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Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData mining

Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD.
PMID: 28770004
BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017.

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol...

Cite
Holzinger ER, Verma SS, Moore CB, et al. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017;10:25doi: 10.1186/s13040-017-0145-5.
Holzinger, E. R., Verma, S. S., Moore, C. B., Hall, M., De, R., Gilbert-Diamond, D., Lanktree, M. B., Pankratz, N., Amuzu, A., Burt, A., Dale, C., Dudek, S., Furlong, C. E., Gaunt, T. R., Kim, D. S., Riess, H., Sivapalaratnam, S., Tragante, V., van Iperen, E. P. A., Brautbar, A., Carrell, D. S., Crosslin, D. R., Jarvik, G. P., Kuivaniemi, H., Kullo, I. J., Larson, E. B., Rasmussen-Torvik, L. J., Tromp, G., Baumert, J., Cruickshanks, K. J., Farrall, M., Hingorani, A. D., Hovingh, G. K., Kleber, M. E., Klein, B. E., Klein, R., Koenig, W., Lange, L. A., Mӓrz, W., North, K. E., Charlotte Onland-Moret, N., Reiner, A. P., Talmud, P. J., van der Schouw, Y. T., Wilson, J. G., Kivimaki, M., Kumari, M., Moore, J. H., Drenos, F., Asselbergs, F. W., Keating, B. J., & Ritchie, M. D. (2017). Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData mining, 1025. https://doi.org/10.1186/s13040-017-0145-5
Holzinger, Emily R, et al. "Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals." BioData mining vol. 10 (2017): 25. doi: https://doi.org/10.1186/s13040-017-0145-5
Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017. PMID: 28770004; PMCID: PMC5525436.
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Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease.

Annals of clinical and translational neurology

Raghavan NS, Brickman AM, Andrews H, Manly JJ, Schupf N, Lantigua R, Wolock CJ, Kamalakaran S, Petrovski S, Tosto G, Vardarajan BN, Goldstein DB, Mayeux R.
PMID: 30009200
Ann Clin Transl Neurol. 2018 May 24;5(7):832-842. doi: 10.1002/acn3.582. eCollection 2018 Jul.

OBJECTIVE: The genetic bases of Alzheimer's disease remain uncertain. An international effort to fully articulate genetic risks and protective factors is underway with the hope of identifying potential therapeutic targets and preventive strategies. The goal here was to identify...

Cite
Raghavan NS, Brickman AM, Andrews H, et al. Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease. Ann Clin Transl Neurol. 2018;5(7):832-842doi: 10.1002/acn3.582.
Raghavan, N. S., Brickman, A. M., Andrews, H., Manly, J. J., Schupf, N., Lantigua, R., Wolock, C. J., Kamalakaran, S., Petrovski, S., Tosto, G., Vardarajan, B. N., Goldstein, D. B., Mayeux, R. (2018). Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease. Annals of clinical and translational neurology, 5(7), 832-842. https://doi.org/10.1002/acn3.582
Raghavan, Neha S, et al. "Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease." Annals of clinical and translational neurology vol. 5,7 (2018): 832-842. doi: https://doi.org/10.1002/acn3.582
Raghavan NS, Brickman AM, Andrews H, Manly JJ, Schupf N, Lantigua R, Wolock CJ, Kamalakaran S, Petrovski S, Tosto G, Vardarajan BN, Goldstein DB, Mayeux R. Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease. Ann Clin Transl Neurol. 2018 May 24;5(7):832-842. doi: 10.1002/acn3.582. eCollection 2018 Jul. PMID: 30009200; PMCID: PMC6043775.
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Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS.

Journal of Alzheimer's disease : JAD

Briceño EM, Gross AL, Giordani BJ, Manly JJ, Gottesman RF, Elkind MSV, Sidney S, Hingtgen S, Sacco RL, Wright CB, Fitzpatrick A, Fohner AE, Mosley TH, Yaffe K, Levine DA.
PMID: 34459397
J Alzheimers Dis. 2021;83(4):1803-1813. doi: 10.3233/JAD-210459.

