after March 2020 due to COVID-19). Two participants who did not want to continue these lifestyle changes withdrew during this time, both in the intervention group (one male, one female). Participants in both groups completed a follow-up visit at 20 weeks, where clinical and cognitive assessments were completed. Data were analyzed comparing the baseline and 20 week assessments between the groups.

In a drug trial, access to an investigational new drug can be restricted from participants in a randomized control group. However, we learned in our prior clinical trials of this lifestyle intervention with other diseases that it is often difficult to persuade participants who are randomly assigned to a usual-care control group to refrain from making these lifestyle changes for more than 20 weeks, which is why this time duration was chosen. If participants in both groups made similar lifestyle changes, then it would not be possible to show differences between the groups. Therefore, to encourage participants randomly assigned to the control group not to make lifestyle changes during the first 20 weeks, we offered to provide them the same lifestyle program at no cost to them for 20 weeks after being in the usual-care control group and tested after 20 weeks.

We initially planned to enroll 100 patients into this study based on power calculations of possible differences between groups in cognition and function after 20 weeks. However, due to challenges in recruiting patients, especially with the COVID-19 emergency and that many pharma trials began recruiting patients with similar criteria, it took longer to enroll patients than initially planned [ 21 ]. Because of this, we terminated recruitment after 51 patients were enrolled. This decision was based only on recruitment issues and limited funding, without reviewing the data at that time.

Patients were recruited from advertisements, presentations at neurology meetings, referrals from diverse groups of neurologists and other physicians, and a search of an online database of patients at UCSF. We put a special emphasis on recruiting diverse patients, although we were less successful in doing so than we hoped (Table 1 ).

This clinical trial was approved by the Western Institutional Review Board on 12/31/2017 (approval number: 20172897) and all participants and their study partners provided written informed consent. The trial protocol was also approved by the appropriate Institutional Review Board of all participating sites, and all subjects provided informed consent. Due to the COVID-19 emergency, planned MRI and amyloid PET scans were no longer feasible, and the number of cognition and function tests was decreased. An initial inclusion criterion of “current diagnosis of mild to moderate dementia due to AD (McKhann et al., 2011)” was further clarified to include a MoCA score of 18 or higher. This study was registered with clinicaltrials.gov on October 8, 2020 (NCT04606420, Unique Protocol ID: 20172897) retrospectively due to an administrative error. None of the sponsors who provided funding for this study participated in its design, conduct, management, or reporting of the results. Those providing the lifestyle intervention were separate from those performing testing and from those collecting and analyzing the data, who were blinded to group assignment. All authors contributed to manuscript draft revisions, provided critical comment, and approved submission for publication.

Any modifications in the protocol were approved in advance and in writing by the senior biostatistician (Charles McCulloch PhD) or the senior expert neuropsychologist (Dorene Rentz PsyD), and subsequently approved by the WIRB.

Patients were initially recruited only from the San Francisco Bay area beginning October 2018 and met in person until February 2020 when the COVID-19 pandemic began. Subsequently, this multimodal lifestyle intervention was offered to patients at home in real time via Zoom.

Offering this intervention virtually provided an opportunity to recruit patients from multiple sites, including the Massachusetts General Hospital/Harvard Medical School, Boston, MA; the University of California, San Diego; and Renown Regional Medical Center, Reno, NV, as well as with neurologists in the San Francisco Bay Area. These participants were recruited and tested locally at each site and the intervention was provided via Zoom and foods were sent directly to their home.

Patient recruitment

This is described in the Supplemental Materials section.

Intensive multimodal lifestyle intervention

Each patient received a copy of a book which describes this lifestyle medicine intervention for other chronic diseases. [ 2 ]

A whole foods minimally-processed plant-based (vegan) diet, high in complex carbohydrates (predominantly fruits, vegetables, whole grains, legumes, soy products, seeds and nuts) and especially low in harmful fats, sweeteners and refined carbohydrates. It was approximately 14-18% of calories as total fat, 16-18% protein, and 63-68% mostly complex carbohydrates. Calories were unrestricted. Those with higher caloric needs were given extra portions.

To assure the high adherence and standardization required to adequately test the hypothesis, 21 meals/week and snacks plus the daily supplements listed below were provided throughout the 40 weeks of this intervention to each study participant and his or her spouse or study partner at no cost to them. Twice/week, we overnight shipped to each patient as well as to their spouse or study partner three meals plus two snacks per day that met the nutritional guidelines as well as the prescribed nutritional supplements.

We asked participants to consume only the food and nutritional supplements we sent to them and no other foods. We reasoned that if adherence to the diet and lifestyle intervention was high, whatever outcomes we measured would be of interest. That is, if patients in the intervention group were adherent but showed no significant benefits, that would be a disappointing but an important finding. If they showed improvement, that would also be an important finding. But if they did not follow the lifestyle intervention sufficiently, then we would not have been able to adequately test the hypotheses.

Aerobic (e.g., walking) at least 30 minutes/day and mild strength training exercises at least three times per week from an exercise physiologist in person or with virtual sessions. Patients were given a personalized exercise prescription based on age and fitness level. All sessions were overseen by a registered nurse.

• Stress management

Meditation, gentle yoga-based poses, stretching, progressive relaxation, breathing exercises, and imagery for a total of one hour per day, supervised by a certified stress management specialist. The purpose of each technique was to increase the patient’s sense of relaxation, concentration, and awareness. They were also given access to online meditations. Patients had the option of using flashing-light glasses at a theta frequency of 7.83 Hz plus soothing music as an aid to meditation and insomnia [ 22 ]. They were also encouraged to get adequate sleep.

Group support

Participants and their spouses/study partners participated in a support group one hour/session, three days/week, supervised by a licensed mental health professional in a supportive, safe environment to increase emotional support and community as well as communication skills and strategies for maintaining adherence to the program. They also received a book with memory exercises used periodically during group sessions [ 23 ].

To reinforce this lifestyle intervention, each patient and their spouse or study partner met three times/week, four hours/session via Zoom: 2

one hour of supervised exercise (aerobic + strength training)

one hour of stress management practices (stretching, breathing, meditation, imagery)

one hour of a support group

one hour lecture on lifestyle

Additional optional exercise and stress management classes were provided.

Supplements

Omega-3 fatty acids with Curcumin (1680 mg omega-3 & 800 mg Curcumin, Nordic Naturals ProOmega CRP, 4 capsules/day). Omega-3 fatty acids: In those age 65 or older, those consuming omega-3 fatty acids once/week or more had a 60% lower risk of developing AD, and total intake of n-3 polyunsaturated fatty acids was associated with reduced risk of Alzheimer disease [ 24 ]. Curcumin targets inflammatory and antioxidant pathways as well as (directly) amyloid aggregation, [ 25 ] although there may be problems with bioavailability and crossing the blood-brain barrier [ 26 ].

Multivitamin and Minerals (Solgar VM-75 without iron, 1 tablet/day). Combinatorial formulations demonstrate improvement in cognitive performance and the behavioral difficulties that accompany AD [ 27 ].

Coenzyme Q10 (200 mg, Nordic Naturals, 2 soft gels/day). CoQ10. May reduce mitochondrial impairment in AD [ 28 ].

