Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss.

Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife.

We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD-GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle-aged participants (311 with brain MRI). A higher AD-GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (-0.14 standard deviation [SD] [95% confidence interval {CI}: -0.26, -0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE ε4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629-634.

Plasma proteomic biomarkers and the association between poor cardiovascular health and incident dementia: The UK Biobank study.

BACKGROUND: The study examined how plasma proteome indicators may explain the link between poor cardiovascular health (CVH) and dementia risk. METHODS: The present study involved 28,974 UK Biobank participants aged 50-74y at baseline (2006-2010) who were followed-up for ≤ 15 y for incidence of dementia. CVH was calculated using Life's Essential 8 (LE8) total scores. The scores were standardized and reverse coded to reflect poor CVH (LE8z_rev). OLINK proteomics was available on this sample (k = 1,463 plasma proteins). The study primarily tested the mediating effects of the plasma proteome in LE8z_rev-dementia effect. The total effect was decomposed into "mediation only" or pure indirect effect (PIE), "interaction only" or interaction referent (INTREF), "neither mediation nor interaction" or controlled direct effect (CDE), and "both mediation and interaction" or mediated interaction (INTMED). RESULTS: The study found poorer CVH assessed by LE8z_rev increased the risk of all-cause dementia by 11 % [per 1 SD, hazard ratio, (HR) = 1.11, 95 % CI: 1.03-1.20, p = 0.005). The study identified 11 plasma proteins with strong mediating effects, with GDF15 having the strongest association with dementia risk (per 1 SD, HR = 1.24, 95 % CI: 1.16, 1.33, P < 0.001 when LE8z_rev is set at its mean value) and the largest proportion mediated combining PIE and INTMED (62.6 %; 48 % of TE is PIE), followed by adrenomedullin or ADM. A first principal component with 10 top mediators (TNFRSF1A, GDF15, FSTL3, COL6A3, PLAUR, ADM, GFRAL, ACVRL1, TNFRSF6B, TGFA) mediated 53.6 % of the LE8z_rev-dementia effect. Using all the significant PIE (k = 526) proteins, we used OLINK Insight pathway analysis to identify key pathways, which revealed the involvement of the immune system, signal transduction, metabolism, disease, protein metabolism, hemostasis, membrane trafficking, extracellular matrix organization, developmental biology, and gene expression among others. STRING analysis revealed that five top consistent proteomic mediators were represented in two larger clusters reflecting numerous interconnected biological gene ontology pathways, most notably cytokine-mediated signaling pathway for GDF15 cluster (GO:0019221) and regulation of peptidyl-tyrosine phosphorylation for the ADM cluster (GO:0050730). CONCLUSION: Dementia is linked to poor CVH mediated by GDF15 and ADM among several key proteomic markers which collectively explained âˆ¼ 54 % of the total effect.

Infection burden and its association with neurite orientation dispersion and density imaging markers in the UK Biobank.

BACKGROUND: Infection burden (IB), although linked to neurodegeneration, including Alzheimer's Disease (AD), has not been examined against neurite orientation, dispersion, and density imaging (NODDI) measures. METHODS: Among 38,803 UK Biobank adults (Age:40-70 years), we tested associations of total IB (IBtotal, 47.5 %) and hospital-treated IB (IBhosp, 9.7 %) with NODDI measures (5-15 years later), including volume fraction of Gaussian isotropic diffusion (ISOVF), intra-cellular volume fraction (ICVF) and orientation dispersion (OD) indices, using multiple linear regression models. RESULTS: Total and hospital-treated infection burdens (IBtotal and IBhosp) were associated with increased ISOVF, indicating increased free-water component. IBtotal was positively associated with OD, indicating that at higher IBtotal there was greater fanning of neurites. This was more evident in the lower cardiovascular health group. IBhosp was associated with higher OD, and lower ICVF at higher AD polygenic risk. Together, these findings indicate that both total and hospital-treated infections have effects on NODDI outcomes in the direction of poor brain health. These effects were largely homogeneous across cardiovascular health and AD polygenic risk groups, with some effects shown to be stronger at poor cardiovascular health and/or higher AD risk. CONCLUSIONS: Total and hospital-treated infections were associated with poorer white matter microstructure (higher ISOVF or OD or lower ICVF), with some heterogeneity across cardiovascular health and AD risk. Longitudinal studies with multiple repeats on neuroimaging markers in comparable samples are needed.

Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

The magnitude and direction of the relationship between risk factor and cognition depends on age: a pooled analysis of 5 community-based studies.

The mixed evidence of the association between high levels of cardiovascular risk factors (CVRF) and the risk for cognitive impairment may be due to confounding of age across studies. We pooled and harmonized individual-level data (30,967 persons, age range 42-96 years) from five prospective cohorts to investigate by 1 year age increments to investigate whether or not there is change in slope describing the association of CVRF to a cognitive outcome (Digit Symbol Substitution Test; DSST). The CVRF included: systolic and diastolic blood pressure, total cholesterol, fasting glucose and body mass index. Linear and quadratic piecewise regression models were fit to the trajectory patterns of these slopes (betas). The pattern of yearly slope changes showed higher CVRF were associated with lower DSST, but associations attenuated toward zero as age increased for all but DBP where 1 year slopes for DBP changed direction from negative to positive from mid- to late-age. Age is not only a driver of cognitive decline-age also modifies the direction and strength of the association of cognitive function to CVRF and cohort age may be one reason why the evidence for CVRF-CD association is mixed.

Blood pressure, executive function, and network connectivity in middle-aged adults at risk of dementia in late life.

Midlife blood pressure is associated with structural brain changes, cognitive decline, and dementia in late life. However, the relationship between early adulthood blood pressure exposure, brain structure and function, and cognitive performance in midlife is not known. A better understanding of these relationships in the preclinical stage may advance our mechanistic understanding of vascular contributions to late-life cognitive decline and dementia and may provide early therapeutic targets. To identify resting-state functional connectivity of executive control networks (ECNs), a group independent components analysis was performed of functional MRI scans of 600 individuals from the Coronary Artery Risk Development in Young Adults longitudinal cohort study, with cumulative systolic blood pressure (cSBP) measured at nine visits over the preceding 30 y. Dual regression analysis investigated performance-related connectivity of ECNs in 578 individuals (mean age 55.5 ± 3.6 y, 323 female, 243 Black) with data from the Stroop color-word task of executive function. Greater connectivity of a left ECN to the bilateral anterior gyrus rectus, right posterior orbitofrontal cortex, and nucleus accumbens was associated with better executive control performance on the Stroop. Mediation analyses showed that while the relationship between cSBP and Stroop performance was mediated by white matter hyperintensities (WMH), resting-state connectivity of the ECN mediated the relationship between WMH and executive function. Increased connectivity of the left ECN to regions involved in reward processing appears to compensate for the deleterious effects of WMH on executive function in individuals across the burden of cumulative systolic blood pressure exposure in midlife.

Circulating Metabolome and White Matter Hyperintensities in Women and Men.

BACKGROUND: White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. METHODS: We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant. RESULTS: In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047). CONCLUSIONS: Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.

Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer's disease and myocardial infarction.

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P < 5.30 × 10-7); including a novel signal near TOMM40/APOE. Joint analysis of TOMM40/APOE variants revealed the TOMM40 signal was attributed to APOE rs429358-T; APOE rs7412 was not associated with liver attenuation. Moreover, rs429358-T was associated with higher serum alanine aminotransferase, liver steatosis, cirrhosis, triglycerides and obesity; as well as, lower cholesterol and decreased risk of myocardial infarction and Alzheimer's disease (AD) in phenome-wide association analyses in the Michigan Genomics Initiative, United Kingdom Biobank and/or public datasets. These results implicate APOE in imaging-based identification of NAFLD. This association may or may not translate to nonalcoholic steatohepatitis; however, these results indicate a significant association with advanced liver disease and hepatic cirrhosis. These findings highlight allelic heterogeneity at the APOE locus and demonstrate an inverse link between NAFLD and AD at the exome level in the largest analysis to date.

Milk intake and hip fracture incidence in community-dwelling old Icelandic adults.

Milk and milk products have been known as important for bone health. Can ingestion of milk and milk products lower hip fracture risk for older adults? In this study, older Icelandic adults who were ingesting higher milk had a lower risk of hip fractures. INTRODUCTION: This study describes associations between milk intake and hip fracture risk in older Icelanders. The data indicate that no/low milk consumption is related to greater hip fracture risk. Hip fracture can have a severe effect on the life of older adults. Health authorities recommend milk intake for better bone health. However, previous studies addressing this association have been divergent. METHODS: This prospective study included 4614 subjects (mean age 76 years) recruited between 2002 and 2006 into the Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study. Information on hip fractures occurring between recruitment and end of follow-up in 2012 was extracted from hospital records. RESULTS: A total of 14% of participants reported milk intake < 0.5 times/day (the lowest category) and 22% of the participants consumed at least milk two times/day (highest category). Milk consumption was positively related to the volumetric bone mineral density at baseline with a sex- and age-adjusted difference of 8.95 ± 2.5 mg/cm3 between the highest compared to lowest milk intake categories (P < 0.001). During the follow-up, 7.4% of participants had a hip fracture, and we observed a decreased risk of incident hip fractures in the highest compared to the lowest milk intake category with a hazard ratio of 0.69 (95% CI: 0.47-0.99) in adjusted model. Further analysis indicated a linear relationship between milk intake and fracture risk (P-value for linear trend < 0.001). CONCLUSION: Milk intake is associated with a lower risk of incident hip fracture in a linear way in Icelandic community-dwelling older adults.

Physical activity and diet associations with the gut microbiota in the Coronary Artery Risk Development in Young Adults (CARDIA) study.

BACKGROUND: Gut microbiota may influence metabolic pathways related to chronic health conditions. Evidence for physical activity and diet influences on gut microbial composition exists, but data from diverse population-based cohort studies are limited. OBJECTIVES: We hypothesized that gut microbial diversity and genera are associated with physical activity and diet quality. METHODS: Data were from 537 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort, who attended the year 30 follow-up examination (2015-2016; aged 47-61 y; 45% Black race/55% White race; 45% men/55% women). The 16S ribosomal RNA marker gene was sequenced from stool DNA, and genus-level taxonomy was assigned. Within-person microbial diversity (α-diversity) was assessed with Shannon diversity index and richness scores; between-person diversity (ß-diversity) measures were generated with principal coordinates analysis (PCoA). Current and long-term physical activity and diet quality measures were derived from data collected over 30 y of follow-up. Multivariable-adjusted regression analysis controlled for: sociodemographic variables (age, race, sex, education, and field center), other health behaviors (smoking, alcohol consumption, and medication use), and adjusted for multiple comparisons with the false discovery rate (<0.20). RESULTS: Based on PCoA ß-diversity, participants' microbial community compositions differed significantly (P < 0.001), with respect to both current and long-term physical activity and diet quality. α-Diversity was associated only with current physical activity (positively) in multivariable-adjusted analysis. Multiple genera (n = 45) were associated with physical activity and fewer with diet (n = 5), including positive associations with Lachnospiraceae UCG-001 and Ruminococcaceae IncertaeSedis with both behaviors. CONCLUSIONS: Physical activity and diet quality were associated with gut microbial composition among 537 participants in the CARDIA study. Multiple genera were associated with physical activity. Physical activity and diet quality were associated with genera consistent with pathways related to inflammation and short-chain fatty acid production.

Dynamic relationships between depressive symptoms and insulin resistance over 20 years of adulthood.

BACKGROUND: Bidirectional longitudinal relationships between depression and diabetes have been observed, but the dominant direction of their temporal relationships remains controversial. METHODS: The random-intercept cross-lagged panel model decomposes observed variables into a latent intercept representing the traits, and occasion-specific latent 'state' variables. This permits correlations to be assessed between the traits, while longitudinal 'cross-lagged' associations and cross-sectional correlations can be assessed between occasion-specific latent variables. We examined dynamic relationships between depressive symptoms and insulin resistance across five visits over 20 years of adulthood in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) study. Possible differences based on population group (Black v. White participants), sex and years of education were tested. Depressive symptoms and insulin resistance were quantified using the Center for Epidemiologic Studies Depression (CES-D) scale and the homeostatic model assessment for insulin resistance (HOMA-IR), respectively. RESULTS: Among 4044 participants (baseline mean age 34.9 ± 3.7 years, 53% women, 51% Black participants), HOMA-IR and CES-D traits were weakly correlated (r = 0.081, p = 0.002). Some occasion-specific correlations, but no cross-lagged associations were observed overall. Longitudinal dynamics of these relationships differed by population groups such that HOMA-IR at age 50 was associated with CES-D score at age 55 (ß = 0.076, p = 0.038) in White participants only. Longitudinal dynamics were consistent between sexes and based on education. CONCLUSIONS: The relationship between depressive symptoms and insulin resistance was best characterized by weak correlations between occasion-specific states and enduring traits, with weak evidence that insulin resistance might be temporally associated with subsequent depressive symptoms among White participants later in adulthood.

Cardiovascular health, infection burden and their interactive association with brain volumetric and white matter integrity outcomes in the UK Biobank.

BACKGROUND: Cardiovascular health is associated with brain magnetic resonance imaging (MRI) markers of pathology and infections may modulate this association. METHODS: Using data from 38,803 adults (aged 40-70 years) and followed-up for 5-15 years, we tested associations of prevalent total (47.5%) and hospital-treated infection burden (9.7%) with brain structural and diffusion-weighted MRI (i.e., sMRI and dMRI, respectively) common in dementia phenome. Poor white matter tissue integrity was operationalized with lower global and tract-specific fractional anisotropy (FA) and higher mean diffusivity (MD). Volumetric sMRI outcomes included total, gray matter (GM), white matter (WM), frontal bilateral GM, white matter hyperintensity (WMH), and selected based on previous associations with dementia. Cardiovascular health was measured with Life's Essential 8 score (LE8) converted to tertiles. Multiple linear regression models were used, adjusting for intracranial volumes (ICV) for subcortical structures, and for demographic, socio-economic, and the Alzheimer's Disease polygenic risk score for all outcomes, among potential confounders. RESULTS: In fully adjusted models, hospital-treated infections were inversely related to GM (ß ± SE: -1042 ± 379, p = 0.006) and directly related to WMH as percent of ICV (Loge transformed) (ß ± SE:+0.026 ± 0.007, p < 0.001). Both total and hospital-treated infections were associated with poor WMI, while the latter was inversely related to FA within the lowest LE8 tertile (ß ± SE:-0.0011 ± 0.0003, p < 0.001, PLE8×IB < 0.05), a pattern detected for GM, Right Frontal GM, left accumbens and left hippocampus volumes. Within the uppermost LE8 tertile, total infection burden was linked to smaller right amygdala while being associated with larger left frontal GM and right putamen volumes, in the overall sample. Within that uppermost tertile of LE8, caudate volumes were also positively associated with hospital-treated infections. CONCLUSIONS: Hospital-treated infections had more consistent deleterious effects on volumetric and white matter integrity brain neuroimaging outcomes compared with total infectious burden, particularly in poorer cardiovascular health groups. Further studies are needed in comparable populations, including longitudinal studies with multiple repeats on neuroimaging markers.

A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study).

AIMS: Atrial fibrillation (AF) is associated with high risk of comorbidities and mortality. Our aim was to examine causal and predictive relationships between 4137 serum proteins and incident AF in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study. METHODS AND RESULTS: The study included 4765 participants, of whom 1172 developed AF. Cox proportional hazards regression models were fitted for 4137 baseline protein measurements adjusting for known risk factors. Protein associations were tested for replication in the Cardiovascular Health Study (CHS). Causal relationships were examined in a bidirectional, two-sample Mendelian randomization analysis. The time-dependent area under the receiver operating characteristic curve (AUC)-statistic was examined as protein levels and an AF-polygenic risk score (PRS) were added to clinical risk models. The proteomic signature of incident AF consisted of 76 proteins, of which 63 (83%) were novel and 29 (38%) were replicated in CHS. The signature included both N-terminal prohormone of brain natriuretic peptide (NT-proBNP)-dependent (e.g. CHST15, ATP1B1, and SVEP1) and independent components (e.g. ASPN, AKR1B, and LAMA1/LAMB1/LAMC1). Nine causal candidates were identified (TAGLN, WARS, CHST15, CHMP3, COL15A1, DUSP13, MANBA, QSOX2, and SRL). The reverse causal analysis suggested that most AF-associated proteins were affected by the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide improved the prediction of incident AF events close to baseline with further improvements gained by the AF-PRS at all time points. CONCLUSION: The AF proteomic signature includes biologically relevant proteins, some of which may be causal. It mainly reflects an NT-proBNP-dependent consequence of the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide is a promising marker for incident AF in the short term, but risk assessment incorporating a PRS may improve long-term risk assessment.

Gene-mapping study of extremes of cerebral small vessel disease reveals TRIM47 as a strong candidate.

Cerebral small vessel disease is a leading cause of stroke and a major contributor to cognitive decline and dementia, but our understanding of specific genes underlying the cause of sporadic cerebral small vessel disease is limited. We report a genome-wide association study and a whole-exome association study on a composite extreme phenotype of cerebral small vessel disease derived from its most common MRI features: white matter hyperintensities and lacunes. Seventeen population-based cohorts of older persons with MRI measurements and genome-wide genotyping (n = 41 326), whole-exome sequencing (n = 15 965), or exome chip (n = 5249) data contributed 13 776 and 7079 extreme small vessel disease samples for the genome-wide association study and whole-exome association study, respectively. The genome-wide association study identified significant association of common variants in 11 loci with extreme small vessel disease, of which the chr12q24.11 locus was not previously reported to be associated with any MRI marker of cerebral small vessel disease. The whole-exome association study identified significant associations of extreme small vessel disease with common variants in the 5' UTR region of EFEMP1 (chr2p16.1) and one probably damaging common missense variant in TRIM47 (chr17q25.1). Mendelian randomization supports the causal association of extensive small vessel disease severity with increased risk of stroke and Alzheimer's disease. Combined evidence from summary-based Mendelian randomization studies and profiling of human loss-of-function allele carriers showed an inverse relation between TRIM47 expression in the brain and blood vessels and extensive small vessel disease severity. We observed significant enrichment of Trim47 in isolated brain vessel preparations compared to total brain fraction in mice, in line with the literature showing Trim47 enrichment in brain endothelial cells at single cell level. Functional evaluation of TRIM47 by small interfering RNAs-mediated knockdown in human brain endothelial cells showed increased endothelial permeability, an important hallmark of cerebral small vessel disease pathology. Overall, our comprehensive gene-mapping study and preliminary functional evaluation suggests a putative role of TRIM47 in the pathophysiology of cerebral small vessel disease, making it an important candidate for extensive in vivo explorations and future translational work.

The Proteomic Profile of Interstitial Lung Abnormalities.

