Johnson, Leigh

AbstractIntroductionRepresentation of Mexican Americans in Alzheimer's disease (AD) clinical research has been extremely poor.MethodsData were examined from the ongoing community‐based, multi‐ethnic Health & Aging Brain among Latino Elders (HABLE) study. Participants underwent functional exams, clinical labs, neuropsychological testing, and 3T magnetic resonance imaging of the brain. Fasting proteomic markers were examined for predicting mild cognitive impairment (MCI) and AD using support vector machine models.ResultsData were examined from n = 1649 participants (Mexican American n = 866; non‐Hispanic White n = 783). Proteomic profiles were highly accurate in detecting MCI (area under the curve [AUC] = 0.91) and dementia (AUC = 0.95). The proteomic profiles varied significantly between ethnic groups and disease state. Negative predictive value was excellent for ruling out MCI and dementia across ethnic groups.DiscussionA blood‐based screening tool can serve as a method for increasing access to state‐of‐the‐art AD clinical research by bridging between community‐based and clinic‐based settings.

AbstractIntroductionWe sought to determine if a proteomic profile approach developed to detect Alzheimer's disease would distinguish patients with Lewy body disease from normal controls, and if it would distinguish dementia with Lewy bodies (DLB) from Parkinson's disease (PD).MethodsStored plasma samples were obtained from 145 patients (DLB n = 57, PD without dementia n = 32, normal controls n = 56) enrolled from patients seen in the Behavioral Neurology or Movement Disorders clinics at the Mayo Clinic, Florida. Proteomic assays were conducted and analyzed as per our previously published protocols.ResultsIn the first step, the proteomic profile distinguished the DLB‐PD group from controls with a diagnostic accuracy of 0.97, sensitivity of 0.91, and specificity of 0.86. In the second step, the proteomic profile distinguished the DLB from PD groups with a diagnostic accuracy of 0.92, sensitivity of 0.94, and specificity of 0.88.DiscussionThese data provide evidence of the potential utility of a multitiered blood‐based proteomic screening method for detecting DLB and distinguishing DLB from PD.

Abstract Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART ) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross‐PIA white paper that provides both a concise “state‐of‐the‐science” report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.

AbstractThe last decade has seen a substantial increase in research focused on the identification of blood‐based biomarkers that have utility in Alzheimer's disease (AD). Blood‐based biomarkers have significant advantages of being time‐ and cost‐efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood‐based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public‐private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.

AbstractIntroductionThis study combined data across four independent cohorts to examine the positive and negative predictive values of an Alzheimer's disease (AD) blood test if implemented in primary care.MethodsBlood samples from 1329 subjects from multiple independent, multiethnic, community‐based, and clinic‐based cohorts were analyzed. A “locked‐down” referent group of 1128 samples was generated with 201 samples randomly selected for validation purposes. Random forest analyses were used to create the AD blood screen. Positive (PPV) and negative (NPV) predictive values were calculated.ResultsIn detecting AD, PPV was 0.81, and NPV was 0.95 while using the full AD blood test. When detecting mild cognitive impairment, PPV and NPV were 0.74 and 0.93, respectively. Preliminary analyses were conducted to detect any “neurodegenerative disease”. The full 21‐protein AD blood test yielded a PPV of 0.85 and NPV of 0.94.DiscussionThe present study creates the first‐ever multiethnic referent sample that spans community‐based and clinic‐based populations for implementation of an AD blood screen.