Vitamin C (1 gram, Solgar, 1 tablet/day): Maintaining healthy vitamin C levels may have a protective function against age-related cognitive decline and AD [ 29 ].

Vitamin B12 (500 mcg, Solgar, 1 tablet/day): B12 hypovitaminosis is linked to the development of AD pathology [ 30 ].

Magnesium L-Threonate (Mg) (144 mg, Magtein, 2 tablets/day). A meta-analysis found that Mg deficiency may be a risk factor of AD and Mg supplementation may be an adjunctive treatment for AD [ 31 ].

Hericium erinaceus (Lion’s Mane, Stamets Host Defense, 2 grams/day): Lion’s mane may produce significant improvements in cognition and function in healthy people over 50 [ 32 ] and in MCI patients compared to placebo [ 33 ].

Super Bifido Plus Probiotic (Flora, 1 tablet/day). A meta-analysis suggests that probiotics may benefit AD patients [ 34 ].

Primary outcome measures: cognition and function testing

Four tests were used to assess changes in cognition and function in these patients. These are standard measures of cognition and function included in many FDA drug trials: ADAS-Cog; Clinical Global Impression of Change (CGIC); Clinical Dementia Rating Sum of Boxes (CDR-SB); Clinical Dementia Rating Global (CDR Global). All cognition and function raters were trained psychometrists with experience in administering these tests in clinical trials. Efforts were made to have the same person perform cognitive testing at each visit to reduce inter-observer variability. Those doing ADAS-Cog assessments were certified raters and tested patients in person. The CGIC and CDR tests were administered for all patients via Zoom by different raters than the ADAS-cog. Also, raters were blind to treatment arm to the degree possible.

Secondary outcome measures: biomarkers and microbiome

These are described in the Supplemental Materials section. These include blood-based biomarkers (such as the plasma Aβ42/40 ratio) and microbiome taxa (organisms).

Statistical methods

These are described in the Supplemental Materials section.

The recruitment effort for this trial lasted from 01/23/2018 to 6/16/2022. The most effective recruitment method was referral from the subjects’ physician or healthcare provider. Additional recruitment efforts included advertising in print and digital media; speaking to community groups; mentioning the study during podcast and radio interviews; collaborating with research institutions that provide dementia diagnosis and treatment; and contracting a clinical trials recruitment service (Linea). A total of 1585 people contacted us; of these, 1300 did not meet the inclusion criteria, 102 declined participation, and 132 were screening incomplete when enrollment closed, resulting in the enrollment of 51 participants (Fig. 1 ).

CONSORT flowchart: patients, demographics, and enrollment

The remaining 51 patients were randomized to an intervention group (26 patients) that received the lifestyle intervention for 20 weeks or to a usual-care control group (25 patients) that was asked not to make any lifestyle changes. Two patients in the intervention group withdrew during the intervention because they did not want to continue the diet and lifestyle changes. No patients in the control group withdrew prior to 20-week testing. Analyses were performed on the remaining 49 patients. No patients were lost to follow-up.

All of these 49 patients had plasma Aβ42/40 ratios <0.089 (all were <0.0672), strongly supporting the diagnosis of Alzheimer’s disease [ 35 ].

At baseline, there were no statistically significant differences between the intervention group and the randomized control group in any measures, including demographic characteristics, cognitive function measures, or biomarkers (Table 1  and Table 2 ).

Cognition and function testing: primary analysis

Results after 20 weeks of a multimodal intensive lifestyle intervention in all patients showed overall statistically significant differences between the intervention group and the randomized control group in cognition and function in the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and of borderline significance in the ADAS-Cog test ( p = 0.053, Table 3 ). Three of these measures (CGIC, CDR Global, ADAS-Cog) showed improvement in cognition and function in the intervention group and worsening in the control group, and one test (CDR-SB) showed significantly less progression when compared to the randomized control group, which worsened in all four of these measures.

PRIMARY ANALYSIS (with outlier included), Table 3 :

CGIC (Clinical Global Impression of Change)

These scores improved in the intervention group and worsened in the control group.

(Fisher’s exact p -value = 0.001). 10 people in the intervention group showed improvement compared to none in the control group. 7 people in the intervention group and 8 people in the control group were unchanged. 7 people in the intervention group showed minimal worsening compared to 14 in the control group. None in the intervention group showed moderate worsening compared to 3 in the control group.

CDR-Global (Clinical Dementia Rating-Global)

These scores improved in the intervention group (from 0.69 to 0.65) and worsened in the randomized control group (from 0.66 to 0.74), mean difference = 0.12, p = 0.037 (Table 3 and Fig. 2 ).

Changes in CDR-Global (lower = improved)

ADAS-Cog (Alzheimer’s Disease Assessment Scale)

These scores improved in the intervention group (from 21.551 to 20.536) and worsened in the randomized control group (from 21.252 to 22.160), mean group difference of change = 1.923 points, p = 0.053 (Table 3 and Fig. 3 ). (ADAS-Cog testing in one intervention group patient was not administered properly so it was excluded.)

Changes in ADAS-Cog (lower = improved)

CDR-SB (Clinical Dementia Rating Sum of Boxes)

These scores worsened significantly more in the control group (from 3.34 to 3.86) than in the intervention group (from 3.27 to 3.35), mean group difference = 0.44, p = 0.032 (Table 3 and Fig. 4 ).

Changes in CDR-SB (lower = improved)

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups.

Secondary sensitivity analyses

One patient in the intervention group was a clear statistical outlier in his cognitive function testing based on standard mathematical definitions (none was an outlier in the control group) [ 36 ]. Therefore, this patient’s data were excluded in a secondary sensitivity analysis. These results showed statistically significant differences in all four of these measures of cognition and function (Table 4 ). Three measures (ADAS-Cog, CGIC, and CDR Global) showed significant improvement in cognition and function and one (CDR-SB) showed significantly less worsening when compared to the randomized control group, which worsened in all four of these measures.

Sensitivity analysis (with outlier excluded)

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups in either analysis.

A reason why this patient might have been a statistical outlier is that he reported intense situational stress before his testing. As a second sensitivity analysis, this same outlier patient was retested when he was calmer, and all four measures (ADAS-Cog, CGIC, CDR Global, and CDR-SB) showed significant improvement in cognition and function, whereas the randomized control group worsened in all four of these measures.

Biomarker results

We selected biomarkers that have a known role in the pathophysiology of AD (Table 5 ). Of note is that the plasma Aβ42/40 ratio increased in the intervention group but decreased in the randomized control group ( p = 0.003, two-tailed).

Correlation of lifestyle index and cognitive function

In the current clinical trial, despite the inherent limitations of self-reported data, we found statistically significant correlations between the degree of lifestyle change (from baseline to 20 weeks) and the degree of change in three of four measures of cognition and function as well as correlations between the adherence to desired lifestyle changes at just the 20-week timepoint and the degree of change in two of the four measures of cognition and function and borderline significance in the fourth measure.

