@article {7796, title = {Exome Chip Analysis Identifies Low-Frequency and Rare Variants in for White Matter Hyperintensities on Brain Magnetic Resonance Imaging.}, journal = {Stroke}, year = {2018}, month = {2018 Jul 12}, abstract = {

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 , , and (<6{\texttimes}10). We also identified a novel association with 2 low-frequency nonsynonymous variants in (lead, rs34136221; =4.5{\texttimes}10) partially independent of known common signal (=1.4{\texttimes}10). We further identified a locus at 2q33 containing common variants in , , and (lead, rs2351524; =1.9{\texttimes}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 variants (=2.8{\texttimes}10).

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.

}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.118.020689}, author = {Jian, Xueqiu and Satizabal, Claudia L and Smith, Albert V and Wittfeld, Katharina and Bis, Joshua C and Smith, Jennifer A and Hsu, Fang-Chi and Nho, Kwangsik and Hofer, Edith and Hagenaars, Saskia P and Nyquist, Paul A and Mishra, Aniket and Adams, Hieab H H and Li, Shuo and Teumer, Alexander and Zhao, Wei and Freedman, Barry I and Saba, Yasaman and Yanek, Lisa R and Chauhan, Ganesh and van Buchem, Mark A and Cushman, Mary and Royle, Natalie A and Bryan, R Nick and Niessen, Wiro J and Windham, Beverly G and DeStefano, Anita L and Habes, Mohamad and Heckbert, Susan R and Palmer, Nicholette D and Lewis, Cora E and Eiriksdottir, Gudny and Maillard, Pauline and Mathias, Rasika A and Homuth, Georg and Vald{\'e}s-Hern{\'a}ndez, Maria Del C and Divers, Jasmin and Beiser, Alexa S and Langner, S{\"o}nke and Rice, Kenneth M and Bastin, Mark E and Yang, Qiong and Maldjian, Joseph A and Starr, John M and Sidney, Stephen and Risacher, Shannon L and Uitterlinden, Andr{\'e} G and Gudnason, Vilmundur G and Nauck, Matthias and Rotter, Jerome I and Schreiner, Pamela J and Boerwinkle, Eric and van Duijn, Cornelia M and Mazoyer, Bernard and von Sarnowski, Bettina and Gottesman, Rebecca F and Levy, Daniel and Sigurdsson, Sigurdur and Vernooij, Meike W and Turner, Stephen T and Schmidt, Reinhold and Wardlaw, Joanna M and Psaty, Bruce M and Mosley, Thomas H and DeCarli, Charles S and Saykin, Andrew J and Bowden, Donald W and Becker, Diane M and Deary, Ian J and Schmidt, Helena and Kardia, Sharon L R and Ikram, M Arfan and Debette, Stephanie and Grabe, Hans J and Longstreth, W T and Seshadri, Sudha and Launer, Lenore J and Fornage, Myriam} } @article {9163, title = {Associations of Pulmonary Function with MRI Brain Volumes: A Coordinated Multi-Study Analysis.}, journal = {J Alzheimers Dis}, year = {2022}, month = {2022 Oct 03}, abstract = {

BACKGROUND: Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent.

OBJECTIVE: To study the cross-sectional associations of pulmonary function with structural brain variables.

METHODS: Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses.

RESULTS: FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95\% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume.

CONCLUSION: In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.

}, issn = {1875-8908}, doi = {10.3233/JAD-220667}, author = {Frenzel, Stefan and Bis, Josh C and Gudmundsson, Elias F and O{\textquoteright}Donnell, Adrienne and Simino, Jeannette and Yaqub, Amber and Bartz, Traci M and Brusselle, Guy G O and B{\"u}low, Robin and DeCarli, Charles S and Ewert, Ralf and Gharib, Sina A and Ghosh, Saptaparni and Gireud-Goss, Monica and Gottesman, Rebecca F and Ikram, M Arfan and Knopman, David S and Launer, Lenore J and London, Stephanie J and Longstreth, W T and Lopez, Oscar L and Melo van Lent, Debora and O{\textquoteright}Connor, George and Satizabal, Claudia L and Shrestha, Srishti and Sigurdsson, Sigurdur and Stubbe, Beate and Talluri, Rajesh and Vasan, Ramachandran S and Vernooij, Meike W and V{\"o}lzke, Henry and Wiggins, Kerri L and Yu, Bing and Beiser, Alexa S and Gudnason, Vilmundur and Mosley, Thomas and Psaty, Bruce M and Wolters, Frank J and Grabe, Hans J and Seshadri, Sudha} } @article {9184, title = {Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.}, journal = {Brain}, year = {2022}, month = {2022 Aug 09}, abstract = {

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 approximately 450,000 CpG sites in 9,732 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 {\texttimes} 10-8), was associated with F2 expression in blood (P = 6.4 {\texttimes} 10-5), and colocalized 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 colocalization 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 antihyperlipidemic 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 antihyperlipidemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood brain barrier disruption.

