@article {8016, title = {Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.}, journal = {Nat Genet}, volume = {44}, year = {2012}, month = {2012 Apr 15}, pages = {491-501}, abstract = {

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 {\texttimes} 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 {\texttimes} 10(-4), Bonferroni corrected), of which six reached P < 5 {\texttimes} 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

}, keywords = {Bone Density, Computational Biology, European Continental Ancestry Group, Extracellular Matrix Proteins, Female, Femur Neck, Fractures, Bone, Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Glycoproteins, Humans, Intercellular Signaling Peptides and Proteins, Low Density Lipoprotein Receptor-Related Protein-5, Lumbar Vertebrae, Male, Mitochondrial Membrane Transport Proteins, Osteoporosis, Phosphoproteins, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Spectrin}, issn = {1546-1718}, doi = {10.1038/ng.2249}, author = {Estrada, Karol and Styrkarsdottir, Unnur and Evangelou, Evangelos and Hsu, Yi-Hsiang and Duncan, Emma L and Ntzani, Evangelia E and Oei, Ling and Albagha, Omar M E and Amin, Najaf and Kemp, John P and Koller, Daniel L and Li, Guo and Liu, Ching-Ti and Minster, Ryan L and Moayyeri, Alireza and Vandenput, Liesbeth and Willner, Dana and Xiao, Su-Mei and Yerges-Armstrong, Laura M and Zheng, Hou-Feng and Alonso, Nerea and Eriksson, Joel and Kammerer, Candace M and Kaptoge, Stephen K and Leo, Paul J and Thorleifsson, Gudmar and Wilson, Scott G and Wilson, James F and Aalto, Ville and Alen, Markku and Aragaki, Aaron K and Aspelund, Thor and Center, Jacqueline R and Dailiana, Zoe and Duggan, David J and Garcia, Melissa and Garc{\'\i}a-Giralt, Natalia and Giroux, Sylvie and Hallmans, G{\"o}ran and Hocking, Lynne J and Husted, Lise Bjerre and Jameson, Karen A and Khusainova, Rita and Kim, Ghi Su and Kooperberg, Charles and Koromila, Theodora and Kruk, Marcin and Laaksonen, Marika and LaCroix, Andrea Z and Lee, Seung Hun and Leung, Ping C and Lewis, Joshua R and Masi, Laura and Mencej-Bedrac, Simona and Nguyen, Tuan V and Nogues, Xavier and Patel, Millan S and Prezelj, Janez and Rose, Lynda M and Scollen, Serena and Siggeirsdottir, Kristin and Smith, Albert V and Svensson, Olle and Trompet, Stella and Trummer, Olivia and van Schoor, Natasja M and Woo, Jean and Zhu, Kun and Balcells, Susana and Brandi, Maria Luisa and Buckley, Brendan M and Cheng, Sulin and Christiansen, Claus and Cooper, Cyrus and Dedoussis, George and Ford, Ian and Frost, Morten and Goltzman, David and Gonz{\'a}lez-Mac{\'\i}as, Jes{\'u}s and K{\"a}h{\"o}nen, Mika and Karlsson, Magnus and Khusnutdinova, Elza and Koh, Jung-Min and Kollia, Panagoula and Langdahl, Bente Lomholt and Leslie, William D and Lips, Paul and Ljunggren, Osten and Lorenc, Roman S and Marc, Janja and Mellstr{\"o}m, Dan and Obermayer-Pietsch, Barbara and Olmos, Jos{\'e} M and Pettersson-Kymmer, Ulrika and Reid, David M and Riancho, Jos{\'e} A and Ridker, Paul M and Rousseau, Fran{\c c}ois and Slagboom, P Eline and Tang, Nelson L S and Urreizti, Roser and Van Hul, Wim and Viikari, Jorma and Zarrabeitia, Mar{\'\i}a T and Aulchenko, Yurii S and Castano-Betancourt, Martha and Grundberg, Elin and Herrera, Lizbeth and Ingvarsson, Thorvaldur and Johannsdottir, Hrefna and Kwan, Tony and Li, Rui and Luben, Robert and Medina-G{\'o}mez, Carolina and Palsson, Stefan Th and Reppe, Sjur and Rotter, Jerome I and Sigurdsson, Gunnar and van Meurs, Joyce B J and Verlaan, Dominique and Williams, Frances M K and Wood, Andrew R and Zhou, Yanhua and Gautvik, Kaare M and Pastinen, Tomi and Raychaudhuri, Soumya and Cauley, Jane A and Chasman, Daniel I and Clark, Graeme R and Cummings, Steven R and Danoy, Patrick and Dennison, Elaine M and Eastell, Richard and Eisman, John A and Gudnason, Vilmundur and Hofman, Albert and Jackson, Rebecca D and Jones, Graeme and Jukema, J Wouter and Khaw, Kay-Tee and Lehtim{\"a}ki, Terho and Liu, Yongmei and Lorentzon, Mattias and McCloskey, Eugene and Mitchell, Braxton D and Nandakumar, Kannabiran and Nicholson, Geoffrey C and Oostra, Ben A and Peacock, Munro and Pols, Huibert A P and Prince, Richard L and Raitakari, Olli and Reid, Ian R and Robbins, John and Sambrook, Philip N and Sham, Pak Chung and Shuldiner, Alan R and Tylavsky, Frances A and van Duijn, Cornelia M and Wareham, Nick J and Cupples, L Adrienne and Econs, Michael J and Evans, David M and Harris, Tamara B and Kung, Annie Wai Chee and Psaty, Bruce M and Reeve, Jonathan and Spector, Timothy D and Streeten, Elizabeth A and Zillikens, M Carola and Thorsteinsdottir, Unnur and Ohlsson, Claes and Karasik, David and Richards, J Brent and Brown, Matthew A and Stefansson, Kari and Uitterlinden, Andr{\'e} G and Ralston, Stuart H and Ioannidis, John P A and Kiel, Douglas P and Rivadeneira, Fernando} } @article {7142, title = {GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium.}, journal = {Aging Cell}, volume = {15}, year = {2016}, month = {2016 Oct}, pages = {792-800}, abstract = {