Correlation with lifestyle at 20 weeks: p = 0.052; correlation: 0.241

Correlation with degree of change in lifestyle: p = 0.015; correlation: 0.317

Correlation with lifestyle at 20 weeks: p = 0.043; correlation: 0.251

Correlation with degree of change in lifestyle: p = 0.081; correlation: 0.205

Correlation with lifestyle at 20 weeks: p = 0.065; correlation: 0.221

Correlation with degree of change in lifestyle: p = 0.024; correlation: 0.286

Correlation with lifestyle at 20 weeks: p = 0.002

Correlation with degree of change in lifestyle: p = 0.0005

(CGIC tests are non-parametric analyses, so standard effect size calculations are not included for this measure.)

Also, we also found a significant correlation between dietary total fat intake and changes in the CGIC measure ( p = 0.001), but this was not significant for the other three measures.

Correlation of lifestyle index and biomarker data

In the current clinical trial, despite the inherent limitations of self-reported data, we found statistically significant correlations between the degree of lifestyle change (from baseline to 20 weeks) and the degree of change in many of the key biomarkers, as well as correlations between the degree of lifestyle change at 20 weeks and the degree of change in these biomarkers:

Plasma Aβ42/40 ratio

Correlation with lifestyle at 20 weeks: p = 0.035; correlation: 0.306

Correlation with degree of change in lifestyle: p = 0.068; correlation: 0.266

Correlation with lifestyle at 20 weeks: p = 0.011; correlation: 0.363

Correlation with degree of change in lifestyle: p = 0.007; correlation: 0.383

LDL-cholesterol

Correlation with lifestyle at 20 weeks: p < 0.0001; correlation: 0.678

Correlation with degree of change in lifestyle: p < 0.0001; correlation: 0.628

Beta-Hydroxybutyrate (ketones)

Correlation with lifestyle at 20 weeks: p = 0.013; correlation: 0.372

Correlation with degree of change in lifestyle: p = 0.034; correlation: 0.320

Correlation with lifestyle at 20 weeks: p = 0.228; correlation: 0.177

Correlation with degree of change in lifestyle: p = 0.135; correlation: 0.219

GFAP/glial fibrillary acidic protein

Correlation with lifestyle at 20 weeks: p = 0.096; correlation: 0.243

Correlation with degree of change in lifestyle: p =0.351; correlation: 0.138

What degree of lifestyle change is correlated with improvement in cognitive function tests?

What degree of lifestyle is needed to stop or improve the worsening of MCI or early dementia due to AD? In other words, what % of adherence to the lifestyle intervention was correlated with no change in MCI or dementia across both groups? Higher adherence than this degree of lifestyle change was associated with improvement in MCI or dementia.

Correlation with lifestyle at 20 weeks: 71.4% adherence

Correlation with lifestyle at 20 weeks: 120.6% adherence

CDR-Global:

Correlation with lifestyle at 20 weeks: 95.6%

Microbiome results

There was a significant and beneficial change in the microbiome configuration in the intervention group but not in the control group.

Several taxa (groups of microorganisms) that increased only in the intervention group were consistent with those involved in reduced AD risk in other studies. For example, Blautia, which increased during the intervention in the intervention group, has previously been associated with a lower risk of AD, potentially due to its involvement in increasing γ-aminobutyric acid (GABA) production [ 37 ].  Eubacterium also increased during the intervention in the intervention group, and prior studies have identified Eubacterium genera (namely Eubacterium fissicatena) as a protective factor in AD [ 38 ].

Also, there was a decrease in relative abundance of taxa involved in increased AD risk in the intervention group, e.g., Prevotella and Turicibacter , the latter of which has been associated with relevant biological processes such as 5-HT production. Prevotella and Turicibacter have previously been shown to increase with disease progression, [ 39 ] and these taxa decreased over the course of the intervention.

These results support the hypothesis that the lifestyle intervention may beneficially modify specific microbial groups in the microbiome: increasing those that lower the risk of AD and decreasing those that increase the risk of AD. (Please see Supplement for more detailed information.)

We report the first randomized, controlled trial showing that an intensive multimodal lifestyle intervention may significantly improve cognition and function and may allay biological features in many patients with MCI or early dementia due to AD after 20 weeks.

After 20 weeks of a multimodal intensive lifestyle intervention, results of the primary analysis when all patients were included showed overall statistically significant differences between the intervention group and the randomized control group in cognition and function as measured by the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and of borderline significance in the ADAS-Cog test ( p = 0.053).

Three of these measures (CGIC, CDR Global, ADAS-Cog) showed improvement in cognition and function in the intervention group and worsening in the randomized control group, and one test (CDR-SB) showed less progression in the intervention group when compared to the control group which worsened in all four of these measures.

These differences were even clearer in a secondary sensitivity analysis when a mathematical outlier was excluded. These results showed statistically significant differences between groups in all four of these measures of cognition and function. Three of these measures showed improvement in cognition and function and one (CDR-SB) showed less deterioration when compared to the randomized control group, which worsened in all four of these measures.

The validity of these changes in cognition and function and possible biological mechanisms of improvement is supported by the observed changes in several clinically relevant biomarkers that showed statistically significant differences in a beneficial direction after 20 weeks when compared to the randomized control group.

One of the most clinically relevant biomarkers is the plasma Aβ42/40 ratio, which increased by 6.4% in the intervention group and decreased by 8.3% in the randomized control group after 20 weeks, and these differences were statistically significant ( p = 0.003, two-tailed).

In the lecanemab trial, plasma levels of the Aβ42/40 biomarker increased in the intervention group over 18 months with the presumption that this reflected amyloid moving from the brain to the plasma [ 40 ]. We found similar results in the direction of change in the plasma Aβ42/40 ratio from this lifestyle intervention but in only 20 weeks. Conversely, this biomarker decreased in the control group (as in the lecanemab trial), which may indicate increased cerebral uptake of amyloid.

Other clinically relevant biomarkers also showed statistically significant differences (two-tailed) in a beneficial direction after 20 weeks when compared to the randomized control group. These include hemoglobin A1c, insulin, glycoprotein acetyls (GlycA), LDL-cholesterol, and β-Hydroxybutyrate (ketone bodies).

Improvement in these biomarkers provides more biological plausibility for the observed improvements in cognition and function as well as more insight into the possible mechanisms of improvement. This information may also help in predicting which patients are more likely to show improvements in cognition and function by making these intensive lifestyle changes.

Other relevant biomarkers were in a beneficial direction of change in the intervention group compared with the randomized control group after 20 weeks. These include pTau181, GFAP, CRP, SAA, and C-peptide. Telomere length increased in the intervention group and was essentially unchanged in the control group. These differences were not statistically significant even when there was an order of magnitude difference between groups (as with GFAP and pTau181) or an almost four-fold difference (as with CRP), but these changes were in a beneficial direction. At least in part, these findings may be due to a relatively small sample size and/or a short duration of only 20 weeks.

We found a statistically significant dose-response correlation between the degree of lifestyle changes in both groups (“lifestyle index”) and the degree of change in many of these biomarkers. This correlation was found in both the degree of change in lifestyle from baseline to 20 weeks as well as the lifestyle measured at 20 weeks. These correlations also add to the biological plausibility of these findings.