}, issn = {1460-2156}, doi = {10.1093/brain/awac290}, author = {Yang, Yunju and Knol, Maria J and Wang, Ruiqi and Mishra, Aniket and Liu, Dan and Luciano, Michelle and Teumer, Alexander and Armstrong, Nicola and Bis, Joshua C and Jhun, Min A and Li, Shuo and Adams, Hieab H H and Aziz, Nasir Ahmad and Bastin, Mark E and Bourgey, Mathieu and Brody, Jennifer A and Frenzel, Stefan and Gottesman, Rebecca F and Hosten, Norbert and Hou, Lifang and Kardia, Sharon L R and Lohner, Valerie and Marquis, Pascale and Maniega, Susana Mu{\~n}oz and Satizabal, Claudia L and Sorond, Farzaneh A and Vald{\'e}s Hern{\'a}ndez, Maria C and van Duijn, Cornelia M and Vernooij, Meike W and Wittfeld, Katharina and Yang, Qiong and Zhao, Wei and Boerwinkle, Eric and Levy, Daniel and Deary, Ian J and Jiang, Jiyang and Mather, Karen A and Mosley, Thomas H and Psaty, Bruce M and Sachdev, Perminder S and Smith, Jennifer A and Sotoodehnia, Nona and DeCarli, Charles S and Breteler, Monique M B and Arfan Ikram, M and Grabe, Hans J and Wardlaw, Joanna and Longstreth, W T and Launer, Lenore J and Seshadri, Sudha and Debette, Stephanie and Fornage, Myriam} } @article {9323, title = {Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.}, journal = {Neurology}, year = {2023}, month = {2023 Mar 16}, abstract = {

BACKGROUND AND OBJECTIVES: Previous studies suggest lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer{\textquoteright}s disease (AD) and AD related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.

METHODS: We included dementia-free participants from nine diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within {\textpm}5 years (i.e., cross-sectional analyses) or 5 to 20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs. >=60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed Mendelian randomization (MR) analyses to assess causality.

RESULTS: We included up to 19,152 participants (mean age 59 years, 57\% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (Beta=0.04; 95\% CI 0.02, 0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.

DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the US. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.

}, issn = {1526-632X}, doi = {10.1212/WNL.0000000000207157}, author = {Zhang, Yuankai and Liu, Xue and Wiggins, Kerri L and Kurniansyah, Nuzulul and Guo, Xiuqing and Rodrigue, Amanda L and Zhao, Wei and Yanek, Lisa R and Ratliff, Scott M and Pitsillides, Achilleas and Aguirre Pati{\~n}o, Juan Sebastian and Sofer, Tamar and Arking, Dan E and Austin, Thomas R and Beiser, Alexa S and Blangero, John and Boerwinkle, Eric and Bressler, Jan and Curran, Joanne E and Hou, Lifang and Hughes, Timothy M and Kardia, Sharon L and Launer, Lenore and Levy, Daniel and Mosley, Tom H and Nasrallah, Ilya M and Rich, Stephen S and Rotter, Jerome I and Seshadri, Sudha and Tarraf, Wassim and Gonz{\'a}lez, Kevin A and Ramachandran, Vasan and Yaffe, Kristine and Nyquist, Paul A and Psaty, Bruce M and DeCarli, Charles S and Smith, Jennifer A and Glahn, David C and Gonz{\'a}lez, Hector M and Bis, Joshua C and Fornage, Myriam and Heckbert, Susan R and Fitzpatrick, Annette L and Liu, Chunyu and Satizabal, Claudia L} } @article {9940, title = {Selected social and lifestyle correlates of brain health markers: the Cross-Cohort Collaboration Consortium.}, journal = {Alzheimers Dement}, volume = {21}, year = {2025}, month = {2025 Apr}, pages = {e70148}, abstract = {

INTRODUCTION: To investigate the associations of education level, marital status, and physical activity with dementia risk and brain MRI markers.

METHODS: Data from six community-based samples from the Cross-Cohort Collaboration Consortium were analyzed. Self-reported education level, marital status, and physical activity at age 60 to 75 years were harmonized. Subsamples of participants with brain MRI markers at time of exposure were selected. Associations with dementia risk and cross-sectional MRI markers were meta-analyzed.

RESULTS: Higher education level was associated with lower dementia risk (hazard ratio [HR]~=~0.65, 95\% confidence interval [CI]~=~0.59; 0.72~vs low level) but not significantly with brain MRI markers. Compared with being unmarried, being married was only associated with higher total brain and hippocampal volumes. Being physically active was associated with lower dementia risk (HR~=~0.73, 95\% CI~=~0.52; 1.04), as well as larger total brain volume and smaller white matter hyperintensity volume.

DISCUSSION: This study provides further evidence regarding the contribution of education level and physical activity to dementia resilience.

HIGHLIGHTS: Education level, marital status, and physical activity are thought to contribute to resilience against ADRD. We used random-effects meta-analysis to summarize results from six community-based samples from the CCC. In this cross-cohort meta-analysis, higher education level and being physically active were associated with lower risk of dementia. In cross-sectional analyses, being married was associated with larger TBV and HV, while being physically active was associated with larger TBV and lower WMHV.

}, keywords = {Aged, Brain, Cohort Studies, Cross-Sectional Studies, Dementia, Educational Status, Exercise, Female, Humans, Life Style, Magnetic Resonance Imaging, Male, Marital Status, Middle Aged, Risk Factors}, issn = {1552-5279}, doi = {10.1002/alz.70148}, author = {Grasset, Leslie and Bis, Joshua C and Frenzel, Stefan and Kojis, Daniel and Simino, Jeannette and Yaqub, Amber and Beiser, Alexa and Berr, Claudine and Bressler, Jan and B{\"u}low, Robin and DeCarli, Charles S and Fohner, Alison E and Harrington, Laura B and Helmer, Catherine and Ikram, M Arfan and Lemaitre, Rozenn N and Lopez, Oscar L and Longstreth, W T and Neitzel, Julia and Odden, Michelle C and Palta, Priya and Schmidt, Carsten O and Talluri, Rajesh and Vernooij, Meike W and V{\"o}lzke, Henry and Voortman, Trudy and Whalen, Quest and Wittfeld, Katharina and Grabe, Hans J and Mosley, Thomas H and Psaty, Bruce M and Wolters, Frank J and Seshadri, Sudha and Dufouil, Carole} }