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3. Whole genome‐wide sequence analysis of long‐lived families (Long‐Life Family Study) identifies MTUS2 gene associated with late‐onset Alzheimer's disease

Author

Xicota, Laura, Cosentino, Stephanie, Vardarajan, Badri, Mayeux, Richard, Perls, Thomas T, Andersen, Stacy L, Zmuda, Joseph M, Thyagarajan, Bharat, Yashin, Anatoli, Wojczynski, Mary K, Krinsky‐McHale, Sharon, Handen, Benjamin L, Christian, Bradley T, Head, Elizabeth, Mapstone, Mark E, Schupf, Nicole, Lee, Joseph H, Barral, Sandra, Study, the Long‐Life Family, Abner, Erin, Adams, Perrie M, Aguirre, Alyssa, Albert, Marilyn S, Albin, Roger L, Allen, Mariet, Alvarez, Lisa, Andrews, Howard, Apostolova, Liana G, Arnold, Steven E, Asthana, Sanjay, Atwood, Craig S, Ayres, Gayle, Barber, Robert C, Barnes, Lisa L, Bartlett, Jackie, Beach, Thomas G, Becker, James T, Beecham, Gary W, Benchek, Penelope, Bennett, David A, Bertelson, John, Biber, Sarah A, Bird, Thomas D, Blacker, Deborah, Boeve, Bradley F, Bowen, James D, Boxer, Adam, Brewer, James B, Burke, James R, Burns, Jeffrey M, Bush, William S, Buxbaum, Joseph D, Byrd, Goldie, Cantwell, Laura B, Cao, Chuanhai, Carlsson, Cynthia M, Carrasquillo, Minerva M, Chan, Kwun C, Chasse, Scott, Chen, Yen‐Chi, Chesselet, Marie‐Francoise, Chin, Nathaniel A, Chui, Helena C, Chung, Jaeyoon, Craft, Suzanne, Crane, Paul K, Cranney, Marissa, Cruchaga, Carlos, Cuccaro, Michael L, Culhane, Jessica, Cullum, C Munro, Darby, Eveleen, Davis, Barbara, De Jager, Philip L, DeCarli, Charles, DeToledo, John C, Dickson, Dennis W, Dobbins, Nic, Duara, Ranjan, Ertekin‐Taner, Nilufer, Evans, Denis A, Faber, Kelley M, Fairchild, Thomas J, Fallin, Daniele, Fallon, Kenneth B, Fardo, David W, Farlow, Martin R, Farrell, John, Farrer, Lindsay A, Fernandez‐Hernandez, Victoria, Foroud, Tatiana M, Frosch, Matthew P, Galasko, Douglas R, Gamboa, Adriana, Gauthreaux, Kathryn M, Gefen, Tamar, Geschwind, Daniel H, Ghetti, Bernardino, and Gilbert, John R

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Neurodegenerative, Dementia, Alzheimer's Disease, Genetics, Aging, Brain Disorders, Acquired Cognitive Impairment, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Neurological, Humans, Alzheimer Disease, Amyloid beta-Peptides, Genetic Predisposition to Disease, Genome-Wide Association Study, Microtubule-Associated Proteins, Polymorphism, Single Nucleotide, Sequence Analysis, genetic risk, late-onset Alzheimer's disease, microtubule protein, MTUS2 gene, whole genome sequence, Long‐Life Family Study, Alzheimer's Disease Genetic Consortium, Alzheimer's Biomarkers Consortium‐Down Syndrome, late‐onset Alzheimer's disease, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionLate-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.MethodsWe conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.ResultsWe identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.DiscussionMTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.HighlightsLong-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

