Lane, Kathleen A.

Key Points In individuals undergoing bariatric surgery, the magnitude of decline in GFR postbariatric surgery is directly associated with presurgery GFR. Reductions in GFR postsurgery were only weakly correlated with weight loss. In obese individuals, GFR-estimating equations performed best when deindexed and when applied in people with reduced kidney function. Background Important questions remain about how bariatric ( i.e ., weight loss) surgery affects measured GFR (mGFR) and eGFR as well as what factors influence change in mGFR postsurgery. Methods Data were pooled from all seven available studies (dates: 2004–2018) measuring GFR prebariatric and postbariatric surgery using gold standard methods. Change in postsurgery mGFR, factors that could influence change in mGFR, and effects on five GFR-estimating equations were analyzed using standard statistical methods. Results The cohort included 105 individuals from the United States and Europe. Sixty-eight percent were female, 97% were White, the mean age was 50 years (range, 24–70), and the mean body mass index was 46±8 kg/m 2 . The mean presurgery mGFR of 107 ml/min (range, 31–215) fell to 92 ml/min (−14%; 95% confidence interval, −21 to −10) postsurgery, with a strong linear relationship existing between presurgery mGFR and % change in GFR ( r =−0.51; −0.64 to −0.35). Individuals with presurgery mGFR ≥90, 60 to <90, and<60 ml/min had −25 (−32 to −19), 1 (−11 to 13), and 7 (0 to 14) ml/min mean postoperative changes in mGFR. Change in weight was significantly correlated with change in mGFR ( r =0.22; 0.03 to 0.40). After adjusting for sex, changes in mGFR postsurgery were associated with higher presurgical age (−0.6 ml/min per year; −1.1 to −0.2), mGFR (−0.5 ml/min per 1 ml/min; −0.6 to −0.4), and change in systolic BP (−0.3 ml/min per 1 mm Hg; −0.6 to 0.0). All GFR-estimating equations significantly underestimated postsurgical GFR reductions in people with preserved kidney function and had improved bias, precision, and accuracy when deindexed and applied to individuals with mGFR <90 ml/min. Conclusions In individuals with obesity undergoing bariatric surgery, the magnitude of postsurgical decline in mGFR was directly associated with presurgery GFR and weakly correlated with weight loss. In addition, GFR-estimating equations' performance improved when deindexed and used in people with reduced kidney function, with the combined creatinine/cystatin C equations having the best overall performance.

AbstractBackgroundEarly‐onset Alzheimer’s disease (EOAD) occurs before age 65 and has more diverse disease presentations than late‐onset AD. To improve our understanding of phenotypic heterogeneity among EOAD individuals, we analyzed cognitive scores using data‐driven statistical analysis.MethodBaseline cognitive data from 286 sporadic EOAD individuals from the Longitudinal EOAD study (LEADS) were transformed to z‐scores using data from 95 cognitively normal (CN) individuals. Cognitive composites were generated for domains of memory, language, speed/attention, visuospatial, and executive function. Residuals from linear regression models on Z‐scores adjusted for age, sex, and education were obtained. Cluster analysis using the Ward method on the cognitive domain residuals was performed and scree plot using the pseudo T‐squared determined the optimal number of clusters for the EOAD sample. We also compared gray matter density (GMD) of each EOAD cluster to CN participants using voxel‐wise multiple linear regressions.ResultsThree clusters of cognitive performance were identified from the EOAD sample. Disease duration was not significantly different across clusters. Using a z‐score of ‐1.5 SD as the impairment threshold, all clusters were impaired across most domains (Table 1). Cluster‐3 was more impaired than cluster‐2 in all domains (Table 2; all p<.0001), and in all domains except episodic memory compared to cluster‐1 (all p<.01). Cluster‐1 (n = 71; 85.9% amnestic) was most impaired in executive function, visuospatial, and speed/attention. Cluster‐2 (n = 133; 88.7% amnestic) was most impaired in episodic memory. Cluster‐3 (n = 82; 69.5% amnestic) was most impaired in executive function, visuospatial, and speed/attention (Table 1). 3D‐comparisons showed all EOAD clusters had reduced GMD compared to CN. Cluster‐1 and cluster‐3 both showed widespread atrophy, with cluster‐3 being more severe. Cluster‐2 showed the most atrophy in the temporal and parietal lobes (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among sporadic EOAD individuals. Cluster‐3 appeared to reflect widespread impairment, and cluster‐2 represented an amnestic‐only presentation. Despite comparable disease duration, some EOAD patients progress faster, while some are more resilient. 3D‐comparisons showed neurodegenerative changes affecting brain regions responsible for respective impaired cognitive functions in each cluster (e.g., cluster‐2 is primarily amnestic‐impaired and has temporoparietal atrophy). Future work should explore amyloid‐PET and tau‐PET burden.

AbstractBackgroundApproximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer’s Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns.MethodCognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume.ResultScree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration.