Bastin, Mark E.

Summary Background Clonal haematopoiesis (CH), the age-related expansion of mutated blood stem cells, is detectable in around 10% of people in their seventies, rises steeply with age, and is associated with several diseases. Its relationship with neurodegeneration remains contentious, with conflicting evidence for both protective and detrimental effects on Alzheimer’s disease (AD). Methods Here, we applied COMET, a mutation-agnostic, methylation-based predictor of clonal haematopoiesis burden that estimates predicted VAF (pVAF), to examine longitudinal associations between clonal burden and brain structure in the Lothian Birth Cohort 1936. In addition, to capture broader clonal burden, we developed CIMS, a novel methylation-based score derived from clonal haematopoiesis of indeterminate potential (CHIP) EWAS summary statistics, which reflects the epigenetic profile of both mutant and wild-type blood immune cells. Blood DNA methylation and structural MRI data were available at three timepoints spanning ages 73–79 years. The analytic dataset comprised 1,091 participants, of whom 808 (pVAF) and 836 (CIMS) contributed clonality data and 744 had brain MRI; 479–481 had complete baseline and longitudinal imaging measures with covariates. Trajectories were modelled with latent growth curve models fitted by full information maximum likelihood. Findings Longitudinal trajectories of clonality and grey matter volume were significantly associated over 6 years (Std. est. = −0.176, p adj = 0.030), revealing a progressive, left-lateralised cortical atrophy pattern affecting medial temporal and parietal regions. This pattern showed significant spatial correspondence with established AD signatures ( r = 0.357, p = 0.003), suggesting that clonality is linked to AD-related patterns of neurodegeneration. Subcortical analyses revealed nominal relative preservation of the caudate and did not detect a statistically significant association with hippocampal volume, suggesting potential divergence from the canonical AD subcortical profile. The CIMS confirmed global atrophy but revealed divergent tissue-type and regional patterns, suggesting the two measures may capture distinct aspects of CH biology. Interpretation Together, these findings suggest that CH burden may mark biological processes associated with structural brain atrophy in cognitively healthy older adults, with clonality showing a regional pattern that resembles the one reported in AD. CH burden may therefore be a candidate marker of adverse brain ageing; whether it tracks AD pathology in particular, rather than age-related neurodegeneration more broadly, remains to be tested.

Abstract 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.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Background and Purpose— White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods— In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results— At 17q25, we confirmed the association of multiple common variants in TRIM65 , FBF1 , and ACOX1 ( P <6×10 −7 ). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; P EA =4.5×10 −8 ) partially independent of known common signal ( P EA(conditional) =1.4×10 −3 ). We further identified a locus at 2q33 containing common variants in NBEAL1 , CARF , and WDR12 (lead, rs2351524; P all =1.9×10 −10 ). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( P rs34136221 =2.8×10 −8 ). Conclusions— Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.