Published
2024

4. A metabolomic signature of the APOE2 allele

Author

Sebastiani, Paola, Song, Zeyuan, Ellis, Dylan, Tian, Qu, Schwaiger-Haber, Michaela, Stancliffe, Ethan, Lustgarten, Michael S, Funk, Cory C, Baloni, Priyanka, Yao, Cong-Hui, Joshi, Shakchhi, Marron, Megan M, Gurinovich, Anastasia, Li, Mengze, Leshchyk, Anastasia, Xiang, Qingyan, Andersen, Stacy L, Feitosa, Mary F, Ukraintseva, Svetlana, Soerensen, Mette, Fiehn, Oliver, Ordovas, Jose M, Haigis, Marcia, Monti, Stefano, Barzilai, Nir, Milman, Sofiya, Ferrucci, Luigi, Rappaport, Noa, Patti, Gary J, and Perls, Thomas T

Subjects
Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Genetics, Aging, Aged, 80 and over, Humans, Apolipoprotein E2, Polymorphism, Genetic, Alleles, Longitudinal Studies, Apolipoproteins E, Apolipoprotein E, Longevity, Metabolomics, Lipid metabolism, Clinical sciences
Abstract

With the goal of identifying metabolites that significantly correlate with the protective e2 allele of the apolipoprotein E (APOE) gene, we established a consortium of five studies of healthy aging and extreme human longevity with 3545 participants. This consortium includes the New England Centenarian Study, the Baltimore Longitudinal Study of Aging, the Arivale study, the Longevity Genes Project/LonGenity studies, and the Long Life Family Study. We analyzed the association between APOE genotype groups E2 (e2e2 and e2e3 genotypes, N = 544), E3 (e3e3 genotypes, N = 2299), and E4 (e3e4 and e4e4 genotypes, N = 702) with metabolite profiles in the five studies and used fixed effect meta-analysis to aggregate the results. Our meta-analysis identified a signature of 19 metabolites that are significantly associated with the E2 genotype group at FDR

Published
2023

5. Metabolite signatures of chronological age, aging, survival, and longevity

Author

Sebastiani, Paola, Monti, Stefano, Lustgarten, Michael S., Song, Zeyuan, Ellis, Dylan, Tian, Qu, Schwaiger-Haber, Michaela, Stancliffe, Ethan, Leshchyk, Anastasia, Short, Meghan I., Ardisson Korat, Andres V., Gurinovich, Anastasia, Karagiannis, Tanya, Li, Mengze, Lords, Hannah J., Xiang, Qingyan, Marron, Megan M., Bae, Harold, Feitosa, Mary F., Wojczynski, Mary K., O’Connell, Jeffrey R., Montasser, May E., Schupf, Nicole, Arbeev, Konstantin, Yashin, Anatoliy, Schork, Nicholas, Christensen, Kaare, Andersen, Stacy L., Ferrucci, Luigi, Rappaport, Noa, Perls, Thomas T., and Patti, Gary J.

Published
2024
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7. A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Author

Deelen, Joris, Evans, Daniel S, Arking, Dan E, Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K, Biggs, Mary L, van der Spek, Ashley, Atzmon, Gil, Ware, Erin B, Sarnowski, Chloé, Smith, Albert V, Seppälä, Ilkka, Cordell, Heather J, Dose, Janina, Amin, Najaf, Arnold, Alice M, Ayers, Kristin L, Barzilai, Nir, Becker, Elizabeth J, Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C, Cubaynes, Sarah, Cummings, Steven R, Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D, Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B, Huisman, Martijn, Hurme, Mikko A, Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon LR, Kingston, Andrew, Kirkwood, Thomas BL, Launer, Lenore J, Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B, Nie, Chao, Nohr, Ellen A, Orwoll, Eric S, Perls, Thomas T, Province, Michael A, Psaty, Bruce M, Raitakari, Olli T, Reinders, Marcel JT, Robine, Jean-Marie, Rotter, Jerome I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild IA, Taylor, Kent D, Uitterlinden, André G, van der Flier, Wiesje, van der Lee, Sven J, van Duijn, Cornelia M, van Heemst, Diana, Vaupel, James W, Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P, Lunetta, Kathryn L, Slagboom, P Eline, and Murabito, Joanne M

Subjects
Humans, Heat-Shock Proteins, Longevity, Apolipoprotein E2, Apolipoprotein E4, Genome-Wide Association Study
Abstract