We also found a statistically significant dose-response correlation between the degree of lifestyle changes in both groups (“lifestyle index”) and changes in most measures of cognition and function testing. In short, the more these AD patients changed their lifestyle in the prescribed ways, the greater was the beneficial impact on their cognition and function. These correlations also add to the biological plausibility of these findings. This variation in adherence helps to explain in part why some patients in the intervention group improved and others did not, but there are likely other mechanisms that we do not fully understand that may play a role. These statistically significant correlations are especially meaningful given the greater variability of self-reported data, the relatively small sample size, and the short duration of the intervention.

These findings are consistent with earlier clinical trials in which we used this same lifestyle intervention and the same measure of lifestyle index and found significant dose-response correlations between this lifestyle index (i.e., the degree of lifestyle changes) and changes in the degree of coronary atherosclerosis (percent diameter stenosis) in coronary heart disease; [ 41 , 45 ] changes in PSA levels and LNCaP cell growth in men with prostate cancer; [ 42 ] and changes in telomere length [ 43 ].

We also found significant differences between the intervention and control groups in several taxa (groups of micro-organisms) in the microbiome which may be beneficial.

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups. Therefore, reduction in depression is unlikely to account for the overall improvements in cognition and function seen in the intervention group patients.

We also found that substantial lifestyle changes were required to stop the progression of MCI in these patients. In the primary analysis, this ranged from 71.4% adherence for ADAS-Cog to 95.6% adherence for CDR-Global to 120.6% adherence for CDR-SB. In other words, extensive lifestyle changes were required to stop or improve cognition and function in these patients. This helps to explain why other studies of less-intensive lifestyle interventions may not have been sufficient to stop deterioration or improve cognition and function.

For example, comparing these results to those of the MIND-AD clinical trial provides more biological plausibility for both studies [ 44 ]. That is, more moderate multimodal lifestyle changes may slow the rate of worsening of cognition and function in MCI or early dementia due to early-stage AD, whereas more intensive multimodal lifestyle changes may result in overall average improvements in many measures of cognition and function when compared to a randomized usual-care control group in both clinical trials.

Lifestyle changes may provide additional benefits to patients on drug therapy. Anti-amyloid antibodies have shown modest effects on slowing progression, but they are expensive, have potential for adverse events, are not yet widely available, and do not result in overall cognitive improvement [ 40 ]. Perhaps there may be synergy from doing both.

Limitations

This study has several limitations. Only 51 patients were enrolled and randomized in our study, and two of these patients (both in the intervention group) withdrew during the trial. Showing statistically significant differences across different tests of cognition and function and other measures despite the relatively small sample size suggests that the lifestyle intervention may be especially effective and has strong internal validity.

However, the smaller sample size limits generalizability, especially since there was much less racial and ethnic diversity in this sample than we strived to achieve. Also, we measured these differences despite the relative insensitivity of these measures, which might have increased the likelihood of a type II error.

Raters were blinded to the group assignment of the participants. However, unlike a double-blind placebo-controlled drug trial, it is not possible to blind subjects in a lifestyle intervention about whether or not they are receiving the intervention. This might have affected outcome measures, although to reduce positive expectations and because it was true, patients were told during the study that we did not know whether or not this lifestyle intervention would be beneficial, and we said that whatever we showed would be useful.

Also, 20 weeks is a relatively short time for any intervention with MCI or early dementia due to AD. We did not include direct measures of brain structure in this trial, so we cannot determine whether there were direct impacts on markers of brain pathology relevant to AD. However, surrogate markers such as the plasma Aβ42/40 ratio are becoming more widely accepted.

Not all patients in the intervention group improved. Of the 24 patients in the intervention group, 10 showed improvement as measured by the CGIC test, 7 were unchanged, and 7 worsened. In the control group, none improved, 8 were unchanged, and 17 worsened. In part, this may be explained by variations in adherence to the lifestyle intervention, as there was a significant relationship between the degree of lifestyle change and the degree of change in cognition and function across both groups. We hope that further research may further clarify other factors and mechanisms to help explain why cognition and function improved in some patients but not in others.

The findings on the degree of lifestyle change required to stop the worsening or improve cognition and function need to be interpreted with caution. Since data from both groups were combined, it was no longer a randomized trial for this specific analysis, so there could be unknown confounding influences. Also, it is possible that those with improved changes in cognition were better able to adhere to the intervention and thus have higher lifestyle indices.

In summary, in persons with mild cognitive impairment or early dementia due to Alzheimer’s disease, comprehensive lifestyle changes may improve cognition and function in several standard measures after 20 weeks. In contrast, patients in the randomized control group showed overall worsening in all four measures of cognition and function during this time.

The validity of these findings was supported by the observed changes in plasma biomarkers and microbiome; the dose-response correlation of the degree of lifestyle change with the degree of improvement in all four measures of cognition and function; and the correlation between the degree of lifestyle change and the degree of changes in the Aβ42/40 ratio and the changes in some other relevant biomarkers in a beneficial direction.

Our findings also have implications for helping to prevent AD. Newer technologies, some aided by artificial intelligence, enable the probable diagnosis of AD years before it becomes clinically apparent. However, many people do not want to know if they are likely to get AD if they do not believe they can do anything about it. If intensive lifestyle changes may cause improvement in cognition and function in MCI or early dementia due to AD, then it is reasonable to think that these lifestyle changes may also help to prevent MCI or early dementia due to AD. Also, it may take less-extensive lifestyle changes to help prevent AD than to treat it. Other studies cited earlier on the effects of these lifestyle changes on diseases such as coronary heart disease support this conclusion. Clearly, intensive lifestyle changes rather than moderate ones seem to be required to improve cognition and function in those suffering from early-stage AD.

These findings support longer follow-up and larger clinical trials to determine the longer-term outcomes of this intensive lifestyle medicine intervention in larger groups of more diverse AD populations; why some patients beneficially respond to a lifestyle intervention better than others besides differences in adherence; as well as the potential synergy of these lifestyle changes and some drug therapies.

Availability of data and materials

The datasets used and/or analyzed during the current study may be available from the corresponding author on reasonable request. Requesters will be asked to submit a study protocol, including the research question, planned analysis, and data required. The authors will evaluate this plan (i.e., relevance of the research question, suitability of the data, quality of the proposed analysis, planned or ongoing analysis, and other matters) on a case-by-case basis.

Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, Brayne C, Burns A, Cohen-Mansfield J, Cooper C, Costafreda SG, Dias A, Fox N, Gitlin LN, Howard R, Kales HC, Kivimäki M, Larson EB, Ogunniyi A, Orgeta V, Ritchie K, Rockwood K, Sampson EL, Samus Q, Schneider LS, Selbæk G, Teri L, Mukadam N. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413–46. https://doi.org/10.1016/S0140-6736(20)30367-6 . (Epub 2020 Jul 30. Erratum in: Lancet. 2023 Sep 30;402(10408):1132. PMID: 327389 PMCID: PMC7392084).

Article   PubMed   PubMed Central   Google Scholar  

Ornish D, Ornish A. UnDo It. New York: Ballantine Books; 2019.

Google Scholar  

Dhana K, Agarwal P, James BD, Leurgans SE, Rajan KB, Aggarwal NT, Barnes LL, Bennett DA, Schneider JA. Healthy Lifestyle and Cognition in Older Adults With Common Neuropathologies of Dementia. JAMA Neurol. 2024. https://doi.org/10.1001/jamaneurol.2023.5491 . Epub ahead of print. PMID: 38315471.