Rationale: Knowledge on biomarkers of interstitial lung disease is incomplete. Interstitial lung abnormalities (ILAs) are radiologic changes that may present in its early stages. Objectives: To uncover blood proteins associated with ILAs using large-scale proteomics methods. Methods: Data from two prospective cohort studies, the AGES-Reykjavik (Age, Gene/Environment Susceptibility-Reykjavik) study (N = 5,259) for biomarker discovery and the COPDGene (Genetic Epidemiology of COPD) study (N = 4,899) for replication, were used. Blood proteins were measured using DNA aptamers, targeting more than 4,700 protein analytes. The association of proteins with ILAs and ILA progression was assessed with regression modeling, as were associations with genetic risk factors. Adaptive Least Absolute Shrinkage and Selection Operator models were applied to bootstrap data samples to discover sets of proteins predictive of ILAs and their progression. Measurements and Main Results: Of 287 associations, SFTPB (surfactant protein B) (odds ratio [OR], 3.71 [95% confidence interval (CI), 3.20-4.30]; P = 4.28 × 10-67), SCGB3A1 (Secretoglobin family 3A member 1) (OR, 2.43 [95% CI, 2.13-2.77]; P = 8.01 × 10-40), and WFDC2 (WAP four-disulfide core domain protein 2) (OR, 2.42 [95% CI, 2.11-2.78]; P = 4.01 × 10-36) were most significantly associated with ILA in AGES-Reykjavik and were replicated in COPDGene. In AGES-Reykjavik, concentrations of SFTPB were associated with the rs35705950 MUC5B (mucin 5B) promoter polymorphism, and SFTPB and WFDC2 had the strongest associations with ILA progression. Multivariate models of ILAs in AGES-Reykjavik, ILAs in COPDGene, and ILA progression in AGES-Reykjavik had validated areas under the receiver operating characteristic curve of 0.880, 0.826, and 0.824, respectively. Conclusions: Novel, replicated associations of ILA, its progression, and genetic risk factors with numerous blood proteins are demonstrated as well as machine-learning-based models with favorable predictive potential. Several proteins are revealed as potential markers of early fibrotic lung disease.

Associations of Monocyte Count and Other Immune Cell Types with Interstitial Lung Abnormalities.

Rationale: Higher blood monocyte counts are associated with worse survival in adults with clinically diagnosed pulmonary fibrosis. Their association with the development and progression of interstitial lung abnormalities (ILA) in humans is unknown. Objectives: We evaluated the associations of blood monocyte count, and other immune cell types, with ILA, high-attenuation areas, and FVC in four independent cohorts. Methods: We included participants with measured monocyte counts and computed tomographic (CT) imaging enrolled in MESA (Multi-Ethnic Study of Atherosclerosis, n = 484), AGES-Reykjavik (Age/Gene Environment Susceptibility Study, n = 3,547), COPDGene (Genetic Epidemiology of COPD, n = 2,719), and the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points, n = 646). Measurements and Main Results: After adjustment for covariates, a 1-SD increment in blood monocyte count was associated with ILA in MESA (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.0-1.8), AGES-Reykjavik (OR, 1.2; 95% CI, 1.1-1.3), COPDGene (OR, 1.3; 95% CI, 1.2-1.4), and ECLIPSE (OR, 1.2; 95% CI, 1.0-1.4). A higher monocyte count was associated with ILA progression over 5 years in AGES-Reykjavik (OR, 1.2; 95% CI, 1.0-1.3). Compared with participants without ILA, there was a higher percentage of activated monocytes among those with ILA in MESA. Higher monocyte count was associated with greater high-attenuation areas in MESA and lower FVC in MESA and COPDGene. Associations of other immune cell types were less consistent. Conclusions: Higher blood monocyte counts were associated with the presence and progression of interstitial lung abnormalities and lower FVC.

Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study.