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Published
2019

10. All-Cause Mortality and Cause-Specific Death in U.S. Long-Lived Siblings: Data From the Long Life Family Study.

Author

Yao, Shanshan, Boudreau, Robert M, Galvin, Angéline, Murabito, Joanne M, Honig, Lawrence S, Perls, Thomas T, Christensen, Kaare, and Newman, Anne B

Subjects
CAUSES of death, FAMILIES, MORTALITY, LONGEVITY, SIBLINGS
Abstract

Background This study compared the mortality risk of long-lived siblings with the U.S. population average and their spouse controls, and investigated the leading causes of death and the familial effect in death pattern. Methods In the Long Life Family Study (LLFS), 1 264 proband siblings (mean age 90.1, standard deviation [ SD ] 6.4) and 172 spouses (83.8, 7.2) from 511 U.S.-based families were recruited and followed more than 12 years. Their survival function was compared with a birth cohort-, baseline age-, sex-, and race-matched pseudo sample from U.S. census data. To examine underlying and contributing causes, we examined in detail 338 deaths with complete death adjudication at the University of Pittsburgh Field Center through the year 2018. A familial effect on survival and death patterns was examined using mixed-effect models. Results The LLFS siblings had better survival than the matched U.S. population average. They also had slightly but not significantly better survival than their spouses' (HR = 1.18 [95%CI 0.94–1.49]) after adjusting for age and sex. Age at death ranged from 75 to 104 years, mean 91.4. The leading causes of death were cardiovascular disease (33.1%), dementia (22.2%), and cancer (10.7%). Mixed effect model shows a significant random effect of family in survival, with adjustment of baseline age and sex. There was no significant familial effect in the underlying cause of death or conditions directly contributing to death among siblings recruited by the University of Pittsburgh Field Center. Conclusions Our findings demonstrate a higher survival in the LLFS siblings than the U.S. census data, with a familial component of survival. We did not find significant correspondence in causes of death between siblings within families. [ABSTRACT FROM AUTHOR]

Published
2024
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11. A Novel Gene ARHGAP44 for Longitudinal Changes in Glycated Hemoglobin (HbA1c) in Subjects without Type 2 Diabetes: Evidence from the Long Life Family Study (LLFS) and the Framingham Offspring Study (FOS)

Author

Wang, Siyu, primary, Lenzini, Petra, additional, Thygarajan, Bharat, additional, Lee, Joseph H., additional, Vardarajan, Badri N., additional, Yashin, Anatoli, additional, Miljkovic, Iva, additional, Daw, E. Warwick, additional, Lin, Shiow J., additional, Patti, Gary, additional, Brent, Michael, additional, Zmuda, Joseph M., additional, Perls, Thomas T., additional, Christensen, Kaare, additional, Province, Michael A., additional, and An, Ping, additional

Published
2024
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12. Cross-platform proteomics signatures of extreme old age

Author

Reed, Eric R, primary, Chandler, Kevin B, additional, Lopez, Prisma, additional, Costello, Catherine E, additional, Anderson, Stacy L, additional, Perls, Thomas T, additional, Li, Mengze, additional, Bae, Harold, additional, Soerensen, Mette, additional, Monti, Stefano, additional, and Sebastiani, Paola, additional

Published
2024
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16. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy.

Author

Broer, Linda, Buchman, Aron S, Deelen, Joris, Evans, Daniel S, Faul, Jessica D, Lunetta, Kathryn L, Sebastiani, Paola, Smith, Jennifer A, Smith, Albert V, Tanaka, Toshiko, Yu, Lei, Arnold, Alice M, Aspelund, Thor, Benjamin, Emelia J, De Jager, Philip L, Eirkisdottir, Gudny, Evans, Denis A, Garcia, Melissa E, Hofman, Albert, Kaplan, Robert C, Kardia, Sharon LR, Kiel, Douglas P, Oostra, Ben A, Orwoll, Eric S, Parimi, Neeta, Psaty, Bruce M, Rivadeneira, Fernando, Rotter, Jerome I, Seshadri, Sudha, Singleton, Andrew, Tiemeier, Henning, Uitterlinden, André G, Zhao, Wei, Bandinelli, Stefania, Bennett, David A, Ferrucci, Luigi, Gudnason, Vilmundur, Harris, Tamara B, Karasik, David, Launer, Lenore J, Perls, Thomas T, Slagboom, P Eline, Tranah, Gregory J, Weir, David R, Newman, Anne B, van Duijn, Cornelia M, and Murabito, Joanne M