BACKGROUND: Meta-analyses of individuals' cognitive data are increasing to investigate the biomedical, lifestyle, and sociocultural factors that influence cognitive decline and dementia risk. Pre-statistical harmonization of cognitive instruments is a critical methodological step for accurate cognitive data harmonization, yet...

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Briceño EM, Gross AL, Giordani BJ, et al. Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS. J Alzheimers Dis. 2021;83(4):1803-1813doi: 10.3233/JAD-210459.
Briceño, E. M., Gross, A. L., Giordani, B. J., Manly, J. J., Gottesman, R. F., Elkind, M. S. V., Sidney, S., Hingtgen, S., Sacco, R. L., Wright, C. B., Fitzpatrick, A., Fohner, A. E., Mosley, T. H., Yaffe, K., & Levine, D. A. (2021). Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS. Journal of Alzheimer's disease : JAD, 83(4), 1803-1813. https://doi.org/10.3233/JAD-210459
Briceño, Emily M, et al. "Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS." Journal of Alzheimer's disease : JAD vol. 83,4 (2021): 1803-1813. doi: https://doi.org/10.3233/JAD-210459
Briceño EM, Gross AL, Giordani BJ, Manly JJ, Gottesman RF, Elkind MSV, Sidney S, Hingtgen S, Sacco RL, Wright CB, Fitzpatrick A, Fohner AE, Mosley TH, Yaffe K, Levine DA. Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS. J Alzheimers Dis. 2021;83(4):1803-1813. doi: 10.3233/JAD-210459. PMID: 34459397.
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Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData mining

Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD.
PMID: 28770004
BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017.

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol...

Cite
Holzinger ER, Verma SS, Moore CB, et al. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017;10:25doi: 10.1186/s13040-017-0145-5.
Holzinger, E. R., Verma, S. S., Moore, C. B., Hall, M., De, R., Gilbert-Diamond, D., Lanktree, M. B., Pankratz, N., Amuzu, A., Burt, A., Dale, C., Dudek, S., Furlong, C. E., Gaunt, T. R., Kim, D. S., Riess, H., Sivapalaratnam, S., Tragante, V., van Iperen, E. P. A., Brautbar, A., Carrell, D. S., Crosslin, D. R., Jarvik, G. P., Kuivaniemi, H., Kullo, I. J., Larson, E. B., Rasmussen-Torvik, L. J., Tromp, G., Baumert, J., Cruickshanks, K. J., Farrall, M., Hingorani, A. D., Hovingh, G. K., Kleber, M. E., Klein, B. E., Klein, R., Koenig, W., Lange, L. A., Mӓrz, W., North, K. E., Charlotte Onland-Moret, N., Reiner, A. P., Talmud, P. J., van der Schouw, Y. T., Wilson, J. G., Kivimaki, M., Kumari, M., Moore, J. H., Drenos, F., Asselbergs, F. W., Keating, B. J., & Ritchie, M. D. (2017). Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData mining, 1025. https://doi.org/10.1186/s13040-017-0145-5
Holzinger, Emily R, et al. "Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals." BioData mining vol. 10 (2017): 25. doi: https://doi.org/10.1186/s13040-017-0145-5
Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017. PMID: 28770004; PMCID: PMC5525436.
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Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData mining

Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD.
PMID: 28770004
BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017.

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol...

