Adam Mecca, MD, PhD
Associate Professor of PsychiatryCards
About
Research
Publications
2025
The Impact of Cognitive Impairment on Cardiovascular Disease
Jamil Y, Krishnaswami A, Orkaby A, Stimmel M, Brown Iv C, Mecca A, Forman D, Rich M, Nanna M, Damluji A. The Impact of Cognitive Impairment on Cardiovascular Disease. Journal Of The American College Of Cardiology 2025, 85: 2472-2491. PMID: 40562512, DOI: 10.1016/j.jacc.2025.04.057.Peer-Reviewed Original ResearchConceptsImpact of cognitive impairmentCognitive impairmentCardiovascular diseaseHealth care utilizationOlder adult populationEvidence-based management strategiesMedical adverse eventsHealth literacyCare utilizationOlder adultsMitigate cognitive impairmentUnder-prescribedReduced participationU.S. populationTreatment of patientsAdult populationGuideline-directedExcess morbidityCardiac patientsRisk factorsOlder patientsAdverse eventsHealthMechanism of cognitive impairmentInterventional managementCerebrospinal fluid and brain positron emission tomography measures of synaptic vesicle glycoprotein 2A: Biomarkers of synaptic density in Alzheimer's disease
Mecca A, Ashton N, Chen M, O'Dell R, Toyonaga T, Zhao W, Young J, Salardini E, Bates K, Ra J, Goodcase S, Silva‐Rudberg J, Nabulsi N, Brinkmalm A, Kvartsberg H, Schöll M, Nilsson J, Arnsten A, Huang Y, Hansson O, Zetterberg H, Carson R, Blennow K, van Dyck C. Cerebrospinal fluid and brain positron emission tomography measures of synaptic vesicle glycoprotein 2A: Biomarkers of synaptic density in Alzheimer's disease. Alzheimer's & Dementia 2025, 21: e70344. PMID: 40491249, PMCID: PMC12149441, DOI: 10.1002/alz.70344.Peer-Reviewed Original ResearchConceptsSynaptic vesicle glycoprotein 2APositron emission tomographyAlzheimer's diseaseSynaptic densityEnzyme-linked immunosorbent assayC]UCB-J positron emission tomographyPositron emission tomography measurementsEmission tomographyAxonal proteinsCN participantsImmunosorbent assaySymptomatic Alzheimer's diseaseAD groupProteinAssayParticipantsSV2AAlzheimerCerebrospinal fluidBrainInvestigate associationsCerebrospinal fluid assaysSV2A positron emission tomographyDetection of emergency department patients at risk of dementia through artificial intelligence
Cohen I, Taylor R, Xue H, Faustino I, Festa N, Brandt C, Gao E, Han L, Khasnavis S, Lai J, Mecca A, Sapre A, Young J, Zanchelli M, Hwang U. Detection of emergency department patients at risk of dementia through artificial intelligence. Alzheimer's & Dementia 2025, 21: e70334. PMID: 40457744, PMCID: PMC12130574, DOI: 10.1002/alz.70334.Peer-Reviewed Original ResearchConceptsElectronic health record dataHealth record dataEmergency departmentDetect dementiaDementia detectionYale New Haven HealthRecord dataRisk of dementiaEmergency department patientsBalance detection accuracyDementia algorithmsImprove patient outcomesCare coordinationCare transitionsDementia diagnosisReal-time applicationsClinical decision-makingClinician supportED usePatient safetyProbable dementiaMachine learning algorithmsED workflowED visitsED encountersSex differences in the confounders influencing the relationships linking socioeconomic factors and cognitive performance with family history of Alzheimer's disease and related dementias
He J, Cabrera‐Mendoza B, Friligkou E, Mecca A, van Dyck C, Pathak G, Polimanti R. Sex differences in the confounders influencing the relationships linking socioeconomic factors and cognitive performance with family history of Alzheimer's disease and related dementias. Alzheimer's & Dementia 2025, 21: e70215. PMID: 40421744, PMCID: PMC12107445, DOI: 10.1002/alz.70215.Peer-Reviewed Original ResearchConceptsSocioeconomic factorsFamily historySocioeconomic statusFamily history of Alzheimer's diseaseAssociation of socioeconomic factorsHistory of Alzheimer's diseaseUs Research ProgramCognitive performanceHigher socioeconomic statusSex-specific associationsAlzheimer's disease assessmentSex differencesUK BiobankADRDAlzheimer's diseaseGenetically informed analysesDementiaSample sizeSexGenetic analysisAlzheimerLimited informationStatusConfoundingBiobank0434 Comparison of Machine Learning Models for fMRI-Based Sleep Staging
Cho G, Hahm D, Mecca A, Miner B. 0434 Comparison of Machine Learning Models for fMRI-Based Sleep Staging. Sleep 2025, 48: a190-a190. DOI: 10.1093/sleep/zsaf090.0434.Peer-Reviewed Original Research0074 The Relationship of Sleep Disorder History with Gray Matter BOLD-CSF Coupling Among Persons at Risk for and with Alzheimer’s Disease
Cho G, Liu X, Mecca A, Miner B. 0074 The Relationship of Sleep Disorder History with Gray Matter BOLD-CSF Coupling Among Persons at Risk for and with Alzheimer’s Disease. Sleep 2025, 48: a34-a34. DOI: 10.1093/sleep/zsaf090.0074.Peer-Reviewed Original ResearchAssessment of the relationship between synaptic density and metabotropic glutamate receptors in early Alzheimer’s disease: a multi-tracer PET study