Subjects
Humans, Apolipoproteins E, Cell Adhesion Molecules, Receptors, Kainic Acid, Cohort Studies, Longevity, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, Female, Male, Forkhead Transcription Factors, Genome-Wide Association Study, Forkhead Box Protein O3, APOE., FOXO3, GWAS, APOE, Receptors, Kainic Acid, Polymorphism, Single Nucleotide, and over, Gerontology, Clinical Sciences
Abstract

BackgroundThe genetic contribution to longevity in humans has been estimated to range from 15% to 25%. Only two genes, APOE and FOXO3, have shown association with longevity in multiple independent studies.MethodsWe conducted a meta-analysis of genome-wide association studies including 6,036 longevity cases, age ≥90 years, and 3,757 controls that died between ages 55 and 80 years. We additionally attempted to replicate earlier identified single nucleotide polymorphism (SNP) associations with longevity.ResultsIn our meta-analysis, we found suggestive evidence for the association of SNPs near CADM2 (odds ratio [OR] = 0.81; p value = 9.66 × 10(-7)) and GRIK2 (odds ratio = 1.24; p value = 5.09 × 10(-8)) with longevity. When attempting to replicate findings earlier identified in genome-wide association studies, only the APOE locus consistently replicated. In an additional look-up of the candidate gene FOXO3, we found that an earlier identified variant shows a highly significant association with longevity when including published data with our meta-analysis (odds ratio = 1.17; p value = 1.85×10(-10)).ConclusionsWe did not identify new genome-wide significant associations with longevity and did not replicate earlier findings except for APOE and FOXO3. Our inability to find new associations with survival to ages ≥90 years because longevity represents multiple complex traits with heterogeneous genetic underpinnings, or alternatively, that longevity may be regulated by rare variants that are not captured by standard genome-wide genotyping and imputation of common variants.

Published
2015

17. A longevity-specific bank of induced pluripotent stem cells from centenarians and their offspring

Author

Dowrey, Todd W., primary, Cranston, Samuel F., additional, Skvir, Nicholas, additional, Lok, Yvonne, additional, Gould, Brian, additional, Petrowitz, Bradley, additional, Villar, Daniel, additional, Shan, Jidong, additional, James, Marianne, additional, Dodge, Mark, additional, Belkina, Anna C., additional, Giadone, Richard M., additional, Sebastiani, Paola, additional, Perls, Thomas T., additional, Andersen, Stacy L., additional, and Murphy, George J., additional

Published
2024
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18. Publisher Correction: A meta-analysis of genome-wide association studies identifies multiple longevity genes

Author

Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloé, Smith, Albert V., Seppälä, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psaty, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome I., Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., Taylor, Kent D., Uitterlinden, André G., van der Flier, Wiesje, van der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, and Murabito, Joanne M.

Published
2021
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19. Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits

Author

Kraja, Aldi T., Liu, Chunyu, Fetterman, Jessica L., Graff, Mariaelisa, Have, Christian Theil, Gu, Charles, Yanek, Lisa R., Feitosa, Mary F., Arking, Dan E., Chasman, Daniel I., Young, Kristin, Ligthart, Symen, Hill, W. David, Weiss, Stefan, Luan, Jian’an, Giulianini, Franco, Li-Gao, Ruifang, Hartwig, Fernando P., Lin, Shiow J., Wang, Lihua, Richardson, Tom G., Yao, Jie, Fernandez, Eliana P., Ghanbari, Mohsen, Wojczynski, Mary K., Lee, Wen-Jane, Argos, Maria, Armasu, Sebastian M., Barve, Ruteja A., Ryan, Kathleen A., An, Ping, Baranski, Thomas J., Bielinski, Suzette J., Bowden, Donald W., Broeckel, Ulrich, Christensen, Kaare, Chu, Audrey Y., Corley, Janie, Cox, Simon R., Uitterlinden, Andre G., Rivadeneira, Fernando, Cropp, Cheryl D., Daw, E. Warwick, van Heemst, Diana, de las Fuentes, Lisa, Gao, He, Tzoulaki, Ioanna, Ahluwalia, Tarunveer S., de Mutsert, Renée, Emery, Leslie S., Erzurumluoglu, A. Mesut, Perry, James A., Fu, Mao, Forouhi, Nita G., Gu, Zhenglong, Hai, Yang, Harris, Sarah E., Hemani, Gibran, Hunt, Steven C., Irvin, Marguerite R., Jonsson, Anna E., Justice, Anne E., Kerrison, Nicola D., Larson, Nicholas B., Lin, Keng-Hung, Love-Gregory, Latisha D., Mathias, Rasika A., Lee, Joseph H., Nauck, Matthias, Noordam, Raymond, Ong, Ken K., Pankow, James, Patki, Amit, Pattie, Alison, Petersmann, Astrid, Qi, Qibin, Ribel-Madsen, Rasmus, Rohde, Rebecca, Sandow, Kevin, Schnurr, Theresia M., Sofer, Tamar, Starr, John M., Taylor, Adele M., Teumer, Alexander, Timpson, Nicholas J., de Haan, Hugoline G., Wang, Yujie, Weeke, Peter E., Williams, Christine, Wu, Hongsheng, Yang, Wei, Zeng, Donglin, Witte, Daniel R., Weir, Bruce S., Wareham, Nicholas J., Vestergaard, Henrik, Turner, Stephen T., Torp-Pedersen, Christian, Stergiakouli, Evie, Sheu, Wayne Huey-Herng, Rosendaal, Frits R., Ikram, M. Arfan, Franco, Oscar H., Ridker, Paul M., Perls, Thomas T., Pedersen, Oluf, Nohr, Ellen A., Newman, Anne B., Linneberg, Allan, Langenberg, Claudia, Kilpeläinen, Tuomas O., Kardia, Sharon L.R., Jørgensen, Marit E., Jørgensen, Torben, Sørensen, Thorkild I.A., Homuth, Georg, Hansen, Torben, Goodarzi, Mark O., Deary, Ian J., Christensen, Cramer, Chen, Yii-Der Ida, Chakravarti, Aravinda, Brandslund, Ivan, Bonnelykke, Klaus, Taylor, Kent D., Wilson, James G., Rodriguez, Santiago, Davies, Gail, Horta, Bernardo L., Thyagarajan, Bharat, Rao, D.C., Grarup, Niels, Davila-Roman, Victor G., Hudson, Gavin, Guo, Xiuqing, Arnett, Donna K., Hayward, Caroline, Vaidya, Dhananjay, Mook-Kanamori, Dennis O., Tiwari, Hemant K., Levy, Daniel, Loos, Ruth J.F., Dehghan, Abbas, Elliott, Paul, Malik, Afshan N., Scott, Robert A., Becker, Diane M., de Andrade, Mariza, Province, Michael A., Meigs, James B., Rotter, Jerome I., and North, Kari E.

Published
2019
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20. Genetic Signatures of Exceptional Longevity in Humans

Author

Sebastiani, Paola, Solovieff, Nadia, DeWan, Andrew T, Walsh, Kyle M, Puca, Annibale, Hartley, Stephen W, Melista, Efthymia, Andersen, Stacy, Dworkis, Daniel A, Wilk, Jemma B, Myers, Richard H, Steinberg, Martin H, Montano, Monty, Baldwin, Clinton T, Hoh, Josephine, and Perls, Thomas T

Subjects
Clinical Research, Prevention, Human Genome, Aging, Genetics, Aged, Aged, 80 and over, Alleles, Bayes Theorem, Cohort Studies, Female, Gene Frequency, Genetic Predisposition to Disease, Genome, Human, Genotype, Humans, Longevity, Male, Models, Genetic, Models, Statistical, Polymorphism, Single Nucleotide, General Science & Technology
Abstract

Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different "genetic signatures" of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.