Cite
Holzinger ER, Verma SS, Moore CB, et al. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017;10:25doi: 10.1186/s13040-017-0145-5.
Holzinger, E. R., Verma, S. S., Moore, C. B., Hall, M., De, R., Gilbert-Diamond, D., Lanktree, M. B., Pankratz, N., Amuzu, A., Burt, A., Dale, C., Dudek, S., Furlong, C. E., Gaunt, T. R., Kim, D. S., Riess, H., Sivapalaratnam, S., Tragante, V., van Iperen, E. P. A., Brautbar, A., Carrell, D. S., Crosslin, D. R., Jarvik, G. P., Kuivaniemi, H., Kullo, I. J., Larson, E. B., Rasmussen-Torvik, L. J., Tromp, G., Baumert, J., Cruickshanks, K. J., Farrall, M., Hingorani, A. D., Hovingh, G. K., Kleber, M. E., Klein, B. E., Klein, R., Koenig, W., Lange, L. A., Mӓrz, W., North, K. E., Charlotte Onland-Moret, N., Reiner, A. P., Talmud, P. J., van der Schouw, Y. T., Wilson, J. G., Kivimaki, M., Kumari, M., Moore, J. H., Drenos, F., Asselbergs, F. W., Keating, B. J., & Ritchie, M. D. (2017). Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData mining, 1025. https://doi.org/10.1186/s13040-017-0145-5
Holzinger, Emily R, et al. "Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals." BioData mining vol. 10 (2017): 25. doi: https://doi.org/10.1186/s13040-017-0145-5
Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017. PMID: 28770004; PMCID: PMC5525436.
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Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets.

Alzheimer's & dementia (New York, N. Y.)

Evans S, McRae-McKee K, Hadjichrysanthou C, Wong MM, Ames D, Lopez O, de Wolf F, Anderson RM.
PMID: 31650008
Alzheimers Dement (N Y). 2019 Oct 03;5:515-523. doi: 10.1016/j.trci.2019.04.005. eCollection 2019.

There exist a large number of cohort studies that have been used to identify genetic and biological risk factors for developing Alzheimer's disease (AD). However, there is a disagreement between studies as to how strongly these risk factors affect...

Cite
Evans S, McRae-McKee K, Hadjichrysanthou C, et al. Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets. Alzheimers Dement (N Y). 2019;5:515-523doi: 10.1016/j.trci.2019.04.005.
Evans, S., McRae-McKee, K., Hadjichrysanthou, C., Wong, M. M., Ames, D., Lopez, O., de Wolf, F., Anderson, R. M. (2019). Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets. Alzheimer's & dementia (New York, N. Y.), 5515-523. https://doi.org/10.1016/j.trci.2019.04.005
Evans, Stephanie, et al. "Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets." Alzheimer's & dementia (New York, N. Y.) vol. 5 (2019): 515-523. doi: https://doi.org/10.1016/j.trci.2019.04.005
Evans S, McRae-McKee K, Hadjichrysanthou C, Wong MM, Ames D, Lopez O, de Wolf F, Anderson RM. Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets. Alzheimers Dement (N Y). 2019 Oct 03;5:515-523. doi: 10.1016/j.trci.2019.04.005. eCollection 2019. PMID: 31650008; PMCID: PMC6804515.
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Biomarkers in Alzheimer's disease.

Frontiers in neurology

Riverol M, López OL.
PMID: 21808632
Front Neurol. 2011 Jul 14;2:46. doi: 10.3389/fneur.2011.00046. eCollection 2011.

Alzheimer's disease (AD) is the most common form of dementia in the elderly, and it is characterized by progressive impairment in multiple cognitive domains of sufficient severity to interfere with individuals' daily living activities. Historically, the diagnosis of AD...

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Riverol M, López OL. Biomarkers in Alzheimer's disease. Front Neurol. 2011;2:46doi: 10.3389/fneur.2011.00046.
Riverol, M., & López, O. L. (2011). Biomarkers in Alzheimer's disease. Frontiers in neurology, 246. https://doi.org/10.3389/fneur.2011.00046
Riverol, Mario, and López, Oscar L. "Biomarkers in Alzheimer's disease." Frontiers in neurology vol. 2 (2011): 46. doi: https://doi.org/10.3389/fneur.2011.00046
Riverol M, López OL. Biomarkers in Alzheimer's disease. Front Neurol. 2011 Jul 14;2:46. doi: 10.3389/fneur.2011.00046. eCollection 2011. PMID: 21808632; PMCID: PMC3139171.
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Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment.