Morris MC, Evans DA, Tangney CC, Bienias JL, Wilson RS. Associations of vegetable and fruit consumption with age-related cognitive change. Neurology. 2006;67(8):1370–6. https://doi.org/10.1212/01.wnl.0000240224.38978.d8 . (PMID:17060562;PMCID:PMC3393520).

Article   CAS   PubMed   Google Scholar  

Morris MC, Evans DA, Bienias JL, Tangney CC, Bennett DA, Aggarwal N, Schneider J, Wilson RS. Dietary fats and the risk of incident Alzheimer disease. Arch Neurol. 2003;60(2):194–200. https://doi.org/10.1001/archneur.60.2.194 . (Erratum.In:ArchNeurol.2003Aug;60(8):1072 PMID: 12580703).

Article   PubMed   Google Scholar  

Yu JT, Xu W, Tan CC, Andrieu S, Suckling J, Evangelou E, Pan A, Zhang C, Jia J, Feng L, Kua EH, Wang YJ, Wang HF, Tan MS, Li JQ, Hou XH, Wan Y, Tan L, Mok V, Tan L, Dong Q, Touchon J, Gauthier S, Aisen PS, Vellas B. Evidence-based prevention of Alzheimer’s disease: systematic review and meta-analysis of 243 observational prospective studies and 153 randomised controlled trials. J Neurol Neurosurg Psychiatry. 2020;91(11):1201–9. https://doi.org/10.1136/jnnp-2019-321913 . (Epub 2020 Jul 20. PMID: 32690803; PMCID: PMC7569385).

Blumenthal JA, Smith PJ, Mabe S, Hinderliter A, Lin PH, Liao L, et al. Lifestyle and neurocognition in older adults with cognitive impairments: A randomized trial. Neurology. 2019;92(3):e212–23. https://doi.org/10.1212/WNL.0000000000006784 . (Epub 2018/12/21. PubMed PMID: 30568005; PubMed Central PMCID: PMCPMC6340382).

Ngandu T, Lehtisalo J, Solomon A, Levälahti E, Ahtiluoto S, Antikainen R, Bäckman L, Hänninen T, Jula A, Laatikainen T, Lindström J, Mangialasche F, Paajanen T, Pajala S, Peltonen M, Rauramaa R, Stigsdotter-Neely A, Strandberg T, Tuomilehto J, Soininen H, Kivipelto M. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. Lancet. 2015;385(9984):2255–63. https://doi.org/10.1016/S0140-6736(15)60461-5 . (Epub 2015 Mar 12 PMID: 25771249).

Rosenberg A, Ngandu T, Rusanen M, Antikainen R, Backman L, Havulinna S, et al. Multidomain lifestyle intervention benefits a large elderly population at risk for cognitive decline and dementia regardless of baseline characteristics: The FINGER trial. Alzheimers Dement. 2018;14(3):263–70. https://doi.org/10.1016/j.jalz.2017.09.006 . (Epub 2017/10/23. PubMed PMID: 29055814).

Solomon A, Turunen H, Ngandu T, Peltonen M, Levalahti E, Helisalmi S, et al. Effect of the apolipoprotein e genotype on cognitive change during a multidomain lifestyle intervention: a subgroup analysis of a randomized clinical trial. JAMA Neurol. 2018;75(4):462–70. https://doi.org/10.1001/jamaneurol.2017.4365 . (Epub 2018/01/23. PubMed PMID: 29356827; PubMed Central PMCID: PMCPMC5885273).

Lehtisalo J, Rusanen M, Solomon A, Antikainen R, Laatikainen T, Peltonen M, et al. Effect of a multi-domain lifestyle intervention on cardiovascular risk in older people: the FINGER trial. Eur Heart J. 2022. https://doi.org/10.1093/eurheartj/ehab922 . Epub 2022/01/21. PubMed PMID: 35051281.

Kivipelto M, Mangialasche F, Snyder HM, Allegri R, Andrieu S, Arai H, et al. World-Wide FINGERS Network: a global approach to risk reduction and prevention of dementia. Alzheimers Dement. 2020;16(7):1078–94. https://doi.org/10.1002/alz.12123 . (Epub 2020/07/07. PubMed PMID: 32627328).

Kivipelto M, Mangialasche F, Snyder H M, Allegri R, Andrieu S, Arai H, Baker L, Belleville S, Brodaty H, Brucki SM, Calandri I, Caramelli P, Chen C, Chertkow H, Chew E, Choi S H, Chowdhary N, Crivelli L, De La Torre R, Du Y, Dua T, Espeland M, Feldman H H, Hartmanis M, Hartmann T, Heffernan M, Henry C J, Hong C H, Håkansson K, Iwatsubo T, Jeong J H, Jimenez‐Maggiora G, Koo E H, Launer L J, Lehtisalo J, Lopera F, Martínez‐Lage P, Martins R, Middleton L, Molinuevo J L, Montero‐Odasso M, Moon S Y, Morales‐Pérez K, Nitrini R, Nygaard H B, Park Y K, Peltonen M, Qiu C, Quiroz Y T, Raman R, Rao N, Ravindranath V, Rosenberg A, Sakurai T, Salinas R M, Scheltens P, Sevlever G, Soininen H, Sosa A L, Suemoto C K, Tainta‐Cuezva M, Velilla L, Wang Y, Whitmer R, Xu X, Bain L J, Solomon A, Ngandu T, Carillo, M C. World‐Wide FINGERS Network: A global approach to risk reduction and prevention of dementia. Alzheimer's Dement. 2020, https://doi.org/10.1002/alz.12123 .

Yaffe K, Vittinghoff E, Dublin S, Peltz CB, Fleckenstein LE, Rosenberg DE, Barnes DE, Balderson BH, Larson EB. Effect of personalized risk-reduction strategies on cognition and dementia risk profile among older adults: the SMARRT randomized clinical trial. JAMA Intern Med. 2023:e236279. https://doi.org/10.1001/jamainternmed.2023.6279 . Epub ahead of print. PMID: 38010725; PMCID: PMC10682943

Ornish D, Scherwitz LW, Billings JH, Brown SE, Gould KL, Merritt TA, Sparler S, Armstrong WT, Ports TA, Kirkeeide RL, Hogeboom C, Brand RJ. Intensive lifestyle changes for reversal of coronary heart disease. JAMA. 1998;280(23):2001–7. https://doi.org/10.1001/jama.280.23.2001 . (Erratum.In:JAMA1999Apr21;281(15):1380 PMID: 9863851).

Ornish D, Scherwitz LW, Doody RS, Kesten D, McLanahan SM, Brown SE, DePuey E, Sonnemaker R, Haynes C, Lester J, McAllister GK, Hall RJ, Burdine JA, Gotto AM Jr. Effects of stress management training and dietary changes in treating ischemic heart disease. JAMA. 1983;249(1):54–9 (PMID: 6336794).