Published
2012

22. Examination of Genetic Risk Factors for Alzheimer’s Disease in a Cohort of Familial Longevity: the Long Life Family Study

Author

Xicota, Laura, primary, Cheng, Rong, additional, Barral, Sandra, additional, Honig, Lawrence S., additional, Schupf, Nicole, additional, Gu, Yian, additional, Cosentino, Stephanie, additional, Zmuda, Joseph M, additional, Perls, Thomas T., additional, Christensen, Kaare, additional, Province, Michael A, additional, and Lee, Joseph H., additional

Published
2023
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28. Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: The Long Life Family Study (LLFS)

Author

An, Ping, Miljkovic, Iva, Thyagarajan, Bharat, Kraja, Aldi T., Daw, E. Warwick, Pankow, James S., Selvin, Elizabeth, Kao, W.H. Linda, Maruthur, Nisa M., Nalls, Micahel A., Liu, Yongmei, Harris, Tamara B., Lee, Joseph H., Borecki, Ingrid B., Christensen, Kaare, Eckfeldt, John H., Mayeux, Richard, Perls, Thomas T., Newman, Anne B., and Province, Michael A.

Published
2014
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29. Cross-platform proteomics signatures of extreme old age

Author

Reed, Eric R., Chandler, Kevin B., Lopez, Prisma, Costello, Catherine E., Andersen, Stacy L., Perls, Thomas T., Li, Mengze, Bae, Harold, Soerensen, Mette, Monti, Stefano, and Sebastiani, Paola

Abstract

In previous work, we used a SomaLogic platform targeting approximately 5000 proteins to generate a serum protein signature of centenarians that we validated in independent studies that used the same technology. We set here to validate and possibly expand the results by profiling the serum proteome of a subset of individuals included in the original study using liquid chromatography tandem mass spectrometry (LC-MS/MS). Following pre-processing, the LC-MS/MS data provided quantification of 398 proteins, with only 266 proteins shared by both platforms. At 1% FDR statistical significance threshold, the analysis of LC-MS/MS data detected 44 proteins associated with extreme old age, including 23 of the original analysis. To identify proteins for which associations between expression and extreme-old age were conserved across platforms, we performed inter-study conservation testing of the 266 proteins quantified by both platforms using a method that accounts for the correlation between the results. From these tests, a total of 80 proteins reached 5% FDR statistical significance, and 26 of these proteins had concordant pattern of gene expression in whole blood generated in an independent set. This signature of 80 proteins points to blood coagulation, IGF signaling, extracellular matrix (ECM) organization, and complement cascade as important pathways whose protein level changes provide evidence for age-related adjustments that distinguish centenarians from younger individuals. The comparison with blood transcriptomics also highlights a possible role for neutrophil degranulation in aging.

Published
2024
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30. A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants

Author

Bae, Harold, primary, Gurinovich, Anastasia, additional, Karagiannis, Tanya T., additional, Song, Zeyuan, additional, Leshchyk, Anastasia, additional, Li, Mengze, additional, Andersen, Stacy L., additional, Arbeev, Konstantin, additional, Yashin, Anatoliy, additional, Zmuda, Joseph, additional, An, Ping, additional, Feitosa, Mary, additional, Giuliani, Cristina, additional, Franceschi, Claudio, additional, Garagnani, Paolo, additional, Mengel-From, Jonas, additional, Atzmon, Gil, additional, Barzilai, Nir, additional, Puca, Annibale, additional, Schork, Nicholas J., additional, Perls, Thomas T., additional, and Sebastiani, Paola, additional