NeuroImage. Clinical

Rajagopalan P, Jahanshad N, Stein JL, Hua X, Madsen SK, Kohannim O, Hibar DP, Toga AW, Jack CR, Saykin AJ, Green RC, Weiner MW, Bis JC, Kuller LH, Riverol M, Becker JT, Lopez OL, Thompson PM.
PMID: 24179750
Neuroimage Clin. 2012 Oct 04;1(1):179-87. doi: 10.1016/j.nicl.2012.09.012. eCollection 2012.

A commonly carried C677T polymorphism in a folate-related gene, MTHFR, is associated with higher plasma homocysteine, a well-known mediator of neuronal damage and brain atrophy. As homocysteine promotes brain atrophy, we set out to discover whether people carrying the...

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Rajagopalan P, Jahanshad N, Stein JL, et al. Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment. Neuroimage Clin. 2012;1(1):179-87doi: 10.1016/j.nicl.2012.09.012.
Rajagopalan, P., Jahanshad, N., Stein, J. L., Hua, X., Madsen, S. K., Kohannim, O., Hibar, D. P., Toga, A. W., Jack, C. R., Saykin, A. J., Green, R. C., Weiner, M. W., Bis, J. C., Kuller, L. H., Riverol, M., Becker, J. T., Lopez, O. L., Thompson, P. M. (2012). Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment. NeuroImage. Clinical, 1(1), 179-87. https://doi.org/10.1016/j.nicl.2012.09.012
Rajagopalan, Priya, et al. "Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment." NeuroImage. Clinical vol. 1,1 (2012): 179-87. doi: https://doi.org/10.1016/j.nicl.2012.09.012
Rajagopalan P, Jahanshad N, Stein JL, Hua X, Madsen SK, Kohannim O, Hibar DP, Toga AW, Jack CR, Saykin AJ, Green RC, Weiner MW, Bis JC, Kuller LH, Riverol M, Becker JT, Lopez OL, Thompson PM. Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment. Neuroimage Clin. 2012 Oct 04;1(1):179-87. doi: 10.1016/j.nicl.2012.09.012. eCollection 2012. PMID: 24179750; PMCID: PMC3757723.
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Multilocus genetic profiling to empower drug trials and predict brain atrophy.

NeuroImage. Clinical

Kohannim O, Hua X, Rajagopalan P, Hibar DP, Jahanshad N, Grill JD, Apostolova LG, Toga AW, Jack CR, Weiner MW, Thompson PM.
PMID: 24179834
Neuroimage Clin. 2013 Jun 13;2:827-35. doi: 10.1016/j.nicl.2013.05.007. eCollection 2013.

Designers of clinical trials for Alzheimer's disease (AD) and mild cognitive impairment (MCI) are actively considering structural and functional neuroimaging, cerebrospinal fluid and genetic biomarkers to reduce the sample sizes needed to detect therapeutic effects. Genetic pre-selection, however, has...

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Kohannim O, Hua X, Rajagopalan P, et al. Multilocus genetic profiling to empower drug trials and predict brain atrophy. Neuroimage Clin. 2013;2:827-35doi: 10.1016/j.nicl.2013.05.007.
Kohannim, O., Hua, X., Rajagopalan, P., Hibar, D. P., Jahanshad, N., Grill, J. D., Apostolova, L. G., Toga, A. W., Jack, C. R., Weiner, M. W., Thompson, P. M. (2013). Multilocus genetic profiling to empower drug trials and predict brain atrophy. NeuroImage. Clinical, 2827-35. https://doi.org/10.1016/j.nicl.2013.05.007
Kohannim, Omid, et al. "Multilocus genetic profiling to empower drug trials and predict brain atrophy." NeuroImage. Clinical vol. 2 (2013): 827-35. doi: https://doi.org/10.1016/j.nicl.2013.05.007
Kohannim O, Hua X, Rajagopalan P, Hibar DP, Jahanshad N, Grill JD, Apostolova LG, Toga AW, Jack CR, Weiner MW, Thompson PM. Multilocus genetic profiling to empower drug trials and predict brain atrophy. Neuroimage Clin. 2013 Jun 13;2:827-35. doi: 10.1016/j.nicl.2013.05.007. eCollection 2013. PMID: 24179834; PMCID: PMC3777716.
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Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences.