Salardini E, O’Dell R, Tchorz E, Nabulsi N, Huang Y, Carson R, van Dyck C, Mecca A. Assessment of the relationship between synaptic density and metabotropic glutamate receptors in early Alzheimer’s disease: a multi-tracer PET study. Alzheimer's Research & Therapy 2025, 17: 98. PMID: 40329311, PMCID: PMC12054321, DOI: 10.1186/s13195-025-01739-1.Peer-Reviewed Original ResearchConceptsDistribution volume ratioMedial temporal lobePositron emission tomographyTemporal lobeSynaptic densityMetabotropic glutamate receptor subtype 5Multi-tracer PET studiesAlzheimer's diseaseCerebellum reference regionAmyloid-positive participantsSynaptic lossSynaptic vesicle glycoprotein 2AMetabotropic glutamate receptorsPositron emission tomography scanNeocortical regionsSubtype 5MGluR5Entorhinal cortexAD groupReference regionGlutamate receptorsExploratory analysisWidespread reductionsLongitudinal studyReceptor bindingAssessing Synaptic Density in Behavioral Variant Frontotemporal Dementia: A Head-to-Head Comparison of 18F-SynVesT-1 and 18F-FDG PET (P9-3.019)
Cayir S, Yang Y, Ibrahim W, Naganawa M, Gallezot J, Toyonaga T, Nabulsi N, huang H, Carson R, Vandyck C, Mecca A, Fesharaki-Zadeh A, Matuskey D. Assessing Synaptic Density in Behavioral Variant Frontotemporal Dementia: A Head-to-Head Comparison of 18F-SynVesT-1 and 18F-FDG PET (P9-3.019). Neurology 2025, 104 DOI: 10.1212/wnl.0000000000212121.Peer-Reviewed Original ResearchGenerating synthetic brain PET images of synaptic density based on MR T1 images using deep learning
Zheng X, Worhunsky P, Liu Q, Guo X, Chen X, Sun H, Zhang J, Toyonaga T, Mecca A, O’Dell R, van Dyck C, Angarita G, Cosgrove K, D’Souza D, Matuskey D, Esterlis I, Carson R, Radhakrishnan R, Liu C. Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning. EJNMMI Physics 2025, 12: 30. PMID: 40163154, PMCID: PMC11958861, DOI: 10.1186/s40658-025-00744-5.Peer-Reviewed Original ResearchCannabis use disorderStructural similarity indexPET imagingImages of higher qualityMR-T1 imagesMean square errorUse disorderEncoder-decoderDeep learningCross-validation processData-driven approachDiagnostic categoriesLow-dose scansPredicted imageTemporal regionsBrain disordersGround truthT1-weighted MRISynaptic densityHuman brainSimilarity indexDisordersSevere neurological disordersTranslation accuracyNoise reductionLower slow wave sleep and rapid eye movement sleep are associated with brain atrophy of AD-vulnerable regions.
Cho G, Mecca A, Buxton O, Liu X, Miner B. Lower slow wave sleep and rapid eye movement sleep are associated with brain atrophy of AD-vulnerable regions. Journal Of Clinical Sleep Medicine 2025 PMID: 40110600, DOI: 10.5664/jcsm.11630.Peer-Reviewed Original ResearchRapid eye movementSlow wave sleepSleep architectureArousal indexAssociated with smaller volumesCerebral microbleedsLobar cerebral microbleedsProportion of rapid eye movementBaseline sleep architectureRapid eye movement sleepProportion of slow wave sleepAssociated with cerebral microbleedsEye movement sleepSleep architecture variablesModifiable risk factorsAtrophy of hippocampusSleep deficiencyMedian ageParietal regionsMovement sleepMRI outcomesAssociated with brain atrophyAnatomical featuresRisk factorsCuneus regions
Clinical Trials
Current Trials
Studying the Adult Brain
HIC ID2000025671RoleSub InvestigatorPrimary Completion Date07/31/2025Recruiting ParticipantsImaging mGluR5 and synaptic density in psychiatric disorders
HIC ID2000020186RoleSub InvestigatorPrimary Completion Date01/31/2018Recruiting ParticipantsGenderBothAge18 years - 80 years
Clinical Care
Overview
Adam Mecca, MD, PhD is a geriatric psychiatrist who specializes in memory disorders including Alzheimer’s disease, dementia, mild cognitive impairment, and other related conditions.
“I enjoy meeting patients and their families and working together to understand the cause of a person's symptoms and finding the best way to help,” Dr. Mecca says. “I value the opportunity to work with patients experiencing changes in their memory and thinking. We discuss the important changes occurring in their life, and work on building supports so that they can continue to thrive in all ways possible.”
An active researcher, Dr. Mecca studies Alzheimer’s disease and related disorders. “It is a very satisfying focus since memory disorders affect so many people. There is an enormous need for effective treatments,” he says. “I am passionate about bringing understanding of a life-altering disease process into awareness. It is vital to educate, provide treatment, and to help patients and families work through what is often a progressive and incurable illness.”
As the associate director of the Yale Alzheimer’s Disease Research Unit, he works with a team to better understand Alzheimer’s disease and develop effective therapies. He and his collaborators are creating neuroimaging methods to investigate the neurobiology of Alzheimer’s disease.
Their efforts have led to a novel positron emission tomography (PET) imaging technique to measure decreases in the number of connections between nerve cells in people with Alzheimer’s disease. This work may accelerate the development of effective treatments.
Clinical Specialties
Fact Sheets
Dementia
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