Published
2022
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32. Evaluation of GENESIS, SAIGE, REGENIE and fastGWA-GLMM for genome-wide association studies of binary traits in correlated data

Author

Gurinovich, Anastasia, Li, Mengze, Leshchyk, Anastasia, Bae, Harold, Song, Zeyuan, Arbeev, Konstantin G., Nygaard, Marianne, Feitosa, Mary F, Perls, Thomas T, and Sebastiani, Paola

Subjects
Genetics, Molecular Medicine, Genetics (clinical)
Abstract

Performing a genome-wide association study (GWAS) with a binary phenotype using family data is a challenging task. Using linear mixed effects models is typically unsuitable for binary traits, and numerical approximations of the likelihood function may not work well with rare genetic variants with small counts. Additionally, imbalance in the case-control ratios poses challenges as traditional statistical methods such as the Score test or Wald test perform poorly in this setting. In the last couple of years, several methods have been proposed to better approximate the likelihood function of a mixed effects logistic regression model that uses Saddle Point Approximation (SPA). SPA adjustment has recently been implemented in multiple software, including GENESIS, SAIGE, REGENIE and fastGWA-GLMM: four increasingly popular tools to perform GWAS of binary traits. We compare Score and SPA tests using real family data to evaluate computational efficiency and the agreement of the results. Additionally, we compare various ways to adjust for family relatedness, such as sparse and full genetic relationship matrices (GRM) and polygenic effect estimates. We use the New England Centenarian Study imputed genotype data and the Long Life Family Study whole-genome sequencing data and the binary phenotype of human extreme longevity to compare the agreement of the results and tools’ computational performance. The evaluation suggests that REGENIE might not be a good choice when analyzing correlated data of a small size. fastGWA-GLMM is the most computationally efficient compared to the other three tools, but it appears to be overly conservative when applied to family-based data. GENESIS, SAIGE and fastGWA-GLMM produced similar, although not identical, results, with SPA adjustment performing better than Score tests. Our evaluation also demonstrates the importance of adjusting by full GRM in highly correlated datasets when using GENESIS or SAIGE.

Published
2022
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35. Mosaic Chromosomal Alterations and Human Longevity.

Author

Leshchyk, Anastasia, Xiang, Qingyan, Andersen, Stacy L, Gurinovich, Anastasia, Song, Zeyuan, Lee, Joseph H, Christensen, Kaare, Yashin, Anatoliy, Wojczynski, Mary, Schwander, Karen, Perls, Thomas T, Monti, Stefano, and Sebastiani, Paola

Subjects
LONGEVITY, FALSE discovery rate, CENTENARIANS
Abstract

Mosaic chromosomal alterations (mCAs) are structural alterations associated with aging, cancer, cardiovascular disease, infectious diseases, and mortality. The distribution of mCAs in centenarians and individuals with familial longevity is poorly understood. We used MOsaic CHromosomal Alteration (MoChA) to discover mCAs in 2050 centenarians, offspring, and 248 controls from the New England Centenarian Study (NECS) and in 3 642 subjects with familial longevity and 920 spousal controls from the Long-Life Family Study (LLFS). We analyzed study-specific associations of somatic mCAs with age, familial longevity, the incidence of age-related diseases, and mortality and aggregated the results by meta-analysis. We show that the accumulation of mCAs > 100 KB increased to 102 years and plateaued at older ages. Centenarians and offspring accumulated fewer autosomal mCAs compared with controls (relative risk 0.637, p =.0147). Subjects with the APOE E4 allele had a 35.3% higher risk of accumulating autosomal mCAs (p =.002). Males were at higher risk for mCAs compared to females (male relative risk 1.36, p = 5.15e−05). mCAs were associated with increased hazard for cancer (hazard ratio 1.2) and dementia (hazard ratio 1.259) at a 10% false discovery rate. We observed a borderline significant association between mCAs and risk for mortality (hazard ratio 1.07, p =.0605). Our results show that the prevalence of individuals with mCAs does not continue to increase at ages >102 years and factors promoting familial longevity appear to confer protections from mCAs. These results suggest that limited mCA accumulation could be an important mechanism for extreme human longevity that needs to be investigated. [ABSTRACT FROM AUTHOR]

