Citations

Abstract The design of clinical trials in Alzheimer's disease (AD) must consider the development of new plasma, cerebrospinal fluid (CSF), and imaging biomarkers. They must also define clinically meaningful outcomes for patients and set endpoints that measure these outcomes accurately. With the accelerated United States Food and Drug Administration (FDA) approval of the first anti‐amyloid, disease‐modifying treatment for AD, a monoclonal antibody called aducanumab, the landscape of clinical trial design is evolving. Enrolment in clinical trials may be impacted by the availability of this and other treatments, and trial design must take into consideration that patients may desire a disease‐modifying treatment rather than potentially being randomized to the placebo arm. The Alzheimer's Association Research Roundtable (AARR) Fall 2021 meeting discussed the consideration of well‐defined AD staging criteria in protocol design and how they influence more standardized inclusion/exclusion criteria for trials, as well as what constitutes meaningful differentiation between the stages. Discussion explored the current state of knowledge regarding biomarkers and how they can inform AD staging criteria, as many trials are now designed based on specific biomarker features, further underscoring the importance of coordinating AD staging criteria and biomarkers. The relationship between cognition and biomarkers has been studied and this must continue as trials move forward. Researchers, patients, clinicians, regulatory scientists, and payers discussed the state of the field as well as the future of symptomatic Alzheimer's disease clinical trials. Highlights The Alzheimer's Association Research Roundtable (AARR) convened leaders from academia and industry as well as patients, care partners, clinicians, regulators, and payers to discuss the topic of operationalizing selection criteria for clinical trials and the role of biomarkers. Well‐defined Alzheimer's disease (AD) staging criteria are an important consideration in study protocol design. Staging criteria and biomarkers must be coordinated to yield high‐quality clinical trial results that have meaning for patients with AD by selecting a population most likely to benefit from a specific treatment.

Abstract Alzheimer's disease (AD) staging criteria lack standardized, empirical description. Well‐defined AD staging criteria are an important consideration in protocol design, influencing a more standardized inclusion/exclusion criteria and defining what constitutes meaningful differentiation among the stages. However, many trials are being designed on the basis of biomarker features and the two need to be coordinated. The Alzheimer's Association Research Roundtable (AARR) Spring 2021 meeting discussed the implementation of preclinical AD staging criteria, and provided recommendations for how they may best be incorporated into clinical trials research. Discussion also included what currently available tools for global clinical trials may best define populations in preclinical AD trials, and if are we able to differentiate preclinical from clinical stages of the disease. Well‐defined AD staging criteria are key to improving early detection, diagnostics, clinical trial enrollment, and identifying statistically significant clinical changes, and researchers discussed how emerging blood biomarkers may help with more efficient screening in preclinical stages.

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.