PLoS genetics

Zhan L, Li J, Jew B, Sul JH.
PMID: 34516545
PLoS Genet. 2021 Sep 13;17(9):e1009772. doi: 10.1371/journal.pgen.1009772. eCollection 2021 Sep.

Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic...

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Zhan L, Li J, Jew B, et al. Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences. PLoS Genet. 2021;17(9):e1009772doi: 10.1371/journal.pgen.1009772.
Zhan, L., Li, J., Jew, B., & Sul, J. H. (2021). Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences. PLoS genetics, 17(9), e1009772. https://doi.org/10.1371/journal.pgen.1009772
Zhan, Lingyu, et al. "Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences." PLoS genetics vol. 17,9 (2021): e1009772. doi: https://doi.org/10.1371/journal.pgen.1009772
Zhan L, Li J, Jew B, Sul JH. Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences. PLoS Genet. 2021 Sep 13;17(9):e1009772. doi: 10.1371/journal.pgen.1009772. eCollection 2021 Sep. PMID: 34516545; PMCID: PMC8460036.
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Multilocus genetic analysis of brain images.

Frontiers in genetics

Hibar DP, Kohannim O, Stein JL, Chiang MC, Thompson PM.
PMID: 22303368
Front Genet. 2011 Oct 21;2:73. doi: 10.3389/fgene.2011.00073. eCollection 2011.

The quest to identify genes that influence disease is now being extended to find genes that affect biological markers of disease, or endophenotypes. Brain images, in particular, provide exquisitely detailed measures of anatomy, function, and connectivity in the living...

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Hibar DP, Kohannim O, Stein JL, et al. Multilocus genetic analysis of brain images. Front Genet. 2011;2:73doi: 10.3389/fgene.2011.00073.
Hibar, D. P., Kohannim, O., Stein, J. L., Chiang, M. C., & Thompson, P. M. (2011). Multilocus genetic analysis of brain images. Frontiers in genetics, 273. https://doi.org/10.3389/fgene.2011.00073
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Comparing years of healthy life, measured in 16 ways, for normal weight and overweight older adults.

Journal of obesity

Diehr P, Thielke S, O'Meara E, Fitzpatrick AL, Newman A.
PMID: 22778920
J Obes. 2012;2012:894894. doi: 10.1155/2012/894894. Epub 2012 Jun 20.

Introduction. The traditional definitions of overweight and obesity are not age specific, even though the relationship of weight to mortality is different for older adults. Effects of adiposity on aspects of health beside mortality have not been well investigated....

Cite
Diehr P, Thielke S, O'Meara E, et al. Comparing years of healthy life, measured in 16 ways, for normal weight and overweight older adults. J Obes. 2012;2012:894894doi: 10.1155/2012/894894.
Diehr, P., Thielke, S., O'Meara, E., Fitzpatrick, A. L., & Newman, A. (2012). Comparing years of healthy life, measured in 16 ways, for normal weight and overweight older adults. Journal of obesity, 2012894894. https://doi.org/10.1155/2012/894894
Diehr, Paula, et al. "Comparing years of healthy life, measured in 16 ways, for normal weight and overweight older adults." Journal of obesity vol. 2012 (2012): 894894. doi: https://doi.org/10.1155/2012/894894
Diehr P, Thielke S, O'Meara E, Fitzpatrick AL, Newman A. Comparing years of healthy life, measured in 16 ways, for normal weight and overweight older adults. J Obes. 2012;2012:894894. doi: 10.1155/2012/894894. Epub 2012 Jun 20. PMID: 22778920; PMCID: PMC3388309.
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