Published
2023
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36. A metabolomic signature of the APOE2 allele

Author

Sebastiani, Paola, primary, Song, Zeyuan, additional, Ellis, Dylan, additional, Tian, Qu, additional, Schwaiger-Haber, Michaela, additional, Stancliffe, Ethan, additional, Lustgarten, Michael S., additional, Funk, Cory C., additional, Baloni, Priyanka, additional, Yao, Cong-Hui, additional, Joshi, Shakchhi, additional, Marron, Megan M., additional, Gurinovich, Anastasia, additional, Li, Mengze, additional, Leshchyk, Anastasia, additional, Xiang, Qingyan, additional, Andersen, Stacy L., additional, Feitosa, Mary F., additional, Ukraintseva, Svetlana, additional, Soerensen, Mette, additional, Fiehn, Oliver, additional, Ordovas, Jose M., additional, Haigis, Marcia, additional, Monti, Stefano, additional, Barzilai, Nir, additional, Milman, Sofiya, additional, Ferrucci, Luigi, additional, Rappaport, Noa, additional, Patti, Gary J., additional, and Perls, Thomas T., additional

Published
2022
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49. Association of longer telomeres with better health in centenarians

Author

Terry, Dellara F., Nolan, Vikki G., Andersen, Stacy L., Perls, Thomas T., and Cawthon, Richard

Subjects
Centenarians -- Physiological aspects, Telomeres -- Properties, Longevity -- Research, Health, Seniors
Abstract

Prior animal model studies have demonstrated an association between telomere length and longevity. Our study examines telomere length in centenarians in good health versus poor health. Using DNA from blood lymphocytes, telomere length was measured by quantitative polymerase chain reaction in 38 sex- and age-matched centenarians (ages 97-108). 'Healthy' centenarians (n = 19) with physical function in the independent range and the absence of hypertension, congestive heart failure, myocardial infarction, peripheral vascular disease, dementia, cancer, stroke, chronic obstructive pulmonary disease, and diabetes were compared to centenarians with physical function limitations and [greater than or equal to] 2 of the above conditions (n = 19). Healthy centenarians had significantly longer telomeres than did unhealthy centenarians (p = .0475). Our study demonstrated that investigations of the association between telomere length and exceptional longevity must take into account the health status of the individuals. This raises the possibility that perhaps it is not exceptional longevity but one's function and health that may be associated with telomere length. Key Words: Telomere length--Centenarian--Longevity--Morbidity.

Published
2008

50. Sex differences in genetic associations with longevity in Han Chinese: sex-stratified genome-wide association study and polygenic risk score analysis

Author

Zeng, Yi, primary, Chen, Huashuai, additional, Liu, Xiaomin, additional, Ye, Rui, additional, Xie, Enjun, additional, Chen, Zhihua, additional, Lu, Jiehua, additional, Li, Jianxin, additional, Tian, Yaohua, additional, Ni, Ting, additional, Bolund, Lars, additional, Land, Kenneth C., additional, Yashin, Anatoliy, additional, O'Rand, Angela M., additional, Sun, Liang, additional, Yang, Ze, additional, Tao, Wei, additional, Gurinovic, Anastasia, additional, Franceschi, Claudio, additional, Xie, Jichun, additional, Gu, Jun, additional, Hou, Yong, additional, Liu, Xiao, additional, Xu, Xun, additional, Robine, Jean-Marie, additional, Deelen, Joris, additional, Sebastiani, Paola, additional, Slagboom, P. Eline, additional, Perls, Thomas T., additional, Hauser, Elizabeth R., additional, Gottschalk, William, additional, Tan, Qihua, additional, Christensen, Kaare, additional, Lutz, Mike, additional, Tian, Xiao-Li, additional, Yang, Huanming, additional, Min, Junxia, additional, Nie, Chao, additional, and Vaupel, James W., additional

Published
2017
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