BACKGROUND: Early identification of dementia is crucial for prompt intervention for high-risk individuals in the general population. External validation studies on prognostic models for dementia have highlighted the need for updated models. The use of machine learning in dementia prediction is in its infancy and may improve predictive performance. The current study aimed to explore the difference in performance of machine learning algorithms compared to traditional statistical techniques, such as logistic and Cox regression, for prediction of all-cause dementia. Our secondary aim was to assess the feasibility of only using clinically accessible predictors rather than MRI predictors. METHODS: Data are from 4,793 participants in the population-based AGES-Reykjavik Study without dementia or mild cognitive impairment at baseline (mean age: 76 years, % female: 59%). Cognitive, biometric, and MRI assessments (total: 59 variables) were collected at baseline, with follow-up of incident dementia diagnoses for a maximum of 12 years. Machine learning algorithms included elastic net regression, random forest, support vector machine, and elastic net Cox regression. Traditional statistical methods for comparison were logistic and Cox regression. Model 1 was fit using all variables and model 2 was after feature selection using the Boruta package. A third model explored performance when leaving out neuroimaging markers (clinically accessible model). Ten-fold cross-validation, repeated ten times, was implemented during training. Upsampling was used to account for imbalanced data. Tuning parameters were optimized for recalibration automatically using the caret package in R. RESULTS: 19% of participants developed all-cause dementia. Machine learning algorithms were comparable in performance to logistic regression in all three models. However, a slight added performance was observed in the elastic net Cox regression in the third model (c = 0.78, 95% CI: 0.78-0.78) compared to the traditional Cox regression (c = 0.75, 95% CI: 0.74-0.77). CONCLUSIONS: Supervised machine learning only showed added benefit when using survival techniques. Removing MRI markers did not significantly worsen our model's performance. Further, we presented the use of a nomogram using machine learning methods, showing transportability for the use of machine learning models in clinical practice. External validation is needed to assess the use of this model in other populations. Identifying high-risk individuals will amplify prevention efforts and selection for clinical trials.

Mid- and later-life risk factors for predicting neuropathological brain changes associated with Alzheimer's and vascular dementia: The Honolulu Asia Aging Study and the Age, Gene/Environment Susceptibility-Reykjavik Study.

INTRODUCTION: Dementia prediction models are necessary to inform the development of dementia risk reduction strategies. Here, we examine the utility of neuropathological-based risk scores to predict clinical dementia. METHODS: Models were developed for predicting Alzheimer's disease (AD) and non-AD neuropathologies using the Honolulu Asia Aging neuropathological sub-study (HAAS; n = 852). Model accuracy for predicting clinical dementia, over 30 years, was tested in the non-autopsied HAAS sample (n = 2960) and the Age, Gene/Environment Susceptibility-Reykjavik Study (n = 4614). RESULTS: Different models were identified for predicting neurodegenerative and vascular neuropathology (c-statistic range: 0.62 to 0.72). These typically included age, APOE, and a blood pressure-related measure. The neurofibrillary tangle and micro-vascular lesion models showed good accuracy for predicting clinical vascular dementia. DISCUSSION: There may be shared risk factors across dementia-related lesions, suggesting common pathways. Strategies targeting these models may reduce risk or postpone clinical symptoms of dementia as well as reduce neuropathological burden associated with AD and vascular lesions.

Cardiovascular health, infection burden, and incident dementia in the UK Biobank.

INTRODUCTION: Among older adults, total and hospitalized infection may be associated with incidence of all-cause and Alzheimer's disease (AD) dementias, with variation by cardiovascular health (CVH). METHODS: We used Cox proportional hazards (PH) models to examine the relationships between International Classification of Diseases-10th revision (ICD-10)-specific viral and bacterial infectious agents and incident all-cause and AD dementia among 355,046 UK Biobank participants ≥50 years at baseline. Life's Essential 8 (LE8) index reflected CVH. RESULTS: In both sexes, total infection burden (yes vs. no) was associated with all-cause dementia, with significant interactions by LE8 tertiles, whereby this relationship was significant only in the lowest LE8 tertile. Hospital-treated infection burden (yes vs no) was significantly related to all-cause and AD dementia, with no significant interaction with LE8 tertile. Age group patterns were detected. DISCUSSION: AD and all-cause dementia were related to hospital-treated infections, while CVH modified the relationship of total infection burden with all-cause dementia. Highlights Secondary analysis on >355,000 UK Biobank participants ≥50 years at baseline. Alzheimer's disease and all-cause dementia are both related to hospital-treated infection. Cardiovascular health modifies association of infection burden with all-cause dementia.