Gould KL, Ornish D, Scherwitz L, Brown S, Edens RP, Hess MJ, Mullani N, Bolomey L, Dobbs F, Armstrong WT, et al. Changes in myocardial perfusion abnormalities by positron emission tomography after long-term, intense risk factor modification. JAMA. 1995;274(11):894–901. https://doi.org/10.1001/jama.1995.03530110056036 . (PMID: 7674504).

Dhana K, Evans DA, Rajan KB, Bennett DA, Morris MC. Healthy lifestyle and the risk of Alzheimer dementia: Findings from 2 longitudinal studies. Neurology. 2020;95(4):e374–83. https://doi.org/10.1212/WNL.0000000000009816 . (Epub 2020 Jun 17. PMID: 32554763; PMCID: PMC7455318).

Article   CAS   PubMed   PubMed Central   Google Scholar  

McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):263–9. https://doi.org/10.1016/j.jalz.2011.03.005 . (Epub 2011 Apr 21. PMID: 21514250; PMCID: PMC3312024).

Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:270–9.

McDonald K, Seltzer E, Lu M, Gaisenband SD, Fletcher C, McLeroth P, Saini KS. Quantifying the impact of the COVID-19 pandemic on clinical trial screening rates over time in 37 countries. Trials. 2023;24(1):254. https://doi.org/10.1186/s13063-023-07277-1 . (PMID:37013558;PMCID:PMC10071259).

Tang HY, Vitiello MV, Perlis M, Mao JJ, Riegel B. A pilot study of audio-visual stimulation as a self-care treatment for insomnia in adults with insomnia and chronic pain. Appl Psychophysiol Biofeedback. 2014;39(3–4):219–25. https://doi.org/10.1007/s10484-014-9263-8 . (PMID:25257144;PMCID:PMC4221414).

Horsley K. Unlimited Memory. Granger Indiana: TCK Publishing; 2016.

Morris MC, Evans DA, Bienias JL, Tangney CC, Bennett DA, Wilson RS, et al. Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease. Arch Neurol. 2003;60(7):940–6. https://doi.org/10.1001/archneur.60.7.940 . (Epub 2003/07/23. PubMed PMID: 12873849).

Voulgaropoulou SD, van Amelsvoort T, Prickaerts J, Vingerhoets C. The effect of curcumin on cognition in Alzheimer’s disease and healthy aging: A systematic review of pre-clinical and clinical studies. Brain Res. 2019;1725:146476. https://doi.org/10.1016/j.brainres.2019.146476 . Epub 2019/09/29. PubMedPMID:31560864.

Ringman JM, Frautschy SA, Teng E, Begum AN, Bardens J, Beigi M, Gylys KH, Badmaev V, Heath DD, Apostolova LG, Porter V, Vanek Z, Marshall GA, Hellemann G, Sugar C, Masterman DL, Montine TJ, Cummings JL, Cole GM. Oral curcumin for Alzheimer’s disease: tolerability and efficacy in a 24-week randomized, double blind, placebo-controlled study. Alzheimers Res Ther. 2012;4(5):43. https://doi.org/10.1186/alzrt146 . (PMID:23107780;PMCID:PMC3580400).

Shea TB, Remington R. Nutritional supplementation for Alzheimer’s disease? Curr Opin Psychiatry. 2015;28(2):141–7. https://doi.org/10.1097/YCO.0000000000000138 . (Epub 2015/01/21. PubMed PMID: 25602242).

Pradhan N, Singh C, Singh A. Coenzyme Q10 a mitochondrial restorer for various brain disorders. Naunyn Schmiedebergs Arch Pharmacol. 2021;394(11):2197–222. https://doi.org/10.1007/s00210-021-02161-8 . (Epub 2021/10/02 PubMed PMID: 34596729).

Harrison FE. A critical review of vitamin C for the prevention of age-related cognitive decline and Alzheimer’s disease. J Alzheimers Dis. 2012;29(4):711–26. https://doi.org/10.3233/JAD-2012-111853 . (Epub 2012/03/01. PubMed PMID: 22366772; PubMed Central PMCID: PMCPMC3727637).

Lauer AA, Grimm HS, Apel B, Golobrodska N, Kruse L, Ratanski E, et al. Mechanistic Link between Vitamin B12 and Alzheimer's Disease. Biomolecules. 2022;12(1). https://doi.org/10.3390/biom12010129 . Epub 2022/01/22. PubMed PMID: 35053277; PubMed Central PMCID: PMCPMC8774227.

Du K, Zheng X, Ma ZT, Lv JY, Jiang WJ, Liu MY. Association of Circulating Magnesium Levels in Patients With Alzheimer’s Disease From 1991 to 2021: A Systematic Review and Meta-Analysis. Front Aging Neurosci. 2021;13:799824. https://doi.org/10.3389/fnagi.2021.799824 . (Epub 2022/01/28. PubMed PMID: 35082658; PubMed Central PMCID: PMCPMC8784804).

Saitsu Y, Nishide A, Kikushima K, Shimizu K, Ohnuki K. Improvement of cognitive functions by oral intake of Hericium erinaceus. Biomed Res. 2019;40(4):125–31. https://doi.org/10.2220/biomedres.40.125 . (Epub 2019/08/16. PubMed PMID: 31413233).

Mori K, Inatomi S, Ouchi K, Azumi Y, Tuchida T. Improving effects of the mushroom Yamabushitake (Hericium erinaceus) on mild cognitive impairment: a double-blind placebo-controlled clinical trial. Phytother Res. 2009;23(3):367–72. https://doi.org/10.1002/ptr.2634 . (Epub 2008/10/11. PubMed PMID: 18844328).

Xiang S, Ji JL, Li S, Cao XP, Xu W, Tan L, et al. Efficacy and Safety of probiotics for the treatment of alzheimer’s disease, mild cognitive impairment, and Parkinson’s Disease: a systematic review and meta-analysis. Front Aging Neurosci. 2022;14:730036. https://doi.org/10.3389/fnagi.2022.730036 . (Epub 2022/02/22. PubMed PMID: 35185522; PubMed Central PMCID: PMCPMC8851038).

Fogelman I, West T, Braunstein JB, Verghese PB, Kirmess KM, Meyer MR, Contois JH, Shobin E, Ferber KL, Gagnon J, Rubel CE, Graham D, Bateman RJ, Holtzman DM, Huang S, Yu J, Yang S, Yarasheski KE. Independent study demonstrates amyloid probability score accurately indicates amyloid pathology. Ann Clin Transl Neurol. 2023;10(5):765–78. https://doi.org/10.1002/acn3.51763 . (Epub 2023 Mar 28. PMID: 36975407; PMCID: PMC10187729).

Exploratory data analysis. John W. Tukey, 1977. Addison-Wesley, Reading MA. https://doi.org/10.1002/bimj.4710230408 .

Zhuang Z, Yang R, Wang W, Qi L, Huang T. Associations between gut microbiota and Alzheimer’s disease, major depressive disorder, and schizophrenia. J Neuroinflammation. 2020;17(1):288. https://doi.org/10.1186/s12974-020-01961-8 . (PMID:33008395;PMCID:PMC7532639).