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27~581 individuals of European descent over 65~years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5~{\texttimes}~10(-8) ) and 39 suggestive (P-value< 5~{\texttimes}~10(-5) ) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β~=~0.47, SE~=~0.08, P-value~=~5.20~{\texttimes}~10(-10) ). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength.

}, issn = {1474-9726}, doi = {10.1111/acel.12468}, author = {Matteini, Amy M and Tanaka, Toshiko and Karasik, David and Atzmon, Gil and Chou, Wen-Chi and Eicher, John D and Johnson, Andrew D and Arnold, Alice M and Callisaya, Michele L and Davies, Gail and Evans, Daniel S and Holtfreter, Birte and Lohman, Kurt and Lunetta, Kathryn L and Mangino, Massimo and Smith, Albert V and Smith, Jennifer A and Teumer, Alexander and Yu, Lei and Arking, Dan E and Buchman, Aron S and Chibinik, Lori B and De Jager, Philip L and Evans, Denis A and Faul, Jessica D and Garcia, Melissa E and Gillham-Nasenya, Irina and Gudnason, Vilmundur and Hofman, Albert and Hsu, Yi-Hsiang and Ittermann, Till and Lahousse, Lies and Liewald, David C and Liu, Yongmei and Lopez, Lorna and Rivadeneira, Fernando and Rotter, Jerome I and Siggeirsdottir, Kristin and Starr, John M and Thomson, Russell and Tranah, Gregory J and Uitterlinden, Andr{\'e} G and V{\"o}lker, Uwe and V{\"o}lzke, Henry and Weir, David R and Yaffe, Kristine and Zhao, Wei and Zhuang, Wei Vivian and Zmuda, Joseph M and Bennett, David A and Cummings, Steven R and Deary, Ian J and Ferrucci, Luigi and Harris, Tamara B and Kardia, Sharon L R and Kocher, Thomas and Kritchevsky, Stephen B and Psaty, Bruce M and Seshadri, Sudha and Spector, Timothy D and Srikanth, Velandai K and Windham, B Gwen and Zillikens, M Carola and Newman, Anne B and Walston, Jeremy D and Kiel, Douglas P and Murabito, Joanne M} } @article {9640, title = {Plasma proteomic signature of human longevity.}, journal = {Aging Cell}, year = {2024}, month = {2024 Mar 05}, pages = {e14136}, abstract = {

The identification of protein targets that exhibit anti-aging clinical potential could inform interventions to lengthen the human health span. Most previous proteomics research has been focused on chronological age instead of longevity. We leveraged two large population-based prospective cohorts with long follow-ups to evaluate the proteomic signature of longevity defined by survival to 90 years of age. Plasma proteomics was measured using a SOMAscan assay in 3067 participants from the Cardiovascular Health Study (discovery cohort) and 4690 participants from the Age Gene/Environment Susceptibility-Reykjavik Study (replication cohort). Logistic regression identified 211 significant proteins in the CHS cohort using a Bonferroni-adjusted threshold, of which 168 were available in the replication cohort and 105 were replicated (corrected p value <0.05). The most significant proteins were GDF-15 and N-terminal pro-BNP in both cohorts. A parsimonious protein-based prediction model was built using 33 proteins selected by LASSO with 10-fold cross-validation and validated using 27 available proteins in the validation cohort. This protein model outperformed a basic model using traditional factors (demographics, height, weight, and smoking) by improving the AUC from 0.658 to 0.748 in the discovery cohort and from 0.755 to 0.802 in the validation cohort. We also found that the associations of 169 out of 211 proteins were partially mediated by physical and/or cognitive function. These findings could contribute to the identification of biomarkers and pathways of aging and potential therapeutic targets to delay aging and age-related diseases.

}, issn = {1474-9726}, doi = {10.1111/acel.14136}, author = {Liu, Xiaojuan and Axelsson, Gisli Thor and Newman, Anne B and Psaty, Bruce M and Boudreau, Robert M and Wu, Chenkai and Arnold, Alice M and Aspelund, Thor and Austin, Thomas R and Gardin, Julius M and Siggeirsdottir, Kristin and Tracy, Russell P and Gerszten, Robert E and Launer, Lenore J and Jennings, Lori L and Gudnason, Vilmundur and Sanders, Jason L and Odden, Michelle C} }