@article {7594, title = {Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study.}, journal = {JAMA Oncol}, volume = {3}, year = {2017}, month = {2017 May 01}, pages = {636-651}, abstract = {

Importance: The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

Objective: To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

Data Sources: Genomewide association studies (GWAS) published up to January 15, 2015.

Study Selection: GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

Data Extraction and Synthesis: Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

Main Outcomes and Measures: Odds ratios (ORs) and 95\% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

Results: Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95\% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95\% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95\% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95\% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95\% CI, 0.05-0.15]).

Conclusions and Relevance: It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

}, keywords = {Adult, Aged, Aged, 80 and over, Cardiovascular Diseases, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Germ-Line Mutation, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Neoplasms, Polymorphism, Single Nucleotide, Risk Assessment, Telomere, Telomere Homeostasis}, issn = {2374-2445}, doi = {10.1001/jamaoncol.2016.5945}, author = {Haycock, Philip C and Burgess, Stephen and Nounu, Aayah and Zheng, Jie and Okoli, George N and Bowden, Jack and Wade, Kaitlin Hazel and Timpson, Nicholas J and Evans, David M and Willeit, Peter and Aviv, Abraham and Gaunt, Tom R and Hemani, Gibran and Mangino, Massimo and Ellis, Hayley Patricia and Kurian, Kathreena M and Pooley, Karen A and Eeles, Rosalind A and Lee, Jeffrey E and Fang, Shenying and Chen, Wei V and Law, Matthew H and Bowdler, Lisa M and Iles, Mark M and Yang, Qiong and Worrall, Bradford B and Markus, Hugh Stephen and Hung, Rayjean J and Amos, Chris I and Spurdle, Amanda B and Thompson, Deborah J and O{\textquoteright}Mara, Tracy A and Wolpin, Brian and Amundadottir, Laufey and Stolzenberg-Solomon, Rachael and Trichopoulou, Antonia and Onland-Moret, N Charlotte and Lund, Eiliv and Duell, Eric J and Canzian, Federico and Severi, Gianluca and Overvad, Kim and Gunter, Marc J and Tumino, Rosario and Svenson, Ulrika and van Rij, Andre and Baas, Annette F and Bown, Matthew J and Samani, Nilesh J and van t{\textquoteright}Hof, Femke N G and Tromp, Gerard and Jones, Gregory T and Kuivaniemi, Helena and Elmore, James R and Johansson, Mattias and Mckay, James and Scelo, Ghislaine and Carreras-Torres, Robert and Gaborieau, Valerie and Brennan, Paul and Bracci, Paige M and Neale, Rachel E and Olson, Sara H and Gallinger, Steven and Li, Donghui and Petersen, Gloria M and Risch, Harvey A and Klein, Alison P and Han, Jiali and Abnet, Christian C and Freedman, Neal D and Taylor, Philip R and Maris, John M and Aben, Katja K and Kiemeney, Lambertus A and Vermeulen, Sita H and Wiencke, John K and Walsh, Kyle M and Wrensch, Margaret and Rice, Terri and Turnbull, Clare and Litchfield, Kevin and Paternoster, Lavinia and Standl, Marie and Abecasis, Goncalo R and SanGiovanni, John Paul and Li, Yong and Mijatovic, Vladan and Sapkota, Yadav and Low, Siew-Kee and Zondervan, Krina T and Montgomery, Grant W and Nyholt, Dale R and van Heel, David A and Hunt, Karen and Arking, Dan E and Ashar, Foram N and Sotoodehnia, Nona and Woo, Daniel and Rosand, Jonathan and Comeau, Mary E and Brown, W Mark and Silverman, Edwin K and Hokanson, John E and Cho, Michael H and Hui, Jennie and Ferreira, Manuel A and Thompson, Philip J and Morrison, Alanna C and Felix, Janine F and Smith, Nicholas L and Christiano, Angela M and Petukhova, Lynn and Betz, Regina C and Fan, Xing and Zhang, Xuejun and Zhu, Caihong and Langefeld, Carl D and Thompson, Susan D and Wang, Feijie and Lin, Xu and Schwartz, David A and Fingerlin, Tasha and Rotter, Jerome I and Cotch, Mary Frances and Jensen, Richard A and Munz, Matthias and Dommisch, Henrik and Schaefer, Arne S and Han, Fang and Ollila, Hanna M and Hillary, Ryan P and Albagha, Omar and Ralston, Stuart H and Zeng, Chenjie and Zheng, Wei and Shu, Xiao-Ou and Reis, Andre and Uebe, Steffen and H{\"u}ffmeier, Ulrike and Kawamura, Yoshiya and Otowa, Takeshi and Sasaki, Tsukasa and Hibberd, Martin Lloyd and Davila, Sonia and Xie, Gang and Siminovitch, Katherine and Bei, Jin-Xin and Zeng, Yi-Xin and F{\"o}rsti, Asta and Chen, Bowang and Landi, Stefano and Franke, Andre and Fischer, Annegret and Ellinghaus, David and Flores, Carlos and Noth, Imre and Ma, Shwu-Fan and Foo, Jia Nee and Liu, Jianjun and Kim, Jong-Won and Cox, David G and Delattre, Olivier and Mirabeau, Olivier and Skibola, Christine F and Tang, Clara S and Garcia-Barcelo, Merce and Chang, Kai-Ping and Su, Wen-Hui and Chang, Yu-Sun and Martin, Nicholas G and Gordon, Scott and Wade, Tracey D and Lee, Chaeyoung and Kubo, Michiaki and Cha, Pei-Chieng and Nakamura, Yusuke and Levy, Daniel and Kimura, Masayuki and Hwang, Shih-Jen and Hunt, Steven and Spector, Tim and Soranzo, Nicole and Manichaikul, Ani W and Barr, R Graham and Kahali, Bratati and Speliotes, Elizabeth and Yerges-Armstrong, Laura M and Cheng, Ching-Yu and Jonas, Jost B and Wong, Tien Yin and Fogh, Isabella and Lin, Kuang and Powell, John F and Rice, Kenneth and Relton, Caroline L and Martin, Richard M and Davey Smith, George} } @article {9086, title = {Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing.}, journal = {Eur J Epidemiol}, year = {2022}, month = {2022 Jul 05}, abstract = {

BACKGROUND: In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.

METHODS AND RESULTS: In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61\% women, mean age 74~years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.

CONCLUSION: The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.

}, issn = {1573-7284}, doi = {10.1007/s10654-022-00888-z}, author = {Austin, Thomas R and McHugh, Caitlin P and Brody, Jennifer A and Bis, Joshua C and Sitlani, Colleen M and Bartz, Traci M and Biggs, Mary L and Bansal, Nisha and B{\r u}zkov{\'a}, Petra and Carr, Steven A and deFilippi, Christopher R and Elkind, Mitchell S V and Fink, Howard A and Floyd, James S and Fohner, Alison E and Gerszten, Robert E and Heckbert, Susan R and Katz, Daniel H and Kizer, Jorge R and Lemaitre, Rozenn N and Longstreth, W T and McKnight, Barbara and Mei, Hao and Mukamal, Kenneth J and Newman, Anne B and Ngo, Debby and Odden, Michelle C and Vasan, Ramachandran S and Shojaie, Ali and Simon, Noah and Smith, George Davey and Davies, Neil M and Siscovick, David S and Sotoodehnia, Nona and Tracy, Russell P and Wiggins, Kerri L and Zheng, Jie and Psaty, Bruce M} } @article {9635, title = {Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures.}, journal = {J Bone Miner Res}, year = {2024}, month = {2024 Jan 04}, abstract = {

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Tr{\o}ndelag Health Study) with circulating proteomics data (aptamer-based 5~K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 {\texttimes} 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.

}, issn = {1523-4681}, doi = {10.1093/jbmr/zjad011}, author = {Austin, Thomas R and Fink, Howard A and Jalal, Diana I and T{\"o}rnqvist, Anna E and B{\r u}zkov{\'a}, Petra and Barzilay, Joshua I and Lu, Tianyuan and Carbone, Laura and Gabrielsen, Maiken E and Grahnemo, Louise and Hveem, Kristian and Jonasson, Christian and Kizer, Jorge R and Langhammer, Arnulf and Mukamal, Kenneth J and Gerszten, Robert E and Nethander, Maria and Psaty, Bruce M and Robbins, John A and Sun, Yan V and Skogholt, Anne Heidi and {\r A}svold, Bj{\o}rn Olav and Valderr{\'a}bano, Rodrigo J and Zheng, Jie and Richards, J Brent and Coward, Eivind and Ohlsson, Claes} } @article {9700, title = {A plasma protein-based risk score to predict hip fractures.}, journal = {Nat Aging}, year = {2024}, month = {2024 May 27}, abstract = {

As there are effective treatments to reduce hip fractures, identification of patients at high risk of hip fracture is important to inform efficient intervention strategies. To obtain a new tool for hip fracture prediction, we developed a protein-based risk score in the Cardiovascular Health Study using an aptamer-based proteomic platform. The proteomic risk score predicted incident hip fractures and improved hip fracture discrimination in two Tr{\o}ndelag Health Study validation cohorts using the same aptamer-based platform. When transferred to an antibody-based proteomic platform in a UK Biobank validation cohort, the proteomic risk score was strongly associated with hip fractures (hazard ratio per s.d. increase, 1.64; 95\% confidence interval 1.53-1.77). The proteomic risk score, but not available polygenic risk scores for fractures or bone mineral density, improved the C-index beyond the fracture risk assessment tool (FRAX), which integrates information from clinical risk factors (C-index, FRAX 0.735 versus FRAX + proteomic risk score 0.776). The developed proteomic risk score constitutes a new tool for stratifying patients according to hip fracture risk; however, its improvement in hip fracture discrimination is modest and its clinical utility beyond FRAX with information on femoral neck bone mineral density remains to be determined.

}, issn = {2662-8465}, doi = {10.1038/s43587-024-00639-7}, author = {Austin, Thomas R and Nethander, Maria and Fink, Howard A and T{\"o}rnqvist, Anna E and Jalal, Diana I and B{\r u}zkov{\'a}, Petra and Barzilay, Joshua I and Carbone, Laura and Gabrielsen, Maiken E and Grahnemo, Louise and Lu, Tianyuan and Hveem, Kristian and Jonasson, Christian and Kizer, Jorge R and Langhammer, Arnulf and Mukamal, Kenneth J and Gerszten, Robert E and Psaty, Bruce M and Robbins, John A and Sun, Yan V and Skogholt, Anne Heidi and Kanis, John A and Johansson, Helena and {\r A}svold, Bj{\o}rn Olav and Valderr{\'a}bano, Rodrigo J and Zheng, Jie and Richards, J Brent and Coward, Eivind and Ohlsson, Claes} }