Cammann D, Lu Y, Cummings MJ, Zhang ML, Cue JM, Do J, Ebersole J, Chen X, Oh EC, Cummings JL, Chen J. Genetic correlations between Alzheimer’s disease and gut microbiome genera. Sci Rep. 2023;13(1):5258. https://doi.org/10.1038/s41598-023-31730-5 . (PMID:37002253;PMCID:PMC10066300).

Borsom EM, Conn K, Keefe CR, Herman C, Orsini GM, Hirsch AH, Palma Avila M, Testo G, Jaramillo SA, Bolyen E, Lee K, Caporaso JG, Cope EK. Predicting Neurodegenerative Disease Using Prepathology Gut Microbiota Composition: a Longitudinal Study in Mice Modeling Alzheimer’s Disease Pathologies. Microbiol Spectr. 2023;11(2):e0345822. https://doi.org/10.1128/spectrum.03458-22 . (Epub ahead of print. PMID: 36877047; PMCID: PMC10101110).

van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, Kanekiyo M, Li D, Reyderman L, Cohen S, Froelich L, Katayama S, Sabbagh M, Vellas B, Watson D, Dhadda S, Irizarry M, Kramer LD, Iwatsubo T. Lecanemab in Early Alzheimer’s Disease. N Engl J Med. 2023;388(1):9–21. https://doi.org/10.1056/NEJMoa2212948 . (Epub 2022 Nov 29 PMID: 36449413).

Ornish D, Scherwitz LW, Billings JH, Brown SE, Gould KL, Merritt TA, Sparler S, Armstrong WT, Ports TA, Kirkeeide RL, Hogeboom C, Brand RJ. Intensive lifestyle changes for reversal of coronary heart disease. JAMA. 1998;280(23):2001–7. https://doi.org/10.1001/jama.280.23.2001 .

Ornish D, Weidner G, Fair WR, Marlin R, Pettengill EB, Raisin CJ, Dunn-Emke S, Crutchfield L, Jacobs FN, Barnard RJ, Aronson WJ, McCormac P, McKnight DJ, Fein JD, Dnistrian AM, Weinstein J, Ngo TH, Mendell NR, Carroll PR. Intensive lifestyle changes may affect the progression of prostate cancer. J Urol. 2005;174(3):1065–9. https://doi.org/10.1097/01.ju.0000169487.49018.73 . (discussion 1069-70. PMID: 16094059).

Ornish D, Lin J, Chan JM, Epel E, Kemp C, Weidner G, Marlin R, Frenda SJ, Magbanua MJM, Daubenmier J, Estay I, Hills NK, Chainani-Wu N, Carroll PR, Blackburn EH. Effect of comprehensive lifestyle changes on telomerase activity and telomere length in men with biopsy-proven low-risk prostate cancer: 5-year follow-up of a descriptive pilot study. Lancet Oncol. 2013;14(11):1112–20. https://doi.org/10.1016/S1470-2045(13)70366-8 . (Epub 2013 Sep 17 PMID: 24051140).

Kivipelto M et al. Multimodal preventive trial for Alzheimer’s disease. Alzheimer’s Dement. 2021;17(Suppl.10):e056105. https://alz-journals.onlinelibrary.wiley.com/doi/abs/10.1002/alz.056105 .

Ornish D, Brown SE, Scherwitz LW, Billings JH, Armstrong WT, Ports TA, McLanahan SM, Kirkeeide RL, Brand RJ, Gould KL. Can lifestyle changes reverse coronary heart disease? The Lifestyle Heart Trial. Lancet. 1990;336(8708):129–33. https://doi.org/10.1016/0140-6736(90)91656-u . (PMID: 1973470).

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Acknowledgements

We are grateful to each of the following people who made this study possible. Paramount among these are all of the study participants and their spouse or support person. Their commitment was inspiring, and without them this study would not have been possible. Each of the staff who provided and supported this program is exceptionally caring and competent, and includes: Heather Amador, who coordinated and administered all grants and infrastructure; Tandis Alizadeh, who is chief of staff; as well as Lynn Sievers, Nikki Liversedge, Pamela Kimmel, Stacie Dooreck, Antonella Dewell, Stacey Dunn-Emke, Marie Goodell, Emily Dougherty, Kamala Berrio, Kristin Gottesman, Katie Mayers, Dennis Malone, Sarah & Mary Barber, Steven Singleton, Kevin Lane, Laurie Case, Amber O’Neill, Annie DiRocco, Alison Eastwood, Sara Henley, Sousha Naghshineh, Sarah Reinhard, Laura Kandell, Alison Haag, Sinead Lafferty, Haley Perkins, Chase Delaney, Danielle Marquez, Ava Hoffman, Sienna Lopez, and Sophia Gnuse. Dr. Caitlin Moore conducted much of the cognition and function testing along with Dr. Catherine Madison, Trevor Ragas, Andrea Espinosa, Lorraine Martinez, Davor Zink, Jeff Webb, Griffin Duffy, Lauren Sather, and others. Dr. Cecily Jenkins trained the ADAS-Cog rater. Dr. Jan Krumsiek and Dr. Richa Batra performed important analyses in Dr. Rima Kaddurah-Daouk’s lab. Dr. Pia Kivisåkk oversaw biomarker assays in Dr. Steven Arnold's lab. We are grateful to all of the referring neurologists. Board members of the nonprofit Preventive Medicine Research Institute provided invaluable oversight and support, including Henry Groppe, Jenard & Gail Gross, Ken Hubbard, Brock Leach, and Lee Stein, as well as Joel Goldman.

Author’s information

DO is the corresponding author. RT contributed as the senior author.

We are very grateful to Leonard A. Lauder & Judith Glickman Lauder; Gary & Laura Lauder; Howard Fillit and Mark Roithmayr of The Alzheimer’s Drug Discovery Foundation; Mary & Patrick Scanlan of the Mary Bucksbaum Scanlan Family Foundation; Laurene Powell Jobs/Silicon Valley Community Foundation; Pierre & Pamela Omidyar Fund/Silicon Valley Community Foundation (Pat Christen and Jeff Alvord); George Vradenburg Foundation/Us Against Alzheimer’s; American Endowment Foundation (Anna & James McKelvey); Arthur M. Blank Family Foundation/Around the Table Foundation (Elizabeth Brown, Natalie Gilbert, Christian Amica); John Paul & Eloise DeJoria Peace Love & Happiness Foundation (Constance Dykhuizen); Maria Shriver/Women’s Alzheimer’s Movement (Sandy Gleysteen, Laurel Ann Gonsecki, Erin Stein); Mark Pincus Family Fund/Silicon Valley Community Foundation; Christy Walton/Walton Family Foundation; Milken Family Foundation; The Cleveland Clinic Lou Ruvo Center for Brain Health (Larry Ruvo); Jim Greenbaum Foundation; R. Martin Chavez; Wonderful Company Foundation (Stewart & Lynda Resnick); Daniel Socolow; Anthony J. Robbins/Tony Robbins Foundation; John Mackey; John & Lisa Pritzker and the Lisa Stone Pritzker Family Foundation; Ken Hubbard; Greater Houston Community Foundation (Jenard & Gail Gross); Henry Groppe; Brock & Julie Leach Family Charitable Foundation; Bucksbaum/Baum Foundation (Glenn Bucksbaum & April Minnich); YPO Gold Los Angeles; Lisa Holland/Betty Robertson; the Each Foundation (Lionel Shaw); Moby Charitable Fund; California Relief Program; Gary & Lisa Schildhorn; McNabb Foundation (Ricky Rafner); Renaissance Charitable Foumdation (Stephen & Karen Slinkard); Network for Good; Ken & Kim Raisler Foundation; Miner Foundation; Craiglist Charitable Fund (Jim Buckmaster and Annika Joy Quist); Gaurav Kapadia; Healing Works Foundation/Wayne Jonas; and the Center for Innovative Medicine (CIMED) at the Karolinska Institutet, Hjärnfonden, Stockholms Sjukhem, Research Council for Health Working Life and Welfare (FORTE). In-kind donations were received from Alan & Rob Gore of Body Craft Recreation Supply (exercise equipment), Dr. Andrew Abraham of Orgain, Paul Stamets of Fungi Perfecta ( Host Defense Lion’s Mane), Nordic Naturals, and Flora. Dr. Rima Kaddurah-Daouk at Duke is PI of the Alzheimer Gut Microbiome Project (funded by NIA U19AG063744). She also received additional funding from NIA that has enabled her research (U01AG061359 & R01AG081322).

The funders had no role in the conceptualization; study design; data collection; analysis; and interpretation; writing of the report; or the decision to submit for publication.

Author information

Authors and affiliations.

Preventive Medicine Research Institute, 900 Bridgeway, Sausalito, CA, USA

Dean Ornish, Catherine Madison, Anne Ornish, Nancy DeLamarter, Noel Wingers & Carra Richling

University of California, San Francisco and University of California, San Diego, USA

Dean Ornish

Ray Dolby Brain Health Center, California Pacific Medical Center, San Francisco, CA, USA

Catherine Madison

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Karolinska vägen 37 A, SE-171 64, Solna, Sweden

Miia Kivipelto

Theme Inflammation and Aging, Karolinska University Hospital, Karolinska vägen 37 A, SE-171 64, Stockholm, Solna, Sweden

The Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, St Mary’s Hospital, Norfolk Place, London, W2 1PG, United Kingdom

Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Yliopistonranta 8, 70210, Kuopio, Finland

Clinical Services, Preventive Medicine Research Institute, Bridgeway, Sausalito, CA, 900, USA

Colleen Kemp & Sarah Tranter

Division of Biostatistics, Department of Epidemiology & Biostatistics, UCSF, San Francisco, CA, USA

Charles E. McCulloch

Neurosciences, University of California, San Diego, CA, USA

Douglas Galasko

Clinical Neurology, School of Medicine, University of Nevada, Reno, USA

Renown Health Institute of Neurosciences, Reno, NV, USA

Harvard Medical School, Boston, MA, USA

Dorene Rentz, Rudolph E. Tanzi & Steven E. Arnold

Center for Alzheimer Research and Treatment, Boston, MA, USA

Dorene Rentz

Mass General Brigham Alzheimer Disease Research Center, Boston, MA, USA

Elizabeth Blackburn Lab, UCSF, San Francisco, CA, USA

UCSF, San Francisco, CA, USA

Departments of Medicine and Psychiatry, Duke University Medical Center and Member, Duke Institute of Brain Sciences, Durham, NC, USA

Rima Kaddurah-Daouk

Department of Pediatrics; Department of Computer Science & Engineering; Department of Bioengineering; Center for Microbiome Innovation, Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA

Department of Pediatrics and Scientific Director, American Gut Project and The Microsetta Initiative, University of California San Diego, La Jolla, CA, USA

Daniel McDonald

Bioinformatics and Systems Biology Program; Rob Knight Lab; Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA

Lucas Patel

Buck Institute for Research on Aging, San Francisco, CA, USA

Eric Verdin

University of California, San Francisco, CA, USA

Genetics and Aging Research Unit, Boston, MA, USA

Rudolph E. Tanzi

McCance Center for Brain Health, Boston, MA, USA

Massachusetts General Hospital, Boston, MA, USA

Interdisciplinary Brain Center, Massachusetts General Hospital, Boston, MA, USA

Steven E. Arnold

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Contributions

DO, CM, MK, CK, DG, JA, DR, CEM, JL, KN, AO, ST, ND, NW, CR, RKD, RK, EV, RT, and SEA were involved in the study design and conduct. DO conceptualized the study hypotheses (building on the work of MK), obtained funding, prepared the first draft of the manuscript, and is the principal investigator. CEM oversaw the statistical analyses and interpretation, and DR oversaw the cognition and function testing and interpretation. CK and ST oversaw all clinical operations and patient recruitment, including the IRB. JL conducted the telomere analyses. CM oversaw patient selection. AO developed the learning management system and community platform for patients and providers. KN managed an IRB. ND co-led most of the support groups, and CR oversaw all aspects involving nutrition. All authors participated in writing the manuscript. NW and ST oversaw data collection and prepared the databases other than the microbiome databases which were overseen by RK and prepared by DM and LP who helped design this part of the study. CM, CK, JL, RKD, RK, DM, and LP were involved in the acquisition of data. SA, RT, and RKD did biomarker analyses. All authors contributed to critical review of the manuscript and approved the final manuscript.

Corresponding author

Correspondence to Dean Ornish .

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Competing interests.

MK is one of the Editors-in-Chief of this journal and has no relevant competing interests and recused herself from the review process. RKD is an inventor on key patents in the field of metabolomics and holds equity in Metabolon, a biotech company in North Carolina. In addition, she holds patents licensed to Chymia LLC and PsyProtix with royalties and ownership. DO and AO have consulted for Sharecare and have received book royalties and lecture honoraria and, with CK, have received equity in Ornish Lifestyle Medicine. RK is a scientific advisory board member and consultant for BiomeSense, Inc., has equity and receives income. He is a scientific advisory board member and has equity in GenCirq. He is a consultant and scientific advisory board member for DayTwo, and receives income. He has equity in and acts as a consultant for Cybele. He is a co-founder of Biota, Inc., and has equity. He is a cofounder of Micronoma, and has equity and is a scientific advisory board member. The terms of these arrangements have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. DM is a consultant for BiomeSense. RT is a co-founder and equity holder in Hyperion Rx, which produces the flashing-light glasses at a theta frequency of 7.83 Hz used as an optional aid to meditation. The rest of the authors declare that they have no competing interests.

Ethics approval and consent to participate

This clinical trial was approved by the Western Institutional Review Board on 12/31/2017 (approval number: 20172897) and all participants and their study partners provided written informed consent. The trial protocol was also approved by the appropriate Institutional Review Board of all participating sites; and all subjects provided informed consent.

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Informed consent was received from all patients. All data from research participants described in this paper is de-identified.

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Ornish, D., Madison, C., Kivipelto, M. et al. Effects of intensive lifestyle changes on the progression of mild cognitive impairment or early dementia due to Alzheimer’s disease: a randomized, controlled clinical trial. Alz Res Therapy 16 , 122 (2024). https://doi.org/10.1186/s13195-024-01482-z

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Received : 21 February 2024

Accepted : 15 May 2024

Published : 07 June 2024

DOI : https://doi.org/10.1186/s13195-024-01482-z

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